Datasets:

TomTBT

/

pmc_open_access_section

like 1

PMC10788335

38221532

Introduction Degenerative lumbar spine disease (DLSD) is one of the most common musculoskeletal conditions that affect the lower back and is characterized by the progressive deterioration of intervertebral discs, facet joints, and other structures in the lumbar region 1 , 2 . This degenerative process can cause a variety of symptoms, including back pain, leg pain, tingling, and weakness, which can significantly impact an individual's quality of life 3 , 4 . While various treatment options exist for DLSD, including conservative management such as physical therapy and medication, some patients may require surgical intervention to alleviate their symptoms and improve their quality of life 5 , 6 . Surgical procedures such as lumbar fusion or discectomy are often effective in providing relief, restoring spinal stability, and improving functional outcomes 7 – 10 . However, despite the success of initial surgical interventions, a subset of patients may experience recurrent symptoms or the progression of their condition over time. This may necessitate a second surgical procedure, commonly referred to as secondary surgery 11 – 13 . The need for secondary surgery in DLSD can arise due to various reasons, including adjacent segment disease (ASD), implant failure, persistent or recurrent symptoms, or disease progression 14 – 17 . Secondary surgeries often require more complex surgical techniques compared to the initial surgery, which can contribute to an increase in healthcare costs including surgical fees, hospitalization costs, and post-operative care 18 – 21 . The increasing incidence of secondary surgery has raised concerns regarding its impact on healthcare costs 22 . Therefore, screening secondary surgery for DLSD is essential not only for the efficient allocation of healthcare resources and rational medical expenditure but also for formulating appropriate policies regarding the medical costs associated with DLSD. Factors associated with secondary surgery are complex, but there has been no indicator showing the possibility of secondary surgery from the perspective of health insurance. The objective of this study is to propose indicators for screening patients requiring secondary surgery for DLSD, focusing on the aspect of increased healthcare costs, using data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC) of the Republic of Korea (ROK).

Methods Data source The data for this study were derived from the National Health Insurance Database (NHID), which records personal information, demographics, and medical treatment data for all Korean citizens. In the ROK, all citizens have been beneficiaries of the NHIS for more than 20 years, and the NHIS covers both Western and Oriental medicine 23 – 25 . Because the NHIS follows a fee-for-service payment system, all nationwide inpatient and outpatient data on diseases and services (i.e., procedures and surgeries) are coded and registered in the National Health Insurance Corporation (NHIC) database and the Health Insurance Review & Assessment Service (HIRA) database 23 – 28 . The disease codes in the database adhere to the 10th version of the International Classification of Diseases (ICD-10), and procedure codes are standardized for billing purposes. Nearly all hospitals providing Western medicine and clinics providing Oriental medicine must follow the guidelines to obtain reimbursement. The detailed surgical and nonsurgical management were determined by the attending physicians 23 , 25 , 29 . By using the database, the NHIS-NSC was identified in 2017 for analysis while maintaining representativeness and protecting personal information 28 . The NHIS-NSC represents a representative sample cohort, consisting of 1,000,000 individuals (approximately 2.1% of the total Korean population) randomly selected from a population of 48,438,292 in 2006 ( https://nhiss.nhis.or.kr/bd/ab/bdaba021eng.do ) 28 . Systematic stratified random sampling with proportional allocation within each stratum, including sex, age, location, and health insurance, was employed. To ensure privacy, the resident registration numbers were replaced with unique eight-digit personal IDs, enabling longitudinal follow-ups for all individuals until 2015. The cohort was updated annually during the follow-up period, and the size of the cohort was maintained. The records for each person in the NHIS-NSC can be traced back to 2002. Study population For this study, we utilized a cohort study design established in a previous study 30 . The study included patients diagnosed with lumbar disc herniation (LDH), lumbar spinal stenosis without spondylolisthesis (LSS without SPL), lumbar spinal stenosis with spondylolisthesis (LSS with SPL), and spondylolysis (SP) 30 , 31 . The disease codes for each diagnosis were as follows: (1) LDH, M51, M472; (2) LSS without SPL, M4800, M4805-8; (3) LSS with SPL, M431, M4315-9; (4) SP, M430, M4306-9. The selection of the surgical treatment cohort involved identifying patients who underwent specific surgical procedures between 2006 and 2008. The codes for each surgical procedure were as follows: (1) open discectomy, N1493; (2) laminectomy, N4199, N2499; (3) endoscopic lumbar discectomy, N1494; (4) spinal fusion, N0466, N1466, N0469, N2470, N1460, and N1469. A total of 4577 patients were selected in the surgical treatment cohort. Among them, patients with the following conditions were excluded: (1) patients with a history of spinal surgery within the past 3 years (n = 105), (2) patients who had utilized medical services with disease indicating spinal fracture, pathological fracture, spinal infection, malignancy, or inflammatory joint disease within the past 1 year (n = 207), (3) patients with concomitant rare diseases such as metabolic diseases, blood diseases, or congenital anomalies (n = 1), (4) patients admitted via the emergency room (n = 362), and (5) patients below 18 years of age (n = 21) 30 . After applying exclusion criteria, 3,881 patients remained in the surgical treatment cohort. After surgery, patients visited clinic for follow-up and may receive additional interventions, physiotherapy or medications depending on their specific needs following the surgery. All patients were followed up for at least 7 years. The patient flow diagram is presented in Fig. 1 . Secondary surgery was defined as any kind of lumbar spinal surgery at any lumbar level being performed after initial surgery. However, since the exact lumbar level was not recorded in the registry, treatment failure after initial surgery could include both the index level and the other lumbar levels 24 , 25 , 27 , 29 , 30 , 32 . This study was conducted in accordance with the Declaration of Helsinki and the Guideline for Good Clinical Practice. The study protocol was approved by the Seoul National University Hospital ethics committee/institutional review board (2010-076-1164). The Seoul National University Hospital ethics committee/institutional review board approved the exemption of informed consent due to the retrospective nature of this study. Statistics We analyzed direct medical costs for Western and Oriental medicine in two groups: those who had secondary surgery (S-group) and those who did not (NS-group). Costs only considered medical expenses and did not account for societal costs. Initial costs for surgical treatment were incurred during hospitalization for surgery. In the S-group, interim costs covered expenses between initial and secondary surgeries, including consultation fees, procedures, physiotherapy, and medications. In the NS-group, interim costs included expenses after the initial surgery. Costs related to the secondary surgery were specific to the secondary surgery purpose. We compared costs between groups using the Mann–Whitney U test. To find the optimal cutoff for interim costs predicting secondary surgery, we selected the value maximizing sensitivity and specificity based on Youden's index. Statistical analysis was done using SAS version 9.4, with significance set at P < 0.05.

Results Baseline characteristics of the cohort The characteristics of patients are described in Table 1 . The most common disease was LDH (47.85%) followed by LSS without SPL (36.12%), LSS with SPL (13.63%), and SP (2.4%). Open discectomy was the most common surgical technique in all diseases. The initial surgical methods for each diagnosis are shown in Table 2 . Fusion surgery was performed in 3.82%, 12.91%, 37.24%, and 43.01% of patients with LDH, LSS without SPL, LSS with SPL, and SP, respectively. The distribution of secondary surgery methods for each diagnosis is presented in Table 3 . Secondary surgery was performed in 14.81%, 15.62%, 11.34%, and 6.45% of patients with LDH, LSS without SPL, LSS with SPL, and SP, respectively. Open discectomy was the most common secondary surgical method, and the fusion surgery was more frequently performed than initial surgery in LDH and LSS without SPL; 9.09% (vs 3.82%) and 17.35% (vs 12.91%), respectively. Medical costs by diagnosis in each group The surgery costs and interim costs of the patients are presented in Table 4 . The initial surgery costs were $1618.40 (range, 11.31–16,803.78), while the secondary surgery costs were $1829.59 (range, 9.89–19,988.60), which were higher than the initial surgery costs (P = 0.002). In LDH, LSS without SPL, and SP, the secondary surgery costs were higher than the initial surgery costs. However, the initial surgery costs were higher than the median secondary surgery costs in LSS with SPL. Before secondary surgery, the S-group incurred higher interim costs ($30.03; 1.86% of initial surgery costs) compared to the NS-group ($16.09; 0.99% of initial surgery costs). Higher interim costs before secondary surgery were observed in LDH (1.62% vs 0.99% of initial surgery costs), LSS without SPL (2.04% vs 1.06% of initial surgery costs), and LSS with SPL (1.36% vs 0.47% of initial surgery costs) in S-group than NS-group (P < 0.0001, < 0.0001, and < 0.0001, respectively). A comparison of initial, secondary, and interim costs for each diagnosis is presented in Fig. 2 . The cutoff interim costs between S-group and NS-group The cutoff interim costs for screening secondary surgery based on the surgical methods in each diagnosis of DLSD are presented in Table 5 . For LDH, if interim costs after initial surgery were greater than $8.24 (0.63% of initial surgery costs), a secondary surgery could be predicted with sensitivity of 0.80 and specificity of 0.37. The cutoff value for predicting secondary surgery was $20.63 (1.58% of initial surgery costs; sensitivity of 1.00 and specificity of 0.51) for laminectomy as initial surgery and $16.83 (1.29% of initial surgery costs; sensitivity of 0.68 and specificity of 0.72) for endoscopic discectomy as initial surgery. The cutoff values were $25.16 (1.35% of initial surgery costs; sensitivity of 0.67 and specificity of 0.58) in LSS without SPL. For decompression as initial surgery, the cutoff value was $23.32 (1.25% of initial surgery; sensitivity of 0.71 and specificity of 0.56). The cutoff value was $28.42 (0.75% of initial surgery costs; sensitivity of 0.73 and specificity of 0.64) in LSS with SPL. The cutoff value for anterior fusion as initial surgery was $88.41 (2.34% of initial surgery costs; sensitivity of 1.00 and specificity of 0.96), and the cutoff value for posterior fusion as initial surgery was $20.50 (0.54% of initial surgery; sensitivity of 0.88 and specificity of 0.60). For decompression as initial surgery, the cutoff value was $28.69 (0.76% of initial surgery; sensitivity of 0.74 and specificity of 0.60).

Discussion Frequency and causes of secondary surgery in patients with degenerative lumbar spine disease For LDH, the secondary surgery rate is reported to be 10% at 2 years, 15% at 5 years, and 20% at 10 years 11 , 32 . The most common cause of secondary surgery is known to be the recurrence of disc protrusion 16 . Factors such as age, gender, body mass index (BMI), smoking, and diabetes are known to contribute to the secondary surgery of LDH 33 , 34 . For LSS, secondary surgery is reported to occur at a rate of 11% to 18% between 8 and 10 years 13 , 35 , 36 . The main causes of secondary surgery are known to be the recurrence of stenosis due to disease progression or technical issues during surgery, accounting for about 50% 14 , 37 . Other causes include inadequate decompression, persistent pain, and complications resulting from the initial surgery 38 – 40 . Secondary surgery rates for degenerative SPL have been reported to range from 10 to 38% in previous literature 12 , 24 , 41 . Patients may undergo secondary surgery due to various reasons following the initial surgery, including facet joint hypertrophy, persistent pain, infection, and progression of degenerative changes 15 , 41 , 42 . The main complications that require secondary surgery in degenerative SPL are ASD and same segment disease (SSD). The risk factors associated with the occurrence of ASD and SSD are age, gender, BMI, facet tropism, disc height, and spinal instability 15 , 43 . The need to predict the occurrence of secondary surgery in degenerative lumbar spine disease The prevalence of DLSD is increasing worldwide and it has placed a burden on healthcare budgets 44 , 45 . The growing burden of healthcare costs related to DLSD is a consequence of various factors, including an aging population, the increasing prevalence of the condition, the need for long-term management and treatment, advancements in medical technologies, the overall increase in use of medical resources, and increased number of secondary surgery 46 – 48 . In ROK, just like in other countries, the medical costs associated with DLSD are increasing 26 and DLSD is placing a burden on the health insurance finances 26 . In this study, patients who underwent secondary surgery were found to incur significantly higher interim costs before secondary surgery compared to patients who did not undergo secondary surgery. In addition, the medical costs associated with secondary surgery were higher than the medical costs of the initial surgery. While many factors are known to be associated with the risk of secondary surgery for DLSD, there are no financial indicators for predicting secondary surgery 33 , 38 , 41 , 49 . In this study, interim costs after initial surgery showed promise in predicting the occurrence of secondary surgery in DLSD. Specifically, the study presented the cutoff interim costs that can predict secondary surgery based on the surgical methods for each diagnosis. Therefore, by tracking the post-surgical medical costs associated with DLSD, it may be possible to predict the occurrence of secondary surgery. Therefore, although it is an indirect indicator, the surrogate (interim costs) may indicate the number of patients having the possibility of secondary surgery. Screening secondary surgery in DLSD is a crucial factor in managing healthcare insurance budgets and can provide valuable information for the development of efficient healthcare policies. Limitations Firstly, our pilot study used a sample cohort, which, while representing the national population, may not fully represent all cases of lumbar spine disease. Secondly, we hypothesized that higher medical costs could be linked to poor clinical outcomes. However, medical resource utilization varied among patients and doctors, and the study did not consider the impact of time on surgical outcomes 50 . Thirdly, the medical cost claims data lacked comprehensive clinical and imaging details. These limitations restricted our analysis of individual patient conditions, including the direct relationship between secondary and primary surgeries, and hindered our ability to fully assess patient-specific factors affecting surgical outcomes and subsequent healthcare costs. Fourthly, our analysis relied on medical cost data submitted to NHIS and did not consider factors like the patient's quality of life decline or losses due to unemployment. Additionally, non-insurance treatments were not included in the analysis.

Conclusion Among patients who underwent surgery for DLSD, those who underwent secondary surgery tend to have higher interim costs than those who did not undergo secondary surgery. Furthermore, secondary surgeries generally involve higher medical expenses than the initial surgery. Therefore, tracking the trend of medical costs increases in patients with DLSD who have undergone surgery can serve as an indicator for screening the need for secondary surgery.

This study aims to identify healthcare costs indicators predicting secondary surgery for degenerative lumbar spine disease (DLSD), which significantly impacts healthcare budgets. Analyzing data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC) database of Republic of Korea (ROK), the study included 3881 patients who had surgery for lumbar disc herniation (LDH), lumbar spinal stenosis without spondylolisthesis (LSS without SPL), lumbar spinal stenosis with spondylolisthesis (LSS with SPL), and spondylolysis (SP) from 2006 to 2008. Patients were categorized into two groups: those undergoing secondary surgery (S-group) and those not (NS-group). Surgical and interim costs were compared, with S-group having higher secondary surgery costs ($1829.59 vs $1618.40 in NS-group, P = 0.002) and higher interim costs ($30.03; 1.86% of initial surgery costs vs $16.09; 0.99% of initial surgery costs in NS-group, P < 0.0001). The same trend was observed in LDH, LSS without SPL, and LSS with SPL (P < 0.0001). Monitoring interim costs trends post-initial surgery can effectively identify patients requiring secondary surgery. Subject terms

Acknowledgements The authors appreciate the Medical Research Collaborating Center for statistical analysis and consultation. Author contributions C.H.K. contributed to the study's conception and design. Material preparation was performed by J.H.L., Y.H.C., S.B.P., and K.T.K. Data collection and analysis were performed by J.H.K., S.K., Y.R.K., C.H.L., and J.M.R. The first draft of the manuscript was written by H.G.P., and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding This study was supported by Ministry of National Defence of Republic of Korea (800-20230466) and Doosan Yonkang foundation (800-20210527). This study was also supported by grant (30-2023-0120) from the Seoul National University Hospital research fund. Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1295

oa_package/da/f3/PMC10788335.tar.gz

PMC10788336

38221536

Introduction Metabolomics enables the simultaneous study of multiple metabolic processes, including pathways, transport, and reactions. Metabolomics assays are diverse and complex in terms of their analytical conditions, but they can generate quantitative and semi-quantitative data for hundreds of endogenous metabolites 1 . Recently reported datasets can have between 1500 and 2000 named metabolites and several thousand unidentified metabolites 1 , 2 . These metabolites originate from overlapping pathways of catabolic and anabolic reactions and can also be biomarkers for metabolic processes 3 . Environmental, genetic, or biological factors can alter the regulatory, signaling, and enzyme kinetic mechanisms in one or more metabolic pathways and processes, leading to altered levels of related metabolites in cells, tissues or body fluids 4 , 5 . For example, aging reprograms carbohydrate and lipid metabolism pathways in the liver 6 , tobacco smoke exposure alters the nucleotide and reactive oxidative stress species metabolism 7 , and FADS gene polymorphisms alter the levels of circulating PUFAs 8 . We can expect to see a continuous growth in the number of named metabolites in metabolomic datasets due to new advances 9 , 10 in analytical techniques and computational methods and resources. One of the key challenges in utilizing metabolomic datasets is how to interpret these large chemical lists for mechanistic insights 11 . Pathway and network analysis can provide mechanistic insights into the biological pathways linked to the altered metabolites 12 . Interestingly, metabolomic datasets often have metabolites that are yet to be connected to a biochemical reaction and pathway 13 , 14 . To also include these poorly studied metabolites, hybrid approaches of the atomic mapping of reaction and chemical similarity network (MetaMapp) and enrichment analysis (ChemRICH) can be used 13 , 14 . Transcripts and protein lists are also often interpreted using gene ontology (GO) term enrichment analysis 15 , which covers terms that relate to pathways as well as other biological processes such as cell cycle or apoptosis, or even pathways that are not yet included in other biochemical databases. However, there is not yet a single tool developed that can perform a GO analysis for a metabolite list. We have developed a new tool named 'IDSL.GOA' (Gene Ontology Analysis by the Integrated Data Science Laboratory for Metabolomics and Exposomics) to perform GO enrichment analysis for a list of metabolites. The tool is supported by a knowledge base of genes, enzymes, and reactants (metabolites) that are directly sources from National Center for Biotechnology Information (NCBI), Expasy and GO consortium databases. We present a case study of an aging mouse metabolic atlas to highlight the metabolic processes that were suggested to be related to the aging process and were only identified by the IDSL.GOA based GO analysis method. The online tool is available at https://goa.idsl.me/ site.

Material and methods IDSL.GOA knowledgebase We assembled and integrated information from a diverse set of data sources, including genes, enzymes, compounds, gene ontology terms and the relationships among them. Table 1 provides the web addresses for the publicly available data sources and their respective locations. To focus specifically on metabolism, we restricted our gene selection to those related to GO term GO: 0,008,152 (metabolic process) and linked with the human genome. Only the downstream entities for these metabolic genes were included in the knowledgebase. Utilized identifiers for creating the knowledgebase were—NCBI Gene, NCBI Protein, NCBI Nucleotide, GO Term, Enzyme Commission Number (EC) and InChiKeys. Linkages among these entities were extracted or accessed from the resources listed in Table 1 . Over-representation statistics For the GO analysis, we employed an overrepresentation analysis (ORA) test using the hypergeometric distribution. This statistical test is a widely accepted method for determining whether a set of molecular entities (gene or proteins or metabolites) is significantly overrepresented in a particular biological pathway or process, given a background database. We also applied filters (1) overlap > = 3, (2) at least three genes in the GO process (3) The set size < 5% of total compounds (4) FDR < 0.05 and (5) the overlap should be > 5% of the total set size for a GO term. The overlap represents how many out of the input InChiKey list are found among the InChiKey identifiers linked with a GO term. Only the first 14 characters of an InChiKey, which represent the two-dimensional structure were used to find the overlap. These filters narrow down the list of GO terms to only the most relevant ones. We have used “phyper” function in R to compute the hypergeometric test. The parameter for the test were – phyper(x-1,y,a,b, lower.tail = FALSE) , where x is the overlap between the input list of InChiKey and compounds linked with a GO term, y is the count of all compounds(2D structures) linked with the GO term, a is the count of all compounds (2D structures) not linked with the GO-term (1,856-y), b is the count of the InChiKey from the input list that were found in the knowledgebase. By default, the phyper function in R calculates the probability of drawing less than or equal to x for a GO term. Use of the parameters “x-1” and “lower.tail = FALSE” returns the probability of drawing more than or equal to x for a GO term. The total number of compounds (2D structures) linked with GO terms was 1856. For example, for the Nucleoside salvage (GO:0,043,174), x was 12, y was 58, b was 73, and a was 1798 (1,856–58) for the test study’s results. The p -value of this GO term was computed as ‘ phyper(11,58,1784,73, lower.tail = FALSE)’ which returns 1.158242e-06. The IDSL.GOA tool uses the False Discovery Rate (FDR) cutoff of 0.05 to control the proportion of false positives in multiple hypothesis testing in GO analysis. We repeated this test for all metabolically relevant 2,392 GO-terms. Case study and its analysis Our test study was based on publicly available data from the Aging Mouse Brain Metabolome Atlas 1 , a comprehensive resource that provides information on the metabolites found in the different regions of brain of aging mice. Specifically, we compared the brain metabolome of the cortex region in an older female mouse against that of a young mouse. To identify the significantly different metabolites, we used the student t-test. We used InChiKey identifiers for the compounds that had a p -value of less than 0.05 in the student t-test. IDSL.GOA online tool The online tool was developed using the ReactJS JavaScript framework ( https://reactjs.org/ ), which is known for its efficient rendering of dynamic user interfaces. To facilitate data visualization, we utilized the Google Chart ( https://developers.google.com/chart ) and Cytoscape JS plugins ( https://github.com/plotly/react-cytoscapejs ), specifically designed to work with ReactJS. Cytoscape online version is a lightweight and user-friendly tool that allows users to perform basic network visualization and analysis tasks without the need to install the software locally. For small networks, the online version may be sufficient, but for larger and complex network, it is recommended to download the Cytoscape SIF (Simple Interaction Format) file and use the local version of Cytoscape software to create high resolution graphics. Instructions to use the IDSL.GOA tool are provided on the landing page.

Results Creating the IDSL.GOA metabolic knowledgebase: To perform IDSL.GOA over-representation analysis, we first needed to create a database of relationships among metabolic entities. This database was designed to capture the heterogenous relationships among genes, enzymes, compounds, and gene ontology terms. The source data for these relationships were obtained from various publicly available key databases, including the NCBI, Expasy – SIB Swiss Institute of Bioinformatics, and the Gene Ontology Consortium (Table 1 ). We restricted the knowledgebase to only human genes and their products in the first version of the KB. The resulting version 1 of the IDSL.GOA database contained a total of 3,144 genes, 1,492 enzyme commission numbers, 2,621 compounds, 1,856 2D chemical structures and 2,393 gene ontology terms for metabolic processes (Fig. 1 ). Overall, the IDSL.GOA database provided a comprehensive resource for performing GO over-representation analysis for metabolite lists. Aging mouse brain metabolomics- a case study In this study, we aimed to investigate the changes in metabolite levels in the brain cortex of old and young mice using a metabolomic atlas that contained close to 1,547 identified compounds. We identified 557 metabolites that were significantly different between the old (59 weeks) and young (3 weeks) female mouse brain cortex (Table S1 ). InChiKeys for these significant metabolites were used as input for IDSL.GOA analysis. The GO analysis results suggested a total of 82 GO processes that were over-represented in the input list at an FDR cutoff of 0.05 (Table S2 ). The GO network and the impact plot visualization suggested that processes in nucleotide and amino acid metabolism (GO:0,043,174, GO:0,046,415 and GO:0,006,166) were significantly affected during the aging process (Figs. 2 and 3 , Table S2 ). IDSL.GOA online tool The IDSL.GOA online tool is a user-friendly resource for identifying overrepresented metabolic processes in a list of metabolites. The online interface offers features including analysis, query, explore, statistic and download options. The ‘Run Go Analysis’ option on the landing page allows users to input a list of InChiKeys and obtain results in various formats, including Cytoscape SIF, Microsoft Excel, and CSV. The InChiKeys for only the significant compounds ( p < 0.05) in a statistical test should be used as input. The Cytoscape SIF and node attribute files are useful for creating high-resolution figures in the Cytoscape desktop software 16 . The primary analysis results are visualized in a ‘GO Ontology network’ graph using Cytoscape JS library, which provides an intuitive and interactive way to explore the data. This view is analogous to the pathway ontology visualization in the Reactome database 17 . The size of the node in the graph reflects the significance of the term, with larger nodes indicating more significant terms in the hypergeometric test. Additionally, an impact plot shows how specific the GO terms are for the input list, by plotting the set size versus -log( p -value). The explore option allows users to navigate the GO ontology tree. Clicking on a GO term in the main analysis, query or explore options provide the GO-term specific InChikeys that overlap with the input list. The query option allows users to query a single compound, reaction, gene, protein and transcript to retrieve the associated metabolic GO terms. All GO network visualization has a basic set of layouts (views) implemented which can be explored by a user to find the most readable and helpful views for a GO ontology network that can aid in the biological interpretation of metabolite lists. Finally, the statistics and download tabs provide updates on the database version and download links, and the landing page offers Instructions for using the database.

Discussion IDSL.GOA is the first bioinformatics tool that used GO terms for over-representation analysis of metabolomic datasets. By mapping the metabolites to their associated GO terms, IDSL.GOA can improve the mechanistic interpretation of metabolomics data by providing a functional annotation of the metabolites based on their associated metabolic processes and pathways in the Gene Ontology database. It is a more sensitive and accurate tool for data with larger lists (> 1000 named metabolites) 1 , 2 . This can lead to the identification of key regulatory pathways and molecular mechanisms that are involved in the observed changes and can guide further experimentation and hypothesis testing. By leveraging the new IDSL.GOA knowledgebase, we were able to identify the overrepresented metabolic pathways and processes in our case study dataset and gain new insights into the underlying mechanisms that govern metabolic activity in aging brain tissue. Advantages of using GO terms for metabolomics data interpretation There are several advantages of GO analysis over traditional pathway analysis. GO analysis provides a more comprehensive annotation system for genes and their products than pathway analysis, allowing for a broader range of metabolic processes and pathways to be analyzed 18 . Unlike pathway analysis, GO analysis is not limited to hand-drawn pathway maps which tend to differ from one database to another, making it more flexible and adaptable to different experimental conditions. Depending on the background pathway database, the interpretation of metabolite lists can differ and may be inaccurate, leading to contradicting results and less impact 3 . On contrast, GO analysis allows for a more detailed and accurate interpretation of results, as it provides a broader context for the function and regulation of metabolite levels. Because the GO system is standardized, it allows for greater consistency and comparability between different studies and datasets. GO terms not only covers the known pathway maps but also covers additional metabolic processes that are not yet included in the pathway databases. Key strengths of IDSL.GOA tool The IDSL.GOA tool is a free, user-friendly and web-based platform that utilizes Gene Ontology (GO) terms for the analysis of metabolomics data. It offers an intuitive interface that allows users to perform GO enrichment analysis for an input metabolite list. The tool has a range of useful features to facilitate the interpretation and has a wide range of capabilities, including query, explore, statistics, and download options. The use of GO terms provides an improved biological interpretation of metabolomics data, which can help researchers identify novel and metabolically relevant pathways and processes. The tool is built on a robust knowledgebase that contains relationships among metabolic entities, obtained from various sources including NCBI, Expasy and the Gene Ontology Consortium databases. The tool allows for a more comprehensive and accurate analysis of metabolomics data by identifying not only the predefined pathways but also relevant metabolic processes that are not included in the commonly used pathway databases. It is the first of its kind tool for metabolomics data. Future plan In the follow up work, we plan to improve IDSL.GOA by expanding the underlying database of GO to metabolite relationships. For this, we will curate and map the annotated compounds in the publicly available metabolomic datasets to the enzyme activity annotations and subsequently to the GO terms. There is also a need to harmonize the chemical information across reaction databases and metabolomics reports. Since the mapping between GO terms to genes, proteins and transcripts is available, the future version of IDSL.GOA may also facilitate a multi-omics GO analysis. Limitations Few limitations should be noted. The IDSL.GOA tool relies on the availability of InChiKey-linked metabolite data, and the coverage of metabolite curation may vary across different metabolomics laboratories. Not all annotated compounds in the metabolomic datasets have been linked with EC numbers in the biochemical databases. The GO hierarchy and associated annotations may contain biases or inaccuracies due to incomplete or outdated information. There is some redundancy in GO term names which may inflate the over-representation analysis results. The mechanistic interpretation still needs to be validated by additional experimentation. By discussing these limitations, we can provide a more balanced view of the capabilities and potential drawbacks of the IDSL.GOA tool for GO analysis in metabolomics.

Conclusions In summary, the IDSL.GOA tool can enable a comprehensive and accurate biological interpretation of metabolomics data. A much-needed transition from pathway maps to GO terms for interpreting metabolomic datasets can be supported by the IDSL.GOA tool. It is more sensitive in identifying significantly enriched GO terms that are relevant for metabolic processes. By providing a comprehensive view of the underlying biology, this approach can facilitate the identification of key regulatory pathways and biomarkers that may be useful for diagnosis, prognosis, and therapeutic targeting.

Biological interpretation of metabolomic datasets often ends at a pathway analysis step to find the over-represented metabolic pathways in the list of statistically significant metabolites. However, definitions of biochemical pathways and metabolite coverage vary among different curated databases, leading to missed interpretations. For the lists of genes, transcripts and proteins, Gene Ontology (GO) terms over-presentation analysis has become a standardized approach for biological interpretation. But, GO analysis has not been achieved for metabolomic datasets. We present a new knowledgebase (KB) and the online tool, Gene Ontology Analysis by the Integrated Data Science Laboratory for Metabolomics and Exposomics (IDSL.GOA) to conduct GO over-representation analysis for a metabolite list. The IDSL.GOA KB covers 2393 metabolic GO terms and associated 3144 genes, 1,492 EC annotations, and 2621 metabolites. IDSL.GOA analysis of a case study of older versus young female brain cortex metabolome highlighted 82 GO terms being significantly overrepresented (FDR < 0.05). We showed how IDSL.GOA identified key and relevant GO metabolic processes that were not yet covered in other pathway databases. Overall, we suggest that interpretation of metabolite lists should not be limited to only pathway maps and can also leverage GO terms as well. IDSL.GOA provides a useful tool for this purpose, allowing for a more comprehensive and accurate analysis of metabolite pathway data. IDSL.GOA tool can be accessed at https://goa.idsl.me/ . Subject terms

Supplementary Information

Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-51992-x. Author contributions P.M. and D.K.B. developed the database and online interface, prepared the figures and wrote the main manuscript text. O.F. provided the test data. All authors reviewed the manuscript. Funding NIH (U24ES035386, U2CES026561, R01ES032831, R35ES030435, U2CES026555 P30ES023515, K12ES033594, U2CES030859, UL1TR004419). Data availability The Aging Mouse Metabolome Atlas dataset can be accessed at https://doi.org/ 10.21228/M8C68D IDSL.GOA knowledgebase elements and relationships are available at https://zenodo.org/records/10223649 . IDSL.GOA tool can be accessed at https://goa.idsl.me/ site and https://github.com/idslme/IDSL.GOA . Competing interests DKB has been a consultant for the Brightseed Bio, South San Francisco, California. The remaining author has no competing interest to declare.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1299

oa_package/f4/40/PMC10788336.tar.gz

PMC10788337

38221530

Introduction Cholangiocarcinoma, a malignant cancer which initiates from the epithelial cells lining the bile ducts, is the second most common primary hepatic malignancy 1 – 3 . It is classified as being either intrahepatic or extrahepatic 4 , 5 . In Southeast Asia, especially in Thailand, cholangiocarcinoma is common where a high incidence in the northeast region is correlated with infections by the local liver fluke, Opisthorchis viverrini 6 – 9 . According to epidemiologic studies, the worldwide incidence and mortality of this cancer continue to rise 10 , 11 . At present, surgical resection is the only curative treatment selection for patients and even with this, recurrences are reported 12 – 15 . Therefore, the identification of novel non-surgical therapies is essential for improving outcomes in patients with cholangiocarcinoma. Because the immune response can be highly specific, it is hoped that tumor-specific immunity may be used to selectively eradicate tumors without injuring the patient 13 , 16 . Several immunotherapeutic approaches in cholangiocarcinoma are being actively investigated. These include peptide-based and dendritic cell (DC)-based vaccines, and antibody and adoptive cell immunotherapy. One of these interesting strategies relies on adoptive cell immunotherapy, in which immune effectors cells (such as T cells) are used for treatment of cancer patients with cholangiocarcinoma 17 – 19 . For instance, cholangiocarcinoma patients who receive a T cell transfer in combination with dendritic cells which were pulsed with a cholangiocarcinoma cell lysate have a lasting response and overall survival of 95.5 months 20 . A similar result has been found in patients with metastatic cholangiocarcinoma who received T cell-based adoptive immunotherapy combined with cetuximab, an epidermal growth factor receptor (EGFR) inhibitor 21 . However, the efficacy of T cell immunotherapies still has limitations because many tumor antigens are only weakly immunogenic. The immune cell may be unable to detect malignant cells and becomes tolerant to further tumor growth and metastasis. Replacing of conventional T cell therapies might include the use of a subset of lymphocytes, γδ T lymphocytes, an exclusive population of T lymphocyte that express the γδ T cell receptor 22 . Interestingly, many research studies have indicated that tumor cells can be recognized by Vγ9Vδ2 T lymphocytes, the major subset of γδ T cells in peripheral blood, through their expression of specific receptors for mediating anti-tumor responses and controlling tumor development. Vγ9Vδ2 T cells mediate anti-tumor immunity via several evident pathways such as the secretion of proinflammatory cytokines, and cell-to-cell contact-dependent lysis through a natural killer-like pathway or a T cell receptor-dependent pathway 23 . γδ T cells have been shown to devastate cells of many different types of tumor cell lines, including B cell lymphomas, multiple myeloma, and solid tumors of kidneys, colon, prostate and breast. The unique anti-tumor activities of γδ T cells call attention to their potential as candidates for cancer immunotherapy 24 , 25 . Two possible strategies for Vγ9Vδ2 T cell-based immunotherapy are i) adoptive cell transfer of in vitro expanded γδ T cells, and ii) in vivo therapeutic application of γδ-stimulating phosphoantigens or nitrogen containing bisphosphonates with low-dose recombinant interleukin-2 (rIL-2) 26 . Currently, use of Vγ9Vδ2 T cells as a therapeutic appliance has been studied in both solid tumors and hematologic malignancies. However, studies of Vγ9Vδ2 T cells in cholangiocarcinoma immunotherapy are limited. We found no published literature about the functional assessment of Vγ9Vδ2 T cells against cholangiocarcinoma target cells. Thus, the efficacy of Vγ9Vδ2 T cell-based immunotherapy against cholangiocarcinoma needs to be evaluated. In the present study, we showed that expanded Vγ9Vδ2 T cells recognized and efficiently killed cholangiocarcinoma cells. Pretreatment of cholangiocarcinoma cell lines with zoledronate can induce anti-tumor activity of Vγ9Vδ2 T cells. Our investigations revealed that the Vγ9Vδ2 T cell cytotoxicity was largely dependent on degranulation via the perforin and granzyme pathway. Importantly, we compared three different stimulation protocols for Vγ9Vδ2 T cells derived from the peripheral blood mononuclear cells (PBMCs) of healthy donors using zoledronate stimulated with cytokines IL-2, IL-15, and IL-18. In vitro characterization of expanded Vγ9Vδ2 T cells was based on data from phenotype, cytokine and apoptotic profiles of the cells. These data provide evidence that Vγ9Vδ2 T cells may be a promising candidate for adoptive immunotherapy against cholangiocarcinoma.

Materials and methods Cholangiocarcinoma cell line Two human cholangiocarcinoma cell lines, HuCCT1 and TFK-1, were used HuCCT1 (TKG0389) and TFK-1 (TKG0367) were purchased from Ricken Cell Bank. Both cell lines were grown in RPMI 1640 medium (Hyclone, USA) supplemented with 10% FBS (Department of Transfusion Medicine, Karolinska University Hospital, Huddinge, Sweden), 100 IU/mL penicillin G and 100 mg/mL streptomycin (Gibco, USA). Cells were incubated at 37 °C in 5% CO 2 and passaged in T75 flasks once the cells reached 90% confluence. Ex vivo expansion of Vγ9Vδ2 T cells PBMCs, obtained from six peripheral blood buffy coats of healthy donors, were separated by density gradient centrifugation using LymphoprepTM (AXIS-Shied PoC AS, Oslo, Norway). Cells were cultured at a concentration of 1 × 10 6 viable cells/mL in RPMI 1640 supplemented with 10% pooled human AB serum (Department of Transfusion Medicine, Karolinska University Hospital) and antibiotics in the presence of 5 μM zoledronate (Novartis Pharma) and 500 U/mL recombinant IL-2. After that, cultivated cells were treated with 30 ng/mL IL-15 or 30 ng/mL IL-18. All cell cultures were performed at 37 °C under 5% CO 2 . Viable cells were counted using trypan blue exclusion every other day and re-plated to maintain cell concentration. At day 10 of cultivation, γδ T cells were separated using a γδ T cell separation kit (Miltenyi Biotech, Bergisch Gladbach, Germany) according to the manufacturer’s instructions and checked subsequently for purity using flow cytometry. The study was approved by the ethical committees of the Karolinska University Hospital in Huddinge, Stockholm, Sweden. Informed consent was obtained from all patients according to the Karolinska Institute and with the declaration of Helsinki. Immunophenotyping by flow cytometry After cultivation of Vγ9Vδ2 T cells, cell surface staining was performed. Briefly, cells were incubated at 4 °C for 15 min with a combination of antibodies as follows before flow cytometric (FACS) analysis: anti-CD3-BV510 (UCHT1), anti-CD8-APC-cy7 (SK1), anti-CD27-BV421 (M-T271) (BD Biosciences, USA), anti-CD4-Alexa fluor 700 (RPA-T4), anti-TCR Vγ9-FITC (B3), anti-TCR Vδ2-FITC (B6), anti-CD45RA-PE (HI100), anti-PD-1-PE (EH12.2H7), anti-CD158-PE-cy7 (HP-MA4) (BioLegend, USA) and anti-CD152/CTLA4-FITC (A3.4H2.H12) (LifeSpan Biosciences, USA). Acquisition was performed on a FACSCANTO flow cytometry instrument using the FACSDiva software (BD Biosciences, USA). The acquired data was analyzed with FlowJo software (Tree Star, Inc., Ashland, OR). Stained control samples were used for gating according to the fluorescence minus one technique. Real-time polymerase chain reaction (PCR) analysis Real-time PCR of cytokine and apoptotic gene expressions (mRNA) were performed with the expanded γδ T cells which had been cultured with 5 μM zoledronate and 500 IU IL-2/mL, and stimulated with 30 ng/mL IL-15 or 30 ng/mL IL-18 cytokine or neither. After cultivation, cells were collected and RNA extracted using the PureLinkTM RNA Mini Kit (Thermo Fisher Scientific, USA). cDNA was generated using the SuperScriptTM IV VILOTM Master Mix (Thermo Fisher Scientific, USA) according to the manufacturer’s instructions. RNA and cDNA were checked for purity using the NanoDrop Spectrophotometer (Thermo Fisher Scientific, USA). Real-time PCR was performed on an ABI 7500 fast real-time PCR instrument (Applied Biosystems, USA). Relative gene expression of IL-1B, IL-2, IL-6, IL-7, IL-8, IL-12B, IL-15, and IL-17 was measured using pre-formulated TaqMan Gene Expression Assays and the TaqMan BACTIN Gene Expression Control Kit (Applied Biosystems, USA) as a previously published method 49 . Relative gene expression of caspase 3, caspase 8, caspase 9 and bcl-2 was measured using the PowerUpTM SYBRTM Green Master Mix Kit (Applied Biosystems, USA). All measurements were performed in duplicate. Cytotoxic assay To test the killing activity of the cultured Vγ9Vδ2 T cells, a cytotoxicity assay was performed as previously described 49 . Purified Vγ9Vδ2 T cells were re-suspended at a final concentration of 5 × 10 6 cells/mL; 200 μL was then added to round-bottom polystyrene tubes together with cholangiocarcinoma cells (100 μL) to obtain an E:T ratio of 10:1. Target tumor cells, both HuCCT1 and TFK-1, were labeled with the CellTraceTM Violet Cell Proliferation Marker (CTV, Thermo Fisher Scientific, USA) prior to co-cultivation. Briefly, a total of 10 mL of 2 μM CellTraceTM reagent was added to target tumor cells. Cells were incubated for 20 min at 37 °C. After incubation, cells were washed twice with culture medium containing FBS. Cells were then trypsinized to pellet target cells. Control tubes containing only labeled target cells were also prepared to establish background levels of cell death. Tubes, with or without 5 μM zoledronate, were gently mixed and centrifuged at 1700 rpm for 2 min, and incubated at 37 °C in 5% CO 2 for 24 h. At the end of the incubation period, 3 μL Annexin V was added to each tube and placed in the dark for 15 min. Finally, 200 μL PBS was added before acquisition using a FACSCANTO flow cytometry. The calculation of cytolytic activity was calculated utilizing the following equation: CD107 assay A CD107 assay, with the Vγ9Vδ2 T cells and cholangiocarcinoma cell lines, was set up according to the manufacturer’s instructions (BD Biosciences, USA) and a previously published method 63 . The cholangiocarcinoma cells, HuCCT1 and TFK-1 cell lines, were plated at 1 × 10 6 cells/mL in round-bottom polystyrene tubes and the Vγ9Vδ2 T cells were added to the tubes for E:T ratios of 10:1. Control tubes containing only Vγ9Vδ2 T cells were also set up and run with each assay. One microliter of GolgiStop (BD GolgiStopTM Protein Transport Inhibitor) and 20 μL of anti-CD107a-PE (H4A3) were added to each tube. Tubes were then incubated at 37 °C under 5% CO 2 for 4 h. At the end of the incubation period the cells were harvested and stained with anti-CD3-BV510 (UCHT1) and anti-TCR Vδ2-FITC (B6) for 15 min. Cells were then washed again and re-suspended in PBS and analyzed using flow cytometry. Statistical analyses All data were analyzed using the SPSS program (PASW Statistics program 18.0). The mean difference was compared by using compared mean and One-Way ANOVA with Least Significant Difference (LSD) test. The results were considered statistically significant ( p < 0.05) at the 95% confidence interval. The data shown as Mean ± Standard Error. The mean difference between values shown as mean difference (MD), 95% confidence interval, P-value .

Results Immunophenotyping of Vγ9Vδ2 T cell cultures PBMC from healthy donors were cultured simultaneously with one of three different conditions: complete medium containing 5μM zoledronate and 200 IU IL-2/ml alone, or with 30 ng IL-15/ml, or with 30 ng IL-18/ml or with neither. All subsequent flow cytometry measurements were performed after gating on γδ T cells. Assessments with flow cytometry at the end of cultivation for phenotype and viability indicated that all three protocols resulted in high numbers of viable Vδ2 + T cells (IL-2 = 96.53% ± 0.55, IL-15 = 91.68% ± 1.56, IL-18 = 93.00% ± 1.61). The number of cells in these three groups which increased with time in culture can reflect the efficiency of the protocols in proliferating the cells. Following the purification method, isolated cells consisted of > 98% Vγ9Vδ2 T cells as determined by FACS analysis (representative result out of 6 different experiments in each three protocols). Interestingly, zoledronate and IL-2, without either IL-15 or IL-18, provided the best results with regards to a high percentage of Vδ2 + T cells with significantly high percentage of CD158, also known as KIRs (killer cell immunoglobulin-like receptors) (IL-2 = 12.07% ± 0.78/IL-2,Zol,IL-15 = 10.34% ± 0.38/IL-2,Zol,IL-18 = 7.93 ± 0.69) [MD, 95%CI between IL-2 and IL-2,Zol,IL-18 = 4.14, 2.22–6.06, p = 0.001, and between IL-2,Zol,IL15 and IL-2,Zol,IL-18 = 2.41%, 0.48–4.33, p = 0.02] (Fig. 1 A). Moreover, no significant differences were observed in the expression of the CTLA4 on γδ T cells stimulated with the different protocols. Analysis of cytokine gene expression Vγ9Vδ2 T cells were subsequently analyzed for their expression of the cytokine genes IL-1β, IL-2, IL-6, IL-12β, IL-15, and IL-17 by using real-time PCR. Expression of all the cytokine genes expression could be observed with all three cultivation protocols. The determination of the gene expression pattern of Vγ9Vδ2 T cells cultivated from peripheral blood of all healthy donor indicated there were only IL-8 gene expression with significantly increased in condition with IL-2 alone in compared with IL-2,Zol,IL-15 (IL-2 = 0.0007 ± 0.0005/IL-2,Zol,IL-15 = 0.00025 ± 0.0001) [MD, 95%CI = 0.0005, 0.00004 ± 0.0009, p = 0.048] as well as IL15 gene expression with significantly increased in condition with IL-2 alone in compared with IL-2,Zol,IL-15 and IL-2,Zol,IL-18 (IL-2 = 0.00004 ± 0.0003/IL-2,Zol,IL-15 = 0.00001 ± 0.00001/IL-2,Zol,IL-18 = 0.00001 ± 0.00001) [MD, 95%CI between IL-2 and IL-2,Zol,IL-15 = 0.00003, 0.0001–0.00005, p = 0.047] [MD, 95%CI between IL-2 and IL-2,Zol,IL-18 = 0.00003, 0.0001–0.00006, p = 0.012]. However, there were no significantly differences among our three protocols in IL-1b, IL-2, IL-6, IL-7, IL-12b and IL-17. This might be implied that cultivation of Vγ9Vδ2 T cells supplemented with those supportive cytokines led to the same quality of Vγ9Vδ2 T cells (Fig. 2 ). Analysis of apoptotic profile of Vγ9Vδ2 T cell cultures To investigate whether different protocols for generation of Vγ9Vδ2 T cells result in differential pro- and anti-apoptotic signaling, the mRNA levels of various signaling molecules were analyzed. From the real-time PCR results, expression of pro-apoptotic signals, especially caspase 3, was significantly decreased in the IL-15 and IL-18 stimulation protocol when compared to IL-2 protocol (Mean ± SD of IL-2 = 4.16 ± 1.45/IL-2,Zol,IL-15 = 1.44 ± 0.11/IL-2,Zol,IL-18 = 2.78 ± 0.46) [MD, 95%CI between IL-2 and IL-2,Zol,IL-15 = 2.72, 2.32–3.12, p < 0.01, and between IL-2 and IL-2,Zol,IL-18 = 1.38%, 0.89–1.79, p < 0.01]. Caspase 8 was significantly decreased in the IL-15 and IL-18 (Mean ± SD of IL-2 = 1.87 ± 0.17 / IL-2,Zol,IL-15 = 1.43 ± 0.10 /IL-2,Zol,IL-18 = 1.38 ± 0.33) [MD, 95%CI between IL-2 and IL-2,Zol,IL-15 = 0.44, 0.11–0.87, p = 0.02, and between IL-2 and IL-2,Zol,IL-18 = 0.49%, 0.41–1.84, p < 0.01]. Caspase 9 was significantly decreased in the IL-15 and IL-18 (Mean ± SD of IL-2 = 0.18 ± 0.01/IL-2,Zol,IL-15 = 0.13 ± 0.01/IL-2,Zol,IL-18 = 0.15 ± 0.01) [MD, 95%CI between IL-2 and IL-2,Zol,IL-15 = 0.06, 0.41–0.74, p < 0.01, and between IL-2 and IL-2,Zol,IL-18 = 0.36%, 0.19–0.52, p < 0.01]. BCL-2 was significantly increased in the IL-15 but not significantly difference in IL-18 (Mean ± SD of IL-2 = 0.07 ± 0.01/IL-2,Zol,IL-15 = 0.14 ± 0.01 /IL-2,Zol,IL-18 = 0.09 ± 0.01) [MD, 95%CI between IL-2 and IL-2,Zol,IL-15 = 0.07, 0.04–0.98, p < 0.01] (Fig. 3 ). Cholangiocarcinoma cells treated with zoledronate enhanced cytotoxicity of Vγ9Vδ2 T cells The cytotoxic activity of expanded Vγ9Vδ2 T cells from healthy donors against cholangiocarcinoma cell lines was tested. Both of the cell lines, HuCCT1 and TFK-1, were efficiently killed by Vγ9Vδ2 T cells. HuCCT1 cells were more susceptible to kill by Vγ9Vδ2 T cells compared to TFK-1 cells. Treatment with zoledronate for 24 h was sufficient to render both HuCCT1 and TFK-1 cell lines highly susceptible to Vγ9Vδ2 T cell killing (E:T ratio of 10:1). Data showed increasing levels of cytotoxicity in zoledronate treated HuCCT1 compared with non-treated cells in three protocols (Mean ± SD of IL-2 = 74.02 ± 12.80, p = 0.04/ IL-2,Zol,IL-15 = 78.36 ± 11.20, p = 0.02 /IL-2,Zol,IL-18 = 67.35 ± 4.47, p = 0.04) (Fig. 4 A). Moreover, the cytotoxic activity towards both zoledronate treated HuCCT1 and TFK-1 target cells of Vγ9Vδ2 T cells were compared. The Vγ9Vδ2 T cells from IL-15 stimulation protocol apparently kill TFK-1 target cells significantly less than the other groups (Mean ± SD of IL-2 = 44.14 ± 3.99/IL-2,Zol,IL-15 = 34.59 ± 2.50/IL-2,Zol,IL-18 = 43.15 ± 2.25) [ P-value between IL-2 and IL-2,Zol,IL-15 = 0.01, and between IL-2,Zol,IL-15 and IL-2,Zol,IL-18 = 0.001]. In the same experiments, the E:T ratios were varied as 1:1, 5:1, 10:1, 20:1 to demonstrate the cytotoxic activity towards cholangiocarcinoma cells of Vγ9Vδ2 T cells. At E:T ratios of 1:1 and 5:1, the cytotoxic activity of Vγ9Vδ2 T cells did not shift significantly whereas at E:T ratios of 20:1, similar results as 10:1 were obtained with expanded Vγ9Vδ2 T cells derived from healthy donors. Killing of cholangiocarcinoma cells mediated by CD107 pathway To determine possible mechanisms involved in Vγ9Vδ2 T cell-mediated cytotoxicity, we examined cell surface expression of a lysosomal-associated membrane protein (LAMP-1). Also known as CD107a, this is an integral membrane protein localized within cytolytic granules transiently mobilized to the surface of the cell during degranulation. As shown in Fig. 5 A, the average expression of CD107a on the surface of Vγ9Vδ2 T cells exposed to both HuCCT1 and TFK-1 cell lines were higher than control, especially in HuCCT1 in our three protocols (Mean ± SD of IL-2,Zol = 29.29 ± 2.96, p = 0.04/IL-2,Zol,IL-15 = 30.20 ± 10.05, p < 0.001/IL-2,Zol,IL-18 = 29.40 ± 5.60, p < 0.001). Based on these initial findings, both cholangiocarcinoma cell lines can activate the degranulation process of Vγ9Vδ2 T cells.

Discussion Human Vγ9Vδ2 T cells, a major subset of γδ T cells in peripheral blood, have received increased interest regarding this immune response to cancer over the past decade. Clinical trials utilizing Vγ9Vδ2 T cell-based cancer immunotherapy have been launched and their efficiency to lyse a broad range of tumor cells has been reviewed 27 – 29 . Given that T cell receptors (TCRs) of Vγ9Vδ2 T cells can recognize antigens in a non-MHC restriction manner, these cells can be generated as adoptive allogeneic cells therapy with low chance to cause graft-versus-host disease (GVHD) 30 , 31 . Indeed, with the APC property, Vγ9Vδ2 T cells can bridge between innate and adaptive immune systems and lead to other immune cell types providing anti-tumor function 32 . Altogether, Vγ9Vδ2 T cell-based cancer immunotherapy provide the advantages over other forms of cancer treatment. It is known that Vγ9Vδ2 T cells acquaint isopentenyl diphosphate (IPP, also called phosphoantigens), intermediates of the mevalonate pathway, via their TCRs 33 , 34 . In order to obtain large numbers of Vγ9Vδ2 T cells from PBMCs, nitrogen-containing bisphosphonate drugs (N-BPs, synthetic drugs commonly used for the treatment of postmenopausal osteoporosis) can be used to indirectly activate Vγ9Vδ2 T cells. This occurs through inhibition of farnesyl diphosphate (FPP) synthase and yields in IPP accumulation in human monocytes 35 – 37 . Zoledronate, a third-generation N-BP, has been shown to stimulate Vγ9Vδ2 T cells relying upon farnesylated proteins. The in vitro proliferation of Vγ9Vδ2 T cells activated by zoledronate combined with IL-2 allows a promising strategy for both in vitro and clinical studies. The feasibility and clinical safety of Vγ9Vδ2 T cells therapy have been evaluated 31 , 38 . Unknown is whether Vγ9Vδ2 T cells have immunosuppressive function or proinflammatory cytokines releasing which may exert some side effects or risks of using these cells in cancer treatment. The effective way to manage would be identifying and depletion of these cells from the adoptive cell product before infusion in clinical trial 31 , 39 . Normally, IL-2 exerts T lymphocytes proliferation and differentiation into effector T cells and memory T cells 40 – 42 . Vγ9Vδ2 T cell expansion can be furthered by the addition of various cytokines, such as IL-15, which act via Toll-like receptors (TLRs) as reviewed by Wesch, et al . 43 . IL-15 is an important cytokine involved in induction of T cell proliferation and cytotoxic activity 44 . It was reported that the greater proliferative and cytotoxic capacities of γδ T cells were resulted from the addition of IL-15 into γδ T cell cultures 45 . IL-18 is also specifically known for its role in inducing cell-mediated immunity. The functional effects of IL-18 on human intraepithelial lymphocyte (IEL) proliferative responses have been reported 46 , 47 . However, the stimulatory effects of IL-18 on γδ T cells remains unclear. In this study, three different stimulation protocols for Vγ9Vδ2 T cell cultures were compared: one protocol using only recombinant IL-2, one using IL-2 with additive IL-15, and one using IL-2 with additive IL-18. In all of the cultivation protocols, zoledronic acid was used as a stimulant of phosphoantigens. Cultivation with all three protocols resulted in γδ T cells predominantly expressing Vδ2 TCRs as shown in Fig. 1 A, in concordance with previous studies 45 , 48 . Interestingly, there is significant difference in co-inhibitory markers CD158 expression among three groups, suggesting that supportive cytokines can augment the proliferative responses of Vγ9Vδ2 T cells. Normally, variety protocols for cultivation of Vγ9Vδ2 T cells have been launched mostly based on cytokine-based stimulation method. Different protocols might result in different Vγ9Vδ2 T cells persistent and this might be the importance issue to concern since the existence of cultivated Vγ9Vδ2 T cells will affect the yield and purity of the cultivation for further analysis experiment significantly. Therefore, we identified the molecular mechanisms of cytokine-based stimulation protocols. Regarding cytokine production by Vγ9Vδ2 T cells, highly elevated mRNA levels of cytokines needed for T cell proliferation and differentiation were detected in all protocols. These types of cytokines were reported to specify a preferential development of a cytokine-producing phenotype of Vγ9Vδ2 T cells. However, there is no significant difference among three protocols which might suggest that cultivation of Vγ9Vδ2 T cells supplemented with supportive cytokines, IL-15 and IL-18 led to the same phenotype of Vγ9Vδ2 T cells. In addition, the significant differences of cytokine gene expression were found in umbilical cord blood and peripheral blood γδ T cells from previous studies suggesting the capable of generating of cytokine-producing phenotype in umbilical cord blood γδ T cells 49 , 50 . We also analyzed for pro-apoptotic gene expression in every cultivation protocol. Interestingly, there were with significantly lower expression of caspase 3, caspase 8 and caspase 9 in both IL-15 and IL-18 cultivation protocols (Fig. 3 ). This knowledge regarding cytokine-based stimulation protocols may increase the therapeutic efficacy of Vγ9Vδ2 T cells, especially where the additional stimulation with IL-15 and IL-18 might be useful in generating very high numbers with high persistency of Vγ9Vδ2 T cells. Our data is in concordance with previous studies 45 , 46 . To investigate the in vitro cytotoxicity of Vγ9Vδ2 cells against cholangiocarcinoma, ex vivo-expanded Vγ9Vδ2 T cells from all cultivation methods were assessed. Our study clearly demonstrated that purified and ex vivo-expanded Vγ9Vδ2 T cells can kill cholangiocarcinoma cell lines and pretreatment of target cells with zoledronate further activated the cytotoxicity of Vγ9Vδ2 T cells in vitro (Fig. 4 A) which is similar to previous reports 51 , 52 . According to the accumulation of IPP within zoledronate-treated cancer cells, expanded Vγ9Vδ2 T cells expressed higher cytotoxic functions against zoledronate-treated cholangiocarcinoma cell lines compared to non-treated cells. Taken together, cultivation based on IL-15 or IL-18 stimulation should be considered when appropriate persistency and anti-tumor functions of Vγ9Vδ2 T cells are required. Exploration of the protocol here used, combining zoledronate and IL-2 with addition of IL-15 or IL-18, led to a substantial induction and proliferation of Vγ9Vδ2 T cells. The hallmark of Vγ9Vδ2 T lymphocytes aimed to kill tumors is their histocompatibility unrestricted cytotoxic ability and their potentiality to secrete cytokines involved in the anti-tumor response 38 , 53 , 54 . Direct cell contact-dependent lysis is other important antitumor effect mediated by Vγ9Vδ2 T cells 52 , 55 , 56 . As a general note, the specific cytotoxic potential of cytotoxic T lymphocytes can be described by the detection of CD107a expression, a LAMP-1 dwelling in cytolytic granule membranes located within the cytoplasm. CD107a transiently expressed and mobilized to the effector T cells surface following stimulation thus providing cytotoxic functional readout 57 – 59 . The mechanisms of cytotoxic activity of Vγ9Vδ2 T cells against cholangiocarcinoma cells are important to better understand. We observed high levels of CD107a expression on Vγ9Vδ2 T cell surfaces after exposure to tumor cell lines. This suggested that potential Vγ9Vδ2 T cell targeting of cholangiocarcinoma might be via a perforin-dependent cytolytic pathway. Our observation is in line with the findings of a previous study 60 . In addition, other possible mechanisms involved in the induction of cholangiocarcinoma apoptosis by Vγ9Vδ2 T cells need to be studied. According to the ongoing identification of new targets for immunotherapy in cholangiocarcinoma, a T cell basis has been developed for improving outcomes in patients with cholangiocarcinoma. Of note, with the antigen cytolytic capacity, allogenic γδ T cells have demonstrated safety and antitumor efficacy in cholangiocarcinoma patient with no adverse effect from treatment. 21 , 30 , 61 , 62 . Hence, Vγ9Vδ2 T cells could be a good candidate for development as an effective treatment of patients with this type of lethal disease.

Conclusions Taken together, data from our study support the addition of the immunostimulatory cytokines IL-15 and IL-18 to in vitro γδ T cell cultures as a feasible and efficacious approach to activation and expansion of Vγ9Vδ2 T cells. This may offer the good approach to achieve higher yields of expanded γδ T cells with suitable characteristics for consideration for use in clinical trials. In seeking more specific effector cells for adoptive therapeutics against cholangiocarcinoma, we demonstrated that Vγ9Vδ2 T cells can mediate cytotoxicity against cholangiocarcinoma and that zoledronate can be used to sensitize cholangiocarcinoma cells to this cytotoxic activity. In this regard, Vγ9Vδ2 T cells may help facilitate development of novel strategies for adoptive immunotherapy in cholangiocarcinoma.

Human Vγ9Vδ2 T lymphocytes are regarded as promising effector cells for cancer immunotherapy since they have the ability to eliminate several tumor cells through non-peptide antigen recognition. However, the cytotoxic function and the mechanism of Vγ9Vδ2 T cells leading to specific killing of cholangiocarcinoma cells are yet to be confirmed. In this study, we established a protocol for ex vivo expansion of Vγ9Vδ2 T cells from healthy donors’ peripheral blood mononuclear cells by culture with zoledronate and addition of IL-2, and IL-15 or IL-18 or neither. Testing the cytotoxic capacity of cultured Vγ9Vδ2 T cells against cholangiocarcinoma cell lines showed higher reactivity than against control cells. Surface expression of CD107 was detected on the Vγ9Vδ2 T cells, suggesting that these cells limit in vitro growth of cholangiocarcinoma cells via degranulation of the perforin and granzyme pathway. Analysis of molecular signaling was used to demonstrate expression of pro- and anti-survival genes and a panel of cytokine genes in Vγ9Vδ2 T cells. We found that in the presence of either IL-15 or IL-18, levels of caspase 3 were significantly reduced. Also, IL-15 and IL-18 stimulated cells contained cytotoxicity against cholangiocarcinoma cells, suggesting that stimulated Vγ9Vδ2 T cells may provide a feasible therapy for cholangiocarcinoma. Subject terms

Acknowledgements This work was supported by the Thailand Research Fund under Royal Golden Jubilee Ph.D. Program Grant (No. PHD 0156/2556 to PS and KJ), Mahidol University and the Office of National Higher Education Science Research and Innovation Policy Council (NXPO), Thailand, through Program Management Unit for Competitiveness (PMU C) (No. C10F630292 to KJ) and the Research Chair Grant from the National Science and Technology Development Agency of Thailand (No. FDA-CO-2559-3325-TH to SH). The authors sincerely thank to Dr. Arther E. Brown for English language proofing. Author contributions M.U. and K.J. conceived and supervised study. M.U., K.J., C.L. and S.H. designed the study and contributed to the literature search. P.S. and A.G. performed the experiments and contributed to data collection and data interpretation. K.J., P.S., A.G. and S.L. contributed to data analysis. P.S. and K.J. wrote the paper. All authors discussed the results and commented on the manuscript. Data availability All data generated or analysed during this study are included in this published article. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1291

oa_package/c2/5b/PMC10788337.tar.gz

PMC10788338

38221527

Introduction Traumatic brain injury (TBI) is a leading cause of death and disability worldwide 1 with incidence of 0.2–0.5% per year 2 . It is a complex, heterogeneous condition affecting a broad population, with a wide range of clinical presentations and outcomes. Despite advances toward understanding the pathophysiology of TBI 3 , 4 , outcome-improving treatments remain rare. A potential explanation for this lack of progress is the heterogeneity of TBI, which may underlie the lack or heterogeneity of benefit observed in multiple large-scale TBI trials (CRASH, DECRA, RESCUE-ICP) 5 – 7 . One of the important frontiers of TBI research is to deconvolve the condition into a spectrum of disorders that manifest differently between patients 8 . Precision medicine aims to address the shortcomings of our current reductionist approach to the treatment of TBI, instead considering clinical characteristics in individual patients. This strategy expects to identify relatively homogenous patient subgroups that share treatment responses. Precision approaches appear well adapted to increasingly data-rich healthcare systems 9 . The evolution of high-dimensional longitudinal databases and adaptation of data analytics have improved insight into disease heterogeneity 10 , 11 . Specifically, the analysis of completed clinical trials or molecular datasets on acute respiratory distress syndrome 12 , asthma 13 , 14 and sepsis 15 have identified homogenous subgroups with distinct clinical features, transforming clinical practice. These analyses promoted the concept of patient “endotypes”, defined as patient subgroups that share clinical and/or molecular characteristics. Endotype research on TBI patient subgroups aims to identify homogeneous populations that share diagnostic criteria, outcomes, and treatment response 16 , 17 . The identification of such relevant endotypes in TBI may enhance our understanding of disease mechanisms, enable targeted therapeutic approaches, and facilitate stratification for randomized controlled trials. Comorbidity, the coexistence of two or more chronic conditions, is increasingly common secondary to aging populations 18 with prevalence between 15 and 54% 19 . Within TBI heterogeneity, patient comorbidity is a commonly reported prognostic factor 20 – 22 . However, comorbidities do not typically arise in patients randomly. Often, they follow distinct patterns of co-occurrence due to underlying pathophysiological mechanisms. Latent class analysis (LCA) is a well-validated unsupervised machine learning algorithm that can be used as an objective way to discover co-occurrence patterns of comorbidities. LCA assumes unobserved (or latent) clusters underlying the data and uses a probabilistic approach to determine the set of clusters that best explains the observed data 23 . Given comorbidity data inputs, these latent clusters represent patient subgroups with similar comorbidity profiles. LCA has been successfully implemented to describe endotypes in ARDS 12 , sepsis 15 , diabetes 24 , and obesity 25 . In this study, we hypothesize that TBI patient outcomes vary between comorbidity endotypes. Our primary outcome of interest was survival to discharge, while our secondary outcomes included surgical intervention and duration of hospital stay. We leveraged the prospective Medical Information Mart for Intensive Care III (MIMIC-III) dataset to create a study cohort of adult patients with TBI and used LCA to identify comorbidity endotypes with distinct characteristics. These endotypes may help formalize clinical intuition about prognostication of groups of patients, inform recruitment to clinical trials, and contribute towards the foundation for improved treatment of TBI.

Methods MIMIC III database Patient information on clinical characteristics and outcomes were extracted from MIMIC-III, a large, single-centre database including 38,597 adult (≥ 16 years old) patients admitted to critical care units at, Beth Israel Deaconess Medical Center, a large tertiary care hospital in Boston, MA 26 . TBI patients were identified from MIMIC-III based on International Classification of Diseases, Ninth Edition (ICD-9) codes. Our study cohort was selected based on established ICD-9 diagnostic codes previously shown to capture the diagnosis of TBI and can be found in Supplementary Table 1 27 – 29 . We extracted data on patient sex, date of birth, admission date, discharge date, discharge status, ICD-9 diagnosis codes (for patient comorbidities), ICD-9 procedure codes, and initial Glasgow Coma Score (GCS). In patients with re-admission, only data from their first admission was used as this represents the acute TBI treatment phase of interest. Data variable construction The initial total GCS score for each patient was used in defining injury severity as mild (GCS 14–15), moderate (GCS 9–13), or severe (GCS 3–8), as per Brain Trauma Foundation Guidelines 30 . Age was stratified into three bins: young (16–39), middle-aged (40–69), and old (70 +). We used previously published procedure codes that capture intracranial pressure monitor placement, craniotomy/craniectomy, and ventriculostomy, to derive a logistical variable for neurosurgical intervention 28 . Definition of comorbidities We used the well-established Elixhauser comorbidity index 31 to define chronic conditions by implementing an algorithm provided by the authors of the MIMIC-III database 32 . This algorithm groups ICD-9 codes into 30 chronic conditions to define comorbidity categories. The output is a binary matrix reflecting the presence or absence of a morbidity category by patient ID which was used in subsequent analyses. Network discovery We implemented network discovery to identify co-occurrences in morbidities as described previously 11 . Relative risk (RR) of observing a pair of comorbidities affecting the same patient was calculated using the formula described by Hidalgo et al. 33 . The RR is calculated from the number of patients affected by the two comorbidities, study population, and prevalence of each comorbidity (Supplementary Fig. 1 ). We then constructed a network of associated comorbidities by only including associations over the significance threshold of p < 0.05 to visualize the relationships between various conditions. Within this network graph, each node represents an Elixhauser comorbidity with node size corresponding to its prevalence and each edge between nodes representing an association between comorbidities with the color corresponding to the RR of the pair and the width to the number of co-occurrences. The colormap for RRs was capped at 5.0 to prevent outliers from skewing visualization. Latent class analysis and cluster stability Latent class analysis (LCA) uses structural equation modeling to identify different subgroups (endotypes) within study populations that share certain characteristics. The R package “poLCA” 34 was used to identify patient endotypes based on the derived 30 Elixhauser comorbidities. The LCA algorithm fits mixture models to the input data and, through optimization steps, determines the latent classes (endotypes) based on the best-fitting model. For optimization, we used previously published guidance 35 , 36 , including the elbow method and Akaike information criteria (AIC) to find the optimal number of endotypes. This method involves finding the inflection point of the graph and plotting the number of clusters against an evaluation metric (AIC in this case) which can be seen in Supplementary Fig. 2 . We used the R package “inflection” 37 to objectively determine the inflection point to be at five clusters which represents the optimal number of endotypes. Due to the stochastic nature of implementing LCA, we took the following additional measures to ensure model validity and cluster stability. We repeated the LCA clustering algorithm on the same data to generate 30 sets of five endotypes. The comorbidity distributions of all 150 total endotypes were then analyzed using latent profile analysis (LPA) which, like LCA, looks for clusters, but in continuous variables rather than categorical. This was done via the R package “mClust” 38 and compressed the 150 endotypes into a smaller number of recurring endotypes which are visualized in Supplementary Fig. 3 . We found that the most well-fit models (models with the lowest AIC) had statistically identical endotype comorbidity profiles. Therefore, we decided to use a representative model within these low-AIC models for our subsequent analysis as this model was inferred to contain endotypes with the greatest stability. Resultant endotypes were characterized clinically through consensus agreement among study authors. Quantitative analysis/statistics and visualization Absolute counts with percentages were reported for categorical data and mean with standard deviation (SD) for continuous data. Statistics were completed using R packages “stats” 39 and “multcomp” 40 and Python libraries “statsmodels” 41 and “SciPy” 42 . The primary outcome was defined as survival to discharge and the secondary outcomes as hospital length of stay (LOS), and neurosurgical intervention. The Pearson Correlation analysis was conducted to assess the collinearity between age and the number of comorbidities as these were the most likely variables to demonstrate correlation. Only a weak correlation between age and number of comorbidities was found so we used multivariable logistic regression to analyze the relationship between our primary outcome of survival to discharge and number of comorbidities while accounting for key prognostic factors: age, sex, and GCS. Pairwise chi-squared (survival and intervention rates) and t-tests (LOS) were used for the initial comparisons of clinical outcomes across endotypes and P-values were adjusted using the Holm-Bonferroni method. Multivariable logistic regression and Analysis of Covariance (ANCOVA) was used for more in-depth comparisons of clinical outcomes across endotypes: Multivariable logistic regression analysis was used to compare survival to discharge (yes/no) and neurological intervention (yes/no) between comorbidity endotypes (using the “Healthy” (HE) endotype as the reference category) adjusting for age, sex, and GCS. The odds ratios (OR) with 95% confidence intervals (CI) were reported where appropriate. ANCOVA was used to compare hospital LOS between comorbidity endotypes while adjusting for age, sex, and GCS with a Tukey post-hoc for comparisons between each pair combination of endotypes. To obtain additional analysis resolution for our primary outcome of survival, we stratified patients within endotypes into groups based on age and GCS bins and conducted paired t-tests between the strata of the endotypes. Additionally, we created the following multivariable logistic regression models to isolate and assess the performance of endotypes in predicting our primary outcome of survival: (1) model 1 using only the 30 Elixhauser comorbidity categories, (2) model 2 using only the 5 derived comorbidity endotypes and, (3) model 3 using both the 30 Elixhauser comorbidity categories and 5 derived comorbidity endotypes. These models were compared using ANOVA with F scores and P-values reported. Area under the curve (AUC) was also calculated for each model using the R package “pROC” 43 . The above analysis was repeated after adding age, GCS, and sex as covariates to models to assess the effect of Elixhauser comorbidities and endotypes on overall survival prediction performance. Logistic regression models and AUC calculations were also completed for a base model that included only age, GCS, and sex as well as models using only these individual variables. Cases with missing data were excluded from statistical analyses. Figures were generated via the R library “ggplot2” and the Python libraries “matplotlib” and “networkX”.

Results Comorbidity characterization We included 2,629 patients in our analysis. The mean age was 59.0, 61.9% were male, average GCS was 10.4, the mean number of comorbidities was 2.0, and the rate of survival to discharge was 36.7%. The demographics of our study cohort are summarized in Table 1 . The relationship between age, number of comorbidities, and survival can be visualized in Fig. 1 . Age and comorbidity count was only weakly associated (r = 0.20, p < 0.001). We then tested the association of the comorbidity count with the survival to discharge after accounting for age and GCS score in a multivariable logistic regression model and found that the number of comorbidities was negatively associated with survival (OR for survival per one increase in comorbidity count = 0.984, CI: 0.975–0.994). We next investigated the pattern of comorbidities, specifically their associations in the entire cohort to test our hypothesis that many comorbidities co-occur. These relationships between the Elixhauser comorbidity groups are visualized by the network graph in Fig. 2 . This network discovery of the data revealed intuitive subgroups: congestive heart failure (CHF) with arrhythmia (RR = 2.76, CI: 2.73–2.79), drug abuse with alcohol abuse (RR = 3.02, CI: 2.95–3.11), and renal failure with complicated hypertension (RR = 16.27, CI: 15.96–16.58). Clinical characterization of comorbidity endotypes We next analyzed the comorbidity data for the presence of endotypes using LCA. After 30 iterations, five stable clusters of patient endotypes emerged, detailed in Fig. 3 by their comorbidity probability distribution. Endotype 1 was labeled Heart Failure and Arrhythmia (HFA), characterized by cardiac comorbidities. Endotype 2 featured few comorbidities and was labelled Healthy (HE) and used as the reference endotype for subsequent analyses. Endotype 3 is characterized mainly by high rates of renal failure with complicated hypertension and was labelled Renal Failure with Hypertension (RFH). Endotype 4 was labelled Alcohol Abuse (AA), featuring high rates of alcohol abuse and relatively low rates of other comorbidities. Endotype 5 had high rates of hypertension and relatively low rates of other comorbidities, labelled Hypertension (HTN). The distribution of TBI injury severity categories was relatively similar although HE and AA endotypes contained slightly larger proportions of severe TBI at 46.9% and 39.4%, respectively (Table 2 ). The HFA and RFH endotypes had nearly identical age distributions of mostly older individuals in addition to a small subpopulation of middle-aged individuals (17.9% middle-aged, 82.4% old vs 19.7% middle-aged, 80.9% old, respectively). The HTN endotype was composed mainly of older adults (68.6%) with a moderate proportion of middle-aged individuals (28.3%) and a small subpopulation of young individuals (3.7%). The AA group was primarily composed of middle-aged individuals (73.7%). HE endotype was composed of mainly young (47.6%) and middle-aged (40.0%) individuals. There were minor sex differences among a few endotypes, contributed to mainly by the young age segment which consistently had a higher proportion of male patients; middle-aged and old age groups across endotypes had comparable sex distributions (Supplementary Table 2 ). For comorbidity count, HE had the least number of comorbidities (0.8 ± 0.8) followed by HTN (2.5 ± 1.2) while the other comorbidities had higher averages within a similar range (AA: 4.0 ± 1.2, HFA: 4.5 ± 1.6, RFH: 5.5 ± 2.1). Each endotype had distinct rates of survival to discharge (Table 3 ). HE had the highest survival to discharge, followed by AA, HTN, RFH, and HFA. Survival differences between all endotypes were statistically significant (HE 78.5%, AA 70.1%, HTN 51.4%, RFH 40.4%, HFA 27.8%, p < 0.05 for all comparisons). RFH had the lowest rate of neurosurgical intervention (13.2%) which was statistically lower than HFA (27.3%) and HTN (25.7%) which had the highest intervention rates (RFH vs HFA p = 0.033, RFH vs HTN p = 0.022). All other comparisons of intervention rates were non-significant between endotypes). For LOS, endotypes were split into long (HFA: 10.2 ± 7.2 days, RFH: 8.7 ± 6.0 days, AA: 10.6 ± 7.5 days,) and short (HE: 7.3 ± 6.9 days, HTN: 7.7 ± 6.4 days) LOS groups in where p < 0.05 for comparisons between endotypes across groups and p > 0.05 for comparisons of endotypes within a group. Survival to discharge Multivariable logistic regression models accounting for age, sex, and GCS showed that the endotypes HE, AA, and HTN had the highest survival rates (Table 4 ). Using the HE endotype as reference, AA (OR = 0.999, CI: 0.935–1.066) and HTN (OR = 0.962, CI: 0.919–1.007) had statistically similar survival rates compared to HE. HFA had the lowest survival rate (OR with respect to HE = 0.803, CI: 0.747–0.862) which was statistically different from all other endotypes. RFH had lower survival than HE (OR with respect to HE = 0.889, CI: 0.821–0.964) but higher than HFA (OR with respect to HFA = 1.108, CI: 1.011–1.214). Survival rates when accounting for age, sex, and GCS are as such: HE, AA, HTN > RFH > HFA. In contrast to the initial analyses, comparison of survival rates between HE, AA, and HTN becomes statistically insignificant when including age (OR per increase in age = 0.991, CI: 0.991–0.992) and GCS (OR per increase in GCS score = 1.028, CI: 1.024–1.031). Additional investigation of these three endotypes based on stratification by age and GCS revealed that HE had higher survival in the middle-aged group compared to AA (80.3% vs 69.8%, p = 0.010) and was similar in all age groups in comparison to HTN (Table 5 ). However, when further sub-stratifying age groups by GCS, some substrata comparisons become significant: HE has a higher survival rate than AA for the mild GCS group in both young (97.5% vs 83.3%, p = 0.043) and middle-aged groups (94.1% vs 70.0%, p < 0.001). Although survival was not different across age strata between HE and HTN, sub-stratification by GCS revealed that HE had better survival for the mild (94.1% vs 87.2%, p = 0.043) and severe (66.7% vs 52.6%, p = 0.043) GCS groups within the middle-aged group. Neurosurgical intervention In comparison to HE, HFA (OR = 1.146, CI: 1.067–1.231) and HTN (OR = 1.123, CI: 1.074–1.175) had the highest rate of neurosurgical intervention while RFH (OR = 1.005, CI: 0.928–1.089) and AA (OR = 1.037, CI: 0.972–1.107) had statistically similar rates of intervention after adjusting for age, sex, and GCS (Table 6 ). Overall, results from the multivariable logistic regression divide the endotypes into the low (HE, RFH, AA) and high (HFA, HTN) intervention groups where rates are statistically different compared to endotypes of the other group for comparisons) while being statistically similar to endotypes of the same group. Length of stay Using ANCOVA to adjust for the covariates of age, sex, and GCS, HE had shorter LOS than HFA (difference = 4.6 ± 0.9 days, p < 0.001), RFH (difference = 3.3 ± 1.1 days, p = 0.015), and AA (different = 4.8 ± 0.9 days, p < 0.001) but had similar LOS compared to HTN (difference = 1.2 ± 0.6 days, p = 0.214) (Table 7 ). HFA and AA had almost identical LOS (difference = 0.2 ± 1.2 days, p = 1.000). LOS for the RFH endotype was statistically comparable to every other endotype ( p > 0.05 for all comparisons) except HE. Overall, HE and HTN had the shortest LOS while HFA and AA had the longest LOS of the endotypes after accounting for age, sex, and GCS. Predictive value of comorbidities and endotypes for survival Logistic regression using all 30 Elixhauser comorbidity categories to predict survival to discharge accounts for ~ 15.3% of the variation in outcome (F(30, 2598) = 15.59, R 2 = 0.153, p < 0.001) and had an AUC of 0.73. A simpler logistic regression using the five derived comorbidity endotypes accounted for 11.9% of the variation in survival (F(4, 2624) = 88.61, R 2 = 0.119, p < 0.001) with an AUC of 0.69. Combining the base 30 Elixhauser categories with the endotypes in a full logistic regression model explains 17.0% of the variation in survival (F(34, 2594) = 15.57, R 2 = 0.170, p < 0.001) and has an AUC of 0.74. The decrease in model error for predicting survival to discharge seen between the base logistic regression (including only the comorbidities) and the full model (including both comorbidities and endotypes) is statistically significant (F(4, 2594) = 13.23, p < 0.001). With the inclusion of age, GCS, and sex into the logistic model using the 30 Elixhauser comorbidities, the model explains ~ 30.5% of the variation in survival (F(33, 2548) = 35.28, R 2 = 0.305, p < 0.001) and had an AUC of 0.83. The addition of the five derived endotypes into this model results in explanation of ~ 31.7% of the variation in survival (F(37, 2544) = 31.91, R 2 = 0.317, p < 0.001) with an AUC of 0.84. The decrease in model error in predicting survival after adding endotypes is statistically significant (F(4, 2544) = 3.13, p = 0.014). A model with age, GCS, sex, and comorbidity endotypes explains ~ 28.7% of survival variation (F(7, 2574) = 142.9, R 2 = 0.287, p < 0.001) with an AUC of 0.82.For reference, a logistic model with only age, GCS, and sex accounts for 26.8% of the variation in survival with an AUC of 0.80. A model with only age accounts for 19.7% of survival variation with an AUC of 0.77; a model with only GCS accounts for 2.7% of survival variation with an AUC of 0.61; a model with only sex accounts for 0.9% of survival variation with an AUC of 0.55.

Discussion Endotypes in TBI and other conditions Our initial analyses are consistent with previous literature and clinical experience—that comorbidities are associated with clinical outcomes and that comorbidities tend to occur in patterns 44 , 45 . In characterizing the relationship between comorbidities and clinical outcomes, we have identified five patient endotypes using LCA, based solely on the presence of medical conditions. These represent the most observed clinical patterns within the TBI population of the MIMIC III dataset. The notion of patient endotypes is a validated approach to precision medicine and has been used to elucidate heterogeneity in many other conditions such as sepsis and asthma 14 , 16 , 46 . In TBI, Åkerlund et al. suggested six endotypes in TBI patients based on GCS, body temperature, and lab values that added predictive value for in-hospital mortality 47 . This is the first study to consider endotypes in TBI patients utilizing comorbidities. Our previous work 11 investigated comorbidity endotypes within all of MIMIC III, identifying six overall endotypes while this current study focuses on the TBI population and produces similar but distinct endotypes. Both studies’ endotypes included hypertension, cardiac comorbidities, renal failure, and the lack of comorbidities (i.e., healthy). However, there were also major differences. While the AA endotype contained only alcohol use disorder as a comorbidity, the corresponding endotype in our previous analysis was “Hepatic addiction”, which, in addition to alcohol abuse, had significant rates of liver failure and coagulopathy. As well, the current analysis did not find any endotype that corresponded to the “Cardiopulmonary” endotype in our previous study, characterized by high rates of chronic pulmonary and cardiac comorbidities. Although similarities exist, these results suggest that distinct TBI comorbidity endotypes exist that differ from those of the general ICU population. Viewing TBI clinical outcomes by endotypes Analyzing comorbidities via endotypes rather than individually shifts emphasis onto the fact that individual comorbidities don't exist in isolation and allows for a more comprehensive understanding of how a group of conditions affects the outcomes of acute injuries such as TBI. Additionally, it allows us to group patient presentations into clusters based on common pathophysiological patterns and clinical considerations which may facilitate decision-making. Outcomes differences between medically complex endotypes Heart failure comorbid with arrhythmia (HFA) and renal failure comorbid with hypertension (RFH) appear to be two common patterns of comorbidity in medically complex TBI patients. Overall, HFA has higher rates of neurosurgical intervention and mortality but similar LOS. The association between renal failure and cardiac comorbidities is supported by many studies 48 – 51 and may explain notable rates of congestive heart failure (CHF) and arrhythmia in the RFH comorbidity distribution. However, it is interesting that despite the notable presence of cardiac comorbidities in RFH, the pure cardiac endotype HFA, which has fewer comorbidities overall, still exhibited poorer outcomes. A large multicenter study by Shibahashi et al. 52 found that both CHF and chronic kidney disease (CKD) increased the odds of in-hospital mortality for TBI patients. The odds ratio estimate for CKD (2.76, CI: 1.96–3.89) was notably higher than CHF (1.82, CI: 1.31–2.51), contrasting our results. However, Shibahashi et al. compared individual comorbidities while our analysis compares endotypes that contain multiple comorbidities at different rates. A possible explanation for the difference in our findings could be the notable prevalence of arrhythmias in the HFA and RFH endotypes. Patients with arrhythmias are frequently administered anticoagulant and/or antiplatelet medications, which may increase the need for intervention, risk of intervention, and mortality rates 53 , 54 . Hence, HFA having a higher rate of intervention and mortality may be contributed to by its higher rate of arrhythmia compared to the RFH endotype. Overall, our results suggest that the TBI patients of the cardiac-centric HFA endotype carry a poorer prognosis than the renal-centric RFH endotype. Both endotypes represent cohorts of older, clinically complex patients that fare significantly worse than the other endotypes even after controlling for age or injury severity. Future trials of TBI interventions may benefit from treating patients that fit into these endotypes as their own subgroups. Alcohol abuse and length of stay As alcohol abuse and hypertension are common in TBI patients 22 , we were interested in how the AA and HTN endotypes differed from HE. There is a robust relationship between alcohol use and TBI 55 that is consistent with our finding that AA is a major TBI endotype. Overall, HE and AA had similar rates of survival and neurosurgical intervention but notably higher LOS. There have been many factors linking alcohol use disorder and increased LOS such as alcohol withdrawal including seizure 56 – 58 , increased risk of hospital complications and infection, particularly of pneumonia 59 , and pre-injury cerebral atrophy secondary to neurotoxicity 60 , 61 . Taken together, a slow and potentially turbulent recovery may explain the increased LOS in AA. Overall, we see that the AA endotype identified via LCA is consistent with previous literature and aligns with clinical observations. Hypertension and outcomes of intervention and survival We found that the HTN endotype has a higher rate of intervention compared to HE and a lower rate of survival, isolated to the middle-aged strata, particularly among mild and severe injury severities. Given that chronic hypertension is known to cause and accelerate cerebrovascular damage 62 , higher rates of adverse outcomes after TBI in the HTN endotype could be explained by a less compliant, and hence less resilient, remodelled cerebrovascular system 63 , 64 . The same mild injuries to HTN patients may result in greater damage and hence warrant a more aggressive treatment (e.g., ICP monitoring, craniotomy). The observation that differences in survival were only significant for the middle-aged group and not for the old age group may be due to the effect of age overshadowing the weaker effect of hypertension in this age group. While pre-hospital hypertension has been linked to increased TBI mortality 65 , 66 , a systematic review did not find chronic hypertension to increase in-hospital mortality in TBI patients 22 . These differences may result from other studies using the presence/absence of hypertension for their effect analysis in patients that potentially have other pre-existing comorbidities, contrasting our analysis that directly compares healthy patients with patients primarily with hypertension (without other comorbidities). Endotypes for precision medicine LCA endotyping assesses the patient more holistically, accounting for both the presence and absence of diseases, to make comparisons between groups of patients that are similar. Linear regression attempts to describe the net effect of a single condition (e.g., hypertension) across a potentially heterogeneous population and struggles when input variables are correlated with each other, as is the case with comorbidities 67 , 68 . It also struggles to describe outcomes that cannot be explained by a linear combination of the model inputs whereas LCA endotypes have an aspect of non-linearity inherent to the complex relationships between input variables that they capture 69 , 70 . Our observed improvement in a logistic regression model's ability to predict survival by incorporating endotypes, in addition to individual comorbidities, supports the capturing of such additional non-linear effects through LCA. A large proportion of the endotypes’ predictive power for survival likely comes from their capture of patient age (e.g., patients with hypertension are likely to be older than those with alcohol abuse). Such is suggested by the large amount of variation in survival explained by age alone (19.7%) combined with the minor improvement in performance seen by adding endotypes as a variable to the base model of only age, GCS, and sex (R 2 : 26.8% to 28.0%; AUC: 0.80 to 0.82). Interestingly, our comorbidity endotypes have more predictive value as an isolated variable for survival than GCS (R 2 : 11.9%vs 2.7%, AUC: 0.69 vs 0.61) suggesting that patient-inherent factors may be more important to TBI outcomes than initial injury severity as measured by GCS. As our endotypes involved only broad comorbidity variables, the overall improved predictability offered by endotypes in our analysis was relatively modest (~ 2% in model fit by R 2 , ~ 2% in model AUC). This improvement may be larger for complex endotypes that integrate continuous variables, especially those exhibiting a parabolic association with outcomes such as blood pressure, hemoglobin, and temperature. Therefore, endotype analysis offers a different perspective on the data that may be better suited to precision medicine and prognostication than regression with individual variables. Limitations LCA is a method that attempts to deduce a possible explanation given the observed data points. A common concern with LCA is that results invite interpretation despite the lack of a true reasonable interpretation in reality 23 , 71 . Therefore, it relies on the researcher’s judgement to determine if the latent classes represent meaningful entities which introduce a degree of interpretive bias into the analysis. Through our cluster selection process, we have attempted to ensure that the final set of clusters represented the simplest clinical explanation, but we cannot exclude the existence of a potentially more complex set of endotypes that better explain the variance in TBI patient comorbidities. While the LCA endotypes help explain the variation of comorbidities across patients, there also exists more layers of variation within each identified endotype, as not all patients within endotypes are identical. We try to account for this in the analysis of our primary outcome of survival with the use of stratification by GCS and age to capture important variations common to all TBI patients. However, it could be argued that GCS and age have differential effects on outcomes depending on endotype and that there may be additional condition-specific factors to consider for each endotype. For example, creatinine measures may be relevant in RFH to account for the extent of renal failure while total cumulative alcohol intake could be used to stratify AA patients into different exposure levels. Unfortunately, due to limited granularity, and potentially limited sample size in substrata, we did not investigate this further. This approach of granular analysis could be a strategy for future research toward increasingly personalized medicine using big data. Another limitation of this study is the size of the MIMIC III dataset. Although it is a large and comprehensive dataset, there is limited granularity that may not capture the full complexity of patient health or outcomes. We do not have clinical justifications behind decisions, such as neurosurgical intervention, which requires the context of individual patient risk assessment. The data is limited to a single center, which may not be generalizable to the overall population and may have policies and personnel preferences that introduce artifacts in variable coding. In particular, there may be inaccuracies and staff biases in the ICD9 codes that we have used for the implementation of Elixhauser comorbidities. The same analysis using another database may yield a set of comorbidity endotypes that differ in significant ways. Finally, limitations inherent to retrospective designs apply as well. Therefore, the next steps for our research will involve the replication of our methods on different TBI databases, and ultimately prospective studies, to assess the generalizability of our findings.

Conclusion TBI, like many other conditions, is complex with varied clinical and biological presentations that contribute to their heterogeneity. In this study, we demonstrate the discovery of TBI comorbidity endotypes with distinct clinical outcomes. Our results suggest that viewing clinical variables, such as the presence or absence of a disease, in combinations is a promising way to address and better understand the heterogeneity observed in TBI and other complex conditions. This study serves to expand the applicability of the growing concept of clinical endotypes by validating the approach in a highly prevalent condition such as TBI. By utilizing approaches such as LCA that can extract meaningful combinations from large volumes of data, we can move towards precision medicine in an era that is becoming increasingly data-rich.

Traumatic brain injury (TBI) is a complex condition where heterogeneity impedes the advancement of care. Understanding the diverse presentations of TBI is crucial for personalized medicine. Our study aimed to identify clinically relevant patient endotypes in TBI using latent class analysis based on comorbidity data. We used the Medical Information Mart for Intensive Care III database, which includes 2,629 adult TBI patients. We identified five stable endotypes characterized by specific comorbidity profiles: Heart Failure and Arrhythmia, Healthy, Renal Failure with Hypertension, Alcohol Abuse, and Hypertension. Each endotype had distinct clinical characteristics and outcomes: The Heart Failure and Arrhythmia endotype had lower survival rates than the Renal Failure with Hypertension despite featuring fewer comorbidities overall. Patients in the Hypertension endotype had higher rates of neurosurgical intervention but shorter stays in contrast to the Alcohol Abuse endotype which had lower rates of neurosurgical intervention but significantly longer hospital stays. Both endotypes had high overall survival rates comparable to the Healthy endotype. Logistic regression models showed that endotypes improved the predictability of survival compared to individual comorbidities alone. This study validates clinical endotypes as an approach to addressing heterogeneity in TBI and demonstrates the potential of this methodology in other complex conditions. Subject terms

Supplementary Information

Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-51474-0. Acknowledgements We would like to thank Dr. Frank Rudzicz (University of Toronto) for his feedback and comments on the manuscript. Author contributions Study conception and design: H. Q., Z. Z.; data collection: H. Q.; data analysis: H. Q.; interpretation of results: H. Q., Z. Z., M. L., F. F., T. D., S. S.; draft manuscript preparation: H. Q., Z. Z., M. L., F. F., T. D., S. S.; all authors reviewed and approved the final version of the manuscript. Data availability All code used for analysis and visualization of our data is available on GitHub: https://github.com/SteveHQiu/TBIClustering . Data used in our analysis were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) dataset which is a freely available database: https://physionet.org/content/mimiciii/1.4/ . Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1294

oa_package/c8/6c/PMC10788338.tar.gz

PMC10788339

38221546

Introduction Glioblastoma (GBM), the most lethal type of intracranial tumor, is characterized by highly infiltrative and aggressive growth, along with abundant neovascularization 1 . The current standard treatment for GBM involves surgical resection, chemotherapy and radiotherapy, a widely adopted approach for an extended period. Precision treatment plan, incorporating one or a combination of these therapies, are typically tailored for individual patients. However, the median overall survival (OS) time for GBM patients remains unsatisfactory despite these efforts 2 , 3 . Though great development has been achieved in cancer diagnosis and therapy in recent years, clinical advances in GBM treatment have been limited.. Recent reports suggest that anti-angiogenic reagents, such as bevacizumab, a type of monoclonal antibody of vascular endothelial growth factor (VEGF),may enhance the effectiveness of post-operative chemo-therapy and wreck recurrent GBMs. However, the role of RNA modification in anti-angiogenic therapy is still unveiled. Consequently, there is an urgent need to identify novel targets and develop new agents or inhibitors to advance GBM treatment 4 . RNA modification represents a crucial facet of epigenetic regulation in eukaryotic cells, encompassing various modifications such as N6-methyladenosine (m6A), N7-methylguanosine (m7G), N1-methyladenosine (m1A), 5-methylcytidine (m5C), adenosine to inosine transition (I), pseudouridine (ψ), 5-methoxycarbonylmethyluridine (mcm5U) and 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2U) 5 among others. Notably, N6-methyladenosine (m6A) stands out as the most prevalent type of RNA modification in eukaryotic cells, with recent emphasis on its vital functions in regulating RNA stability, splicing, processing, translation and degradation 6 – 9 . The crucial role of RNA modification in cancers has garnered attention. exemplified by instances such as ALKBH5's modulation of cancer anti-PD-1 therapy efficacy by controlling lactate accumulation and suppressive cells in the cancer microenvironment 10 . Moreover, hepatitis B virus (HBV) infection has been linked to enhanced m6A modification of PTRN mRNA, impacting cancer immunity and contributing to the malignant progression of liver cancer 11 . Bioinformatic analysis have identified m6A-associated long non-coding RNAs (lncRNA) as promising prognostic biomarkers for WHO grade II–III gliomas 12 . Consequently, targeting m6A has emerged as a promising strategy for illuminating the path forward for cancer patients. In our current study, our objective was to screen out the angiogenesis-associated RNA modification regulators from the 53 RM regulators. Employing a comprehensive set of bioinformatic analyses, including gene set enrichment analysis (GSEA), protein–protein interaction (PPI) analysis, Pearson correlation analysis, single-cell data analysis and Kaplan–Meier survival analysis, we pinpointed that ALKBH5 as a potentially significant and prognostic biomarker. Subsequent validation experiments confirmed that knockdown of ALKBH5 significantly impacted the angiogenesis promotion ability of glioblastoma (GBM) both in vitro and in vivo.

Methods and materials Data acquisition Transcriptomic and clinical data of GBM patients from the Cancer Genomic Atlas (TCGA) and the Chinese Glioma Genomic Atlas (CGGA) were downloaded from the UCSC dataset ( https://xenabrowser.net/datapages/ ) and CGGA website ( http://www.cgga.org.cn/ ), respectively. A total of 516 GBM samples were analyzed across three independent cohorts: TCGA-GBM (n = 145), CGGA-seq1 (n = 236) and CGGA-seq2 (n = 135). Transcriptomic data of normal human samples were sourced from the Genotype-Tissue Expression (GTEx) portal ( https://gtexportal.org/home/ ). The genes encoding RNA modification regulators were acquired from a collection of prior study 5 . Gene set enrichment analysis (GSEA) The gene set of “Angiogenesis” was fetched from the database of molecular signatures database (MSigDB, https://www.gsea-msigdb.org/gsea/msigdb/index.jsp ). Before conducting GSEA analysis, TCGA-GBM patients were divided into two subgroups based on the top 30% and bottom 30% expression of each RNA modification regulator (RM). Differential expression analysis (DEA) was subsequently conducted to identify differential expression genes (DEGs) associated with each RM regulator expression via the R packages “Simpleaffy” 13 and “affy” 14 . The criteria for DEGs were set at log2 (fold change) > 1 and p value < 0.05. Subsequently, GSEA analysis was conducted via utilizing the R package “clusterProfiler” 15 . The most positive and negative associated RM regulators were recognized based on the criteria: normalized enrichment score (NES) > 1.9 or < − 1.9, and normalized p value < 0.05. Protein–protein interaction (PPI) The data of protein–protein interaction (PPI) was obtained from the website of STRING ( https://string-db.org/ ). A total of 36 angiogenesis regulators downloaded from the MSigDB, fiftly-two RM regulators obtained from the previous publication were co-input into the software of Cytoscape (version 3.7.1). Both data analysis and figure visualization were performed within Cytoscape. Pearson correlation analysis Pearson correlation analysis was employed to assess the statistical correlations between the expressions of angiogenesis regulators and RNA modification regulators. Pearson Correlation coefficient “R value” and statistical p value were calculated to evaluate the correlation level and significance between two factors. Expression comparison analysis The most positive and negative enriched RM genes were used to conduct expression comparison between normal brain tissues (NBTs) and TCGA GBMs. Willcoxon’s rank sum test was applied to compare the expression levels between them. Statistical p value < 0.05 was the threshold to distinguish the statistical significance. Single cell data research Single-cell data of GBMs were sourced from a previous study 16 and analyzed in the Tumor Immune Single-cell Hub (TISCH, http://tisch.comp-genomics.org/ 17 . The analysis procedure was conducted according to previous studies 18 . The data, identified by the serial number GSE89567 in the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/gds ), encompassed 6341 cells from 10 GBM patients, categorized into AC-like Malignant, Mono/Macro, OC-like Malignant, and Oligodendrocyte cell types. Scatter diagrams were generated to illustrate the distribution of RM regulators across these cell types. Kaplan–Meier survival analysis Kaplan–Meier survival model was applied to judge the prognostic role of RM regulators across three independent GBM cohorts. The R packages “survival” (version 3.3–1) and “survminer” (version 0.4.9) were used to analyze and visualize the survival curves. Statistical p values were calculated by the method or log-rank test. p < 0.05 was set as statistical significance standard. The ‘surv-cutpoint’ function of R package “survminer” was utilized to select the most statistically significant cut-off for each analysis. Human protein atlas (HPA) and protein interaction analysis Immunofluorescent staining figures of ALKBH5 in U251 GBM cell line and the immunohistochemical staining data of glioma samples with low- and high grade were obtained from the Human Protein Atlas (HPA, https://www.proteinatlas.org/ 19 . Interactors of ALKBH5 protein Information of ALKBH5 interactors were downloaded from the Compartmentalized Protein–Protein Interaction Database (ComPPI, version 2.1, https://comppi.linkgroup.hu/ ). The protein codes were mapped and translated in the Uniport database ( https://www.uniprot.org/ ). Protein–protein interactions were visualized by the R package “ggplot2”. Sample collection Seven paired GBM and adjacent tissues were collected from the inpatients in the department of neurosurgery of the Yan’an People’s Hospital from 2020 to 2021. All tissues were immediately stored in the liquid nitrogen after resection. Patients involved in this study had provided informed consent for the usage of sample, and the usage of clinical samples was in strict accordance with the guideline of the Medical Ethics Committee of Yan’an People’s Hospital. Gene ontology and encyclopedia of genes and genomes analysis GBM patients in the TCGA cohort were grouping as the description in the “Gene Set Enrichment Analysis” part. Differential expressed genes (DEGs) were identified by R package “limma” 20 under the standard of |log2(fold change) |> = 1 and p value < 0.01. Then the DEGs were input to perform the GO and KEGG analysis using R package “clusterProfiler” 15 , the top fifteen terms in each project, such as biological process (BP), molecular function (MF), cellular component (CC) and KEGG pathway were visualized in the bubble plots. Cell lines and cell culture The U87 GBM cell line and Human Umbilical Vein Endothelial Cells (HUVECs) were purchased from the American Type Culture Collection (ATCC, USA). Dulbecco's modified eagle medium (DMEM, Gibco) and Endothelial Cell Mediums (ECM, ScienCell) were used to culture U87 and HUVEC cells, respectively. Except 5% fetal bovine serum (FBS, Gibco) and 1% Penicillin/Streptomycin solution (P/S, Gibco) were added in both mediums, 1% Endothelial Cell Growth Supplement (ECGS, ScienCell) was used to maintain HUVEC culture. 10% FBS and 1% Penicillin/Streptomycin solution were supplemented in DMEM for culturing U87 cells. Both cells were grown in 5% CO 2 at 37 °C conditions. Short hairpin RNA (shRNA) construction and transfection To achieve ALKBH5 knockdown, U87 cells were transfected with lentivirus packaging sh-RNAs targeting ALKBH5, using the pLKO.1—TRC cloning vector from the addgene (#10878, addgene, USA). The specific shRNA sequences of targets are listed: shALKBH5-1: 5′-GACTCTTGATGACCGCGTT-3′; shALKBH5-2: 5′-GAAGCTTCAATGGTCTCCTTA-3′; and a non-targeting control (sh-Con): 5′-TTCTCCGAACGTGTCACGT-3′. Transfection reagent Lipofectamine 3000 (#L3000008, ThermoFisher Scientific, USA) was employed to sensibilize the cell transfection reactions. RNA isolation and reverse transcription quantitative polymerase chain reaction (RT-qPCR) Cell total RNA was extracted by using RNA isolation kit (S1550S, New England Biolabs, USA) under the instruction of protocol. Subsequently, 100 ng of total mRNA was reverse transcribed using TaqManTM universal master mix II (#4440042, ThermoFisher Scientific, USA) according to the manufacturer’s protocol. The ALKBH5 mRNA expression level was quantified from amplified cDNA, and normalized by the GAPDH expression, which was set as internal control. The ΔΔCT method was utilized to compared the expressions of ALKBH5 a different groups. One-way ANOVA was the statistical method for calculating the significance of distinction. The primers used in our study were listed below: ALKBH5 Forward: 5′-CCCGAGGGCTTCGTCAACA-3′, Reverse: 5′-CGACACCCGAATAGGCTTGA-3′; VEGFA Forward: 5′-GGGCAGAATCATCAC GAAGT-3′, Reverse: 5′-TGGTGATGTTGGACTCCTCA-3′; FGFR1 Forward: 5′-GTGGCT-GTGAAGATGTTGAA-3′, Reverse: 5′-GCC-AGGTCTCGGTGTATGCA-3′; VAV2 Forward: 5′-TCAGGCCTTTTCCCTCAGAG-3′, Reverse: 5′-TGCACCTCCACCTTGATGAT-3′; GAPDH Forward: 5′-ACCCAGAAGACTGTGGATGG-3′, Reverse: 5′-CAGTGAGCTTCCCGTTCAG-3′. Protein extraction and western blot Cell lysis buffer (#R0010, Solarbio, China) was used to collapse the cells on the ice, phenylmethanesulfonylfluoride (PMSF, #P0100, Solarbio) was added in one hundredth of the volume of lysis buffer to restrain the degradation of protein. The protein concentration of lysates was quantified using the Enhanced BCA Protein Assay Kit (#P0010S, Beyotime, China). The western blot assay was strictly following the procedures of a previous publication 21 . The primary antibodies included ALKBH5 Monoclonal antibody (#67811-1-Ig, Proteintech, China), VEGFA Monoclonal antibody (#66828-1-Ig, Proteintech, China), VAV1 Polyclonal antibody (#16364-1-AP, Proteintech, China), FGFR1 Monoclonal antibody (#60325-1-Ig, Proteintech, China), and GAPDH Polyclonal antibody (#10494-1-AP, Proteintech, China). The horseradish peroxidase (HRP)-conjugated affinipure goat anti-rabbit IgG (1:5000, SA00001-2, Proteintech, China) and HRP-conjugated affinipure goat anti-mouse IgG (1:5000, SA00001-1, Proteintech, China) served as corresponding secondary antibodies after incubation with primary antibody. The value of protein was calculated using the ImageJ software. Enzyme‐linked immunosorbent assay (ELISA) The quantification of human-derived VEGFA secretion from U87 cell lines was conducted using the enzyme-linked immunosorbent assay (ELISA) kit from Proteintech (#KE00216, China). The procedure was applied in strict accordance with the manufacturer’s protocol provided by the kit. Wound healing and transwell assay For the wound healing assay, a total of 10^5 HUVEC cells were seeded in a well of 6-well plates prior to the assay. Once the cells firmly attached in the well, a straight line was scratched into the fully confluent monolayer using a 1 ml tip. The cultured medium of U87 cells (control and sh-ALKBH5 transfected) were then added to replace the ECM for 24 h culture. Pictures were captured at 0 h and 24 h timepoint after medium replace. In the transwell assay, a total of 20,000 HUVEC cells were placed in the transwell chamber (# 07-200-150, Corning, USA), and an equal number of GBM cells were seeded in the wells of 48-well plates. After 24 h co-culturing, the wells were washed three times using PBS, and stained the cells using gentian violet solution (#G1072, Solarbio, Beijing, China) for 1 h. Subsequently, the cells were washed,, and photographed the cells by using microscope. Tube formation assay To explore the role of GBM intrinsic ALKBH5 in tumor angiogenesis, the culture medium of U87 cells (control and sh-ALKBH5 transfected) were collected to dilute Matrigel with 1:1 ratio. A 50 μl medium-matrigel mix was added in 96-well plates on ice, and allowed to solidify in incubator (37 °C) before seeding the HUVECs. Each well was gently added with 15,000 HUVECs suspended in 50ul ECM medium without FBS and ECGS. Images were captured at 3 h after cell paved, and tube number was calculated with ImageJ software. Subcutaneous U87 Xenograft model Animal experiments were approved by the Medical Ethics Committee of Yan’an People’s Hospital following the UK Animals (Scientific Procedures) Act, 1986 and Animal Research Reporting In Vivo Experiments (ARRIVE) guidelines. Six-week-old female BALB/c nude mice were purchased from GemPharmatech company (Nanjing, China). A total of 1 × 10 6 control or ALKBH5 knock-down U87 GBM cells were resuspended in 200μL PBS (pH = 7.4) and injected into the backs of nude mice subcutaneously. The tumor size was measured every five days for each mouse when tumor growing. The nude mice were euthanized at the 20th day, and then the tumors were harvested and measured. Immunohistochemical (IHC) staining The procedure of tumor sample IHC staining was performed, and the quantification was calculated according to a previous publication strictly 22 . Statistical analysis Statistical analysis used in this study were conducted under R programming (version 4.1.3). The data with non-normal distribution between two groups were compared by Wilcoxon rank-sum test. As for normal distributed data, two-sided Student’s t-test was carried out. The protein expression of ALKBH5 in clinical samples were quantified and compared by two-sided paired t-test. Statistical correlations between two genes were quantified using Pearson Correlation analysis by R programming language. Ethics approval and consent to participate This study is approved by the Medical Ethics Committee of Yan’an People’s Hospital, the usage of clinical samples and all methods were in strict accordance with the guideline of the Declaration of Helsinki. All enrolled inpatients have informed consent to participate in this study.

Results Examining RNA modification regulators linked to angiogenesis The role of RNA modification in the angiogenesis of GBM microenvironment remains unclear, to address this, we employed the GSEA method to identify angiogenesis-related RNA modification (RM) regulators. A total of 53 RM regulators spanning eight types of RNA modification were subjected to GSEA for the Angiogenesis hallmark, the Fig. 1 A shows the GSEA results of all RM regulators through a bubble plot. The color indicates the normalized enrichment score (NES) and the bubble size represents the false discovery rate (FDR) of the GSEA results. Subsequently, significant RM regulators were individually visualized based on NES values exceeding 1.9 or falling below − 1.9 (Fig. 1 B). Notably, ALKBH5, YTHDF3, WTAP exhibited positive associations with the angiogenesis hallmark, while FTO, NSUN5, NSUN6, RPUSD1 and YTHDC1 displayed negative associations. To unravel the interaction landscape of proteins between RNA modification and angiogenesis, we conducted an analysis using STRING database (Fig. 1 C). The results indicated fewer interactions or predictions between RM and angiogenesis regulators, emphasizing transcriptomic interactions as the primary means of linking RNA modification and angiogenesis in GBM. Correlations between angiogenesis-associated regulators and RNA modification regulators Thus, transcriptomic relationships between RM and angiogenesis regulators were investigated subsequently. The eight angiogenesis related RM regulators were selected to perform Pearson correlation analysis with 36 angiogenesis regulators using their transcriptomic data in GBM. The correlation results were visually represented in a heatmap, with red indicating positive correlations and blue indicating negative correlations (Fig. 2 A). We visualized several significant correlations in scatter plots. Scatter plots illustrated significant correlations; for instance, WTAP exhibited positive associations with angiogenesis regulators like CXCL6 (Fig. 2 B, Pearson R = 0.42, p < 0.0001) and S100A4 (Fig. 2 C, Pearson R = 0.53, p < 0.0001). ALKBH5, as a m6A demethylase coding gene, showed positive correlations with VEGFA (Fig. 2 D, Pearson R = 0.33, p < 0.0001) and FGFR1 (Fig. 2 E, Pearson R = 0.32, p < 0.0001) expression. In contrast, NSUN6 displayed negative correlations with most angiogenesis regulators like S100A4 (Fig. 2 F, Pearson R = 0.58, p < 0.0001) but positively associated with PTK2 expression (Fig. 2 G, Pearson R = 0.48, p < 0.0001). YTHDC1 is also negatively associated with most angiogenesis regulators, indicating a broad relationship with the RNA expressions of angiogenesis regulators. These results indicated RNA modification regulators have a wide range relationship with angiogenesis regulators’ RNA expressions, which suggested they might regulate GBM angiogenesis via influencing RNA metabolism of angiogenesis regulators. Transcriptomic expression of RNA modification regulators in GBM Our investigation delved into the roles of eight angiogenesis-associated RM regulators in GBMs. We compared the expressions of these regulators by integrating RNA-seq data from normal brain tissues (NBTs, GTEx database) and GBMs (TCGA database). As represented in Fig. 3 A, ALKBH5, YTHDF3, WTAP, FTO, NSUN5 and YTHDC1 are significantly upregulated in GBMs, while NSUN6 decreases. Only RPUSD1 showed nonsense between NBTs and GBMs. To gain a detailed view of these RM regulators' expression distributions in GBM microenvironment, single cell analysis was conducted using a public GBM single-cell dataset GSE89567. The cells in GBM microenvironment are mainly divided into four types: AC-like Malignant, OC-like Malignant, oligodendrocyte and Mono/Macro cells (Fig. 3 B). Across the eight RM regulators, ALKBH5, FTO, NSUN6, RPUSD1 and YTHDC1 were mainly expressed in malignant cells, while YTHDF3 and WTAP were highly expressed in both malignancy and monocytes/macrophages (Fig. 3 C). Prognostic of angiogenesis-associated RNA modification regulators in GBMs To access the clinical relevance of the eight RM regulators, we performed Kaplan–Meier survival analysis on three independent GBM cohorts (Fig. 3 D). As shown in the survival analysis, only ALKBH5 acts as a risky factor in all the three GBM cohorts, the survival curves indicate that GBM patients with higher ALKBH5 expressions had a shorter survival time and rate (Fig. 3 E–G). This part of results highlight ALKBH5 is not only associated with GBM angiogenesis, but also a stable prognostic biomarker for predicting GBM prognosis. Landscape of ALKBH5 protein in GBM Summarizing it all together, ALKBH5 emerges as an angiogenesis associated RM regulator, exhibiting higher expression in GBM tissues and cells, and serving as a predictor of GBM patient prognosis. Further exploration of ALKBH5's protein distribution, interactors, and expression in GBMs reveals its presence in both the nucleus and cytoplasm of U251 GBM cells (Fig. 4 A) Immunohistochemistry staining images from the HPA datasets suggest higher expression of ALKBH5 in higher-grade gliomas (Fig. 4 B). The protein–protein interaction (PPI) analysis identifies interactors such as FOXA1, LMNA, CSNK2A1, JUN, TRIM25, ELAVL1, HSCB, and HECW2, known for their crucial roles in GBM 23 – 27 (Fig. 4 C). Thus, the interactions between ALKBH5 and its interactors are also worthy to be paid attentions. Finally, the protein expression level was also accessed in our clinical GBM samples compared with adjacent tissues by western blotting (Fig. 4 D, Original gel images showed in Supplementary Fig. 1 A, B). Paired t-test was applied to access the different expression levels of ALKBH5 protein, and it indicated that ALKBH5 protein is significantly upregulated in GBM samples compared with NBTs (Fig. 4 E). We also analyzed the ALKBH5 expression across gliomas with different WHO grades in the TCGA and CGGA cohorts, all the results indicated the highest expression of ALKBH5 in WHO IV gliomas (Fig. 4 F–H). Besides, a higher ALKBH5 expression is observed in IDH-wild GBM compared IDH-mutant GBM (Fig. 4 I–K). These results underscore the association between ALKBH5 and glioma malignant phenotypes. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of ALKBH5 in GBM To elucidate the biological processes, molecular function, cellular component and pathway associations of ALKBH5 in GBMs, we conducted gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis in GBM by categorizing GBMs into ALKBH5-low and ALKBH5-high two subgroups. In the most significant biological process, vasculature development was enriched in ALKBH5-high GBMs (Fig. 5 A), which is consistent with our GSEA analysis. Additionally, ALKBH5-high GBMs exhibited enrichment in cell migration, biological adhesion, inflammatory and response. Cytokine-associated activities were significantly enriched in ALKBH5-high GBMs in terms of molecular functions (Fig. 5 B). Regarding cellular components, secretory associated cellular components were significantly enriched in ALKBH5-high GBMs (Fig. 5 C). The most interesting is that the enriched KEGG pathways in ALKBH5-high GBMs include PI3K-AKT signaling, TNF signaling, NF-κB signaling, HIF-1 signaling pathways (Fig. 5 D), all of these oncogenic pathways had been reported to have angiogenesis promotive functions in GBMs. ALKBH5 Konck-down impairs the pro-angiogenesis ability of U87 cells in vitro To access the role of intrinsic ALKBH5 in GBM angiogenesis, two shRNA sequences targeting ALKBH5 from a previous study 28 were used to downregulate the expression of ALKBH5. Both RT-qPCR and western blot confirmed the successful downregulation of ALKBH5 by both shRNAs (Fig. 6 A-C, Original gel images showed in Supplementary Fig. 2 A, B). Subsequent assays demonstrated that the culture medium from sh-ALKBH5-U87 cells reduced the migratory ability of co-cultured HUVECs in wound healing and transwell assays compared to control U87 cells (Fig. 6 D–G). This indicated that down-regulation of ALKBH5 in GBM cells could influence the mobility of HUVEC via the method of external secretion. To be sure of the impact of ALKBH5 in angiogenesis, Tube formation assays also revealed that ALKBH5 downregulation in U87 cells impacted the angiogenic potential of co-cultured HUVECs (F i g. 6 H,I). Down-regulation of ALKBH5 decreases VEGFA expression in vitro and in vivo To elucidate how ALKBH5 regulats GBM angiogenesis, we selected FGFR1, VAV2 and VEGFA as potential downstream angiogenesis regulator according to the bioinformatic results (Fig. 2 A), and verified the expression levels of FGFR1, VAV2 and VEGFA in ALKBH5-knock-down U87 cells. By RT-qPCR analysis, we found VEGFA mRNA expressions were downregulated in sh-ALKBH5 U87 cells (Fig. 7 A), rather than VAV2 and FGFR1 (Fig. 7 B,C). Besides, western blot also verified the VEGFA downregulation effect in sh-ALKBH5 U87 cells (Fig. 7 D,E, Original images showed in Supplementary Fig. 3 A–D). Finally, considering VEGFA is secreted to promote cancer angiogenesis, we also test the VEGFA levels in the culture medium of sh-ALKBH5 U87 cells (Fig. 7 F), and results also indicated knock-down ALKBH5 in U87 cells will lead to less VEGFA expression and secretion. In vivo experiments using subcutaneous implantation of sh-Con and sh-ALKBH5 U87 cells in nude mice demonstrated a significant decrease in tumor size with ALKBH5 knockdown (Fig. 8 A,B). And by detecting VEGFA and CD31 expressions in tumors via immunohistochemical (IHC) staining, we proved that both VEGFA (Fig. 8 C,D) and CD31 (Fig. 8 E,F) were downregulated in sh-ALKBH5 U87 subcutaneous tumors, which means angiogenesis activities were impaired in sh-ALKBH5 U87 subcutaneous tumors. These findings collectively indicate that ALKBH5 plays a crucial role in promoting GBM angiogenesis through modulation of VEGFA expression.

Discussion RNA modification has become a focal point in cancer research, and while the role of ALKBH5 has been established in regulating endothelial cell angiogenesis via a SPHK1 dependent manner under ischemic stress, but the crosstalk between RNA modification and angiogenesis of GBM has been less explored. This comprehensive study systematically gathered RNA modification regulators and GBM clinical cohorts, employing various bioinformatic methods to uncover potential associations with the angiogenesis hallmark in GBMs. ALKBH5 is identified as a noteworthy RNA modification regulator linked to angiogenesis, exhibiting a significant positive association with VEGFA expression—core regulator in GBM angiogenesis. Besides, it also showed a stable and promising prognostic role in predicting the prognostic clinical GBM patients. In vitro and in vivo experiments further validated the role of intrinsic ALKBH5 in GBM angiogenesis via regulating VEGFA expression and secretion. The study employed a heuristic approach, employing GSEA, differential expression, and prognostic analysis to systematically identify hallmark-correlated RNA modification regulators, with ALKBH5 emerging as a novel player in GBM angiogenesis regulation. While ALKBH5 has been previously implicated in GBM invasion, radio-resistance, chemo-resistance and microenvironment shaping 29 – 31 , this study is the first to establish its role in angiogenesis regulation. Considering the vital function of ALKBH5 in mRNA biology, it is speculated that ALKBH5 may control the angiogenesis via direct RNA modification method or indirectly way, this point needs subsequent experiments to understand. Despite demonstrating ALKBH5's pro-angiogenesis role in GBM and establishing that down-regulation of ALKBH5 in GBM substantially reduces both in vitro and in vivo VEGFA expression and secretion, there remain several limitations that must be addressed. The first is the unclear deeper mechanism, which requires further investigation. The second point concerns the translation of research findings into clinical applications, specifically the need for additional testing to determine whether ALKBH5 inhibitors can effectively restrain GBM angiogenesis. A recent publication found ALKBH5 can facilitate the advancement and angiogenesis of lung cancer by modulating the stability of the long non-coding RNA (LncRNA) PVT1 32 , and PVT1 was also reported highly upregulated in GBM tissues and cells, and involved in GBM malignant progression 33 . This potential mechanism identified in ALKBH5-regulated GBM angiogenesis suggests a promising direction for further exploration in pursuit of our research objectives. In summary, these findings present a fresh opportunity to tackle GBM by inhibiting angiogenesis through the suppression of RNA modification, specifically targeting ALKBH5. While the present results are promising, the subsequent stages entail conducting comprehensive analyses and translating these theoretical insights into tangible applications for potential therapeutic interventions.

Despite numerous reports indicating the significant impact of RNA modification on malignant glioblastoma (GBM) cell behaviors such as proliferation, invasion and therapy efficacy, its specific involvement in glioblastoma (GBM) angiogenesis is remains unclear and is currently under investigation. In this study, we aimed to investigate the relevance between RNA modification regulators and GBM angiogenesis. Our study employed bioinformatic analyses, including Gene Set Enrichment Analysis (GSEA), differential expression analysis, and Kaplan–Meier survival analysis, to identify regulators of angiogenesis-associated RNA modification (RM). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied to identify the enrichment of angiogenesis associated signatures in ALKBH5-high expression GBMs. We also utilized Western blot to verify the upregulation of ALKBH5 in clinical GBM samples. By a series of in vitro and in vivo assays, including plasmid transfection, wound healing, transwell invasion test, tube formation, RT-qPCR, ELISA assays and xenograft mice model, we validated the angiogenesis regulation ability of ALKBH5 in GBM. The N6-methyladenosine (m6A) modification “erase” ALKBH5 emerged as a candidate regulator associated with angiogenesis, demonstrating elevated expression and robust prognostic predictive ability in GBM patients. We also revealed enrichment of vasculature development biological process in GBMs with high ALKBH5 expression. Subsequently, we validated the elevated the expression of ALKBH5 in clinical GBM and paired adjacent tissues through western blot. Additionally, we knocked down the expression of ALKBH5 using sh-RNAs in U87 GBM cells to access the angiogenesis induction ability in U87 cells. In vitro experiments, Human Umbilical Vein Endothelial Cells (HUVECs) were used to perform wound healing, transwell migration and tube formation analysis, results indicated that ALKBH5 knock-down of U87 cells could decrease the pro-angiogenesis ability of U87 GBM cells. Further validation of our bioinformatic findings confirmed that ALKBH5 knockdown impaired VEGFA secretion in both in vitro and in vivo settings in U87 cells. These results comprehensively affirm the crucial role of ALKBH5 in regulating GBM-induced angiogenesis, both in vitro and in vivo. ALKBH5 not only emerges as a promising prognostic factor for GBM patients, but also plays a pivotal role in sustaining GBM progression by promoting angiogenesis. Subject terms

Supplementary Information

Abbreviations Glioblastoma Gene set enrichment analysis N6-methyladenosine Gene ontology Kyoto encyclopedia of genes and genomes Human umbilical vein endothelial cell Overall survival Vascular endothelial growth factor N7-methylguanosine N1-methyladenosine 5-Methylcytidine 5-Methoxycarbonylmethyluridine Adenosine to inosine transition Pseudouridine Protein–protein interaction Genotype-tissue expression Differential expression genes Normalized enrichment score Normal brain tissue Gene expression omnibus Human protein atlas Biological process Molecular function Cellular component Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-51994-9. Acknowledgements All authors would like to acknowledge the open databases showed in the manuscript. Author contributions X.K. and Y.H. designed the research framework. Y.F. and D.Y. performed the bioinformatic analysis and experiments, visualized the figures, and wrote the manuscript. L.M. and G.L. helped to revise the manuscript; X.L. collected the clinical samples. All co-authors approved the version of manuscript to be published. Funding This research is supported by the National Natural Science Foundation of Shaanxi Province (Grant No. 2021SF-093). Data availability The data used in this study were public datasets, and could be obtained from the websites listed below: UCSC (TCGA-GBM cohort , https://xenabrowser.net/datapages/ ), CGGA (mRNAseq_693 and mRNAseq_325 cohorts, http://www.cgga.org.cn/ ), GEO (GSE89567, https://www.ncbi.nlm.nih.gov/gds ), GTEx (file = ”GTEx_Analysis_2017-06-05_v8_RNASeQCv1.1.9_gene_tpm.gct.gz”, https://gtexportal.org/home/ ). Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1303

oa_package/9c/0f/PMC10788339.tar.gz

PMC10788340

38221531

Introduction Pyroptosis is a lytic type of programmed cell death, which is initiated by inflammatory caspases and characterized by gasdermin (GSDM)-mediated membrane pore-formation and the release of cellular contents 1 , 2 Pyroptosis could be activated by extracellular or intracellular stimulation, including pathogen infection, inflammation, tumorigenesis, and mechanical forces, which play an important role in maintaining tissue homeostasis and activating the inflammatory responses. 3 , 4 Depending on different environmental stimuli and inflammatory caspases, pyroptosis can be divided into canonical and non-canonical types. 5 In canonical pyroptosis, inflammasomes such as Nod-like receptor protein 3 (NLRP3) activate Caspase-1 to cleave gasdermin D (GSDMD) and process pro-IL-1β into mature IL-1β. 1 In non-canonical pyroptosis, Caspase-11/4/5 is activated to cleave GSDMD upon recognition of cytosolic lipopolysaccharide, which is independent of inflammasomes and Caspase-1. 2 Orthodontic tooth movement (OTM) is an aseptic inflammatory bone remodeling process induced by mechanical force stimulation. 6 Under force stimulation, numerous inflammatory cytokines, chemokines, and increased activation of immune cells were detected in periodontal tissues. 7 – 9 Periodontal ligament (PDL) stem/progenitor cells were the main cellular components in the periodontal tissues, constantly receive force stimuli and contribute to the inflammatory responses and bone remodeling process during OTM. 10 Our previous studies have reported that the expressions of inflammatory cytokines, chemokines, and gas molecules such as hydrogen sulfide were all increased in the force-stimulated PDL stem/progenitor cells. 11 – 13 In addition, cyclic stretch could activate NLRP inflammasomes and induce the release of IL-1β via a Caspase-1-related mechanism in PDL cells in vitro. 14 However, whether and how mechanical force induces PDL stem/progenitor cell pyroptosis and thus influences OTM and alveolar bone remodeling remain unknown. Transient receptor potential (TRP) calcium channel is a classic mechanosensitive channel contributing to the transduction of mechano-signals into biological responses in various tissues and cells. 15 TRP subfamily V member 4 (TRPV4) could regulate mechano-transduction, inflammation activation, and mechanical force-induced alveolar bone remodeling. 16 Previously, we have found that TRPV4 was involved in the modulation of PDL stem cell function during OTM both in vivo and in vitro. 17 In addition, a previous study also suggested that TRPV4 could mediate airway epithelial cell pyroptosis in chronic obstructive pulmonary disease. 18 Therefore, we hypothesize that TRPV4 participates in force-induced pyroptosis in PDL progenitor cells. In the present study, we aim to illustrate whether and how mechanical force induced PDL progenitor cell pyroptosis and influenced OTM and alveolar bone remodeling. By using OTM animal models, force-induced human PDL progenitor cells ex-vivo, and a compressive force loading model in vitro, we found that mechanical force induced Caspase-1-dependent pyroptosis in PDL progenitor cells, which contributed to OTM and alveolar bone remodeling. This study shed light on a novel mechanism of OTM and indicated that targeting Caspase-1 might be a promising approach to accelerate OTM.

Materials and methods Animals and orthodontic force treatment 6–8-week-old Male Sprague Dawley rats (body weight of 200–250 g) and C57BL/6N mice were obtained from Weitong Lihua Experimental Animal Center (China), and Caspase-1 −/− mice were generated by Viewsolid Biotech (Beijing, China). They were housed in controlled animal facilities with a temperature of (23 ± 2) °C, a humidity of 40% to 65%, and a 12/12 h light/dark cycle. Animals were fed with a standard laboratory diet and allowed ad libitum access to drinking water. All animals were maintained in specific pathogen-free (SPF) cages randomly and fed a normal diet. The animal number in each group ( n = 3–6) is estimated according to our pre-experiment. 12 Humane care was provided to each animal during the experiments according to the criteria outlined in the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health. Six- to eight-week-old male Sprague-Dawley rats, C57BL/6 N mice, and Caspase-1 −/− mice were used in the study. All the protocols were approved by the Peking University Ethical Committee (LA2013-92). The study conforms to the ARRIVE guidelines. Mechanical force was applied to rats or mice as previously described. 26 Briefly, in rats, nickel-titanium coil springs of 0.2 mm in wire size, 1 mm in diameter, and 4 mm in length (Smart Technology) were ligated between the maxillary right first molar and the maxillary incisors to provide 50–60 g force for 3 d, 7 d and 14 d. 7 , 27 The maxillary left first molar without force application served as the control. Five rats were used at each time point. Another 3 rats received force application for 7 d, and the periodontal tissues including the alveolar bone and periodontal ligament of the mesial side of the maxillary first molars were collected for the detection of gene expressions. In mice, nickel-titanium coil springs with the same size and 1 mm in length were ligated in a similar way to provide 20–30 g force for 7 d. 12 , 28 , 29 The contralateral first molar served as control. Mice were randomly divided into four groups as follows: (i) Force: force loading and 0.9% NaCl treatment every two days; (ii) Force + PPVI: force loading and pyroptosis activator Polyphyllin VI (PPVI, S9302, Selleck) treatment (5 mg/kg every two days); (iii) Force + MCC950: force loading and pyroptosis inhibitor MCC950 (S7809, Selleck) treatment (20 mg/kg every two days); (iv) Control: the group without force loading and treatment. Drugs were injected intraperitoneally (i.p.). 30 , 31 Each group comprised 5 mice. In addition, force was also applied to the Caspase-1 −/− mice for 7d to compare the difference of OTM and alveolar bone remodeling with the wild-type mice ( n = 5). After OTM, the animals were sacrificed and the maxillae were harvested for micro-CT scanning and histological staining. For histological staining, consecutive horizontal sections (4 μm) were obtained from the middle to apical third of each maxillary first molar. The sections from similar position of the roots were used for histological study. Micro-CT scanning and measurement of orthodontic tooth movement (OTM) distance The animals were sacrificed by overdose of pentobarbital sodium, and the maxillae were harvested, fixed in 4% paraformaldehyde (PFA), and scanned by micro-CT system (Inveon MMCT, Berlin, Germany) at 80 kV, 500 μA, and an image voxel size of 18 μm. Mimics 13.1 software (Materialise, Leuven, Belgium) was used for 3D image reconstruction and segmentation. The distance of OTM was measured from the occlusal view of the maxillae in 3D images using a modified method described previously. 7 Briefly, the distance between the midpoint of the first molar distal-marginal ridge and the midpoint of the second molar mesial-marginal ridge was measured by a trained researcher who was blinded to the group assignment. The average of the three measurements was calculated as the tooth movement distance. Tartrate-resistant acid phosphatase (TRAP) staining TRAP staining was utilized to detect the number of osteoclasts using an acid phosphatase kit (387A-1KT; Sigma) according to the manufacturer’s protocol. The number of TRAP-positive multinucleated (>3 nuclei) osteoclasts in five visual fields at 20× magnification in each well was counted. The final results came from the average of 5 independent tests. In histological sections, the number of TRAP-positive multinucleated (>3 nuclei) osteoclasts in five visual fields at 40× magnification in each histological section was counted. The final results came from the average of 5 independent tests. Immunohistochemical staining, immunofluorescence staining For immunohistochemical staining, after mice sacrifice, the trimmed maxillae were fixed in 4% PFA for 24 h. After decalcifying in ethylenediaminetetraacetic acid for 4 weeks, the tissues were embedded in paraffin. 4-μm consecutive horizontal sections were obtained from the middle to apical third of the roots, and sections from the similar positions were chosen. Immunohistochemistry was performed with a two-step detection kit (Zhongshan Golden Bridge Biotechnology, Beijing, China) as previously described. 7 Primary antibodies included anti-GSDMD (1:200; AF4012, Affinity), anti-Caspase-1 (1:200; AF5418, Affinity), and anti-IL-1β (1:200; AF5103, Affinity). Histological changes in stained tissues were observed using an optical microscope (Olympus, Japan). The positive staining cells were counted in five different slides from each sample. Immunofluorescence staining was performed as previously described. 32 The sections were incubated with primary antibodies including anti-CD90 (1:200; ab225, Abcam), anti-GSDMD (1:200; AF4012, Affinity), anti-Caspase-1 (1:200; AF5418, Affinity), anti-IL-1β (1:200; AF5103, Affinity) to observe the numbers of Caspase-1 + CD90 + cells, GSDMD + CD90 + cells, and IL-1β + CD90 + cells in the compression side of the periodontal tissues after force loading; antibodies including anti-TRPV4 (1:200; ab39260, Abcam), anti-GSDMD (1:200; SC-393581, Santa Cruz), anti-Caspase-1 (1:200; SC-392736, Santa Cruz) were used to observe the numbers of Caspase-1 + TRPV4 + cells and GSDMD + TRPV4 + cells in the compression side of the periodontal tissues after force loading. Then, sections were incubated with fluorescein isothiocyanate-conjugated or tetramethylrhodamine isothiocyanate-conjugated secondary antibodies (1:200; Zhongshan Golden Bridge Biotechnology, Beijing, China). Nuclei were counterstained with 4′,6-diamidino-2-phenylindole (DAPI, P0131, Beyotime). Confocal images were processed with LSM 5 Release 4.2 software after acquisition by a laser-scanning microscope (LSM510; Zeiss, Germany). The cells double-stained by red and green immunofluorescence were calculated. The positively double-stained cells were counted in five different slides from each sample. The final results came from the average of 5 independent samples. Human PDL (h-PDL) progenitor cell isolation ex vivo The volunteers planning to extract four premolars due to orthodontic treatment demands were included. The h-PDL progenitor cells were isolated from the upper premolars of receiving orthodontic force for 7 d (hF7d) representing active force stimulus. 33 The h-PDL progenitor cells from the lower premolars without force loading from the same patient served as controls. Six teeth of three patients were isolated in each group ( n = 3). The clinical procedures were approved by Peking University Ethical Committee (PKUSSIRB-201311103) and informed consent was signed by the patients. Briefly, the periodontal ligament scraped from the root surface of the premolars with or without force stimuli were digested in a mixture of 3 mg/mL type I collagenase (Worthington Biochem, USA) and 4 mg/mL dispase II (Roche, Germany) for 1 h at 37 °C. The single cell suspensions were obtained and used for cell culture with a-MEM medium (Invitrogen, USA) with 20% fetal bovine serum (Gibco, USA) and 1% Penicillin/Streptomycin (Gibco, USA). When the single cell suspensions adhered to the wall for 3 days, the primary cells were digested and cultivated on the six-well plate for further experiments. Mechanical loading and treatments on human PDL progenitor cells in vitro Human PDL progenitor cells were isolated as previously described and were identified following previous protocols, 34 which used at passage 4. Compressive force loading was provided by glass layers and 50 mL plastic tube caps containing weighed metal balls as previously described. 35 , 36 1.5 g/cm 2 compressive force was applied to PDL progenitor cells for different time points (3–24 h), and different compressive force (0.5–2.0 g/cm 2 ) was applied to PDL progenitor cells for 6 h. In addition, after being subjected to 1.0 g/cm 2 and 1.5 g/cm 2 compressive force for 6 h, PDL progenitor cells were collected for further experiments of optical microscope (OM, Olympus, Japan), scanning electron microscope (SEM) and transmission electron microscope (TEM). To confirm the influence of pyroptosis under mechanical stimuli, pyroptosis activator PPVI (4 μmol/L), pyroptosis inhibitor MCC950 (10 μmol/L) and Caspase-1 inhibitor Belnacasan (VX765, 20 μM, S2228, Selleck) were added to PDL progenitor cells for 18 h in advance, then 1.5 g/cm 2 force was applied to PDL progenitor cells for 6 h. 31 , 37 In addition, TRPV4 inhibitor GSK219 (10 mmol/L, Selleck) were applied to PDL progenitor cells for 1 h and then stimulated with force loading (1.5 g/cm 2 , 6 h). 17 PDL progenitor cells without force-loaded and drug treatment served as controls. Co-culture of PBMCs and PDL progenitor cells H-PBMCs were selected from peripheral blood. The h-PDL progenitor cells of passage 1 (5 × 10 3 cells per mL) with or without orthodontic force stimuli were seeded into 24-well plates to co-cultured with h-PBMCs (1 × 10 6 cells per mL). Macrophage colony-stimulating factor (MCS-F, 30 ng/mL) and soluble receptor activator of nuclear factor–κB ligand (sRANKL, 50 ng/mL) were added to the cultured medium. After co-culturing for 14 days, cells were fixed and stained with an acid phosphatase kit (387A-1KT; Sigma) for tartrate-resistant acid phosphatase (TRAP) staining. Immunocytofluorescense staining Immunocytofluorescense staining was performed according to a previously described method. 11 Briefly, cells were fixed in 4% paraformaldehyde and permeabilized with 0.1% Triton X-100 at room temperature for 10 min. Next, the cells were incubated with 5% Bovine Serum Albumin (BSA) at room temperature for 1 h, followed by incubation with anti-CD90 (1:200; SC-53456, Santa Cruz), anti-TRPV4 (1:200; ab39260, Abcam), anti-GSDMD (1:200; AF4012, Affinity), anti-Caspase-1 (1:200; AF5418, Affinity), and anti-IL-1β (1:200; AF5103, Affinity) at 4 °C overnight. After thoroughly washed, the cells were then incubated with fluorescein isothiocyanate-conjugated or tetramethylrhodamine isothiocyanate-conjugated secondary antibodies (1:200; Zhongshan Golden Bridge Biotechnology, Beijing, China) in the dark at room temperature for 1 h. Nuclei were counterstained with DAPI (P0131, Beyotime, China). Confocal microscopic images were processed with LSM 5 Release 4.2 software after acquisition by a laser-scanning microscope (LSM510; Zeiss, Germany). The positively stained cells were counted in five different slides from each sample. Quantitative real-time polymerase chain reaction (PCR) The rat periodontal tissues included the alveolar bone and periodontal ligament were separated from the mesial side of first molars. Tissues were collected in 1.5 mL EP tube with 1 mL TRizol reagent (Invitrogen, Carlsbad, CA), and smashed for 5 min. Then tissues were centrifuged and the supernatant was collected. For PDL pregenitors in vitro, they were washed by PBS and added TRizol reagent. Total RNA was extracted from cultured cells or periodontal tissues with TRizol reagent (Invitrogen, Carlsbad, CA) following the manufacturer’s protocol. 2 μg of RNA was reverse transcribed into complementary first-strand cDNA using cDNA synthesis kits (Takara Bio, Inc., Otsu, Japan). Then real-time Polymerase Chain Reaction (PCR) was performed using the FastStart Universal SYBR Green master kit (Roche) on an Applied Biosystems 7500 real-time PCR System (Life Technologies Corporation, United States) to determine the relative mRNA expression level. Fold changes of target genes were calculated with ΔCT method using GAPDH or β-actin as a reference control. The sequences of primers were designed by Primer Premier 5.0 software and were listed as follows: Human: GAPDH sence/antisence: 5′- TGCCACTCAGAAGACTGTGG-3′/5′- TTCAGCTCTGGGATGACCTT-3′. NLRP3 sence/antisence:5′-CCACAAGATCGTGAGAAAACCC-3′/5′- CGGTCCTATGTGCTCGTCA-3′ Caspase-1 sence/antisence:5′- CGTTCCATGGGTGAAGGTACA-3′/5′- TGCCCCTTTCGGAATAACGG-3′ GSDMD sence/antisence:5′-GTGTGTCAACCTGTCTATCAAGG-3′/5′- CATGGCATCGTAGAAGTGGAAG-3′ IL-1β sence/antisence:5′- TTCGACACATGGGATAACGAGG-3′/5′- TTTTTGCTGTGAGTCCCGGAG-3′ RANKL sence/antisence:5′- ATCAGAGCAGAGAAAGCGATG-3′/5′-GACTCACTTTATGGGAACCAG-3′ OPG sence/antisence:5′- TTGAAATGGCAGTTGATTCCTTT -3′/5′- TATCCTCTTTCTCAGGGTGCTTG-3′ CTSK sence/antisence:5′-ATCCGGACTGTGACGAGTTG -3′/5′-ATTTGGGAGCAGCTGGGATG-3′ TRAP sence/antisence: 5′-ACTACCAGAAACGAGTGGGAA-3′/5′-GCATCTGTTCTCGGAAAACCT-3′ Rat: β-actin sence/antisence:5′- TGACAGGATGCAGAAGGAGA-3′/5′- TAGAGCCACCAATCCACACA-3′ Nlrp3 sence/antisence:5′- TCACGTCTTGAAGCCACATCC-3′/5′- GAAGCAAAGTTCCTCCAGACAG-3 Caspase-1 :5′- GTGGTTCCCTCAAGTTTTGC-3′/5′-CCGACTCTCCGAGAAAGATG-3′ Gsdmd sence/antisence:5′- CCAACATCTCAGGGCCCCAT-3′/5′-TGGCAAGTTTCTGCCCTGGA-3′ Il-1β sence/antisence:5′- CACCTCTCAAGCAGAGCACAG-3′/5′- GGGTTCCATGGTGAAGTCAAC-3′ Trpv1 sence/antisence:5′-GCCGCTGAACCGACTC-3′/5′-CCCATCTGCTGGAAAC-3′ Trpv2 sence/antisence:5′- CGCCATTGAGAAGAGGAGTC-3′/5′- GCTTACCACATCCCACTGCT-3′ Trpv3 sence/antisence:5′- GCGTGGAGGAGTTGGTAGAG-3′/5′- CTCTGTGTACTCGGCGTTGA-3′ Trpv4 sence/antisence:5′- CAGGTGGGGAGGCTTTT-3′/5′- GCGGCTGCTTCTCTATG-3′ Western blotting Western blottings were performed as previously described. 17 Cells were lysed with RIPA buffer (Thermo Fisher Scientific) and the total proteins were harvested. A Pierce BCA protein assay kit (Thermo Fisher Scientific) was used to perform the protein quantification. Total protein (30 μg) was separated by 10% SDS–polyacrylamide gel and then transferred onto a polyvinylidene difluoride (PVDF) membrane (Millipore). After being blocked in 5% BSA for 1 h at room temperature, the membranes were incubated overnight at 4 °C with primary antibodies including GAPDH (1:5 000, AF7021, Affinity), NLRP3 (1:1 000, PA5-79740, Thermo Fisher), Caspase-1 (1:500, AF5418, Affinity), Cl-Casp-1 (1:300, AF4005, Affinity), GSDMD and N-GSDMD (1:500, AF4012, Affinity), IL-1β (1:500, AF5103, Affinity), Cl-IL-1β (1:300, AF4006, Affinity), RANKL (1:500, AF0313, Affinity), OPG (1:500, DF6824, Affinity), TRPV4 (1:1 000, ab39260, Abcam). The blots were then incubated with a horseradish peroxidase-conjugated secondary antibody (1:5 000; Zhongshan Golden Bridge Biotechnology, Beijing, China). The membranes were washed three times with 0.1% TBS Tween (P9416, Sigma-Aldrich). The bands were detected using enhanced chemiluminescence (34577, Thermo Fisher Scientific), and BioMax film (Kodak, Rochester, New York, USA) was used to detect the immunoreactive proteins. The relative density of at least three independent results was measured by Image J software. All the western blotting results were the average of 3 independent experiments. Enzyme-linked immunosorbent assay (ELISA) RANKL and IL-1β concentrations in culture supernatants were detected by ELISA (mlbio, China) following the manufacturer’s instructions. The results were determined by comparing the samples to the standard curve generated by the kit. All samples and standards were assayed in triplicate. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) For SEM, the PDL pregenitor samples were pre-fixed in 2.5% glutaraldehyde in PBS (pH 7.4) at 4 °C for 12 h and washed with PBS three times. The samples were dehydrated in a graded series of ethanol solutions and critical-point dried, and then sputter-coated with gold for 2 min at 20 mA. The PDL pregenitor samples were observed using SEM (Hitachi S-4800, Japan) at 10 kV. For TEM, PDL pregenitors were harvested, washed three times with PBS, and fixed in 2.5% glutaraldehyde for 2 days at 4 °C. PDL pregenitors were post-fixed in 1% osmium tetroxide for 2 h. After they were dehydrated using a graded series of ethanol solutions, the samples were embedded in Embed-812 resin and cut into ultrathin sections (70 nm thick). The ultrathin sections were installed on a copper wire and stained with dioxyuranium acetate and lead citrate. These sections were examined with TEM (JEM-100CX, Japan) at 100 kV. Ca 2+ influx measurement The calcium-regulated fluorescent intracellular calcium indicator, Fluo-4 acetoxymethyl ester form (Fluo-4 AM, F8500, Solarbio, China) was used to monitor real-time elevations of intracellular calcium following force stimuli and the inhibition of TRPV4, according to the manufacturer’s instructions. Briefly, PDL pregenitors of different groups (Control, Force, Force+GSK219) were loaded with 4 × 10 −4 mol/L Fluo-4 AM fluorescent dye diluted 1/200 in Ca 2+ free Hank’s buffered salt solution (HBSS) for 60 min at room temperature. After this period, cells were washed two times with HBSS and further incubated with 300 μL of HBSS for 60 min. Cells were stained with Hoechst 33342 (C1027, Beyotime, China) in the dark for 20 min. Then, Fluo-4 AM positive cells were photographed by confocal microscopy (LSM510; Zeiss, Germany), and the images were processed using LSM 5 Release 4.2 software. Measurement of intracellular reactive oxygen species (ROS) The content of intracellular ROS was detected by the H2DCF-DA fluorescence probe (Beyotime, China) according to the manufacturer’s instructions. After that PDL pregenitors of different groups (Control, Force, Force+GSK219) were incubated with 10 mM DCFH-DA for 20 min at 37 °C in the dark, PDL pregenitors were washed twice with serum-free medium and resuspended with a-MEM medium including Hoechst 33342 (C1027, Beyotime, China). The intracellular ROS was assessed at 488/525 nm using fluorescent microscopy (Leica, Germany) and analyzed by Image-Pro Plus 6.0 software (Media Cybernetics, MD, USA). Mitochondrial morphology detection and mitochondrial membrane potential (Δψm) Mitochondrial morphology was detected by Mito-tracker dyes. Mitochondria were labeled with the MitoTracker Red (C1049B, Beyotime, China) for 30 min in the dark. The mitochondrial morphology was photographed by a confocal microscope (LSM510; Zeiss, Germany). The Δψm was analyzed using the fluorescent probe JC-1 assay kit (C2003S, Beyotime, China) according to the manufacturer’s instructions. JC-1 exhibits red fluorescence aggregates in the mitochondrial matrix in normal cells. When the Δψm is reduced, monomeric JC-1 displays green fluorescence. Therefore, the rate of green/red fluorescence was used to represent the Δψm in each cell sample. PDL pregenitors of different groups (Control, Force, and Force + GSK219) were cultured on the coverslips in 12-well plates and loaded with JC-1 (1:400 dilution) at 37 °C for 20 min. The images were observed and captured under a fluorescence microscope (Leica, Germany). Adenosine triphosphate (ATP) Assay ATP levels were measured using the ATP bioluminescence detection kit (S0026, Beyotime, China). Briefly, PDL pregenitors were lysed with a lysis buffer supplied with the kit and centrifuged at 12 000 × g for 5 min at 4 °C. The supernatant was collected for ATP detection. The protein concentration of the supernatant was measured using the BCA Protein Assay Kit (P0012S, Beyotime, China). Furthermore, 100 μL supernatant with 100 μL ATP detection buffer was measured using a microplate reader (EnSpire, USA). The standard solution was diluted in gradient to obtain the standard curve (1 nmol/L-1 μmol/L). Then, ATP levels were calculated according to standard curves and normalized according to standard protein concentrations. Statistical analysis Statistical analysis was performed with GraphPad Prism 9.0 software. Data were presented as mean ± standard deviation (SD). Statistical differences between two groups were assessed by a two-tailed independent Student’s t test, and statistical differences among three and more groups were assessed by one-way analysis of variance (ANOVA). Tukey’s multiple-comparison test was used for the post hoc comparison of ANOVA. A p -value less than 0.05 represented statistically significant.

Results Force induces PDL progenitor cell pyroptosis during OTM and alveolar bone remodeling in vivo To investigate whether mechanical force-induced pyroptosis regulates alveolar bone remodeling in vivo, a classic force-induced OTM and alveolar bone remodeling model was established. Micro-CT images showed that the OTM distance in rats gradually increased to (207 ± 17.64) μm, (350 ± 31.62) μm, and (488 ± 36.64) μm after force loading for 3 d, 7 d, and 14 d (Fig. 1a ). CD90 has been widely used as a marker for characterizing PDL progenitor cells in rats (Kon et al. 2009; Hosoya et al. 2012), as it is expressed in stem/progenitor cells (Dennis et al. 2007). Immunofluorescence showed that the number of Caspase-1 + CD90 + cells, GSDMD + CD90 + cells, and IL-1β + CD90 + cells was all increased in the compression side of the periodontal tissues after force loading for 3 d and lasted to 14 d, while force loading for 7 d triggered the strongest responses (Fig. 1b and Supplementary Fig. S1 ). The number of tartrate-resistant acid phosphatase (TRAP) + osteoclasts showed a similar trend (Fig. 1c ). However, on the tension side, the expressions of pyroptosis-related markers did not change compared with the control group (Supplementary Fig. S2 ). Moreover, after force stimulation for 7 d, the periodontal tissues from the mesial side of the first molars were collected and the expression of pyroptosis-related genes including Caspase-1 , Gsdmd and IL-1β were significantly upregulated (Fig. 1d ). Force-induced pyroptosis modulates OTM and alveolar bone remodeling in a Caspase-1 depended manner To further explore the influence of pyroptosis level on OTM, we enhanced or blocked the pyroptosis level by systemic administration of the pyroptosis activator Polyphyllin VI (PPVI) or inhibitor MCC950 in mice respectively (Fig. 2a ). After force loading for 7 d, the OTM distance was increased after PPVI injection and decreased after MCC950 injection compared with the force group (Fig. 2b ). Concomitantly, after PPVI injection, the force-induced expressions of Caspase-1, GSDMD and IL-1β were further elevated in the periodontal tissues, whereas the MCC950 injection partially reversed the expressions of pyroptosis-related markers compared with the force group. Moreover, the number of TRAP + osteoclasts increased after force application, which was further enhanced by the PPVI injection and suppressed by the MCC950 injection (Fig. 2c ). Caspase-1 was a key factor to cleave GSDMD in canonical pyroptosis, therefore we further confirm whether force-induced pyroptosis requires the activation of Caspase-1 using Caspase-1 −/− mice. After force application for 7d, the OTM distance was significantly reduced in Caspase-1 −/− mice (Fig. 3a ). Correspondingly, the expressions of Caspase-1, GSDMD, IL-1β, as well as the number of TRAP + osteoclasts were all significantly decreased in the periodontal tissues of Caspase-1 −/− mice compared with WT mice (Fig. 3b ). These data suggest that mechanical force could induce Caspase-1-dependent pyroptosis, which further contributed to the OTM and alveolar bone remodeling. In addition, the Caspase-1 inhibitor Belnacasan (VX765) was also injected into mice every other day during the force-induced tooth movement process. After VX765 injection, the tooth movement distance decreased significantly compared to the Force group (Fig. 3c ). Moreover, the force-induced upregulated expressions of Caspase-1, GSDMD, and IL-1β were partially reversed, as well as the number of TRAP + osteoclasts (Fig. 3d ). Mechanical force induces pyroptosis in human PDL progenitor cells and influences osteoclastic activity PDL stem/progenitor cells are the main cells responding to mechanical force and contributing to OTM, therefore we further detect whether mechanical force induces pyroptosis in PDL progenitor cells under force stimuli. Firstly, the expression of pyroptosis-related markers in ex-vivo h-PDL progenitor cells isolated from the same patients with or without force loading were detected (Fig. 4a ). The protein expression of pyroptosis-related markers including NLRP3 inflammasomes, cleaved Caspase-1 (Cl-Casp-1), GSDMD, cleaved GSDMD (N-GSDMD), as well as IL-1β and cleaved IL-1β (Cl-IL-1β), were all significantly increased in h-PDL progenitor cells with force application for 7 d (hF7d group) (Fig. 4b ). The mRNA expressions of pyroptosis-related genes showed the same trend (Supplementary Fig. S3a ). To verify the relationship between PDL progenitor pyroptosis and osteoclastic activity, ex-vivo h-PDL progenitor cells with or without orthodontic force pretreatment were co-cultured with peripheral blood mononuclear cells (PBMCs). The protein expression of RANKL significantly enhanced in the hF7d group, whereas OPG expression remained unchanged (Fig. 4c and Supplementary Fig. S3b ). Correspondingly, the gene expressions of RANKL and RANKL/OPG ratio were upregulated in the hF7d group (Fig. 4d ). Moreover, the secretion of RANKL also increased detected by ELISA (Fig. 4e ). In addition, the number of TRAP + osteoclasts increased significantly in the hF7d group (Fig. 4f ), and the mRNA expression of Cathepsin K ( CTSK )) and TRAP also increased significantly in osteoclasts (Fig. 4g ). These data indicated that mechanical force induced pyroptosis in human ex-vivo PDL progenitor cells and influenced osteoclastic activity. In addition, compressive force was further applied to PDL progenitor cells in vitro. Western blotting revealed that under 1.5 g/cm 2 force stimuli, the expression of pyroptosis-related proteins increased from 3 h and lasted to 24 h, which reached to the peak at 6 h (Fig. 4h , and Supplementary Fig. S4a ). In addition, under different force stimuli for 6 h, the protein expression of pyroptosis-related markers increased from 0.5 g/cm 2 and reached to the peak at 1.5 g/cm 2 or 2.0 g/cm 2 . (Fig. 4i and Supplementary Fig. S4b ). Correspondingly, real-time PCR showed the similar trends (Supplementary Fig. S4c, d ). Notably, no significant change in the Caspase-5 expression was detected after force stimulation, indicating that force induced the Caspase-1-dependent canonical type of pyroptosis instead of the noncanonical type (Supplementary Fig. S4f ). The pyroptotic morphology of swollen and flat cells with blurred cellular contour and large bubbles were observed in optical microscope (OM) images. Moreover, scanning electron microscope (SEM) and transmission electron microscope (TEM) images showed multiple pores in the membranes of PDL progenitor cells under 1.0 g/cm 2 force stimulation, and more obvious membrane disruption, cell swelling, and lysis were observed under 1.5 g/cm 2 force stimulation (Fig. 4j and Supplementary Fig. S4e ). Overall, these findings revealed that mechanical force induced pyroptosis in PDL progenitor cells both in vivo and in vitro. Regulation of PDL progenitor cell pyroptosis influences osteoclastic activity Pyroptosis activator PPVI and inhibitor MCC950 were also utilized to treat force-loaded PDL progenitor cells in vitro. Western blotting analysis revealed that force increased the expression level of pyroptosis-related proteins, including NLRP3, Caspase-1, Cl-Casp-1, and the downstream GSDMD, N-GSDMD, IL-1β, and Cl-IL-1β. These protein expression levels were further enhanced after PPVI application and partially suppressed after MCC950 application (Fig. 5a and Supplementary Fig. S5a ). Moreover, the immunofluorescence images also showed that the numbers of GSDMD + CD90 + cells, Caspase-1 + CD90 + cells, and IL-1β + CD90 + cells were all increased after the PPVI application and decreased after the MCC950 application compared to the Force group (Fig. 5b ). Furthermore, the ratio of RANKL/OPG was upregulated after PPVI application and downregulated after MCC950 application compared to the Force group (Fig. 5c and Supplementary Fig. S5b ). Real-time PCR also showed the same trend (Fig. 5d ). Moreover, ELISA showed that the secretion of RANKL increased after PPVI application and decreased after MCC950 application compared with the force group (Fig. 5e ). In addition, the Caspase-1 inhibitor Belnacasan (VX765) was further utilized to treat force-loaded PDL progenitor cells in vitro. VX765 application reduced the force-induced pyroptosis-related protein expressions of NLRP3, Caspase-1, Cl-Casp-1, GSDMD, N-GSDMD, IL-1β, and Cl-IL-1β compared to the Force group (Fig. 6a and Supplementary Fig. S6a ). In addition, the immunofluorescence images also showed that the numbers of Caspase-1 + CD90 + cells, GSDMD + CD90 + cells, and IL-1β + CD90 + cells were all decreased after VX765 application compared to the Force group (Fig. 6b ). Moreover, the application of VX765 significantly reversed the upregulated protein expression of RANKL and RANKL/OPG ratio (Fig. 6c and Supplementary Fig. S6b ). Similar results were found in their gene expression levels (Fig. 6d ). Moreover, the secretion of RANKL was also decreased after VX765 application compared with the force group by ELISA (Fig. 6e ). Taken together, these data suggest that force-induced pyroptosis in PDL progenitor cells required the activation of Caspase-1, which further contributed to the osteoclastogenesis. TRPV4 signaling is involved in force-induced pyroptosis in PDL progenitor cells TRPV channels could induce biological cellular responses under mechanical stimulation. Western blotting and immunofluorescence staining showed that the expression of TRPV4 was enhanced in ex-vivo h-PDL progenitor cells in the hF7d group (Fig. 7b ). In rat OTM models, the number of Caspase-1 + TRPV4 + cells and GSDMD + TRPV4 + cells increased from F3d to F7d and F14d (Fig. 7c and Supplementary Fig. S7 ). In addition, real-time PCR of the rat periodontal tissues after force application for 7 d showed that Trpv4 increased significantly, whereas no significant difference was detected on Trpv1-3 (Supplementary Fig. S8a ). Moreover, force-induced increased expression of pyroptosis-related markers was partially suppressed after application of a TRPV4 inhibitor GSK2193874 (GSK219) (Fig. 7d ). TRPV4 regulates numerous cellular functions through intracellular Ca 2+ influx. Therefore, we hypothesized that TRPV4 regulates PDL progenitor cell pyroptosis through Ca 2+ influx, which further induces reactive oxygen species (ROS) elevation and mitochondrial damage. Immunofluorescence staining of Fluo 4 and H2DCF-DA showed that force increased Ca 2+ influx and intracellular ROS in PDL progenitor cells, which were blocked by the application of GSK219 (Fig. 7e ). TEM and mito-tracker dyes showed that mitochondria were swollen and fragmented in force-treated PDL progenitor cells. After GSK219 application, mitochondrial morphology tended to be normal (Fig. 7e ). The functional consequences of force-induced morphological changes in the mitochondria including decreased mitochondrial membrane potential detected by JC-1 and impaired ATP production were reversed after GSK219 application (Fig. 7e , and Supplementary Fig. S8b, c ). In sum, these findings demonstrated that TRPV4 signaling plays an important role in regulating force-induced Caspase-1-dependent pyroptosis in PDL progenitor cells (Fig. 7a ).

Discussion Pyroptosis plays a vital role in activating inflammatory responses under mechanical stimuli. However, whether and how force induces PDL progenitor cell pyroptosis, thereby influencing OTM and alveolar bone remodeling is unclear. In this study, we revealed a novel mechanism that mechanical force induced pyroptosis in periodontal tissues and PDL progenitor cells, which further promoted OTM and alveolar bone remodeling. The functional role of the force-induced pyroptosis depended on Caspase-1 and activated the TRPV4 signaling. The role of pyroptosis has been primarily studied in phagocytes, which is initiated by inflammatory caspases and leads to GSDMD-induced pore formation and cleavage of pro-inflammatory cytokine IL-1β. 19 Recently, pyroptosis was also observed in the inflammatory-related diseases including arthritis, myocarditis and bacterial-induced periodontitis. 20 – 22 OTM is an aseptic inflammatory reaction and alveolar bone remodeling process activated by mechanical stimuli, characterizing by bone resorption in the compression side and bone apposition in the tension side. 6 , 9 We previously found that during OTM, various inflammatory cytokines, chemokines, and the activations of immune cells were detected. 7 , 8 However, the underlying mechanism has not been explored. In this study, we revealed that mechanical force could induce Caspase-1-dependent pyroptosis in PDL progenitor cells, which contributes to OTM and alveolar bone remodeling. Previous studies have found that cyclic stretch could induce pyroptosis in PDL cells. 14 , 23 Consistent with the previous findings, the present study shows a novel finding that mechanical force could induce pyroptosis in PDL progenitor cells, which contributes to OTM and alveolar bone remodeling. Nevertheless, the activation of osteoclastic activity by pyroptosis may influence root resorption, which needs further investigation in future studies. Depending on different environmental stimuli, pyroptosis can be divided into canonical and non-canonical types. In canonical pyroptosis, NLRP3 inflammasomes bind to Caspase-1 and activate Cleaved-Casp-1 to cleave GSDMD and execute pyroptosis via pore-forming activity. 2 In non-canonical pyroptosis, Caspase-11/4/5 was activated to cleave GSDMD upon recognition of cytosolic lipopolysaccharide (LPS), which is independent of inflammasomes and Caspase-1. 24 Force-induced OTM was an aseptic inflammatory reaction, which was different from LPS-induced inflammatory process. 9 In this study, we confirmed that force-induced pyroptosis required the activation of Caspase-1. Caspase-1 −/− mice showed reduced expressions of pyroptosis markers and decreased number of TRAP + osteoclasts compared with WT mice. Consistently, blocking the Caspase-1 level by the application of Caspase-1 inhibitor VX765 also decreased the expressions of pyroptosis-related markers in PDL progenitor cells and the ratio of RANKL/OPG compared with the force group. These results suggest that Caspase-1-dependent pyroptosis contribute to force-induced OTM and alveolar bone remodeling. So far, how mechanical force induced pyroptosis remains unclear. TRPV4, a typical mechanosensitive channel, is associated with force-induced alveolar bone remodeling processes. 16 , 17 Our previous study found that TRPV4 was activated in force-induced PDL progenitor cells, which contributed to the modulation of PDL progenitor cells function and regulated alveolar bone remodeling. 17 Interestingly, TRPV4 was recently reported to be involved in some pyroptosis-related diseases. 18 In this study, we showed that TRPV4 activation under mechanical force contributed to the induction of Caspase-1-dependent canonical pyroptosis in PDL progenitor cells. Inhibiting TRPV4 could suppress the expressions of pyroptosis-related markers, decrease force-induced Ca 2+ influx, suppresse ROS expression, and reverse the repression of mitochondrial membrane potential and mitochondrial damage induced by force. The phenomenon that the pyroptosis genes remain upregulated in ex vivo PDL progenitor cells is very interesting. Previous studies have found that external stimulus including stress, nutrients and pathogens could trigger transcriptional memory in many cells, which was defined as a phenomenon that transient gene activation by a variety of external signals results in a heritable primed state that is maintained in the absence of active transcription. 25 Our previous study has also demonstrated that mechanical force in vivo could change the characteristics of rat primary PDL progenitor cells including promoting their proliferation, pro-inflammatory cytokine expression and immunoregulation. 17 In this study, increased expressions of pyroptosis related markers were detected in ex-vivo human PDL progenitor cells with force stimuli, which is consistent with the previous findings. The mechanism of how the PDL progenitor cells possess stimulus memory needs our further exploration. In summary, these data indicate that mechanical force induces Caspase-1-dependent pyroptosis in PDL progenitor cells in rat, mice and human models. This Caspase-1-dependent pyroptosis contributes to OTM and alveolar bone remodeling (Fig. 8 ). This study provides a novel insight into the modulation of osteoclastogenesis under mechanical stimuli. It suggests that targeting Caspase-1-dependent pyroptosis may be a promising strategy to accelerate OTM.

Pyroptosis, an inflammatory caspase-dependent programmed cell death, plays a vital role in maintaining tissue homeostasis and activating inflammatory responses. Orthodontic tooth movement (OTM) is an aseptic force-induced inflammatory bone remodeling process mediated by the activation of periodontal ligament (PDL) progenitor cells. However, whether and how force induces PDL progenitor cell pyroptosis, thereby influencing OTM and alveolar bone remodeling remains unknown. In this study, we found that mechanical force induced the expression of pyroptosis-related markers in rat OTM and alveolar bone remodeling process. Blocking or enhancing pyroptosis level could suppress or promote OTM and alveolar bone remodeling respectively. Using Caspase-1 −/− mice, we further demonstrated that the functional role of the force-induced pyroptosis in PDL progenitor cells depended on Caspase-1. Moreover, mechanical force could also induce pyroptosis in human ex-vivo force-treated PDL progenitor cells and in compressive force-loaded PDL progenitor cells in vitro, which influenced osteoclastogenesis. Mechanistically, transient receptor potential subfamily V member 4 signaling was involved in force-induced Caspase-1-dependent pyroptosis in PDL progenitor cells. Overall, this study suggested a novel mechanism contributing to the modulation of osteoclastogenesis and alveolar bone remodeling under mechanical stimuli, indicating a promising approach to accelerate OTM by targeting Caspase-1. Subject terms

Supplementary information

Supplementary information The online version contains supplementary material available at 10.1038/s41368-023-00268-7. Acknowledgements We thank Dr. S.C. for providing Caspase-1 −/− mice. This work was supported by the National Natural Science Foundations of China No. 82230030, No. 81871492 (Y.L.) and No. 82170996 (D.H.), Beijing International Science and Technology Cooperation Project No. Z221100002722003 (Y.L.), Beijing Natural Science Foundation No. L23002, No. L234017 (Y.L.), Ten-Thousand Talents Program No. QNBJ2019-2 (Y.L.), Key R & D Plan of Ningxia Hui Autonomous Region No. 2020BCG01001 (Y.L.), Innovative Research Team of High-level Local Universities in Shanghai No. SHSMU-ZLCX20212402 (Y.L.). Author contributions L.C. contributed to conception, design, data acquisition and interpretation, performed all statistical analyses, drafted and critically revised the manuscript; H.Y., Z.L., Y.W., S.J., M.Y., L.Z., C.D., X.W., T.W., C.X., Y.Z., contributed to data acquisition and analysis, critically revised the manuscript; D.H., Y.L. contributed to conception, design, data acquisition and interpretation, drafted and critically revised the manuscript. All authors gave their final approval and agree to be accountable for all aspects of the work. Data availability All data associated with this study are presented in the paper. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Int J Oral Sci. 2024 Jan 15; 16:3

oa_package/91/05/PMC10788340.tar.gz

PMC10788341

38221519

GJA1 is the causative gene for oculodentodigital dysplasia (ODDD). A novel de novo GJA1 variant, NM 000165:c263C > T [p.P88L], was identified in a mosaic state in a patient with short stature, seizures, delayed myelination, mild hearing loss, and tooth enamel hypoplasia. Although the patient exhibited severe neurodevelopmental delay, other clinical features of ODDD, including limb anomalies, were mild. This may be due to differences in the mosaic ratios in different organs. Subject terms

Oculodentodigital dysplasia (ODDD [MIM: 164200]) is characterized by multiple congenital anomalies 1 . The major clinical features include (1) distinctive facial findings, including a thin nose with hypoplastic ala nasi, small anteverted nares, prominent columella, and microcephaly; (2) eye findings, such as microphthalmia and glaucoma; (3) syndactyly, typically digital malformation, including bilateral complete syndactyly of digits 4 and 5 (type III syndactyly), camptodactyly, and permanent joint flexion of the digits; (4) teeth anomalies and enamel hypoplasia; and (5) cardiac dysfunctions 2 – 4 . Some patients exhibit dysplastic ears and conductive hearing loss 5 , 6 . Various neurological symptoms, including dysarthria, spastic paraparesis, ataxia, and seizures, occur in ~30% of patients with ODDD 7 – 10 . ODDD is a genetic disorder inherited as an autosomal dominant trait. In 2003, connexin-43 (gap junction protein alpha 1; GJA1 ) [MIM*121014] on chromosome 6q22 was identified as the gene responsible for this condition 11 . Recently, we identified a novel GJA1 variant in an undiagnosed patient with a neurodevelopmental disorder; however, the variant was identified as mosaic. The details of this study are as follows. The patient was a 5-year-old Japanese girl who was the third child of healthy parents. She was born at 37 weeks and 6 days of gestation by vaginal delivery in the cephalic position without any abnormalities. Her birth weight was 2738 g (25–50th centile). Her parents noticed that she showed her eye movements pursuing moving objects but showed no social smiles at 2 months of age. At 12 months of age, she was referred to our hospital because of developmental delay with no acquisition of a sitting position. On admission, her vital signs were normal, and no cardiac arrhythmias were detected. She displayed a flat nasal bridge and bilateral epicanthus. Very mild webbing was observed between her fingers and toes, except between the first and second fingers and toes. Camptodactyly was also noted in both the fingers and toes. No abnormalities were observed in the skull bone. Neurological examination revealed deep tendon hyperreflexia but no evidence of extrapyramidal signs. Hypotonia or muscle weakness was not observed. An auditory brainstem response revealed mild hearing loss in the left ear. Cranial computed tomography showed bilateral basal ganglia calcifications (Fig. 1a ). Brain magnetic resonance imaging revealed mild dilatation of the extracerebral space and lateral ventricles. Delayed myelination of the subcortical white matter and a thin corpus callosum were also observed (Fig. 1b–d ). At the age of 2 years, the patient experienced her first epileptic seizure. Electroencephalography revealed focal epileptic discharges in the right frontal lobe, and zonisamide was prescribed. She can currently hold a sitting position but has difficulty walking. She does not speak meaningful words but can communicate through babbling and eye contact, indicating severe neurodevelopmental delay. She can eat orally but needs assistance. The erupted lower anterior teeth are fused and have weak enamel. No visual loss or visual field defects were observed. The intelligence scale test showed that her developmental quotient was <20. At present (5 years of age), her height is 97.5 cm (<3rd centile), her weight is 14.1 kg (3rd~10th centile), and her occipitofrontal circumference is 49.5 cm (25–50th centile), indicating short stature. For precise diagnosis, this patient was enrolled in the research project “Initiative on Rare and Undiagnosed Disorders” 12 , which was performed in accordance with the Declaration of Helsinki and approved by the ethics committee of our institution. After informed consent was obtained from the family, blood samples were collected from the patient and her parents. Genomic DNA was extracted from peripheral blood samples following a standard protocol, and exome sequencing was performed using trio samples, including parental samples, as previously described 13 . GATK HaplotypeCaller was used for variant calling ( https://www.broadinstitute.org/ ). The results revealed a de novo variant of GJA1 (NM 000165:c263C > T [p.P88L]). This variant is not included in the gnomAD or ClinVar databases. CADD_phred was 28.2, and the MutationTaster_score was 1, suggesting that the variant is damaging. According to the ACMG/AMP guidelines 14 , four scores (PS2, PM2, and PP3) were adaptive. Thus, this variant was classified as “likely pathogenic”. The identified variant was analyzed using Sanger sequencing. Because there are many homologous genes with similar nucleotide sequences to GJA1 , PCR primer sets (3′-TTGTCTCTTTGTTTCTTTCAG-5′ and 3′-GTACCACTGGATCAGCAAGAA-5′) were designed at unique sequence sites. For PCR amplification, we used GoTaq® (Promega, Madison, WI). As shown in Fig. 2a , neither of the parents showed p.P88L, and de novo occurrence was confirmed; however, the peak of the minor variant in the patient was lower than that in the wild-type, suggesting the possibility of mosaicism. The read depth of the variant was retrospectively checked, and the read ratio of the minor allele was 8/59 (no contradiction for mosaic status). In this study, GATK HaplotypeCaller was used for variant calling. GATK HaplotypeCaller uses probability calculations to determine whether a variant is heterozygous, homozygous, or wild-type homozygous, even if the proportion of variant reads at depth is less than half. This explains why even a mosaic variant at a low depth could be detected. To confirm the mosaicism ratio, the PCR products were subcloned and inserted into a pGEM-T Vector® (Promega) and transformed into E. coli . After transformation, colonies were selected on ABPC-supplemented agar culture medium. The plasmids were extracted from each colony and sequenced. Finally, a minor variant was found in 7 out of 34 colonies (Fig. 2b ), indicating that the estimated mosaicism rate in lymphocytes was 41%. Previously, 77 GJA1 variants have been reported in patients with ODDD or erythrokeratodermia 4 , 6 , 15 – 23 . These findings have been reported in a wide range of medical fields, including pediatrics, dermatology, dentistry, ophthalmology, and orthopedics. This is due to the wide variety of clinical symptoms and severity of this disease, as connexin-43 is pleiotropically expressed in many tissues and regulates intercellular signaling. As shown in Table 1 , the present patient exhibited most of the possible clinical findings in ODDD, such as camptodactyly, enamel hypoplasia, hearing loss, and neurological findings. In particular, abnormal brain imaging, including brain calcification, is not rare in patients with ODDD 7 , 17 . On the other hand, a thin nose and hypoplastic alae, the typical facial findings of ODDD, were not observed. Syndactyly, one of the major findings of ODDD, was also not observed; however, ODDD cases without syndactyly are not rare, and the webbed fingers identified in the present patient were considered to be the consequence of incomplete syndactyly. Therefore, we diagnosed the present patient as having ODDD. Although arrythmia and ocular involvement were not observed, the development of these findings is dependent on the clinical course and may appear in the future. Therefore, careful clinical follow-up is important for this patient. GJA1 consists of four transmembrane domains, two extracellular loops, and exposed amino- and carboxyl-termini in the cytoplasm 15 . The p.P88L variant identified in this study is located in one of the transmembrane regions. As shown in Supplementary Fig. 1 , most variants in the transmembrane regions are related to ODDD. There were some variants in the region neighboring p.P88L. p.S86Y was identified as a de novo variant in a patient with ODDD 19 who was first diagnosed with syndactyly and later developed distinctive facial findings and ophthalmological involvement. Psychomotor development was mildly delayed. p.T89I was identified in a familial case of syndactyly with no neurological features 21 . In contrast, the present patient showed severe neurodevelopmental delay but very mild signs of syndactyly (mild webbing of fingers and toes). This may be due to the mosaicism in the present patient. Mosaicism is known to produce atypical or attenuated clinical symptoms due to masking by normal cells 24 . Therefore, we hypothesized that different mosaic ratios in different organs may contribute to the differences in severity of the clinical features in the present patient. Patients with ODDD who exhibit neurological features as the main finding, but mild syndactyly may not be rare. By applying comprehensive genetic analysis, the existence of such atypical cases has become apparent, and the disease concept is being expanded. HGV Database The relevant data from this Data Report are hosted at the Human Genome Variation Database at 10.6084/m9.figshare.hgv.3354. Supplementary information

Supplementary information The online version contains supplementary material available at 10.1038/s41439-023-00262-9. Author contributions T.Y. designed this study. R.S. was involved in organizing this study and drafting the manuscript. T.Y., K.I., M.S., T.S., K.I., and S.N. contributed to the acquisition of clinical data. K.S.Y., M.N., Y.I., Y.M., and Y.A. contributed to the acquisition of genomic data. All the authors contributed to the analysis and interpretation of the data. All the authors agree to be accountable for all the aspects of the work and ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Funding This work was supported by the Initiative on Rare and Undiagnosed Diseases (Grant Number 22ek0109549) from the Japan Agency for Medical Research and Development (AMED); Grants-in-Aid for Scientific Research from Health Labor Sciences Research Grants from the Ministry of Health, Labor, and Welfare, Japan (22FC1005); and Grants-in-Aid for Scientific Research (KAKENHI) from the Japan Society for the Promotion of Science (JSPS) (Grant Number 21K07873). Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Hum Genome Var. 2024 Jan 15; 11:2

oa_package/b5/2b/PMC10788341.tar.gz

PMC10788342

38221517

Introduction Medicinal plants are high in phytochemicals and antibacterial compounds. Various medicinal plant components are harvested for their diverse therapeutic properties 1 . Medicinal plants have been utilized in folk medicine in Saudi Arabia and the rest of the Arabian Peninsula throughout the dawn of time to cure a variety of ailments 2 . This region has a collection of wild medicinal plants, making it a natural reservoir, and accounts for around 27% of the flora that has been documented to be medicinally valuable 3 , 4 . Rhazya stricta Decne is a perennial evergreen dwarf poisonous shrub with a smooth central stem and thick semi-erect branches that belongs to the Apocynaceae family and is extensively found in the Middle East and Indian subcontinent 5 . R. stricta thrives in depressions with silty and sandy soils, establishing a pure stand at times. It also grows in rocky terrain, hills, plains, and wadis. R. stricta is found in the sandy plains of Saudi Arabia 5 , 6 . Plants in this family are widely recognized for their unique array of terpenoid indole alkaloids with different biological activity, as well as flavonoids, glycosides, triterpenes, and tannins 6 . R. stricta has been used to treat a variety of ailments, including fever and chronic rheumatism 7 . Indole alkaloids have several biological actions, including anticancer, antibacterial, and antihypertensive effects, as well as being central nervous system stimulants 8 . The existence of 20 monomeric terpenoid indole alkaloids with molecular weights ranging from 278 to 354 was discovered in R. stricta hairy root extracts. These included aspidospermine, eburnamine, aspidospermatin, pleiocarpaman, strychnos, sarpagine, heteroyohimbine, yohimbinoid, and hunterburine alkaloids. According to GC–MS analysis, eburenine is the most abundant alkaloid in the hairy roots and leaves of R. stricta 9 . Maladies of plants that spread through seeds are known as seed-borne diseases. One of the major culprits is seed-borne fungus. They may reduce seed germination, weaken germs, negatively impact freshly growing plants, and taint the soil 10 . Wheat seed-borne diseases are caused by harmful types of fungi, such as Alternaria alternata, Cladosporium herbarum, Drechslera sorokiniana , and Drechslera tetramera , which can cause yield losses if not treated 11 . Other phytopathogenic fungi transmitted through soil (soil-borne fungus), such as Macrophomina phaseolina , have been shown to infect over 500 plant species. These pathogens cause various diseases, including stem and root rot, charcoal rot, and seedling blight 12 . The unregulated and random use of pesticides in agriculture caused several environmental issues, including pollution of water, soil, animals, and food, as well as the unintended extermination of non-target species and phytopathogens 13 . As a result, alternative methods for controlling plant disease and minimizing the harmful effects of synthetic fungicides have been developed, including biological control through the use of natural compounds having antimicrobial properties. This includes the use of medicinal plant extracts and essential oils 14 . Because of their unique optical, magnetic, electrical, and chemical capabilities, nanoparticles have been employed in a wide range of applications, including solar cells, photovoltaic devices, heterogeneous catalysts, and medicine 15 . Nanoparticles have the potential to saturate and stick to the surface of fungal hyphae, preventing harmful fungi from growing 16 . Because of the stabilizing factors that easily allow nanoparticles to connect with other biomolecules and increase their interactions with bacteria, biologically generated nanoparticles have higher antimicrobial efficacy 17 . Biogenic silver nanoparticles (AgNPs), for example, had more antibacterial activity than chemically generated nanoparticles 18 . By interacting with proteins and enzymes, AgNPs can induce persistent cell damage by disrupting the electron transport chain, resulting in membrane permeability barrier disruption 19 . Examples for the biogenic activities of biosynthesized AgNPs from different plants extracts highlighted their antimicrobial, anticancer, and apoptosis inducing ability. For example, a pervious study showed that AgNPs synthesized from the Lagerstroemia speciosa (L.) Pers. flower buds had antimicrobial activity against Staphylococcus aureus , Escherichia coli , Candida albicans , and Candida glabrata , besides, its significant anticancer activity against MG-63 cells of Osteosarcoma 20 . Another study used AgNPs bio-fabricated from the aqueous extract of Ixora brachypoda leaves and showed antifungal activity against Bacillus subtilis, Pseudomonas aeruginosa, E. coli, S. aureus, C. albicans, Fusarium oxysporum, and A. alternata 21 . So, the current work attempted to evaluate the antifungal capabilities of AgNPs biosynthesized from R. stricta aqueous extract and its alkaline fraction against certain plant pathogenic fungi. Drechslera halodes, D. tetramera, M. phaseolina, A. alternata, and Curvularia australiensis were the species evaluated.

Materials and methods Plant collection Fresh leaves of R. stricta were obtained from the desert surrounding Riyadh, Saudi Arabia (latitude: 24°56′52" N, longitude: 45°42′37" E). The plant was identified at the Botany and Microbiology Department of the College of Science at King Saud University in Riyadh, Saudi Arabia, according to the Morphology Characteristics 42 . Experimental research on plant, including the collection of plant material, comply with the international guidelines and the Nagoya Protocol of the Convention on Biological Diversity (CBD), available from: https://www.cbd.int/doc/legal/cbd-en.pdf . Fungi species In the current investigation, five fungus species were examined. The species were obtained from the American Type Culture Collection (ATCC) in Manassas, Virginia, USA. D. halodes (ATCC, 34172), D. tetramera (ATCC, 18957), M. phaseolina (ATCC, 64333), and A. alternata (ATCC, 66981) were among those identified. As previously reported 43 , C. australiensis was acquired and identified by the Botany and Microbiology Department, College of Science, King Saud University, Riyadh, Saudi Arabia. These strains were all cultivated in petri plates using 5.7% potato dextrose agar (PDA). The strains were either stored at 4 °C or sub-cultured once a month until they were used. Preparation of plant extracts The leaves aqueous extract was made in the same manner as previously described 44 . Leaves were cleansed with distilled water, then shade-dried before being ground into a fine powder. 10 g were steeped in 100 ml distilled water and heated until ebullition occurred. Before filtering using Whatman filter paper No. 1, the three aqueous extracts were combined and filtered through muslin cloth. The filtrate was vacuum distilled at reduced pressure at 50 °C using a Rotavapor ® R-300 (BÜCHI Labortechnik AG, Flawil, Switzerland) to remove water. The filtrate was concentrated and lyophilized, yielding an aqueous extract with approximately 40 g of dark brown residue. The alkaline fraction of R. stricta was created in the same way as it was reported earlier 45 . The residue of R. stricta filtration using Whatman filter paper was removed and filtered with 100 cc of 0.15 M NaOH at 80 °C for 30 min. To obtain the alkaline residue extract, the filtrate was neutralized with HCl, condensed, and lyophilized. Preparation of AgNPs AgNPs were prepared as previously described by Shaik and colleagues (2018), with minor adjustments 46 . In brief, the R. stricta aqueous extract or alkaline fraction was combined, separately, in a 1:9 ratio with silver nitrate AgNO 3 (1 mM). The mixture was gently boiled at 90°C with a magnetic stirrer (VELP scientica Srl, Usmate, Italy). During that phase, a dropper was used to add roughly 5 ml of 1N sodium hydroxide (NaOH) to the mixture, and the yellow hue of the liquid turned dark brown. The reaction was halted at that moment, and after cooling, the mixture was spun at 9000 rpm for 30 min, yielding a black precipitate. The filtrate was gently withdrawn, and the black residues were separated for manufacture of aqueous extract AgNPs (Aq. AgNPs) or Alkaline Aq. AgNPs. The precipitates were washed twice with deionized water, dried for 12 h at 80 °C, and kept at 4 °C for future use. Characterization of AgNPs UV–visible (UV–Vis) spectroscopy A Shimadzu UV–visible spectrophotometer (Tokyo, Japan) was used. The reduction of pure Ag + ions was measured at UV-245 double-beam (200–800 nm) according to the manufacturer's recommendations 44 , 47 . Fourier-transform infrared spectroscopy (FTIR) The infrared absorption and emission spectra of the macromolecules detected in the prepared test samples were measured using FT-IR spectroscopy 19 . The FTIR spectra of each produced nanoparticle were measured using a Nicolet 6700 FTIR spectrometer (Thermo Scientific, Waltham, MA, USA) with an absorption range of 400–4000/cm. The functional groups contained in each nanoparticle were identified via FTIR analysis. The spectrometer (Nicolet 6700) has a beam splitter and a detector (DTGS) with OMNIC software that was used to gather and analyze the spectra in the 400 to 4000/cm scan. As specified in the manufacturer's instructions, the IR spectra obtained were utilized to interpret the functional moieties contained in each biogenic AgNPs 22 . Zeta potential analysis The average hydrodynamic diameter of the biogenic AgNPs was determined using Dynamic Light Scattering (DLS) analysis in this work. In this case, the Zeta sizer instrument (Malvern Instruments Ltd., zs90, Worcestershire, UK) was used to determine the zeta potential value and hydrodynamic diameter of AgNPs, as directed by the manufacturer 22 , 48 . Transmission electron microscopy (TEM) A Transmission Electron Microscope (model JEOL JEM-1011, Peabody, MA, USA) was used to investigate the form and particle size distribution of the biosynthesized AgNPs. Each test sample was put in an 8-L container on a 300-mesh carbon-coated copper grid. Images were captured at an acceleration voltage of 200 kV 19 , 48 . Assessment of the antifungal activity The poison plate method was used to assess the antifungal properties of R. stricta and biosynthesized AgNPs 49 . Four concentrations of crude aqueous extract (0, 5, 10, and 20% (w/v)) were made, whereas five concentrations of biosynthesized AgNPS (0, 25, 50, 75, and 100% (w/v)) were prepared. At a concentration of 53%, Previcur Energy (SL-840, Bayer Crop Science Ltd., Dublin, Ireland), a multi-site, broad-spectrum fungicide (Propamocarb) formulated to protect plants from many infectious diseases 50 , was employed as a positive control. 1 ml of each treatment was made in distilled water and filtered using a 0.45 m bacterial filter (MF-Millipore, Sigma-Aldrich, St. Louis, MO, USA). Then, 1 ml of each filtrate was gently mixed with 19 ml of the molten PDA and placed into a 60 cm 2 Petri plate. For each concentration and species, a single plate was created. After solidification, a mycelial plug (6mm) of each of the tested fungus, none-days old, was centered in each plate in a sterile laminar flow cabinet. The cultures were incubated at 25 °C in dark. All tests were carried out in triplicate. The suppression of mycelial growth was estimated as follows: where C represents the colony diameter in the control plate and T represents the colony diameter in the treated petri plates. Detection of the ultrastructural alterations in the treated species The morphological and ultrastructure characterization of selected fungal growth in response to treatment with aqueous R. stricta extract and biosynthesized AgNPs was investigated. Light microscopy According to the manufacturer's instructions, the ECLIPSE Ni-E light microscope augmented with an F-mount camera with a digital sight of 50M (NIKON Corp., Tokyo, Japan) was employed here. A sterile spatula was used to take a disc of 6mm diameter from each mycelial growth and insert it in the center of a sterile slide. Lactophenol blue solution (Sigma-Aldrich, St. Louis, MO, USA) was used to stain the slides, which were then covered with sterile coverslips and inspected at 40 × power 51 . Scanning electron microscope (SEM) Some of the tested species were SEM scanned to evaluate the ultra-morphological alterations caused by different R. stricta treatments. The samples were examined using a JEOL JSM-6060LV scanning electron microscope equipped with a pre-centered W hairpin filament electron source (JEOL LTD., Tokyo, Japan). As previously stated, the slides were fixed overnight at 4°C with 2.5% Glutaraldehyde, then washed with phosphate buffer (pH 7.2), and re-fixed with 1% Osmium Tetroxide. As previously stated, dehydration in successive dilutions of ethanol, freeze-drying in a critical point drier, and mounting on gold-plated stubs were all completed 52 . Statistical analysis For statistical purposes, the experimental experiments were carried out in triplicates. The statistical analysis was carried out using IBM's Statistical Package for the Social Sciences (SPSS) version 22 (Armonk, NY, USA). If the P-Values were less than 0.05, the results were considered significant.

Results AgNPs were successfully biosynthesized The extraction of R. stricta leaves yielded a semi-solid dark green aqueous extract and its alkaline fraction (Dark brown) with yields of 40 g and 30.1g, respectively. Both preparations were light yellow when dissolved in distilled water for AgNPs synthesis. The biosynthesized AgNps displayed a dramatic serial color shift from bright yellow to yellow, brown, and eventually dark brown, indicating silver ion reduction and full production of stable silver ions. Various spectroscopy and microscopic examinations were used to characterize biosynthesized AgNPs. AgNPs' UV–visible spectra were measured between 200 and 900 nm. The UV–Vis spectra of Aq. AgNPs and Alkaline Aq. AgNPs resulted in two broad peaks at 405 and 415 nm, respectively (Fig. 1 ). As shown in Fig. 1 , the peak of Alkaline Aq. AgNPs were higher than that of aqueous AgNPs, which might be attributed to increased energy consumption by the nanoparticles due to complicated bonding. The FTIR spectra of R. stricta aqueous extract and biosynthesized AgNPs were analyzed to determine the nature of active ingredients responsible for nanoparticle reduction, stability, and bio-capping (Table 1 and Fig. 2 ). The presence of both bonded and non-bonded hydroxyl groups was indicated by broad peaks at 3402–3431 cm −1 and very weak peaks at 3402 cm -1 in the FTIR spectra of R. stricta preparations. Furthermore, all preparations showed peaks around 611–695 cm −1 , indicating the existence of aliphatic bromo compounds. Methylene, aromatic rings, methyl, and cyclic ethers were found in both the crude extract and aq. AgNPs. The FTIR study of aqueous AgNPs indicated two distinct functional groups for nitrile (2365.55 cm −1 ) and secondary alcohol (1119.67 cm −1 ) compounds. At 836–897 cm −1 , the aq. AgNPs and Alkaline Aq. AgNPs indicated the presence of peroxide. Table 1 shows that only the Alkaline Aq. AgNPs possessed four distinct functional groups for Quinone or conjugated ketone (at 1635.69 cm −1 ), sulfate (at 1386.00 cm −1 ), and amines (at 1242.06 and 1071.57 cm −1 ). By calculating the velocity of the nano-sized particles, zeta potential analysis may be used to measure the surface charge and stability of the formulation of biosynthesized AgNPs. The velocity of nanoparticles is determined by their movement towards electrodes under the influence of an applied electric field. The Zeta potential of AgNPs produced by various R. stricta extracts and fractions was measured. The results showed that the A. AgNPs had a − 27.7 mV and the Alkaline Aq. AgNPs had a − 37.9 mV. These results demonstrated that the AgNPs produced are stable (Fig. 3 ). The average particle size, diameter, and polydispersity indices (PDI) of all pre-synthesized AgNPs, on the other hand, were evaluated. The average particle sizes (z-average) of Aq. AgNPs and Alkaline Aq. AgNPs were 95.9 nm (PDI value 0.220, intercept 0.874) and 54.04 nm (PDI value 0.464, intercept 0.829), respectively (Fig. 3 ). This shows a difference in particle size between the two preparations, which might be related to pH changes. The two AgNPs preparations from R. stricta were analyzed by TEM imaging to corroborate the results of the zeta potential study. The findings revealed that both AgNPs were spherical in form, widely dispersed, and exhibited no aggregation (Fig. 4 ). The average diameter of Aq. AgNPs nanospheres ranged from 32 to 87 nm, whereas the average diameter of Alkaline Aq. AgNPs were 7.3–24.5 nm. Fungistatic properties of R. stricta aqueous preparations The antifungal effects of R. stricta aqueous extract and biosynthesized AgNPs against plant diseases such as D. halodes, D. tetramera, M. phaseolina, A. alternata, and C. australiensis were tested on a PDA medium. The suppression of mycelial growth was measured in all treatments and compared to positive and negative controls by measuring the diameter of clear zones in PDA dishes. As shown in Fig. 5 , the antifungal activity of the aqueous extract was at its maximum with a concentration of 20%. D. halodes was the most sensitive species to the fungicidal effects of all concentrations of R. stricta aqueous. On the other hand, C. australienses was the most resistant among all species ( P < 0.001). Previcur energy had similar activities; however, it didn’t affect the mycelial growth of A. alternate (Fig. 5 , Table 2 ). Treatment with Aq. AgNPs showed stronger antifungal activities against all species. As shown in Fig. 6 , all concentrations almost stopped the mycelial growth of all species compared to the negative control. The calculated percentages of the mycelial growth inhibition (IMG%) of A. alternata had the maximum IMG% (100%) followed by D. tetramera (95.9%), C. australiensis (93.4%), D. halodes (91.5%), and M. phaseolina (90.4%) at the 100% dose of Aq. AgNPs ( P < 0.001) (Table 3 ). Treatment with Aq. AgNPs showed stronger antifungal activities against all species. As shown in Fig. 7 , various concentrations had variable effects on the mycelial growth of all species compared to the negative control. The calculated IMG% was the maximum for D. halodes (86.4%), followed by D. tetramera (75.5%), C. australiensis (74.8%), A. alternata (54.2%), and M. phaseolina (46.2%) at the 100% dose of Aq. AgNPs ( P < 0.001) (Table 4 ). A summary of the different antifungal effects of tested preparations of R. stricta is shown in Fig. 8 . It was revealed that Aq. AgNPs were the most effective fungicide among all treatments, while the crude extract had the weakest antifungal effects except for M. phaseolina and A. alternata compared to the Alkaline Aq. AgNPs. Among all of the tested species, it seems like A. alternata was the most sensitive to the highest concentrations of Aq. AgNPs, while D. halodes was the most sensitive species to the treatment with the crude aqueous extract and Alkaline Aq. AgNPs of R. stricta. Controversially, M. phaseolina was statistically the most resistant to the inhibitory effects of all treatments, compared to the negative control. Ultra-structural changes induced by AgNPs of R. stricta Light microscopy imaging was used in the current investigation to compare the morphological changes in treated samples to the untreated control. All investigated fungal strains showed variances in the natural shape and size of hyphae and conidiophores. The morphological analysis of untreated D. tetramera showed light brown conidiophores, semi-elongated ellipsoid, cylindrical, and with round to oval ends. They are septate with no more than three pseudoseptates. The hyphae were brownish, granulated, unbranched, and with slight winding walls. Treatments with various preparations of R. stricta affected the septation and cylindrical shape of conidiophores, which appeared more oval, darker, and less viable than the control. The hyphae looked smoother, zigzag-shaped, swollen (in the case of crude aqueous extract), semi-branched (in the case of biosynthesized AgNPs), and bale-brown in Aq. AgNPs treatment (Fig. 9 ). The morphological analysis of untreated D. halodes showed the light brown, subcylindrical conidia with smooth, elongated walls. The geniculated conidiophores are septate transversally and have distinct septa at the basal cells with 6–8 pseudosepta. The hilum appeared distinctly protuberant and unbranched. Images of different treatments of R. stricta showed the conidia darker and less septate than in the control. The hyphae looked smoother, vacuolated, swollen, and semi-branched (in the case of crude biosynthesized AgNPs), budding, thicker, and bale-brown (in the case of Alkaline Aq. AgNPs treatment) (Fig. 10 ). The light microscopic analysis of untreated M. phaseolina revealed a distinct morphology. The hyphae were hyaline, thin-walled, septate, and branched at the right angle. The microsclerotia were hyphae that were hardened with compact masses and oblong-shaped. The crude aqueous extract of R. strica didn’t induce any clear changes, whereas both of the biosynthesized AgNPs induced the thickening and rapture of hyphae, which appeared bale and hardened (Fig. 11 ). The images of the untreated control of C. australiensis showed the sympodial, septate, flexuous, geniculated conidiophores with verrucose walls. The curved ellipsoidal conidia had rounded ends with four pseudosepta. The hyphae were protuberant, subhyaline, flexuous, light brown, and septate, with swollen and darker basal cells. The treatment with the crude aqueous extract of R. stricta or the Alkaline Aq. AgNPs didn’t reveal any significant changes in the hyphal structure, while the conidia didn’t appear. On the other hand, Aq. AgNPs induced extensive changes, where the hyphae were shorter, condensed, darker, and tighter than the control. The conidia appeared darker and raptured (Fig. 12 ). Finally, the microscopic analysis of A. alternata showed that the untreated fungus had clear morphology for both conidia and hyphae. The conidia were reddish-brown, ellipsoidal with a cylindrical beak, septate with 3–4 pseudosepta, and had verrucose smooth walls. The hyaline hyphae were multicell, septate, and branched. Different treatments of R. stricta caused the conidia to be more swollen, darker (in the case of crude extract and Aq. AgNPs), non-septate (in the case of Alkaline Aq. AgNPs), and oval to circular-shaped. The hyphae were more bale, transparent, and granulated in the species treated with the Alkaline Aq. AgNPs of R. stricta (Fig. 13 ). In the current study, we employed SEM to explore the morphological properties of the some of the susceptible species to the treatments under consideration. We show the species of D. halodes, D. tetramera, and C. australiensis here. The hyphae were deformed after treatment with Alkaline Aq. AgNPs, while the spores resembled the untreated control. After treatment with the aqueous extract and both biogenic AgNPs, there was an obvious contraction in hyphae and deformed spores of D. halodes. When compared to the natural structure exhibited in the untreated sample, these deformed spores had irregular forms and smaller hyphae (Fig. 14 a). Without treatment, the D. tetramera control sample revealed the fungus's original structure. However, significant hyphae deformation was seen after treatment with the aqueous extract and both biogenic AgNPs. When treated with Aq. AgNPs, the fungal spores were deformed relative to the control and were essentially missing (Fig. 14 b). C. australiensis control showed the fungus in its optimum form without treatment. Significant damage was detected after treatment with R. stricta aqueous extract and biosynthesized AgNPs. The hyphae appear to be cemented together, which might be explained by the fungus' capacity to make hydrophobic glue as a way of resistance to treatment. In comparison to the control, the detected spores look deformed and abundant (Fig. 14 c).

Discussion and conclusion Nanotechnology is defined as the creation, display, manipulation, and use of nanoparticles 22 . Nanoparticles have a single dimension ranging from 1 to 100 nm. They have unique properties that set them apart from bulk materials, which might be affected their shape and size 23 . Solar cells, photovoltaic devices, heterogeneous catalysts, and pharmaceuticals have all benefited from their use 22 , 23 . Nanoparticles may exhibit improved or completely unique characteristics when specified qualities (such as size, shape, and structure) are considered. Because of their excellent properties and flexibility, gold and silver (noble metal) nanoparticles have piqued the interest of researchers 24 . In the current study R. stricta aqueous extract and the alkaline fraction were used to produce various AgNPs. For measuring and comprehending the biological activity of biogenic AgNPs, comprehensive characterization was necessary. AgNPs size, form, size distribution, and aggregation are among these differentiating properties 25 . FTIR, UV–vis, Zeta potential, and TEM analysis were used to assess the properties of the biosynthesized AgNPs. In the current study, the UV–visible spectrum of AgNPs was investigated, and large peaks were discovered to give surface Plasmon resonance (SPR) of AgNPs formed from aqueous extract and aqueous alkaline fraction of R. stricta leaves at 405 nm and 415 nm, respectively. The observed elevated shift of the UV peak might be ascribed to nanoparticle agglomeration generated by AgNPs assembly and the presence of various secondary metabolites in the reaction solution that interact with the silver nitrate 25 . Previous research has revealed that AgNPs biosynthesized from R. stricta aqueous extract had broad peaks at 405–420 nm 26 – 28 . In the study conducted by Rahman and colleagues (2023), the AgNPs produced from the aqueous extract of R. stricta whole plant had a specific peak at 420–450, which decreased to 305 nm after 30 min of UV exposure 29 . Another study indicated that the ZnO nanoparticles synthesized from the aqueous leaf extract of R. stricta had an SPR of 335 nm 30 . FTIR is a very reliable analytical technique for detecting and displaying molecules' components, chemical structure, chemical bonds, functional groups, and bonding patterns 31 . FTIR analysis is a valuable method for studying the functional moieties involved in metal ion-biomolecule interactions 32 . In the current study, both of the biosynthesized AgNPs were analyzed using FTIR and compared to the crude aqueous extract to identify the compounds that function as stabilizing and coating agents, as well as to detect silver ion reduction. The FTIR spectra of various R. stricta’s aqueous leaf extract preparations indicated that they were high in hydroxyl groups, methylene, aromatic rings, methyl, and cyclic ether functional groups. Extra functional groups for nitrile, secondary alcohol, peroxide, conjugated ketone, and amines were added to the biosynthesized AgNPs. The changes in the plant extract's functional groups confirm that it serves as a reducing and capping agent in the production of AgNPs. In accordance with these findings, a previous study showed that the FTIR spectrum of R. stricta 's aqueous leaf extract contained hydroxyl, carboxyl, saturated aldehydes, amides, ketones, ethers, and alcohol functional groups 29 . Another study employed FTIR to analyze the AgNPs biosynthesized from the methanolic root extract of R. stricta and reported the existence of hydroxyl, amino, amide, and carboxyl groups 33 . All of these studies, in addition to the current findings, evaluated that biological molecule act as capping and reducing agents in the AgNPs synthesis. Dynamic light scattering has been frequently used to characterize AgNPs that are generated utilizing chemical components. It calculates the size of the AgNPs colloidal solution, which scatters light and indicates their dispersion size in the 3–10 m range 23 . Furthermore, by calculating the velocity of biosynthesized AgNPs, zeta potential analysis may be used to evaluate their surface charge and stability. The velocity of nanoparticles is determined by their movement towards electrodes under the influence of an applied electric field 34 . In the current study, the Zeta potential of AgNPs synthesized by the aqueous extract of R. stricta detected their velocity at − 27.7 mV and − 37.9 mV for the Aq. AgNPs and Alkaline Aq. AgNPs, respectively, which indicated their stability. Similar study showed that a zeta potential value of -24.1 mv indicated the long-term stability. colloidal nature, and high dispersion of the AgNPs biosynthesized from Urtica dioica Linn. Leaves 35 . Another study showed that the AgNPs biosynthesized from different extracts of Tabernaemontana ventricose, member of Apocynaceae, had a velocity of -30.1 mV with a particle size of 70 nm 36 . These negative values of zeta potential analysis support the stability and dispersity of AgNPs as a result of the negative-negative repulsion 35 . The surface shape and size of AgNPs biosynthesized from the aqueous and alkaline fractions of R. stricta leaves were determined using TEM. The results showed that the biosynthesized AgNPs were well-dispersed, with average diameters of 21–90 nm for Aq. AgNPs and 7.2–25.3 nm for Alkaline Aq. AgNPs, respectively. The TEM findings for the Aq. AgNPs were similar to the Zeta analysis results; however, the TEM results for the Alkaline Aq. AgNPs showed substantial discrepancies. This might be owing to the zeta analysis's overestimation of aggregates (based on Rayleigh's assumption) and peak width, or the elimination of nanoparticle aggregation in TEM 37 . Previous research found that AgNPs produced from methanolic and aqueous extracts of R. stricta root extract were spherical in form with average diameters of 20–35 nm 29 , 33 . In the current work, R. stricta leaf extract and biosynthesized AgNPs inhibited the tested fungus species significantly. Growth observation of all examined fungi revealed a considerable shift in terms of growth density, color change, and perceived growth weakening. In that context, AgNPs biosynthesized from R. stricta root extract shown promising antibacterial action against B. subtilis and E. coli 33 . Another study found that R. stricta extract contains indole alkaloids and triterpene derivatives as main constituents that act as stabilizing agents during nanoparticle synthesis, increasing the antimicrobial activity of AgNPs against Klebsiella pneumoniae, Salmonella typhi , and B. subtilis 27 . R. stricta is a rich source of alkaloids with a wide range of structures and activities. Hajrah et al. (2020) reported that some of the alkaloids isolated from R. stricta , such as akuammidine, rhazimanine, stemmadenine, strictanol, and tetrahydrosecaminediol, showed potential antimicrobial activity against different human pathogens such as P. aeruginosa, E. coli, S. aureus, and C. albicans 38 . Also, ethanolic extract of R. stricta fruit shown outstanding antibacterial action against S. aureus, E. coli, P. aeruginosa, B. subtilis, Streptococcus pyogenes , and S. typhi 39 . Ahmed et al. (2018) isolated 27 monoterpene indole alkaloids from R. stricta , which demonstrated significant antifungal activity against C. albicans, Candida lusitaniae, Candida guilliermondii, C. glabrata, Candida krusei , and Candida parapsilosis with MIC values ranging from 3.125 to 50 g/m 40 . Furthermore, a previous study reported significant anti-fungal activities of different extracts against Trichophyton longifusis, Aspergillus flavus, C. albicans, and Fusarium solani 41 . For our knowledge, different extracts of R. stricta or the biosynthesized nanoparticles were examined for their antifungal activities against the tested species. As a conclusion, our findings revealed that tested R. stricta extracts and fractions have antifungal efficacy against some plant pathogenic fungi. When compared to Alkaline Aq. AgNPs, the pre-synthesized Aq. AgNPs demonstrated high activity. That might be because the Alkaline aqueous AgNPs missed some of the functional groups which weakened its activity; however, of its significant fungicidal activity as compared to the untreated species. More experimental study on employing plant extracts as an alternative to toxic chemicals is required, as well as a deeper analysis of the ultra-cellular and molecular damage induced by R. stricta extract to elucidate its probable antifungal processes. Also, further research to explore the mechanisms underlying the antifungal activity of R. stricta different extracts and biosynthesized nanoparticles.

Discussion and conclusion Nanotechnology is defined as the creation, display, manipulation, and use of nanoparticles 22 . Nanoparticles have a single dimension ranging from 1 to 100 nm. They have unique properties that set them apart from bulk materials, which might be affected their shape and size 23 . Solar cells, photovoltaic devices, heterogeneous catalysts, and pharmaceuticals have all benefited from their use 22 , 23 . Nanoparticles may exhibit improved or completely unique characteristics when specified qualities (such as size, shape, and structure) are considered. Because of their excellent properties and flexibility, gold and silver (noble metal) nanoparticles have piqued the interest of researchers 24 . In the current study R. stricta aqueous extract and the alkaline fraction were used to produce various AgNPs. For measuring and comprehending the biological activity of biogenic AgNPs, comprehensive characterization was necessary. AgNPs size, form, size distribution, and aggregation are among these differentiating properties 25 . FTIR, UV–vis, Zeta potential, and TEM analysis were used to assess the properties of the biosynthesized AgNPs. In the current study, the UV–visible spectrum of AgNPs was investigated, and large peaks were discovered to give surface Plasmon resonance (SPR) of AgNPs formed from aqueous extract and aqueous alkaline fraction of R. stricta leaves at 405 nm and 415 nm, respectively. The observed elevated shift of the UV peak might be ascribed to nanoparticle agglomeration generated by AgNPs assembly and the presence of various secondary metabolites in the reaction solution that interact with the silver nitrate 25 . Previous research has revealed that AgNPs biosynthesized from R. stricta aqueous extract had broad peaks at 405–420 nm 26 – 28 . In the study conducted by Rahman and colleagues (2023), the AgNPs produced from the aqueous extract of R. stricta whole plant had a specific peak at 420–450, which decreased to 305 nm after 30 min of UV exposure 29 . Another study indicated that the ZnO nanoparticles synthesized from the aqueous leaf extract of R. stricta had an SPR of 335 nm 30 . FTIR is a very reliable analytical technique for detecting and displaying molecules' components, chemical structure, chemical bonds, functional groups, and bonding patterns 31 . FTIR analysis is a valuable method for studying the functional moieties involved in metal ion-biomolecule interactions 32 . In the current study, both of the biosynthesized AgNPs were analyzed using FTIR and compared to the crude aqueous extract to identify the compounds that function as stabilizing and coating agents, as well as to detect silver ion reduction. The FTIR spectra of various R. stricta’s aqueous leaf extract preparations indicated that they were high in hydroxyl groups, methylene, aromatic rings, methyl, and cyclic ether functional groups. Extra functional groups for nitrile, secondary alcohol, peroxide, conjugated ketone, and amines were added to the biosynthesized AgNPs. The changes in the plant extract's functional groups confirm that it serves as a reducing and capping agent in the production of AgNPs. In accordance with these findings, a previous study showed that the FTIR spectrum of R. stricta 's aqueous leaf extract contained hydroxyl, carboxyl, saturated aldehydes, amides, ketones, ethers, and alcohol functional groups 29 . Another study employed FTIR to analyze the AgNPs biosynthesized from the methanolic root extract of R. stricta and reported the existence of hydroxyl, amino, amide, and carboxyl groups 33 . All of these studies, in addition to the current findings, evaluated that biological molecule act as capping and reducing agents in the AgNPs synthesis. Dynamic light scattering has been frequently used to characterize AgNPs that are generated utilizing chemical components. It calculates the size of the AgNPs colloidal solution, which scatters light and indicates their dispersion size in the 3–10 m range 23 . Furthermore, by calculating the velocity of biosynthesized AgNPs, zeta potential analysis may be used to evaluate their surface charge and stability. The velocity of nanoparticles is determined by their movement towards electrodes under the influence of an applied electric field 34 . In the current study, the Zeta potential of AgNPs synthesized by the aqueous extract of R. stricta detected their velocity at − 27.7 mV and − 37.9 mV for the Aq. AgNPs and Alkaline Aq. AgNPs, respectively, which indicated their stability. Similar study showed that a zeta potential value of -24.1 mv indicated the long-term stability. colloidal nature, and high dispersion of the AgNPs biosynthesized from Urtica dioica Linn. Leaves 35 . Another study showed that the AgNPs biosynthesized from different extracts of Tabernaemontana ventricose, member of Apocynaceae, had a velocity of -30.1 mV with a particle size of 70 nm 36 . These negative values of zeta potential analysis support the stability and dispersity of AgNPs as a result of the negative-negative repulsion 35 . The surface shape and size of AgNPs biosynthesized from the aqueous and alkaline fractions of R. stricta leaves were determined using TEM. The results showed that the biosynthesized AgNPs were well-dispersed, with average diameters of 21–90 nm for Aq. AgNPs and 7.2–25.3 nm for Alkaline Aq. AgNPs, respectively. The TEM findings for the Aq. AgNPs were similar to the Zeta analysis results; however, the TEM results for the Alkaline Aq. AgNPs showed substantial discrepancies. This might be owing to the zeta analysis's overestimation of aggregates (based on Rayleigh's assumption) and peak width, or the elimination of nanoparticle aggregation in TEM 37 . Previous research found that AgNPs produced from methanolic and aqueous extracts of R. stricta root extract were spherical in form with average diameters of 20–35 nm 29 , 33 . In the current work, R. stricta leaf extract and biosynthesized AgNPs inhibited the tested fungus species significantly. Growth observation of all examined fungi revealed a considerable shift in terms of growth density, color change, and perceived growth weakening. In that context, AgNPs biosynthesized from R. stricta root extract shown promising antibacterial action against B. subtilis and E. coli 33 . Another study found that R. stricta extract contains indole alkaloids and triterpene derivatives as main constituents that act as stabilizing agents during nanoparticle synthesis, increasing the antimicrobial activity of AgNPs against Klebsiella pneumoniae, Salmonella typhi , and B. subtilis 27 . R. stricta is a rich source of alkaloids with a wide range of structures and activities. Hajrah et al. (2020) reported that some of the alkaloids isolated from R. stricta , such as akuammidine, rhazimanine, stemmadenine, strictanol, and tetrahydrosecaminediol, showed potential antimicrobial activity against different human pathogens such as P. aeruginosa, E. coli, S. aureus, and C. albicans 38 . Also, ethanolic extract of R. stricta fruit shown outstanding antibacterial action against S. aureus, E. coli, P. aeruginosa, B. subtilis, Streptococcus pyogenes , and S. typhi 39 . Ahmed et al. (2018) isolated 27 monoterpene indole alkaloids from R. stricta , which demonstrated significant antifungal activity against C. albicans, Candida lusitaniae, Candida guilliermondii, C. glabrata, Candida krusei , and Candida parapsilosis with MIC values ranging from 3.125 to 50 g/m 40 . Furthermore, a previous study reported significant anti-fungal activities of different extracts against Trichophyton longifusis, Aspergillus flavus, C. albicans, and Fusarium solani 41 . For our knowledge, different extracts of R. stricta or the biosynthesized nanoparticles were examined for their antifungal activities against the tested species. As a conclusion, our findings revealed that tested R. stricta extracts and fractions have antifungal efficacy against some plant pathogenic fungi. When compared to Alkaline Aq. AgNPs, the pre-synthesized Aq. AgNPs demonstrated high activity. That might be because the Alkaline aqueous AgNPs missed some of the functional groups which weakened its activity; however, of its significant fungicidal activity as compared to the untreated species. More experimental study on employing plant extracts as an alternative to toxic chemicals is required, as well as a deeper analysis of the ultra-cellular and molecular damage induced by R. stricta extract to elucidate its probable antifungal processes. Also, further research to explore the mechanisms underlying the antifungal activity of R. stricta different extracts and biosynthesized nanoparticles.

One of the most promising, non-toxic, and biocompatible developments for many biological activities is the green synthesis of nanoparticles from plants. In this work, we investigated the antifungal activity of silver nanoparticles (AgNPs) biosynthesized from Rhazya stricta aqueous extract against several plant pathogenic fungi. UV–visible spectroscopy, Zeta potential analysis, Fourier-transform infrared spectroscopy (FTIR), and transmitted electron microscopy (TEM) were used to analyze the biosynthesized AgNPs. Drechslera halodes, Drechslera tetramera, Macrophomina phaseolina, Alternaria alternata, and Curvularia australiensis were tested for their potential antifungal activity. Surface Plasmon Resonance (SPR) of Aq. AgNPs and Alkaline Aq. AgNPs was observed at 405 nm and 415 nm, respectively. FTIR analysis indicated hydroxyl, nitrile, amine, and ketone functional groups. Aq. AgNPs and Alka-line Aq. AgNPs had velocities of − 27.7 mV and − 37.9 mV and sizes of 21–90 nm and 7.2–25.3 nm, respectively, according to zeta potential studies and TEM. The antifungal examination revealed that all species' mycelial development was significantly inhibited, accompanied by severe ultra-structural alterations. Among all treatments, Aq. AgNPs were the most effective fungicide. M. phaseolina was statistically the most resistant, whereas A. alternata was the most vulnerable. To the best of our knowledge, this is the first report on R. stricta' s antifungal activity against these species. Subject terms

Acknowledgements The authors extend their appreciation to the Deputyship for Research & Innovation “Ministry of Education” in Saudi Arabia for funding this research work through project no. (IFKSUOR3-132-4). Author contributions Conceptualization, F.A. and N.M.A.; methodology, S.A.A., R.I.A, and M.A.; software, R.I.A.; validation, F.A and N.M.A.; formal analysis, S.A.A.; investigation, S.A.A, and M.A.; resources, F.A. and S.A.A.; data curation, F.A. and N.M.A.; writing—original draft preparation, S.A.A.; writing—review and editing, F.A and N.M.A.; visualization, R.I.A.; supervision, F.A and N.M.A.; project administration, F.A..; funding acquisition, F.A. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the Deputyship for Research & Innovation “Ministry of Education” in Saudi Arabia for funding this research work through project no. (IFKSUOR3-132-4). Data availability The raw data presented in this study are available from the corresponding author upon reasonable request. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1297

oa_package/a9/1a/PMC10788342.tar.gz

PMC10788343

38221535

Introduction The heart is more susceptible to ischemic injury compared to other solid organs because of its innately high metabolic demands. Mitochondria, the organelle vital to cardiomyocytes 1 , continuously supply oxidative energy to maintain heart function. During myocardial injury, mitochondrial impairment is an essential determinant of cardiomyocyte damage due to impaired mitochondrial ATP synthesis; increased generation of reactive oxygen species (ROS) 2 ; inability to maintain mitochondrial membrane potential; decreased ion balance maintenance, particularly Ca 2+ ; and increased mitochondrial permeability. Accumulating evidence has highlighted interplays between the circadian rhythm and mitochondrial metabolic pathways 3 – 9 . Particularly, period circadian regulator 2 (Per2) is reported to control mitochondrial oxidative metabolism in mouse skeletal myoblasts 3 and lipid metabolism in adipogenesis 6 . Per2 knockout (KO) worsens cold treatment (4 °C)-lowered triglyceride levels in brown adipocytes and reduces β-oxidation in brown adipose tissue mitochondria 7 . Per2 is also involved in metabolic regulation in the heart during ischemic damage 5 , 8 . These findings suggest a role for Per2 in the regulation of mitochondrial metabolic activity. However, Per2’s regulatory activity in mitochondrial metabolism in these studies is contingent upon the central nervous system’s response to stress. Cyclical production and activity of Per2 in the suprachiasmatic nucleus, midbrain, and forebrain is responsible for the activation of central clock pathways and subsequent metabolic adaptations of whole body and peripheral organs and tissues. Still, the direct role of Per2 in mitochondrial performance, besides circadian rhythm, remains unknown. Our most recent study identified Per2 as a significantly down-regulated gene with upstream regulator activity that was inhibited in adult mouse hearts after 6 h-cold storage ex vivo 10 . Its downregulation corresponded with mitochondrial dysfunction. Knockdown of Per2 was also observed to impair mitochondrial membrane potential in H9c2 cells following cold storage 10 . Furthermore, hypoxia preconditioning increased Per2 translocation into the mitochondria and induced binding of Per2 to Complex IV in endothelial cells 11 . These findings imply a suspected role of Per2 in directly impacting mitochondrial function beyond circadian rhythm activities. During a variety of acute myocardial injury, TNFα and H 2 O 2 (one of the most stable ROS forms) rise markedly proceeding cardiac damage and dysfunction 12 – 19 . Local increase in inflammatory mediators and oxidative stress have been shown to impair cardiac mitochondria. In this study, we aim to determine the importance of Per2 protein’s regulatory role in mitochondrial function following exposure to inflammatory cytokine TNFα and oxidative stressor H 2 O 2 in human cardiomyocytes.

Materials and methods Animals All animal studies were conducted in compliance with the Guide for the Care and Use of Laboratory Animals ( NIH Pub. No. 85-23, revised 1996). The animal protocol was reviewed and approved by the Institutional Animal Care and Use Committee of Indiana University. Male C57BL/6J mice (9–12 weeks) were purchased from the Jackson Laboratories (Bar Harbor, ME). The animals were acclimated for > 5 days with a standard diet feeding prior to the experiments and maintained on the same light–dark cycle. All animal experiments were performed between 10:00 am and 2:00 pm. The study is reported in accordance with ARRIVE guidelines. Global myocardial ischemia in vivo After deep anesthesia by isoflurane, the mice were placed supine on a heated pad (37 °C) and injected peritoneally with 0.15 ml of heparin (100 U/ml). The chest was then opened, and the diaphragm was dissected to introduce respiratory arrest. The heart was collected 30 min after the heart stopped beating (30 min-warm ischemia) and snap-frozen in liquid nitrogen. Freshly isolated mouse hearts without global myocardial warm ischemia served as control. Mitochondria were obtained by differential centrifugation using mitochondria isolation kit for tissue (ThermoFisher Scientific) according to manufacturer's protocols. The purity of mitochondrial preparations using this method was confirmed in our previous study 20 . Measurement of mitochondrial complex I activity Mitochondrial complex I activity was detected using the enzyme activity microplate assay kit (Abcam, Cambridge, MA, ab109721) according to manufacturer's protocols. Isolated heart mitochondrial pellets (10 μg of mitochondrial protein) were resuspended in PBS with 10% detergent provided in the kit. Enzyme activities were analyzed by increased absorbance at OD = 450 nm due to the oxidation of NADH to NAD + using a microplate reader (represented as absorbance changes per minute per milligram protein). Each sample was conducted in duplicate. Adult mouse cardiomyocyte isolation By using a Langendorff perfusion system, cardiomyocytes were isolated from adult male mouse hearts based on our previous studies 20 , 22 , 34 . Briefly, after mice were heparinized and euthanized with isoflurane overdose, the hearts were excised and rapidly placed into ice-cold calcium-free perfusion buffer. Hearts were perfused and digested with collagenase II (1.5 mg/ml) in perfusion buffer containing 50 mM calcium. Isolated cardiomyocytes were then restored sequentially in perfusion buffer with calcium (100, 250, 500, or 1000 mmol/L CaCl 2 ) and seeded into laminin (20 mg/ml)-precoated 6-well plate in cardiomyocyte plating medium. After 2-h cultivation for adherence, cardiomyocytes were treated with vehicle, 10 ng/ml TNF or 50 μM of H 2 O 2 for 2 h and then collected for protein isolation. The doses of TNFα- and H 2 O 2 were selected based on our previous studies 20 , 22 . The cardiomyocytes were also plated into laminin (20 mg/ml)-precoated XF96 cell culture plates with 1500 cells/well 22 . After the cultivation for adherence, the cells were used for the Seahorse XF Cell Mito Stress Assay. Knocking down of Per2 in AC16 human cardiomyocyte cell line The AC16 human cardiomyocyte cell line was purchased from the Millipore Sigma and cultured in 100 mm cell culture dishes with DMEM/F12 (Sigma, D6434) containing 12.5% FBS (EMD Millipore, ES-009-B), 2 mM l -Glutamine (EMD Millipore, TMS-002-C), and 1X Penicillin–Streptomycin Solution (EMD Millipore, TMS-AB2-C) at 37 °C, 5% CO 2 and 90% humidity, based on the manufacturer's protocols. AC16 cells were plated in 12-well plate at 1.0X10 5 cells/well or in 96-well plate at 1.0X10 4 cells/well. Twenty-four hour later, cells were transfected with human Per2 or control siRNAs (Life Technologies) using Lipofectamine 2000 (Life Technologies). After one day of transfection, normal AC16 growth medium was added. The cells were allowed to incubate for an additional day and then used for experiments. Different doses of Per2 siRNA (10, 20, and 30 pmol) were used to determine their effects on transcript levels of Per2 and the dose of 20 pmol was selected for subsequent trials in this study. All cell culture studies were performed in accordance with our approved protocol by the Institutional Biosafety Committee of Indiana University. Real-time quantitative PCR Total RNA was extracted from AC16 cells using Trizol (Life Technology) and used for the first-strand cDNA reverse transcription using Quantum (ThermoFisher Scientific). TaqMan assays were used to determine transcript levels of human Per2 (Fam dye-labeled) and GAPDH (VIC dye-labeled) (ThermoFisher Scientific) by Real-time PCR (7500 Real-Time PCR System, Applied Biosystems). The probes of both Per2 and GAPDH were added into the same reaction and Per2 expression was normalized to the GAPDH level. Western Blotting The heart tissues and the cells were lysed in cold RIPA buffer containing Halt protease and phosphatase inhibitor cocktail (ThermoFisher Scientific). The protein and mitochondrial extracts were loaded into a 4–15% Criterion TGX Precast midi protein gel (Bio-Rad, Hercules, CA, USA) for electrophoresis and transferred to a nitrocellulose membrane. The membranes were incubated with the following primary antibodies respectively: Per2 antibody (ThermoFisher Scientific, 100107), OXPHOS antibody cocktail (complex I-NDUFB8, complex II-SDHB, complex IV-MTCO1, complex III-UQCRC2, and complex V-ATP5A) (ThermoFisher Scientific), and GAPDH (#2118) (Cell Signaling Technology, Beverly, MA, USA) and then incubated with the fluorescence-conjugated secondary antibody. A ChemiDoc system (BioRad) was used to detect immunoblotting bands, which were quantified using the Image J software (NIH). Cell death detection by flow cytometry Control siRNA- and Per2 siRNA-transfected AC16 cells were collected from 12-well plate after treatment with vehicle, 100 ng/ml TNFα 35 or 100 μM of H 2 O 2 36 for 4 h and stained with Annexin-V FITC and propidium iodide (PI) using a Dead Cell Apoptosis kit (BD Sciences). Dead cells were analyzed with a LSR4 flow cytometer (BD Biosciences) and determined by Flowjo software (Annexin-V + /PI− [apoptotic cells], Annexin V-/PI + [late apoptotic and necrotic cells] and Annexin V + /PI + [end stage apoptosis and death]). The experiments were repeated three times. Seahorse cell mito stress test We detected mitochondrial bioenergetic response shown by oxygen consumption rate (OCR) in adult mouse cardiomyocytes and AC16 human cardiomyocytes using a Seahorse XF-96 instrument (Seahorse Biosciences, USA) as we recently reported 22 , 34 . Adult mouse cardiomyocytes (1500 cells/well) were treated with TNFα (10 ng/ml) or H 2 O 2 (50 μM) in supplemented XF medium (5 mM Glucose, 1 mM pyruvate, and 2 mM Glutamine) for 1 h according to our previous studies 20 , 22 . AC16 cells (6000 cells/well) transfected with control or Per2 siRNAs were exposed to TNFα (100 ng/ml) or H 2 O 2 (100 μM) in supplemented XF medium (25 mM Glucose, 1 mM pyruvate, and 2 mM Glutamine) for 2 h. The metabolic profile of these cells was detected sequentially as baseline OCR, ATP-linked respiration by adding oligomycin (Oligo, 1 μM), maximal uncoupled respiration after injecting FCCP (1 μM), and non‐mitochondrial respiration by addition of rotenone (R) and antimycin A (A) (1 μM). The basal OCR was calculated by subtracting non-mitochondrial OCR from the last value before addition of oligomycin. Maximal OCR was obtained by subtracting non-mitochondrial OCR from the FCCP-stimulated rate. Mitochondrial membrane potential Two days after transfection with Per2 or control siRNA, AC16 human cardiomyocytes in the 96-well plate were treated with vehicle, 100 ng/ml TNFα or 100 μM of H 2 O 2 . Two-hour later, AC16 growth medium containing a fluorescent probe JC-1 (5 μM, G-Biosciences, St. Louis, MO, USA) was added. After 30-min incubation at 37C, live-cell imaging was taken using a Nikon Eclipse Ts2R microscope with a 20X objective. In addition, fluorescence intensity in each well was recorded using a microplate reader (BioTek) with total red (excitation: 535 nm; emission: 585 nm) and green (excitation: 485 nm; emission: 535 nm) fluorescence. Mitochondrial membrane potential was indicated by the red to green fluorescence intensity ratio. Statistical analysis The results were means ± SEM and each dot represents individual measurement for each sample. Data was analyzed using either student t -test or one-way ANOVA. p < 0.05 indicates statistically significant difference. The GraphPad Prism software (GraphPad, La Jolla, CA, USA) was used for all statistical analyses.

Results Stress-induced mitochondrial dysfunction is associated with reduced Per2 levels in the heart mitochondria and primary cardiomyocytes Mitochondrial damage is evident following myocardial ischemia. In this study, we first confirmed that the activity of mitochondrial complex-I was severely impaired following ischemia in mitochondria isolated from adult male mouse hearts ± 30-min ischemia (Fig. 1 A). Interestingly, we observed that ischemia decreased mitochondrial Per2 content in the heart compared to controls (Fig. 1 B). Our previous study has demonstrated purity of the mitochondrial preparation, confirming no cytosolic and nuclear protein contamination 20 . Per2 may impact mitochondrial function independent of its subcellular location. Therefore, we mainly utilized the whole cell Per2 instead of mitochondria in this study. To emulate the high levels of TNFα or H 2 O 2 induced early by myocardial ischemia, we then utilized TNFα or H 2 O 2 as stressors in mouse adult cardiomyocytes and assessed the resulting mitochondrial metabolic function. We found that TNFα and H 2 O 2 individually impaired maximal respiratory capacity in cardiomyocyte mitochondria (Fig. 1 C), which was associated with decreased Per2 levels (Fig. 1 D). Given that mitochondrial fraction of Per2 is involved in the circadian rhythm-controlled glycolysis-related energy pathway 21 , our results suggested a possible role of Per2 in protecting cardiac mitochondrial function during stress. Per2 expression impacts mitochondrial membrane potential (∆ψ M ) in AC16 human cardiomyocytes subjected to TNFα or H 2 O 2 To evaluate the role of Per2 in regulating mitochondrial vulnerability during stress, we then employed siRNA to knockdown Per2 expression in AC16 cells (human cardiomyocyte cell line). Our data showed a dose-dependent decrease in Per2 mRNA transcripts, with 10 pmol of Per2 siRNA resulting in the smallest reduction of Per2 mRNA compared to control levels, whereas 30 pmol of Per2 siRNA treatment resulted in the greatest reduction (Fig. 2 B). We selected a dose of 20 pmol Per2 siRNA in this study, as higher doses of siRNA transfection are injurious to cells, but this dose still induced a significant reduction in Per2 mRNA (Fig. 2 B). Western blot analysis further confirmed Per2 protein knockdown with 20 pmol of Per2 siRNA usage in AC16 cells (Fig. 2 C). Mitochondrial membrane potential ( ∆ψ M ) is critical for maintaining mitochondrial function and health. We first assessed mitochondrial membrane potential using JC-1 fluorescent probe in TNFα- or H 2 O 2 -stressed AC16 cells with control or Per2 siRNA transfection. JC-1 displays green fluorescence in the monomeric form in the cytosol upon depolarization, whereas it shows red fluorescence in the aggregated form in active mitochondria. Thus, the ratio of red/green fluorescent intensity indicates mitochondrial membrane potential. In addition to live-cell imaging on AC16 cells using a fluorescent microscope (Fig. 3 A), we quantified the ratio of red/green fluorescent intensity using a microplate reader. Our data revealed that 2 h treatment of TNFα or H 2 O 2 damaged ∆ψ M in AC16 cells, denoted by the decreased ratio of red/green fluorescent intensity in these cells compared to their vehicle control counterpart (Fig. 3 B). Intriguingly, knockdown of Per2 further reduced TNFα- or H 2 O 2 -impaired ∆ψ M in AC16 cells compared to the control siRNA group (Fig. 3 C), displaying a likely protective role of Per2 in maintaining mitochondrial function during stress. However, Per2 siRNA alone did not affect ∆ψ M (Fig. S3 ). Per2 knockdown increases cell death in AC16 human cardiomyocytes exposed to TNFα TNFα or H 2 O 2 can induce cell death in a variety of cells and mitochondrial membrane potential is also involved in apoptosis induction. Therefore, we evaluated the role of Per2 in regulating AC16 cell death following TNFα or H 2 O 2 stimulation. After Annexin V and PI staining and analysis of Flow cytometry (Fig. 4 A), our data indicated that 4 h treatment of TNFα or H 2 O 2 significantly increased cell death in AC16 cells (Fig. 4 B). Furthermore, Per2 knockdown resulted in greater cell death in TNFα-stressed AC16 cells compared to control. siRNA transfected cells (Fig. 4 C), suggesting that Per2 likely plays a role in TNFα-induced cell death signaling in cardiomyocytes. However, Per2 siRNA alone did not impact cell viability (Fig. S4 ). The implication of Per2 in mitochondrial respiration function following TNFα or H 2 O 2 stress Our previous studies have demonstrated mitochondrial functional impairment in cardiomyocytes subjected to TNFα or H 2 O 2 20 , 22 . In this study, we determined the role of Per2 in mitochondrial metabolic function in AC16 cells upon exposure of TNFα or H 2 O 2 using Seahorse Cell Mito Stress test (Fig. 5 A). While decreased Per2 level did not affect mitochondrial respiration function in AC16 cells without stress of TNFα or H 2 O 2 (Fig. S5 ), Per2 knockdown did significantly decrease mitochondrial maximal respiration (Fig. 5 B) and ATP-linked respiration (Fig. 5 C) in AC16 cells subjected to 2 h treatment of TNFα or H 2 O 2 . We further studied effects of stress on mitochondrial oxidative phosphorylation (OXPHOS) complex proteins. Western blot data demonstrated that TNFα significantly increased complex V-ATP5A, complex III-UQCRC2 and complex IV-MTCO1 proteins in AC16 cells (Fig. 6 A,C), while a trend of augmented levels of ATP5A and MTCO1 was noticed in AC16 cells exposed to H 2 O 2 . Per2 knockdown markedly upregulated protein levels of ATP5A and UQCRC2 and abolished TNFα-induced increase in these complex molecules (Fig. 6 B,C).

Discussion Mitochondria are central to heart bioenergetics, as mitochondrial dysregulation is an underlying mechanism of cardiac dysfunction. In this present study, our data clearly demonstrated that: (1) acute stress reduced Per2 levels and concurrently impaired mitochondrial function in the heart mitochondria and adult cardiomyocytes; (2) Increased cell death and decreased M were observed in human cardiomyocytes treated with TNFα or H 2 O 2 ; (3) Knockdown of Per2 potentiated TNFα-induced cell death and TNFα- or H 2 O 2 - disrupted M ; and (4) Per2 knockdown worsened TNFα- or H 2 O 2 -induced impairment of mitochondrial respiration function. These findings supported a strong implication of Per2 in mitochondrial regulation to protect cardiomyocytes during stress. Evidence supports the local inflammation and redox imbalance as important primary factors in cardiomyocyte injury and cardiac functional damage 23 – 25 . Acute injury including ischemia induces excessive production of TNFα or H 2 O 2 that leads to cell death (apoptosis and necrosis) in many types of cells. Our current findings confirmed that TNFα and H 2 O 2 significantly increased cell death in human cardiomyocytes. However, it is unknown whether Per2 plays a role in TNFα- or H 2 O 2 -induced cell death in human cardiomyocytes. In addition to being a circadian regulator protein, emerging research has suggested the involvement of Per2 in the regulation of cell death through several pathways. Per2 has been found to inhibit activation of PI3K/Akt signaling, thus reducing proliferation while promoting apoptosis in human adenocarcinoma cell lines 26 . In the cytosol, Per2 can function as a scaffolding protein to block mTORC1-induced cell proliferation and increase autophagy in the liver during fasting 27 . Our previous work has also shown that reduction of Per2 in H9c2 cells increased apoptosis following cold storage 10 . In this study, Per2 knockdown enhanced TNFα-induced cell death in human cardiomyocytes, suggesting that Per2 plays a role in the regulation of cell death in cardiomyocytes in response to local inflammatory mediators. TNFα binding to its receptors leads to cell death through multiple regulatory pathways including the extrinsic pathway of apoptosis involving mitochondria 19 . However, the interaction of Per2 and TNFα-initiated cell death pathways are not well elucidated and necessitates further study. Of note, we did not observe the impact of Per2 in preventing cell death of human cardiomyocytes exposed to H 2 O 2 . Since only one time point (4 h treatment of H 2 O 2 ) was studied, we cannot confirm whether the H 2 O 2 treatment period is suitable to detect cell death here. It is evident that Per2 deficiency reduces the tolerance of H9c2 cells to H 2 O 2 following serum shock, with increased cell death in Per2 knockdown H9c2 cells 28 . However, reduction of Per2 did not significantly affect cell death in the H9c2 cells only exposed to serum shock 28 . This suggests that the relationship between Per2 and cell death may vary depending on the different stressed conditions and the balance of various signaling pathways involved. The exact mechanisms through which Per2 impacts cardiomyocyte cell death are a subject of ongoing research. Future investigations are needed to completely understand the underlying mechanistic details of Per2’s role in modulating cell viability. Recent studies have revealed that the clock regulator Per2 influences mitochondrial metabolic modulation 4 – 6 . Per2 regulates mitochondrial oxidative metabolism in mouse C2C12 myoblasts exposed to fatty acid oxidation 3 . During ischemia, Per2 is activated by the hypoxia-inducible factor1a (HIF-1a) pathway, which facilitates induction of glycolytic enzymes to maximize energy production through glycolysis in low O 2 conditions 5 . Increased oxygen consumption and impaired glycolysis are observed in Per2KO mice subjected to myocardial ischemia. Disruption of Per2 affects mitochondrial morphology and glycogen accumulation following myocardial ischemia 5 , 8 . Our present findings indicate that Per2 knockdown significantly decreased mitochondrial maximal respiration and ATP-linked respiration in human cardiomyocytes exposed to TNFα or H 2 O 2 . However, the precise mechanisms through which Per2 influences mitochondrial metabolic regulation remains unknown. Emerging evidence has indicated that mutation of Per2 is reported to cause a decrease of complex I activity and a higher NADH/NAD + ratio, thus impacting mitochondrial activity 29 . In addition, Per2 binds to complex IV to mediate mitochondrial respiratory function in endothelial cells following hypoxia 11 . Indeed, the Western Blot data establishes dysregulation of complex III–V protein levels in the AC16 cells with Per2 knockdown, suggesting a potential disruption of the mitochondrial electron transport chain. This is a rational explanation of Per2 knockdown impairing mitochondrial respiratory capacity in human cardiomyocytes. Notably, mitochondrial membrane potential is essential for preserving normal proton gradient, thus maintaining mitochondrial respiratory function. In this study, TNFα or H 2 O 2 significantly reduced ∆ψ M in human cardiomyocytes. Knockdown of Per2 further worsened TNFα- or H 2 O 2 -impaired ∆ψ M compared to control counterparts. This disrupted ∆ψ M might be another reason to explain why Per2 is important in regulating mitochondrial metabolic function. In addition, severe decrease in mitochondrial membrane potential results in changes of mitochondrial structure to release cytochrome C, triggering intrinsic apoptosis through the activation of caspases 30 . This may also explain why reduction of Per2 enhances TNFα-induced cell death in cardiomyocytes. Overexpression of Per2 via adenovirus provides heart protection from ischemia 31 . Daylight or intense light exposure increases cardiac Per2, leading to reduced myocardial damage following ischemia 5 , 32 . Intense light-upregulated Per2 overexpression also improves maintenance of endothelial barrier function via promotion of metabolic reprogramming of cellular adaptation to myocardial ischemia 11 . Considering the role of Per2 in modulating cell survival and mitochondrial function during stress from our current study and previous publications as discussed earlier, it is therefore logical that overexpression or delivery of Per2 is protective to prevent cell death in cardiomyocytes and ameliorate mitochondrial dysregulation following myocardia injury 5 , 33 , thus benefiting mitochondrial bioenergetics and cardiac function. We will explore the therapeutic potential of increasing cardiac Per2 to improve mitochondrial function in our future investigations. In summary, our findings provide the direct evidence to support that Per2 is important to protect mitochondrial function and cell viability in human cardiomyocytes during inflammatory and oxidative stress (Fig. 7 ). We speculate that delivery of Per2 protein to cardiomyocytes during myocardial injury could serve as a cardioprotective factor, possibly by supporting mitochondrial function and improving cell survival observed in this study.

During myocardial injury, inflammatory mediators and oxidative stress significantly increase to impair cardiac mitochondria. Emerging evidence has highlighted interplays between circadian protein—period 2 (Per2) and mitochondrial metabolism. However, besides circadian rhythm regulation, the direct role of Per2 in mitochondrial performance particularly following acute stress, remains unknown. In this study, we aim to determine the importance of Per2 protein’s regulatory role in mitochondrial function following exposure to inflammatory cytokine TNFα and oxidative stressor H 2 O 2 in human cardiomyocytes. Global warm ischemia (37 °C) significantly impaired complex I activity with concurrently reduced mitochondrial Per2 in adult mouse hearts. TNFα or H 2 O 2 decreased Per2 protein levels and damaged mitochondrial respiratory function in adult mouse cardiomyocytes. Next, mitochondrial membrane potential ( M ) using JC-1 fluorescence probe and mitochondrial respiration capacity via Seahorse Cell Mito Stress Test were then detected in Per2 or control siRNA transfected AC16 Human Cardiomyocytes (HCM) that were subjected to 2 h-treatment of TNFα (100 ng/ml) or H 2 O 2 (100 μM). After 4 h-treatment, cell death was also measured using Annexin V and propidium iodide apoptosis kit through flow cytometry. We found that knockdown of Per2 enhanced TNFα-induced cell death and TNFα- or H 2 O 2 -disrupted M , as well as TNFα- or H 2 O 2 -impaired mitochondrial respiration function. In conclusion, Per2 knockdown increases likelihood of cell death and mitochondrial dysfunction in human cardiomyocytes exposed to either TNFα or H 2 O 2 , supporting the protective role of Per2 in HCM during stress with a focus on mitochondrial function. Subject terms

Supplementary Information

Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-51799-w. Acknowledgements We thank the Indiana University Medical Student Program for Research and Scholarship (IMPRS) for supporting medical student research and thank the Hypoxia Core at the Indiana University Cooperative Center of Excellence in Hematology for allowing access to the Seahorse Bioscience XF-96 instrument. Author contributions Conceptualization, M.W., M.B.; methodology, M.W., M.B, O.A., A.Y. and J.L.; investigation, M.B, O.A., J.L. and M.W.; data analysis: M.B, O.A., J.L. and M.W.; interpretation of data, M.W., M.B, O.A., J.L., and A.Y.; writing—original draft preparation, M.W. and M.B.; writing—review and editing, M.B., J.L., O.A., and A.Y. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by National Institutes of Health (NIH) R01 HL155957 and R01 HL168282 (to M. Wang), as well as a Short-Term Training in Biomedical Sciences Grant from the NIH/NHLBI (T35 HL110854). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. Data availability The data presented in this paper are available by contacting Dr. Meijing Wang via meiwang@iupui.edu. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1290

oa_package/6b/7e/PMC10788343.tar.gz

PMC10788344

38221550

Introduction The development of new and effective substances against pathological bacteria is receiving a great deal of attention since there is a number of concerns about bacterial resistance to various current antibiotics or disinfectants 1 . Although antimicrobial agent resistance has been known for more than 50 years, it is still a significant factor in rising morbidity, death, and medical expense 2 . The overuse of antibiotics is thought to be the primary contributing factor, but inadequate infection control methods, extended hospital stays, admission to intensive care units, the use of invasive operations, and environmental discharge of antimicrobial substances without regulation are all contributors 2 . The key challenges of antibiotic therapy include overuse and misuse, multi-drug resistance, side effects, potential allergies, improper administration and the lack of new developments to treat infections (Ref). Even though improvements in the field of antibiotics have increased the average human lifetime, there are challenges which require novel and advanced solutions. Finding novel chemical materials with the distinct physicochemical properties needed for the synthesis of antibiotics is a major scientific challenge. Drug resistance can be described as a state of insensitivity or decreased sensitivity to drugs that ordinarily cause growth inhibition or cell death. Bacteria, fungi, viruses, and particularly parasites all exhibit high levels of antimicrobial resistance and such resistance could be innate or acquired 3 . Pseudomonas aeruginosa , Acinetobacter baumannii , and Gram-negative bacilli that produce carbapenemase are among the organisms that cause infections that may be extensively drug-resistant (XDR) or pan drug-resistant (PDR). Moreover, all FDA-approved antibacterial drugs, except for aminoglycosides, tigecycline, and polymyxins B or E, are resistant to gram-negative bacilli (GNB) 4 . However, the focus of this work is on bacterial resistance and possible solutions for it. Gram-negative bacteria are resistant to glycopeptides, while Gram-positive bacteria are resistant to aztreonams. Anaerobic microorganisms, including Enterococcus species, are resistant to aminoglycosides while Pseudomonas species are resistant to tetracycline and penicillin except ureidopenicillins. Staphylococcus species are found to be resistant to Penicillin. The global threat posed by pneumococcal resistance keeps growing, as it began with penicillin resistance and now displays resistance to macrolides and tetracyclines 5 . Therefore, it is of great importance to investigate alternative antibiotics which would be more active against broad-spectrum bacteria and cause fewer side effects along with no harm to the environment. Despite the new antibiotics being researched nanomaterials have attracted attention due to their high efficiency and effectiveness towards a broad range of bacterial species. Due to their size and capacity to damage cells through a variety of methods, nanoparticles have demonstrated antibacterial effectiveness towards a variety of diseases. Nanomaterials offer an intriguing way to restrict microbial development before human infection, in contrast to antibiotics, which are used to treat illnesses and infections in patients 6 . Nanostructure materials have been subjected to extensive research over the past ten years due to their unique physicochemical and biological properties 7 . This technology can be used for a range of novel applications, including cutting-edge fabric chemicals, waste water management, advanced pharmaceutical procedures, and food and agricultural production 8 – 10 . Due to their numerous bactericidal capabilities, straightforward production processes, good photo-responsive performance, etc., noble metal nanoparticles (NMNPs), particularly gold (Au), silver (Ag), and platinum (Pt), have drawn significant attention in the antimicrobial field 11 , 12 . Graphene oxide (GO) nanoparticles and other carbon-based nanomaterials, including fullerenes, carbon nanotubes (CNTs), particularly single-walled carbon nanotubes (SWCNTs), and carbon nanotubes (CNTs), have been found to exhibit strong antibacterial characteristics in recent studies 13 . Metal-based nanomaterials, such as Al 2 O 3 , CrO 3 , Fe 3 O 4 , SiO 2 , TiO 2 and ZnO 2 as well as quantum dots and different metallic nanoparticles like Ag, Au, and Pt. Such metal oxides have been discovered to be the underlying cause of conditions like oxidative stress, endothelial cell inflammation, apoptosis, and ecotoxicity 14 It has been discovered that nanomaterials come in a wide variety of shapes and structures such as spheres, plates, tubes, needles, sheets, etc. which can influence the overall antibacterial capacity 15 . On the antibacterial characteristics of metal oxide nanoparticles, there is scarce information available compared to existing publications on chemical properties 16 . ZnO in the nanoscale range has a wide range of forms and exhibits strong antibacterial activity against a wide range of bacterial species that have been researched extensively 17 , 18 . Due to their increased specific surface area and reduced particle size, which increases particle surface reactivity, ZnO-nanomaterials have appealing antibacterial capabilities 7 , 19 , 20 . ZnO doped with Boron and Zn doped CuO have been shown to act against Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumonia, and Escherichia coli 21 , 22 . ZnO and ZnO coupled with Cu and CuO have not only been reported to be antibacterial but also have been photocatalytically active in degrading methylene blue which is important in wastewater treatment 23 , 24 . Once within the bacterial cell, they interact with the surface and/or the core of the bacteria and exhibit specific bactericidal mechanisms 7 , 25 . CuO is another nano-metal oxide which has been researched for its ability to inhibit overall bacterial growth 25 – 28 (add reference Cymbopogon citratus). Nanoflowers, nanorods, nanoleaves, and nanoflakes are examples of hierarchical cupric oxide (CuO) nanostructures which show significant antibacterial activity 29 . It is assumed that materials containing Cu nanoparticles are capable of killing both Gram-positive and Gram-negative bacteria through the "attract-kill-release" pathway 30 . Reactive oxygen species (ROS) generation and the release of Cu ions from Cu nanoparticles are both thought to be responsible for the contact killing of bacteria 30 , 31 . Additionally, they inactivate the microbes by promoting oxidative stress reactions, destroying membrane integrity and binding to the proteins 29 , 31 – 35 . PEGs identified as Macrogols, is a polyether of repeated ethylene glycol units [-(CH 2 CH 2 O)n] 36 and it is renowned for their highly flexible structure, biocompatibility, amphiphilicity, lack of any steric obstructions, and high capacity for hydration 37 . PEGylation is known as the process of attaching one or more PEG molecules to substances used in treating or preventing disease, to modify the therapeutic efficacy 37 , 38 . Numerous scientists have investigated the antioxidant capacity of several nanomaterials such as CeO 3 , Fe 3 O 4 , TiO 2 and Se 6 . According to Saikia et al., nanoparticles of NiO and Fe 3 O 4 exhibit strong antioxidant properties. Interestingly, CuO nanoparticles coated with polyethylene-glycol (PEG) and polyvinyl-pyrrolidone (PVP) have shown increased biological activities including antioxidant properties compared to the naked CuO nanoparticles 33 whereas, CuO nanoparticles synthesized by thermal decomposition have shown effective antioxidant activity 35 . ZnO nanoparticles have also shown promising antioxidant activities. ZnO nanoparticles which were synthesized utilizing Cassia sieberiana 's methanolic root bark extract and the ZnO nanoparticles synthesized by Pichia kudriavzevii Yeast Strain have demonstrated potent antioxidant properties against the DPPH free radical scavenging assay 39 . However, the biocompatibility of those nanomaterials remains the challenge demarcating applicability of them in the biological systems. Hence, it is significant to determine a method of improving the biocompatibility of the nanomaterials to improve the overall effectiveness and efficiency. In this study, we report the antibacterial activity and antioxidant activity by DPPH radical scavenging activity of PEG-coated ZnO–CuO nanocomposite on Escherichia coli , Pseudomonas aeruginosa, Klebsiella pneumoniae and Staphylococcus aureus. ZnO–CuO nanocomposites were functionalized with PEG to enhance the biocompatibility of the nanocomposite which increases the cell contact and cell uptake. The possible antibacterial mechanisms of PEG-coated ZnO and CuO nanomaterials are discussed in detail. To our knowledge, the antibacterial activity and the possible mechanisms of ZnO and CuO nanomaterials synthesized with PEG functionalization in the proposed proportions and with the co-precipitation method have not been reported.

Materials and methodology Chemicals and materials CuCl 2 and ZnSO 4 were procured from Sigma Aldrich (UK), NaOH pellets were purchased from Sisco Research Laboratories (Pvt) Ltd, India, PEG was purchased from HiMedia Leading Biosciences Company, Muller Hinton Agar was purchased from HiMedia Laboratories (Germany), Luria Bertani Broth (LB broth) was purchased from HiMedia Laboratories (Germany) and Deionized water (DI), with resistivity greater than 18.0 MΩ.cm (Millipore Milli-Q system), was used in the experiments. All of the chemicals utilized in the experiments were of analytical grade and were used without further purification. Synthesis of nanocomposites coated with PEG Samples were synthesized in different ratios of ZnO and CuO as follows: ZnO: CuO, 1:1, 1:2, 2:1, and is expressed as pure ZnO, Zn: Cu(1:1), Zn: Cu(1:2) and Zn: Cu(2:1) in the text. Each metal salt was weighed to prepare the above-mentioned ratios and they were dissolved in a minimum amount of deionized water until a completely dissolved solution was obtained. For example, 16.147 g of ZnSO 4 was dissolved and mixed with 15.961 g of CuSO 4 to prepare Zn:Cu (1:1) composite. PEG powder (2 g) was dissolved in 100 ml of deionized water to prepare a 2% (w/w) solution. Then metal ion solutions were added dropwise to the PEG solution while stirring. Once the solution was homogenized in a sonicator for 30 min, 1% NaOH solution was added to the mixture dropwise and stirred for two hours until a dark blue precipitate appeared except for ZnSO 4 where a white precipitate was obtained. Then stirring was continued overnight where a black colour precipitate was obtained except for pure ZnO. Then the solutions were hydrothermally treated in a hydrothermal via at 180 °C for 15 h. Then the obtained samples were filtered and washed with deionized water until the samples were free of Cl − and SO 4 2− ions, and a neutral pH was achieved. The washed samples were then oven-dried at 100 °C until completely dried and stored for further analysis. Antibacterial activity Preparation of media The required quantities of media were prepared with Muller Hinton agar and Luria Bertani broth using deionized water and sterilized in the autoclave. Microbial strain and inoculum preparation The test organisms, gram-negative Escherichia coli , Pseudomonas aeruginosa , Klebsiella pneumoniae, and gram-positive Staphylococcus aureus , were procured from Medical Research Institute, Sri Lanka. For preparing the inoculum, Escherichia coli , Staphylococcus aureus , Pseudomonas aeruginosa , and Klebsiella pneumoniae were cultured in Luria Bertani broth medium at 37 °C overnight. The microbial cultures were sub-cultured and overgrown 24 h prior to the assay and later diluted and adjusted the concentrations to obtain a microbial suspension of 5 × 10 5 colony-forming units (CFUs)/ml using the spectrophotometer for further analysis 40 , 41 . Agar well diffusion method Nanocomposites were weighed (20, 40 and 60 mg), and sonicated to disperse in Dimethyl sulfoxide (DMSO) for 1 h. The Mueller Hinton Agar plate surface was inoculated by spreading the adjusted microbial inoculum of 5 × 10 5 colony-forming units (CFUs)/ml over the entire agar surface via streaking. Holes wich were punched aseptically with a sterile cork borer and volume (70 μL) of the antimicrobial agent solution of desired concentrations; 20, 40 or 60 mg in 1 ml of DMSO was introduced into the wells 42 . A standard antibiotic (amoxicillin) and Dimethyl sulfoxide (DMSO) were also introduced into one well each as a positive and negative control, respectively. Then the agar plates were incubated at 37 °C for about 18 h and the zones of inhibition were measured in mm. Three replicates were prepared for each sample and each bacterial species 43 . The zone diameters were measured with the use of a metric ruler from the back of the Petri plate, while it was resting on a black, nonreflecting, flat surface, illuminated by a light source. Pairs of measurements were taken for each petri plate in mm and the average value was determined 44 . The antibacterial testing for PEG polymer was conducted via the agar well diffusion method as explained above. PEG polymer solutions of 20, 40 or 60 mg/ml concentrations were prepared by measuring the respective weights and dissolving them in DMSO solvent. Amoxicillin was used as a positive control while DMSO was used as a negative control in the agar well diffusion assay. Minimum inhibitory (MIC) and minimum bactericidal concentration (MBC) evaluation The antibacterial agents prepared were diluted into various concentrations, 0.3125, 0.625, 1.25, 2.5, 5, 10, 20, and 40 mg/ml, and a control concentration of 0 mg/ml in sterile Eppendorf tubes. Using a micropipette, 1 ml of each microbial culture was to be tested, and (0.5 McFarland standard) was inoculated into test tubes containing 2 ml of the various concentrations of the antibacterial agent in Luria Bertani broth for determination of MIC 45 . MBCs were determined by performing serial dilutions of the samples in DMSO and plated on to nutrient agar plates. In detail, 2 μL of the treated samples containing the nanomaterial and the test organism from each test tube, was inoculated into Muller Hinton agar plates for the determination of MBC. No nanomaterial was introduced to the control Muller Hinton agar plate. Both the test tubes and the plates were then incubated at 37 °C for 18 to 24 h and thereafter observed for the growth of bacteria and viable count, respectively 46 . The minimum incubation concentration (MIC) of nanocomposite suspension was determined as the concentration at which there was no visible turbidity. In contrast, MBC was determined as the lowest concentration of nanocomposite suspension that prevented the growth of bacteria yielding three log reductions (99.9%) on spread plates 41 . Time-kill synergy assay To determine the antibacterial activity of the synthesized nanomaterials against the test bacterial pathogens, which were cultured at a concentration of 5 × 10 5 colony-forming units (CFUs)/ml, 9 ml of LB broth and 1 ml of the nanosuspensions prepared were mixed. The time-kill synergy assay was carried out while the samples were kept in a rotary shaker at 200 rpm. The optical density was measured at intervals of 1 h for a total of 12 h using 600 nm wavelength. Turbidity was shown on a graph against time. To investigate for any indications of antibacterial actions of the synthesized nanomaterials, the growth curve thus obtained was examined. The positive control utilized was amoxicillin. The negative control was DMSO; the solvent used to dissolve the sample 47 . The time-kill synergy assay was performed by the broth macro dilution method. Each pathogenic bacterial strain was tested against each nanocomposite. The time-kill assay was conducted with a final inoculum of approximately 5 × 10 5 CFU/ml in a final volume of 10 ml. The concentration of the bacterial culture was verified with the spectrophotometer at 600 nm. LB broth and nano suspension from each sample were mixed in 9:1 ratio to obtain the 10 ml final volume in test tubes shaken continuously on an orbital shaker at 200 rpm and incubated at 37 °C. The optical density of each test tube was measured at intervals of 1 h for a total of 12 h using 600 nm wavelength. Turbidity was tabulated on a graph against time. To investigate the antibacterial actions of the synthesized nanomaterials, the growth curve obtained was examined. The positive control utilized was amoxicillin. The negative control was DMSO; the solvent used to dissolve the sample. Determination of antioxidants by DPPH radical scavenging activity The nanocomposites' free RSA was determined using the 1,1-diphenyl-2-picryl hydrazyl (DPPH) method. The stock solution was prepared by dissolving 24 mg of DPPH in 100 ml of methanol. The solution was filtered and used for the subsequent analysis. Methanol was used to prepare varied concentrations of synthesized nanomaterial ZnO, Zn:Cu 2:1, Zn:Cu 1:2 and Zn:Cu 1:1 (20 mg/ml). DPPH solution (500 ul) was mixed with 3 ml of the nanomaterial solution and incubated in the dark for 30 min which was exposed to sunlight after that. Absorbance was recorded at 517 nm for all three concentrations. 3 ml methanol mixed with 500 ul of DPPH solution was used as the positive control. The percentage (%) of inhibition was calculated to determine the antioxidant activity using the formula below: Ac absorbance of the control; As absorbance of the sample.

Results FT-IR analysis FT-IR spectra were collected to confirm the coating of PEG to the nanomaterials (supplementary Fig. 1 ). The C-O bond stretching frequency of aliphatic ether of PEG appeared at 1157 cm −1 and the C-H bending of the same appeared at 1458 cm −1 indicating the coating of PEG to the nanomaterials. Additionally, the peak at 2360 cm −1 is ascribed to the O = C = O of CO 2 and the peaks in the range of 3600–3800 cm −1 are attributed to the stretching frequency of O–H. XRD analysis The XRD patterns were collected to determine the crystallographic orientation of the synthesized nanomaterials (Fig. 1 ). The XRD pattern of the ZnO nanomaterial consisted of the hexagonal wurtzite crystal structure. The pattern comprised of peaks at 2θ of 32.07, 34.74, 36.55, 47.83, 56.85, 63.13, 66.58, 68.19, 69.35, 73.26 and 77.70° which correspond to (100), (002), (101), (102), (110), (103), (200), (112), (201), (004) and (202) planes and the lattice constants were calculated to be a = b = 0.324 nm and c = 0.521 nm (JPCDS-36–141). The d spacing calculated by λ = 2dsinθ of the (101) plane represented by the peak at 36.55° is 0.2456 nm, the crystallite size calculated by the Debye–Scherrer formula (L = Kλ/β cosθ) is 48.50 nm and the lattice strain is 0.00238. XRD patterns of the composite materials consisted of peaks at 32.84, 35.84, 39.12, 48.64, 53.30, 61.75, 66.38 and 68.40, 72.40 and 75.16° additional to the peaks correspond to the ZnO phase and they are attributed to (110), (002), (111), (-202), (020), (-113), (-311), (220), (222) and (311) planes of monoclinic CuO (JCPDS-48–1548). The peak at 35.84° with the highest intensity was selected for further calculations. The interlayer distance of the (002) plane, the crystallite size and the lattice strain are calculated to be 0.2504 nm, 40.52 nm and 0.00290, respectively. The synthesized nanomaterials are composites of ZnO and CuO at different ratios. The respective parameters calculated from XRD data are tabulated in Table 1 . The crystallite size of CuO decreased and the lattice strain increased with increasing weight ratio of CuO in the CuO–ZnO composite. However, the crystallite size of ZnO increased and the lattice strain decreased with increasing weight of CuO. Further, it is evident that the crystallographic orientation of the composite hasn’t been changed with increasing weight ratio of CuO in the composite and no other crystal natures of oxides of Cu were observed either. The composites are free of crystalline impurities as shown by the absence of peaks corresponding to such impurities in the XRD patterns. SEM analysis SEM images were collected to study the morphology of the synthesized nanomaterials at the macroscale. Flowers-like architectures were observed in the SEM image of pure ZnO (Fig. 2 a). Upon addition of NaOH, [Zn(OH − ) 4 ] was formed and further during the hydrothermal treatment ZnO crystal phase was formed. The nucleation and the crystal growth processes control the morphology of the materials where the nucleation occurs followed by the crystal growth. The quantity of the nuclei produced in a weak alkaline solution is rather low, but more crystal growth occurs. Therefore, the ZnO crystal grows along the c-axis around the smaller number of seeds into a petal-like crystal forming a flower-like nanostructure. The width of the petal was about 45 nm. However, a perfect flower-like structure was not established everywhere and only the petal-like structures were present without organizing around a center ZnO seed. This could be due to the polyethylene glycol polymer co-existing during the formation of the nanostructure which interferes with the proper formation of the flower-like structure due to the bulkiness of the polymer. The morphology of the CuO–ZnO composites clearly shows two different architectures where proper flower-like ZnO are located with CuO rods. As shown in the SEM image of Zn:Cu (2:1) (Fig. 2 b) sharp CuO nanorods with a width in the range of 50–230 nm were present with bulky ZnO flower-like architectures. The SEM image of Zn:Cu (1:1) (Fig. 2 c) isolated nanorods were not present instead they were aggregated randomly and the images were abundant with CuO nanorods rather than with ZnO flower-like structures. Interestingly, the sharp edges of the rods were not observed and the non-uniform wave-like edges were present. ZnO flower-like structures were completely absent in the SEM image of Zn:Cu (1:2) (Fig. 2 d) and are abundant with rods with some rice panicle-like structures. Rods of pencil-like architectures of CuO were present with sharp edges and the rice panicle-like structures of ZnO were present. Rods were relatively abundant compared to corn-like structures as the incorporated Cu is higher in Zn:Cu (1:2). TEM analysis TEM images were acquired to further study the morphology of the materials. The 2-D structure of the flower-like arrangement is visible in the TEM image of ZnO (Fig. 3 a). However, the features that are more apparent in the 3D structure of the flower-like structures in the SEM images were not prominently present in the TEM image because the detailed structure including the surface roughness and the surface imperfections are more apparent due to the scattering effect of the secondary electrons. The TEM images of Zn:Cu (2:1) and Zn:Cu (1:1) (Fig. 3 b,c) show the CuO nanorods and not the ZnO flower-like arrangements. The TEM image of Zn:Cu (1:2) nanocomposite (Fig. 3 d) shows the sharp needle-like nanorods with disorganized structures of ZnO deviating from the flower-like arrangement. The supplementary Figs. 2 (a) and (b) of Zn:Cu (2:1) and Zn:Cu (1:1) show the mesoporosity developed in the synthesized nanomaterials due to the biopolymer PEG used in the synthesis. XPS analysis XPS survey spectra of the synthesized nanomaterials were collected to identify the surface elemental composition while the higher resolution spectra were collected to study the surface chemical environments of the individual elements in detail. The survey spectra of ZnO, Zn:Cu (2:1), Zn:Cu (1:1) and Zn:Cu (1:2) are shown in Fig. 4 a–d, respectively. The survey spectrum of ZnO shows the presence of Zn, O and C and the survey spectra of the composites exhibit the presence of Cu in addition to those elements. The higher resolution spectra of C 1 s of ZnO shown in Fig. 4 e are deconvoluted four peaks at 284.5, 286.11,287.86 and 289.56 eV which are assigned to sp 2 hybridized C–C, C-O-Zn 2+ , C = O and π-π interactions, respectively. The higher resolution spectra of C 1 s of the nanocomposites Zn:Cu (2:1), Zn:Cu (1:1) and Zn:Cu (1:2) (Fig. 4 f–h, respectively show peaks at 284.5, ~ 285.3, ~ 286.3 and ~ 288.5 eV which are attributed to C–C, C-O-Cu 2+ , C-O-Zn 2+ and C = O, respectively. Oxygen in ether bond (C–O–C) of PEG forms dative bonds with both Zn 2+ and Cu 2+ creating two different chemical environments in the C-O bond of the composites. The higher resolution spectrum of O 1 s of ZnO (Fig. 4 i) is deconvoluted to two peaks at 531.36 and 532.86 eV which are ascribed to Zn 2+ -O and OH/H 2 O, respectively. The higher resolution spectra of O 1 s of the Zn:Cu (2:1), Zn:Cu (1:1) and Zn:Cu (1:2) nanocomposites shown in Fig. 4 j–l, respectively, are deconvoluted to three peaks at ~ 530.35, ~ 531.8, ~ 533.2 eV, which are assigned to Cu 2+ -O, Zn 2+ -O and OH/H 2 O, respectively. The ratio between the area under the curve of Zn 2+ -O: Cu 2+ -O of Zn:Cu (2:1), Zn:Cu (1:1) and Zn:Cu (1:2) are 9.6, 2.2 and 0.8, where the area under the curve of Cu 2+ -O dramatically increased with increasing Cu content in the composite. The higher resolution spectrum of Zn 2p of ZnO (Fig. 4 m) is deconvoluted to three peaks at 1022.6, 1040, and 1045.6 eV which are attributed to 2p 3/2 and 2p 1/2 , respectively. The higher resolution spectra of Zn 2p of Zn:Cu (2:1), Zn:Cu (1:1) and Zn:Cu (1:2) are shown in Fig. 4 n–p, respectively. Two different chemical environments were observed in both 2p 3/2 and 2p 1/2 peaks representing the tetrahedral and octahedral geometries of Zn 2+ in coordination with oxygen. The higher resolution spectra of Cu 2p of Zn:Cu (2:1), Zn:Cu (1:1) and Zn:Cu (1:2) are exhibited in Fig. 4 q–s, respectively. Splitting of Cu 2p 3/2 and 2p 1/2 into two sub-peaks as shown in the figures suggests the presence of Cu 2+ in two different chemical environments which are the Cu 2+ being complexed with PEG appearing at the low binding energy and the Cu 2+ appeared at higher binding energy represents the Cu 2+ present in the lattice. Raman spectroscopic analysis The Raman spectra were acquired to confirm the crystallography of the nanomaterials determined by the XRD patterns. The Raman spectra of the synthesized nanomaterials are shown in Fig. 5 . The Raman spectrum of ZnO nanomaterial shows Raman bands at 327, 382, 432, 574, and 657 cm −1 . The basic phonon modes of hexagonal ZnO appeared at 382, 432, and 574 cm −1 and are attributed to the A 1T , E 2H and A 1L /E 1L , respectively, while the muti phonon scattering modes are represented at 327, and 657 cm −1 which are assigned to the E 2H -E 2L and E 2L + B 1H . The Raman spectrum of Zn:Cu (1:2) shows additional Raman bands at 275 and 356 cm −1 representing the A g and B g modes of CuO 48 , 49 . The Raman bands of pure ZnO have been shifted to the low Raman shifts indicating the coupling of ZnO with CuO. Antibacterial activity by agar well diffusion method The metal oxides and metal oxide nanocomposites showed antibacterial activity on both gram-positive and Gram-negative bacterial strains tested. The zone of inhibition of all four samples against the test organisms is shown in Fig. 6 . Interestingly the metal oxide nanocomposites were found to be more sensitive towards the Gram-positive strain Staphylococcus aureus, than the Gram-negative strains; Escherichia coli , Pseudomonas aeruginosa and Klebsiella pneumoniae as depicted in Fig. 7 a. For example, the diameter of the zone of inhibition for Staphylococcus aureus by ZnO nanomaterials is 25.67 ± 0.58 mm while the same for Escherichia coli , Pseudomonas aeruginosa and Klebsiella pneumonia are determined to be 14.33 ± 0.58 mm, 15.17 ± 0.29 mm and 12.00 ± 0.5 mm, respectively. Among the composite nanomaterials Zn:Cu 2:1 showed the highest antibacterial activity for Staphylococcus aureus and Pseudomonas aeruginosa with diameters of 18.00 ± 1.73 mm and 12.17 ± 0.29 mm, respectively, while the antibacterial activity of all the composites were quite similar on Klebsiella pneumonia with an average diameter of 9.11 ± 0.25 mm. A different behaviour was observed for Escherichia coli where the highest antibacterial activity among the composite nanomaterials was obtained in the presence of Zn:Cu 1:2 (12.83 ± 0.29 mm) and the least was found to be with Zn:Cu 2:1 (10.50 ± 0.50 mm). The zone of inhibition and hence the antibacterial activity of the nanomaterials decrease with a decreasing proportion of Zn 2+ for Staphylococcus aureus , Pseudomonas aeruginosa and Klebsiella pneumonia . However, such a trend was not observed for Escherichia coli . Figure 7 b shows the zone of inhibition produced by different metal oxide nanoparticles against both Gram-positive and Gram-negative bacterial strains. The effect of the concentration of the nanocomposite on the inhibition of the bacteria was further investigated varying the concentration as 20, 40 and 60 mg/ml. The diameters of the inhibition zones are tabulated in Table 2 . The inhibitory action of the nanocomposites on the growth of E.Coli increased with increasing concentration in all the composites. For example, the diameter of the inhibition zone increased from 10.50 ± 0.50 mm with 20 mg/ml to 12.83 ± 0.29 mm with 40 mg/ml and to 13.50 ± 0.50 mm with 60 mg/ml when Zn:Cu 2:1 is used as the nanocomposite. A similar trend was observed with all the composites. In general, all the antibacterial mechanisms applicable and will be discussed in section " Antibacterial activity by agar well diffusion method " have increasingly affected the bacteria with increasing doses of the antibacterial reagent which is the nanocomposite. The same antibacterial behaviors were observed for Pseudomonas aeruginosa and Klebsiella pneumonia where only the inhibitory action decreased with increasing concentration of Pseudomonas aeruginosa with ZnO nanomaterial. A different behaviour was observed for Staphylococcus aureus where the antibacterial activity of all the nanocomposites decreased moving from 20 to 40 mg/ml and again increased when the concentration was increased to 60 mg/ml. The diffusion of the nanomaterials from the well to the medium has lowered when the concentration of the nanocomposite increased from 20 mg/ml to 40 mg/ml lowering the physical damage caused to the bacterial species and hence resulting in lower antibacterial activity. However, when the concentration is increased from 40 mg/ml to 60 mg/ml, though the physical damage caused by the nanomaterials through the restriction of nanoparticle diffusion lowers the antibacterial activity, other antibacterial mechanisms profoundly become active and more prominent and cause an increase in the antibacterial activity on Staphylococcus aureus . Time-kill synergy assay The antibacterial activity of the composites was then evaluated in the liquid medium through the determination of the time-kill synergy assay of the bacteria tested. In-vitro bacterial growth is inhibited by ZnO and CuO nanomaterials in similar studies 7 , 25 , 27 , 43 , 47 , 50 – 54 . The concentration of the nanomaterials (20 mg/ml) demonstrated significant antibacterial action against gram negative Escherichia coli , Pseudomonas aeruginosa and Klebsiella pneumoniae . Gram positive Staphylococcus aureus was similarly suppressed at concentrations of 20 mg/ml. Figure 8 displays the time-kill curves obtained from the tested bacterial pathogens against all of the investigated bacterial nanomaterials. Bacterial suspensions in LB broth were used in a time-kill kinetic test for 12 h with the addition of nanomaterials (20 mg/ml) and the observations were taken at 600 nm. MIC and MBC assay The MIC and MBC values were determined for all four test microorganisms. MIC is defined as the lowest concentration of a material that can inhibit the visible growth of an organism; whereas MBC is defined as the lowest concentration of a material that inhibits the growth of an organism in batch cultures, this can be determined from broth dilution MIC tests by subculturing to agar media without antibiotics 7 , 47 , 51 . The obtained MIC, MBC, and MBC/MIC values are shown in Table 3 . The antibacterial activity was further evaluated based on the MBC/MIC ratio. If the MBC/MIC ratio ≤ 4, the effect is bactericidal and if the MBC/MIC > 4, the effect is bacteriostatic 55 . The MBC/MIC ratios are shown in Table 3 . The MBC/MIC ratio for E. coli in the presence of ZnO, Zn:Cu 1:1 and Zn:Cu 1:2 were greater than 4 suggesting that they cause bacteriostatic effect while Zn:Cu 1:2 showed the bactericidal effect on the growth of E. coli . Similarly, ZnO and Zn:Cu 1:1 were bacteriostatic against Pseudomonas aeruginosa while Zn:Cu 2:1 and Zn:Cu 1:2 exhibited bactericidal effect . All the nanomaterials showed bactericidal effect on both Staphylococcus aureus and Klebsiella pneumoniae . Interestingly, Zn:Cu 2:1 showed the bactericidal effect on all the bacterial strains tested. PEG functionalization In this study, the antibacterial activity in terms of zone of inhibition of PEG-coated ZnO nanomaterials for Escherichia coli , Pseudomonas aeruginosa , Klebsiella pneumoniae and Staphylococcus aureus (14.33 ± 0.58, 15.17 ± 0.29, 12.00 ± 0.50 and 25.67 ± 0.58 mm, respectively,) was found to be significantly higher than the naked ZnO nanomaterials (10.83 ± 1.04, 13.00 ± 2.60, 10.83 ± 1.15 and 10.33 ± 1.89 mm, respectively,) confirming the capability to enhance the biocompatibility of the fabricated nanomaterials against tested microorganisms.

Discussion Antibacterial activity by agar well diffusion method The agar well diffusion method was performed to evaluate the antibacterial activity of the synthesized nanocomposites. Based on prior research findings and the preliminary trials conducted, it was found that the inhibition zone is greater in the well-diffusion method than in other assays like disk diffusion, hence the agar well-diffusion test was used for this study. This is so that the well-diffusion test may increase the antibacterial activity by doubling the volume of nanomaterial suspensions and increasing nanomaterial diffusion through the medium 25 , 56 . To our knowledge, no research has been published about the antibacterial activity of the ZnO and CuO nanomaterials synthesized with PEG functionalization in the ratios and co-precipitation method used in this study. Nevertheless, numerous publications have cited that metal nanomaterials show antibacterial activity and that PEG functionalization improves the bactericidal effect of nanomaterials 25 , 51 , 56 – 59 . Depending on the type of microorganism, different metal oxide nanoparticles have different levels of microbial sensitivity. Understanding the distinctions between the cell walls of Gram-positive and Gram-negative bacteria is crucial since the primary toxicological effect that antimicrobial substances exert on bacteria occurs when they come into direct contact with the cell surface 28 . The structure of the Gram positive and Gram negative cell walls is illustrated in Fig. 9 The surface of bacteria, both Gram-positive and Gram-negative, is negatively charged 27 . The peptidoglycan layer of gram-positive bacteria is composed of linear chains that alternate N-acetylglucosamine (NAG) and N-acetylmuramic acid (NAM) residues. These chains are linked together by an arrangement of 3 to 5 amino acids that cross-link one another to form a cohesive mesh. Most Gram-positive bacteria also have negatively charged teichoic acids (with substantial phosphate groups) that stretch from the cell wall to the surface. On the other hand, gram-negative bacteria have a significantly more complex structure. Gram-negative bacteria have an outer membrane made of phospholipids and partly phosphorylated lipopolysaccharides (LPS), in addition to the thin layer of peptidoglycan, which helps to enhance the negative surface charge of their cell envelope 60 . Electrostatic interactions cause positively charged nanoparticles to be attracted to the surface of negatively charged bacterial cell walls. Positively charged metal-based nanoparticles, on the other hand, form a firm bond with membranes, disrupting cell walls and therefore increasing permeability 61 . Additionally, metal ions released by nanoparticles from the extracellular environment can penetrate cells and interfere with biological processes 61 . When the metal ions are free to interact with biological components like proteins, membranes, and DNA, cell functions are disrupted 61 . Reactive oxygen species (ROS) can be produced inside the cell by metal ions or nanoparticles 62 . A variety of ROS can be formed by nanomaterials in cells, i.e.,·O 2 − , 1 O 2 , OH, and H 2 O 2 which can take part in physiological and pathological cellular processes 62 – 64 . The cells have a variety of repairing and antioxidant mechanisms for defence and tripeptide glutathione is one of the most effective antioxidants 62 . Upon exposure to ROS glutathione is oxidized as a result of the oxidative stress it causes, and bacteria's antioxidant defence system against ROS is suppressed. Thus, the glutathione depletion may be a defining sign of the negative effects imposed on by nanomaterials' prooxidative actions in cells 62 , 65 . Hence the overall antibacterial effect will be caused by the metal nanomaterial, the ROs generated, and the metal ions as shown in Fig. 10 . Furthermore, it was found that pure ZnO nanomaterials show superior antibacterial activity against the four bacterial species tested compared to the composites synthesized as shown in Fig. 7 b while the nanoparticles are located in the wells, the bacteria are inoculated on the surface of the MHA media. Therefore, either the nanoparticles or the metal ions of the nanoparticles should diffuse through the solid agar medium to interact and inhibit the growth of bacteria. It is difficult to assume that the flower-like arrangement of ZnO and CuO rods is diffusing through a solid medium due to the size and corresponding steric hindrance. Hence, it should be the metal ions, Zn 2+ and Cu 2+ which should easily diffuse through the medium. Strong coordination bonds can be formed between metal ions with the N, O, or S atoms that are prevalent in organic molecules and biomolecules. These biomolecules' functioning can be impacted by the binding of metal ions with them. Metal ion-associated antibacterial medicines frequently exhibit broad-range activity since the binding relationship between metal ions and biomolecules is typically nonspecific 30 . Metal ions disrupt the cell wall and the cytoplasmic membrane and once they enter the bacterial cell, they denature the ribosomes and interfere with the protein synthesis. Further, the metal ions would interrupt ATP production because metal ions deactivate respiratory enzymes on the cytoplasmic membrane. By altering the charge balance of bacteria, zinc ions can cause them to undergo apoptosis 66 (Fig. 11 ). Bacterial cells are affected by Cu 2+ ions leading to microbial growth inhibition. Recently, the use of Cu nanoparticles or CuO nanoparticles as antibacterial agents has been investigated 67 , 68 . Recently Cu nanoparticles have been incorporated into polymers such as starch hydrogels and functional polymer coatings which would show broad-spectrum antimicrobial activity 69 , 70 . Both ROS generation and release of Cu ions from Cu nanoparticles are considered to be responsible for contact killing of bacteria, and it is presumed that Cu nanoparticles-incorporated materials are capable of eradicating both Gram-positive and Gram-negative bacteria through the "attract-kill-release" route. Additionally, it has been discovered that Cu nanoparticles-incorporated coatings can also inhibit E. coli biofilm formation on the surfaces, which is important for the prevention of infections. Although CuO nanoparticles have been shown to have antibacterial activity, the stability of Cu nanoparticles in the ambient air and their rapid oxidation could pose a challenge to their practical usage 30 . This could be the possible reason for the reduced zone of inhibitions given by Cu-incorporated nanocomposites compared to ZnO alone. Additionally, Zn 2+ ions play an important part in many physiological functions, yet at certain levels, they are harmful to cells. Releasing of zinc ions in media comprising ZnO nanoparticles and bacterial cells is one of the key antibacterial mechanisms for ZnO nanoparticles 18 , 26 , 71 – 73 . It appears that different cellular targets harbouring a variety of reactions and responses are related to the mode of antibacterial action of Zn 2+ ions 74 , 75 . Zn 2+ is known as a sulfhydryl reactive agent, which can form bonds with sulfhydryls (–SH) in cells which causes inhibition of growth in cells and cell death 76 . It has been discovered that the metal oxide nanomaterial complex ions get released in an aqueous medium and it depends on both the dissolving and adsorption processes of the nanomaterial. While the CuO nanomaterial antibacterial impact arises from both the released Cu 2+ and the CuO particles, the ZnO nanomaterial’s antibacterial effect is mostly due to the released Zn 2+ 7 . The dissolution rate of ZnO nanoparticles is significantly higher than the other CuO nanoparticles 77 , 78 . In a similar study, it was shown that 1–4.5 mg/L of Zn 2+ were detected at the ZnO concentration of 5.0 mg/L, which was close to the reported aqueous solubility of ZnO (1.6–5 mg/L) 78 . Additionally, it was discovered that over time, the amount of dissolved Zn 2+ in ZnO suspensions increased which was similar to how the bactericidal effects of both ZnO suspensions and ZnO supernatants changed, indicating a link between the Zn 2+ release and the antibacterial properties of ZnO nanoparticles 78 , 79 . Because the dissolution of ZnO is greater than that of CuO and hence, the concentration of Zn 2+ diffuse through the agar medium would be higher than that of Cu 2+. Moreover, the amount of Zn 2+ diffused from a given weight of the nanomaterial in the composites would be lesser than that from the pure ZnO. Hence, the antibacterial activity of pure ZnO has resulted to be greater than that of CuO. However, it should also be noted that Gram-positive bacterial strain, Staphylococcus aureus had the highest inhibition-zones, 44%, 41% and 53% higher than Gram-negative bacterial strains Escherichia coli , Pseudomonas aeruginosa and Klebsiella pneumoniae , respectively, in the case of ZnO nanoparticles. This observation suggests a higher Gram-negative strain resistance/tolerance against the ZnO functionalized with PEG, over Gram-positive bacterial strains. This finding is in agreement with similar studies which reported that the ZnO nanoparticle effect is more pronounced against Gram-positive bacterial strains than Gram-negative bacterial strains 7 , 80 . Time-kill synergy assay The time-kill curve of nanomaterials against all of the studied bacterial pathogen strains demonstrated time-dependent rapid bactericidal action, which directly affected the bacterial cells before they reached the stationary phase. The growth curves of bacteria exposed to nanomaterials show that they can inhibit both bacterial growth and reproduction. We have demonstrated that synthesized nanomaterials can inhibit the growth of Gram-negative and Gram-positive bacteria using MIC tests, MBC tests and conventional growth curves. All of the investigated bacterial development was proven to be blocked or slowed down by Cu:Zn 1:1 nanomaterial during the lag phase and log phase. There is a rapid rise in cellular metabolism during the lag phase leading to the active production of cellular macromolecules, primarily enzymes 81 . Cells begin consistently dividing during the log (exponential) phase via the binary fission process. The culture grows at the highest rate possible, exponentially. In other words, the increase in the number of cells is proportional to the size of the current population: where n is the number of bacteria present in the culture medium at time t and α is a constant known as the "specific growth rate." Integration yields the well-known logarithmic growth relation: where n 0 is the initial number of bacteria at a time t 0 when the lag phase concludes or the log phase begins, and n 0 is the initial number of bacteria at that moment. Thus, below is the formula for the generation time, often known as the "doubling time," (τ) of the cell population 82 . Because the specific growth rate α, and the number of bacterial cells at the point of completion in lag phase n, change due to the bactericidal effect of metal oxides nanocomposites, "doubling time," (τ) may also be changed in the media where synthesized nanomaterials are introduced in comparison with the non-treated control. Moreover, distinct phases of a typical bacterial growth curve have also been affected by the contact of nanomaterials synthesized. Ultimately a bacterial cell size that is appropriate for a particular environmental situation and the developmental fate is achieved by the coordination of cell growth and division 83 . Once that coordination is disrupted the developmental fate is influenced. These findings suggest that synthesized nanomaterials are highly efficient in the lag and log phases against all of the investigated bacterial pathogens. The Zn:Cu (1:1) sample showed the highest antibacterial activity against all the bacterial species tested being different to ZnO which showed the highest antibacterial activity in the agar well diffusion method. CuO needle-like nanorods perforate the cell wall and cell membrane and get into the bacterial cell easily due to the size and the shape of the nanomaterial in which the diameter of the nanorods is in the range of 50–230 nm where they can easily pass through the channels of which the diameter is in the micrometer level. Further, flower-like ZnO materials also cause physical damage to the bacterial cells. However, penetration of such nanostructures into the cells is not feasible due to the steric hindrance of them. The antibacterial mechanisms of the nanocomposites in the liquid medium are mainly contributed by the metal ions effect and the damage caused by the CuO nanorods. Metal nanopales due to their small particle size and large surface area have contributed to increasing their antibacterial action and cause cytotoxicity in bacteria 84 . The metal ions Zn 2+ and Cu 2+ cause inhibitory effects on the bacteria via different mechanisms as described above. The contribution from both effects is equally effective when Zn:Cu (1:1) is used as the nanomaterial giving the maximum antibacterial effect. The other composites, Zn:Cu (2:1) and Zn:Cu (1:2) are less effective than the Zn:Cu (1:1) because the contribution from one effect is lesser than the other in both circumstances. The effect of metal ions especially of Zn 2+ is greater when Zn:Cu (2:1) is used and the effect of CuO nanorods is higher once Zn:Cu (1:2) is used as the antibacterial agent. Pure ZnO is contributed mainly by the release of the Zn 2+ and the physical damage caused to the bacterial cells by the collisions of ZnO with bacterial cells may have also contributed. Since Zn 2+ can only pose the bacteriostatic effect on microorganisms it is evident that the ZnO flower-like nanomaterials and the ROs generated from Zn nanomaterials have also contributed to the overall inhibition of bacteria 74 . Aquatic ZnO-nanomaterials suspensions have been reported to result in an increased level of ROS. ROS production has been identified as one of the primary sources of nanotoxicity in many studies 85 – 88 . The antibacterial activity has been attributed to the release of ROS onto the surface of ZnO-nanomaterials under UV and visible light, and the ROS release resulted in the death of bacteria. The researchers presented the following explanation for the generation of ROS (OH-, H 2 O 2 , and O 2 2− ) on the ZnO surface and suggested a relationship between photon reactions and antibacterial activity. Water (H 2 O) and the electron and hole interact to create ·OH and H + . Additionally, superoxide anion (·O 2 − ), produced by O 2 molecules (suspended within the combination of bacteria and ZnO), interacts with H + to create HO· 2 which interferes with electrons to produce hydrogen peroxide (·HO 2 ), which then reacts with H + to produce molecules of hydrogen peroxide (H 2 O 2 ). The latter can travel across membranes and kill or injure bacteria there. The surface of ZnO nanomaterials plays a major role in the generation of H 2 O 2 by producing extra-active molecules which can harm bacterial cells 89 . It is widely known that copper causes DNA damage and ROS production through Fenton-like and other processes. CuO nanoparticles' strong antibacterial action is caused by the ROS that are produced by the nanoparticles attached to the bacterial cells, which in response causes an increase in intracellular oxidative stress. MIC MBC assay The gram-positive bacteria Staphylococcus aureus as well as the gram-negative bacteria Escherichia coli, Pseudomonas aeruginosa and Klebsiella pneumoniae showed promising antibacterial activity. Despite the prevalent belief that bactericidal antibacterial agents are more effective than static antibacterial agents, this is not supported by adequate literature. The terms "cidal" and "static" are both used to describe the effects of antibacterial drug concentrations on bacterial growth over a specific tolerance. Antibacterial drugs that target bacterial protein synthesis are mostly bacteriostatic while those that target bacterial cell walls are generally bactericidal 90 . For instance, bactericidal drugs like cephalosporins and other beta-lactam antibiotics hinder or impede the formation of bacterial cell walls. In contrast, bacteriostatic antibiotics like chloramphenicol and clindamycin function by preventing or slowing down bacterial growth by blocking protein synthesis. Fundamental data on an antibacterial agent's me chanism of action is provided by the MIC and MBC assays 43 , 45 , 91 . An antibacterial agent’s minimum bactericidal concentration (MBC) is its lowest concentration of bactericidal activity. It is found by re-culturing (subculturing) broth dilutions (i.e., those at or above the MIC) that prevent the development of a bacterial organism 92 . After streaking the broth dilutions onto agar, they are left to incubate for 24 h to 48 h. The MBC is the lowest antimicrobial broth dilution that prevents the organism from growing on the agar plate. The organism's inability to proliferate on the plate suggests that there are only nonviable organisms there. Previous research conducted by Kotb et al. has also demonstrated that silver nanoparticles against methicillin-resistance (MRSA) and methicillin-susceptible Staphylococcus aureus (MSSA) strains have equal MBC and MIC values indicating the overall bactericidal effect towards the microorganisms similar to that of Cu:Zn 1:2 against E. coli is bactericidal 93 . This may occur if the lowest concentration of a material that can inhibit the visible growth of an organism is the same as the lowest concentration of a material which can inhibit the growth after subsequent culturing. The antibacterial activity of copper, cobalt, silver and zinc has been studied via MIC and MBC assays against S. aureus , E. coli and S. epidermidi by Farah et al . Compared to copper and cobalt nanoparticles, zinc and silver have shown stronger antibacterial activity. S. aureus was found to have a greater sensitivity against zinc and silver than E. coli , although both bacteria have shown comparable sensitivity patterns against copper and cobalt nanoparticles. S. aureus displayed a greater MIC for copper in comparison to silver and zinc, indicating increased efficacy of zinc and silver as well as strain specificity. E. coli , on the other hand, displayed equal MICs for copper, zinc, and silver nanoparticles, except for cobalt 41 . PEG functionalization Antibacterial activity is increased, utilizing polyethyleneglycol (PEG) as a surface functionalization agent. Studies have also demonstrated the stability of PEG functionalized nanomaterials following administering in vitro and in vivo settings 94 . Additionally, these were discovered to be more successful at killing cells by penetrating the cell membrane 95 , 96 . It has also been effectively examined how using varied PEG molecular weights can increase the bactericidal impact and it has been observed that PEG surface modification has enhanced metal nanoparticles antibacterial activity overall 97 . Furthermore, the longer PEG chains are preferable because more hydroxyl groups are formed on the surface of metal nanoparticles in longer-chain polymers, increasing their bactericidal activity. In addition, the structural characteristics of the higher-molecular-weight PEG, which has a greater affinity with actin proteins and can inhibit cellular processes in bacterial cells 98 , 99 . Additionally, higher molecular weight PEG may have greater antibacterial efficacy because of their high hydrophilic characteristics, which enable more water to be removed and inhibit microbial development because bacteria require a certain amount of water to grow optimally 100 . Hydroxyl groups of the PEG polymer chain could also weaken the extracellular polymeric substance—membrane attachment 101 which would have a detrimental effect on bacterial growth. PEG's hydroxyl groups can also be used to form intricate nanostructured films with higher antibacterial activity than simple metal nanoparticles 102 . According to our findings functionalizing the metal nanoparticles with PEG led to higher antibacterial activity. These functionalized nanoparticles could be utilized successfully in the future to coat food packaging, surgical instruments, and delicate devices due to their significant antibacterial activity. Growth curves were typically obtained by monitoring the optical density (OD), at the wavelength of 600 nm, a typical wavelength for cells. The density of bacterial isolates must be adjusted to an optimal density of 0.5 McFarland standards and the OD should serially be monitored hourly up to 12 h of incubation. Distinctive mechanisms that have been put forward in the literature are listed as follows: direct contact of ZnO nanomaterial with cell walls, resulting in destructing bacterial cell integrity 17 , 85 , 86 , liberation of antimicrobial ions mainly Zn 2+ ions 72 , 103 , 104 , and ROS formation 105 – 108 . However, the toxicity mechanism varies in various media as the species of dissolved Zn may change according to the medium components besides the physicochemical properties of ZnO nanomaterials 72 . As shown in Table 4 , the antibacterial activity of the ZnO nanoparticles which showed the highest activity was compared with the antibacterial activity of ZnO reported in the literature. It is worth noting that the antibacterial activity reported here is greater in some studies and lesser in some other studies. The antibacterial activity is dependent not only on the type of nanomaterial but also on the size, shape and capping agent used during the synthesis. Further, antibacterial activity also depends on the experimental and environmental conditions. Antioxidant activity The antioxidant activity of the nanocomposites synthesized was determined by DPPH (2,2-diphenyl-1-picrylhydrazyl) assay using 20 mg/ml, the lowest concentration used for the antibacterial study including for kill curves. In the presence of sunlight, all the nanocomposites generate electron hole pairs which lead to the generation of oxygen based free radicals where the electron density is transferred from the oxygen atom to the odd electron located at the N of the DPPH molecule resulting in the formation of the stable DPPH molecule converting the purple colour solution to yellow colour. The highest DPPH scavenging activity resulted in the presence of Cu:Zn 1:2 (51.13%) followed by ZnO (47.79%), Cu:Zn 1:1 (33.85%) and Cu:Zn 2:1 (32.06%). Free radical generation depends on the charge transfer mechanism resulting in the proper band alignment which also influenced the resulting results in the DPPH assay. The generation of radicals by the nanocomposites evident in this study further supports the existence of an antibacterial mechanism in which the radicals are involved in creating an inhibitory effect on bacteria. Further, dye adsorption and degradation studies were also conducted. It was noted that no dye adsorption occurred for all the composites synthesized throughout the period tested. Moreover, the same dye samples were exposed to sunlight in the presence of the composites synthesized to investigate the photocatalytic activity and noticed that no dye degradation also occurred during the period in all samples though the generation of radicals was proven from the antioxidant study described above. The nanocomposites are insitu functionalized with PEG of which the steric hindrance is high. The surface of the nanocomposites is covered with PEG and hence bulky methylene blue molecules cannot reach the surface of the catalysts minimizing the adsorption. Though the radicals are generated, as the methylene blue molecules have not been adsorbed to the surface and are located away from the catalyst radicals do not reach the reactant molecules resulting in no dye degradation as observed. The antioxidant activity resulted in this study was compared with the literature as given in Table 5 . It is evident that though the studies given below haven’t used the same nanocomposite concentration, the antioxidant activities reported in this study for both the ZnO and CuO–ZnO are greater than the values reported.

Conclusion PEG functionalized ZnO, Zn:Cu 2:1, Zn:Cu 1:1 and Zn:Cu 1:2 nanomaterials were fabricated by the co-precipitation method and used as antibacterial agents to inhibit the bacterial growth and/or kill the bacteria. The synthesized nanomaterial had inhibitory effects on Gram negative Escherichia coli , Pseudomonas aeruginosa , Klebsiella pneumoniae and the Gram positive Staphylococcus aureus indicating their ability to penetrate both thin and thick peptidoglycan cell walls in agar well diffusion assay. Among the synthesized nanomaterials PEG-coated ZnO showed the highest antibacterial activity in inhibiting the growth of the above bacterial species, 14.33 ± 0.53, 15.17 ± 0.29, 12.00 ± 0.50 and 25.67 ± 0.58 mm, respectively with nanoparticle concentration of 20 mg/ml. The metal oxide nanocomposites were found to be more sensitive towards the Gram positive strain Staphylococcus aureus. Most Gram-positive bacteria have negatively charged teichoic acids (with substantial phosphate groups) that stretch from the cell wall to the surface which enhances the negative surface charge of their cell envelope allowing positively charged metal ions to bind more effectively. Additionally, the reactive oxygen species (ROS) produced in the presence of nanomaterials also can interfere with biological processes. All of the tested bacterial pathogen strains exhibited time-dependent rapid bactericidal action by nanomaterials, as shown by the time-kill synergy assay, which restricted the bacterial growth before they reached the stationary phase. The development and the growth of all the bacterial species were investigated in this study, restricted or slowed down by Cu:Zn 1:1 nanomaterial during the lag phase and log phase. Overall, the findings suggest that the synthesized nanomaterials are highly efficient in the lag and log phases against all the investigated bacterial pathogens. The antibacterial activity was further evaluated based on the MBC/MIC ratio and it was found that some of the synthesized nanomaterials possessed bacteriostatic effect while others possessed bactericidal effect on test organisms. The utilization of polyethylene glycol (PEG) as a coating agent, significantly increased the antibacterial activity of the fabricated antibacterial agents. The antioxidant activity of the synthesized nanomaterials varied as Cu:Zn 1:2 (51.13%) followed by ZnO (47.79%), Cu:Zn 1:1 (33.85%) and Cu:Zn 2:1 (32.06%). Overall, the fabricated biocompatible nanomaterials can be used as models to be used in biotechnological, pharmaceutical and food packaging applications owing to their high antibacterial activity, stability and durability. However, the main limitations before industrial implementation seem to reside in the need for carefully assessing any possible nano-toxicology effect of the fabricated nanomaterials, related to the exposure of eukaryotic cells and hence further research is required to assess the safety and the risk of these novel nanomaterials.

Polyethyleneglycol-coated biocompatible CuO–ZnO nanocomposites were fabricated hydrothermally varying Zn:Cu ratios as 1:1, 2:1, and 1:2, and their antibacterial activity was determined through the well diffusion method against the Gram-negative Escherichia coli , Pseudomonas aeruginosa , Klebsiella pneumoniae, and the Gram-positive Staphylococcus aureus. The minimum inhibitory concentration and the minimum bactericidal concentration values of the synthesized samples were determined. Subsequently, the time synergy kill assay was performed to elucidate the nature of the overall inhibitory effect against the aforementioned bacterial species. The mean zone of inhibition values for all four samples are presented. The inhibitory effect increased with increasing concentration of the nanocomposite (20, 40 and 60 mg/ml) on all the bacterial species except for S. aureus . According to the MBC/MIC ratio, ZnO was found to be bacteriostatic for E. coli and P. aeruginosa, and bactericidal for S. aureus and K. pneumoniae . Zn:Cu 2:1 was bactericidal on all bacterial species. A bacteriostatic effect was observed on E. coli and P. aeruginosa in the presence of Zn:Cu 1:1 whereas, it showed a bactericidal effect on S. aureus and K. pneumoniae. Zn:Cu 1:2 exhibited a bacteriostatic effect on E. coli while a bactericidal effect was observed for E. coli, P. aeruginosa, and K. pneumoniae. The metal oxide nanocomposites were found to be more sensitive towards the Gram-positive strain than the Gram-negative strains . Further, all the nanocomposites possess anti-oxidant activity as shown by the DPPH assay. Subject terms

Characterization The XRD patterns were obtained using the D8 Advance Bruker machine, which employs Cu K α (λ = 0.154 nm) radiation, shifting the 2θ from 5° to 80° at a scan speed of 2°/min. The morphology of the produced nanocomposites was evaluated using transmission electron microscopy (TEM). The microscope was run at 200 kV (JEOL JEM 2100), and the energy-dispersive spectra (EDS) were also acquired by the same device with TEAM EDX software. Before the TEM investigation, a quantity of 1 L was put on a carbon copper grid with holes and let dry at room temperature. The EDAX element EDS system was used to capture the EDX spectra, while a ZEISS EVO 18 RESEARCH instrument was used to collect the SEM pictures. The survey spectra and higher-resolution spectra of the synthesized catalysts were collected using the Thermo Scientific ESCALAB Xi + X-ray photoelectron spectrometer. The Shimadzu 1800 UV–visible spectrophotometer, which uses a precise Czerny-Turner optical system, was used to gather the diffuse reflectance spectra of the prepared samples. With a bandwidth of 1.0 nm and a wavelength accuracy of ± 0.1 nm, measurements were made in the 400–750 nm range. The Raman analysis was performed using a Bruker Senterra Raman microscope spectrophotometer. Supplementary Information

Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-52014-6. Acknowledgements The authors acknowledge the Sri Lanka Institute of Nanotechnology and the University of Moratuwa for providing the instrument facilities. Author contributions Conceptualization, M.J., and C.T., methodology, M.J., H.L.; G.E., A.M., L.U.; formal analysis, M.J., H.L.; G.E., A.M.; investigation, M.J., H.L., G.E., A.M.; resources, C.T.; data curation, H.L., G.E.; writing—original draft preparation, M.J., and C.T.; writing—review and editing, M.J. and C.T.; supervision, C.T.; project administration, C.T.; funding acquisition, C.T. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by the Accelerating Higher Education Expansion and Development (AHEAD) Operation of the Ministry of Higher Education funded by the World Bank. Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1293

oa_package/9f/96/PMC10788344.tar.gz

PMC10788345

38221534

Introduction Metagenomics has provided important information on the composition and functional potentials of the gut microbiota and associations between gut bacteria and complex phenotypic traits 1 , 2 . However, in part due to limited availability of cultivated bacterial strains and regulatory issues, causal relations have been difficult to establish in relation to human health and disease 3 . Consequently, cultivation and bacterial genome sequencing have attracted increased attention to provide updated taxonomic annotation and expanded resources of cultivated bacterial isolates and genome references 4 – 6 . Illumina HiSeq/MiSeq, Roche-454, and Ion Torrent Personal Genome Machine (PGM) have been adopted for bacterial genome sequencing and metagenomic research for many years, with the Illumina HiSeq platform being a widely used sequencing platform owing to its ability to provide rapid and accurate analysis of entire bacterial genomes. BGISEQ-500 and later developed versions, employing combinatorial probe-anchor 7 , synthesis (cPAS)-based sequencing combined with DNB nanoarrays have contributed significantly to advance DNA and RNA sequencing of humans 8 , animals 9 , 10 , and plants 11 , 12 . Compared to Illumina sequencers, DNBSEQ sequencers have produced reads of at least similar quality in studies of genomes 13 – 15 , exomes 16 , 17 , transcriptomes 12 , 18 , and metagenomes 19 . In a recent benchmarking study, the DNBSEQ platform was reported to provide the lowest sequencing error rates among short-read technologies 8 . Thus, the BGISEQ-500 sequencer and updated versions have the potential to be a perfect substitute for Illumina platforms to satisfy the increasing demands for cultivated bacterial genome sequencing. Here we performed a comparison on bacterial genome assembly using sequencing data of BGISEQ-500 and Illumina HiSeq 2000 in relation to genome quality assessment, genome alignment, functional annotation, mutation detection, and metagenome mapping. Considering the potential contamination in sequencing and potential insert size bias in the DNB technology 20 , we simulated sequencing reads and analyzed the impact of sequence contamination and insert size on genome assembly.

Methods Genome sequencing, assembling, and quality assessment Whole-genome sequencing was performed using BGISEQ-500 and HiSeq 2000 as described previously 19 . SOAPdenovo (v2.04) 29 was used for de novo assembly of sequencing reads. CheckM (v1.0.13) 30 was used to evaluate the completeness and contamination of genomes. QUAST (v5.0.2) 31 was used to assess the quality of genome assemblies and conduct paired comparison with parameters ‘-f’ and ‘-r’. Unconstrained principal coordinates analysis (PCoA) based on Jaccard dissimilarity of all features in the result of QUAST was conducted using the R function ‘vegdist’ and ‘pcoa’. Taxonomy annotation and 16S rRNA gene prediction GTDB-Tk (v204, database release 214, ‘classify_wf’ function and default parameters) 32 was used to perform taxonomic annotation of each genome. Reference genomes were downloaded from the NCBI Genome database by searching the species name identified by GTDB-Tk. 16S ribosomal RNA coding regions of genome assemblies from BGISEQ-500, HiSeq 2000, and NBCI-downloaded references were predicted using Barrnap ( https://github.com/tseemann/barrnap ). We used an in-house script to extract 16S rRNA genes and calculate gene length. BLAST was used to determine the sequence identity of 16S rRNA genes between BGISEQ-500 assemblies and HiSeq 2000 assemblies. Calculation of ANI, AAI, tetra correlation, and mash distance Pairwise comparisons for genomes of the same strain from BGISEQ-500 and HiSeq 2000 sequencing platforms were performed by the calculation of pairwise ANI, AAI, Tetra correlation, and Mash distance. FastANI (v1.32) 33 , CompareM (v0.1.2, https://github.com/dparks1134/CompareM ), pyani (v0.2.11, https://github.com/widdowquinn/pyani ) and Mash (v2.3) 34 were used to calculate ANI, AAI, Tetra correlation, and Mash distance. Identification of SNV and InDel and genome collinearity Whole-genome alignments of genome assemblies from the same strain were created with the Parsnp (v1.5.6) 35 using NCBI downloaded genomes belonging to the same species as references and MAFFT as an alignment program. Harvesttools (v1.2) 35 was subsequently used to extract SNV. MUMmer (v3.23) 36 toolkit was additionally used for reference mapping (nucmer), filtering (delta-filter), and SNV/InDel detection (show-snps). We used an in-house script to calculate the numbers of SNV and InDel. Genome collinearity, genome annotation, and BUSCO assessment Analysis of genomic collinearity among genome assemblies and references was conducted by the MCScanX software. Genomic comparison was visualized with proksee ( https://proksee.ca/ ). Prokka (v1.13.4) 37 was used to predict genes and generate gene annotation, including COGs (Clusters of Orthologous Genes), enzymes, gene names, and RNA. BUSCO (v5.1.2, Benchmarking Universal Single-Copy Orthologs) 38 was used to assess genome completeness and generate the numbers of ‘Complete’ BUSCOs, ‘Complete and single-copy’ BUSCOs, ‘Complete and duplicated’ BUSCOs, ‘Fragmented’ BUSCOs, and ‘Missing’ BUSCOs with bacteria_odb10 as the only reference. In-house R/shell scripts were used to summarize the outputs and compare BGISEQ-500 and HiSeq 2000 regarding the numbers of annotated genes or BUSCOs. Distribution of genome assemblies from BGISEQ-500 and HiSeq 2000 in a metagenome cohort Human gut metagenome sequencing data of a Chinese cohort (a part of 4D-SZ 39 ) were downloaded from the CNGB Sequence Archive (CNSA) 27 ( https://db.cngb.org/cnsa/ ) of China National GeneBank DataBase (CNGBdb) 28 under the accession code CNP0000426. The 152 assemblies of 76 strains were built as a BGISEQ-500 custom genome database and a HiSeq 2000 custom genome database by Kraken2 40 and Bracken 41 . In addition, Kraken2 and Bracken were used to map the reads of the Chinese metagenome cohort to the two databases. The median and mean of the relative abundances of the BGISEQ-500 and HiSeq 2000 assemblies in the Chinese cohort were calculated, and the correlations between the medians and means of paired assemblies were analyzed based on Spearman’s rank correlation coefficient. R function vegdist (Bray–Curtis dissimilarity) and R function pcoa were used to perform PCoA, and the R function envfit was used to test the correlation of platforms and the PCoA coordinates. Sequencing reads simulation Dwgsim was used to simulate sequencing data with parameters ‘-1 100 -2 100 -r 0 -R 0 -X 0 -e 0 -E 0 -N 30000’. NCBI-downloaded genomes were used as the template. Three million reads were produced by dwgsim for each genome as clean reads. To produce contamination in sequencing reads, (1) all reference genomes were pooled together, (2) simulating 0%*3M, 0.5%*3 M, 1%*3 M, 2%*3 M, 4%*3 M, and 7%*3 M reads from pooled genomes as the contamination, (3) mixing clean reads with contamination reads. In addition, insert sizes of 200 bp, 300 bp, 400 bp, 500 bp, and 600 bp were used for reads simulation. Genome completeness and contamination were calculated with CheckM 30 . FastANI was also used to calculate ANI between assemblies and reference genomes. Wilcoxon rank test and ANOVA were used to conduct statistical analysis.

Results Strains collection and taxonomic information In this study, we included 76 bacterial strains, comprising 64 unique species from the project of the Culturable Genome Reference version two (CGR2) 4 , 21 deposited in China National GeneBank (CNGB) with accession numbers CNP0000126 and CNP0001833. These strains were sequenced on both BGISEQ-500 and Illumina HiSeq 2000 to yield 152 shotgun sequencing datasets. Through genome assembly and taxonomic annotation, these strains could be classified into 5 phyla (Firmicutes 32 strains, Bacteroidota 26 strains, Actinobacteriota 10 strains, Proteobacteria 7 strains, Fusobacteriota 1 strain), 34 genera, and 64 species (Supplementary Table S1 ). These representative bacteria, which cover the main phyla of the human gut microbiota were selected for the comparison of the two sequencing platforms. Quality assessment of genome assemblies All the 152 genome assemblies from both BGISEQ-500 and HiSeq 2000 were high-quality with completeness higher than 93% and contamination of less than 5% (Supplementary Table S2 ). Wilcoxon tests showed that the completeness of genome assemblies from BGISEQ-500 was significantly higher than that from HiSeq 2000 (p < 0.001) (Fig. 1 A) and similar results were also shown for assemblies of GC percentage higher than 40% and less than 60% (Supplementary Fig. S1 A,B). There was no significant difference in the contamination between assemblies using data from BGISEQ-500 and HiSeq 2000 (Fig. 1 B). We assessed these assemblies by paired comparison of the output of QUAST (Supplementary Table S2 ). The comparison of the mean values of assembly parameters showed that the numbers of contigs and numbers of N per 100Kb were lower, and the length of the largest contig and N50 were higher in HiSeq 2000 assemblies compared to BGISEQ-500 assemblies (Supplementary Fig. S2 A–D). However, the number of N per 100Kb was lower in BGISEQ-500 assemblies (GC content > 60%). The length of genomes based on data from the two platforms was extremely consistent (Supplementary Fig. S2 E). To evaluate all the assembly parameters from QUAST, PCoA (Principal Coordinates Analysis) with Jaccard dissimilarity was used and the results showed that the assemblies from the same strain were close together, irrespective of the platform (Fig. 1 C). Sequence similarity of 16S rDNA, whole genome, and mutation detection The 16S rRNA gene is the most commonly used marker in bacterial taxonomy analysis. BLAST alignment (Fig. 2 A) showed that 16S rDNA predicted from paired genomes possessed similar sequences, with 72 paired sequence identity being higher than 99%. There was no difference in the length of the 16S rDNA sequences of 76 paired genome assemblies (Fig. 2 A). AAI (average amino acid identity), ANI (average nucleotide identity), Tetra (Tetra-nucleotide signature) correlation 22 , and Mash distance have often been used in establishing clusters of species at the genome level. These genome dissimilarity parameters were calculated to compare the differences between the pairwise genome assemblies from the two platforms. All pairwise ANIs and (1 − MASH)*100 were higher than 99.9, AAIs were higher than 99.935, and Tetras were above 99.975 (Fig. 2 B). ANI > 95%, Tetra > 0.99, AAI > 95%, and MASH < 0.05 were used to evaluate whether two genomes should be considered as members of the same genomic species. The comparisons supported that the pairwise genomes from the two platforms were extremely close and did not differ significantly. Seventy-one genomes were downloaded from the NCBI genome database as references (Supplementary Table S3 ). Parsnp and MUMmer were used as the main programs to align genome assemblies of BGISEQ-500 or HiSeq 2000 data to reference genomes, SNV and InDel were subsequently extracted from alignments. The numbers of SNV called by MUMmer were higher than those called using Parsnp. The platforms had no significant effect on SNV calling (Fig. 2 C). Compared to SNV, more insertions were detected in HiSeq 2000 genome assemblies (p = 5.6e−12) and more deletions were detected in BGISEQ-500 genome assemblies (p = 2.9e−11) (Fig. 2 C). Genome collinearity and functional regions assessment To conduct genomic collinearity analysis, genome assemblies of BGISEQ-500 and HiSeq 2000 were mapped to reference genomes. The result showed the percentage of collinear genes in the mapping of BGISEQ-500 assemblies was significantly correlated with that in the mapping of HiSeq 2000 assemblies (Pearson coefficient 0.992, p < 0.001) (Fig. 3 A, and Supplementary Table S4 ). Although the AAI of AM22-17 assemblies from BGISEQ-500 and HiSeq 2000 was lower than that of other pairs, they had a high degree of genome collinearity with 5168 collinear genes (85.35%) (Fig. 3 B). The result of prokaryotic genome annotation by Prokka showed that almost all paired genome assemblies (74/76) had the same numbers of functional regions, including the numbers of enzymes, COGs (Cluster of Orthologous Groups), genes, CDSs (coding sequences), tRNAs (transfer RNAs), rRNAs (ribosomal RNAs) and tmRNAs (transfer-messenger RNAs) (Supplementary Table S5 ). Genome assembly and annotation completeness were also evaluated by BUSCO (Benchmarking Universal Single-Copy Orthologues). Comparisons of the numbers of BUSCOs showed that only one difference occurred in five complete BUSCOs, six complete and single-copy BUSCOs, one complete and duplicated BUSCOs, two fragmented BUSCOs, and three missing BUSCOs in the 76 paired genome assemblies (Fig. 3 C, and Supplementary Table S6 ). Distribution of genome assemblies in metagenome cohort To identify the impact of sequencing platform on metagenomic reads mapping, the distribution of genome assemblies from BGISEQ-500 and HiSeq 2000 in a Chinese healthy cohort was analyzed (Fig. 4 A). Beta-diversity showed that there was no difference between genome assemblies from BGISEQ-500 and HiSeq 2000 (p = 0.99) (Fig. 4 B). The relative abundance of BGISEQ-500 assemblies and HiSeq 2000 assemblies in metagenomes were very similar; for both the sums of relative abundance were about 32% (Fig. 4 C). In addition, the means and medians of the relative abundance of genome assemblies from the two platforms had a significant correlation, with coefficient of greater than 0.99 (Fig. 4 D). These results demonstrate that the use of the two platforms for bacteria genome sequencing has no significant impact on sequence mapping in metagenomic data analysis. The impact of sequence contamination and insert size on genome assembly Three million reads were simulated for each reference genome with a percentage of contamination reads from 0 to 7%. Compared to clean genomes, only genomes mixed with 7% contamination reads had significantly higher numbers of contigs, degree of contaminations, and lower ANI, but N50, completeness, length of largest contigs, and genome length did not differ significantly (Fig. 5 A–D, and Supplementary Fig. S3 A–C). Our results showed that it was difficult for CheckM to identify low rates of sequence contamination. To evaluate the impact of insert size on genome assembly, 200-600bp insert sizes were applied for sequence simulation. There was no significant difference in assembly assessment parameters, completeness, contamination, and ANI between assemblies for different insert sizes in reads simulation (Fig. 5 E,F, and Supplementary Fig. S3 D,E).

Discussion The cPAS-based BGI DNBSEQ sequencer has been commonly used and shown to perform well in eukaryotic genome sequencing 8 and metagenomic sequencing 19 . Considering the increasing demand for cultivated bacterial genome sequencing, the DNBSEQ platform seems as an excellent candidate for bacterial genome research. To evaluate the performance of the DNBSEQ platform, we compared genomes assembled from BGISEQ-500 sequencing data and Illumina HiSeq 2000 sequencing data of 76 strains by detecting and comparing the completeness, contamination, genome assembly quality, 16S rRNA genes, mutations, and metagenomic read mapping. The values of most assembly parameters of genomes from the two sequencing strategies were very close. HiSeq 2000 has a little better performance in relation to the length of the largest contigs and N50, and the numbers of contigs and N bases per 100Kb. The completeness of BGISEQ-500 genome assemblies was higher, with similar results obtained for genome assemblies of high and low GC content. We noted that the numbers of N bases per 100Kb were lower in BGISEQ-500 genomes of high GC content. Although smaller insert sizes may have a higher priority in DNB sequencing, the results showed that insert size had no significant impact on genome assembly. The 16S rRNA gene is a frequently used marker gene in the taxonomy analyses of bacteria. 16S rRNA genes from BGISEQ-500 genomes and HiSeq 2000 genomes were extremely close in the sequence similarity and there was no significant difference in gene length. In addition, the comparison with genome distance algorithms of ANI, AAI, Mash, and Tetra supported the high similarity between BGISEQ-500 assemblies and HiSeq 2000 assemblies. Furthermore, we calculated the numbers of SNV and functional genes, and the follow-up comparison showed that the use of the two platforms had no significant impact on the detection of mutation at the single nucleotide level and in the functional annotation of bacterial genomes. The BGISEQ-500 platform appeared to have higher efficiency in deletion calling, but lower in insertion calling. Culture-independent metagenomic studies have used cultivated bacterial genomes and metagenome-assembled genomes (MAGs) to build customized databases for metagenome classification and calculation of bacterial relative abundance by metagenomic reads mapping 23 – 26 . To assess the metagenomic read classification performance, customized genomic databases of BGISEQ-500 genome assemblies and HiSeq 2000 genome assemblies were built and mapped against metagenomic sequencing data by Kraken2 and Bracken. Comparison of relative abundances and beta-diversity analyses showed that the distribution of genome assemblies from the two platforms was extremely consistent. The Illumina platforms produce accurate sequencing data rapidly and have been widely used in genome sequencing of eukaryotes and prokaryotes, and metagenome sequencing. The DNBSEQ sequencer perform better in the comparison of sequencing error rates 8 . Compared with Illumina platforms, the DNBSEQ platform was shown to be applicable for metagenomic studies providing high accuracy and technical reproducibility 19 . In this work, we compared the assemblies of BGISEQ-500 sequencing reads and HiSeq 2000 sequencing reads by genome assembly assessment, sequence similarity analysis of 16S rRNA genes and genomes, mutation detection, and metagenomic reads mapping demonstrating excellent performance and applicability of the BGISEQ-500 platform for bacteria genome sequencing, as also demonstrated in our recent work 21 . Besides BGISEQ-500 and Illumina HiSeq 2000, more upgraded sequencers have been produced, including DNBSEQ-T20, Illumina NovaSeq and NextSeq 1000/2000, more comparison (cost, index hopping) should be conducted on these newer platforms.

The Illumina HiSeq platform has been a commonly used option for bacterial genome sequencing. Now the BGI DNA nanoball (DNB) nanoarrays platform may provide an alternative platform for sequencing of bacterial genomes. To explore the impact of sequencing platforms on bacterial genome assembly, quality assessment, sequence alignment, functional annotation, mutation detection, and metagenome mapping, we compared genome assemblies based on sequencing of cultured bacterial species using the HiSeq 2000 and BGISEQ-500 platforms. In addition, simulated reads were used to evaluate the impact of insert size on genome assembly. Genome assemblies based on BGISEQ-500 sequencing exhibited higher completeness and fewer N bases in high GC genomes, whereas HiSeq 2000 assemblies exhibited higher N50. The majority of assembly assessment parameters, sequences of 16S rRNA genes and genomes, numbers of single nucleotide variants (SNV), and mapping to metagenome data did not differ significantly between platforms. More insertions were detected in HiSeq 2000 genome assemblies, whereas more deletions were detected in BGISEQ-500 genome assemblies. Insert size had no significant impact on genome assembly. Taken together, our results suggest that DNBSEQ platforms would be a valid substitute for HiSeq 2000 for bacterial genome sequencing. Subject terms

Supplementary Information

Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-51725-0. Acknowledgements This work was supported by grants from National Natural Science Foundation of China (No. 32100009) and the Shenzhen Municipal Government of China (No. XMHT20220104017). We also thank the colleagues at BGI Research for sample collection, and discussions, and China National GeneBank (CNGB) Shenzhen for DNA extraction, library construction, and genome sequencing. Author contributions Y.Z., L.X., and K.K. conceived and designed this research. T.H., Y.Z., and J.C. conducted data analysis and wrote the manuscript. T.H., Y.Z., J.C., X.L., W.H., H.L., W.L., M.W., Z.W., X.J., and M.H. contributed the materials and methodology. Y.Z., J.C., K.K., and L.X. revised and edited the paper. All authors commented on the manuscript. Data and code availability The 76 bacterial strains in this article have been deposited in China National GeneBank (CNGB), a non-profit, public-service-oriented organization in China. The data that support the findings of this study have been deposited into the CNGB Sequence Archive (CNSA) 27 of China National GeneBank DataBase (CNGBdb) 28 . The 76 Illumina HiSeq 2000 assemblies can be downloaded from CNSA ( https://db.cngb.org/search/project/CNP0000126/ , https://db.cngb.org/search/project/CNP0001833/ ). The 76 BGISEQ-500 assemblies are publicly available from https://db.cngb.org/search/project/CNP0003311/ . The Chinese gut metagenome sequencing data can be found and accessed through https://db.cngb.org/search/project/CNP0000426/ . The scripts of SNV and InDel calling, and reads simulation are publicly available through Github ( https://github.com/hutongyuan/BGISEQ-500_VS_HiSeq-2000 ). Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1292

oa_package/7e/a2/PMC10788345.tar.gz

PMC10788346

38221518

Introduction In recent years, there has been a growing trend towards the use of renewable energy sources and energy efficiency measures in the metallurgical sector to reduce greenhouse gas emissions and mitigate climate change. The metallurgical sector, which includes the production of iron, steel, aluminum, copper, and other metals, is an energy-intensive industry that requires large amounts of energy for various processes such as smelting, refining, and casting. The energy systems in the metallurgical sector can be categorized into two types: primary energy systems and secondary energy systems. Secondary energy systems involve the use of by-products from primary energy systems or renewable energy sources such as hydropower, solar and wind energy. Furthermore, energy efficiency in metallurgy sector includes an implementation of energy-efficient technologies such as optimization of incoming energy and materials flows, waste heat recovery, energy-efficient lighting and equipment 1 – 3 . The metallurgical sector in European Union uses up to 33% of the total energy consumptions that comes from productions of ferrous and non-ferrous metals 2 , 4 , 5 . Based on it several strategies in many developed countries have been implemented in the metallurgical sector to reduce the usage of primary energy and materials, such as optimization of incoming energy and materials flows, adjustment of energy-related processes, and valorization of process residues 6 – 8 . Furthermore, it has been adopted renewable energies for supporting metallurgical sector and reducing environmental impacts 9 – 11 . According to the latest available data from the International Energy Agency (IEA), the industrial sector in Albania accounted for approximately 28% of the country's total energy consumption 12 . This includes energy used in metallurgy, manufacturing, construction, mining and other industrial activities. The largest energy-consuming sub-sectors are coming from the production of iron, steel, ferrochrome and aluminum from Albanian metallurgical companies called respectively “Kurum International Ltd”, “AlbChorme Ltd” and “Everest Ltd”. Albania’s energy system is primarily based on hydroelectric power and some smaller amounts of thermal energy. Hydroelectric power accounts for approximately 95% of Albania's electricity generation, with the remaining 5% coming from solar energy. In general, the energy system covers 60% of energy consumptions and the other 40% comes from imports. In the current conditions of the global energy crisis, the import of electricity in Albania means higher costs of products and services for all consumers in the country. During the Covid-19 pandemic, the energy consumption in Albania from the metallurgical sector surpassed the residential consumption 13 . As a result of the high prices of imported electricity, the two aforementioned companies have stopped their activity. Due to the high level of energy consumption that comes from metallurgical sector as well as suitable climate conditions the Albanian government has given support to private companies for increasing and implementing renewable energies by focusing on hydroelectrically power, solar and wind energy. Furthermore, a sustainable development of the energy sector in particular for the metallurgical sector, in the conditions of our country, requires the diversification of renewable energy sources by implementing wind and solar energy on a large scale. This way, the energy needed to produce materials and make them into products, would be mostly coming from renewable energy, thus reducing the carbon footprint in the life cycle of the products. Furthermore, renewable energies would reduce the environmental impact from thermal electricity import and decrease the number of the small hydropower plants. In this paper, we present the energy efficiency analysis in Albanian metallurgical sector by focusing on the implementation of the wind energy in the above mentioned private metallurgical industries. Modern-Era Retrospective Analysis for Research and Applications (MERRA), ERA5, New European Wind Atlas (NEWA) and Wind Balkan Atlas (WBA) has been used in most of the studies as the best tools to simulate wind power production 14 – 17 . WBA and NEWA has been used in our research work to select the appropriate areas. The Wind Atlas Analysis and Application Program (WAsP) was used to develop the wind potential distribution maps, as well as for selecting the most suitable type of wind turbine based on capacity factors. Clean Energy Management Software (RETScreen Expert) was used for the detailed economic analysis and environmental impact of proposed wind farms.

Methodology and measurement results Under the context of the global energy crisis, the price increase in electricity and imports caused some Albanian metallurgical companies to temporarily interrupt parts of their activities. The energy consumption profile for these three metallurgical companies are shown in the Fig. 1 . This event emphasizes the need for higher energy security in Albania overall, and especially for the metallurgical sector. This would require diversifying the source of energy production through renewable sources, which for Albania means implementing solar and wind power. Some important factors mentioned below has made our research work to focused on the implementation of wind energy instead of solar panels: Producing energy from photovoltaic panels require a large surface area which is not ideal considering Albania is a small country with area of 28,748 km 2 . The production capacity of photovoltaic panels is small and insufficient to fulfill the needs of the metallurgical industry sector. There are higher costs associated with producing energy from photovoltaic panels compared to wind turbines The suitable areas for photovoltaic panels are predominantly used for agriculture and based on Albanian law they cannot be substituted for energy production. Two wind farms were simulated and proposed based on wind turbine placement that optimizes electric energy production and minimizes wake losses. Figure 2 depicts a methodology algorithm used for feasibility study of setting up wind farms in the selected areas. Areas selections One of the reasons Albania has been slow to adopt wind power solutions, is because there is a lack of long-term measurements of wind speed in the country that follow the standards for selecting high potential areas for wind farms. Due to the lack of real measurements a good solution for identifying general areas of high wind potential are wind atlases. Many research works have shown that wind atlases are useful for initial assessment of wind conditions 18 – 23 . Since 2019, Albania is specifically included in the Balkan Wind Atlas (BWA) as well as the New European Wind Atlas (NEWA). The business activities of the companies “Kurum International”, “Everest Construction Group”, and Ferrochrome Metallurgical Plant-Burrel, are located in central Albania. Wind speed distribution maps at 50 m a.g.l. from both atlases were used to investigate areas of high wind potential in central Albania, see Fig. 3 . Important factors in selection were access to road infrastructure and transmission lines, land ownership and respecting forest areas. Therefore, geographic information system (GIS) was used since it offers information on topography, road infrastructure, transmission lines, land usage, formal and informal urban regions. GIS information is updated based on satellite images. The process of area selection is one of the most important aspects of planning and developing a new wind farm. After careful investigation based on wind potential, two areas were selected in the regions of “Vajkal”, Bulqizë and “Selitë e Malit”, Tirana county based on long-term data from BWA and NEWA, see Fig. 4 . Long-term data on wind speed is crucial in forecasting long term energy production 14 . The Universal Transverse Mercator (UTM) coordinates of the hypothetical anemometric towers from both atlases for the selected areas are given in Table 1 . Figure 5 depicts the reciprocal position of anemometric towers found in both atlases of the selected areas. The terrain in both selected areas is land owned by the state. The “Vajkal” region includes a mountain slope over the town of “Vajkal” close to a transmission line (110 kV) and the national road Peshkopi–Maqellare, see Fig. 6 . In case of “Selite e Malit” region, the top of mountain bare was thought to be the most suitable area without any environmental impact. Analysis of wind source for selected areas Since the variation in wind speed impacts the wind turbines’ electric power production level, in order to achieve a credible mean yearly wind speed value, long term data over the span of 14 years at 50 m of altitude a.g.l. from both atlases (Balkan Wind Atlas 2000–2013 and New European Wind Atlas 2005–2018) were used for the selected areas. In order to determine the source of wind in the selected areas, the evaluation of the wind speed direction and power was performed using WAsP software. WAsP Observed Wind Climate (OWC) files for each atlas tower at 50 m above ground level were used to visualize the wind patterns by giving the wind rose charts and Weibull probability distributions as can be seen in Fig. 7 . The probability of a specific wind speed value is described in terms of the wind power density probability function. The Weibull probability distribution gives a very close estimate of the observed wind speed probability and is mathematically expressed with Eq. ( 1 ): where A (m/s) is a scale parameter, closely related with mean wind speed U , and k as a shape parameter is a measure of the width of the distribution. Higher values of k indicate a narrower wind speed range. The comparison of wind rose charts of each area shows that the dominating wind blowing directions are very similar across both atlases. There are however some divergent values in mean wind speed, wind power density and in the A and k parameters of the Weibull probability distribution. Nonetheless, the values of parameters A and k as well as the mean speed U and power density P which result from both hypothetical anemometric antennas in each area show that these areas have a wind source which can be deemed adequate for setting up wind farms. Furthermore, in two previous research works 17 , 19 it was shown that the models in both atlases are comparable to each other, but the New European Wind Atlas is closer to the real area measurements. Therefore, wind speed and power density distribution maps were developed with the WAsP program using NEWA’s OWC files. In the Fig. 8 are shown the wind potential distribution maps for both the selected areas, in terms of wind speed (m/s) and power density (W/m 2 ) according to data from NEWA towers. Table 2 depicts the mean speed (m/s) and power density (W/m 2 ) in the areas with the highest wind speed potential in the two territories under study based on the wind potential distribution maps in the area developed by the WAsP simulation program. Based on the wind speed class ranking, referring to speed values (m/s) and power density (W/m 2 ) at 50 m of altitude a.g.l. both selected areas can be classified as wind power class IV, V and VI. Four different types of Vestas wind turbines were tested in the same wind source conditions. Currently there is a tendency towards larger turbines, with 2–5 MW rated energy generation, with rotor diameters that surpass 100 m and hub heights of 100–120 m 20 . In the Fig. 9 it has been shown that the turbine with the highest capacity factor was Vestas V100-1.8 MW 21 . The main characteristics of the selected wind turbines are presented in Table 3 . Consequently, the WAsP program was used to develop the wind farm set up with a site layout design of 5 wind turbines V100-1.8 that maximizes annual electric power production and minimizes wake losses. The WAsP simulation program is a software that calculates a regional wind atlas and a resource grid in order to establish wind farms by performing a wind source analysis based on long term anemometric tower data. Table 4 shows the electric power production, wake loss, mean wind speed, and power density data applicable in the two parks proposed for “Vajkal” and “Selite e Malit”. The values were calculated using the WAsP simulation program. The area with high wind potential in the proposed "Selitë e Malit" park is in the top of the mountain which is bare of vegetation. While the plateau at the foot of the mountain is wooded. Therefore, the turbines were placed in the top of the mountain. In the Fig. 10 it can be shown an important overview in regarding the visual and environmental impact of placing the turbines in the proposed areas. Economic analysis The decision to implement the proposed research work wind farm in the “Vajkal” and “Selite e Malit” areas will depend on the results of a detailed economic analysis. Wind energy costs The costs that generate the implementation of wind farms are determined by several important factors related to the source of the wind, the efficiency of the wind turbines, lifetime of wind farm, the time that wind turbines are able to generate electricity, site layout design, capital costs, financing costs, as well operation and maintenance costs or variable costs. The capital costs of wind energy projects or upfront capital cost are often referred to as capital expenditures (CAPEX) and are the costs that dominate in wind energy projects 22 . They consist of the cost of the turbines, their transport and installation, cost of grid connection, the construction cost including foundations, roads and buildings, underground cabling within the wind farm, as well as the licensing procedural costs, long term measurement costs and preliminary design of the wind energy project. While these costs vary based on the types of turbines, markets and locations where they are placed, they represent 80% of the total cost of the project over its entire lifetime. The largest cost component is the cost of the wind turbines. Wind turbine prices have declined globally over the last decade in spite of the continued increase in rotor diameters, hub heights and their rated powers. Since 2019 Vestas wind turbines continue to be under 1000 €, varying between 780 and 960 €/kW 22 , 23 . This has led to a decline in wind energy project capital costs regardless of some variability within the European Union. According to a report by the European Wind Energy Association (EWEA), the cost of installed power of onshore wind projects in Europe, differs between countries and typically varies from around 1100 €/kW to 1350 €/kW 24 , 25 . In 2019, the CAPEX was on average 1300 €/kW. The global weighted average total installed cost of onshore wind according to IRENA (2023) fell by 35% between 2010 and 2021, from 2042 to 1325 €/kW 22 . For the economic sensitivity analysis of the two projects in our study, the total installed capital cost was assumed to have the values of 1100 €/kW, 1200 €/kW, 1300 €/kW, and 1350 €/kW. The Variable costs of an onshore wind project consist of operating & maintenance (O&M) cost, land rental, insurance, taxes, and administration cost. O&M costs for onshore wind projects, according to IRENA 2021 data vary by location. Generally, in 2020 however, the O&M costs ranged between 10 and 30% of the LCoE for the majority of projects. Applying those percentages to the total investment cost, at the country level, between 2016 and 2019, O&M costs for onshore wind projects ranged from 33 €/kW per year in Denmark to 56 €/kW per year in Germany 20 . Nonetheless, investigations from several reputable sources have shown that O&M costs for onshore wind projects, in terms of cost per kWh, were between 0.01 and 0.02 €/kWh over the lifetime of the wind farm 23 . Since in Albania all onshore wind farm perspectives implementations are in the phase of collecting wind speed measurements on the ground, we do not have any data indicative of the O&M value. For this reason, in our research work, for both proposed parks O&M was assumed to be 0.018 €/kWh over the lifetime of the wind turbine or 55 €/kW of installed power. Methodology for wind energy cost analysis The main methods that represent the indicators for determining the efficiency and technical–economic character of energy systems in general and wind energy systems in particular were analyzed in this section. Levelized cost of electricity ( LCoE ) is an energy source measuring scale that has been used to compare the different methods of energy production through comparable criteria. This would be cost information for the investor to produce one kWh of electricity produced by a certain technology. LCoE can be calculated by using Eq. ( 2 ). Where n is the lifetime of the energy farm in which electricity is generated in years, E t is the annual energy production (AEP) in the year t (kWh) or (MWh), I t is CAPEX in year t (€), O&M t is operation and maintenance cost (OPEX) in year t (€), F t is fuel expenditures in the year t (€), and r is the discount rate 26 – 28 . The levelized cost of electricity of onshore wind farms in Europe, according to the Bloomberg New Energy Finance data, in 2018 ranges from 50 € to 65 €/MWh 29 . The Discount rate ( r ) is used to bring future costs back to their present value. We predict the project yearly income to remain the same during a 20-year project lifetime. However, due to inflation, this income would not have the same value in the future as it does now. The discount rate is used to calculate the decline in value of money in the future. This financial method is known as the discount cash flow. Discount rate values vary depending on the technology of the investment projects. Many studies analyzing wind energy project cost elements, based on the evidence gathered from the literature review, show that the range of discount rates for onshore wind energy projects varies between 7 and 10%, directly affecting the LCoE value. Several factors increase the perception of risk for wind energy technology investments including wholesale electricity prices, changes in government policy and less mature technology. The discount rate range for onshore projects is predicted to be between 5 and 8% in the year 2040. This takes into account the importance that renewable energy technologies are gaining currently not only due to the energy crisis but also to the 1.5 0 C climate target under the Paris Agreement. On the other hand, this will be paired with high expectations of improved wind technology maturity in the future. In this study the discount rate was assumed to be 5, 7 and 11%. The net present value ( NPV ), gives us the ability to estimate whether or not to move forward with the project. The total project yearly cash flow equals the given year’s income (B i ) minus that year’s costs C i . But this yearly project cash flow is expressed in today’s value of money. Then we subtract the initial capital investment cost C 0 from the total cash generated during the planned lifetime of the project N to obtain the next present value of the project. This is shown in Eq. ( 3 ). If the net present value is positive then the project is feasible and suitable for further consideration 30 . Internal rate of return ( IRR ) is considered to be the discount rate for which the Net Present Value (NPV) of the project is zero. This is expressed in Eq. ( 4 ). where N is the lifetime of the project in years, and C n is the cash flow for year n . An investment is considered acceptable if it’s IRR is greater than the investor’s minimum acceptable rate of return. The Benefit–Cost ratio ( B–C ) is an expression of the relative profitability of the project. It is calculated as a ratio of the present value of annual revenue minus the annual costs to the project equity which is expressed by Eq. ( 5 ). where f d is the debt ratio. The greater the value of this ratio, the bigger the return on investment in either revenue or savings terms. Obviously in order for the investment to be considered economically efficient this ration needs to be greater than one. Simple payback time refers to the number of years necessary for the project revenue by excluding debt payments and is equal to the total investment cost. While Equity payback indicates the years after which the project will generate income beyond the initial investment value. Research work proposal cost The RETScreen Expert model was used to perform the financial analysis and determine the aforementioned financial parameters LCoE, NPV, IRR, B-C , and SPB for the research work proposed in “Vajkal”, Bulqizë and “Selitë e Malit”, Tirana county. RETScreen Expert is a clean energy management software used for energy efficiency, renewable energy, energy performance analyses and environmental impact. Via sensitive analyses, this program quickly allows professionals to determine whether a proposed renewable energy research work contains financial parameters suitable to move it forward. Therefore, the RETScreen software is a great and user-friendly tool for analyzing the feasibility of renewable energy projects since it can estimate energy production, entire life cycle cost, and the greenhouse gas emission reductions resulting from implementing the project. In order to perform the financial analysis for the proposed projects, the model requests average monthly wind speed data as well as other climate data such as average air temperature, humidity, atmospheric pressure, etc. RETScreen referred to the climate data obtained from the National Aeronautics and Space Administration (NASA) regarding the geographic location of the antennas. Meanwhile, average monthly wind speed data was manually inputted in accordance to the NEWA hypothetical antennas in the 2005–2018 timeframe. Table 5 depicts the main tecno-economic components considered by RETScreen to conduct the financial analysis for the selected areas “Vajkal” and “Selite e Malit”. Based on the tecno-economic data in Table 5 , the RETScreen Expert model calculated the financial indicators presented in Table 6 . The difference between the annual energy production of the proposed parks calculated by WAsP and RETScreen are explained by the fact that RETScreen ran with average annual wind speed values from the NEWA hypothetical antennas which unlike the WAsP turbines were not positioned in the highest potential. The mean annual wind speed for the locations of the Vajkal and Selitë e Malit turbines from WAsP were found to be respectively 6.72 m/s and 6.81 m/s. Hence this difference is to be expected given that energy production is proportional to wind speed cubed. Sensitivity and risk analysis An important parameter that helps determine whether to produce wind energy is the energy production cost LCoE of the proposed wind farms. Figure 11 depicts LCoE as a function of the different values of total installation cost for discount rates 5, 7, and 11% and electricity export rate 76 €/MWh for the “Vajkal” and “Selitë e Malit” wind farms. From the Fig. 11 it has been clearly shown that the LCoE for the park proposed in “Vajkal” is similar to European wind farms for every discount rate value and for a total installation cost of 1350 €/kW. For the wind farm proposed in “Selitë e Malit”, the variation of LCoE as a function of annual energy production within a sensitivity range of ± 25%, at 1350 €/kW installation cost and at 11% discount rate, is given in Fig. 12 . Furthermore, in this sensitivity analysis it is observed that by increasing the annual electricity production by at least 9%, even when the proposed research work is perceived to be high risk, the LCoE calculated by the RETScreen model will be within the European wind farm values. Hence, we can consider the annual energy production calculated by WAsP, both proposed parks are feasible in terms of LCoE . Investors would be interested to understand what happens to the other important financial indicator such as NPV if the electricity export rate changes within a sensitivity range of ± 30%, assuming a total installation cost of 1350 €/kW, at 7 and 11% discount rates, see Fig. 13 . Through a total installation cost of 1350 €/kW, an inflation rate of 3%, a debt rate of 70%, a debt term of 15 years, and an electricity export rate within a range of ± 30%, it is observed that the NPV calculated at 7 and 11% discount rate reduces by a factor of 2.5 and 4 respectively if an electricity export rate of 60.80 €/MWh is assumed. For electricity export rates smaller than this value, the NPV declines significantly, sliding even into negative values. In this case the proposed “Vajkal” park is considered infeasible. For the park proposed in “Selite e Malit”, at the same parameters mentioned above, an electricity export rate would be no smaller than 70 €/MWh. This price can go down to 63.3 €/MWh if the total installation cost declines to 1125 €/kW. In the Fig. 14 it has been shown IRR as a function of the total installation cost (1100, 1200, 1300, and 1350 €/kW) and electricity export rate within a sensitivity range of ± 30%, calculated for a debt rate of 70% and inflation rate of 3%. The discount rate does not have an effect on IRR . As it can be seen, the lower the total installation cost is, the higher the IRR values. For an electricity export rate of 64.6 and 76 €/MWh, which actually is the electricity price benchmark, the IRR values for the project proposed in “Vajkal” are optimal throughout the entire range of electricity export rates in the graph. Another financial indicator is the Benefit–Cost ratio (B–C). B–C is an expression of the relative profitability of the project. B–C variation as a function of total installation cost and discount rate for 76 €/MWh for “Vajkal” and “Selitë e Malit” parks, is given in Table 7 . Sensitivity and risk analysis for “Selitë e Malit” park with the values highlighted in bold has shown that a total installation of 1300 and 1350 €/kW at discount rate 11% corresponds to the lower values B–C ratio values. However, the values of 1300 and 1350 €/kW at equity payback will not been acceptable and therefore the proposed research work in this case will not be feasible. Environmental impact The technology of producing electricity from wind energy does not emit greenhouse gases in the environment whereas the conventional technologies in energy production contributed 78% of total EU emissions 31 – 33 . The electricity produced in Albania comes 100% from renewable energies. Since Albania is a net importer of energy, it is forced, depending on the hydrological conditions, to import energy from the region and mainly from Kosovo. Coal is the most important energy source of Kosovo, from which about 97% of electricity is produced. Therefore, we can say that every MWh of energy produced by wind energy in Albania would contribute to the decarbonization of the energy sector in the region 34 – 38 . To calculate the contribution of the electricity produced by the two proposed parks to the reduction of CO 2 was used RETScreen Greenhouse Gas (GHG) Emission Reduction Analysis model. Scenarios were assumed as if this electricity was produced by coal-fired power plants in Kosovo, or by those with natural gas under the conditions of the parameters of the power plants in Germany. RETScreen model calculates the amount reduced in tCO 2 and equates it to barrels of crude oil not consumed. Figure 15 depicts the annual amount in tCO 2 that is reduced by producing electricity from the proposed parks in “Vajkal” and “Selitë e Mali” and is compared to the base case if this energy would be produced from coal. In Fig. 1 6, the base case that will replace the wind energy production is a natural gas plant. In this case, it will be reduced every year for 20 years of wind farms lifetime, the emission of 17,088.7 tCO 2 which is equivalent to 39,740.9 barrels of oil not consumed.

Methodology and measurement results Under the context of the global energy crisis, the price increase in electricity and imports caused some Albanian metallurgical companies to temporarily interrupt parts of their activities. The energy consumption profile for these three metallurgical companies are shown in the Fig. 1 . This event emphasizes the need for higher energy security in Albania overall, and especially for the metallurgical sector. This would require diversifying the source of energy production through renewable sources, which for Albania means implementing solar and wind power. Some important factors mentioned below has made our research work to focused on the implementation of wind energy instead of solar panels: Producing energy from photovoltaic panels require a large surface area which is not ideal considering Albania is a small country with area of 28,748 km 2 . The production capacity of photovoltaic panels is small and insufficient to fulfill the needs of the metallurgical industry sector. There are higher costs associated with producing energy from photovoltaic panels compared to wind turbines The suitable areas for photovoltaic panels are predominantly used for agriculture and based on Albanian law they cannot be substituted for energy production. Two wind farms were simulated and proposed based on wind turbine placement that optimizes electric energy production and minimizes wake losses. Figure 2 depicts a methodology algorithm used for feasibility study of setting up wind farms in the selected areas. Areas selections One of the reasons Albania has been slow to adopt wind power solutions, is because there is a lack of long-term measurements of wind speed in the country that follow the standards for selecting high potential areas for wind farms. Due to the lack of real measurements a good solution for identifying general areas of high wind potential are wind atlases. Many research works have shown that wind atlases are useful for initial assessment of wind conditions 18 – 23 . Since 2019, Albania is specifically included in the Balkan Wind Atlas (BWA) as well as the New European Wind Atlas (NEWA). The business activities of the companies “Kurum International”, “Everest Construction Group”, and Ferrochrome Metallurgical Plant-Burrel, are located in central Albania. Wind speed distribution maps at 50 m a.g.l. from both atlases were used to investigate areas of high wind potential in central Albania, see Fig. 3 . Important factors in selection were access to road infrastructure and transmission lines, land ownership and respecting forest areas. Therefore, geographic information system (GIS) was used since it offers information on topography, road infrastructure, transmission lines, land usage, formal and informal urban regions. GIS information is updated based on satellite images. The process of area selection is one of the most important aspects of planning and developing a new wind farm. After careful investigation based on wind potential, two areas were selected in the regions of “Vajkal”, Bulqizë and “Selitë e Malit”, Tirana county based on long-term data from BWA and NEWA, see Fig. 4 . Long-term data on wind speed is crucial in forecasting long term energy production 14 . The Universal Transverse Mercator (UTM) coordinates of the hypothetical anemometric towers from both atlases for the selected areas are given in Table 1 . Figure 5 depicts the reciprocal position of anemometric towers found in both atlases of the selected areas. The terrain in both selected areas is land owned by the state. The “Vajkal” region includes a mountain slope over the town of “Vajkal” close to a transmission line (110 kV) and the national road Peshkopi–Maqellare, see Fig. 6 . In case of “Selite e Malit” region, the top of mountain bare was thought to be the most suitable area without any environmental impact. Analysis of wind source for selected areas Since the variation in wind speed impacts the wind turbines’ electric power production level, in order to achieve a credible mean yearly wind speed value, long term data over the span of 14 years at 50 m of altitude a.g.l. from both atlases (Balkan Wind Atlas 2000–2013 and New European Wind Atlas 2005–2018) were used for the selected areas. In order to determine the source of wind in the selected areas, the evaluation of the wind speed direction and power was performed using WAsP software. WAsP Observed Wind Climate (OWC) files for each atlas tower at 50 m above ground level were used to visualize the wind patterns by giving the wind rose charts and Weibull probability distributions as can be seen in Fig. 7 . The probability of a specific wind speed value is described in terms of the wind power density probability function. The Weibull probability distribution gives a very close estimate of the observed wind speed probability and is mathematically expressed with Eq. ( 1 ): where A (m/s) is a scale parameter, closely related with mean wind speed U , and k as a shape parameter is a measure of the width of the distribution. Higher values of k indicate a narrower wind speed range. The comparison of wind rose charts of each area shows that the dominating wind blowing directions are very similar across both atlases. There are however some divergent values in mean wind speed, wind power density and in the A and k parameters of the Weibull probability distribution. Nonetheless, the values of parameters A and k as well as the mean speed U and power density P which result from both hypothetical anemometric antennas in each area show that these areas have a wind source which can be deemed adequate for setting up wind farms. Furthermore, in two previous research works 17 , 19 it was shown that the models in both atlases are comparable to each other, but the New European Wind Atlas is closer to the real area measurements. Therefore, wind speed and power density distribution maps were developed with the WAsP program using NEWA’s OWC files. In the Fig. 8 are shown the wind potential distribution maps for both the selected areas, in terms of wind speed (m/s) and power density (W/m 2 ) according to data from NEWA towers. Table 2 depicts the mean speed (m/s) and power density (W/m 2 ) in the areas with the highest wind speed potential in the two territories under study based on the wind potential distribution maps in the area developed by the WAsP simulation program. Based on the wind speed class ranking, referring to speed values (m/s) and power density (W/m 2 ) at 50 m of altitude a.g.l. both selected areas can be classified as wind power class IV, V and VI. Four different types of Vestas wind turbines were tested in the same wind source conditions. Currently there is a tendency towards larger turbines, with 2–5 MW rated energy generation, with rotor diameters that surpass 100 m and hub heights of 100–120 m 20 . In the Fig. 9 it has been shown that the turbine with the highest capacity factor was Vestas V100-1.8 MW 21 . The main characteristics of the selected wind turbines are presented in Table 3 . Consequently, the WAsP program was used to develop the wind farm set up with a site layout design of 5 wind turbines V100-1.8 that maximizes annual electric power production and minimizes wake losses. The WAsP simulation program is a software that calculates a regional wind atlas and a resource grid in order to establish wind farms by performing a wind source analysis based on long term anemometric tower data. Table 4 shows the electric power production, wake loss, mean wind speed, and power density data applicable in the two parks proposed for “Vajkal” and “Selite e Malit”. The values were calculated using the WAsP simulation program. The area with high wind potential in the proposed "Selitë e Malit" park is in the top of the mountain which is bare of vegetation. While the plateau at the foot of the mountain is wooded. Therefore, the turbines were placed in the top of the mountain. In the Fig. 10 it can be shown an important overview in regarding the visual and environmental impact of placing the turbines in the proposed areas. Economic analysis The decision to implement the proposed research work wind farm in the “Vajkal” and “Selite e Malit” areas will depend on the results of a detailed economic analysis. Wind energy costs The costs that generate the implementation of wind farms are determined by several important factors related to the source of the wind, the efficiency of the wind turbines, lifetime of wind farm, the time that wind turbines are able to generate electricity, site layout design, capital costs, financing costs, as well operation and maintenance costs or variable costs. The capital costs of wind energy projects or upfront capital cost are often referred to as capital expenditures (CAPEX) and are the costs that dominate in wind energy projects 22 . They consist of the cost of the turbines, their transport and installation, cost of grid connection, the construction cost including foundations, roads and buildings, underground cabling within the wind farm, as well as the licensing procedural costs, long term measurement costs and preliminary design of the wind energy project. While these costs vary based on the types of turbines, markets and locations where they are placed, they represent 80% of the total cost of the project over its entire lifetime. The largest cost component is the cost of the wind turbines. Wind turbine prices have declined globally over the last decade in spite of the continued increase in rotor diameters, hub heights and their rated powers. Since 2019 Vestas wind turbines continue to be under 1000 €, varying between 780 and 960 €/kW 22 , 23 . This has led to a decline in wind energy project capital costs regardless of some variability within the European Union. According to a report by the European Wind Energy Association (EWEA), the cost of installed power of onshore wind projects in Europe, differs between countries and typically varies from around 1100 €/kW to 1350 €/kW 24 , 25 . In 2019, the CAPEX was on average 1300 €/kW. The global weighted average total installed cost of onshore wind according to IRENA (2023) fell by 35% between 2010 and 2021, from 2042 to 1325 €/kW 22 . For the economic sensitivity analysis of the two projects in our study, the total installed capital cost was assumed to have the values of 1100 €/kW, 1200 €/kW, 1300 €/kW, and 1350 €/kW. The Variable costs of an onshore wind project consist of operating & maintenance (O&M) cost, land rental, insurance, taxes, and administration cost. O&M costs for onshore wind projects, according to IRENA 2021 data vary by location. Generally, in 2020 however, the O&M costs ranged between 10 and 30% of the LCoE for the majority of projects. Applying those percentages to the total investment cost, at the country level, between 2016 and 2019, O&M costs for onshore wind projects ranged from 33 €/kW per year in Denmark to 56 €/kW per year in Germany 20 . Nonetheless, investigations from several reputable sources have shown that O&M costs for onshore wind projects, in terms of cost per kWh, were between 0.01 and 0.02 €/kWh over the lifetime of the wind farm 23 . Since in Albania all onshore wind farm perspectives implementations are in the phase of collecting wind speed measurements on the ground, we do not have any data indicative of the O&M value. For this reason, in our research work, for both proposed parks O&M was assumed to be 0.018 €/kWh over the lifetime of the wind turbine or 55 €/kW of installed power. Methodology for wind energy cost analysis The main methods that represent the indicators for determining the efficiency and technical–economic character of energy systems in general and wind energy systems in particular were analyzed in this section. Levelized cost of electricity ( LCoE ) is an energy source measuring scale that has been used to compare the different methods of energy production through comparable criteria. This would be cost information for the investor to produce one kWh of electricity produced by a certain technology. LCoE can be calculated by using Eq. ( 2 ). Where n is the lifetime of the energy farm in which electricity is generated in years, E t is the annual energy production (AEP) in the year t (kWh) or (MWh), I t is CAPEX in year t (€), O&M t is operation and maintenance cost (OPEX) in year t (€), F t is fuel expenditures in the year t (€), and r is the discount rate 26 – 28 . The levelized cost of electricity of onshore wind farms in Europe, according to the Bloomberg New Energy Finance data, in 2018 ranges from 50 € to 65 €/MWh 29 . The Discount rate ( r ) is used to bring future costs back to their present value. We predict the project yearly income to remain the same during a 20-year project lifetime. However, due to inflation, this income would not have the same value in the future as it does now. The discount rate is used to calculate the decline in value of money in the future. This financial method is known as the discount cash flow. Discount rate values vary depending on the technology of the investment projects. Many studies analyzing wind energy project cost elements, based on the evidence gathered from the literature review, show that the range of discount rates for onshore wind energy projects varies between 7 and 10%, directly affecting the LCoE value. Several factors increase the perception of risk for wind energy technology investments including wholesale electricity prices, changes in government policy and less mature technology. The discount rate range for onshore projects is predicted to be between 5 and 8% in the year 2040. This takes into account the importance that renewable energy technologies are gaining currently not only due to the energy crisis but also to the 1.5 0 C climate target under the Paris Agreement. On the other hand, this will be paired with high expectations of improved wind technology maturity in the future. In this study the discount rate was assumed to be 5, 7 and 11%. The net present value ( NPV ), gives us the ability to estimate whether or not to move forward with the project. The total project yearly cash flow equals the given year’s income (B i ) minus that year’s costs C i . But this yearly project cash flow is expressed in today’s value of money. Then we subtract the initial capital investment cost C 0 from the total cash generated during the planned lifetime of the project N to obtain the next present value of the project. This is shown in Eq. ( 3 ). If the net present value is positive then the project is feasible and suitable for further consideration 30 . Internal rate of return ( IRR ) is considered to be the discount rate for which the Net Present Value (NPV) of the project is zero. This is expressed in Eq. ( 4 ). where N is the lifetime of the project in years, and C n is the cash flow for year n . An investment is considered acceptable if it’s IRR is greater than the investor’s minimum acceptable rate of return. The Benefit–Cost ratio ( B–C ) is an expression of the relative profitability of the project. It is calculated as a ratio of the present value of annual revenue minus the annual costs to the project equity which is expressed by Eq. ( 5 ). where f d is the debt ratio. The greater the value of this ratio, the bigger the return on investment in either revenue or savings terms. Obviously in order for the investment to be considered economically efficient this ration needs to be greater than one. Simple payback time refers to the number of years necessary for the project revenue by excluding debt payments and is equal to the total investment cost. While Equity payback indicates the years after which the project will generate income beyond the initial investment value. Research work proposal cost The RETScreen Expert model was used to perform the financial analysis and determine the aforementioned financial parameters LCoE, NPV, IRR, B-C , and SPB for the research work proposed in “Vajkal”, Bulqizë and “Selitë e Malit”, Tirana county. RETScreen Expert is a clean energy management software used for energy efficiency, renewable energy, energy performance analyses and environmental impact. Via sensitive analyses, this program quickly allows professionals to determine whether a proposed renewable energy research work contains financial parameters suitable to move it forward. Therefore, the RETScreen software is a great and user-friendly tool for analyzing the feasibility of renewable energy projects since it can estimate energy production, entire life cycle cost, and the greenhouse gas emission reductions resulting from implementing the project. In order to perform the financial analysis for the proposed projects, the model requests average monthly wind speed data as well as other climate data such as average air temperature, humidity, atmospheric pressure, etc. RETScreen referred to the climate data obtained from the National Aeronautics and Space Administration (NASA) regarding the geographic location of the antennas. Meanwhile, average monthly wind speed data was manually inputted in accordance to the NEWA hypothetical antennas in the 2005–2018 timeframe. Table 5 depicts the main tecno-economic components considered by RETScreen to conduct the financial analysis for the selected areas “Vajkal” and “Selite e Malit”. Based on the tecno-economic data in Table 5 , the RETScreen Expert model calculated the financial indicators presented in Table 6 . The difference between the annual energy production of the proposed parks calculated by WAsP and RETScreen are explained by the fact that RETScreen ran with average annual wind speed values from the NEWA hypothetical antennas which unlike the WAsP turbines were not positioned in the highest potential. The mean annual wind speed for the locations of the Vajkal and Selitë e Malit turbines from WAsP were found to be respectively 6.72 m/s and 6.81 m/s. Hence this difference is to be expected given that energy production is proportional to wind speed cubed. Sensitivity and risk analysis An important parameter that helps determine whether to produce wind energy is the energy production cost LCoE of the proposed wind farms. Figure 11 depicts LCoE as a function of the different values of total installation cost for discount rates 5, 7, and 11% and electricity export rate 76 €/MWh for the “Vajkal” and “Selitë e Malit” wind farms. From the Fig. 11 it has been clearly shown that the LCoE for the park proposed in “Vajkal” is similar to European wind farms for every discount rate value and for a total installation cost of 1350 €/kW. For the wind farm proposed in “Selitë e Malit”, the variation of LCoE as a function of annual energy production within a sensitivity range of ± 25%, at 1350 €/kW installation cost and at 11% discount rate, is given in Fig. 12 . Furthermore, in this sensitivity analysis it is observed that by increasing the annual electricity production by at least 9%, even when the proposed research work is perceived to be high risk, the LCoE calculated by the RETScreen model will be within the European wind farm values. Hence, we can consider the annual energy production calculated by WAsP, both proposed parks are feasible in terms of LCoE . Investors would be interested to understand what happens to the other important financial indicator such as NPV if the electricity export rate changes within a sensitivity range of ± 30%, assuming a total installation cost of 1350 €/kW, at 7 and 11% discount rates, see Fig. 13 . Through a total installation cost of 1350 €/kW, an inflation rate of 3%, a debt rate of 70%, a debt term of 15 years, and an electricity export rate within a range of ± 30%, it is observed that the NPV calculated at 7 and 11% discount rate reduces by a factor of 2.5 and 4 respectively if an electricity export rate of 60.80 €/MWh is assumed. For electricity export rates smaller than this value, the NPV declines significantly, sliding even into negative values. In this case the proposed “Vajkal” park is considered infeasible. For the park proposed in “Selite e Malit”, at the same parameters mentioned above, an electricity export rate would be no smaller than 70 €/MWh. This price can go down to 63.3 €/MWh if the total installation cost declines to 1125 €/kW. In the Fig. 14 it has been shown IRR as a function of the total installation cost (1100, 1200, 1300, and 1350 €/kW) and electricity export rate within a sensitivity range of ± 30%, calculated for a debt rate of 70% and inflation rate of 3%. The discount rate does not have an effect on IRR . As it can be seen, the lower the total installation cost is, the higher the IRR values. For an electricity export rate of 64.6 and 76 €/MWh, which actually is the electricity price benchmark, the IRR values for the project proposed in “Vajkal” are optimal throughout the entire range of electricity export rates in the graph. Another financial indicator is the Benefit–Cost ratio (B–C). B–C is an expression of the relative profitability of the project. B–C variation as a function of total installation cost and discount rate for 76 €/MWh for “Vajkal” and “Selitë e Malit” parks, is given in Table 7 . Sensitivity and risk analysis for “Selitë e Malit” park with the values highlighted in bold has shown that a total installation of 1300 and 1350 €/kW at discount rate 11% corresponds to the lower values B–C ratio values. However, the values of 1300 and 1350 €/kW at equity payback will not been acceptable and therefore the proposed research work in this case will not be feasible. Environmental impact The technology of producing electricity from wind energy does not emit greenhouse gases in the environment whereas the conventional technologies in energy production contributed 78% of total EU emissions 31 – 33 . The electricity produced in Albania comes 100% from renewable energies. Since Albania is a net importer of energy, it is forced, depending on the hydrological conditions, to import energy from the region and mainly from Kosovo. Coal is the most important energy source of Kosovo, from which about 97% of electricity is produced. Therefore, we can say that every MWh of energy produced by wind energy in Albania would contribute to the decarbonization of the energy sector in the region 34 – 38 . To calculate the contribution of the electricity produced by the two proposed parks to the reduction of CO 2 was used RETScreen Greenhouse Gas (GHG) Emission Reduction Analysis model. Scenarios were assumed as if this electricity was produced by coal-fired power plants in Kosovo, or by those with natural gas under the conditions of the parameters of the power plants in Germany. RETScreen model calculates the amount reduced in tCO 2 and equates it to barrels of crude oil not consumed. Figure 15 depicts the annual amount in tCO 2 that is reduced by producing electricity from the proposed parks in “Vajkal” and “Selitë e Mali” and is compared to the base case if this energy would be produced from coal. In Fig. 1 6, the base case that will replace the wind energy production is a natural gas plant. In this case, it will be reduced every year for 20 years of wind farms lifetime, the emission of 17,088.7 tCO 2 which is equivalent to 39,740.9 barrels of oil not consumed.

Conclusions This research work demonstrated the importance of implementing renewable energy in the metallurgical sector in Albania. It presented the possibility of implementing wind energy in the metallurgical companies that operate in Albanian for production of steel, aluminum and chromium. The Wind Balkan Atlas (WBA) and New European Wind Atlas (NEWA) were used to select the appropriate areas, while the Wind Atlas Analysis and Application Program (WAsP) was used to develop the wind potential distribution maps, and select the most suitable type of wind turbine based on capacity factors. The results show two suitable areas selected close to metallurgical sectors in the regions of “Vajkal” in Bulqizë and “Selitë e Malit” in Tirana. The selected areas can be classified as wind power class IV, V and VI. Vestas wind turbines type V100-1.8 has been selected and five wind turbines have been implemented for each area to maximizes annual electric power production and minimizes wake losses. It has been installed the power of 9 MW for each wind farm, with a capacity factor of 40% and 36.6% respectively, and with a total annual energy production of about 60 GWh/year, these wind farms will cover about 26% of the total annual consumption of companies. RETScreen Expert was used for the detailed economic analysis and environmental impact of proposed wind farms. The economic sensitivity analysis of the proposed wind farm in “Vajkal” showed that even for the highest installation cost value of 1350 €/kW, for discount rates 5, 7, and 11%, the LCoE values are within the statistically established range for wind farms in Europe. On the other hand, the wind farm in “Selite e Malit” would require an annual electricity production increase of at least 9% so that even when the project is considered at the highest risk level, the LCoE is still within established values. However, keeping in mind the annual energy production calculated from WAsP for optimizing the position of wind turbines, we can conclude that both wind farms proposed are feasible in terms of LCoE . From the implementation of the two proposed parks every year for 20 years of the wind farm lifetime of the parks, the emission of 52,579.9 tCO 2 and 17,088.7 tCO 2 will be reduced, respectively if this amount of energy will be produced by a coal or natural gas power plant. These wind farms will play an important role in the context of industrial energy communities in Albania. All the wind farms will serve as primary and supplementary source of energy by providing clean and renewable electricity in the whole industrial communities . In any energy crises these wind farms implementation can help these companies to avoid the import of electricity and increasement of the production prices of iron, steel, chromium and aluminum. Most of these industrial companies will not be dependent on non-renewable sources of energy and giving contribution to a more sustainable energy infrastructure. The study of the fluctuation of energy produced by wind farms and the profile over time of energy consumption by companies is an aspect of wind energy modeling for these industries. However, in the conditions of Albania, since wind energy is well-balanced with hydroelectric energy, diversifying energy sources will increase supply security. The future research work will be focused on continuing energy efficiency analysis through optimization process in the metallurgy sector by starting from materials flows, waste heat recovery, energy-efficient lighting and equipment.

The metallurgical industry, in the context of the global energy crisis and the new European green deal, needs urgent investments on energy and resource efficiency. The metallurgical sector, which includes the production of different metals is an energy-intensive industry that requires large amounts of energy for various processes such as smelting, refining, and casting. One of the largest consumptions of energy in Albania comes from the metallurgical sector during the production of iron, steel, chromium and aluminum which corresponds respectively to three private companies called “Kurum International Ltd”, “AlbChorme Ltd” and “Everest Ltd”. During the last three years, these companies have temporary interrupted the production process due to the higher electricity price that come from imports. Based on it, our research work presents the energy efficiency analysis in the Albanian metallurgical sector by focusing on the implementation of wind energy in the above mentioned private metallurgical companies, because adding new generation capacity from Renewable Energy Sources in a context of industrial energy communities, will contribute to improve the security of supply for this industry. The Wind Balkan Atlas, New European Wind Atlas, and Wind Atlas Analysis and Application Program (WAsP) has been used to select the appropriate areas and to develop the wind potential distribution maps, as well as to select the most suitable type of wind turbine based on capacity factors. Two areas were selected close to the metallurgical sectors in the regions of “Vajkal” in Bulqizë and “Selitë e Malit” in Tirana. It has been installed the power of 9 MW for each wind farm, with a capacity factor of 40% and 36.6% respectively, and with a total annual energy production of about 60 GWh/year, these wind farms will cover about 26% of the total annual consumption of companies. Clean Energy Management Software (RETScreen Expert) was used for the detailed economic analysis and environmental impact of proposed wind farms. The economic sensitivity analysis of the proposed wind farms showed that even for the highest installation cost value of 1350 €/kW, for discount rates 5, 7, and 11%, the LCoE values are within the statistically established range for wind farms in Europe. Subject terms

Abbreviations Annual energy produced Benefit–cost ratio Balkan Wind Atlas Capital expenditures European Wind Energy Association Geographic Information System International Energy Agency International Renewable Energy Agency Internal rate of return Levelized cost of electricity Modern-Era Retrospective Analysis for Research and Applications National Aeronautics and Space Administration New European Wind Atlas Net present value Operation and maintenance cost Observed wind climate Clean energy management software Universal Transverse Mercator Wind Atlas Analysis and Application Program Acknowledgements This work was supported by the Albanian National Agency for Scientific Research, Technology and Innovation and the Faculty of Mechanical Engineering of the Polytechnic University of Tirana. Author contributions All authors conceived this research work. K.D. and E.B. have been done the conceptualization, methodology, investigation, analysis, and writing the original draft. I.M. has made data collection and validation. P.M. and E.S. drew the figures. S.Q. has done economic analysis. Data availability The data that support the findings of this study are available from the corresponding author upon request. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1302

oa_package/e1/5a/PMC10788346.tar.gz

PMC10788347

38221522

Introduction Oral and maxillofacial bone defects resulting from many causes, including trauma, tumor removal, periodontitis or peri-implantitis, remain a challenge for clinical orthopedic surgery and oral medicine. When injured, bone tissue undergoes three continuing and overlapping regenerative phases: inflammation, regeneration and remodeling. 1 During the normal bone repair process, inflammation is triggered after injury and quickly resolves to create a proregenerative microenvironment that is enriched with proangiogenic and pro-osteogenic factors to stimulate bone regeneration and tissue repair. 2 However, unresolved chronic inflammatory conditions were found to negatively impact bone repair and result in increased rates of delayed healing and nonunion of fractures, which were prevalent in patients with osteoarthritis, type I diabetes, obesity, and rheumatoid arthritis. 3 Due to the distinctive structure of jawbones with teeth, oral and maxillofacial bone defects tend to be irregular and hard to graft with bulky or rigid biomaterials. Complex microbiota colonization in the oral cavity might exist as a source of infection, making the bone defect area chronically infected and impairing the normal healing process. 4 , 5 Thus, a practical biomaterial for repairing irregular oral and maxillofacial bone defects with immunoregulatory function via tissue engineering is still in high demand. MicroRNAs are endogenous small noncoding RNAs that regulate gene expression through post-transcriptional processing. 6 Studies have shown that miR-146a plays an important role in both immunoregulation 7 , 8 and bone homeostasis. 9 , 10 By directly targeting TRAF6 and interleukin-1 receptor-associated kinase 1 (IRAK1), two key adapter molecules in the NF-κB pathway, miR-146a negatively regulates the NF-κB-mediated immune response to microbial infection. 11 With higher expression observed in mouse periodontitis tissues, 8 miR-146a was reported to directly target Toll-like receptor 4 (TLR4) and downregulate its expression. 12 On the other hand, miR-146a was demonstrated to be positively associated with the development of ankylosing spondylitis 13 and to control age-related bone loss in mice. 9 Nucleic acid drugs require a high-efficiency delivery vector in local medication therapy, such as liposomes, cationic polymers and inorganic particles. 14 , 15 By modifying classical monodispersed silica colloidal particles, we fabricated MSNs with a rough surface and hollow mesoporous structure, 16 , 17 which accelerated the in vitro osteogenic differentiation of MC3T3-E1 cells with good biocompatibility as well as high cellular uptake efficiency and drug-loading capacity. 17 , 18 The osteogenic-promoting effect of MSNs may be attributed to magnesium ions by activating the Wnt/β-actin pathway and upregulating the expression of Runt-related transcription factor 2 (Runx2). 19 In addition, it was reported that a simple silica-based material (Si(OH) 4 ) could increase the expression of endogenous miR-146a in human bone marrow mesenchymal stem cells (hBMSCs) and promote osteogenic differentiation. 20 Thus, MSNs may be a suitable vector to load miR-146a in promoting inflammatory bone formation with a potential synergetic effect, and the nanosphere structure made MSNs easy to disperse into every corner of an irregular bone defect area. The objective of this study was to fabricate a novel nanomaterial, MSN+miR-146a, and assess the oligo transfection effect of MSNs as well as the effects of the biomaterial on both osteogenesis and immunoregulation to investigate its potential application value in treating irregular bone defects with an inflammatory microenvironment.

Materials and methods Materials and reagents Ammonium hydroxide aqueous solution (NH 3 ·H 2 O, 28%), ethanol, tetraethyl orthosilicate (TEOS), magnesium chloride hexahydrate (MgCl 2 ·6H 2 O) and ammonia chloride (NH 4 Cl) were all purchased from Aladdin Biochemical Technology Co., Ltd. (China), and polyethyleneimine (PEI, mw = 25 000) was purchased from Sigma-Aldrich (USA). Preparation and characterization of MSNs Magnesium silicate nanospheres (MSNs) were synthesized via a two-step route in accordance with our previous studies. 17 Monodispersed silica colloidal nanospheres (nano-SiO 2 ) with an average diameter of 200 nmol/L were prepared with the modified Stöber method. MgCl 2 ·6H 2 O (304.50 mg), NH 4 Cl (1.07 g) and NH 3 ·H 2 O (2.00 mL) were dissolved in 20 mL of deionized water. Nano-SiO 2 (200 mg) was dispersed in another 20 mL of deionized water with ultrasonic oscillation. Then, the two solutions were mixed and transferred into a reaction still and sealed to heat at 160 °C for 12 h. After naturally cooling to room temperature, the obtained MSNs were rinsed with deionized water and ethanol in turn and dried in vacuum at 60 °C overnight. The morphological and structural features of MSNs were examined by SEM (GeminiSEM 300, Zeiss, Germany) and TEM (JEM-1400flash, JEOL, Japan), and EDS was used to detect the main elements in MSNs. Modification of MSNs and preparation of the MSN+miR-146a complex MSNs were modified with PEI via electrostatic interactions. 21 MSNs were resuspended in deionized water (1 mg/mL) and added to an equivalent PEI solution (1 mg/mL), and the mixed solution was stirred at room temperature at 400 r/min for 3 h. After centrifugation and thorough washing with deionized water, MSN-PEI was prepared and stored in deionized water at a 1 mg/mL concentration and examined by TEM. MiR-146a in this study is referred to as miR-146a-5p, and its sequence is shown in Table S1 . MSN solutions (10 μL) were combined with miR-146a solutions (0.05 μg, 10 μL) at various weight ratios (MSN:miR-146a = 0:1, 25:1, 50:1, 75:1, 100:1, 125:1, 150:1, 200:1), mixed with a vortex mixer for 1 min and then incubated at 4 °C for 30 min. The optimal loading ratio was confirmed using a gel retardation assay with 1% agarose gel containing 1 × GelRed (Us Everbright, USA). The MSN+miR-146a complex was added to 10 × loading buffer, and electrophoresis was carried out at 100 V for 10 min in TAE running buffer (Mei5Bio, China). The miR-146a gel was visualized with a ChemiDoc MP Imaging System (Bio-Rad, USA). Then, the surface charge of MSNs adsorbing various amounts of miR-146a was estimated by a zeta potential analysis meter (Surpass, Anton Paar, Austria). Cell culture hDPSCs were isolated from third molars (clinical waste) or permanent teeth from adolescents following reported protocols, 40 which were approved by the Ethical Committee of Stomatology Hospital of Zhejiang University School of Medicine (ethics approval number: 2023-027) in accordance with the Helsinki Declaration. Written informed consent was obtained from the subject or subject’s parents. Briefly, dental pulp was extracted with a dentinal excavator and then gently rinsed with phosphate-buffered solution (PBS) (Cienry, China). After being dissected into 1–2 mm 3 pieces, the dental pulp tissue was planted into a 25 mm 2 culture flask containing 1 mL of fetal bovine serum (FBS) (Gibco, USA) and cultured in a humidified incubator at 37 °C with 5% CO 2 for 6 h. Then, 0.5 mL of minimum essential medium α (MEM α) containing 2 mmol/L L-glutamine (Gibco, USA) with 10% FBS and 100 U/mL streptomycin/penicillin (Cienry) (complete MEM α) was added into the flask for further culture. The medium was gently changed every 3 days, and the cells were passaged until 80% confluence using 0.05% trypsin containing ethylenediaminetetraacetic acid (EDTA) (Thermo Fisher, USA). hDPSCs after P3 were collected for the study. Mouse BMMs were harvested from the femur and tibia bones of 5-week-old male C57BL/6J mice (Zhang et al., 2008). The bone marrow was flushed out using a 25G needle and 1 mL syringe filled with cold MEM α until the bones turned pale. The turbid cell liquid was pipetted up and down and then filtered through a 70 μm filter. After centrifugation at 250 g for 5 min, the supernatant was discarded, and the cell pellet was resuspended and incubated in ammonium-chloride-potassium (ACK) lysing buffer (Amizona, USA) for 90 s to remove red blood cells. After PBS washes and centrifugation, the cells were resuspended in complete MEM α with 20 ng/mL recombinant mouse macrophage colony-stimulating factor (M-CSF) (Amizona) (MΦ-MEM α). The cells were counted and directly seeded at 1 × 10 5 cells/well into 24-well plates. The same BMMs were treated with 40 ng/mL M-CSF and an additional 40 ng/mL recombinant mouse receptor activator of nuclear factor kappa-B ligand (RANKL) (Amizona) to induce osteoclast differentiation. All animal procedures (including following in vivo experiments) were approved by the Institutional Animal Care and Use Committee of Zhejiang Center of Laboratory Animals (approval No. ZJCLA-IACUC-20010204). Cytotoxic assay of MSNs hDPSCs were seeded at 2 × 10 3 cells/well in 96-well plates. The next day, MSNs were added at various final concentrations (0–50 μg/mL). After coculture for 8 and 24 h, the CCK-8 assay was performed using a CCK-8 Cell Proliferation Kit (Beyotime, China) in accordance with the manufacturer’s instructions. Cellular uptake assay hDPSCs were seeded at 1.5 × 10 3 cells/well on glass coverslips in 24-well plates. The next day, 25 μg/mL MSN+miR-146a-FAM complex (MSN:miR-146a-FAM = 75:1) was added and cocultured with hDPSCs for 24 h. Then, the cells were fixed with 4% (v/v) paraformaldehyde (Haoke Biotech, China) and permeabilized with 0.1% (v/v) Triton X-100 (Servicebio, China). The cells were stained with rhodamine-labeled phalloidin (Invitrogen, USA) to label the cytoskeleton, a DiI probe (Beyotime) to label the cell membrane or LysoTracker Red (Beyotime) to label lysosomes before mounting with DAPI (Servicebio). Samples were imaged using a laser scanning confocal microscope (LSM980, Zeiss). Transfection of miR-146a and in vitro cell experiments All cells were divided into four groups: the miR-146a group and NC group (purely transfected with miRNA by lipidosome), MSN group (loading nonsense oligo) and MSN+miR-146a group. hDPSCs were seeded at 1.5 × 10 4 cells/well in 24-well plates. When cells became confluent, in the non-MSN groups, 20 nmol/L miR-146a or NC miRNA was transfected with Interferin, while the corresponding MSN+miR-146a or MSN-NC complex (MSN: miRNA = 75:1) was added to the MSN-treated groups. After 6 h of culture, all hDPSCs were thoroughly washed in PBS and incubated in fresh complete MEM α with 50 μg/mL ascorbic acid (Mecklin, China), 10 mmol/L β -glycerophosphate (Sangon Biotech, China) and 100 nmol/L dexamethasone (Mecklin) (osteogenic MEM α). The medium was changed every 3 days. The osteogenic differentiation of hDPSCs was evaluated by specific in vitro staining using an ALP staining kit (Beyotime, China), ALP activity assay kit (Beyotime) and SR staining kit (Phygene, China) on Day 7 followed by an ARS staining kit (Beyotime) on Day 14 according to the manufacturer’s instructions. For BMMs, the medium was first changed 2 days after plating, and miR-146a and NC miRNA were transfected with Interferin or MSNs similarly for 6 h. Then, fresh MΦ-MEM α containing 1 μg/mL LPS (Mei5bio) was added to induce the polarization of BMMs. The supernatant was collected and directly added to another culture plate of hDPSCs (already received the same miRNA transfection as above) for 24 h to stimulate an inflammatory microenvironment for hDPSCs. For osteoclasts, the transfection of miRNA was performed on day 3 after M-CSF and RANKL treatment, and the medium was first changed on day 4. Osteoclastic differentiation was evaluated by a TRAP staining kit (Amizona). Quantitative RT‒PCR hDPSCs were collected after culture in osteogenic MEM α for 7 days or coculture with LPS-stimulated BMM-derived conditioned medium for 24 h, and BMMs were collected after 24 h of 1 μg/mL LPS stimulation. Total RNA was extracted with an RNA extraction kit (Vazyme, China) and quantified with a Nanodrop 3000 (Thermo Fisher). Reverse transcription (RT) of mRNA was performed with 400 ng RNA using a cDNA synthesis kit (Vazyme), and RT of miRNA was performed with 100 ng RNA using a miRNA synthesis kit (Accurate Biology, China). Then, qPCR was carried out on QuantStudio 7 Flex (Life Technology, USA) using HiScript II Q RT SuperMix for qPCR (Vazyme) in a 10 μL reaction volume. β-actin and U6 were used as the endogenous reference genes. The sequences of the primer pairs are presented in Table S1 . The relative gene expression level of target genes was calculated using the ΔΔCt method. Western blotting HDPSCs after 7 days of osteogenic induction and BMMs after 24 h of 1 μg/mL LPS stimulation were lysed in RIPA lysis buffer (Beyotime) for 30 min on ice, ultrasonicated for 3 s, and then centrifuged at 15 000 × g at 4 °C for 5 min. The protein concentration of the supernatant was determined using a BCA protein kit (Beyotime). After the samples was mixed with 5 × SDS loading buffer (Mei5bio) to obtain 1 μg/μL protein solution, sodium dodecyl sulfate–polyacrylamide gel electrophoresis was conducted to separate proteins with 10 μg per lane. Then, the protein was transferred to a 0.2 μm polyvinylidene difluoride (PVDF) membrane (Sigma-Aldrich). After being blocked in 5% defatted milk for 50 min at room temperature, the membrane was incubated at 4 °C overnight with primary antibodies against the following proteins: β-actin (1:10 000, 66009-1-Ig) and GAPDH (1:10 000, 60004-1-Ig) (both from Proteintech, USA); Col1a1 (1:1 000, 720260S), TRAF6 (1:500, 67591), p65 (1:500, 8242) and p-p65 (1:500, 3033) (all from Cell Signaling, USA); OSX (1:1 000, ab209484) and VEGF-A (1:1 000, ab214424 (both from Abcam, USA); and RUNX2 (1:500, ET1612-47, Huabio, China). Following a 1 h incubation with secondary horseradish peroxidase (HRP)-conjugated anti-mouse or anti-rabbit IgG antibodies (1:10 000, SA00001-1 and SA00001-2, Proteintech) at room temperature, the membrane was visualized with an enhanced luminol-based chemiluminescent (ECL) kit (Thermo Fisher) and exposed in a ChemiDoc MP Imaging System (Bio-Rad). Flow cytometry BMMs were collected after 24 h of 1 μg/mL LPS stimulation using 0.05% trypsin and resuspended in PBS after centrifugation. Flow cytometry staining was performed according to the manufacturer’s instructions. PE F4/80 antibody (123109) and PerCP/Cy5.5 CD11b antibody (101227) (both from BioLegend, USA) were used to mark mouse macrophages. BV421 CD40 antibody (562846, BD Pharmingen, USA), Alexa Fluor (AF) 488 Arg-1 antibody (53-3697-82) and SB436 CD163 antibody (62-1631-82) (both from Thermo Fisher) were used to stain BMMs as markers of M1 or M2 polarization for 30 min on ice. Data acquisition was performed using CytoFlex (Beckman Coulter, USA) and analyzed with CytoExpert software (Beckman Coulter). Cell immunofluorescence assay HDPSCs after 7 days of osteogenic induction and BMMs after 24 h of 1 μg/mL LPS stimulation were washed thoroughly with PBS, fixed in 4% (v/v) paraformaldehyde and permeabilized with 0.1% (v/v) Triton X-100. The hDPSCs were stained with RUNX2 antibody (1:5 000, 1256S, Cell Signaling) overnight at 4 °C and incubated with secondary AF488 anti-rabbit antibody (1:500, 21441, Thermo Fisher) for 2 h at room temperature. BMMs were stained with CD86 (1:500, 26903-1-AP, Proteintech) or AF488 Arg-1 antibody (1:500, 53-3697-82, Thermo Fisher) overnight at 4 °C followed by secondary CoraLite 594 anti-rabbit antibody (for CD86) (1:500, SA00013-4, Proteintech) for 2 h at room temperature. The cytoskeleton was stained with rhodamine-labeled phalloidin if needed before mounting with DAPI. Samples were imaged using an LSM980 laser scanning confocal microscope, and the mean IF intensity was quantitatively measured by ImageJ software. Mouse mandibular bone defect model Eight-week-old male C57BL/6 mice were used to create mandibular bone defect models and divided into four groups: Blank, GelMA, MSN, MSN+miR-146a ( n = 10 each). GelMA refers to a commercial gelatin methacryloyl hydrogel (EFL-GM 90, Engineering for Life, China). A 5% GelMA solution containing 1 mg/mL MSN with or without a corresponding amount of miR-146a was freshly prepared. Mice were anesthetized by intraperitoneal injection of 2,2,2-tribromoethanol (200 mg/kg; Sigma-Aldrich, USA), and the left mandibular region was shaved and disinfected. A 5-mm-long incision was made to expose the mandibular bone, and a 2 × 1.5 × 1 mm 3 critical-size bone defect was created using a high-speed round bur. Approximately 5 μL of gel solution containing 50 μg/mL LPS and the appropriate biomaterial was injected per site and photocured with 405 nmol/L light, while the blank group was administered the same amount of PBS with LPS at the same time. The incision was carefully closed with a 5-0 silk suture. All mice were monitored every day, and no adverse effects were observed. After 2 and 4 weeks of healing, animals were euthanized using carbon dioxide, and mandible samples were collected and fixed in 4% (v/v) paraformaldehyde for 24 h followed by 70% ethanol at 4 °C. Microcomputed tomography (CT) assay and biomechanical test Mouse mandible samples were scanned using micro-CT (U-CT-XUHR, Milabs, The Netherlands) at a voltage of 55 kV and current of 0.17 mA with a 75 ms exposure time. After 3D volume rendering of scan data in Imalytics software (Gremse-IT, Germany), a virtual cylinder was created (1.2 mm diameter and 1 mm height) inside the mandibular bone defect area and designated as the region of interest (ROI). The bone grayscale threshold was set at 1 400 Hounsfield units (HU) for all samples. The BV/TV, BMD and Th. Sp were calculated to compare new bone formation among groups. Another set of mice ( n = 8) was euthanized after 4 weeks of healing. The paraformaldehyde-fixed mandibles were trimmed into 10 × 4 mm strip-like samples and subjected to a three-point bending test performed in an electronic universal material testing machine (5943, Instron, USA). The middle probe of the machine was directly pressed on the bone defect area, and the mean maximal force detected in the bending process was recorded for statistical analysis. Histological and immunofluorescence analyses The mandible samples were decalcified in a fast decalcified solution (Biotech, China) for 24 h at room temperature, dehydrated in graded ethanol and then embedded in wax. The tissue was cut into 5 μm sections using a microtome (Leica) and stained with HE, Masson’s trichrome and TRAP with commercial staining kits (Servicebio) to assess new bone formation and osteoclast function. After being blocked with bovine serum albumin (Servicebio), the sections were incubated with primary antibodies against Arg-1 (1:500, GB11285, Servicebio) and Runx2 (1:500, GB11264, Servicebio) as well as CD86 (1:500, 26903-1-AP, Proteintech) and Osx (1:500, ab209484, Abcam) at 4 °C overnight. Then, the sections were incubated with appropriate secondary antibodies (Servicebio) before mounting with DAPI. Samples were imaged using a DMI8 inverted fluorescence microscope (Leica Microsystems, Germany) and an LSM980 laser scanning confocal microscope with quantitative analysis by ImageJ. Data analysis Data were analyzed using Prism 8.0 software (GraphPad, USA) and are represented as the mean ± standard deviation (SD). Student’s t -test or one-way analysis of variance (ANOVA) was used to analyze the differences among groups followed by Tukey’s or Dunnett’s multiple comparison tests. The statistical significance level was set at P < 0.05.

Results Fabrication of the MSN+miR-146a complex The main results of this study are summarized in Fig. 1 . MSNs were obtained after modifying classical monodispersed silica colloidal nanospheres (Fig. 1a ). As shown in Fig. 2a, b , scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images showed a rough surface and hollow mesoporous morphology of homogeneous MSNs with a mean diameter of 200 nm. The main elements of MSNs were determined to be magnesium, silicon and oxygen in the energy-dispersive spectroscopy (EDS) spectrum (Fig. 2c ). Figure 2d shows the changed morphology of MSNs after polyethyleneimine (PEI) modification. The toxicity of MSN-PEI in hDPSCs was then validated. As shown in Fig. 2e , the viability of hDPSCs in the CCK-8 test exhibited no differences from that of the blank control group after coculture with MSNs for 48 h at a concentration of 10, 25 or 50 μg/mL, indicating good biocompatibility of MSNs even after PEI modification. Then, a gel retardation assay showed that when the amount of MSNs was increased, more miR-146a remained in the well, and only a negligible amount of miR-146a was released when the weight ratio of MSN:miR-146a was greater than 75:1 (Fig. 2f ). The zeta potential of the MSN+miR-146a complex gradually switched from negative to positive when the amount of MSNs was increased (Fig. 2g ). These results suggested that the optimal miR-146a-loading capacity of MSNs was at a 75:1 weight ratio. To evaluate the cellular uptake of the MSN+miR-146a complex, we mixed FAM-conjugated miR-146a with MSNs at the optimal weight ratio and then cocultured them with hDPSCs for 24 h before thorough washing with PBS. As shown in Fig. 2h, i , the MSN+miR-146a complex was endocytosed into hDPSCs with punctate green fluorescent signals in the cytoplasm indicated by cytoskeletal (phalloidin) or cell membrane (Dil probe) staining. Moreover, lysosomal staining showed colocalization of lysosomes and MSN+miR-146a-FAM, which indicated that the complex was partly encapsulated in lysosomes after internalization. MSN+miR-146a promoted osteogenic differentiation of hDPSCs As pluripotent stem cells, hDPSCs can differentiate into multiple tissue cells, including osteoblasts, under classical osteogenic induction. To determine the effects of both MSNs and miR-146a on the osteogenic differentiation of hDPSCs, we used commercial liposomes, Interferin (Polyplus, France), and MSNs to transfect miR-146a separately, with nonsense miRNA chains as a negative control (NC). The transfection efficiency of miR-146a into hDPSCs was measured by quantitative reverse transcription-polymerase chain reaction (qRT‒PCR) after 7 days of osteogenic induction culture. As shown in Fig. S1a , the level of miR-146a in the miR-146a group or MSN+miR-146a group was significantly greater than that in the corresponding control group. Notably, the miR-146a level was significantly increased in the MSN group compared to the NC group, indicating an effect of MSNs on promoting endogenous miR-146a expression. As biomarkers in osteogenesis, alkaline phosphatase (ALP) staining and Sirius red (SR) staining showed that miR-146a significantly upregulated the expression of ALP and type I collagen (Col1a1) in hDPSCs after 7 days of osteogenic induction, which was not affected by MSNs themselves (Fig. 3a, b ). Then, the enzymatic activity of intracellular ALP was determined by a specific enzyme reaction, which was slightly increased in the miR-146a group but strongly increased in the MSN+miR-146a group (Fig. 3d ). The western blot (WB) results also supported the upregulation effect of miR-146a on Col1a1 expression at the protein level (Fig. 3h ). qRT‒PCR also confirmed the promoting effect of miR-146a on ALP and Col1a1 mRNA expression (Fig. 3g ). Finally, for definite identification of osteogenic differentiation of stem cells, extracellular matrix mineralization was evaluated by typical Alizarin red S (ARS) staining. ARS distinctly increased in both the miR-146a group and MSN group and rose to the highest level in the MSN+miR-146a group after 14 days of osteogenic induction, indicating a synergic promoting effect of the two components, especially in the late phase of osteogenic differentiation of hDPSCs (Fig. 3c ). On the other hand, the mRNA and protein expression of the critical osteogenic transcription factors RUNX2 and Osterix (OSX) was found to be significantly upregulated in the MSN-treated groups compared with the non-MSN groups, but no evident difference was observed between the miR-146a-treated group and the corresponding NC group (Fig. 3g, h ). Higher expression of RUNX2 was also observed in the MSN-treated groups after 7 days of osteogenic induction via immunofluorescence (IF) assays (Fig. 3e, f ). Interestingly, when assessing the effect of MSN+miR-146a on the immunoregulatory function of hDPSCs, we found that MSNs significantly upregulated the expression of vascular endothelial growth factor-A (VEGF-A) when cocultured with LPS-treated BMM-derived conditioned medium for 24 h. However, this effect was potently inhibited by exogenous miR-146a, which decreased the expression of VEGF-A to a normal level, similar to that of the NC group (Fig. 3i, j and Fig. S3 ). MSN+miR-146a regulated the polarization of macrophages and osteoclast formation In an inflammatory microenvironment, macrophages play a crucial role in bone immunity. Here, we investigated the effect of MSN+miR-146a on mouse BMM polarization under LPS stimulation with the same miRNA transfection protocol as that used for hDPSCs. Mouse BMM purity (>95%) was confirmed by both F4/80 and CD11b dual biomarkers (Fig. S2a ). As shown in Fig. S1b , miR-146a expression was significantly upregulated after transfection by either liposomes or MSNs in BMMs such as hDPSCs. Nevertheless, MSNs themselves did not affect the expression of endogenous miR-146a in BMMs. As shown in Fig. 4b and Fig. S2b , after 24 h of 1 μg/mL LPS stimulation, the proportion of CD40 high M1-polarized BMMs decreased significantly in the miR-146a group and the MSN+miR-146a group compared to the corresponding control group. On the other hand, the proportion of arginase 1 (Arg-1) high or CD163 high M2-polarized BMMs apparently rose to higher levels in the MSN-treated groups than in the non-MSN groups. Although the proportion of CD40 high M1 BMMs increased with only MSNs, this effect could be reversed by loading miR-146a, resulting in a lower level than that in the NC group. Similar trends in BMM polarization changes were further confirmed by IF staining with CD86 as an M1 marker and Arg-1 as an M2 marker (Fig. 4c–e ). Accordingly, the mRNA expression of the critical proinflammatory cytokines interleukin (IL)-1β and IL-6 was potently downregulated by miR-146a, while the mRNA expression of Arg-1 increased significantly in the MSN-treated groups compared with the non-MSN groups, with a similar but weaker trend detected for IL-10 expression (Fig. 4b ). The effect of MSN+miR-146a on the activation of the canonical NF-κB pathway was examined. The expression of TRAK6 at both the mRNA and protein levels was significantly downregulated by miR-146a, and the phosphorylation level of p65 decreased as well, indicating that the NF-κB pathway was inhibited by miR-146a in mouse macrophages (Fig. 4f, g ). In addition, the effect of MSN+miR-146a on osteoclast formation was evaluated. In vitro tartrate-resistant acid phosphatase (TRAP) staining experiments showed that miR-146a strongly inhibited osteoclast differentiation and maturation of osteoclast progenitor cells from mouse bone marrow (Fig. 4h, i ), and the mRNA expression of cathepsin K (CTSK) and dendritic cell-specific transmembrane protein (DC-stamp) was significantly downregulated by miR-146a (Fig. 4j ). MSN+miR-146a accelerated bone regeneration in simulated infected mouse mandibular defects To investigate the effect of the MSN+miR-146a complex on in vivo osteogenesis, we generated mouse-infected mandibular bone defect models, and the biomaterials were delivered by a commercial photocuring hydrogel, GelMA. As shown in Fig. 5a , after 2 weeks of uneventful healing, an oval defect could still be observed in all mandibles, with more calcified new bone detected in the MSN group and MSN+miR-146a group. Quantitative analysis showed that compared to those of the blank group, both the bone volume/total volume (BV/TV) and bone mineral density (BMD) of new bone increased slightly in the GelMA group but increased substantially in the MSN group and MSN+miR-146a group, while separation of trabecular bone (Th. Sp) showed the opposite trend. After 4 weeks of healing, the MSN group and MSN+miR-146a group showed better healing with more regenerated high-density mineralized tissue in the defect area. Similarly, the BV/TV and the BMD increased in the three experimental groups but most significantly in the MSN+miR-146a group, with Tb.Sp revealing the opposite trend (Fig. 5b ). The biomechanical properties of the bone defect region after 4 weeks of healing were tested via a three-point bending test, which showed that the mean maximal force detected in the bending process was significantly increased in the MSN group and MSN+miR-146a group (Fig. 5c ). Further histological results also supported the osteogenic-promoting effect of the MSN+miR-146a complex. As shown in Fig. 6a , much more premature bone tissue was observed in the defect area in the MSN group and MSN+miR-146a group after 2 weeks of healing than in the blank group and GelMA group, which was more distinct with blue-stained collagen in the Masson staining results (Fig. 6b ). Similarly, the MSN group and MSN+miR-146a group recovered better with relative contact with the outer bone plate 4 weeks after surgery, as revealed by the HE and Masson staining results (Fig. 6a, b ). The semiquantitative analysis of the bone tissue area supported the beneficial effects of MSNs and miR-146a on bone regeneration (Fig. 6c ), with the highest proportion of hard tissue detected in the MSN+miR-146a group. In vivo osteoclast formation was assessed simultaneously in the 2 week healing groups. Only in the MSN+miR-146a group did the formation of TRAP+ osteoclasts significantly decrease in the simulated infected bone defects (Fig. 6d ). IF staining revealed the immunoregulatory and osteogenic-promoting effects of the MSN+miR-146a complex. As shown in Fig. 7a , after 2 weeks of healing, a lower level of CD86 high M1 BMMs was observed in the MSN+miR-146a group, but a significantly higher level of Arg-1 high M2 BMMs was found in the MSN group and the MSN+miR-146a group. The expression of Runx2 was significantly increased in the MSN+miR-146a group, and the expression of OSX was evidently increased in both the MSN group and MSN+miR-146a group (Fig. 7b ). These results cumulatively suggested that with the help of the GelMA hydrogel, MSN+miR-146a could promote early osteogenesis in stimulated infected mouse mandibular defects with immunoregulatory capacity in macrophages.

Discussion In this study, we comprehensively investigated the application potential of the MSN+miR-146a complex in treating irregular bone defects with an inflammatory microenvironment. The biocompatibility and endocytosis ability of pure MSNs have been confirmed in our previous studies. 16 – 18 Here, PEI, a polymer with a high density of positively charged amino groups, was utilized to increase the oligo-loading capacity of MSNs. 21 PEI-modified MSNs remained favorable for biocompatibility, and the optimal weight ratio of MSNs and miR-146a was determined to be 75:1, giving the complex a positive surface charge to better bind with the negatively charged cell membrane. 22 HDPSCs, first isolated in 2000, 23 appear to be a promising stem cell resource with high proliferation, multidifferentiation potential, 24 , 25 and easier surgical access with less risk of donor site morbidity. 26 , 27 In this study, miR-146a and MSNs were observed to accelerate the in vitro osteogenesis of hDPSCs in different ways. By directly downregulating the tumor necrosis factor α-induced NF-κB pathway, miR-146a was reported to block its negative influence on the osteogenic differentiation of M3CT3-E1 preosteoblasts, 20 indicating that the promoting effect of miR-146a on osteogenesis may be associated with the classical NF-κB pathway. However, the expression of ALP and Col1a1 was not affected by MSNs and appeared to be lower in the MSN+miR-146a group than in the miR-146a group. This result might be attributed to the slower intracellular release of miRNA from high-absorbability hollow nanospheres than from commercial liposomes. Di et al. (2018) reported that by directly targeting Dickkopf-related protein 1, the negative feedback inhibitor in Wnt/β-actin signaling, miR-146a knockout could reverse the excess osteogenic potential in ankylosing spondylitis fibroblasts. 13 However, the speculated upregulation of RUNX2 via the Wnt/β-actin pathway after miR-146a overexpression was not observed in hDPSCs, which needs further investigation. After being internalized, MSNs can be degraded by lysosomes and sustainably release silicon and magnesium ions. Although the silicon-based biomaterial was reported to upregulate endogenous expression of miR-146a in hBMSCs, 20 this effect was weak when compared to the magnitude of exogenous miR-146a. On the other hand, magnesium ions were reported to improve the expression of RUNX2 by activating the Wnt/β-actin pathway. 19 OSX, a zinc finger transcription factor essential to osteogenesis that acts downstream of RUNX2, 28 showed similar significantly upregulated expression in MSN-treated groups, as expected. Interestingly, more mineralized nodules were observed in the MSN-treated groups, suggesting that MSNs might also act as self-standing cores for matrix mineralization. Higher in vivo expression of Runx2 and Osx was also observed in stimulated infected mouse mandibular defects after administration of MSNs, although the upregulation of Runx2 only showed a significant difference in the MSN+miR-146a group. Potent immunoregulatory functions indicate that hDPSCs have more application potential in treating inflammatory bone defects. 29 Surprisingly, MSNs upregulated the expression of VEGF-A in hDPSCs in a simulative inflammatory microenvironment. However, the effect was strongly eliminated by miR-146a, implying a potential shortage of this nucleic acid drug when considering angiogenesis in bone regeneration. 30 In further studies, appropriate molecular drugs may be combined with MSNs to enhance the indirect proangiogenic effect of MSNs. Macrophages play a crucial role in maintaining homeostasis, including bone tissues. 31 As an anti-inflammatory miRNA, 11 miR-146a was reported to be endotoxin-responsive and targeted critical inflammation-related proteins in human monocytes, including TRAF6, IRAK1 and TLR4. 12 , 32 As expected, both in vitro and in vivo M1-polarized BMMs significantly decreased after treatment with miR-146a, which could be attributed to the negative post-translational repression of miR-146a on TRAF6, a crucial intracellular factor that mediates activation of the NF-κB pathway when TLR4 binds specific antigens such as LPS. 33 The lower phosphorylation level of p65 supported the negative regulation of miR-146a on the canonical NF-κB pathway in mouse macrophages. Notably, M1-type BMMs were relatively increased due to MSN addition, which might be a result of foreign body reactions elicited in macrophages by nanoparticle biomaterials, 34 but the inevitable side effect could be finally decreased by miR-146a to a lower level. Interestingly, MSNs significantly increased the proportion of both in vitro and in vivo M2-type BMMs even under high-concentration LPS conditions. It is widely believed that an in-time shift of the macrophage population from a proinflammatory to a proregenerative phenotype is beneficial to bone regeneration after injury, 33 , 35 and the immunomodulatory effect of MSNs gives biomaterials additional potential in treating bone defects with chronic inflammation. High levels of proinflammatory cytokines such as TNF-α and sustained activation of NF-kB signaling are thought to be critical reasons for impaired bone regeneration in chronic inflammatory conditions, 36 which could result in hyperactive osteoclast formation as well. Here, miR-146a potently inhibited in vitro and in vivo osteoclast formation, which may be attributed to the same downregulating effect on TRAF6. 37 , 38 This result suggested the therapeutic potential of MSNs in bone regeneration with an inflammatory microenvironment through regulation of the osteogenesis-osteoclasis balance. There are some limitations of this study. Although the application value of hDPSCs has been widely investigated in bone engineering, the promoting effect of MSNs+miR-146a on the in vitro osteogenesis of hDPSCs should be carefully interpreted, and further studies that incorporate stem cells into the biomaterial system are needed. In addition, the LPS-stimulated mouse-infected mandibular defect model could not fully simulate clinical cases of oral-maxillofacial bone defects resulting from microbial infection, such as periodontitis. Therefore, large animal bone defect models with pre-existing periodontitis or a severe bacterial infection should be built. Due to the hollow mesoporous structure and high adsorption capacity, MSNs could load multiple molecular drugs together with miR-146a to create multifunctional nanomaterial systems, which included benidipine (an antihypertensive drug) that was demonstrated to promote osteogenesis and angiogenesis. 18 , 39

Conclusion By loading the multifunctional nucleic acid drug miR-146a, the pro-osteogenic nanomaterial MSNs successfully accelerated the osteogenic differentiation of hDPSCs and new bone formation in stimulated infected mouse mandibular bone defects with satisfying immunoregulatory capacity in macrophage polarization. The MSN+miR-146a biomaterial complex delivered by the photocuring hydrogel showed good therapeutic potential in treating irregular bone regeneration with an inflammatory microenvironment.

Reconstruction of irregular oral-maxillofacial bone defects with an inflammatory microenvironment remains a challenge, as chronic local inflammation can largely impair bone healing. Here, we used magnesium silicate nanospheres (MSNs) to load microRNA-146a-5p (miR-146a) to fabricate a nanobiomaterial, MSN+miR-146a, which showed synergistic promoting effects on the osteogenic differentiation of human dental pulp stem cells (hDPSCs). In addition, miR-146a exhibited an anti-inflammatory effect on mouse bone marrow-derived macrophages (BMMs) under lipopolysaccharide (LPS) stimulation by inhibiting the NF-κB pathway via targeting tumor necrosis factor receptor-associated factor 6 (TRAF6), and MSNs could simultaneously promote M2 polarization of BMMs. MiR-146a was also found to inhibit osteoclast formation. Finally, the dual osteogenic-promoting and immunoregulatory effects of MSN+miR-146a were further validated in a stimulated infected mouse mandibular bone defect model via delivery by a photocuring hydrogel. Collectively, the MSN+miR-146a complex revealed good potential in treating inflammatory irregular oral-maxillofacial bone defects. Subject terms

Supplementary information

Supplementary information The online version contains supplementary material available at 10.1038/s41413-023-00299-0. Acknowledgements This work is supported by the National Key R&D Program of China (No. 2022YFC2402900), the National Natural Science Foundation of China (No. 81991502), the Key Research and Development Program of Zhejiang Province, China (No. 2021C03074), the Basic Public Welfare Project of Zhejiang Province, China (No. LY22H140002), the Research and Development Program of the Stomatology Hospital, Zhejiang University School of Medicine (No. RD2022JCEL20) and the Student Research Training Program of Zhejiang University School of Stomatology (No. 2022S001). Author contributions J.Y. performed the fabrication of biomaterials and a part of the in vitro and all in vivo experiments and wrote the manuscript. J.S. conducted some of the in vitro experiments and revised the manuscript. L.S., J.L., M.S., and W.A. revised and edited the manuscript. M.Y., B.W., and Q.C. designed and supervised the study. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Bone Res. 2024 Jan 15; 12:2

oa_package/c0/85/PMC10788347.tar.gz

PMC10788348

38221551

Introduction Systemic lupus erythematosus (SLE) is a multisystem autoimmune disorder with the breakdown in self-tolerance and the generation of autoantibodies. 1 – 3 Double-negative (CD3 + CD4 - CD8 - , DN) T cells, a unique subset of T cells lacking CD4 and CD8 co-receptors, play a significant role in the pathogenesis of autoimmune diseases, such as SLE. 4 During SLE progress, DN T cells invade into multiple organs, contributing to the loss of tolerance. Besides, DN T cells are able to facilitate B cell differentiation to enhance the generation of autoantibodies. Moreover, DN T cells produce significant amounts of IFN-γ and IL-17, which can promote the development of SLE. 5 – 7 As a result, the homeostasis of DN T cells is critical for lupus pathogenesis. 6 , 8 – 10 Thus, elucidation of the signaling events mediating the homeostasis of DN T cells could provide new potential therapeutic options for SLE. Neddylation is a type of protein post-translational modification (PTM). In this process, neuronal precursor cell-expressed developmentally downregulated protein 8 (NEDD8), an ubiquitin-like protein, binds to substrate proteins to regulate their stability, localization or activity. 11 , 12 Similar to ubiquitination, neddylation is also catalyzed by a three-step enzymatic cascade of NEDD8-activating enzyme E1 (NAE1), NEDD8-conjugating enzyme E2 (Ube2m or Ube2f) and substrate-specific NEDD8-E3 ligases (RBX1/ROC1, RBX2/ROC2, etc.). 13 The Cullin family, indispensable parts of Cullin-RING ubiquitin E3 ligases (CRL), is well-characterized as substrates for NEDD8 modification. Cullin neddylation is essential for the ubiquitin ligase activity of CRLs, which transfer the ubiquitin from recruited E2-ubiquitin to protein substrates and finally promote substrate ubiquitination. 14 , 15 It is well established that neddylation modification is a critical PTM in modulating T cell-mediated immune response. Recently published researches have demonstrated the essential role of neddylation in regulatory T cell fitness, as well as its requirement for CD4 + T cell activation, survival, proliferation and T cell differentiation into various T helper subsets (Th1, Th2), regulatory T (Treg) cells, and T follicular helper (Tfh) cells to effectively regulate immune-related disorders. 16 – 19 Thus, neddylation serves as a critical modulator for T cell functions. However, the precise involvement of neddylation in SLE remains unclear. In our study, we firstly identified that blockade of neddylation pathway with MLN4924, a pharmacological inhibitor of NAE, 20 significantly attenuated SLE progress with reduced DN T cell number in lupus-prone mice. To explore the function of neddylation pathway in SLE, Ube2m, the NEDD8-conjugating enzyme E2, was specifically knockout (KO) to generate spontaneous lupus-prone mice with Ube2m deficiency in T cells ( Ube2m -/- lpr ), where the neddylation was inactivated. Results showed that Ube2m deficiency attenuated SLE development. Subsequent experiments revealed that this effect resulted from the decreased number of DN T cells. Mechanism studies identified that inactivation of neddylation impaired Bim ubiquitination degradation and maintained Bim level in DN T cells, which induced the apoptosis of accumulated DN T cells in lupus mice. To confirm that neddylation pathway regulated the homeostasis of DN T cells via Bim, we generated the double KO lupus-prone mice ( Ube2m -/- Bim -/- lpr ) and found that the deficiency of Bim disrupted the apoptosis of DN T cells for Ube2m deficiency and cannot inhibit the development of lupus. Clinically, we also found that SLE patients exhibited an accumulation of DN T cells with reduced apoptosis. Furthermore, comparing the DN T cells from SLE groups with the healthy control, we discovered that the neddylation level of Cullin1 was enhanced while Bim level was decreased. Further research showed that neddylation inhibition with MLN4924 facilitated Bim-dependent apoptosis in DN T cells isolated from SLE groups. Our results confirmed that neddylation is necessary for the homeostasis of DN T cells. Neddylation inhibition initiates Bim-mediated mitochondrial apoptosis and restores the disordered immune tolerance in SLE. These results highlight the importance of neddylation pathway for SLE and suggest a novel therapeutic intervention of lupus via targeting neddylation pathway in DN T cells.

Materials and methods Mice We purchased MRL/ lpr and the control MRL/Mpj mice (female, 6 weeks) from SLRC laboratory Animal centre. From 12 weeks to 20 weeks, MLN4924 (15 mg/kg) (MCE) or DMSO were intraperitoneally injected into these mice every 3rd day. The mice status and the deaths were observed and recorded daily. The mice were narcotized at 20 weeks in order to obtain serum and blood for flow cytometry. After that, the mice were sacrificed. Kidneys and spleens were obtained. The weight of spleens was evaluated and the total count of splenic cells was determined using the CEDEX XS system (Roche). The Ube2m fl/fl mice were generous gifts from Yi Sun (Zhejiang University) and C57BL/6MRL.Fas lpr mice were generous gifts from Jun Yan (University of Louisville). Lckcre mice and Bim fl/fl mice were bought from Shanghai Model Organisms. Lckcre Ube2m fl/fl mice (termed Ube2m -/- mice) were generated by crossing Lckcre mice with Ube2m fl/fl mice. Then these mice were crossed with C57BL/6MRL. Fas lpr mice to acquire spontaneous lupus-prone mice with Ube2m deficiency (Lckcre Ube2m fl/fl MRL. Fas lpr , termed Ube2m -/- lpr mice) in T cells. Lckcre Ube2m +/+ MRL. Fas lpr or Ube2m fl/fl MRL. Fas lpr mice were as control (termed WT lpr mice). Lckcre Bim fl/fl mice (termed Bim -/- mice) were generated by crossing Lckcre mice with Bim fl/fl mice. Then these mice were crossed with C57BL/6MRL. Fas lpr mice to acquire Lckcre Bim fl/fl MRL. Fas lpr mice, termed Bim -/- lpr . Lckcre Ube2m fl/fl Bim fl/fl MRL. Fas lpr mice, termed Ube2m -/- Bim -/- lpr , were generated by crossing Lckcre Ube2m fl/fl MRL. Fas lpr with Bim fl/fl MRL. Fas lpr mice. Lckcre Ube2m +/+ Bim +/+ MRL. Fas lpr or Ube2m fl/fl Bim fl/fl MRL. Fas lpr mice were as control (collectively called WT lpr mice). Thymus index (thymus weight to mouse weight ratio) and the number of cells in thymus were calculated and T cell subsets in thymus were examined via flow cytometry from 8-week mice. At 8 months, the blood was obtained for flow cytometry and serum was collected. Subsequently, the mice were euthanized, and their kidneys and spleens were obtained for subsequent experimental analysis. For pristane-induced lupus, WT and Ube2m -/- female mice (2 months) were administered with 0.5 ml of pristane or PBS via intraperitoneal injection. At 8 months, serum was collected and the mice were euthanized. Spleens and kidneys were obtained for following experiments. All animal experiments in the study underwent review and were approved by the Institutional Animal Care and Use Committee of Zhejiang Chinese Medical University. Human samples We collected peripheral blood samples with EDTA anticoagulant from normal and active SLE subjects. The patients met the classification criteria of the 2012 Systemic Lupus International Collaborating Clinics (SLICC) and were subjected to full history taking, thorough clinical and laboratory investigations. 55 Then SLE disease activity index (SLE-DAI) was employed to determine the disease activity level. Healthy people were age and gender-matched individuals without underlying medical conditions. The research received approval from the Medical Ethics Committee of Zhejiang Chinese Medical University (2021-KL-1230-1) and consent informed consents have been provided freely by all participants. Detection of autoantibodies The concentrations of total IgG and anti-dsDNA in serum were measured following the guidelines provided by the manufacturer (Multisciences Biotech Co., Ltd). The assessment of renal function Fresh urine samples were manually harvested prior to sacrificing the mice. Then urine protein, albumin and creatinine were determined with corresponding kits following the instructions provided by Dia Sys Diagnostic Systems GmbH. The periodic acid-Schiff (PAS) and hematoxylin eosin (H&E) staining of renal histology as well as the pathological scores were performed according to our previous study. 56 Bio-Plex cytokine assay Serum cytokines including IL-1β, IL-6, IL-10, IL-17, TNF-α and IFN-γ were measured using a Bio-Plex Pro Mouse Cytokine 6-plex panel (Bio-Rad) in accordance with the manufacturer’s protocols. FACS analysis To explore the development of T cells in thymus, single-cell suspensions in thymus were prepared and subsequently stained with the following anti-mouse antibodies: anti-CD4 (PE-CY7), anti-CD8 (BV510), anti-CD25 (APC) and anti-CD44 (AF700). The proportion of T and B cells in mice was determined by staining splenic cells with anti-mouse antibodies: anti-CD3 (PE) and anti-CD19 (PB450) antibodies (Biolegend). To detect the CD3 + T cell subsets, splenic cells were stained with the indicated anti-mouse antibodies: anti-CD3 (PE), anti-CD4 (PE-CY7), anti-CD8 (APC) (Biolegend). To detect T cell percentage in human peripheral blood, anti-human CD3 (FITC), anti-human CD4 (PE-CY7) and anti-human CD8 (BV510) antibodies were used. All these stained cells were evaluated using Beckman CytoFlex S system (Beckman). Purification of DN T cells and T cells DN T cells of spleens from mice were isolated using fluorescent cell sorting via BD FACSAria (BD Biosciences) by staining cells with anti-CD3 (PE), anti-CD4 (PE-CY7), anti-CD8 (APC) antibodies. CD4 + and CD8 + T cells from mice were obtained from spleens with corresponding Mouse T Cell Isolation Kits following the protocols provided by manufacturer (Stem Cell Technologies Inc). DN T cells of human peripheral blood were also isolated using a human DN T cell isolation kit (Miltenyi Biotec). 4D label free quantitative proteomic analysis The 4D label-free quantitative proteomic analysis was conducted by Jingjie PTM BioLabs including protein extraction, trypsin digestion, HPLC fractionation, LC-MS/MS analysis, and bioinformatics analysis according to the method described previously. 57 Apoptosis assay Annexin V/PI and Annexin V/7-AAD Staining Kit (Beyotime) were used to detect cell apoptosis. Splenic cells or peripheral blood in mice were stained with anti-CD3 (APC), anti-CD4 (PE-CY7) and anti-CD8 (BV510) antibodies (Biolegend), as well as Annexin V-PE and 7-AAD. Human peripheral blood was stained with anti-human CD3 (FITC), anti-human CD4 (PE-CY7) and anti-human CD8 (BV510) antibodies as well as Annexin V-PE and 7-AAD. Purified CD3 + T cells obtained from MRL/ lpr mice were incubated with DMSO or MLN4924 (0.1 and 0.5 μM) for 12 h and then stained with the indicated antibodies: anti-CD3 (APC), anti-CD4 (PE-CY7) and anti-CD8 (BV510) (Biolegend). Peripheral Blood Mononuclear Cell (PBMC) isolated from patients were treated with 0.5 μM MLN4924 for 6 h and then stained with anti-human CD3 (APC-CY7), anti-human CD4 (PE-CY7) and anti-human CD8 (BV510) antibodies as well as Annexin V-FITC and PI-PE to detect cell apoptosis. All these cells were analyzed with Beckman CytoFlex S system (Beckman). Proliferation assays in vivo The BeyoClick TM EdU Cell Proliferation Kit with Alexa Fluor 488 (Beyotime) was employed for the detection of DN T cell proliferation. Mice were intraperitoneally administered with EdU (50 mg/kg) twice a day for 1 week according to previously described methods. 58 Then spleen single-cell suspensions were stained with anti-mouse CD3 (APC), anti-mouse CD4 (BV510) and anti-mouse CD19 (PB450) antibodies (Biolegend). At last, the Click-iT reaction was carried out based on the protocols of manufacturer and cells were examined using Beckman CytoFlex S system (Beckman). Mitochondrial membrane potential (MMP) determination The MMP in DN T cells was quantified using the JC-1 assay kit (Beyotime). Following the manufacturer’s recommendations, after surface staining with anti-mouse CD3 (APC-CY7), anti-mouse CD4 (PE-CY7) and anti-mouse CD8 (APC) antibodies, cells were incubated with JC-1 staining buffer at 37 °C for 20 min, and then analyzed by flow cytometry. The ratio of aggregates to monomers represents the change of MMP. Immunoblotting analysis Cells were homogenized in RIPA buffer, containing phosphatase and protease inhibitors (Beyotime). The protein from cell lysate (40 μg) was processed with SDS-PAGE and transferred to nitrocellulose paper. Then the following proteins were detected with appropriate antibodies: Bim (Cell Signaling), Ube2m (Abcam), Ube2f (Proteintech), Cullin1 (Abcam), Caspase 3 (Cell Signaling Technology), Cleaved-caspase 3 (Cell Signaling Technology) and β-actin (Sigma-Aldrich). The band intensity was quantified with Image J software (NIH). Quantitative PCR analysis The mRNA extraction, reverse transcription and real-time quantitative PCR were conducted in accordance with our previous article. 59 The primer sequences were designed as follows: actin, sense 5’- GGCTGTATTCCCCTCCATCG-3’, antisense 5’- CCAGTTGGTAACAATGCCATGT −3’, Ube2m, sense 5’-AACCTGCCCAAGACGTGTG-3’, antisense 5’-AGCTGAATACAAACTTGCCACT-3’, Bim, sense 5’-CCCGGAGATACGGATTGCAC-3’, antisense 5’- GCCTCGCGGTAATCATTTGC −3’. The mRNA levels were determined with△△Ct method. Co-immunoprecipitation (Co-IP) Cells were lysed in NP-40 buffer (Beyotime) supplemented with phosphatase and protease inhibitors, and the lysates were immunoprecipitated at 4 °C overnight with the SureBeads protein A (Bio-Rad) conjugated with the Bim antibody (Cell Signaling). Precipitates were washed three times with lysis buffer. Protein levels were evaluated using immunoblotting analysis with ubiquitin antibody (Thermo). Statistical analysis The data were expressed as the mean ± SEM and analyzed with GraphPad Prism 8 software. Statistical significance was determined by t -test or two-way ANOVA, with P -values < 0.05 considered significant.

Results Inhibition of neddylation attenuated lupus progression in MRL /lpr mice To investigate the function of neddylation during lupus, female MRL/ lpr mice with the Fas gene mutation were used. From about 12 weeks of age, MRL/ lpr mice exhibit the expansion of lymphocytes and spontaneously develop SLE-like symptoms resembling human SLE. 10 We then treated MRL/MpJ and MRL/ lpr group with DMSO or MLN4924 (a specific inhibitor of neddylation) every 3rd day from 12 weeks to 20 weeks of age (Fig. 1a ). Firstly, we found that treatment of MLN4924 remarkably inhibited the neddylation of Cullin1 in splenocytes of MRL/ lpr mice (Fig. 1b ), suggesting that MLN4924 indeed suppressed neddylation pathway in vivo. Notably, MRL/ lpr mice treated with MLN4924 showed significantly higher survival rates than controls (Fig. 1c ). Besides, MLN4924 treatment resulted in a significant reduction in spleen size as evidenced by a decreased spleen index (spleen weight/body weight ratio) (Fig. 1d ) and decreased splenocyte number in MRL/ lpr mice (Fig. 1e ). Additionally, we assessed the levels of serum IgG and anti-dsDNA antibodies, which are important diagnostic markers of lupus. 21 We found that MLN4924 prominently reduced IgG (Fig. 1f ) and anti-dsDNA (Fig. 1g ) antibody levels in MRL/ lpr group (Fig. 1f, g ). To assess the impact of MLN4924 on kidney function, urine samples were obtained and the levels of urinary total protein, albumin and creatinine were quantified. We noticed that MRL/ lpr mice administrated with MLN4924 exhibited a significantly decrease in total protein (Fig. 1h ) and albumin/creatinine ratio (Fig. 1i ). Histological analysis of kidney sections stained with PAS revealed that MLN4924 markedly reduced the crescent glomerulonephritis in MRL/ lpr group (Fig. 1j ), indicating a protective role of MLN4924 in renal function. Serum cytokine levels were evaluated and results indicated that the production of IL-6, IL-17, TNF-α and IFN-γ was inhibited in MRL/ lpr group with MLN4924 administration while IL-1β and IL-10 level remained unchanged (Fig. 1k ). Together, our data suggest that MLN4924 treatment attenuates lupus symptoms as exemplified by increased survival rate, reduced splenomegaly and autoantibody production, ameliorated renal function, and suppressed inflammatory cytokine levels. MLN4924 significantly reduced the number of DN T cells in MRL/ lpr mice As indicated in Fig. 1e , splenic cell accumulation was considerably reduced for MLN4924 treatment. Thus, we investigated the impact of MLN4924 on splenic cells by examining the T and B cell proportions. Flow cytometry analysis revealed a significant decrease of the percentage and total count of T cells in MLN4924-administered MRL/ lpr mice compared to DMSO-treated mice (Fig. 2a–c ) while the proportion and number of B cells remained unchanged (Fig. 2a, d, e ). Further analysis showed a moderate reduction in DN T cell percentage but a significant decrease in DN T cell number for MLN4924 treatment (Fig. 2f–h ), indicating that inhibition of neddylation suppressed the accumulation of DN T cells in MRL/ lpr mice. Deficiency of Ube2m in T cells attenuated SLE development To thoroughly assess the role of neddylation in SLE, Lckcre Ube2m fl/fl MRL. Fas lpr mice (termed Ube2m -/- lpr mice) were generated according to the procedure in Supplementary Fig. 1a . Ube2m -/- lpr mice showed Ube2m-specific deletion in T cells and spontaneously developed lupus. To assess deletion efficiency, Ube2m protein levels were monitored and results showed a clear reduction in purified T cells of Ube2m -/- lpr mice, while Ube2f, another E2 NEDD8 conjugating enzyme, remains unchanged (Supplementary Fig. 1b ), which suggested the specific deletion of Ube2m in Ube2m -/- mice. Both the percentages and numbers of different T cell subsets from thymus of these mice were analyzed and results showed that Ube2m -/- and Ube2m -/- lpr mice exhibited normal T cell development in thymus, including normal DN T cells, DP cells, CD4 + and CD8 + T cells (Supplementary Fig. 2a–e ). Based on the presence of the specific surface markers, CD25 and CD44, the DN stages have been classified as DN1, DN2, DN3 and DN4. 22 Therefore, we further characterized DN populations according to the expression of CD25 and CD44 to explore whether Ube2m deficiency in T cells affects the development of DN T cells. As shown in Supplementary Fig. 2c, f, g , T cells lacking Ube2m exhibited unchanged DN T cells. The normal development of T cells in thymus of Ube2m KO mice allowed further investigation of the effects of Ube2m deficiency on the pathogenesis of lupus. As shown in Fig. 3a–c , Ube2m -/- lpr mice showed dramatically reduced splenomegaly (Fig. 3a, b ) and decreased number of splenocytes (Fig. 3c ) compared with WT lpr at 8 months. Moreover, the serum IgG and anti-dsDNA antibody production was notably abated (Fig. 3d, e ). Furthermore, we also found that deficiency of Ube2m ameliorated lupus nephritis, including lessened total protein (Fig. 3f ) and albumin/ creatinine ratio (Fig. 3g ), restored renal structures (Fig. 3h, i ). In addition, Ube2m -/- lpr mice showed markedly reduced levels of inflammatory cytokines (Fig. 3j ). Collectively, these results clearly showed that neddylation inactivation in T cells significantly attenuated lupus progression. Loss of Ube2m promoted DN T cell apoptosis In vivo evidence establishing the crucial role of Ube2m in lupus development, we further explored how Ube2m regulated lupus progress. Firstly, we measured the number and proportion of T cells in spleen and results revealed that loss of Ube2m prominently blocked total T cell accumulation both in spleen (Fig. 4a–c ) and peripheral blood (Supplementary Fig. 3a, b ). Further research showed that DN T cell accumulation in spleen (Fig. 4d–f ) and peripheral blood (Supplementary Fig. 3c, d ) were significantly inhibited in Ube2m -/- lpr . Our previous results (Supplementary Fig. 2c–g ) have demonstrated that the development of DN T cells in thymus is not affected by Ube2m KO. Therefore, we then detected the influence of Ube2m on DN T cells in spleens. In view of the deficit of Fas-triggered apoptosis in lpr mice, 23 we firstly measured the level of T cell apoptosis in spleens. Consistent with our above-mentioned phenotype, the apoptosis of DN T cells was blocked in WT lpr mice compared to WT mice, while disruption of Ube2m restored the normal apoptosis of T cells, especially DN T cells (Fig. 4g–i ). Similar results were found in peripheral blood (Supplementary Fig. 4a–c ). Consistently, we also observed that loss of Ube2m significantly promoted DN T cell apoptosis (Fig. 4j, k ) and attenuated disease progression (Supplementary Fig. 5 ) in pristane-induced lupus mice. Then, JC-1 staining assay indicated that Ube2m-deleted DN T cells exhibited reduced MMP, as evaluated by the ratio of JC-1 aggregates to monomer (Fig. 4l ), which indicated increased apoptosis. Consistently, we also found that Ube2m deficiency resulted in an elevated cleaved-caspase 3 level (Fig. 4m ) in DN T cells, which is required for cell apoptosis. Besides, the excessive T cell proliferation is another striking abnormality of lpr mice 24 and our results showed that Ube2m deficiency inhibited total T cell proliferation in vivo (Supplementary Fig. 6a, b ). Notably, loss of Ube2m mainly restrained proliferation of CD4 + and CD8 + T cells while having minimal effect on DN T cell proliferation (Supplementary Fig. 6a, c ), which suggested differential functions of Ube2m in different T cell subsets. These findings demonstrated the essential role of Ube2m in the survival of DN T cells, and deletion of Ube2m facilitated DN T cell apoptosis in lupus mice. Neddylation inactivation upregulated Bim level by inhibiting Bim ubiquitination degradation We have shown that loss of Ube2m promoted DN T cell apoptosis and contributed to alleviated lupus development (Figs. 3 and 4 ), while the mechanism remained unknown. Therefore, DN T cells were sorted and an unbiased quantitative proteomic analysis was conducted to screen for the differential protein between WT lpr and Ube2m -/- lpr mice. Results indicated that the protein Bim (encoded by the Bcl2l11 gene) showed the most significant increase among the apoptosis-related proteins for Ube2m deficiency (Fig. 5a ). Next, the mRNA level of Bim was measured and results indicated that the transcriptional expression of Bim remained unchanged for loss of Ube2m (Fig. 5b, c ). Based on our data, we speculated that neddylation pathway regulated Bim degradation. Consequently, MG-132, a proteasome inhibitor, was used to treat DN T cells. Results indicated that Bim was accumulated upon MG-132 treatment (Fig. 5d ), suggesting that Bim degradation was proteasome-dependent. Previous studies have proven that Bim ubiquitination degradation is dependent on the neddylation of Cullin1. 25 , 26 As a result, the neddylation of Cullin1 was detected and results showed that Cullin1 neddylation was at a lower level in normal mice and remained little change for Ube2m deficiency, resulting in unchanged Bim protein level in DN T cells under normal physiological condition (Fig. 5e ). However, we found that Ube2m expression and the neddylation of Cullin1 was significantly increased in lupus conditions (Fig. 5e ), suggesting that the neddylation pathway activation was necessary for DN T cell abnormal survival in lupus progression. Then, loss of Ube2m prominently blocked the neddylation of Cullin1, contributing to the Bim protein accumulation (Fig. 5e ) and finally promoting DN T cell apoptosis in lupus mice (Fig. 4g, i ). Furthermore, Co-IP assay revealed that the ubiquitination degradation of Bim was indeed remarkably inhibited for Ube2m deletion in DN T cells (Fig. 5f ). In vitro results also showed that neddylation inactivation with MLN4924 promoted DN T cell apoptosis (Fig. 5g, h ), with elevated Bim and cleaved-caspase 3 protein levels (Fig. 5i ). Further Co-IP assay also indicated that MLN4924 treatment disrupted Bim ubiquitination degradation, contributing to the accumulation of Bim (Fig. 5j ). Taken together, we demonstrated that neddylation inactivation impairs Bim ubiquitination degradation and maintains Bim level, ultimately promoting the apoptosis of DN T cells in lupus mice. Loss of Bim reduced Ube2m deficiency-induced apoptosis in DN T cells and reversed the alleviated lupus progression According to our obtained findings, we hypothesized that Bim is a pivotal protein downstream mediated by neddylation pathway, responsible for DN T cell homeostasis. To further test our hypothesis, Lckcre Bim fl/fl MRL. Fas lpr (termed Bim -/- lpr ) and Lckcre Ube2m fl/fl Bim fl/fl MRL. Fas lpr (termed Ube2m -/- Bim -/- lpr ) mice were generated. Firstly, we found that deletion of Bim in T cells led to an increase both in splenic and T cell numbers (Fig. 6a, b ). Further analysis revealed that there was a dramatic increase in the proportion and number of DN T cells (Fig. 6c–e ) due to reduced apoptosis (Fig. 6f–h ) in Bim -/- lpr compared with WT lpr mice, suggesting a significant function of Bim in DN T cell homeostasis. Then, we also found that lack of Bim blocked the increased apoptosis of DN T cells resulted from Ube2m deficiency (Fig. 6f, h ), contributing to more DN T cells in Ube2m -/- Bim -/- lpr mice compared with Ube2m -/- lpr mice (Fig. 6c–e ). Moreover, when Bim is lost, the lack of Ube2m has little effects on the apoptosis and number of DN T cells (Fig. 6c–h ). Thus, Bim served as a key downstream protein of neddylation pathway to regulate DN T cell apoptosis. In addition, Ube2m -/- Bim -/- lpr mice showed reduced T cell (Fig. 6b ) and CD4 + T cell number (Fig. 6e ) with unchanged T cell and CD4 + T cell apoptosis compared with Bim -/- lpr mice (Fig. 6f–h ), which suggested that there are some Bim-independent mechanisms to regulate CD4 + T cell homeostasis. Considering the important function of DN T cells in lupus progress, lupus syndrome of these mice was also detected in Supplementary Fig. 7 . Consistently, Bim -/- lpr mice exhibited the most severe lupus syndrome, including splenomegaly (Supplementary Fig. 7a ), the accumulation of autoantibodies (Supplementary Fig. 7b, c ), renal destruction (Supplementary Fig. 7d–g ) as well as increased inflammatory cytokine level (Supplementary Fig. 7 h). Meanwhile, compared with Bim -/- lpr mice, Ube2m -/- Bim -/- lpr mice also showed slightly remission on lupus development (Supplementary Fig. 7 ), indicating a Bim-independent manner of Ube2m on lupus development. In addition, we also found that the attenuated lupus phenotypes in Ube2m KO mice were mainly reversed in Ube2m -/- Bim -/- lpr mice (Supplementary Fig. 7 ). Collectively, these evidences clearly identified that Bim is an indispensable downstream protein governed by neddylation pathway to regulate DN T cell apoptosis, which mediates the development of lupus. Inhibition of neddylation pathway promoted Bim-dependent DN T cell apoptosis in SLE patients We have verified that neddylation inactivation induced Bim-dependent DN T cell apoptosis in lupus-prone mice. However, the impact of neddylation inactivation on DN T cells derived from SLE patients remains unknown. Peripheral blood samples were collected from both healthy individuals and patients with active SLE. Firstly, we observed that patients with SLE showed a higher percentage of total DN T cells with lower apoptosis in comparison to the healthy group (Fig. 7a–c ). The subsequent correlation analysis revealed a positive association between the percentage of DN T cells and SLE-DAI scores (Fig. 7d ), then a negative association between the apoptosis proportion of DN T cells and SLE-DAI scores (Fig. 7e ). Further exploration showed that Bim protein level was reduced, while the neddylation of Cullin1 was increased in DN T cells of SLE group (Fig. 7f ). On this basis, MLN4924 was used to treat the PBMC isolated from SLE patients and results revealed that neddylation inhibition declined the DN T cell percentage (Fig. 7g, h ) and promoted the apoptosis of DN T cells (Fig. 7i, j ). Consistently, we found the Bim level was upregulated (Fig. 7k ) upon neddylation inhibition. These clinical data identified that neddylation inactivation promotes the Bim-dependent DN T cell apoptosis, thus contributing to the reduction of DN T cells. Our data suggested that inhibition of neddylation pathway is a promising therapeutic option for SLE. In conclusion, our research uncovers the role of neddylation pathway in DN T cell homeostasis (Fig. 8 ), thereby providing a novel treatment approach for SLE.

Discussion SLE is an autoimmune disorder and the underlying causes remains mostly unknown. The abnormal accumulation of DN T cells, which led to the peripheral tolerance defects and systemic damage, is a key pathogenesis of SLE. 4 , 27 Thus, it is necessary to elucidate the mechanisms controlling the homeostasis of DN T cells during SLE. Here, we functionally characterized the unique role of neddylation in DN T cell homeostasis with a specific inhibitor of neddylation and a genetic approach. Neddylation inactivation promoted the apoptosis of DN T cells via stabilizing the Bim level and contributed to SLE remission. These findings underscore the crucial role of neddylation in DN T cell functions and indicate neddylation as a potential target for SLE therapy. Neddylation, a post-translational modification, attaches NEDD8 to substrate proteins to affect their localization, stability or activity. CRLs can be activated by neddylation, which facilitate the ubiquitylation and degradation of substrates and then mediate lots of cellular processed including cell cycle progression, cell apoptosis and cell survival. 28 – 30 In addition, ongoing investigations implicate neddylation is necessary for the regulation of immune cell functions and involved in the pathogenesis of related immune disorders. 31 For example, neddylation plays a pivotal role in pro-inflammatory cytokine production in innate immune cells, including macrophages, neutrophils and dendritic cells (DCs). 32 – 34 Neddylation is also required for the IFN production against RNA viral infection in myeloid DCs. 35 Additionally, neddylation has been proven as an indispensable process for the activation, proliferation and polarization of CD4 + T cells to regulate T cell-mediated immunity response. 16 , 19 , 36 – 38 However, the role of neddylation in DN T cells remains to be explored. The homeostasis of DN T cells was involved in the development of SLE. 4 , 10 DN T cell apoptosis and timely clearance are critical for immune tolerance, which avoided the release of autoantigen and the induction of autoimmunity. Once the apoptosis of DN T cell was disturbed, excessive accumulation of DN T cells will initiate autoimmune response. 4 , 39 – 41 Therefore, the normal apoptosis and clearance of DN T cells are beneficial for lupus remission. Bim, belonging to the Bcl-2 family, is a crucial BH3 protein promoting cell intrinsic apoptosis. 42 In mammalian, two main pathways govern the initiation of apoptosis. One is the extrinsic pathway (or death receptor pathway), triggered by ligand engagement of cell surface death receptors such as Fas. Another is intrinsic apoptotic pathway, which is mediated by Bcl-2 protein family. 43 Fas-dependent death receptor pathway and Bim-mediated intrinsic apoptosis have been proven to suppress chronic immune responses and prevent autoimmunity. 44 – 46 Loss of either Fas or Bim resulted in marked lymphadenopathy and splenomegaly, and deficiency of Bim in MRL /lpr mice developed more extreme lymphadenopathy, indicating that Fas signaling and Bim showed overlapping but non-redundant roles in lymphadenopathy and splenomegaly. 47 , 48 However, the precise role of Bim in DN T cells and the underlying regulatory mechanism governing Bim homeostasis remained elusive. In our study, we found that neddylation inactivation observably reduced DN T cell accumulation in lupus mice with upregulated Bim protein level and normal transcription of Bim. MG-132 treatment suggested that Bim degradation was mediated by ubiquitin-proteasome system. Previous studies have proven that Bim protein was the substrates of CRL1 and neddylation inhibition increased Bim protein level to promote the apoptosis of B cells. 25 , 26 , 49 Therefore, we also detected the Bim ubiquitination degradation and found that the Bim degradation was significantly inhibited accompanied with impaired Cullin1 neddylation in DN T cells when neddylation was inactivated. However, Bim accumulation and Cullin1 neddylation inhibition of DN T cells were only found in lupus mice rather than in non-lupus group. Our data indicated that Ube2m specifically regulates Bim in SLE group. In normal physiological condition, the remaining low level of Ube2m after Cre driven deletion appears to be sufficient to maintain the basal level of Cullin1 neddylation. However, under lupus conditions, Ube2m was significantly induced to ensure sufficient Cullin1 neddylation to activate CRL1, which is consistent with the previous work showing that Ube2m is a stress inducible protein. 50 And Ube2m deletion failed to provide enough Cullin1 neddylation, leading to CRL1 inactivation and subsequent Bim accumulation to induce apoptosis in lupus groups. To further verify the involvement of Bim in neddylation-mediated DN T cell apoptosis, Ube2m -/- Bim -/- lpr mice were generated and results showed that when Bim was deleted, neddylation inactivation failed to promote DN T cell apoptosis, suggesting that neddylation pathway mediated DN T cell apoptosis via regulating Bim protein degradation. In our research, we also found that neddylation function has heterogeneity in different T cell subsets. Our data revealed that neddylation inactivation also blocked Bim ubiquitination and increased Bim protein level in CD4 + and CD8 + T cells similar with DN T cells (Supplementary Fig. 8 a–d). However, the susceptibility of DN T cells to Bim-induced apoptosis was found to be the highest (Fig. 4g–i , Fig. 5g, h and Supplementary Fig. 8 e–h). It has been well demonstrated that cellular metabolism can influence cell sensitivity to apoptosis. 51 , 52 We hypothesized that the heterogeneity of neddylation functions in different T cells depended on their distinct metabolic profiles. More research is necessary to comprehensively elucidate the metabolic modes of different T cells as well as the relationship between apoptosis and metabolic modes during lupus. Besides, we found that neddylation inactivation notably suppressed the proliferation of CD4 + T cells and blocked the differentiation of T follicular helper (Tfh) cells in MRL/ lpr mice and pristane-induced lupus models (data not shown). CD4 + T cells, such as Th1, Tfh and Th17 cells also contribute to tissue inflammation and autoantibody production, promoting the pathogenesis of SLE. 2 , 53 , 54 These changes also explained why Ube2m -/- Bim -/- lpr mice exhibited slightly reduced T cell number and attenuated lupus symptoms compared with Bim -/- lpr mice. However, the mechanism of neddylation pathway in regulating the function of CD4 + T cells during SLE progression requires further investigation. In summary, we have identified a significant role of neddylation in maintaining DN T cell homeostasis and mediating SLE progression. Suppression of neddylation with MLN4924 or genetic abrogation of Ube2m significantly ameliorated the progression of SLE via reconstructing the normal apoptosis of DN T cells. Further experiments indicated that the interception of apoptosis in lupus mice was indeed recovered for neddylation inactivation, which resulted from the inhibition of Bim ubiquitination and the rise of Bim-mediated apoptosis. The clinical data also showed that SLE patients displayed accumulated DN T cells with defects in apoptosis while neddylation inhibition promoted the apoptosis of DN T cells via up-regulating Bim protein level. The findings enhance our comprehension about the pathogenesis of SLE and suggest that neddylation pathway might be a promising target for SLE therapy.

Systemic lupus erythematosus (SLE), a severe autoimmune disorder, is characterized by systemic inflammatory response, autoantibody accumulation and damage to organs. The dysregulation of double-negative (DN) T cells is considered as a crucial commander during SLE. Neddylation, a significant type of protein post-translational modification (PTM), has been well-proved to regulate T cell-mediated immune response. However, the function of neddylation in SLE is still unknown. Here, we reported that neddylation inactivation with MLN4924, a specific inhibitor of NEDD8-activating enzyme E1 (NAE1), or genetic abrogation of Ube2m in T cells decreased DN T cell accumulation and attenuated murine lupus development. Further investigations revealed that inactivation of neddylation blocked Bim ubiquitination degradation and maintained Bim level in DN T cells, contributing to the apoptosis of the accumulated DN T cells in lupus mice. Then double knockout (KO) lupus-prone mice ( Ube2m -/- Bim -/- lpr ) were generated and results showed that loss of Bim reduced Ube2m deficiency-induced apoptosis in DN T cells and reversed the alleviated lupus progression. Our findings identified that neddylation inactivation promoted Bim-mediated DN T cell apoptosis and attenuated lupus progression. Clinically, we also found that in SLE patients, the proportion of DN T cells was raised and their apoptosis was reduced. Moreover, compared to healthy groups, SLE patients exhibited decreased Bim levels and elevated Cullin1 neddylation levels. Meantime, the inhibition of neddylation induced Bim-dependent apoptosis of DN T cells isolated from SLE patients. Altogether, our findings provide the direct evidence about the function of neddylation during lupus, suggesting a promising therapeutic approach for this disease. Subject terms

Supplementary information

Supplementary information The online version contains supplementary material available at 10.1038/s41392-023-01709-9. Acknowledgements The authors thank Professor Jun Yan from University of Louisville for providing C57BL/6 MRL.Fas lpr mice. We express our gratitude for the exceptional technical support provided by the Public Platform of Medical Research Center of Zhejiang Chinese Medical University. We also thank Figdraw ( www.figdraw.com ) for expert assistance to create a graphical abstract. This work was supported by Regional Innovation and Development Joint Fund of the National Foundation of China (U21A20402) to C.W., National Natural Science Foundation of China (No. 82074375) and the Research Project of Zhejiang Chinese Medical University (No. 2023JKZDZC01) to Y.Z., Chongqing International Institute for Immunology (2020YJC10) to L.L., National Natural Science Foundation of China (No. 82074217) to Z.H. Author contributions Y.Z., L.L. and C.W. designed research and guarantee the overall content; L.D., C.W. (Chenxi Wang) and Z.J. performed the experiments; Q.D., Y.L. and Z.H. performed analysis; L.H. and Z.X. collected the clinical samples; Y.Z. and L.H. wrote the manuscript, Y.S., L.L. and C.W. edited the manuscript. All authors have read and approved the article. Data availability The paper and Supplementary Materials contain all the necessary data for evaluating the conclusions. The proteomic data has been submitted to the ProteomeXchange Consortium via the PRIDE (Project accession: PXD045686). Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Signal Transduct Target Ther. 2024 Jan 15; 9:18

oa_package/f4/d1/PMC10788348.tar.gz

PMC10788349

38221520

Introduction Cancer, a significant class of diseases, ranks among the leading causes of human mortality. This malignant disease now stands as the primary cause of death, second only to cardiovascular and cerebrovascular diseases [ 1 ]. In addition to traditional treatment methods such as surgery, chemotherapy, and radiotherapy [ 2 ], current cancer therapies have rapidly evolved, including targeted therapy and immunotherapy [ 3 ]. Targeted therapy is based on the advancements of cellular and molecular biology, and it seeks to inhibit cancer cells by identifying specific target molecules expressed by these cells. While notable progress has been made in enhancing therapeutic effects and reducing side effects, challenges such as drug resistance and off-target effects continue to persist in targeted therapies. On the other hand, immunotherapy has rapidly developed in recent years. It is primarily divided into two categories: immune checkpoint blockade therapy [ 4 ] and immune cell therapy [ 5 ]. These approaches have yielded promising clinical recoveries for certain patients, indicating a bright future for cancer treatment. Natural killer (NK) cells, as a vital type of immune cell, possess dual functions involving cytotoxicity and immune regulation [ 6 ]. These cells originate from hematopoietic stem cells (HSCs) in the bone marrow and acquire the ability to differentiate between “friend” and “foe” through self-major histocompatibility complex (MHC) I molecule recognition [ 7 ]. NK cells exert broad-spectrum anticancer effects without the need for specificity and MHC restriction typically observed in cancer cell inhibition. They act as the “first responders” in the battle of the immune system against cancer development and viral infections. NK cells can spontaneously identify aberrant cells in the body, swiftly eliminating them via cytotoxic means while simultaneously generating various pro-inflammatory cytokines and chemokines. Furthermore, they have the capacity to activate other immune cells, initiating the adaptive immune response [ 8 ]. NK cells were initially discovered in the 1970s and primarily play a role in combating infected microorganisms and malignantly transformed allogeneic and autologous cells. As a distinct population of innate lymphocytes, NK cells inherently possess the ability to recognize and eliminate virus-infected and cancer cells. This recognition and elimination capacity rendered NK cells safe and effective as immunotherapeutic agents for patients with advanced leukemia nearly two decades ago [ 9 ]. In recent years, NK cells have received increasing attention as potential candidates for immunotherapy. With the rapid development of immunotherapy, especially in the realm of cell therapy, research on NK cells has become increasingly intensive due to their pivotal role in disease treatment. In this paper, we aim to elucidate the biological background, cell sources, and the use of NK cells in disease therapy. We have also discussed the principal advantages and disadvantages of engineered NK cells, offering valuable insights into future avenues for NK cell therapy research.

Immunotherapy has rapidly evolved in the past decades in the battle against cancer. Chimeric antigen receptor (CAR)-engineered T cells have demonstrated significant success in certain hematologic malignancies, although they still face certain limitations, including high costs and toxic effects. Natural killer cells (NK cells), as a vital component of the immune system, serve as the “first responders” in the context of cancer development. In this literature review, we provide an updated understanding of NK cell development, functions, and their applications in disease therapy. Furthermore, we explore the rationale for utilizing engineered NK cell therapies, such as CAR-NK cells, and discuss the differences between CAR-T and CAR-NK cells. We also provide insights into the key elements and strategies involved in CAR design for engineered NK cells. In addition, we highlight the challenges currently encountered and discuss the future directions in NK cell research and utilization, including pre-clinical investigations and ongoing clinical trials. Based on the outstanding antitumor potential of NK cells, it is highly likely that they will lead to groundbreaking advancements in cancer treatment in the future. Subject terms

Facts As a crucial immune cell type, natural killer (NK) cells function as the “first responders” in the context of cancer development. With the rapid advancement of immunotherapy, particularly in cell therapy, research on NK cells has intensified due to their pivotal role in disease treatment. An increasing number of NK cell-based therapeutics are under development, holding substantial promise for future breakthroughs in cancer treatment. Discussing the biological background, cell sources, and the use of NK cells in disease therapy, as well as the primary advantages and disadvantages of engineered NK cells (e.g., chimeric antigen receptor [CAR]-NK cells), is a valuable avenue for future research in cell therapy. Open questions What is the current understanding of NK cell development, function, and their application in disease therapy? How do NK cells exert their anticancer effects, and what are the associated mechanisms? What is the rationale behind CAR cell therapy, and how do CAR-T and CAR-NK cells differ? What elements and strategies are relevant in the CAR design for engineered NK cells? What are the existing challenges and development directions for this novel technology of CAR-NK cells? Furthermore, what is the current status of CAR cell therapy from laboratory research to clinical application (bench to bedside)? NK cell biology NK cell origination, development and classification Peripheral blood mononuclear cells (PBMCs) stem from HSCs in the bone marrow, responsible for generating all the blood cells in the immune system through hematopoiesis [ 10 ]. HSCs possess the capacity to differentiate into two primary lineages: myeloid (including monocytes, macrophages, granulocytes, megakaryocytes, dendritic cells, and erythrocytes) and lymphoid (involving T cells, B cells, and NK cells). In healthy human bodies, approximately 70–90% of PBMCs are lymphocytes, and the majority of T cells remain in a naive state (mature but not stimulated by antigens). Only a small fraction of T cells become activated upon antigen recognition, initiating a cell-mediated immune response. Similarly, in normal human bodies, B cells predominantly exist in a naive or memory state, awaiting antigen stimulation and constituting approximately 5–15% of lymphocytes. Upon activation, B cells differentiate into plasma cells, which release substantial quantities of antibodies, triggering a humoral immune response. NK cells account for approximately 5–10% of the lymphocyte population and play a crucial role in the body’s innate immunity [ 11 ]. The development of NK cells primarily occurs from common lymphoid progenitors (CLPs) in the bone marrow, progressing through distinct stages, mainly including NK precursors (NKP), immature NK cells, and mature NK cells as illustrated in Fig. 1 . In the course of normal hematopoiesis, one of the earliest markers of NK cells is IL2RB (CD122), which is expressed when CD34 + CLPs enter the NK cell fate lineage. Recent research has revealed the complexity of NK cell development. A “branched” model associated with NK cell development has been described, and the investigation into NK cell trafficking, tissue residence, and tissue-specific specialization is ongoing [ 12 – 16 ]. Subpopulations of NK cell precursors can be differentiated by their varied gene expression, including markers such as CD34, KIT, KLRB1, CD244, and IL-15R [ 17 ]. To identify immature NK cells, molecular markers like CD244, natural toxicity receptor (NCR)1, NCR2, NCR3, and KLRB1 have been reported. Subsequent differentiation to the mature stage is characterized by the expression of markers such as KLRD1, ITGB2, killer Ig-like receptors (KIRs), PRF1, IFNG, CD56, and CD16 [ 18 ]. The CD56 bright subset is often considered an early stage of NK cell maturation [ 19 ]. Notably, CD56 bright cells exhibit a higher proliferative capacity than CD56 dim cells, likely due to their prominent expression of several key proteins, including CCR7, CSF2, CXCR3, IL2RB, KLRC1, and SELL [ 20 ]. This subpopulation is known for its elevated IFNG expression. Downregulation of CD56 is followed by CD16 expression, resulting in the CD56 dim NK cell subset [ 21 ]. This subgroup is distinguished by its potent cytotoxic activity [ 22 , 23 ], with KIRs being among the genes associated with this subgroup [ 24 ]. Additional genes linked to the CD56 dim subset include CX3CR1 [ 25 ], KLGR1 [ 26 ], and PRF1 [ 12 ]. While the CD56 bright cells make up a smaller portion, estimated at only 5–10% of the total NK cell population in peripheral blood (PB), the CD56 dim NK cells constitute over 90%. However, CD56 bright cells are more prevalent in specific tissues, including secondary lymphoid tissues [ 11 , 21 ]. Recent findings have suggested that NK cell development can also take place in secondary lymphoid tissues such as lymph nodes and the spleen [ 27 ]. During this developmental phase, NK cells are trained to recognize MHC-I, thereby avoiding the targeting of healthy, normal cells. NK cell membrane protein characteristics and biology functions NK cells eliminate infected and cancerous cells upon activation of activating receptors, such as the NCRs, which include NKp30, NKp44, and NKp46 [ 28 – 30 ]. As mentioned earlier, CD56 dim NK cells primarily display robust cytotoxic activity, whereas CD56 bright NK cells primarily secrete cytokines and exhibit lower cytotoxic activity. The regulation of NK cell cytotoxicity involves a complex interplay of activation and inhibition signals. The killing efficiency of NK cells on target cells relies on the delicate balance between inhibitory and activation signals, closely tied to cell membrane receptors and proteins (Fig. 2 ). Activated NK cells employ various mechanisms for target cell elimination (Fig. 3 ), including 1 release of perforin and granzyme, leading to target cell lysis or apoptosis; 2 promotion of FasL expression, inducing cell apoptosis; 3 release of tumor necrosis factor (TNF)-α, interferon (IFN)-γ, granulocyte macrophage colony-stimulating factor (GM-CSF), and chemokines (such as CCL1, CCL2, CCL3, CCL4, CCL5, and CXCL8) to recruit and activate other effector immune cells; 4 antibody-dependent cell-mediated cytotoxicity (ADCC). NK cells express various membrane proteins, as depicted in Fig. 2 , to modulate inhibitory and activation signals [ 16 ]; however, they lack T-cell receptors (TCRs) and B-cell receptors, among which CD56 [ 31 ] (an adhesion molecule mediating homotypic adhesion) and CD16 [ 32 ] (a low-affinity Fc receptor FcγRIII, contributing to NK cell-mediated ADCC) serve as primary surface markers. Unlike T cells, NK cells do not express antigen-specific recognition receptors. The surface receptors of NK cells are broadly categorized into activating and inhibitory receptors, both capable of recognizing classical or non-classical human MHC-class I molecules on normal cells. The interaction between MHC-I molecules and inhibitory receptors signals convey a “Do not eat me” message to NK cells, enabling cell evasion from NK cell-mediated killing [ 33 ]. NK cell engineering Numerous studies suggest the presence of potential neoantigens, such as HSP70, expressed exclusively on tumor cells and absent in normal cells, can activate NK cells. This discovery opens a promising avenue in target-driven cell-based immunotherapies, as the HSP70 protein becomes a viable target for NK cells [ 34 – 36 ]. Currently, several approaches exist in NK cell engineering (Fig. 4 ). A prominent method involves chimeric antigen receptors (CARs), receptor proteins that confer immune cells with the ability to target specific antigenic proteins. CAR-T cell therapy has achieved significant success in hematological malignancies, including acute lymphoblastic leukemia [ 37 , 38 ] and diffuse large B-cell lymphoma [ 39 ]. Various CAR-T therapies have gained approval [ 40 – 42 ]. While CAR-T cell therapy stands as a groundbreaking biotechnological advancement in cancer treatment, it faces challenges such as side effects, toxicity [ 43 ], T cell exhaustion [ 44 ], and limited efficacy against solid tumors [ 45 ]. Presently, new cell therapies such as CAR-NK, CAR-NKT, CAR-macrophage (CAR-M), CAR-Treg, CAR-γδT, with CAR technology at their core, have emerged, especially CAR-NK showing promising prospects in tumor immunotherapy [ 46 ]. NK cell sources There are four primary sources of NK cells in NK cell engineering (e.g., CAR-NK), depicted in Fig. 5 : Peripheral blood (PB), induced pluripotent stem cells (iPSCs), mesenchymal stem cells (e.g., umbilical cord blood), and NK cell lines (such as NK-92, etc.). As previously mentioned, NK cells, as a subset of lymphocytes, possess the ability to recognize and eliminate tumor cells without prior sensitization, antibody involvement, and are not restricted by MHC. Commonly utilized markers for NK cells in experiments include CD16 and CD56. The characteristics and limitations of NK cells from different sources in clinical treatment are detailed below. Peripheral blood (PB-NK) NK cells derived from the patient’s own body or a healthy donor. Due to disease and treatment limitations, the function of the patient’s own NK cells may be compromised. Allogeneic NK cells are clinically favored [ 47 ], but careful T cell removal is essential to mitigate graft-versus-host disease (GVHD) [ 48 ]. PB-NK cells are mature and do not necessitate induction of differentiation, but gene transduction efficiency is relatively low. Prolonged in vitro expansion may result in shortened telomeres and reduced cytotoxicity. Cryopreservation diminishes the viability and toxicity of PB-NK cells. NK cell therapy typically involves reinfusion of 10 6 –10 8 cells per kilogram of body weight [ 49 , 50 ], yet the proportion of NK cells in PB is low [ 51 ], posing challenges for large-scale in vitro culture. However, there are advantages; for instance, these cells are mature and bypass the need for an extended differentiation period. Umbilical cord blood (UCB-NK) These cells exhibit high proliferation efficiency, allowing real-time selection of human leukocyte antigen (HLA)-mismatched products by establishing an NK cell bank [ 52 ]. Cord blood serves as a promising source for NK cells in clinical applications, with two main strategies: direct use of NK cells in cord blood or differentiation of HSCs in cord blood into NK cells. It is crucial to note that mesenchymal cells in cord blood are not utilized for these purposes. Cord blood remains a relatively stable source of NK cells. Due to their high proliferative capacity, only 10% of a cord blood unit is required to generate a nearly pure cell pool of over 10 9 NK cells within 2 weeks, typically suitable for one treatment cycle [ 53 , 54 ]. However, UCB-NK cells are not fully differentiated, exhibiting relatively low expression of NK receptors and limited cell inhibition ability, with a potential risk of tumorigenesis in allogeneic transplantation [ 55 ]. Nevertheless, they demonstrate a robust bone marrow homing ability [ 56 ]. Moreover, the higher proportion of hemoglobin and red blood cells in cord blood can impact the isolation and culture of PBMCs. Stem cell-derived NK cells NK cells are commonly induced from human embryonic stem cells (hESCs), HSCs or iPSCs [ 57 ], with an expansion period extending beyond 3–5 weeks. This extended period helps mitigate the heterogeneity of NK cells between the recipient and the donor. However, NK cells induced by iPSCs present potential risks of malignant transformation and tumorigenesis in vivo, along with the possibility of triggering unexpected immune responses due to their potential immunogenicity. iPSCs efficiently clone, expand, and differentiate in vitro, producing a substantial quantity of uniform NK cell products [ 58 ]. Nevertheless, iPSC-derived NK cells often express low levels of endogenous CD16, a drawback that can be addressed through genetic engineering [ 59 , 60 ]. Moreover, iPSCs may retain DNA methylation signatures consistent with their somatic tissue origin, contributing to “epigenetic memory,” which could influence the development of specific cell lineages distinct from the donor cells. Systemic administration of cytokines in a clinical setting is highly undesirable due to its expense and potential dangers. Additionally, iPSC-derived cells carry the risk of malignant transformation and potential immunogenicity, leading to the destruction of ES cells and even adverse immune responses such as cytokine release storms [ 61 ]. NK cell line Various NK cell lines, including NK-92, HANK-1, KHYG-1, NK-YS, NKG, NK101, NK3.3, YTS, and NKL, have been constructed to date, serving as excellent cell models for studying NK cell biology and associated applications. Among these, the NK-92 cell line is the only one applied in clinical trials, demonstrating a relatively satisfactory response outcome with controllable adverse effects. NK-92 cells lack the CD16 receptor-mediated ADCC effect, but this can be addressed through modification [ 62 ]. These cells are easily genetically manipulated, allowing effective introduction of exogenous genes through electroporation without the need for viral vectors [ 63 ]. Because NK-92 is a tumor-derived aneuploid immortalized cell line [ 64 ], it requires irradiation before use to inhibit in vivo proliferation [ 65 ], negatively impacting long-term persistence and overall therapeutic potential. CAR-NK cells CAR-NK cells typically share the similar CAR structures as CAR-T cells. NK cells enhance their cytotoxic capacity and cytokine production through co-stimulatory molecules like NKG2D and CD244, providing probably stronger tumor-specific targeting and cytotoxicity than CAR-T cells [ 66 ]. CAR-NK cell therapy is a potential alternative to CAR-T therapy due to several unique features. Firstly, allogeneic NK cells are generally safe for adoptive cell therapy (ACT) as they do not typically mediate GVHD [ 66 ]. Moreover, NK cells only secrete small amounts of IFN-γ and GM-CSF [ 67 ], without producing IL-1 and IL-6 that initiate cytokine release syndrome (CRS) [ 68 ]. Secondly, in addition to inhibiting cancer cells through single-chain antibody recognition of tumor surface antigens, NK cells can also recognize various ligands through multiple receptors such as NCRs (NKp46, NKp44, and NKp30), NKG2D, and DNAM-1 (CD226) [ 69 – 71 ]. Lastly, NK cells are abundant in clinical samples [ 13 ] and can be generated from various sources, including PB [ 72 ], UCB [ 54 ], hESCs, iPSCs [ 57 ], and even NK-92 cell lines [ 73 ] as mentioned above. Similar to CAR-T cells, the functional CAR molecule expressed on NK cells comprises three components: an extracellular domain, a transmembrane region, and an intracellular signaling domain (Fig. 6A ). The extracellular domain includes a signal peptide and a single-chain antibody fragment (scFv) responsible for recognizing the antigen. A hinge region connects this structure to the transmembrane region, which, in turn, links to the intracellular domain containing the activation signal. The commonly utilized transmembrane segment for CAR-NK is adapted from CD3ζ, CD8, or CD28, with T cell-specific CD8 and CD28 being the most frequently employed [ 74 ]. The intracellular segment is pivotal for cell activation post-reception of the target antigen signal and constitutes a linear structure of co-stimulatory molecules and signaling domains recruited downstream of signal transduction. Successful CAR design is achieved via a combination of meticulous design and functional testing. The evolution of CAR generations includes the first generation containing only CD3ζ [ 75 ], the second and third generations adding one or two co-stimulatory domains, respectively, based on the first generation [ 76 ], the fourth generation incorporating a cytokine secretion segment based on the third generation [ 77 ], and the fifth generation introducing a special binding motif (Fig. 6A ). Logic-gated control of CAR cells has also been developed to achieve precision therapy and avert potential toxicity (Fig. 6B ). Currently, the second-generation CAR structures CD28-CD3ζ and 41BB-CD3ζ are most commonly used in the field of CAR-NK, whereas in the third generation, CD28-41BB-CD3ζ is also frequently employed [ 74 , 78 ]. A detailed description of each CAR element is discussed below. Vector backbone and promoter The vector backbone incorporates all elements necessary for CAR expression, including a promoter, polyA signal, and transcriptional regulatory fragments. The choice of promoter directly impacts the expression of the transgene. Current reports on CAR-NK cells reveal the use of various promoters to drive CAR expression, whether derived from cell lines [ 79 ] or primary NK cells [ 80 ]. In primary CAR-NK and CAR-NK cell lines, viral promoters (such as MPSV and MMLV) are more commonly utilized than constitutively active promoters (such as EF1α and PGK) [ 81 ]. Signal peptide Signal peptides exhibit substantial heterogeneity, leading to varying levels of protein production efficiency. For CAR-NK and CAR-T cells, comparative studies identifying the optimal signal peptide are lacking. Currently, CD8a-SP is the most commonly used signal peptide sequence for NK cells, and immunoglobulin heavy or light chain signal peptides are reported for NK cell lines [ 82 ]. Single-chain antibody fragment (scFv) The scFv serves as the tumor antigen-binding domain of CAR [ 83 ], determining the specificity and function of CAR-NK cells. As single-chain antibodies deviate from the natural form of antibodies, the order of the heavy and light chains is artificially determined [ 84 ]. For CAR-NK designs, the VH-VL direction is preferred over the VL-VH direction [ 85 – 87 ]. Fujiwara et al. revealed that the order of the heavy and light chains does not affect the expression of CARs on T cells [ 88 ]. Furthermore, cells can be equipped with multiple scFvs, thereby expanding the antigen recognition capacity of CAR effector cells. Several options exist: the CAR can be transduced with a two-element vector, inducing the expression of two CAR constructs; or two scFvs can be fused in one construct, creating a “single-handle” CAR with tandem scFvs [ 44 , 89 ]. While these technologies have been utilized to produce CAR-T cells [ 90 ], their application in CAR-NK cells is not well-documented. In most current clinical CAR-T cell trials, single-chain antibodies derived from mouse antibodies are commonly used, increasing the risk of GVHD in anti-mouse IgG cells. This risk can be mitigated through humanization or screening of fully human antibodies [ 91 ]. Unfortunately, even humanized scFvs may induce host anti-idiotypic immune responses due to the chimeric nature of CAR receptors [ 92 ]. However, in the limited number of CAR-NK clinical trials to date, no major adverse effects associated with anti-CAR immune responses have been identified [ 66 ]. Moreover, several other forms like nanobody were also explored to serve as the tumor antigen-binding domain. Linking region The linking region between the heavy and light chains contributes to stabilizing the conformation of the single-chain antibody. A too-short linking region may lead to multimer formation, whereas a too-long linking region can cause hydrolysis or reduce the association between VH and VL domains [ 93 ]. For CAR-NK cells, the GGGGS pentapeptide is widely used in multimers, typically in 3 repeats. Another linker designed to enhance proteolytic stability is the Whitlow “218” linker (GSTSGSGKPGSGEGSTKG) [ 88 , 94 ]. Hinge region The hinge region, the extracellular domain of the CAR connecting the single-chain antibody unit and transmembrane domain, maintains the stability required for robust CAR expression and activity in effector cells. Most CAR-NK constructions use derivatives of CD8α or CD28 extracellular domains or IgG-based hinge regions. The type and length of the hinge region significantly affect the functional activity of CAR [ 95 ]. Although most information comes from CAR-T, the direct transformation into CAR-NK remains unproven. A direct comparison between CD28 and CD8α hinge regions revealed that CD28 is more likely to promote CAR molecule dimerization, resulting in a stronger activation stimulus [ 93 ]. While beneficial, this can also lead to more serious adverse effects. IgG-based hinge regions, made up of the Fc portion of IgG1 or the CH2/CH3 domains of the Fc portion, offer flexibility in structure. The length of the hinge region can be adjusted to adapt to antigen recognition; however studies have revealed that a shorter spacer region results in higher cytokine production, faster CAR cell proliferation, and improved persistence and antitumor effects in vivo [ 95 ]. Transmembrane domain The transmembrane domain connects the CAR extracellular domain and the intracellular activation signal domain. The most commonly used transmembrane domains for CAR-NK originate from CD3ζ, CD8, and CD28. The choice of transmembrane domain influences the activation extent of the CAR construct in cellular functions. Transmembrane domains from molecules typically expressed on NK cells, such as DNAM-1, 2B4, and NKG2D, lead to increased CD107a degranulation and higher cytotoxicity. Thus, the specific source of the transmembrane domain determines the activity of CAR-NK [ 96 ]. An important aspect of the transmembrane domain is that it should follow the natural orientation (order of N-terminal to C-terminal) of transmembrane proteins on NK cells. At present, CD8α- and CD28-modified transmembrane regions are most common in primary CAR-NK cells, whereas CD28 is the preferred transmembrane region for CAR-NK cell lines [ 93 ]. Activation signal The number of intracellular activation signals in a CAR determines its “generation”. First-generation CAR-NK cells, akin to CAR-T cells, contain only the CD3ζ signal. Second-generation and third-generation CAR-NKs carry one and two additional co-stimulatory signals, respectively, typically derived from the CD28 family (CD28 and ICOS), the TNF receptor family (4-1BB, OX40, and CD27), or the signaling lymphocytic activation molecule-related receptor family (2B4) [ 97 ]. The published CAR-NK clinical trial used a second-generation CAR-NK construct that improved activity by incorporating IL-15 expression. Most current CAR structures depend on the CD3ζ chain signaling domain, and robust activation signals are crucial for eliciting potent antitumor responses but may also result in rapid effector cell exhaustion. Combinations of co-stimulatory domains can be employed to calibrate desired immune cell responses. CD28-based CARs exhibit a faster effector profile than 4-1BB-based CARs, inducing higher levels of IFN-γ, granzyme B, and TNF-α. However, this strong co-stimulatory signal also results in activation-induced cell death (AICD). Conversely, 4-1BB-CD3ζ signaling preferentially induces memory-related genes and sustained antitumor activity [ 98 , 99 ]. This difference may be attributed to the amelioration of T cell exhaustion induced by the 4-1BB domain in contrast to the CD28 domain [ 44 ]. CD3ζ was universally used as the primary activation domain in studies of CAR-NK cell lines and primary CAR-NK cells, with approximately half carrying an additional activation domain, generally with the addition of 4-1BB or CD28. For third-generation constructs, the combination CD28/4-1BB/CD3ζ is most commonly employed. Intracellular signaling domains, such as CD28, 4-1BB, and OX40, often function to trigger immune cell activation and inhibition [ 100 ]. A recent report using iPSC-derived CAR-NK therapy identified the crucial role of the NKG2D transmembrane domain and emphasized the critical role of the 2B4 co-stimulation domain [ 96 ]. Different researchers also performed similar studies using 2B4 to highlight the importance of the activation signal in immune cell therapy [ 101 , 102 ]. At present, four generations of CAR structures have been developed and are available for CAR-NK research. CAR transfection or transduction vector With the advancement of gene modification technology, various methods have been employed to generate CAR-NK cells. The two primary methods include viral transduction [ 103 ] (using lentiviruses or retroviruses) and transfection of naked plasmid DNA [ 87 ], transposase DNA-mediated integration [ 104 ], and mRNA electroporation [ 96 ]. Lentiviruses can efficiently transduce both periodic and non-cyclical cells and have been widely utilized in gene therapy [ 105 ]. They have been successfully used as vectors in studies on primary CAR-NK cells and CAR-NK cell lines. Both second-generation and third-generation lentiviruses have been used in preclinical studies to generate CAR-expressing NK cell lines and primary CAR-NK cells. Retroviral vectors are also commonly used for NK cells [ 54 , 66 ]. Retroviruses have been used as gene therapy vectors for decades, including CAR-NK cell lines and primary NK cells [ 106 ]. In a recent phase I clinical trial, retroviral-transduced CD19 CAR-NK cells were used to treat CD19 + non-Hodgkin’s lymphoma and chronic lymphocytic leukemia. The study results stated that 73% of patients responded to the treatment, with 7 of 8 patients achieving a complete response. Responses were rapid, occurring within 30 days of CAR-NK administration at all dose levels. After the 1-year follow-up, expanded CAR-NK cells remained detectable [ 66 ]. Following infusion, CAR-NK DNA copy numbers remained stable in PB for up to 1 year, indicating, for the first time, that retroviral-transduced CAR-NK cells can exhibit long-term in vivo survival. Different retroviruses types have been used to generate CAR-NK cells. The RD114 retrovirus was reported to be more efficient at transducing primary NK cells than the γ retrovirus and lentivirus [ 107 ]. Although long-term stable CAR expression in NK cells can be achieved using various retroviruses, the safety of retroviral systems remains a concern, especially when compared with the safer lentiviruses. CAR-encoding mRNA electroporation is a rapid, efficient, but short-lived method. To date, mRNA electroporation has been used in CAR-NK cell lines and primary CAR-NK cell studies. Generally, expanded or activated NK cells exhibit much higher mRNA transfection efficiency than freshly isolated NK cells [ 108 ]. Because mRNA synthesis is a good manufacturing practice (GMP)-compliant manner and electroporation can be conducted in a clean room, it is feasible to generate GMP-compliant CAR-NK cells through mRNA electroporation. However, the primary disadvantage of this approach is the short window for CAR expression: after electroporation, CAR-NK cells should be infused back into the patient within 7 days. The Sleeping Beauty transposon system has also been developed. Transposon-based systems offer important advantages over conventional methods, such as the efficient introduction of CAR transgenes at predetermined locations. Transposons are primarily introduced into NK cells via electroporation and then integrated into the host genome by transposonases [ 50 ]. Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 is another powerful genetic modification technology that introduces the Cas9 protein into NK cells along with gRNA. This technique was initially used to disrupt the CD38 gene in primary NK cells [ 109 ], aiming to prevent NK cell cannibalism in combination with daratumumab (anti-CD38) because CD38 is expressed in NK cells, multiple myeloma [ 110 ], and acute myeloid leukemia (AML) cells [ 111 ]. CRISPR/Cas9 has also been recently used to introduce some other new genes [ 112 ]. Overall, using CRISPR/Cas9 strategy is a promising strategy to precisely delete, repair, or introduce specific genes, facilitating the generation of potent antitumor NK cells. While we have established the superiority of a specific domain among multiple candidates based on findings from T cells expressing the CAR applied into NK cells, it is crucial to note that the superiority of CAR domains is complex and depends on factors such as the target and the interaction with other domains. Further exploration is needed to determine if the results and experiences obtained from T cells are applicable to NK cells and to anticipate optimization. Moreover, the expansion of NK cells may result in an adverse phenomenon of “suicide” or “fratricide” as mentioned above, where cells recognize receptors or ligands on the surface of other similar cells and trigger cytotoxic activity against them. The Fas/FasL axis is among the most relevant mechanisms. FasL-mediated cytotoxicity plays a crucial role in NK cell function, triggering caspase-dependent apoptosis when it binds to the receptor Fas in the target cell. Fas can also serve as a steady-state mechanism for inhibiting NK cell activity expressed by NK cells, known as AICD. NKG2D is another receptor that may lead to self-killing among NK cells, which is a natural receptor primarily comprising NK, CD8 + T, and γδ T cell expression, displaying recognition of various stress-induced ligands. Cannibalism may also occur in CAR-NK cells due to CAR ligand/antigen recognition if certain target antigens are also expressed on these effector cells [ 113 ]. Furthermore, trogocytosis is a common phenomenon that often takes place during NK cell-mediated cancer inhibition. Trogocytosis ultimately leads to the transfer of antigens to NK cells, mediating the inhibition of NK cells by other NK cells. The knock out of target antigens in effector cells can overcome fratricide, but this method is unsuitable for antigens transferred to effector cells during trogocytosis. Low affinity of CAR to antigen or optimized CAR signaling transduction may serve as alternative approaches [ 114 ]. Popular targets of CAR-NK research Solid tumor targets In several cancer types, programmed cell death ligand 1 (PD-L1) is upregulated in the tumor microenvironment (TME) and in immunosuppressive cells [ 115 ]. Preclinical tests have revealed that PD-L1-targeted CAR-NK cells exhibit specific antitumor effects against several in vitro tumor cell lines, and exhibit robust in vivo antitumor effects against triple-negative breast cancer [ 116 ], bladder cancer [ 117 ], and lung cancer [ 118 ]. Human epidermal growth factor receptor 2 (HER2)/erythroblastic oncogene B 2 (ERBB2) is often overexpressed in breast, gastric, esophageal, ovarian, and endometrial cancers [ 119 ]. HER2 is associated with poor survival and also expressed in most glioblastomas [ 120 ]. Extensive studies have been conducted on the application of CAR constructs targeting HER2 [ 121 ]. NKG2D is an activating NK cell receptor modulating the anticancer cytotoxic potential of NK cells by interacting with its tumor-associated overexpressed ligands [ 122 ]. NKG2D ligands include MICA, MICB, and ULBPs (ULBP1, ULBP2, ULBP3, ULBP4, ULBP5, ULBP6) [ 123 , 124 ]. Altogether, the targets in solid tumor (pre-) clinical therapy are relatively fewer than hematologic malignancies, but display potentials that CAR-NK cells congregate in these tumors [ 50 ]. Hematologic malignancy targets Clinical studies have demonstrated the significant efficacy of anti-CD19 CAR-T cell therapy in tumor immunotherapy [ 66 ]. However, CAR-T cell therapy is constrained by various adverse effects and manufacturing challenges. CAR-NK cells present themselves as an alternative therapeutic strategy for hematological malignancies, focusing on the currently popular targets (Fig. 7 ). Multiple myeloma (MM) is a hematologic malignancy, and numerous CAR-T and CAR-NK cell therapies are being currently developed [ 125 ], with B-cell maturation antigen being the most popular cell therapy target [ 126 ]. Furthermore, CD38 and CD138 are also common targets for MM treatment with CAR constructs [ 127 ]. CD19, CD20, and CD22 are commonly employed targets for CAR-T cell therapy in B-cell lymphoma and leukemia. Two major challenges in constructing CARs against AML include shared antigen expression and heterogeneity with hematopoietic progenitor cells. Shared antigenic expression of CD123 and CD33 can result in on-target nontumor toxicity [ 128 , 129 ]. In several cases, targeting various AML-associated antigens (such as FLT3 [ 130 ], CD123 [ 131 ], CD33 [ 132 ], CLL-1 [ 133 ], and GRP78 [ 134 ]) using multiple CARs may be necessary because certain tumor-associated antigens (TAAs) may not be expressed on all leukemia cells. Challenges of NK cell therapy At present, CAR-NK cells demonstrate obvious advantages compared with CAR-T cells, as summarized in previous literature [ 135 – 137 ] (Table 1 ). Registered clinical trials using these cells have seen a rapid increase, as shown in Table 2 . Unlike CAR-T cell clinical applications, NK cells exhibit relatively acceptable toxicity adverse effects, avoiding effects such as cytokine release syndrome. Several clinical trial evidences support this, for instance, Tang et al . reported the first-in-man CD33 + CAR-NK-92 cell clinical trial, testing safety in patients with AML experiencing relapsed and refractory conditions. The dose of 5 × 10 9 cells in each patient led to no evident adverse effects [ 138 ]. Additionally, Liu et al. reported phase I and II trial outcomes using CD19 CAR-NK cells, revealing a rapid response in patients with CD19 + cancer with relapsed or refractory conditions, without apparent associations between effectors and adverse effects, including neurotoxicity, cytokine release syndrome, or GVHD [ 66 ]. However, challenges persist in this type of immunotherapy, summarized as follows: Low persistence A major drawback is the lack of in vivo persistence of infused cells in the absence of cytokine support, limiting the effectiveness of NK cell immunotherapy. While exogenous cytokines have been reported to increase proliferation and persistence of adoptive NK cells [ 139 ], they can also lead to undesired adverse effects, including the expansion of suppressive immune subsets, such as Tregs [ 140 ]. Rejection of allogeneic NK cells by host T cells is also a critical consideration in cell therapy using allogeneic NK cells. Further exploration of the role of transmembrane-bound IL-15 in promoting NK cell persistence is warranted. Transport to the desired tumor site The efficient homing of NK cells to tumor sites has been debated, as rapid homing to the tumor bed is critical for adoptive cell therapy efficacy. This process is regulated via complex interactions between NK cells and chemokines released by tumor cells [ 141 ]. Various engineering approaches have been explored to enhance NK cell migration to tumor sites. For instance, NK cells have been subjected to electroporation with mRNA encoding the chemokine receptor CCR7 to enhance migration to lymph nodes expressing the chemokine CCL19 [ 20 , 142 ]. To improve the success rate of NK cell immunotherapy in patients with solid tumors, mouse models have been used to explore novel techniques promoting NK cell translocation to tumor sites [ 143 ]; however, the effectiveness of these approaches requires further verification in clinical trials. Immunosuppressive tumor microenvironment (TME) The TME, encompassing immunosuppressive molecules, immunosuppressive cells, and an unfavorable environment hindering immune cell function, poses a major obstacle for CAR-NK cell therapy. Immunoregulatory factors such as transforming growth factor (TGF)-β and others present in the TME can impair NK cell activity [ 144 ]. Researchers are investigating the development of CAR-NK cells that counteract some of these immunosuppressive effects, such as knocking out associated genes of NK cells using CRISPR/Cas9 technology [ 145 ]. Another strategy to overcome NK cell depletion [ 146 ] in the TME is to eliminate checkpoint components using genome editing to improve their function. Low transduction efficiency of lentivirus Lentivirus-based transduction systems represent one of the most commonly used methods for intracellular gene modification and delivery. However, the natural resistance of NK cells to lentivirus poses a challenge to efficient transduction. Various chemicals, such as protamine sulfate, are employed to enhance viral transduction [ 147 ]. Altogether, while CAR-T cell immunotherapy provides a promising approach to treating certain cancers, there are still several limitations: 1) high costs leading to unavailability; 2) long production cycles resulting in patients being unable to afford waiting; 3) poor cell quality of patient samples potentially leading to production failure; 4) CRS and neurotoxicity contributing to high treatment risks. Therefore, the general CAR holds great promise. NK cells, with their unique biological characteristics, demonstrate distinct advantages as potential “off-the-shelf” universal CAR-NK cells. As a promising alternative, different sources of NK cells (including UCB, PB, cellular lines, and iPSCs) could be utilized. Additionally, the allogeneic context without obvious toxic adverse effects presents a significant advantage, even though most CAR-NK cells are still in preclinical or early clinical trial stages. However, the short persistence of NK cells after infusion in vivo remains a major setback. Optimization and standardization of cell expansion and target gene transfection also need further definition, considering the differences between T cells and NK cells. Lastly, akin to CAR-T cells, the lack of tumor-specific targets poses a significant challenge for CAR-NK cell applications in various cancer treatments, including hematologic and solid tumors, necessitating further development for precision medicine. Development directions of NK cell therapy Recognition of novel target antigens As mentioned above, identifying highly consistently expressed target tumor antigens is a critical step in CAR design. Most TAAs are also expressed by some healthy cells, potentially causing a “targeting nontumor” effect [ 148 ]. Furthermore, the expression of these TAAs can vary greatly among single-cell clones of the same tumor. To address this issue, bispecific CARs have been designed to target multiple antigens simultaneously. This can be achieved by injecting different CAR-NK cells targeting distinct antigens simultaneously or designing one CAR to recognize multiple antigens through “tandem CARs,” wherein two combined elements are attached to individual molecules to enhance the immune synapse [ 149 ]. Additionally, multiple CARs can be simultaneously produced on the same immune cell using a vector. Improving NK cell activity Various immune checkpoints, such as PD-L1, regulate and suppress NK cell activity. For instance, a new NK-92 cell line designed with a CAR targeting PD-L1, known as PD-L1-targeting haNK, demonstrated specific antitumor effects against several tumors in preclinical data [ 150 ]. Another strategy to improve the activity of CAR-NK cells involves regulating tumor metabolism, an area that has not received sufficient attention. Under hypoxic conditions, adenosine is produced via ATP metabolism by CD39 and CD73, contributing to immune evasion, preventing NK cell trafficking to tumor sites, and inhibiting NK cell maturation. NKG2D-engineered CAR-NK cells exhibited efficacy in treating lung cancer following anti-CD73 antibody inhibition [ 151 ]. Therefore, immune checkpoint regulation remains a crucial consideration in cell-based immunotherapy. Overcoming the immunosuppressive TME Tumors harbor various immunosuppressive factors, including TGF-β, IL-10, and PD-1. Several strategies are utilized to mitigate their inhibitory effects. Combining TGF-β kinase inhibitors with NK cells has been observed to restore NK cell cytotoxicity and preserve NKG2D and CD16 expression [ 152 ]. Additionally, hybrid CARs incorporating extracellular TGF-β receptor domains have proven successful in improving the antitumor potential of NK-92 cells [ 153 ]. Furthermore, the concurrent use of immune checkpoint blockade inhibitors presents a promising avenue. Improving security Enhancing the safety of CAR-NK cell-based therapy may involve modifying the CAR structure by incorporating suicide genes [ 154 ]. Developing bispecific CAR molecules to better target tumor-specific antigens is another crucial approach. CAR-NK cells exhibit the unique ability to target tumors in both a CAR-dependent and CAR-independent manner. This ability can be harnessed to achieve enhanced tumor inhibition by developing nonsignaling CARs. These nonsignaling CARs lack direct killing signals but can augment the specific killing of NK cells by promoting residence and adhesion to target cells [ 136 ]. Another intriguing strategy involves designing CAR-NKs capable of modulating the TME. These highly specialized CAR-NK cells express several foreign genes that can modulate the local TME to prevent any harmful effects. Improving accessibility Addressing the accessibility of CAR-NK cells in solid tumors necessitates various approaches, including topical, intraperitoneal, and focused ultrasound-guided drug delivery. For instance, pleural injections proved highly effective in an orthotopic model mimicking human pleural malignancies, demonstrating an even longer duration of function compared to intravenous injections [ 155 ]. The topical administration of CAR immune cells may also help reduce treatment doses. Prospective future NK cells stand as a unique cohort of antitumor effector cells, wielding functions such as MHC-independent cytotoxicity, cytokine production, and immune memory. These attributes position them as pivotal contributors to both innate and adaptive immune response systems. The field of CAR-NK cell therapy holds promise in clinical research, demonstrating commendable safety and preliminary efficacy in certain patients with cancer. In comparison to CAR-T cells, CAR-NK cells boast distinct advantages, yet they grapple with challenges. Enhancing cell proliferation, facilitating more efficient activation of cytotoxicity, and ultimately optimizing NK cell reconstitution are concerns. Consequently, advancements in large-scale preparation methods, cryopreservation measures, and efficacy are imperative. Addressing the short duration of in vivo persistence and exhaustion remains an unresolved frontier. Overall, CAR-NK is poised to evolve into a versatile cell product, holding greater advantages in single-drug or combined transplantation, monoclonal antibody applications, and other treatments. With the formidable antitumor lineage of NK cells as a foundation, overcoming these challenges is likely to usher in groundbreaking developments in tumor treatment. The rapid evolution of NK cell-based immunotherapy (Fig. 8 ), reflected in the expanding cancer cell therapy pipelines [ 156 , 157 ], proves that CAR-NK modifications will pave the way for new breakthroughs. In the near future, the maturation of CAR-NK cell therapy technology promises uplifting news for a broader spectrum of patients with cancer, propelling humanity closer to conquering the challenges of refractory and recurrent cancer treatments.

Author contributions BZ, NY and TR conceived and contributed to the writing of the manuscript. MY, WZ, NL, DW, LJ, NX contributed to the writing of the manuscript. BZ, NY and TR revised and wrote the manuscript. All authors reviewed the manuscript. The authors read and approved the final manuscript. Funding This research was supported by Yunnan Fundamental Research Projects, China (Grant no. 202201AT070198) and the National Natural Science Foundation of China (Grant no. 82260038). Data availability The relevant information is available from the corresponding author upon reasonable request. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Cell Death Dis. 2024 Jan 15; 15(1):50

oa_package/b6/ed/PMC10788349.tar.gz

PMC10788350

38221543

Introduction Engagement with ballistic targets and its challenges As a result of the development of ballistic missiles as high-speed vehicles, combating these missiles has been the main challenge for air defense systems. The priority of countermeasures against these targets is interception during the boost phase, followed by exit from the atmosphere at the mid-course phase. This is related to low velocity besides the large radar cross section in an early stage of flight. Later, despite the high velocity, there is no drag or maneuverability due to the lack of atmosphere. Therefore, the trajectory of the projectile will be completely predictable. In these two phases, countermeasures face numerous tactical and technological obstacles such as the need to be in the enemy’s area for engagement in the boost phase, or the existence of an extensive and powerful radar network even in other countries. Consequently, most air defense systems intercept ballistic threats at the reentry phase. During this phase, the target has a high velocity, a small radar cross section, and the ability to change its trajectory. The first two characteristics reduce the interception time, while drag and maneuverability complicate the geometry of the engagement. To strike ballistic targets, the incident must first be a near-miss or a hit-to-kill one; second, it must occur at high altitudes, where the target cannot maneuver and if one interceptor fails to engage the target, another one still has a chance. Additionally, the cluster or chemical warhead causes less damage to the environment. Loss of aerodynamic efficiency and an increase in the time constant of the interceptor’s autopilot are obstacles posed by engagements at high altitudes. The use of thrusters in defense systems has been investigated as a possible solution to the issues mentioned above. More explanations regarding the types of thrusters and their features are provided in Section “ Thruster description ”. IGC background and common methods Generally, another obstacle is the limited time available during the final phase of engagement. The benefits of IGC include (a) eliminating the inevitable lag between traditional guidance and control loops, resulting in high-speed performance (b) considering interceptor dynamics (like aerodynamic capability) in guidance equations, resulting in desirable performance while preventing saturation during rapid changes in engagement geometry 1 . Due to its robustness against uncertainties and disturbances, Sliding Mode Control (SMC) is one of the categories most commonly employed IGC design methods. In references 2 , 3 , the conventional SMC law is used to intercept a maneuvering target. These studies assume that the target acceleration is known, and if estimation or measurement errors exist, this method will not perform as desired. This technique is applied to a “bang-bang” interceptor in 4 . Using first-order SMC and linear matrix inequalities, a robust IGC law is proposed to intercept targets at the ground level 5 . A high-order SMC approach has been utilized in references 6 , 7 to decrease control signal chattering, finite-time convergence and reduce the amount of required information about the target. Due to the feedback form of IGC equations, back-stepping and inverse dynamics control methods have been highly used in addition to the SMC method. Adaptive variants of these methods are also implemented by authors of 8 , 9 . Moreover, numerical methods, including a State-Dependent Riccati Equation (SDRE) 10 and 11 , have been utilized for the three-dimensional design of IGC. Novel techniques, including the small-gain theorem 12 , and nonlinear Receding Horizon Pseudospectral Control (RHPC) 13 have also been developed. Research motivation The main motivation of this research is to develop a method to destroy a tactical ballistic target in the atmosphere. According to Section “ Engagement with ballistic targets and its challenges ”, the miss distance should be smaller than 1 m (for hit-to-kill interception) and the engagement should be at an altitude as high as possible. Achieving this interception accuracy requires to consider all uncertainties, disturbances and different types of target maneuvers. On the other hand, it is necessary for the developed method to eliminate the need for expensive and very high accuracy seekers. This problem includes complexities such as the existence of nonlinear terms in the equations, high drag acceleration of ballistic targets, target maneuver, change of aerodynamic coefficients due to the interaction of thruster outlet jet with free flow, the uncertainty of coefficients, disturbance torque caused by thruster and seeker error in short time interception. The main issue identified in Section “ IGC background and common methods ” is the inability to deal with target acceleration, uncertainties, and disturbances simultaneously with desirable control performance. Those articles using back-stepping family or numerical methods, account for minute uncertainties and disturbances. Also the effect of some nonlinear terms such as the angle between the velocity vector and the line-of-sight is not seen in the model for simplification, and target without maneuver is assumed. Also the works addressing SMCs, face several problems: (a) In the initial research, they wanted complete information about the target maneuver, and then they tried to make the information less, but this need still exists (b) With increasing target acceleration (which occurs in ballistic targets due to high speed), a larger switching gain should be selected, which leads to chattering. (c) Despite encountering multiple disturbances, perform the simulations at low velocities (long interception time) to avoid chattering to obtain good performance, which is inefficient for intercepting tactical ballistic targets (d) The need for a high fin rate actuator. Today, due to advancements in control strategies, more effective methods are used to deal with disturbances without causing SMC problems. Among these techniques is Disturbance Observer Based Control (DOBC), which employs a double-layer structure for removing disturbances and improves closed-loop performance. Due to complexities mentioned above, this structure as a controller can be helpful. It is no longer necessary to know the acceleration band of the target. There are many methods in the DOBC family, one of them is Active Disturbance Rejection Control (ADRC). Classic ADRC is used for integral chain systems and matching conditions 14 . In contrast, IGC equations are mismatched and formulated in a feedback form. This challenge necessitates initiatives for the IGC structure’s implementation of this method. Also the advantage of this method is the controller’s consideration of all system-affecting factors, including nonlinearities, uncertainties, and external disturbances, as a lumped disturbance that must be estimated and compensated. IGC and DOBC In 15 , 16 ESO estimates target acceleration. Reference 17 focused on ground target with negligible maneuver. It uses ESO combined with back-stepping method. Reference 18 employed a Reduced-order Extended State Observer (RESO) filter and the back-stepping control, demonstrating that RESO has a wider bandwidth than ESO. The actuator rate saturation is not considered in the simulation, and it does not have the ability to engage with high-speed targets with high Zero Effort Miss (ZEM). SMC and super-twisting ESO combination was used for three-dimensional interception, considering the impact angle described in 19 . Due to the type of filter used along with the sliding mode structure, it cannot have the desired efficiency in a short time and at a high speed. To get a faster answer, Non-singular Terminal Sliding Mode control (NTSM) with ESO is used in 20 for intercepting maneuvering target. To avoid chattering, the authors used nonlinear tracking differentiator that complicates the issue. In 21 , RESO combination with the back-stepping and sliding mode framework is also used. The important point of this research is to consider the delay of the actuator. However the desired performance at high speed without complicating the control structure is still neglected. Some other types of observers like nonlinear filter, 22 and adaptive one 23 have been employed to estimate disturbances. Our contributions As reviewed in Section “ IGC and DOBC ” most of the research conducted in the field of combining DOBC and IGC has used the structure of back-stepping or SMC due to easy implementation. However what is neglected, is the simultaneous high maneuver target, high closing velocity and high altitude engagement, with multiple disturbances, all required to intercept a ballistic target. These constraints cause the equations to be changed for the use of Divert Control System (DCS) thruster and the requirement of simultaneous commanding to thruster and fins in the final phase arises. Also, the RESO filter is used to estimate the disturbances and uncertainties with a suitable bandwidth and compatible with the cascade control structure. The next issue is that all the cases investigated, use true value for line-of-sight rate without considering the seeker filter and measurement error in the guidance as an important source of error to reach the hit-to-kill interception. In this regard, the main contributions of the present study are summarized as follows: To overcome the challenges of engagement with a tactical ballistic target, we use an interceptor with a tail and a thruster on the center of mass using the control allocation algorithm in the IGC and DOBC structure. Contrary to all existing solutions, seeker dynamics and measurement errors are formulated and implemented. Due to the short homing phase, this error in the line-of-sight rate poses a significant difficulty in intercepting high-speed targets with a small radar cross-sectional area. A complete simulation was performed by sweeping ZEMs and different heights to demonstrate the effectiveness of this method versus the conventional method. It has been mentioned in some references such as 22 that the cascade structure in IGC has destroyed its advantage over the conventional method. In Section “ Case 3 ” this claim is completely rejected and the reasoning is explained. Organization The current paper is structured as follows: In Section “ Problem formulation ” a mathematical model of the thruster is developed for the engagement problem. Section “ IGC law design with Reduced order ESO ” discusses the design of the controller with an observer. Section “ Stability analysis of the closed-loop system ” demonstrates the stability of the implemented method, while Section “ Seeker filter design ” defines seeker dynamics and measurement error. Furthermore, Section “ Simulation results ” presents the results of detailed comparisons between simulations to illustrate the crucial role of the proposed method. Section “ Concluding Remarks ” provides conclusion remarks, discussing the effectiveness and difficulties of proposed method for intercepting ballistic targets.

IGC background and common methods Generally, another obstacle is the limited time available during the final phase of engagement. The benefits of IGC include (a) eliminating the inevitable lag between traditional guidance and control loops, resulting in high-speed performance (b) considering interceptor dynamics (like aerodynamic capability) in guidance equations, resulting in desirable performance while preventing saturation during rapid changes in engagement geometry 1 . Due to its robustness against uncertainties and disturbances, Sliding Mode Control (SMC) is one of the categories most commonly employed IGC design methods. In references 2 , 3 , the conventional SMC law is used to intercept a maneuvering target. These studies assume that the target acceleration is known, and if estimation or measurement errors exist, this method will not perform as desired. This technique is applied to a “bang-bang” interceptor in 4 . Using first-order SMC and linear matrix inequalities, a robust IGC law is proposed to intercept targets at the ground level 5 . A high-order SMC approach has been utilized in references 6 , 7 to decrease control signal chattering, finite-time convergence and reduce the amount of required information about the target. Due to the feedback form of IGC equations, back-stepping and inverse dynamics control methods have been highly used in addition to the SMC method. Adaptive variants of these methods are also implemented by authors of 8 , 9 . Moreover, numerical methods, including a State-Dependent Riccati Equation (SDRE) 10 and 11 , have been utilized for the three-dimensional design of IGC. Novel techniques, including the small-gain theorem 12 , and nonlinear Receding Horizon Pseudospectral Control (RHPC) 13 have also been developed.

Simulation results Numerous numerical simulations were performed, and the results are reported in this section to evaluate the performance of the proposed IGC law in conjunction with the thruster and to demonstrate its ability to intercept high-speed and accelerated targets. This section examines various aspects of this research through four hypothetical situations. All of these scenarios pertain to an interceptor’s terminal phase against a tactical ballistic target with a maximum velocity of 2500 m / s . The angle between the interceptor’s velocity vector and the predicted intercept point (PIP) suggests that the mid-course guidance failed to nullify the zero effort miss (ZEM) at the beginning of the terminal phase. In this circumstance, it was assumed that: The interceptor’s specifications are listed in Table 1 . As mentioned above, the interceptor has an active seeker, and the terminal phase range is less than 7 km due to issues such as the frequency band of the seeker, its limited power, and the RCS of ballistic targets in that band. Due to the high relative velocity, the homing phase range is highly effective for ZEM ability to compensate. In addition, was chosen as the standard deviation of the angle measurement error for this range. The relative velocity along the LOS and the interceptor-target distance at each instant were utilized to calculate the time to go , and the thruster was activated just 1 s before the interception. In addition, the thruster had a maximum acceleration of 8 g. The bandwidth of the differentiator filter is assumed to be 15 rad/s, whereas the bandwidth of the RESO estimators (for all channels) are set as , and rad/s. In addition, the controller gains are selected as follows: After passing through the second order transfer function ( 49 ), the elevator command was applied to the simulation by passing the rate limit block up to a maximum of and then the saturation block up to a maximum of . where is actuator natural frequency and is damping factor with , . Notably, including the actuator rate limit in the simulation leads to make the case realistic and reduces the controller bandwidth, significantly impacting the engagement outcome. Simulations indicate that actuator rate must be increased for a proper engagement at higher altitudes. Design-wise, this rate should be increased by increasing the interceptor’s height and decreasing the hinge moment. The interceptor was assumed to have a maximum structural load of 22 g due to aerodynamics and thrusters, leading to a restriction of . Finally, miss distance with ZEM calculation is reported at . Remark 6 To calculate ZEM according to reference 33 , the following formula is used: where and are relative velocity vector and relative position vector in inertial frame, respectively. Case 1 The objective of the first scenario is to engage a ballistic target with the specifications listed in Table 2 . This scenario aimed to demonstrate the effectiveness of the proposed IGC method for a dual-controlled interceptor. The terminal phase is begun at an altitude of 12 km and ended at 13 km. The problem carried the following uncertainties and disturbances: 1. Acceleration of the 9g step of the target (as stated previously, the source of this acceleration could be an error in the installation of the ballistic warhead’s fins or the presence of a maneuver to change the trajectory of some tactical ballistic missiles); 2. An 8g drag acceleration at the beginning of the scenario; 3. Reduction of aerodynamic coefficients , , and in the controller relative to simulation equations by , and , respectively; 4. A 7 cm installation error between the thruster nozzle and the interceptor’s center of mass. was supplied directly to ( 10 ), ( 21 ) and ( 23 ) without passing through the filter and adding noise based on the ideal seeker assumption. The kinematics of the engagement is depicted in Figure 4 . The final phase’s engagement time was 1.95 s , and the obtained miss distance was 0.46 m, as represented in Figure 5 . This value indicates the direct interception and success of the scenario. Due to the target’s high speed, the velocity vector has rotated approximately due to gravity, maneuver, and drag, which can result in a larger miss distance if the acceleration is not estimated and compensated for in the IGC law. As depicted in Figure 6 , the interceptor’s velocity vector rotated by in a short period, causing a significant acceleration to compensate for the error. Before using the thruster, the interceptor utilized all its aerodynamic capabilities to minimize the error. The thruster was then activated 1 s before the termination. As the error decreased, the aerodynamic and thruster accelerations decreased too, and in the final moments of the engagement, the interceptor attempted to make the miss distance zero by switching the sign of the acceleration. Figure 7 depicts the elevator steering so that the LOS rotation rate becomes zero and the pitch rate and AOA track the command in the presence of uncertainties, which is illustrated in Figure 8 . In parallel guidance techniques, such as Proportional Navigation (PN), which are based on zeroing the LOS rate, the guidance bandwidth continuously grows by decreasing the relative range 34 . Consequently, the LOS rate changes drastically at the conclusion of the engagement as depicted in Figure 8 . Also, this Figure demonstrates that, given a proper time constant, the AOA and angular velocity can follow their commands. Because the inner loop is quicker, the angular velocity tracking error is less than the AOA. Since tracking differentiator is not used, an initial error with command values is created. As it is well-established, using a first-order lag and pseudo-differentiator in the scenario is sufficient and does not cause any problems. Before the thruster was activated, the aerodynamic acceleration could not prevent the increase in the LOS rotation rate. Once the thruster was activated, however, this parameter became zero. Finally, Figure 9 depicts both the estimated and actual values of the disturbance in the problem. As it can be seen, the disturbance leap parameters that occur at 0.85 s are the activation of the thruster and the torque produced by its distance from the center of mass. The disturbances caused by the target’s drag and acceleration are accurately calculated in , and the observer’s bandwidth is suitable for high speeds and short periods. In this case, it was demonstrated that the proposed method is suitable for use in destroying a ballistic target. Table 3 presents the miss distance for this scenario in four different modes to emphasize the importance of utilizing the thruster and observer in this engagement. Accordingly, an observer is required to estimate disturbances and uncertainty for the hit-to-kill interception. The impact of the thruster on the interception at high altitudes is another element of significance included in Table 3 . Therefore, the absence of a thruster caused a miss distance of 15.3 m at an altitude of 12 km but only 5.5 m at an altitude of 9 km. This is due to a decrease in target velocity resulting from a decrease in interception altitude, required actuator rate, and interceptor time constant. However, it is not recommended to intercept ballistic targets at low altitudes due to factors such as the target’s increased maneuverability, the increased risk of destruction, and the presence of cluster warheads. The last thing that is investigated in this case is the effect of the controller gains on the miss distance at the height of 12 km. By changing the gains as , and , the simulation results show that the tracking error has increased, but in the presence of the thruster, the miss distance has not changed much and has reached 1.23 m. If the thruster is removed, the miss distance increases to 3.71 m. Also, if the gains are chosen as , and , due to the increase in the bandwidth of the inner loop compared to the actuator, the simulation becomes unstable and the miss distance becomes 136.2 m. Case 2 In this scenario, the key difference is that the LOS rotation rate is passed through the dynamics ( 44 ), and the range-dependent error ( 45 ) is added and then inserted into the IGC equations. The parameters for the seeker filter are as follows: Case 1 interception conditions with are used to demonstrate the thruster performance in the presence of seeker error. As ZEM decreases, the miss distance with the ideal seeker and no thruster equals 0.63 m (shifting the target velocity vector by ). Currently, the scenario is recreated in two modes, with and without thrusters, and the results are compared using a non-ideal seeker. Figure 10 depicts the variations in the parameters of the target and interceptor throughout the thruster-powered flight. In this mode, the miss distance corresponds to 0.3 m. Figure 11 illustrates the variations in LOS rotation rate, AOA, and pitch rate. First, due to angle measurement error, the seeker sees the target along the interceptor’s velocity vector, and the interceptor makes no attempt to correct the course. As the distance between the target and interceptor decreases, the seeker’s angle measurement error also decreases. When this accuracy increases, the interceptor has the opportunity to adjust the ZEM. Figure 12 illustrates the changes in aerodynamic and thruster acceleration throughout a flight. The thruster pulses may be observed in the incorrect direction due to the seeker’s inaccurate angle measurement during thruster initiation. It has expended all of its energy on ZEM modification by shortening the distance and increasing the precision of the seeker. Replicating the identical scenario without a thruster, results in a miss distance of 22.17 m. In this case, despite the improvement in seeker error and the interceptor’s command to attack at its maximum angle, there was insufficient time to account for the ZEM, and it could not be reduced to zero, as depicted in Figure 13 . In this scenario, the rate of the actuator is particularly important, as its command undergoes rapid dynamics as depicted in Figure 14 due to the noisy behavior of . The results indicate that a thruster is required to engage high-speed targets, such as ballistic ones when a non-ideal seeker is present. Case 3 In this case, the Monte Carlo execution for various ZEM’s and altitudes is examined to demonstrate the superiority of the proposed approach over the conventional two-loop method. The guidance and control technique described in reference 33 , in which the guidance and control loops are developed independently, serves as a comparison baseline. This method employs the PN law and the three-loop autopilot, as shown in Figure 15 . In this case, the objective was to compare the miss distance between the developed integrated method and the conventional guidance and control one regarding the time lag between the loops. As a result, acceleration was given first to the thruster and then to the three-loop autopilot in the same manner as in the proposed method. In this scenario, a non-ideal seeker was also utilized, as in case 2. No uncertainty was introduced into the problem to reduce the effect of the observer, and the only disturbance was the drag acceleration of the target. Case 3 possessed the same engagement parameters as Case 1. The three-loop control law is as follows: where and are interceptor real and command acceleration in pitch plane, , , denote the control parameters and design as , , . Each point was simulated five times to account for the noise in the seeker measurement, and the mean miss distance at that point was then reported. As shown in Figs. 16 and 17 , the performance of the developed integrated guidance and control method (in identical situations like thruster existence and no uncertainty) is superior to that of the conventional method, despite the time lag existence in both methods. It is due to the consideration of the interceptor’s dynamics in the calculation of AOA command, and required less time lag in the proposed method. This result validates the claim made in subsection 3.1 As can be seen, larger ZEM’s and higher altitudes result in greater increase in miss distance. In addition, the asymmetry of the miss distance around the ZEM is caused by the ballistic target’s drag acceleration. Case 4 In the following explanation, to show the superiority of this method over SMC ones, a comparison with Non-singular Terminal Sliding Mode (NTSM) guidance law, as the main basis of many new research, has been made. To make the comparison fair, this method has been used due to the point that it is developed for the guidance loop against maneuvering targets. We can convert its output acceleration to the and continue the rest of the process as before. Also, the use of thruster, and are also applied like the proposed method. As a result, the change is only in the way of calculating the and estimating the target maneuver. The NTSM guidance law which is taken from 35 is presented as follows: where is the guidance command, is the desired line-of-sight angle, M=500, =10 and a=5/3. The simulation is done for Case 2 scenario (in the presence of seeker noise). Figure 18 illustrates the difference between the paths of proposed IGC and NTSM method. Also, the miss distance of proposed method is 0.3 m (like Case 2) and the miss distance of NTSM method is 18.4 m. Figure 19 depicts the variation in LOS rate, AOA and pitch rate. As mentioned in the introduction section, guidance laws based on SMC that do not have an observer to estimate the target maneuver have problems performing well in a short time. Here too, it is clear that the guidance command is saturated and has caused a drop in performance and an increase in the miss distance. Comparison between methods Using the simulation results, a qualitative comparison can be made between the proposed method, conventional and NTSM ones. In summary, the results of this comparison are shown in Table 4 .

The present paper proposes a novel integrated guidance and control (IGC) method for engaging with high-speed targets such as ballistic projectiles. considering an extreme short period of terminal engagement due to high relative velocity between target and interceptor, it is particularly important for IGC law to show desirable performance in the presence of various uncertainties (e.g. variation in aerodynamic coefficients) and disturbances (e.g. target maneuver and drag). This article extends the ICG law for mismatched and feedback form equations based on the Active Disturbance Rejection Control (ADRC) method using the back-stepping technique and the Reduced-order Extended State Observer (RESO). The primary consideration is the application of thrusters on the center of mass as the Divert Control System (DCS), along with the daisy-chain technique for control allocation between the fins and thruster commands. Contrary to previous research, the filter and angle measurement error are modeled for the seeker as a crucial parameter to highlight the significance of the thruster. The simulation results indicate the efficiency of the developed method for near-miss or hit-to-kill engagement with tactical ballistic targets. It is shown that the thruster plays a significant role in high-altitude engagements, specifically in the presence of non-ideal seeker. Finally, using the Monte Carlo simulation, it is proved that adding inner loops to the developed technique will not remove the IGC’s advantage over the conventional approach and Non-singular Terminal Sliding Mode (NTSM) guidance law. Subject terms

Problem formulation In this section, the mathematical model of the engagement kinematics is derived. Then the nonlinear dynamic model of the interceptor with thruster is used to develop the integrated guidance and control equations in the pitch plane. As mentioned in the previous section, the IGC system is considered in the homing phase and does not affect other flight phases. Then, the control goal of the paper is described. Engagement kinematics The planar geometry of the missile and ballistic target engagement in the inertial system of - - is shown in Fig. 1 , where the missile and target are denoted by M and T , respectively. and are target and missile velocities and and are flight path angles, respectively. Also and are normal accelerations. In addition, R is the relative distance, and is the line-of-sight (LOS) angle. The missile-target relative motion kinematic model is established as 22 : where is assumed as constant, i.e., , and differentiating (1- ) with respect to time and considering (1- )-(1- ), yield: Remark 1 The term is the acceleration perpendicular to the target’s line-of-sight. Tactical ballistic targets generally do not have course correction maneuvers or escape maneuvers in the reentry phase, but even these targets can have accelerations due to the presence of fin installation errors 24 . Remark 2 The term is not considered in most studies in the terminal phase due to low drag, but it should be considered for ballistic targets in equations because of high velocity and high drag. For example, it can be seen in the simulation section that the speed of a tactical ballistic target in the final phase is about 2.7 times that of the interceptor, as a result, its drag force will be about 8 times, and it will be important to consider the drag acceleration even in a short time. However, if the velocity vector of these targets is not in line with the line-of-sight (which is not in most scenarios), a fraction of drag acceleration perpendicular to LOS will be projected, which makes complex near-miss engagement. For this reason, estimating this acceleration and its compensation in the interceptor guidance, significantly affects engagement success. In this study, the observer, estimates both acceleration terms perpendicular to LOS (due to maneuver and drag), which is used in the IGC law. Nonlinear dynamic model The nonlinear model of the interceptor with ACS thruster has been presented in 25 . The model of the interceptor with tail fin and DCS thrusters (as shown in Fig. 2 ) is derived based on this model: where is the angle of attack, denotes the pitch rate, is the pitch angle, m , are the missile mass and pitch moment of inertia, and , denote the lift force and the pitch moment, respectively. The corresponding expressions are: where q is the dynamic pressure, S is the aerodynamic reference area, d is the reference length, is the thruster force, and are the lift force derivatives with respect to and . Also is the deflection angle for pitch control and , and are the pitch moment derivatives with respect to , and , respectively. Considering Eqs. ( 2 ) to ( 4 ) and defining , , , , , the integrated model can be achieved as follows: where and Assumption 1 The term in Eq. ( 4 ) is neglected because of the low lift of control tails compared to the body lift. Assumption 2 Both the actuator and thruster have the bounds of and , because of the physical limitation of the actuator and pressure limitation in the gas generator of the thruster. Assumption 3 In the terminal phase of engagement, (by using the seeker data) and R (by using the fusion of seeker and radar data) are provided with acceptable accuracy. Also, the condition of successful engagement is that R is in the range of [0.1, 1] m. Remark 3 In most references such as 18 , 22 , the term is not considered in Eq. ( 6 ). This does not seem right because the equation is derived with the assumption of acceleration being perpendicular to the velocity vector, and the acceleration due to and thruster are perpendicular to the body x -axis. It is observed that the system of Eq. ( 5 ) is in the feedback form with mismatched uncertainty. These uncertainties are variable with time and functions of state variables. Also, is the acceleration perpendicular to the target s LOS due to drag or maneuver, while and represent the time-varying perturbations caused by variations of aerodynamic parameters and external disturbances . Thruster description Thrusters are typically used in two situations: (a) Attitude Control System (ACS) thruster with less force at a specific distance from the center of mass; This case aims to apply the torque produced by thrusters and rapid rotation of the interceptor to capture the Angle Of Attack (AOA) and, as a result, produce lift force to increase acceleration in the desired direction. In this method, by increasing the altitude, air density decreases and both affect the interceptor’s acceleration. (b) DCS thruster with a greater center of mass force; This case aims to generate acceleration in the desired direction for a given period of time. In this class, the thruster acceleration will be independent of altitude. The interceptor with a thruster with four nozzles and the maximum force of T on the center of mass can generate an acceleration in a square area by controlling the valves of each nozzle, as shown in Fig. 3 . In this paper, it is assumed that the thruster computer can generate the arbitrary controller force in the pitch plane by changing the valves of its nozzle with good resolution in place, and there is no need for the discretization of the controller’s output command. The operation time of a thruster is 1 s before the intercept, and it is activated by estimating . IGC law design objective In this study, the goal is to design an IGC law such that, subject to system (5), a miss distance less than 1 m is achieved against tactical ballistic target. For this purpose, the IGC law should guarantee that the state variable is kept close to zero at the end of the terminal phase. Also, one should not be concerned about disturbance becoming infinity because, as the distance between the interceptor and target decreases to lower than 0.1 m, the simulation is stopped, and destruction occurs in this situation in reality. IGC law design with reduced order ESO It is not possible to apply the classical ADRC structure so that all uncertainties are estimated using an ESO filter and then the estimated values are compensated to nullify LOS rate. The existence of mismatched uncertainty and the feedback form structure of the interceptor equation with two inputs, which differs fundamentally from the classical ADRC, are the root causes of this issue. Therefore, a novel concept is employed to deal with these equations by employing the ADRC concept and the framework for dealing with mismatched equations. The observer is created for each category of equations in this technique, which is identical to the ones used in 18 , 20 . The IGC law in this study is designed using the back-stepping structure and the RESO observer. Back-stepping based IGC law A seeker is used to measure the relative parameters of the target and the interceptor. The input of equations defined in the first stage is . Below are three typical modes: The thruster input is considered zero in this mode and the control structure works to achieve the desired deflection since the thruster activation time corresponding to has not yet occurred. In this mode, the first Eq. in ( 5 ) changes as follows: . The thruster is activated. In this instance, the thruster is initially responsible for providing (noting that the thruster time constant is less than fin actuator’s one). The deflection command is regarded as zero and the controller structure modifies the thruster force and direction until approaches the required value if the computed thrust force is less than the maximum thrust value. The thruster is activated and the needed thrust force exceeds the thruster’s maximum force. In this situation, the angle of attack, which is determined by , is responsible for supplying the necessary acceleration difference. The required values to compute the reference command of angular velocity are obtained by sending through a differentiation filter. Subsequently, the necessary deflection command is given using and . All these phases assume that the controller has access to (the estimation of ) instead of , which is the output of RESO filter with appropriate bandwidth. In the following, the design of the IGC law for the first mode is completely done, and then with the addition of the thruster and use of the daisy chain method, this process is developed for the third mode. The second mode does not require revision because it is only a particular instance of the third mode. Step1 The purpose of IGC is zeroing LOS rate ( ), that is, . Equation ( 8 ) shows the expected dynamics to meet this demand: where is the controller coefficient and indicates the convergence speed to the origin. The first dynamic surface is defined as: Differentiating ( 9 ) with respect to time provides: where is the estimation of . The dynamics ( 8 ) may then be obtained by determining as a virtual command in the form of ( 11 ) using the inverse dynamics method. The objective of the second phase is to choose such that the the state, or the angle of attack ( ), tracks the command value. This calls for altering the dynamics of the angle of attack, as follows: where Eq. ( 10 ) is used to calculate . A differentiator filter is used to compute as follows: where is the bandwidth of the derivative filter and is the Laplace notation. Filter ( 13 ) is used to prevent the explosion of complexity in the analytical calculation. For this computation, there are different approaches, such as using the command filter 26 . Due to the short duration of the final phase and the presence of a thruster, it is not required to employ these methodologies in this study. By defining the second dynamic surface as: and differentiating it with respect to time, we have: where is the estimation of . Now, to achieve dynamics in ( 12 ), it is suggested to choose the virtual command as follows: The controller design without thruster mode is completed after the pitch rate achieves the command value utilizing the suitable elevator. For this reason, the third dynamic surface was defined in the final step as follows: By differentiating ( 17 ) with respect to time, together with ( 14 ) yields: where is the estimation of . Stable dynamics ( 20 ) is generated to send to by passing through ( 13 ) and computing the elevator input as follows: The design created for the first mode is now modified by using the thruster with daisy chain method. The first option in this situation will be to zero the LOS rate by thruster. Since it has a shorter time constant than the electromechanical actuator and does not encounter the rotation rate limit of electromechanical actuators. Then, the difference between the maximum thruster acceleration and the command acceleration is provided by the angle of attack . Consequently, Eqs. ( 10 ) and ( 11 ) are converted to forms ( 21 ) and ( 22 ), respectively: From this stage on, the definition of is continued as previous. The angle of attack command and therefore the elevator command will be zero if the necessary acceleration is less than the thruster’s maximum acceleration. It is worth noting that in this disturbance rejection-based control structure, functions as the guidance loop’s output while acts as the controller’s inner loop command. As mentioned in reference 22 , when this control structure is used, the advantage of IGC compared to conventional guidance and control is lost. However, it should be noted in this structure, the dynamics of the interceptor is still considered in the calculation of the guidance command. This differs from the conventional separate designs for the guidance and control loops, which take the dynamics of the interceptor as a point mass in guidance loop. This issue performs better in high-speed engagement geometry changes. Then, the inherent problem in the classical IGC approach should be considered, which ignores the interceptor’s inherent longitudinal and angular dynamics difference, as was mentioned in 27 , and led to the development of the partial IGC approach with a structure similar to that used in this study. Observer design It was assumed in the previous part that is provided as the estimator’s output. A variety of concepts can be applied while designing the estimator, including ESO, Super twisting ESO, Reduced-order ESO, and high-order nonlinear filters. Each of these approaches has its specific benefit; for example, using super-twisting ESO can ensure the filter’s convergence in a finite-time 19 or using high-order nonlinear filters can improve performance when predicting high-frequency disturbances. The RESO estimator, which according to 18 has a greater bandwidth than the ESO, is utilized in this study because of the high speed terminal phase and the lack of high-frequency disturbances. This section reviews how to implement this approach by designing reduced-order ESO as referred in 28 . Since is present in the dynamics of all three state variables, an ESO estimator like the classical ADRC cannot be used to estimate the total disturbances; instead, this filter needs to be created independently for each state variable. Assumption 4 The constant positive values , , exist for uncertainty of the system ( 5 ) such that , , meets , , i.e. the disturbances and their derivatives are all bounded. For example, concerning the guidance loop, RESO is as follows: where , and represent the filter variable, filter bandwidth, and estimated disturbances in the guidance loop, respectively. In addition, the same procedure is repeated for estimating and , as in Eqs. ( 24 ) and ( 25 ) below: As increases, the observer bandwidth also increases. Practically, the bandwidth cannot be extended to the intended level due to actuator and sensor data acquisition delays, as well as noise on the sensors. Additionally, the estimation error can be decreased by raising . Theorem 1 states the relationship between estimation error and values. Theorem 1 Considering the observer designed in ( 23 ) to ( 25 ) and Assumption 4 for system ( 5 ), we have: where . Proof This theorem has been proved in detail in 18 . It can also be proved using comparison lemma. By using the comparison lemma, the following inequality is obtained: such that the error of observer is bounded for all . Similarly, convergence of other RESO observers (which estimate and ) can be proved. Remark 4 It should be emphasized that the estimation error will be asymptotically stable by utilizing the observer ( 23 ) and adequate adjustment of if the magnitude of disturbance is constant, i.e. . Gain tuning The bandwidth of the RESO is equal to . As increases, the speed of disturbance estimation also increases. Due to the noise of the sensors and also the delay in the system, this value cannot be increased arbitrarily in practice. Controller gains ( , and ), indicate the speed of convergence for LOS rate and tracking for and q . Also, due to the use of a cascade structure in the control law, the bandwidth of the inner loop must be faster than the middle loop and the outer loop, in order to achieve the desired performance. Here too, the bandwidth of the actuator in practice, makes it impossible to speed up the tracking as much as desired. With these explanations, the following method can be used for the initial gains tuning. First, gain (which represents the bandwidth of the inner loop) is chosen a little less than the bandwidth of the actuator, and then we choose the bandwidth of the middle and outer loops, respectively, about 2 to 5 times smaller than the previous loop. After that, we should determine the observer’s gains. In this regard, the observer gain related to each loop can be selected from 2 to 10 times its control bandwidth, depending on the rate of disturbance changes in that loop. It should be kept in mind that the lack of a sufficient difference between the bandwidth of the inner loop and the actuator or the outer loops can lead to instability or bad tracking. Stability analysis of the closed-loop system In this section, the stability of the closed loop system is investigated using Lyapunov theorem. Theorem 2 Consider the IGC system ( 5 ), if Assumption 4 and Theorem 1 are satisfied under the condition that the control gain and observer bandwidth satisfy , , , there exists a positive value for such that following nonlinear IGC law ( 29 ) combined with the RESO estimator can guarantee that the tracking error converges to the origin asymptotically. Proof In the first step, consider the tracking error as follows: Consider the following Lyapunov function: is defined by, Matrix is defined by, By assuming , , and as positive gains which satisfy following inequalities, it can be deduced that matrix is negative-definite, Keeping in mind, the statement that a matrix is positive (negative) definite if and only if all of its principal minors are positive (negative), the latter is concluded. Now the gains can be tuned as follows: Note that c and r can be set arbitrarily. By using such gains, it can be verified easily that satisfies following matrix inequality: Hence, is bounded, and its upper bound is given by, So ultimate bound of can be computed as follows, Seeker filter design Guidance filter plays a crucial role in overall performance of an air defense system 29 . It is well-known that various error sources of onboard seeker, such as low sampling rate besides time-delayed and noisy measurements form the main challenges to achieve a hit-to-kill performance. However, according to authors’ knowledge, all existing IGC schemes have assumed an almost ideal guidance filter to utilize true LOS rate value as the measured variable. Keeping this in mind, a two-stage guidance filter is employed in this study to account for exact known engagement kinematics along with an accurate model of seeker error sources. The first filter stage is inspired by 30 which is briefly explained in what follows. Assume the update rate and measurement delay of seeker to be and , respectively. Furthermore, the pointing angle and attributed LOS rate are expressed by and , respectively. The following filter dynamics in pitch plane is given: in which r ( t ) denotes the inertial angular velocity of inner gimbal measured by gimbal’s gyroscope. The measurement equation indicates that pointing angle is directly measured by seeker. A classical discrete time filter with gains of and is applied to ( 40 ) as follows: where and Utilizing the filter dynamics in ( 41 ) assures the independence of estimated LOS rates from the interceptor’s body angular motions as an important guidance filter performance index 29 . Following straightforward calculations, one can derive the estimated LOS rate dynamic as follows Denoting the standard deviation of pointing angle gaussian noise by , according to ( 44 ), the standard deviation of LOS rate estimation is achieved as follows: and , are determined in a way which the closed-loop poles of ( 44 ) correspond to a standard second order continuous characteristic equation with natural frequency and damping ratio . It is nice to mention that accounting for range-dependent measurement noise for an active seeker, shall preserve the following equality where is the standard deviation of seeker angle measurement error which is a function of signal to noise ratio (SNR) and seeker beam width. Also, is the distance between interceptor and target in the beginning of endgame phase. It is determined according to ( 46 ) the decrease of noise level as the relative range goes toward zero. Remark 5 The main idea behind this section, is to obtain a reasonable model to evaluate the effects of the seeker filter’s bandwidth and sensor’s measurement noise on proposed guidance law performance, as two significant practical issues. Evidently one can use more sophisticated filter schemes such as those introduced in 29 , 31 , 32 to be implemented on seeker’s computer. After that, there is a second filter ( 23 ) in the interceptor’s computer that uses this LOS rate as input to estimate the target’s acceleration and uncertainty due to the aerodynamic coefficients. Concluding remarks This study proposed novel integrated guidance and control method for a dual-controlled interceptor against a tactical ballistic target with back-stepping method based on ADRC structure and daisy-chain procedure for control allocation. The developed method was able to engage with a target at speed of 2500 m/s at an altitude of 13 km in the presence of various disturbances such as drag and high target maneuvering as well as aerodynamic uncertainties with desired miss distance. System stability and asymptotically convergence of tracking error are guaranteed based on the Lyapunov theory. The simulation results indicated, As the engagement height rises, due to an increase in the interceptor’s time constant and a decrease in the efficiency of the fins, the thruster plays a greater role in the near-miss engagement. In addition, obtaining a low miss distance without a thruster is impossible if a non-ideal seeker, with filter and measurement noise, is used due to the restricted rate of the fin actuator, the high interceptor time constant and the seeker error at the beginning of the engagement. The contour of the miss distance of various ZEM’s at different altitudes for the conventional method and the proposed one shows that there is a significant improvement in the miss distance in the same conditions.That is the point, because hit-to-kill or near-miss interception against tactical ballistic, is very important for air defense system. Also, the superiority of the proposed method over NTSM guidance law has been shown. In short, the advantage of this method compared to other IGC methods is to simultaneously deal with uncertainties and disturbances without knowing about them, along with achieving proper control performance. This advantage makes it possible to achieve a hit-to-kill scenario in intercepting a ballistic target by using the DCS thruster. Also, the negative point is the use of the Cascade control structure, which causes the bandwidth of each loop to be limited for the proper operation of the next one. Considering the seeker measurement and actuator delay as an input-output delay in IGC law, using Kalman filter for intercepting a weaving target and integrating seeker filter with IGC law are some ideas for extension of this study in future works.

Author contributions A.C. (First Author): Problem formulation, simulation and writing first draft. A.N. (Second Author): Supervision and editing. F.F.S. (Corresponding author): editing and submitting. Data availability All data for reproduction of the manuscript results is available in the ’simulation’ section in text. Any additional data is available upon request. For this purpose, contact alichitsaz@aut.ac.ir Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1298

oa_package/27/cb/PMC10788350.tar.gz

PMC10788351

38221547

Introduction Fe 3 O 4 superparamagnetic nanoparticles (SPMNP) have significant potential applications in various science branches including drug delivery 1 rheological enhancement of fluids 2 , heat generation in magnetic field 3 , 4 and contrast enhancement in magnetic resonance imaging 5 . Magnetic nanoparticles (MNP) may be modulated by external magnetic fields to penetrate directly into the tumor, making them suitable drug carriers in medical applications and specifically drugs delivery. It has been demonstrated that the sizes, shapes, and surface coatings of MNPs have an important impact in the delivery of drugs in tumor treatment. MNPs having a high surface-to-volume ratio and porosity are favorable for drug delivery systems 6 . Magnetorheological behaviors in fluids are caused by dispersing magnetic nanoparticles (transition metal magnetic oxides) with polymer covering to guarantee stable dispersion in fluids. The formation of a magnetic field in magnetorheological fluids results in the formation of a chain structure of nanoparticles in a relatively short period, causing the viscosity of the fluid to alter. When the magnetic field is removed, these chains vanish, causing the rheological behavior to revert to its original condition 7 . Recently, many efforts have been made to explore the heating of magnetic nanoparticle-containing dispersions in an alternating magnetic field as well as the prevailing process and it has shown that relaxation mechanisms generate more heat than hysteresis mechanisms 8 . Furthermore, due to their biocompatibility, superior magnetic characteristics, and ability to functionalize their surfaces with diverse ligands for molecular MRI, iron oxide nanoparticles are being widely researched as contrast agents for magnetic resonance imaging (MRI) 9 . One of the suitable methods for synthesis of these nanoparticles is co-precipitation because in this method the effective parameters can be controlled more easily and the synthesis conditions are not severe 10 . Number of parameters must be controlled in co-precipitation method to obtain repeatable results, including Fe 3+ to Fe 2+ ratio, reaction temperature, final pH, Fe salts type (sulfate or chloride etc., ...), base type (NH 4 OH or NaOH etc.,...), mixing rate, sequence of addition of reactants and using or not using inert gas for oxidation prevention during synthesis 11 – 19 . Surface modification of the nanoparticles of transient metals oxides (especially Fe) is essential to distribute them evenly in target solution. Moreover, in medical applications of magnetite nanoparticles, surface modification of Fe 3 O 4 nanoparticles is crucial in making them biocompatible 20 , so different agents such as polymeric materials, inorganic materials and surfactants have been used in the researches for surface modification of these nanoparticles 21 – 24 . Several studies have recently reported on the modification of the surface of magnetite nanoparticles and improvement of their properties for various applications, including: collection of spilled oils on the earth’s surface 25 , removal of coomassie brilliant blue-R250 dye (CBB) from aqueous solutions 26 , dye absorption 27 , inhibiting hen egg-white lysozyme (HEWL) fibrillization and destroying mature fibrils 28 . Polyamines 25 , multifunctional pyridinium ionic liquids 26 , citric acid 28 , trisodium citrate 28 , dopamine conjugates 29 , oleic acid and polyacrylic acid 30 were utilized in these studies to modify the surface of nanoparticles. Using different agents to modify the surface of nanoparticles yields unique properties, such as the ability to reuse magnetite nanoparticles modified with polyamines 25 , increasing the absorption of coomassie brilliant blue-R250 dye (CBB) from aqueous solutions from 84.4 mg/g in case of nanoparticles without surface modification to more than 700 mg/g in case of surface modified magnetite nanoparticles 26 , The increase in dye absorption from 60% for nanoparticles without surface modification to 98% for those modified with citric acid and the effect on their anti-amyloid potential 27 , improving bioreactivity with dopamine conjugates 29 , and the increase in dispersibility in aqueous environments by surface modification using polyacrylic acid 30 , the significantly increased stability in saline water and the creation of hydrophobic properties with surface modification using oleic acid 31 are all examples of these outcomes. As mentioned earlier heat production in magnetic field is one of the applications of superparamagnetic nanoparticles. The produced heat can be used for beginning desired chemical reactions or enhancing physical features such as viscosity in the carrier fluid. The heat production by applying magnetic field on superparamagnetic nanoparticles has been studied in many researches 32 – 40 . From the standpoint of the high efficacy of hyperthermia, it is crucial to accurately estimate the quantity of heat produced. It is also vital to minimize the usage of animals in laboratory stages. By dispersing superparamagnetic particles in an environment of glycerol and agarose gel, which has characteristics similar to those of body tissues, and measuring the temperature with optical fiber thermometers, the pseudo-tumor environment system (P-TES) method has been able to produce results with an acceptable level of accuracy 41 . It has been reported that the synthesis of desirable materials, such as nano catalysts, can be aided by the quick and simultaneous selective heating by the magnetic field. Comparing magnetic heating to other heating techniques has revealed that magnetic heating performs significantly better in several laboratory experiments. This is as magnetic heating causes the material’s surface temperature to rise more quickly 42 . Materials suitable for use in heating with the help of magnetic field are not limited to one material and different chemical compounds have also been taken into consideration in different researches according to the environment used. For instance, in different environments, the amorphous composition of FeZrB has demonstrated a faster magnetic heating rate compared to Fe 3 O 4 , which has resulted in a substantial decrease in the time needed for the ambient temperature to reach a degree that is acceptable for hyperthermia. SAR in ferrite nanoparticles is around 27.2 W/g, while SAR in FeZrB nanoparticles is approximately 65 W/g 43 . Due to their stability, adequate heat absorption, good conduction coefficient, and magnetic heating, nanofluids containing Fe 3 O 4 .H 2 O are appropriate for application in solar collectors, heat exchangers, and automobile radiators 44 . The reported specific absorption rate (SAR) values in magnetic heating tests varies in different researches for so many reasons. One of the most major reasons for the uncertainty in determining the SAR value is the lack of a proper setup for measuring the quantity of heat produced. The pulse-heating approach in adiabatic settings has provided pretty accurate SAR data, but its disadvantage is the necessity for an advanced setup 45 . In addition to effect of frequency and magnetic field strength that have been formulated in Rosensweig’s research 46 the effect of nanofluid viscosity and size distribution of nanoparticles are important parameters that change the dominant mechanism of nanoparticles heat generation in AC magnetic field and so the reported results. It should be noted that the formula presented by Rosensweig is only valid for a range of frequency and intensity of the magnetic field in which linear response regime is established. Experimental research on the behavior of nanoparticles in greater field intensities and frequencies has shown that the quantity of heat produced is constant once it reaches the saturation level and does not change with increasing field intensity 47 . Determining the amount of heat released in the hyperthermia process is challenging and variable results have been mentioned in different studies. The two main methods for this work are calorimetry and AC magnetometry. It has been shown that if the frequency and intensity of the magnetic field are in the linear response regime, then the obtained results from these two methods are almost equal to each other 48 . Considering the temperature drop caused by the transfer of energy to the environment is also one of the measures used to reduce the error of SAR calculations in calorimetric methods. For this purpose, the corrected slope technique is employed 49 . According to the formulas that have been presented in the literature the Neel relaxation time and Brownian relaxation time of a single nanoparticle are functions of nanoparticle size; therefore, in constant mean size but different size distribution of the nanoparticles, the dominant mechanism of heat generation in nanofluid may change from Neel to Brownian and so diverse SAR results has been reported in literature. Based on the formulations, increasing the viscosity of the nanofluid results in Brownian relaxation time increase and making the Neel mechanism as the dominant heating mechanism. In different scientific fields such as hyperthermia in body tissues, polymer processing or petroleum industry the carrier fluid is viscous and so the Brownian relaxation time to Neel relaxation time ratio is in the order of 10 3 or more 3 . It is noteworthy to mention that particles without a hysteresis loop generate heat only through Neel and Brownian relaxations, and in the event that one does, calculations pertaining to determining the area of the loop and the heat generated by it must also be accounted for. Additionally, even superparamagnetic particles exhibit a hysteresis loop at a temperature below the blocking temperature and the coercivity of these nanoparticles become zero above the blocking temperature 50 . Consequently, the theoretical computations of the generated heat should take into account the hysteresis loop calculations; however, it should also be noted that the measurements obtained during the vibrating sample magnetometry (VSM) testing indicate the static loop, but there is less chance of aggregation formation and less interaction between the particles when they are distributed in a fluid (in calorimetry tests) comparing to VSM test conditions and taking into account variations in the time constant, particle size, interactions 51 , 52 , ability to respond to an applied magnetic field 53 , and factors influencing the blocking temperature, it is not unlikely to alter the behavior of nanoparticles and change the size of the hysteresis loop when they are being distributed in a fluid 54 . The size of the hysteresis loop, and hence the heat produced by the hysteresis loops, is also affected by the applied waveform 55 .Taking these considerations into account, all feasible options should be included in magnetic heating theoretical calculations in order to produce the most accurate results. Conducting the magnetic heating tests in a high viscous medium in order to eliminate the Brownian mechanism of heat generation and simulating the real applications condition is the aim of the current research. In order to do so the nanoparticles were evenly distributed in a viscous polymer solution to restrict the nanoparticles physical rotations in AC magnetic field and so increasing the ratio of Brownian relaxation time to Neel relaxation to more than 10 5 . In this research Magnetic Fe 3 O 4 nanoparticles were synthesized using co-precipitation method. The nanoparticles were dispersed in a polymer aqueous solution using a mechanical mixer. The viscosity of the polymer solution was high, so the effect of Neel relaxation mechanism on heating of the nanofluid containing Magnetic nanoparticles was investigated more preciously. Five different materials were used for surface modification of the magnetite nanoparticles and making them more dispersible in polymer solution. The used materials for surface modification were citric acid, ascorbic acid, Tetraethyl orthosilicate (TEOS), polyvinyl alcohol (PVA) and polyethylene glycol (PEG). Surface modified nanoparticles and bare Fe 3 O 4 nanoparticles were dispersed in polymer solution. Fourier-transform infrared spectroscopy (FTIR) was used to characterize the functional groups on the nanoparticles. Also VSM was used to investigate the magnetic properties of the nanoparticles. Nanoparticles’ heating was done in five turn coil magnetic induction heating device with variable magnetic field strength and the effect of surface modification, magnetic field strength and nanoparticles’ concentration on the specific absorption rate (SAR) and final temperature of polymeric solution was investigated.

Material and method Material Ferric chloride hexahydrate (FeCl 3 .6H 2 O, Titrachem, Iran), ferrous chloride tetrahydrate, (FeCl 2 .4H 2 O, Titrachem, Iran), Ethanol (C 2 H 5 OH, Titrachem, Iran), Ammonia (NH 4 OH Titrachem, Iran), TEOS (Si(OC 2 H 5 ) 4 , Titrachem, Iran) L-Ascorbic acid (C 6 H 8 O 6 , Loba chemie, India), Citric acid (C 6 H 8 O 7 , Loba chemie, India), Polyvinyl Alcohol (PVA) (Mw = 72,000 D) [CH 2 CH(OH)] n , Merck, Germany) and Polyethylene Glycol (PEG) (Mw = 6000 D) (H(OC 2 H 4 ) n OH, Merck, Germany) without further purification were used in synthesis of surface modified nanoparticles. Co-polymer of 2-acrylamido-2-methylpropane sulfonic acid sodium salt (AMPS) and acrylamide (ACA), in powder form, under the trade name of AN125, with sulfonation degree of 25% and average molecular weight of 8 million Dalton were prepared from SNF Co. (Saint-Étienne, France) in order to prepare aqueous polymeric dispersion of nanoparticles. Synthesis of Fe 3 O 4 nanoparticles The synthesis of nanoparticles were done using the method that were used in our previous work with a little modification 56 . Briefly, a homogeneous solution of FeCl 3 .6H 2 O and FeCl 2 .4H 2 O with molar ratio of 2:1 was prepared in 250 ml of deionized water. The temperature was raised to 80 °C and N 2 purging was done in order to eliminate the O 2 gas in the solution and prohibit the unwanted oxidation of Fe 3 O 4 to γ-Fe 2 O 3 57 . 80 ml NH 4 OH solution (25 v/v %) was added to the solution drop wise in 60 min meanwhile the solution was stirring vigorously. In order to control the nanoparticles mean size and size distribution, the temperature and pH of the solution was being controlled during the synthesis continuously. Finally the reaction was allowed to be continued for another 60 min while the solution medium was being stirred vigorously and refluxed. The final pH of the solution was about 12. The nanoparticles were washed and decanted several times using deionized water and a 0.4T permanent magnet. The washing procedure was continued until the final decanted water became neutral using a PH meter, at this step the nanoparticles were maintained in degased (using N 2 ) deionized water for further usage. Surface modification of the Fe 3 O 4 nanoparticles The surface modification of the nanoparticles was done similar to the method used in our previous work 56 with a little modification. Briefly, the surface modification agent was added to the reaction medium right after the Fe 3 O 4 synthesis reaction completion and without washing or drying the nanoparticles. The amount of surface modification agent was 40 wt% of stoichiometric produced Fe 3 O 4 . The surface modification was allowed to continue for 6 h. The surface modification using TEOS was a little different. In this method ethanol and NH 4 OH was added to the produced Fe 3 O 4 dispersion to enhance the TEOS hydrolysis reaction (Eq. 1 ). The stochiometric amount of TEOS was dissolved in 100 ml of ethanol and the solution was added drop wise while the reaction medium was being stirred vigorously and refluxed. TEOS hydrolyze through the Eq. 1 and produces SiO 2 that cover the surface of Fe 3 O 4 nanoparticles 23 . The molecular structure of the substances used in this research are shown in Fig. 1 . The difference between electronegativity of oxygen and iron is 1.61 and the bonding is polar, so dipole–dipole interaction can be expected between polar molecules and Fe or O atoms in Fe 3 O 4 crystal. The ascorbic acid and citric acid both have OH group which loose H + in water and so makes them suitable to be attached to the surface of Fe 3 O 4 crystal through Fe atoms. On the other hand, PVA has an OH group in each repeating group and so a strong enough interaction can be expected between PVA molecule and Fe 3 O 4 nanoparticle’s crystal. In case of PEG there is only one OH group at one end of each PEG molecule so the interaction well be weak, also there is an ether group in each repeating unit but its’ not polar enough to expect a strong interaction between the PEG molecule and Fe 3 O 4 crystal. Finally, in case of SiO 2 it should be mentioned that SiO 2 just coats the surface of Fe 3 O 4 particles and it is not a surface modification agent. Characterization tests FTIR (frontier spectrometer, PerkinElmer) was used to characterize the functional groups on the surface of the nanoparticles. The spectrum was taken in the range of 400 to 4000 cm –1 . VSM (vibrating sample magnetometer) (MDKB–Co, IRAN) was used for magnetic characterization of the synthesized magnetic nanoparticles and determining the saturation magnetization and magnetic susceptibility 58 of the nanoparticles. The magnetization results was used to determine the magnetic core size (assuming log normal distribution) of the nanoparticles using the Eq. ( 2 ) 59 , 60 In the above equation D m is the magnetic core diameter of the nanoparticles, is the permeability of the free space, M d is the domain magnetization of the nanoparticles, is the initial susceptibility that will be determined using the slope of the M vs H diagram at H → 0 and finally H 0 will be determined by plotting the M vs 1/H at high external field where the diagram become linear, the intercept on the M axis is the H 0 61 . Theoretical determination of heat production in magnetic field The energy produced by nanoparticles in a magnetic field is divided into three components: eddy current loss, hysteresis loss, and relaxation loss. For the theoretical measurement of the quantity of heat produced, many models such as the Rayleigh model, the Stoner-Wohlfarth model based theories (SWMBT), and the linear response model 62 have been proposed based on the applicable conditions. To determine the application scope of each model, two dimensionless parameters and (= are used. In case ξ < 1, the entire heat generation may be assigned to the loss mechanism via relaxation 63 , and thus Rosensweig’s model 46 can be utilized. In trying to formulate the heat production in magnetic field Rosensweig 46 presented the Eq. ( 3 ) for the amount of the produced heat in ferrofluids in AC magnetic field: In the above equation is the permeability of free space ( , is the equilibrium susceptibility, H 0 is the magnetic field amplitude (A/m), is the magnetic field frequency (Hz) and is the effective time constant that is determined using Eq. ( 4 ) 61 : is the Neel relaxation time and is the Brownian relaxation time. Neel relaxation is attributed to alignment of the magnetic moment of the nanoparticle with the magnetic field without rotating the nanoparticle itself that results in heat production in the nanoparticle and so nanofluids 61 , on the other hand at the Brownian relaxation the nanoparticle rotates with the magnetic field and produces heat due to friction between nanoparticle and the fluid 61 . and are determined by Eqs. ( 5 ) and ( 6 ) 5 : In the above equations is the pre-exponential time constant, and variable amounts has been reported for it in literature between 10 –7 and 10 –13 , in this research 3 × 10 –9 will be used according to Berkov et al. 64 . K is the volume anisotropy constant (J.m –3 ) and for bulk magnetite is approximately 10 4 J.m -3 5 , 58 , 65 , 66 while the measurements showed that due to broken symmetry at the surface of the nanoparticles this parameter can increase up to 2.5 × 10 4 J.m –3 in nanoparticles 67 . V is the volume of the magnetic core (m 3 ), k is the Boltzmann’s constant (1.3806503 × 10 –23 m 2 kg s –2 K –1 ), T is the temperature, is the viscosity of the ferrofluids and r h is the hydrodynamic radius of the nanoparticles. According to Eq. ( 4 ) in case of existing one or more orders of magnitudes difference between and the lower one will be a good estimate of the τ. As stated earlier is the equilibrium susceptibility and is determined using Langevin equation 46 as follow; At the Eq. ( 7 ) is the initial susceptibility and determined using the Eq. ( 8 ); is defined as , is the domain magnetization of a suspended particle and defined as and finally is the volume fraction solids 46 . The use of equilibrium susceptibility in cases where the field is alternating is somewhat questionable, and Rosensweig has not specified exactly whether the Langevin parameter should be determined using the peak amplitude of the alternating field or another value should be considered. But in research related to this matter, peak amplitude has been used and accurate answers have been obtained 68 . In order to determine the theoretical SAR values at first the Neel relaxation time and Brownian relaxation time must be measured and in order to determine the Brownian relaxation time constant of the nanoparticles in ferrofluid, the viscosity of polymer solution must be measured. The viscosity of the polymer solutions containing the nanoparticles was measured using QC viscometer (Anton Paar Company) as our previous work 56 . The polymer is shear thinning 56 and as the solutions were stationary in heating test so the viscosity was determined at very low shear rate (0.1 1/s) to accurately estimate the viscosity of the stationary solution. Furthermore as the solution temperature rises during the heating tests, the viscosity was determined at different temperature between 20 °C and 90 °C. Experimental SAR measurement and final temperature An AC magnetic field producer (LABA, iHT-1000W, NATSYCO) was used to conduct the heating tests. The 1 wt% polymer solution was prepared in order to obtain a viscous solution. Nanoparticles test concentrations was 20,000 ppm and 10,000 ppm, test frequency was about 100 kHz and magnetic field intensities was 8 kA/m, 10kA/m and 12 kA/m. The temperature was measured with an alcohol thermometer with an accuracy of 0.1 °C. The experimental specific absorption rate (SAR) values were determined using Eq. ( 9 ) as follow 3 : The amount of was determined at the beginning of the test when this variable was maximum, and the heat flow to environment was at the lowest possible amount. is the weight fraction of nanoparticles in polymer solution. The specific heat capacity of dispersed nanoparticles in polymer solution was assumed to be equal to water specific heat capacity because of low concentration of the polymer and nanoparticles. The heating tests were continued until no temperature change occurred in the solutions and final temperature of the solutions were determined. The effect of surface modification, magnetic field intensity and nanoparticles concentration on the SAR and final temperature was investigated. A schematic drawing of the heating test set up and a picture of the AC magnetic field device is showed in Fig. 2 .

Results and discussion Nanoparticles’ characterization The FTIR test results are shown in Fig. 3 , and the peaks were characterized in Table 1 . The common peaks in all spectrums (570 cm –1 and 3300 cm –1 ) belongs to Fe–O (Fe 3 O 4 ) and O–H (H 2 O). H 2 O not only absorbs to the surface of the Fe 3 O 4 molecule, but also all the surface modification agents that has been used in this project, except SiO 2 , have O–H in their structure and so this peak belongs to both surface absorbed H 2 O and the O–H in the formula. The FTIR spectra of carbonyl group in pure citric acid and ascorbic acid has absorption bond in wave number of about 1700 cm –1 but interaction with Fe–O bonding moves it to around 1600 cm –1 69 . The absorption wave number around 1080 for both Fe 3 O 4 @PVA and Fe 3 O 4 @PEG is indicative of interaction between Fe atoms in Fe 3 O 4 and C–O group of PVA and PEG (Supplementary Fig. 3 ). The results of VSM test is shown in Fig. 4 . It is obvious that all synthesized nanoparticles are not ideal superparamagnetic nanoparticles but the coercivity is low enough to expect Neel relaxation mechanism from these nanoparticles. The coercivity and saturation magnetization and the magnetic core radius of the nanoparticles using the VSM tests results and Eq. ( 2 ) are tabulated in Table 2 (Supplementary Fig. 4 ). It is worth mentioning that an ideal superparamagnetic nanoparticle should have zero coercivity 79 , but on the other hand achivieng to exactly zero coercivity is not common in literature and different low amounts has been reported in literature for this parameter. For example 189.3 Oe 80 , 7.8 Oe 81 and 41.7 Oe 82 . Comparing the results with literature shows that the results are in acceptable range and the hystersis loops are negligable 79 , 83 – 85 . However, the D m obtained from VSM results is for the magnetic core of the nanoparticles and because of surface modifications, existence of some magnetically dead layer on the surface of the magnetic core is unavoidable and so the hydrodynamic radius of the nanoparticles were greater than r m amounts 86 , 87 . It is also noteworthy that the magnetic core radius of the nanoparticles is at the same range and there is a little difference between the magnetic core radiuses of the nanoparticles that was because of robust control on the temperature, composition of the reagents and addition rate of the NH 4 OH to the reaction medium at synthesizing procedure. It should be noticed that the coercivity and size of the hysteresis loop have decreased as temperature have increased and frequency have decreased 88 – 90 , as a result, it is reasonable to assume that the coercivity value will drop during the heating experiments in the magnetic field comparing to the value observed in the VSM test. The presence of nanoparticles in the dry state might cause interactions and the creation of larger–diameter structures, resulting in hysteresis loop 91 . The effect of surface modification on stability of the dispersions was shown in Fig. 5 . As it is obvious all the surface modified samples showed no perception after 72 h except dispersion containing bare Fe 3 O 4 nanoparticles. Theoretical SAR values The viscosity of the nanofluids containing different surface modified Fe 3 O 4 nanoparticles at different temperatures are presented in Fig. 6 . As it is obvious the viscosity has decreased by increasing the temperature. The viscosity of the nanofluids are approximately equal that was predictable because the concentration of the nanoparticles was low and the polymer itself was the dominant factor in the viscosity of the nanofluids (Supplementary Fig. 6 ). The Neel relaxation time and Brownian relaxation time constants at different temperatures for nanofluids containing synthesized nanoparticles using Eqs. ( 5 ) and ( 6 ) are also shown in Fig. 6 . As it is obvious the Brownian relaxation time is much greater than Neel relaxation time in all dispersions ( ) that was predictable, because the viscosity of the nanofluids was much greater than the nanofluid systems that water or solvents with viscosity near to water was used as dispersant. Also as mentioned earlier due to surface modification of the nanoparticles and existence of magnetically dead layer on the surface of the nanoparticles the r h > r m , and as r m was used for Brownian relaxation time measurement in this manuscript, so the real Brownian time constant was greater than the measured amounts. So, it can be said with high certainty that the effective time constant is equal to Neel relaxation time constant and this parameter was used in theoretical SAR values determination. Of course, the important note that should be considered in this part is to ensure that the nanoparticles are in the linear response regime in order to be able to use Eq. ( 3 ). Linear response regime refers to a region where magnetization is linearly related to the magnetic field. Different criteria has been mentioned in order to evaluate this, first, the parameter must be smaller than 1 92 , 93 . The exact solution of the Shlimois relaxation equation has shown that the SAR value for parameter less than one equal to the SAR value obtained from the Rosensweig model 68 . For all the synthesized nanoparticles in this research, the value of the parameter was less than 0.7. Another criteria to ensure being within this region is that the range of applied field intensity must has a certain distance from the saturation intensity 94 . By reviewing the data obtained from the VSM test, it can be seen that in all samples up to 300 Oe (23.9 kA/m), a linear relation is obvious between magnetization and the intensity of the applied field, and up to this applied field, the amount of magnetization has a suitable distance from the saturation magnetization. On the other hand, the maximum applied magnetic field in the conducted experiments was equal to 12 kA/m, and therefore, considering both the first criteria and the second criteria, it can be concluded that the tests are done in the linear response regime. Furthermore it has been determined in literature that the tests performed at a field intensity of 15 kA/m and a frequency of 300 kHz on iron oxide-based nanoparticles are in the linear response region 93 . Due to the fact that in this research, the field intensity and applied frequency values have a significant distance from these values, therefore, it can be ensured that the experiments are carried out in the linear response region. In addition to the parameter, which can be used as a criterion for formula selection, it has been demonstrated that when was less than 1/f (as it was in this study), the hysteresis loop and its area were very small 52 . At coercivity of 125 Oe and remanent magnetization of 16 emu/gr, the quantity of heat resulting from the hysteresis loops is approximately 50% of the total heat resulting from the heating operation in the setup, with relaxation accounting for the remainder 95 , As a result, because the quantity of coercivity and remanent magnetization, and thus the size of the hysteresis loop were lower in this study, it can be assumed that the amount of heat created by hysteresis is significantly lower, and the majority of the heat produced is due to relaxation. Although there is no doubt that the simplification and omission of heat created by the hysteresis loop has introduced some mistakes in the computations. In other words, the numbers provided in Table 3 may be slightly higher than the values already listed, and the results produced from theoretical and experimental measurements are further apart. However, based on the explanations provided, it can be concluded that this simplification did not bring significant mistake into the calculations, and, based on the proper particle distribution, enough system insulation, and the similarity of the results of Table 4 to Table 3 , it can be estimated that the neglected value in the theoretical calculations due to this simplification was just a small fraction. Considering the frequency of the tests (100 kHz) and VSM test results, Eq. ( 3 ) was used to determine the theoretical SAR values for the nanofluids at different magnetic field amplitudes and T = 22 °C and the results are tabulated in Table 3 . As it is obvious from the results the SAR values increases by increasing the magnetic field strength. It should be noted that the theoretical amounts are watt per gram of magnetic core, so the oxidation of the magnetite surface and also the surface modification could result in this parameter decrease in real experiments that will be discussed in the next section. Another point that should be noted is that according to the Eq. ( 3 ) in an ideal suspension without interaction between nanoparticles and coagulation of them, the SAR amount is independent of the nanoparticle’s concentration. Magnetic heating results The heating results in different magnetic fields for nanofluids containing 20,000 ppm of the nanofluids are shown in Fig. 7 (Supplementary Fig. 7 ). The SAR values using Eq. ( 9 ) are given in Table 4 . It is worth mentioning due to low concentration of polymer and nanoparticles C p of the solution was considered equal to C p of water. It is also worth mentioning that ( ) in the first 60 or 80 s are used in calculating theoretical SAR. The heating test results at the beginning of the test (first 90 s of the Fig. 7 diagrams) are tabulated in Fig. 8 . The non-linearity of the graphs even in the first 60 or 80 s is visible. It is clear that assuming this petameter to be linear in the calculations of the produced heat causes errors, and it appears that shortening the time period for measuring the initial temperature changes can lead to more accurate results. However, it should be noted that shortening the measurement duration can result in errors for the following reasons: Even a small error in temperature measurement can lead to a large error in value. Because the denominator of this fraction also becomes very small. The temperature measuring device’s accuracy was just 0.1 °C, so it was impossible to discern between temperature variations brought on by various nanoparticles within a few seconds. Reduced measurement duration causes the tester’s inaccuracies during temperature measurement (in the range of a few seconds) to lead to a substantial inaccuracy in the value of , therefore it is advisable to use a relatively greater time range. Taking into account everything mentioned above, it was determined that the best time period for measuring initial temperature changes was the first 60 and 80 seconds of the tests. Comparison between the theoretical SAR values at Table 3 and experimental results in Table 4 shows that the experimental amounts are lower. In Eq. ( 3 ), it is clear that the SAR is a 2nd order function of the H. The parameter that is defined according to this functionality in various researches is intrinsic loss power (ILP), which is defined as Eq. ( 10 ) 94 . ILP is a system-independent parameter that allows direct comparison of tests performed in different laboratories. If the frequency value is constant in a system, it can be concluded that the dependence of SAR on H 2 should be linear. Therefore, this relationship was used to check the validity of experimental SAR results in terms of H 2 and comparing it with theoretical results. Although this relationship has been shown to be true up to field strengths of about 20 kA/m 68 . In case of bare Fe 3 O 4 the theoretical and experimental results per H 2 are plotted in Fig. 9 . The experimental results are a little (10–15%) less than theoretical expectations (in case of bare Fe 3 O 4 nanoparticles). Although this amount of difference is an acceptable value for an experimental experiment, several reasons can be mentioned for this amount of difference. As mentioned in the introduction, many efforts have been made so far to formulate magnetic heating and the effect of various factors on the difference in the reports provided by various researches 93 . Considering these researches as well as the conditions of the experiment conducted in our research, the following factors can be mentioned as the reasons for the deviation in the results of the experiments compared to the theoretical results 46 , 47 , 68 , 92 – 94 , 96 , 97 : Absence of complete adiabatic conditions in the system. Non-establishment of the conditions related to the linear response region due to the high intensity of the applied magnetic field. The produced nanoparticles had a hysteresis loop and were not ideal superparamagnetic nanoparticles. The low accuracy of the measuring instrument in determining at the initial moment for various reasons such as inaccuracy in temperature measurement, uncertainty in placing the probe, etc. The occurrence of aggregation, agglomeration clustering, sedimentation and to a small extent chemical reaction. Uncertainty in the measurement of magnetic field intensity. The possibility of the effect of sample aging on laboratory results. Non-uniformity of applied magnetic field. Rosensweig’s model for calculating SAR gives an upper limit of SAR and there is a possibility that the actual SAR is slightly lower. Pearson correlation coefficient was used to check the compatibility between experimental and theoretical data 97 . The value of this parameter between these two datasets is equal to 0.999. This coefficient is a measure of the linear relationship between these datasets. An approximately linear relation (with y-intercept near to zero) between SAR and H 2 is obvious in the Fig. 9 in both theoretical and experimental results and this relation is clear in Eq. ( 3 ), also is dependent on applied magnetic field and so there is a little deviation from exact linear relation. The difference between theoretical and experimental SAR amounts are less in lower magnetic field strengths that is because of the lower temperature of the dispersion in this case that is an evidence for thermal losses of the system. In case of surface modified nanoparticles the difference between theoretical and experimental SAR amounts are larger. The reason is that the theoretical SAR amounts are based on weight of magnetic portion of the nanoparticle but in experimental tests the SAR amounts are based on nanoparticles weight (magnetic core and surface modification agent). As previously mentioned in material and method section the amount of used surface modification agents were 40 wt% of the nanoparticles, also not all of the surface modification agent adhere to the surface of the nanoparticle and part of them that has been attached physically -not chemically- on the surface of the magnetite has been eliminated during the washing of the nanoparticles. Figure 9 can also be used to investigate the effect of hysteresis loops on the heating process. Since linear behavior is observed in the quantity of heat absorbed in terms of H 2 (which is a representation of ILP), the heat produced by nanoparticles in the heating measurement tests in the alternating magnetic field was in the linear response regime and so the particles acted like nanoparticles with no coercivity 98 . The effect of the surface modification on the experimental SAR of nanoparticles can also be investigated considering the changes in the amount of saturation magnetization. The decrease in the saturation magnetization of the surface modified nanoparticles compared to the bare nanoparticle is caused by the surface modification agent, which is a non-magnetic material. The ratio of saturation magnetization of surface modified nanoparticles to the saturation magnetization of bare nanoparticles, as well as the ratio of experimental SAR value of surface modified nanoparticles to the experimental SAR values of bare nanoparticles are given in the Table 5 . Except for citric acid, there is a good correlation between these two ratios in the rest of the nanoparticles. In other words, the effect of adding non-magnetic materials has appeared both in reducing saturation magnetization and in the amount of heat produced. In the case of citric acid, it should be noted that the size of nanoparticles modified with citric acid is smaller compared to other nanoparticles, which leads to a decrease in the theoretical SAR of this nanoparticle and ultimately leads to a decrease in its experimental SAR value 68 . The smaller size of citric acid coated nanoparticle is due to the very good surface modification of Fe 3 O 4 nanoparticle by this agent, which prevents any coagulation of it, and it has also been discussed in our previous paper 56 . The ratio of experimental to theoretical SAR values at different magnetic field are brought in Table 6 . The trend of decreasing the ratio by increasing the magnetic field is obvious. Another issue that should be pointed out is that the is lower in case that PVA and PEG was used for surface modification of the nanoparticles. This phenomena is due to the larger molecules of polymers comparing the molecules of SiO 2 , citric acid and ascorbic acid. In other words the in Fe 3 O 4 @ PVA and Fe 3 O 4 @ PEG was lower comparing the other three surface modification agents. The heating test results for dispersions containing 10,000 ppm of nanoparticles at magnetic field of 12 kA.m –1 is shown in Fig. 10 and experimental SAR values and final temperatures are tabulated in Table 7 (Supplementary Fig. 10 ). It is clear that experimental SAR values in case of 10,000 ppm concentration of nanoparticles was more than 20,000 ppm samples. This phenomena has been observed in similar researches, too 4 . In case of solutions with higher concentrations the coagulation possibility would increase and so the amount of experimental SAR amount would decrease by increasing the nanoparticles concentrations. For investigating the effect of surface modification agent on coagulation and agglomeration inhibition of the system the ratio of experimental SAR in case of 20,000 ppm of nanoparticles to experimental SAR in case of 10,000 ppm of nanoparticles ( in magnetic field intensity of 12 kA.m –1 are tabulated in Table 8 . It is obvious that the experimental SAR amounts decreases more by increasing the nanoparticle concentration in nanofluid samples containing Fe 3 O 4 and Fe 3 O 4 @SiO 2 . These two nanoparticles have lower hydrophilic behavior comparing other surface modified nanoparticles and so tends to agglomerate and form bigger clusters.

Results and discussion Nanoparticles’ characterization The FTIR test results are shown in Fig. 3 , and the peaks were characterized in Table 1 . The common peaks in all spectrums (570 cm –1 and 3300 cm –1 ) belongs to Fe–O (Fe 3 O 4 ) and O–H (H 2 O). H 2 O not only absorbs to the surface of the Fe 3 O 4 molecule, but also all the surface modification agents that has been used in this project, except SiO 2 , have O–H in their structure and so this peak belongs to both surface absorbed H 2 O and the O–H in the formula. The FTIR spectra of carbonyl group in pure citric acid and ascorbic acid has absorption bond in wave number of about 1700 cm –1 but interaction with Fe–O bonding moves it to around 1600 cm –1 69 . The absorption wave number around 1080 for both Fe 3 O 4 @PVA and Fe 3 O 4 @PEG is indicative of interaction between Fe atoms in Fe 3 O 4 and C–O group of PVA and PEG (Supplementary Fig. 3 ). The results of VSM test is shown in Fig. 4 . It is obvious that all synthesized nanoparticles are not ideal superparamagnetic nanoparticles but the coercivity is low enough to expect Neel relaxation mechanism from these nanoparticles. The coercivity and saturation magnetization and the magnetic core radius of the nanoparticles using the VSM tests results and Eq. ( 2 ) are tabulated in Table 2 (Supplementary Fig. 4 ). It is worth mentioning that an ideal superparamagnetic nanoparticle should have zero coercivity 79 , but on the other hand achivieng to exactly zero coercivity is not common in literature and different low amounts has been reported in literature for this parameter. For example 189.3 Oe 80 , 7.8 Oe 81 and 41.7 Oe 82 . Comparing the results with literature shows that the results are in acceptable range and the hystersis loops are negligable 79 , 83 – 85 . However, the D m obtained from VSM results is for the magnetic core of the nanoparticles and because of surface modifications, existence of some magnetically dead layer on the surface of the magnetic core is unavoidable and so the hydrodynamic radius of the nanoparticles were greater than r m amounts 86 , 87 . It is also noteworthy that the magnetic core radius of the nanoparticles is at the same range and there is a little difference between the magnetic core radiuses of the nanoparticles that was because of robust control on the temperature, composition of the reagents and addition rate of the NH 4 OH to the reaction medium at synthesizing procedure. It should be noticed that the coercivity and size of the hysteresis loop have decreased as temperature have increased and frequency have decreased 88 – 90 , as a result, it is reasonable to assume that the coercivity value will drop during the heating experiments in the magnetic field comparing to the value observed in the VSM test. The presence of nanoparticles in the dry state might cause interactions and the creation of larger–diameter structures, resulting in hysteresis loop 91 . The effect of surface modification on stability of the dispersions was shown in Fig. 5 . As it is obvious all the surface modified samples showed no perception after 72 h except dispersion containing bare Fe 3 O 4 nanoparticles. Theoretical SAR values The viscosity of the nanofluids containing different surface modified Fe 3 O 4 nanoparticles at different temperatures are presented in Fig. 6 . As it is obvious the viscosity has decreased by increasing the temperature. The viscosity of the nanofluids are approximately equal that was predictable because the concentration of the nanoparticles was low and the polymer itself was the dominant factor in the viscosity of the nanofluids (Supplementary Fig. 6 ). The Neel relaxation time and Brownian relaxation time constants at different temperatures for nanofluids containing synthesized nanoparticles using Eqs. ( 5 ) and ( 6 ) are also shown in Fig. 6 . As it is obvious the Brownian relaxation time is much greater than Neel relaxation time in all dispersions ( ) that was predictable, because the viscosity of the nanofluids was much greater than the nanofluid systems that water or solvents with viscosity near to water was used as dispersant. Also as mentioned earlier due to surface modification of the nanoparticles and existence of magnetically dead layer on the surface of the nanoparticles the r h > r m , and as r m was used for Brownian relaxation time measurement in this manuscript, so the real Brownian time constant was greater than the measured amounts. So, it can be said with high certainty that the effective time constant is equal to Neel relaxation time constant and this parameter was used in theoretical SAR values determination. Of course, the important note that should be considered in this part is to ensure that the nanoparticles are in the linear response regime in order to be able to use Eq. ( 3 ). Linear response regime refers to a region where magnetization is linearly related to the magnetic field. Different criteria has been mentioned in order to evaluate this, first, the parameter must be smaller than 1 92 , 93 . The exact solution of the Shlimois relaxation equation has shown that the SAR value for parameter less than one equal to the SAR value obtained from the Rosensweig model 68 . For all the synthesized nanoparticles in this research, the value of the parameter was less than 0.7. Another criteria to ensure being within this region is that the range of applied field intensity must has a certain distance from the saturation intensity 94 . By reviewing the data obtained from the VSM test, it can be seen that in all samples up to 300 Oe (23.9 kA/m), a linear relation is obvious between magnetization and the intensity of the applied field, and up to this applied field, the amount of magnetization has a suitable distance from the saturation magnetization. On the other hand, the maximum applied magnetic field in the conducted experiments was equal to 12 kA/m, and therefore, considering both the first criteria and the second criteria, it can be concluded that the tests are done in the linear response regime. Furthermore it has been determined in literature that the tests performed at a field intensity of 15 kA/m and a frequency of 300 kHz on iron oxide-based nanoparticles are in the linear response region 93 . Due to the fact that in this research, the field intensity and applied frequency values have a significant distance from these values, therefore, it can be ensured that the experiments are carried out in the linear response region. In addition to the parameter, which can be used as a criterion for formula selection, it has been demonstrated that when was less than 1/f (as it was in this study), the hysteresis loop and its area were very small 52 . At coercivity of 125 Oe and remanent magnetization of 16 emu/gr, the quantity of heat resulting from the hysteresis loops is approximately 50% of the total heat resulting from the heating operation in the setup, with relaxation accounting for the remainder 95 , As a result, because the quantity of coercivity and remanent magnetization, and thus the size of the hysteresis loop were lower in this study, it can be assumed that the amount of heat created by hysteresis is significantly lower, and the majority of the heat produced is due to relaxation. Although there is no doubt that the simplification and omission of heat created by the hysteresis loop has introduced some mistakes in the computations. In other words, the numbers provided in Table 3 may be slightly higher than the values already listed, and the results produced from theoretical and experimental measurements are further apart. However, based on the explanations provided, it can be concluded that this simplification did not bring significant mistake into the calculations, and, based on the proper particle distribution, enough system insulation, and the similarity of the results of Table 4 to Table 3 , it can be estimated that the neglected value in the theoretical calculations due to this simplification was just a small fraction. Considering the frequency of the tests (100 kHz) and VSM test results, Eq. ( 3 ) was used to determine the theoretical SAR values for the nanofluids at different magnetic field amplitudes and T = 22 °C and the results are tabulated in Table 3 . As it is obvious from the results the SAR values increases by increasing the magnetic field strength. It should be noted that the theoretical amounts are watt per gram of magnetic core, so the oxidation of the magnetite surface and also the surface modification could result in this parameter decrease in real experiments that will be discussed in the next section. Another point that should be noted is that according to the Eq. ( 3 ) in an ideal suspension without interaction between nanoparticles and coagulation of them, the SAR amount is independent of the nanoparticle’s concentration. Magnetic heating results The heating results in different magnetic fields for nanofluids containing 20,000 ppm of the nanofluids are shown in Fig. 7 (Supplementary Fig. 7 ). The SAR values using Eq. ( 9 ) are given in Table 4 . It is worth mentioning due to low concentration of polymer and nanoparticles C p of the solution was considered equal to C p of water. It is also worth mentioning that ( ) in the first 60 or 80 s are used in calculating theoretical SAR. The heating test results at the beginning of the test (first 90 s of the Fig. 7 diagrams) are tabulated in Fig. 8 . The non-linearity of the graphs even in the first 60 or 80 s is visible. It is clear that assuming this petameter to be linear in the calculations of the produced heat causes errors, and it appears that shortening the time period for measuring the initial temperature changes can lead to more accurate results. However, it should be noted that shortening the measurement duration can result in errors for the following reasons: Even a small error in temperature measurement can lead to a large error in value. Because the denominator of this fraction also becomes very small. The temperature measuring device’s accuracy was just 0.1 °C, so it was impossible to discern between temperature variations brought on by various nanoparticles within a few seconds. Reduced measurement duration causes the tester’s inaccuracies during temperature measurement (in the range of a few seconds) to lead to a substantial inaccuracy in the value of , therefore it is advisable to use a relatively greater time range. Taking into account everything mentioned above, it was determined that the best time period for measuring initial temperature changes was the first 60 and 80 seconds of the tests. Comparison between the theoretical SAR values at Table 3 and experimental results in Table 4 shows that the experimental amounts are lower. In Eq. ( 3 ), it is clear that the SAR is a 2nd order function of the H. The parameter that is defined according to this functionality in various researches is intrinsic loss power (ILP), which is defined as Eq. ( 10 ) 94 . ILP is a system-independent parameter that allows direct comparison of tests performed in different laboratories. If the frequency value is constant in a system, it can be concluded that the dependence of SAR on H 2 should be linear. Therefore, this relationship was used to check the validity of experimental SAR results in terms of H 2 and comparing it with theoretical results. Although this relationship has been shown to be true up to field strengths of about 20 kA/m 68 . In case of bare Fe 3 O 4 the theoretical and experimental results per H 2 are plotted in Fig. 9 . The experimental results are a little (10–15%) less than theoretical expectations (in case of bare Fe 3 O 4 nanoparticles). Although this amount of difference is an acceptable value for an experimental experiment, several reasons can be mentioned for this amount of difference. As mentioned in the introduction, many efforts have been made so far to formulate magnetic heating and the effect of various factors on the difference in the reports provided by various researches 93 . Considering these researches as well as the conditions of the experiment conducted in our research, the following factors can be mentioned as the reasons for the deviation in the results of the experiments compared to the theoretical results 46 , 47 , 68 , 92 – 94 , 96 , 97 : Absence of complete adiabatic conditions in the system. Non-establishment of the conditions related to the linear response region due to the high intensity of the applied magnetic field. The produced nanoparticles had a hysteresis loop and were not ideal superparamagnetic nanoparticles. The low accuracy of the measuring instrument in determining at the initial moment for various reasons such as inaccuracy in temperature measurement, uncertainty in placing the probe, etc. The occurrence of aggregation, agglomeration clustering, sedimentation and to a small extent chemical reaction. Uncertainty in the measurement of magnetic field intensity. The possibility of the effect of sample aging on laboratory results. Non-uniformity of applied magnetic field. Rosensweig’s model for calculating SAR gives an upper limit of SAR and there is a possibility that the actual SAR is slightly lower. Pearson correlation coefficient was used to check the compatibility between experimental and theoretical data 97 . The value of this parameter between these two datasets is equal to 0.999. This coefficient is a measure of the linear relationship between these datasets. An approximately linear relation (with y-intercept near to zero) between SAR and H 2 is obvious in the Fig. 9 in both theoretical and experimental results and this relation is clear in Eq. ( 3 ), also is dependent on applied magnetic field and so there is a little deviation from exact linear relation. The difference between theoretical and experimental SAR amounts are less in lower magnetic field strengths that is because of the lower temperature of the dispersion in this case that is an evidence for thermal losses of the system. In case of surface modified nanoparticles the difference between theoretical and experimental SAR amounts are larger. The reason is that the theoretical SAR amounts are based on weight of magnetic portion of the nanoparticle but in experimental tests the SAR amounts are based on nanoparticles weight (magnetic core and surface modification agent). As previously mentioned in material and method section the amount of used surface modification agents were 40 wt% of the nanoparticles, also not all of the surface modification agent adhere to the surface of the nanoparticle and part of them that has been attached physically -not chemically- on the surface of the magnetite has been eliminated during the washing of the nanoparticles. Figure 9 can also be used to investigate the effect of hysteresis loops on the heating process. Since linear behavior is observed in the quantity of heat absorbed in terms of H 2 (which is a representation of ILP), the heat produced by nanoparticles in the heating measurement tests in the alternating magnetic field was in the linear response regime and so the particles acted like nanoparticles with no coercivity 98 . The effect of the surface modification on the experimental SAR of nanoparticles can also be investigated considering the changes in the amount of saturation magnetization. The decrease in the saturation magnetization of the surface modified nanoparticles compared to the bare nanoparticle is caused by the surface modification agent, which is a non-magnetic material. The ratio of saturation magnetization of surface modified nanoparticles to the saturation magnetization of bare nanoparticles, as well as the ratio of experimental SAR value of surface modified nanoparticles to the experimental SAR values of bare nanoparticles are given in the Table 5 . Except for citric acid, there is a good correlation between these two ratios in the rest of the nanoparticles. In other words, the effect of adding non-magnetic materials has appeared both in reducing saturation magnetization and in the amount of heat produced. In the case of citric acid, it should be noted that the size of nanoparticles modified with citric acid is smaller compared to other nanoparticles, which leads to a decrease in the theoretical SAR of this nanoparticle and ultimately leads to a decrease in its experimental SAR value 68 . The smaller size of citric acid coated nanoparticle is due to the very good surface modification of Fe 3 O 4 nanoparticle by this agent, which prevents any coagulation of it, and it has also been discussed in our previous paper 56 . The ratio of experimental to theoretical SAR values at different magnetic field are brought in Table 6 . The trend of decreasing the ratio by increasing the magnetic field is obvious. Another issue that should be pointed out is that the is lower in case that PVA and PEG was used for surface modification of the nanoparticles. This phenomena is due to the larger molecules of polymers comparing the molecules of SiO 2 , citric acid and ascorbic acid. In other words the in Fe 3 O 4 @ PVA and Fe 3 O 4 @ PEG was lower comparing the other three surface modification agents. The heating test results for dispersions containing 10,000 ppm of nanoparticles at magnetic field of 12 kA.m –1 is shown in Fig. 10 and experimental SAR values and final temperatures are tabulated in Table 7 (Supplementary Fig. 10 ). It is clear that experimental SAR values in case of 10,000 ppm concentration of nanoparticles was more than 20,000 ppm samples. This phenomena has been observed in similar researches, too 4 . In case of solutions with higher concentrations the coagulation possibility would increase and so the amount of experimental SAR amount would decrease by increasing the nanoparticles concentrations. For investigating the effect of surface modification agent on coagulation and agglomeration inhibition of the system the ratio of experimental SAR in case of 20,000 ppm of nanoparticles to experimental SAR in case of 10,000 ppm of nanoparticles ( in magnetic field intensity of 12 kA.m –1 are tabulated in Table 8 . It is obvious that the experimental SAR amounts decreases more by increasing the nanoparticle concentration in nanofluid samples containing Fe 3 O 4 and Fe 3 O 4 @SiO 2 . These two nanoparticles have lower hydrophilic behavior comparing other surface modified nanoparticles and so tends to agglomerate and form bigger clusters.

Conclusion The Neel mechanism on the heating of the nanofluids was investigated successfully and the experimental trends was as the theoretical trend especially in low concentrations (10,000 ppm). Surface modification right after the synthesis of the nanoparticles resulted in agglomeration prevention of the nanoparticles and so the magnetic core radius of the bare nanoparticles and all surface modified nanoparticles were the same and were about approximately 8 nm. Surface modification of Fe 3 O 4 nanoparticles cause in decreasing the induction heating ability of the nanoparticles per gram of the nanoparticles that was because of magnetically dead layer on the surface of the nanoparticles, in other words the amount of effective substance in induction heating have decreased in surface modified nanoparticles. The amount of decrease in experimental SAR comparing theoretical SAR was more in case that PVA and PEG was used as surface modification agent that was because of bigger molecules of polymers comparing other surface modification agents. The experimental SAR to theoretical SAR was lower in higher magnetic field strengths that was because of thermal losses of the system that was more in higher temperatures. According to the theoretical relation the SAR amount is independent of nanoparticles concentration but in experimental results the SAR decreased by increasing the nanoparticles concentration that was because of agglomeration of nanoparticles. Surface modification prevents the nanoparticles from agglomeration, so the SAR in surface modified nanoparticles is less dependent on the nanoparticles concentration but in case of bare Fe 3 O 4 and Fe 3 O 4 @SiO 2 the hydrophobicity is low and so agglomeration of nanoparticles resulted in SAR decrease. When there is a substantial coercivity value and the ξ parameter is greater than 1, the hysteresis loop should also be taken into account in the generated heat computations. In other words, the heat produced by nanoparticles is exactly equal to the heat produced by relaxation only when the particles are ideal superparamagnetic nanoparticles with zero coercivity. However, when this parameter is not zero and a hysteresis loop occurs in VSM tests, some heat (however minor) is created due to hysteresis, of course, depending on the frequency and quantity of saturation magnetization and coercivity (in general, the area of the hysteresis loop), this heat can be substantial. Of course, in cases where the heat generated by the hysteresis loop is taken into account in the calculations, it should not be limited to the measurement of the static hysteresis loop, but also the measurement of the dynamic hysteresis loop as well as the hysteresis loop in real test conditions (dispersion of the nanoparticles in test medium) and its changes during the test (by changing temperature and frequency) must be considered in the calculations.

The effect of surface modification on enhancing the magnetic heating behavior of magnetic nano fluids were investigated, for this purpose Fe 3 O 4 nanoparticles were synthesized using co-precipitation method and surface modification was done using citric acid, ascorbic acid, tetraethyl orthosilicate (TEOS), polyvinyl alcohol (PVA) and polyethylene glycol (PEG). Experimental heating tests using AC magnetic field were done in the frequency of 100 kHz and different magnetic field (H) intensities. Theoretically the specific absorption rate (SAR) in magnetic nano fluids is independent of nanoparticles concentration but the experimental results showed different behavior. The theoretical SAR value @ H = 12kA.m –1 for Nano fluids containing bare Fe 3 O 4 nanoparticles was 11.5 W/g but in experimental tests the obtained value was 9.72 W/g for nano fluid containing 20,000 ppm of dispersed nanoparticles. The experimental SAR calculation was repeated for sample containing 10,000 ppm of nanoparticles and the results showed increase in experimental SAR that is an evidence of nanoparticles agglomeration in higher concentrations. The surface modification has improved the dispersion ability of the nanoparticles. The Ratio of SAR , experimental, 20000ppm to SAR , experimental, 10000ppm was 0.85 for bare Fe 3 O 4 nanoparticles dispersion but in case of surface modified nanoparticles this ratio has increased up to 0.98 that shows lower agglomeration of nanoparticles as a result of surface modification, although on the other hand the surface modification agents were magnetically passive and so it is expected that in constant concentration the SAR for bare Fe 3 O 4 nanoparticles to be higher than this variable for surface modified nanoparticles. At lower concentrations the dispersions containing bare Fe 3 O 4 nanoparticles showed higher SAR values but at higher concentrations the surface modified Fe 3 O 4 nanoparticles showed better results although the active agent amount was lower at them. Finally, it should be noted that the nanoparticles that were surface modified using polymeric agents showed the highest decrease in experimental SAR amounts comparing theoretical results that was because of the large molecules of polymers comparing other implemented surface modification agents. Subject terms

Supplementary Information

Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-51801-5. Acknowledgements The authors wish to acknowledge the Iran National Science Foundation (INSF), IRAN Nanotechnology Innovation Council and Iranian Central Oil Fields Company for financial support of the research. Author contributions B.S.D. Investigation, Methodology, Formal analysis, Data curation, Writing—original draft, Writing—review & editing. A.J. Conceptualization, Project administration, Supervision, Writing—review & editing. M.V.-S. reviewing the manuscript. R.S. Supervision and guidance of magnetic heating tests Z.F. Supervision and guidance of magnetic nanoparticles synthesis. Data availability All data generated or analyzed during this study are included in this published article [and its supplementary information files]. Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Sci Rep. 2024 Jan 14; 14:1296

oa_package/bb/9d/PMC10788351.tar.gz

PMC10788352

38221571

Introduction The oral cavity is the initial segment of the digestive system, second source of respiration, and a crucial organ for pronunciation, mastication, and facial esthetics. Poor oral health may have an impact on a person’s overall health, causing pain, discomfort, and disfigurement. 1 Oral diseases, such as dental caries, periodontal diseases, and oral cancers, affect nearly 3.5 billion people, which are global burdens that cause patients suffering, especially those with a low socioeconomic status. 2 To alleviate these burdens, researchers have come up with innovative methods for early diagnosis and effective treatment. Extracellular vesicles (EVs) are derived from cellular membranes and released into the extracellular space; they play critical roles in intercellular communication. 3 There are two main categories of EVs, including exosomes and ectosomes. 4 Exosomes, which are principal constituents of EVs, are derived from the endosomal system and possess bilayer lipid encapsulation, with diameters ranging from 30 to 150 nm. 5 Compared with ectosomes, which assemble cargos on the cytosolic surface and transient release in “outward budding”, 6 exosomes exhibit more intricate interactions with cyto-inclusions and have garnered significant attention from biological researchers worldwide for their abundant cargos and various functions associated with physiological or pathological processes. 5 The biogenesis of exosomes is tightly regulated through a complex network of processes. Upon endocytosis, the potential cargos are internalized by the cells and give rise to early-sorting endosomes (ESEs). The subsequent interactions with organelles, such as the endoplasmic reticulum (ER) and Golgi apparatus, lead to the maturation of ESEs into late-sorting endosomes (LSEs). Following this, the cargos accumulate near the limiting membrane of multivesicular bodies (MVBs) and generate intraluminal vesicles (ILVs), which will eventually be released as exosomes via exocytosis. 5 , 7 , 8 It should be noted that some ILVs may also undergo interactions with lysosomes or autophagosomes. 5 , 7 , 8 Throughout the entire process, various regulators, such as the endosomal sorting complex required for transport (ESCRT), tetraspanin CD9/CD63/CD81, and Alix/programmed cell death 6-interacting protein (PDCD6IP), are involved in the intricate mechanisms of sorting and secretion. 5 , 7 – 9 Accordingly, an extensive body of research has confirmed that the final version of the exosomes contains diversified contents, including amino acids, proteins, nucleic acids, and cellular metabolites. These molecules play distinct roles in intercellular signaling transmission, immune-modulation, stromal adaptation, and multiple biological events. 9 Therefore, exosomes exhibit significant potential in managing disease processes. Previous research has elucidated the close correlation between exosomes and oral diseases, including periodontal inflammation, oral squamous cell carcinomas (OSCCs), oral mucosa diseases, etc. The application of exosomes involves monitoring the progression of the diseases, early diagnosis, detection through specific manifestations in fluid, and advanced targeted therapy via precise molecule delivery. This review concludes the recent studies on the applications of exosomes in oral diseases and aims to provide a comprehensive insight into the latest developments in exosome alterations, functions, and applications in oral-related physiological and pathological conditions. The ultimate goal is to identify new opportunities for the effective utilization of exosomes in the prevention and treatment of oral diseases.

Early diagnostic methods utilizing exosomes in oral diseases According to the above, it is convincing that exosomes play a crucial role in the progression of oral diseases. Our particular emphasis lies in exosomal application for early diagnosis due to the potential exacerbation of patients’ suffering caused by delayed detection. In contrast to the more apparent biomarkers, such as inflammatory molecules of periodontitis and gene expression changes in OSCCs, exploring the full advantages of exosomes represents a promising avenue. Liquid biopsy is an emerging disease diagnostic method that primarily involves the isolation and evaluation of fluid entities, such as DNAs/RNAs, proteins, and extracellular vesicles in human saliva, blood, and urine. 79 Compared with the other patterns of biomarkers, exosomes protect their cargos, remarkably enhancing the accuracy and practicability of detection. 80 In the field of oral medicine, exosome-associated liquid biopsy has demonstrated value in the diagnosis of multiple diseases. 81 The identification of novel biomarkers and reliable detective techniques are potential research prospects. Biomarkers for periodontitis The traditional diagnostic criteria for periodontitis primarily rely on clinical symptoms, such as the periodontal pocket depth and the pathological loss of the alveolar bone. However, the possibilities of “overdiagnosis” or “underdiagnosis” remain unsolved, as these clinical variables may fail to accurately predict the disease progression and treatment response. 82 The identification of exosomal biomarkers has the potential to enhance our understanding of the intricate biological mechanisms underlying periodontitis progression and facilitate the development of advanced clinical management strategies for patients. Generally, the concentration of EVs from the GCF of periodontitis patients is evidently higher when compared to that of healthy samples. 83 Nucleic acids, as prominent constituents of exosomal cargos, can provide valuable diagnostic insights. In addition to DNA/RNAs that directly encode proteins, non-coding RNAs play important roles in regulating cellular events through diverse pathways, such as gene silencing and post-translational modification. 84 MiRNAs are small, non-coding RNAs that modulate mRNA expression by forming RNA-induced silencing complexes (RISCs) or directly binding to mRNAs through base pairing. 85 According to Kamal et al., 86 1995 salivary exosomal miRNAs and 333 plasma exosomes were significantly altered in their periodontitis samples. Among these potential biomarkers, serum exosomal miR-let-7d, miR-126-3, miR-199a-3, and salivary exosomal miR-125a-3 were notable for distinguishing the disease status and correlation with the clinical stages. 86 In addition, researchers reported that serum exosomal miR-1304-3p, miR-200c-3p, small nucleolar RNA SNORD57, SNODB1771, 87 salivary exosomal miR-223-3p, 14 Osx mRNA 88 and GCF exosomal miR-1226 89 were downregulated in periodontitis. However, salivary exosomal miR-140-5p, miR-146a-5,miR-628-5p, 90 miR-381-3p, 91 tumor necrosis factor-alpha (TNF-α), 88 and PD-1 mRNAs exhibited higher expression levels in the periodontitis samples. 92 As for proteins, the levels of the tetraspanins CD9 and CD81 were decreased in the salivary exosomes of periodontitis, which is associated with an inflammatory reaction. 93 The levels of immune-related proteins, such as complement components (C6, C8A, and C8B) and chemokines, were increased in the salivary exosomes of young severe periodontitis patients, 94 implying that immune changes are responsible for this pathological alteration. Biomarkers for oral cancers Scalpel biopsies and histological examinations have long been regarded as the golden standard for malignancy research. 95 However, oral cancers, particularly OSCCs, usually develop imperceptibly, with minimal clinical manifestations in the early stages. Therefore, by the time the symptoms have been identified, the malignancy may have already appeared, leading to a poor prognosis. 96 In the meantime, the pursuit of non-invasive detection methods has become a prevailing trend in the medical field. These statuses emphasize the necessity for the application of exosomal biomarkers in OSCC diagnosis. Compared with the samples from healthy controls, the exosomes from OSCC patients showed an increased concentration and larger diameter, with higher CD63 and lower CD9/CD81 expression levels, revealing basic evidence for distinguishment. 97 However, the most comprehensive and convincible distinctions are the cargos of the exosomes. We have summarized these biomarkers and the relevant research in Table 1 . In OSCCs, the altered secretion of exosomal miRNAs can signal the disease status. Based on the statistical evidence, the levels of serum/plasma exosomal miR-19a/27b/20a/28-3p/200c/151-3p/223/20b, 98 miR-130a, 99 miR-155, miR-21, 100 miR-3168, miR-125a-5p, miR-451a, and miR-16-2-3p, 101 and salivary exosomal miR-486-5p, miR-486-3p, miR-24-3p, 102 miR-1307-5p, 103 miR-200a, and miR-134 104 were significantly elevated in the patients with OSCCs, performing potential oncogenic roles. However, the serum exosomal miR-370/139-5p/let-7e/30c, 98 miR-126, 100 and salivary exosomal miR-10b-5p 105 , 106 expression levels were reduced, as they are tumor suppressors. Through the in vitro culturing of OSCC cell lines, miR-365 and other miRNAs are produced in exosomes aberrently 107 and can be used to assess human papilloma virus (HPV) involvement. 101 Tissue-derived exosomal circRNA_047733 can be used to indicate the lymph node metastasis (LNM) outcomes of OSCC cases with satisfying specificity and sensitivity. 108 The in vivo application of these biomarkers necessitates further research. CirRNAs are back-splicing formed RNAs that influence protein translation through interacting with miRNAs, RNA-binding proteins, and RNA Pol. 109 Serum exosomal circ_0000199 showed a higher level in OSCC patients and is associated with the Tumor Node Metastasis (TNM) stage and prognosis. 110 Regarding the protein cargos of the exosomes, there are notable differences between the OSCC patients and healthy individuals. TGFβ, a well-known cancer biomarker, provides much more diagnostic and prognostic information for OSCCs in an exosomal form than in a soluble form. 111 The level of the sera and salivary exosomal marker Alix increases significantly in OSCC patients, but the sensitivity in early cancer (stage I) detection is not satisfying. Moreover, exoAlix behaves differently in sera and saliva in a stage-dependent manner; only serum exoAlix presents prognosis information. 112 In addition to single-exosomal protein biomarker detection, Li et al. 113 demonstrated the advantages of combined exosomal C-reactive protein (CRP), von Willebrand factor (VWF), and leucine-rich alpha-2-glycoprotein (LRG) in the determining specificity and sensitivity of early OSCCs diagnosis. The serum exosomal platelet factor 4 variant (PF4V1), C-X-C motif chemokine (CXCL7), coagulation factor XIII, A (F13A1) and Apolipoprotein A-I (ApoA1) not only enable discrimination between the OSCC cases and healthy controls, but also provide information on the lymph node metastasis status. The combination of these four biomarkers could also increase the preciseness. 114 Biomarkers for other oral diseases Exosomal biomarkers have also been discovered in other oral diseases. Viral infectious hand, foot, and mouth disease (HFMD) mostly affects young patients under 5 years old with herpes. 115 In the sera of patients with HFMD (both the mild and severe types), there is an elevated level of exosomal miR-16-5p, while the miR-671-5p and miR-150-3p levels were decreased. 116 These statistical data demonstrated the satisfying sensitivity and specificity of exosomes as biomarkers in HFMD diagnosis. Oral lichen planus (OLP) is an immune-related mucosa disease that is well recognized as a potentially malignant disorder. 117 Therefore, its early diagnosis would inhibit the progression toward oral cancers and benefit the patients’ prognosis. The exosomal alteration in fluids has provided valuable information regarding OLP detection. Based on the evidence from the polymerase chain reaction (PCR) technique, the serum exosomal miR-34a-5p 118 and salivary exosomal miR-4484 119 were significantly upregulated in the OLP samples. Furthermore, the human cytomegalovirus (HCMV)-encoded miR-UL59 manifested a higher level in the OLP samples, 120 suggesting the underlying connections between HCMV infection and the unclear etiology of OLP. As an autoimmune disease related to the salivary glands, Sjögren’s syndrome causes alterations in various contents of patients’ fluids. Since 2010, scientists have reported the potential of exosomal miRNA biomarkers used for diagnosing Sjögren’s syndrome. 121 Novel sequencing evidence has revealed that the levels of exosomal circRNAs circ-IQGAP2 and circ-ZC3H6 increased in the serum samples from primary Sjögren’s syndrome patients. 122 In addition, in murine models, the levels of serum exosomal miRNA-127-3p, miRNA-409-3p, miRNA-410-3p, miRNA-541-5p, and miRNA-540-5p were upregulated. 123 These findings deserve further research on the underlying mechanism via human studies. Analysis technique for exosomes Prior to our evaluation of exosomal biomarkers, the primary focus was the development of efficient and precise detection techniques. The separation and quantitative analysis of exosomes serve as crucial steps in clinical applications. 124 Centrifugation is the conventional method used for exosome separation. To improve efficiency, differential centrifugation is the most commonly used and practical technique. This approach allows for the isolation of nucleic acid cargos at fractions of 0.3×10 3 and 2.0×10 3 , while protein cargos appear at different fractions; Alix predominantly appears at the 160.0×10 3 fraction, and HSP70 exhibits an even distribution across a wide range from 0.3×10 3 to 160.0×10 3 124 , 125 (Fig. 2a ). The requirements for exosomal quantitative analysis vary depending on specific objectives, such as particle enumeration, protein quantification, RNA quantification, etc. 124 Consequently, the relevant methodologies include nanoparticle tracking analysis (NTA) and flow cytometry for particle enumeration, bicinchoninic acid (BCA) assaying and PAGE-SDS staining for protein quantification. 124 Aiming at enhanced efficiency, other researchers have come up with more practical and precise methods for oral exosomal quantitative analysis. Surface enhancement Raman spectroscopy (SERS) is a modified form of Raman spectroscopy (the inelastic scattering of light), which shows an amplified vibrational Raman spectrum when the testing sample is in close proximity to a plasmonic nanostructured surface (Fig. 2b ). Based on the analysis of saliva exosomes, SERS exhibits exceptional sensitivity and specificity in distinguishing malignant and normal ones, enabling the early diagnosis of head and neck cancers. 126 Cheng et al. introduced a new technique for inductively coupled plasma mass spectrometry, performing excellently in oral exosomes quantitative analysis. 127 They captured exosomes with the CD63 antibody and detected a signal with cholesterol-based rolling circle amplification and gold-nanoparticle-labeled DNA (Fig. 2c-1 ). Also associated with CD63 capturing, red blood cell membrane (RBCM)-modified electrode could produce electrochemical signals once confronting exosomes, showing great precision in saliva exosomes detection 128 (Fig. 2c-2 ). Although significant progress has been made in the identification of exosomal biomarkers for diagnosing oral diseases, certain limitations still exist. The majority of studies lack sufficient evidence due to inadequate sample collection and classifications for exosomal biomarkers. These deficiencies pose challenges in standardizing their clinical applications. Furthermore, the techniques used for isolating and analyzing exosomes from human fluids are impractical for most basic medical institutions, and a valid consensus has not yet been reached. To address these issues, it is imperative to further develop technical capabilities and gain deeper insights into the role of exosomes in the progression of oral diseases, which will undoubtedly inspire more reliable diagnostic standards.

Conclusions and prospects Exosomes have emerged as a novel research frontier, with a significant application potential across diverse fields. In the realm of oral medicine, exosomes hold promise as non-invasive biomarkers for early disease diagnosis by distinguishing between pathological and healthy states, with periodontitis and OSCCs as the most convincing examples. Furthermore, exploring the distinct characteristics and alterations in exosomes during the progression of oral diseases can deepen our understanding of their underlying pathological mechanisms and pave the way for targeted therapeutic interventions and treatment efficacy. Stem cell-related studies and applications are currently at the forefront of medical research, particularly in relation to regenerative treatments for oral diseases. This intersection with exosome biology provides a valuable foundation for the rational utilization of stem cells (Fig. 3 ). Despite the existing research and applications of exosomes in oral medicine, there are still several limitations. First, the identification, analysis, and synthesis of oral exosomes are not precise or convenient enough. In accordance with the updated guidelines for exosomal research 244 and the specific characterization of the oral cavity (such as the availability of saliva), it is imperative to develop more advanced techniques that will undoubtedly expand the applications of exosomes in oral diseases. Reducing the technique barriers is also important for the promotion of exosomes in real-world medicine, especially in large-scale production and stable storage-to-transportation strategies. Exosomal biomimetic materials might also be promising, combining the inherent advantages of natural exosomes with industrial synthesis techniques. Meeting these diverse demands necessitates collaborative efforts across the biomedical field, while we should raise specific views based on oral diseases properties. Second, there is still lack of clear catalog of the exosomes in oral diseases. Though the current studies involve exosomes in various aspects of oral medicine, they are not yet systematic. While exosomes’ classification primarily relies on their origin, it is worth considering alternative approaches, such as their targeting specific signaling pathways or exploring their distinct effects on cellular functions. With more insights into the abundant exosomal roles throughout oral disease progression and treatment, we ought to find general paths for the future exploration of novel exosomes. These avenues necessitate a deeper understanding of both the exosomes themselves and the underlying mechanisms involved in oral diseases. Third, clinical trials on exosomes in oral diseases are still scarce. According to a relevant analysis, the clinical trials on exosomes have mainly fallen under the respiratory research category, such as biomarkers for lung cancer and therapies for SARSCoV-2 pneumonia. 245 The primary challenges in conducting clinical trials on exosomes for oral diseases pertain to establishing standardized production criteria and determining the precise dosages for specific indications. Therefore, future studies should prioritize quality control measures and expand the experimental models to more advanced animals. In addition, investigating the crosstalk between oral diseases and other systemic diseases focusing the exosome’s communications could provide valuable insights for future research. In summary, while the current research on exosomes in oral medicine has yielded significant achievements, there is a substantial amount of work to be conducted. Future studies should not only focus on the physiological and pathological molecular mechanisms associated with exosomes, but also emphasize the feasibility of relevant clinical translation, enhancing the exploration and application of efficient and effective exosomal therapies.

Oral diseases, such as periodontitis, salivary gland diseases, and oral cancers, significantly challenge health conditions due to their detrimental effects on patient’s digestive functions, pronunciation, and esthetic demands. Delayed diagnosis and non-targeted treatment profoundly influence patients’ prognosis and quality of life. The exploration of innovative approaches for early detection and precise treatment represents a promising frontier in oral medicine. Exosomes, which are characterized as nanometer-sized extracellular vesicles, are secreted by virtually all types of cells. As the research continues, the complex roles of these intracellular-derived extracellular vesicles in biological processes have gradually unfolded. Exosomes have attracted attention as valuable diagnostic and therapeutic tools for their ability to transfer abundant biological cargos and their intricate involvement in multiple cellular functions. In this review, we provide an overview of the recent applications of exosomes within the field of oral diseases, focusing on inflammation-related bone diseases and oral squamous cell carcinomas. We characterize the exosome alterations and demonstrate their potential applications as biomarkers for early diagnosis, highlighting their roles as indicators in multiple oral diseases. We also summarize the promising applications of exosomes in targeted therapy and proposed future directions for the use of exosomes in clinical treatment. Subject terms

Exosomes in the progression of oral diseases As researchers have demonstrated the intricate roles of exosomes in biological events, their distinct alterations are significant components in the pathological processes of oral diseases. At the initial stage, analyzing the exosomal information helps to improve our early awareness of oral diseases. During the development and prognosis stages, summarizing the exosome-related manifestations can enhance our comprehension of the selection and response of treatments. Therefore, exosomes serve as a crucial indicator in the diagnosis, monitoring, and treatment of several oral diseases. In this part, we summarize the roles of exosomes in determining the progression of oral diseases, with a focus on periodontal diseases and oral cancers. Periodontal and bone-related pathological status Periodontal inflammation and bone resorption Following exposure to risk factors (intrinsic and/or acquired), the pathological changes in periodontitis are initiated by immune-inflammatory responses, leading to the release of inflammatory molecules, such as cytokines and matrix metalloproteinases (MMPs). These molecules exert their effects on periodontal tissues, thereby inducing clinical manifestations. 10 Osteoclasts are activated in inflammatory microenvironments and lead to the destruction of the surrounding alveolar bone. Subsequently, these irreversible destructions of periodontal structures accelerate the progression of periodontitis and lead to tooth mobility or even tooth loss, severely impacting the patients’ quality of life. 11 The previous studies have demonstrated the significance of inflammatory factors in periodontitis. 10 It is noteworthy that exosomes play important roles in the modulation and alteration of periodontal inflammation and bone resorption. 12 Periodontal ligament stem cell (PDLSC)-derived exosomes significantly improved angiogenesis in inflammatory regions by upregulating the vascular endothelial growth factor (VEGF) in human umbilical vein endothelial cells (HUVECs) via miR-17-5p. 13 Salivary exosomal miR-223-3p increased the interleukin (IL)-1β and IL-6 levels by mediating NLRP3 gene expression and pyroptosis. 14 Oxidative stress is involved in periodontitis progression with abnormal reactive oxygen species (ROS). Protein arginine methyltransferase 1 (PRMT1) induced by oxidative stress inhibited exosome secretion from periodontal ligament cells (PDLCs), resulting in reduced osteogenic differentiation. 15 The interactions between the host inflammatory response and microbe are also closely involved in the progression of periodontitis. 10 Similar to exosomal microRNAs (miRNAs) derived from host cells, small RNAs of miRNA size (msRNAs) from pathogens ( A. actinomycetemcomitans, P. gingivalis, and T. denticola ) were detected in the bacterial outer membrane vesicles. 16 P. gingivalis can also assign a senescence-associated secretory phenotype (SASP) to dendritic cells (DCs) and T cells by exosomes, and ultimately, this results in alveolar bone loss. 17 Moreover, mechanical stimuli are a promoter of periodontal inflammatory and tissue/bone impairment, mainly acting on PDLCs. 18 PDLCs secrete exosomal miR-9-5p when facing cyclic stretching and promote the M1 (pro-inflammatory) polarization of macrophages through the miR-9-5p/SIRT1/NF-kB pathway in murine models. 19 The M1 macrophage was also induced by periodontal ligament fibroblast-derived exosomes when a compressive force was applied. The underlying mechanism was associated with the Yes-associated protein (YAP), 20 which is a crucial component in the Hippo signaling pathway and performs significant roles in cellular mechanotransduction. 21 In the immune-modulation of the inflammatory response, the YAP/Hippo pathway acts as a key upstream regulator. 22 These studies highlight the complex interactions between exosomes and the clinical manifestations of periodontal diseases, according to which we should take more steps to attenuate the progression of periodontitis. Orthodontic movement Orthodontic treatment involves the complex processes of alveolar bone remodeling upon the application of mechanical forces. During movement, the expression of gingival crevicular fluid (GCF) exosomal miR-29 is significantly increased. 23 Meanwhile, the PDLSC-derived exosomal miRNAs are largely altered, 24 , 25 and the quantity of exosomal proteins annexin A3 (ANXA3) increases, which induces osteoclast differentiation by the activation of extracellular regulated protein kinase (ERK). 26 When orthodontic movement stops and teeth position satisfies our needs, PDLSC-derived exosomes also contribute to teeth stabilization. For instance, Simvastatin, a bone-formation-enhancing drug, has better bioavailability in conjunction with PDLSC-derived exosomes. 27 Oral squamous cell carcinomas With increasing incidence and mortality rates, oral cancers rank as the 13th most common cancer worldwide, with an estimated 377,713 new cases and 177,757 deaths in 2020. 28 , 29 The consumption of tobacco and areca nut significantly increases the risk of oral cancers. Specifically, oral cancers cause larger burdens in developing countries due to delayed diagnosis and limited treatment opportunities. 29 Among all the types of oral cancers, OSCCs are the most common, with an estimated 40% higher incidence rate in 2040. 30 Summarizing the alterations in the exosomes in OSCCs could enhance our understanding of malignant progression. Here, we discuss exosomal roles in malignization, angiogenesis, and tumor microenvironment (TME) modification in OSCC progression and the post-treatment response (Fig. 1 ). Malignization According to transcriptome analysis, head and neck squamous cell carcinoma (HNSCC)-associated exosomes play a significant role in various processes throughout cancer development. 31 As the most common malignancy types in HNSCCs, OSCCs exhibit various exosomal alterations. From the outset, the injection of OSCC-tumor-derived exosomes accelerated the malignancy progression of precancerous lesions in murine models, 32 and this phenomenon was attributed to exosomal miR-10b through AKT signaling. 33 The same initiation of malignancy also occurs in recurrent OSCCs with increased serum exosomal long non-coding RNA (lncRNA)-CCDC144NL-AS1 and MAGI2-AS3 via the PI3K-AKT-mTOR pathway 34 (Fig. 1a ). Upon the manifestation of these early malignancy symptoms, the subsequent progression of OSCCs ensues through diverse exosomal alterations. Angiogenesis Inducing the vasculature is an important hallmark of cancer, 35 and the exosomes accelerate this process through several pathways (Fig. 1b ). Phosphatase and tensin homolog deleted on chromosome ten (PTEN) is a tumor-suppressing factor, and its expression is downregulated in OSCCs. 36 Exosomal miR-130b-3p derived from OSCCs cells and miR-23b-3p from salivary adenoid cystic carcinomas (SACCs) cells negatively regulate PTEN expression, promoting migration and angiogenesis in HUVECs. 37 , 38 miR-221s and miR-210-3p also regulated HUVECs angiogenesis through the PI3K/AKT pathway. 39 , 40 Besides cancer cells, the mesenchymal stem cells (MSCs) in oral carcinomas can secrete angiogenesis-stimulative exosomes. OSCC–MSC-derived exosomal matrix metalloproteinases 1 (MMP1) significantly enhances the function of HUVECs. 41 TME modification In addition to tumor cells, TME exerts a dominant influence on the development of OSCCs, involving intricate interactions with exosomes (Fig. 1c ). The TME is composed of the extracellular matrix (ECM) and relevant cells, including cancer-associated fibroblasts (CAFs), endothelial cells, and immune cells. 42 In OSCCs, tumor-derived exosomes induce CAF differentiation. 43 In turn, the CAFs have received great attention for their significance in promoting tumor development through intracellular communications, primarily via exosome secretion. 44 In OSCCs, the CAF-derived miR-382-5p 45 and miR-146b-5p 46 exosomes are upregulated, leading to the invasion of cancer cells and metastasis. In addition, the miR-34a-5p-devoid exosomes from CAFs promote malignancy by targeting the AXL (a component of the receptor tyrosine kinase) of cancer cells. 47 By analyzing the genes related to EV formation in the HNSCCs samples and their impact on cellular behaviors, other scientists have found a significant correlation between EVs and immune modification (T/B cells, macrophage, and neutrophils) when a malignancy occurs. 48 The tumor-associated macrophages (TAMs) play a crucial role as immune cells within the TME. Generally, the TAMs mainly polarize into two states—the M1 and M2 subtypes. 49 According to the conventional perspective, the M1 macrophages perform anti-tumor functions by direct cytotoxicity or antibody-dependent cell-mediated cytotoxicity (ADCC), while the M2 macrophages promote cancer progression and metastasis by secreting cytokines and related molecules, such as ILs, epithelial growth factors (EGFs), and MMPs. 50 However, the involvement of M1 macrophages in the process of malignancy invasion has been recently observed, suggesting that their presence may contribute to more aggressive malignization, but not a higher survival rate. 51 In OSCCs, the TAMs have complex interactions with the tumor cells. The exosomal transforming growth factor beta (TGF-β) derived from HNSCCs cells can promote angiogenesis by both interacting with epithelial cells and modulating TAMs chemotaxis for pro-angiogenic functions. 52 OSCC-derived exosomal thrombospondin 1 (THBS-1) activates an M1-like macrophage through p38, Akt, and SAPK/JNK signaling, which promotes cancer progression. 53 M1-like TAMs enhance the OSCC epithelial–mesenchymal transition (EMT) and cancer stem cell formation through the IL-6/Jak/signal transducer and the activator of transcription 3 (Stat3)/THBS-1 axis. 54 Furthermore, oral cancer cells are closely associated with the conventional oncogenic M2 macrophages through multiple pathways. 50 OSCC cancer stem cell-derived exosomes polarize TAMs into M2 macrophages by the urothelial carcinoma-associated 1 (UCA1) secretion targeting LAMC2-PI3K/AKT signaling pathway. These exosomes also suppress anti-tumor immunity, including CD4 + T cells activation and interferon-γ (IFN-γ) production. 55 In addition, OSCC cancer cells secrete exosome-enclosed cargos, inducing M2 macrophages. MiR-29a-3p, a member of the miR-29 family that significantly increases in OSCCs, 56 exerts effects on M2 polarization through the suppressor of cytokine signaling 1 (SOCS1)/signal transduction and the transcriptional activator (STAT) pathway. 57 The CKLF-like MARVEL transmembrane domain-containing 6 (CMTM6) 58 and heat shock protein-90 (HSP-90) 59 are important proteinic influencers of M2 macrophage conversion, indicating novel crosstalk between cancer cells and immune-modulation. ER stress, a functional proteinaceous response that reacts to cellular events like oncogenesis, drives OSCC cells to secrete exosomal programmed death ligand 1 (PD-L1) and activate the M2 polarization of TAMs. 60 Besides TAMs, T cells are also important immune regulators in OSCCs. T-effector (Teff) cells and T-regulatory (Treg) cells are the two main classifications of T cells. 61 Teff cells primarily execute killing functions toward pathogens or, anomaly, self-antigens. Treg cells modulate over-functioning Teff cells and maintain immune homeostasis. However, in the oncogenesis process, Treg cells may lead to immune evasion. 61 In OSCCs, exosomal circular RNA circ_0069313 could increase the PD-L1 expression in cancer cells with miR-325-3p sponging and interact with Treg cells. Thus, the Teff cells are suppressed, while the Treg cells are activated, resulting in the immune escaping of malignancy. 62 Post-treatment reaction The traditional non-surgical treatments for OSCCs include chemotherapy and radiotherapy. 63 However, resistance and unwilling treatment responses will impact the prognosis and mortality. Therefore, it is imperative to identify precise markers that can effectively assess the efficacy of these therapies. Chemoresistance occurs in nearly all anti-tumor drugs, and the underlying mechanism can be intrinsic (gene mutations) or acquired (TME, epigenetic alteration). 64 According to recent studies, the exosomes play a crucial role in chemoresistance of OSCCs through several pathways 65 (Fig. 1d ). Exosomal microRNAs (such as miR-21 and miR-24) derived from OSCC cell lines contribute to chemoresistance by targeting multiple signaling molecules, including STAT3 and PTEN. 65 , 66 Macrophage-derived exosomes and CAF-derived exosomal miR-196a can also reduce drug sensitivity. 67 , 68 In addition, the exosomes can influence chemoresistance by modulating the drug efflux, vesicular pH, anti-apoptotic signaling, DNA damage repair (DDR), as well as the EMT. 65 In reverse, the delivery of exosomal miR-30a and the inhibitor of exosomal miR-155 showed the ability to enhance the sensitivity of cisplatin-resistant OSCCs, 69 , 70 highlighting their potential role in improving cancer therapy. Cancer cells’ reactions toward radiotherapy are also associated with exosomes (Fig. 1d ), mainly through modulating DDR, cell death signals, and the EMT. 71 In HNSCC radiation-resistance cases, the functions of tumor-promoting exosomes are strengthened after radiation. 72 Besides resistance, the profile of exosomes in OSCCs alters in response to treatment. After surgery and/or chemo-radiotherapies, monitoring immune-related exosomal proteins (such as PD-L1) could accurately indicate the treatment reaction and recurrence possibility. 73 , 74 Melatonin, a hormone secreted by the pineal gland, plays crucial roles in multiple physiological processes. 75 The recent research has highlighted its potential function in OSCC therapy as an adjuvant, owing to its ability to inhibit tumor progression by modulating key regulators, such as MMP-9, p53, and epidermal growth factor receptor (EGFR), as well as enhancing immune functions. 76 , 77 The expression of OSCC cell-derived exosomes (miR-21 and miR-155) undergoes alterations following melatonin application, indicating their potential for assessing the treatment response and predicting the prognosis. 78 In conclusion, exosomes exhibit various characteristics during the development and prognosis of OSCCs. By improving our comprehension of these alterations, we can approach a better understanding of the enigma surrounding OSCC occurrence and conduct further investigations on therapeutic interventions. Exosomes in targeted therapy for oral diseases Over recent years, exosomes have been extensively investigated in the treatment of multiple oral diseases. The primary research areas encompass the utilization of engineered exosomes as an innovative drug delivery tool with specific cargos and the clinical application of exosomes derived from orofacial stem cells in tissue regeneration. In this session, we summarize the current research on exosomal therapies toward infections, oral cancers, and the regeneration of pulp and bone. Engineered exosomes Anti-infection Infectious pathogens play a significant role as causative agents and risk factors in various oral diseases. Recent studies have unveiled the potential of the application of exosomes as innovative therapies against microbial infections. An infection with Enterovirus 71 (EV-71) serves as the primary trigger for HFMD, leading to an elevated level of exosomes in the patients’ sera samples. 116 Consequently, the utilization of the exosome inhibitor GW4869 could effectively reduce infectious activities. 129 Exosomal miR-155 exhibits a comparable antiviral effect by targeting the phosphatidylinositol clathrin assembly protein (PICALM). 130 As the first inhabitant microbes in the oral cavity, streptococci prominently influence oral health status, where dysbacteriosis may lead to caries and other oral inflammatory-related diseases. The exosomes separated from honey contain antimicrobial agents that have more potent effects on Streptococcus mutans in comparison to those of the other strains. 131 Anti-cancer Traditional chemo-/immunotherapies for OSCCs are often non-specific to the malignancy and incompatible with the host tissue. However, exosomes, which act as physiological “packages” between cells, may offer a solution to these issues. 132 The application of engineered exosomes in OSCC treatment can disrupt various processes involved in oncogenesis and tumor microenvironment modulation, thereby effectively inhibiting cancer progression. According to recent studies, many cargos of exosomes attenuate the oncogenesis of OSCCs through complex signaling pathways 133 – 138 (Table 2 ). Engineered exosomes secreted from diverse cell types exert inhibitory effects on OSCC development through administrating different drugs or molecules. Macrophage-derived exosomal miR144/451 (tumor suppressive) connected with chitosan nanoparticles exhibit an anti-tumor effect in OSCCs. 139 The exosomes secreted by menstrual stem cells performed anti-angiogenesis in OSCCs. 140 In addition to host-derived exosomes, other researchers have also explored alternative sources of therapeutic exosomes for OSCC treatment. Milk exosomes are widely recognized for their exceptional resilience in acidic conditions within the digestive system and their ability to traverse physiological barriers. 141 The engineered exosomes of milk combined with doxorubicin and an anthracene endoperoxide derivative demonstrate remarkable efficacy in eradicating OSCCs cells, 142 showing great potential in clinical applications. Novel delivery system based on engineered exosomes Besides the dental tissue-derived and natural original exosomes mentioned above, engineered exosomes have demonstrated great value as a novel delivery system. The procedure of exosome engineering mainly consists of cargo encapsulation and surface modification, with each step encompassing various methodologies and indications. 143 Exosomal cargo packing could be induced in situ by interactions between the cargos and donor cell components or in vitro after exosome purification. 132 Generally, the in vitro methods show more flexibility and practicality in applications, including electroporation, incubation, sonication, extrusion, etc. 80 In OSCC treatment, Epstein–Barr Virus Induced‐3 (EBI3) transfected fibroblasts were electroporated with anti-tumor small interfering RNAs (siRNAs), the productive engineered exosomes of which significantly targeting OSCCs cells by diminishing their proliferations. 144 The incubation of miRNA-34a with HEK-293T cells also acquires effective exosomes against OSCCs. 137 Surface modification is another important step in exosome engineering, aiming at enhancing exosomal targeting toward certain receptors. Multiple components can be added to the exosomal membrane, such as proteins, antigens, antibodies, and DNA/RNA aptamers. 132 The relevant research has proved that the surface-modified exosomes with peptides can cross blood–brain barrier and treat cerebral ischemia. 145 , 146 Although similar research on oral medicine is underway. However, exosome-mimetic nanoparticles have received great attention in oral cancer treatment for their convenience in surface engineering. 147 , 148 These biomimetic particles could resemble membrane structures of multiple host cells (blood and stem cells) and escape from immune clearance. 148 Dental stem cell-derived exosomes in regenerative therapy Dental stem cells (DSCs) refer to a group of primitive cells derived from dental tissue, with the potential to proliferate and differentiate. DSCs are generally classified into dental pulp stem cells (DPSCs), stem cells from human exfoliated deciduous teeth (SHED), stem cells from apical papilla (SCAPs), PDLSCs, dental follicle cells (DFCs), and oral mesenchymal stem cells (OMSCs), based on their distinct histologic origin. 149 – 151 The application of DSCs in oral regeneration treatment has long been embraced, and stem cell-derived exosomes have recently shown great promise for healing dental defects and orofacial tissues. Pulp regeneration Due to infectious or traumatic etiologies, pulpal and/or apical diseases invariably result in the irreversible impairment of blood, neural, and nutrient supplies to the natural teeth. 152 Despite the well-established efficacy of root canal treatment (RCT), the quest for achieving biological pulp regeneration with complete physiological functionality remains ceaseless. There are a series of crucial steps in achieving dental pulp regeneration and forming a physiological pulpodentinal complex, for instance, differentiation from MSCs to functional dental pulp cells (DPCs), the promotion of angiogenesis, and the facilitation of neural reconstruction. 153 Such as stem cells from pulp tissue, DPSC-derived exosomes positively stimulated the differentiation of stem cells toward DPCs through the P38/MAPK 154 and miR‐150‐Tlr4 pathways. 155 Meanwhile, Schwann cells are recruited to enhance neurogenesis with the presence of DPSC-derived exosomes, particularly under the condition of lipopolysaccharide (LPS) stimulation. 156 LPS also promotes angiogenesis via DPSC-derived exosomes, 157 – 159 which simultaneously could be enhanced by hypoxia with higher level of lysyl oxidase-like 2 (LOXL2). 160 , 161 Compared with a normal status, DPSCs under odontogenic differentiation condition secrete more effective exosomes, for instance, the levels of miR-27a-5p are elevated, which induces DPSC differentiation. 154 , 162 Furthermore, the evidence suggested that younger donors of DPSCs gave better performance to exosomal ability in pulp regeneration, 163 as exosomal miR-26a secreted by aggregating stem cells from deciduous teeth (SHED) strongly promotes the angiogenesis of HUVECs in pulp tissue through TGF-β/Smad2/3 signaling. 164 Moreover, the exosomes derived from dental pulp tissue (DPT) exhibit superior efficacy in modulating SCAPs for pulp regeneration compared to that of the DPSCs, which is attributed the “cell-homing technique“. 165 SCAPs can also release exosomes, facilitating an anti-inflammatory effect on pulpitis during Treg conversion and the dentinogenic differentiation of MSCs, 166 , 167 which demonstrate great potential as pulp regenerative therapies. Besides the DSCs, there are several other stem cells that secrete functional exosomes in pulp regeneration. Embryonic stem cell (ESC)-derived exosomes promote DPCs maturation through CD73 (a type of nucleotidase)-mediated AKT/ERK pathway activation. 168 Furthermore, the exosomes from umbilical cord mesenchymal stem cells (UCMSCs) showed a great effect on inflammatory alleviation after a pulp injury. 169 And platelet-sourced exosomes also have the potential for pulp regeneration with thrombin activation. 170 Orofacial bone regeneration The conventional therapeutic sequence for periodontitis encompasses plaque control, re-evaluation, and surgical intervention. Regenerative surgery has emerged as a pioneering approach in clinical practice, aiming to restore periodontal tissue and regain functions. 171 Alongside various biofilm and bone graft materials, recent studies have highlighted the potential of exosomal agents for orofacial bone reconstruction. 172 Controlling the anomaly inflammatory changes in periodontal cells and the microenvironment is the premise of periodontitis regenerative treatment. 11 Exhibiting periodontal anti-inflammatory effect, gingival mesenchymal stem cell (GMSC)-secreted exosomes target NF-κB signaling and Wnt5a in a periodontal microenvironment 173 , 174 and modulate macrophage polarization in high-lipid-level 175 or TNF-α pre-condition circumstances. 176 A similar macrophage transformation also occurs with chitosan hydrogel-engineered DPSC-derived exosomes via miR-1246. 177 In addition, MSC-derived exosomal miR-1246 178 and PDLSC-derived exosomal miR-155-5p 179 /miR-205-5p 180 inhibit inflammation by balancing the Th17/Treg ratio. Alveolar bone loss is a typical manifestation of periodontitis. How to promote bone repair and regeneration is a key issue in periodontitis management. PDLSCs are a group of stem cells residing in the periodontium. The available evidence strongly supports that PDLSCs possess a robust self-renewal capacity and multipotential differentiation abilities. In periodontal regeneration, PDLSCs can differentiate into fibroblasts, osteoblasts, cementoblasts, etc. 181 During these processes, various stem cells become the sources for exosomes, facilitating PDLSC proliferation and differentiation. Bone marrow mesenchymal stromal cell (BMSC)-derived exosomes have been applied with hydrogel in vivo, 182 and SHED-derived exosomes were tested in vitro, 183 both of which showed a promising effect on PDLSCs proliferation, migration, and differentiation. DFC-derived exosomes exhibited a higher efficiency with LPS stimulation through an ROS-mediated antioxidant mechanism in PDLSCs. 184 , 185 UCMSC- and PDLSC-derived exosomes are able to activate PDLSCs’ functions even in high-glucose-level circumstances. 186 – 188 The application of MSCs enhances periodontal ligament (PDL) cell activation after impairment via exosomes through the AKT/ERK pathway. 189 In addition, adipose-derived stem/stromal cells (ADSCs) and DFCs exosomes performed a periodontal healing function in murine periodontitis models with newly formed PDL and alveolar bone. 190 , 191 Nevertheless, there is a paucity of data related to the underlying mechanisms and applications in human models. In addition to enhancing the differentiation of PDLSCs, there are also other methods used to promote orofacial bone regeneration, such as the direct activation of osteoblasts and the induction of BMSC osteogenesis. PDLSC-derived exosomes are capable of inducing osteoblast activation, 192 while osteogenic-induced and differentiated PDLSCs can accelerate BMSC differentiation toward osteoblasts via significant exosomal miRNAs alteration, targeting various osteogenic-related signaling pathways, such as the MAPK and AMPK pathways. 193 In addition, DPSC-derived exosomes induced jaw bone regeneration in vivo, 194 and SHED-derived exosomes are capable of promoting naïve BMSCs’ differentiation into osteoblasts. 195 – 197 While SHED-derived exosomes can promote DPSCs’ osteogenesis by regulating the mitochondrial transcription factor A (TFAM). 198 To strengthen the bone repair effect, BMSCs can be innovatively engineered with overexpressed bone morphogenetic protein 2 (BMP2) or miR-26a cargo. These functional modifications significantly improve bone regeneration through the exosomes, targeting the BMP2-associated signaling cascade/mTOR pathway. 199 , 200 Moreover, immune modifications performed by engineered exosomes also promote bone regeneration. Dendritic cell-derived exosomes loaded with IL-10 and TGF-β can inhibit immune-related bone resorption and suppress bone loss. 201 The exosomes secreted by M2 macrophages can be engineered with melatonin, exhibiting anti-inflammatory behavior and rescuing PDLSC potency in differentiation. 202 Besides periodontitis, there are also other oral diseases characterized by bone destruction that necessitate exosomal regenerative therapies. Osteoarthritis (OA) is a common bone degenerative disease that mainly occurs in joints with cartilage degradation. 203 The temporomandibular joint (TMJ), as the key joint enabling mandible movement, significantly influences chewing and pronouncing functions. Therefore, temporomandibular joint osteoarthritis (TMJOA) causes severe pain and inconvenience among patients. 204 Similar to the mechanism of orofacial bone regeneration, the aims of exosomal therapies for TMJOA are reducing the inflammatory response and inducing chondrocyte differentiation. 205 The SHED-derived exosomal miR-100-5p downregulates the inflammatory factors (IL-6, IL-8, and MMP1) in TMJOA by targeting mTOR signaling. 206 Moreover, MSC-derived exosomes enhanced the overall cartilage regeneration, and this mechanism is associated with the adenosine activation of the AKT, ERK, and AMPK signaling pathways. 205 Salivary gland revitalization Exosomal regenerative therapies have also been developed to treat other oral diseases. The dysfunction of the salivary gland may occur in Sjogren’s syndrome, menopause, diabetes, or after radiotherapy for OSCC patients. In vivo studies of exosomal therapies for salivary gland recovery have been conducted using murine models. The DPSC-derived exosomes rescued salivary gland epithelial cells through the G-protein coupled estrogen receptor (GPER)-mediated cAMP/PKA/CREB pathway in Sjogren’s syndrome. 207 And tonsil mesenchymal stem cell (T-MSC) exosomes contribute to the regaining of salivary gland function after an ovariectomy, resembling the menopause period. 208 The application of BMSC-derived exosomes could reduce the salivary gland complications in diabetes via the TGF-β/Smad3 pathway, 209 while the exosomes from the salivary gland performed a similar effect via an unclear mechanism. 210 Urine-derived stem cells (USCs) under hypoxia stimuli secrete exosomes to repair the salivary gland after radiotherapy via the Wnt3a/GSK3β pathway. 211 Skin regeneration based on anti-aging effect Skin senescence is a progressive process, with the declining proliferation of cells, reducing ECM, and decreasing repair ability resulting in skin dysfunction. Both intrinsic and extrinsic factors (smoking/ultraviolet light) could influence the skin senescence procedure. 212 This issue has garnered significant public attention, particularly in the orofacial area, due to its profound impact on patients’ esthetic appearance and functional needs. Novel research has proved the potential applications of stem cell-derived exosomes in skin regeneration based on their anti-aging effects. The dermis, the layer of skin under the epidermis, mainly consists of the ECM, which is regulated by dermal fibroblasts. As a long-lived cell type, dermal fibroblasts can be used to indicate the skin senescent status through accumulated damage and repair. 213 Induced pluripotent stem cell (iPSC)-derived exosomes exhibit significant anti-aging effects on dermal fibroblasts, which manifests as the downregulated level of senescence-associated-β-galactosidase (SA-β-Gal) and MMP1/3 and the restoration of collagen type I. 214 In aged murine models with wounds, the exosomes isolated from young donor wound edge fibroblasts can facilitate fibroblasts differentiation through miR-125b, inhibiting sirtuin 7 (Sirt7). 215 Similarly, trophoblast-derived exosomes can activate dermal fibroblasts as well. 216 Wound healing is an intricate process including an inflammatory response, stem cell differentiation and proliferation, ECM modulation, etc. 217 Senescent skin cells can perform SASP, inducing vicinal inflammation and postponing the healing process. 218 A pressure ulcer, defined as the localized damage of skin tissue due to a combination of shear and friction, 219 commonly appears in the orofacial area. A recent survey has suggested the high incidence of facial pressure ulcers in patients with respiratory destruction (such as COVID-19) due to staying prone. 220 ESC-derived exosomes can rejuvenate epithelial cells and promote the angiogenesis process in aged murine models of pressure ulcers. This mechanism is associated with enriched miR-200a cargo and activated nuclear factor-like 2 (Nrf2) signaling. 221 Besides the aging factor, the SASP also plays a role in several endocrine diseases, including diabetes. 222 Diabetic wounds commonly appear on oral soft and hard tissues, which struggle to heal, leading to great suffering. 223 Therefore, diabetic wound healing requires anti-aging therapies as well, and stem cell-derived exosomes can reduce the SASP. ADSC-derived exosomes accelerated diabetic wound healing, and Nrf2 overexpression enhanced this effect. 224 A novel biomaterial, oxygen-releasing, antioxidant wound dressing, OxOBand, loaded with ADSC-derived exosomes has been applied in murine diabetic models and shown great performances. 225 Fetal mesenchymal stem cells (fMSC) can also promote diabetic wound healing through exosomes. 226 Of note, dental stem cells, such as SHED-derived exosomes, have been used for tendon regeneration, with a significant anti-aging effect through NF-κB inhibition, 227 which has encouraged us to expand the application of oral original exosomes into other fields. Scaffolds for exosomes in oral regenerative therapy In addition to exploring the novel sources of exosomes for oral tissue regeneration, it is crucial to consider appropriate scaffolds that interact synergistically with the exosomes in order to optimize the therapeutic efficacy. According to previous studies on pulp regenerative treatment with stem cells, an injectable hydrogel is convenient as a biomaterial applied to the root canals. Different types of scaffolds (such as natural collagen-based scaffolds and synthetic/hybrid materials) with injectable hydrogel have been investigated. 228 In terms of the scaffolds loaded with exosomes, we should widen our scope to meet the new demands for exosomal applications. Generally, DPSC-derived exosomes can bind to collagen type I and fibronectin, thereby connecting with the biomaterials and promoting DPSC differentiation. 154 However, these findings were not completed with a certain implementable biomaterial system. Furthermore, the hydrogels engineered with hydroxypropyl chitin (HPCH)/chitin whisker (CW) and the hydrogels with fibrin can both facilitate attraction between the exosomes and MSCs, showing injectable and biocompatible behaviors, ultimately accelerating the exosomes’ effect on pulp regeneration. 229 , 230 The controlled releasement of exosomes is also a promising prospect for bio-scaffolding. Poly(lactic-co-glycolic acid) (PLGA)-based biodegradable microspheres have been recently developed to have continuous exosomal effects on pulp regeneration. 231 In orofacial bone regeneration, the traditional scaffolds mostly focus on mimicking the extracellular matrix (ECM) of natural bones, aiming at enhancing MSC adhesion and osteogenic differentiation. 232 With a further understanding of the role of exosomes in bone regeneration, new demands for bio-scaffolds are emerging in cell-free therapies. Lyophilized BMSC-derived exosomes on hierarchical mesoporous bioactive glass (MBG) can satisfy both bioactive maintenance and the continuous releasement of exosomes. 233 In vitro experiments also proved that titanium nanotubes loaded with BMP2-stimulated macrophage-derived exosomes upregulate osteogenic marker (such as alkaline phosphatase) expression. 234 As a biodegradable polymer that has been widely accepted in controlled delivery, 235 PLGA has a great performance in exosomal bone regeneration. 236 Poly-dopamine (pDA)-modified PLGA can ensure the controlled release of exosomes from adipose-derived stem cells (ADSCs), significantly enhancing skull bone repair in murine models. 237 Combined with metal-organic framework (MOF), the PLGA/Exo-Mg 2+ -gallic acid (GA) system provides the advantages of ADSC-derived exosomes, Mg 2+ and GA in the anti-inflammation, angiogenesis, and osteogenic differentiation of bone regeneration. 238 Moreover, adding VEGF and DPSC-derived exosomes to an injectable chitosan nanofibrous microsphere-based PLGA-poly(ethylene glycol) (PEG)-PLGA hydrogel strongly promotes angiogenesis and osteogenesis. 239 In recent decades, the production of three-dimensional (3D) scaffolds has been widely used in exosomal regenerative medicine. 240 Three-dimensional-printed silk fibroin/collagen I/nano-hydroxyapatite (SF/COL-I/nHA) scaffolds loaded with UCMSC-derived exosomes could stimulate alveolar bone defect repair in murine models. 241 In addition, novel scaffolds can also enhance cartilage regeneration. Lithium-substituted bioglass ceramic (Li-BGC) significantly promoted the BMSC-derived exosomal effect on chondrogenesis. 242 Based on the convincing evidence that DSC-derived exosomes contribute to various oral regenerative therapies, more research is underway. The expansion of MSC-derived exosomes from other tissue origins may benefit oral therapies. And the crosstalk between oral and other diseases, such as general OA 243 and TMJOA, should be highlighted. Overall, the application of exosomes is one of the key points in oral regenerative treatment. Basic-to-clinic translation is one of the future focuses.

Acknowledgements This work was supported by the National Natural Science Foundation of China Grants (82370945, 82171001, 82222015 and 82370915). Research Funding from West China School/Hospital of Stomatology Sichuan University (RCDWJS2023-1). Figures were created with BioRender.com. Author contributions J.W. and Y.F. organized the manuscript. J.W. wrote the draft. J.J., C.Z. and Y.F. reviewed and edited the manuscript. All authors have read and approved the article Competing interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:41:59

Int J Oral Sci. 2024 Jan 15; 16:4

oa_package/d5/9a/PMC10788352.tar.gz

PMC10788353

37852616

Introduction Hypoxia is a state of oxygen deficiency commonly observed in most cancers. Tumor hypoxia causes the formation of blood vessels, enhancing the potential for metastasis. Previous studies revealed that hypoxia strongly induces vascular endothelial growth factor (VEGF) expression [ 1 ]. Angiogenesis is the process of creating new blood vessels from pre-existing vessels. Through this process, cells receive blood containing oxygen and nutrients for growth. Moreover, as the degree of angiogenesis increases in primary tumors, the prognosis worsens [ 2 ]. VEGF-VEGF receptors, well-known as key angiogenic factors, have been shown to play crucial roles in tumor initiation, progression, and metastasis. Despite ongoing efforts to investigate association between hypoxia and genes that promote angiogenesis, no studies have been conducted using VEGF family genes across pan-cancer. The VEGF family comprises VEGFA , VEGFB , VEGFC , VEGFD , and placental growth factor ( PGF ), and they differ in function and expression. For a few cancers, overexpression of VEGF family genes and their correlation with the prognosis, metastasis, and recurrence have been reported. Compared to low expression, high VEGFA expression is associated with poor survival outcomes in gastric cancer [ 3 ], lung cancer [ 4 ], and colon cancer [ 5 ]. VEGFB facilitates tumor advancement by elevating plasminogen activators, which can lead to the metastasis of breast cancer [ 6 ]. The expression of VEGFC and VEGFD correlates with recurrence in head and neck squamous cell carcinomas [ 7 ] and lymphatic metastases in gastric cancer [ 8 ], respectively. Previous study reported that up-regulated PGF is associated with lymph node metastases and serosal invasion in gastric cancer [ 9 ]. Despite the potential involvement of the VEGF family genes in various tumor-related pathways, little is known of their roles in the tumor microenvironment (TME) and their impact on tumor hypoxia across pan-cancer. Therefore, the link between expression of the VEGF family genes and hypoxia, prognoses, immune subtypes, and pharmacological activity should be explored. Here, we comprehensively analyzed the expression patterns of VEGF family genes and their association with hypoxia scores, survival rates, immune subtypes, TME, and responses to chemotherapy in 33 cancers.

Methods Data collection Pan-cancer data were downloaded (September 2022) from the UCSC Xena website ( http://xena.ucsc.edu/ ). RNA-sequencing gene expression data (HTSeq-FPKM), micro-RNA (miRNA) expression data, survival data, clinical data, and immune subtypes were obtained from the Cancer Genome Atlas (TCGA) database. Data from TCGA comprised 11,057 samples from 33 cancers. The TCGA abbreviations and the detailed sample information, including tumor stage, and the number of tumor and normal samples, were summarized in Supplementary Table 1 . Gene expression analysis The average expression of VEGF family genes was estimated in 33 cancers with average of each cancer type. To compare the expression of VEGF family genes between tumors and normal tissues, we performed the Wilcoxon signed-rank test on 18 cancers which have more than five normal samples. The p-value was adjusted with Benjamini-Hochberg method and adjusted p-value < 0.05 was considered as significant. We estimated the expression correlation between the VEGF family genes using Spearman’s correlation method. Survival and tumor stage analysis The patients were divided into two groups, high expression and low expression, based on the median expression level of each VEGF family gene. To analyze the prognostic differences between two groups, we used the “survival” and “survminer” R package to draw the Kaplan-Meier survival curves. The log-rank test was used to assess significance at p < 0.05. We explored the association between the expression of VEGF family genes and overall survival using univariate Cox proportional hazards regression. Moreover, the association between tumor stage and the expression of VEGF family genes was analyzed using the Kruskal-Wallis test and Benjamini-Hochberg p-value correction. Adjusted p-value < 0.05 was considered as significant. Hypoxia analysis Tumor hypoxia was quantified using published gene signatures in 20 cancers [ 10 ]. The mRNA data of the genes in the hypoxia signature were extracted from each cancer and combined as a single cohort to compare hypoxia across cancers. According to Bhandari et al. [ 10 ], cancers with mRNA abundance values in the top 50% for each gene signature were assigned a score of +1. Cancers with mRNA abundance values in the bottom 50% for that gene were assigned a score of –1. Using the Spearman correlation method, we demo nst rated an association between hypoxia and the expression of VEGF family genes and miRNAs targeting them from all tumor samples of each cancer type. Immune and TME analysis Six immune subtypes, namely C1 (wound healing), C2 (interferon-γ dominant), C3 (inflammatory), C4 (lymphocyte-depleted), C5 (immunologically quiet), and C6 (transforming growth factor β [TGF-β] dominant), were identified using the global transcriptomic immune classification of solid tumors [ 11 ]. Because each immune subtype has various clinical and biological characteristics, understanding how the expression of VEGF family genes relates to the immune subtype affects cancer treatment determination is important. To analyze the relationship between the expression of VEGF family genes and the six immune subtypes, we performed differential expression analysis by using the Kruskal-Wallis test and Benjamini-Hochberg adjustment. Adjusted p < 0.05 indicated statistical significance. To investigate the TME which consists of tumor cells and normal cells, such as stromal and immune, the ESTIMATE algorithm and Spearman’s correlation method were used to examine correlation between tumor purity and the expression of VEGF family genes from all tumor samples of each cancer type. By the ESTIMATE algorithm [ 12 ], the gene expression levels of a specific sample were normalized based on their ranks, and an enrichment score was generated by summing the difference of the empirical cumulative distribution functions (CDFs) of the signature genes and those of the remaining non-signature genes according to [ 13 ]. For a given signature S with n S genes and a single sample T , the n genes in the data set are assigned ranks based on their absolute expression levels and ordered by their rank from highest ( nst ) to lowest (1 st ), represented as L = { r 1 , r 2 , ..., r n }. An enrichment score ES ( S , T ) is obtained by summing the difference between the weighted empirical CDF of the signature genes and the empirical CDF of the non-signature genes P n S . When calculating the , α was set to 0.25 to apply an appropriate weight to the ranks. where and Drug sensitivity analysis Transcripts and compound activity data were downloaded from the CellMiner database ( https://discover.nci.nih.gov/cellminer/ ) that contains 60 human cancer cell lines (NCI-60). Raw data were processed using “impute” R package. Pearson’s correlation analysis was used to explore the correlation between the expression of VEGF family genes and drug sensitivity. Drugs used in clinical trials and Food and Drug Administration–approved drugs were included.

Results Expression patterns of VEGF family genes To understand the role of VEGF family genes in human cancers, we examined their expression patterns across 33 cancers. VEGFB has the highest gene expression level, and VEGFD has the lowest gene expression level ( Fig. 1A ). All expression pairs of VEGF family genes showed positive correlations, suggesting potential common features in biological functions and structures ( Fig. 1B ). The strongest positive correlation was observed between VEGFC and PGF (r = 0.34). Differential expression analysis of each VEGF family gene was performed in 18 cancers which have more than five normal samples. A higher expression of VEGF family genes, except VEGFD , was observed in tumor tissues than in normal tissues across most cancers ( Fig. 1C – H ). Notably, up-regulated VEGFA and PGF were observed in 15 cancers, with the highest differences observed in kidney renal clear cell carcinoma (KIRC) ( Fig. 1C ). The expression of VEGFD tended to be down-regulated in most cancers, except Cholangiocarcinoma (CHOL) and liver hepatocellular carcinoma (LIHC). Moreover, VEGFA , VEGFB , VEGFC , and PGF expression was significantly increased in CHOL, head and neck squamous cell carcinoma (HNSC), KIRC, and LIHC tumor tissues. LIHC was the only cancer with significant up-regulation of all VEGF family genes. Clinical correlation of VEGF family genes To predict whether the expression of VEGF family genes promotes or inhibits cancer, we performed a survival analysis in 33 cancers. Kaplan-Meier survival curves and univariate Cox proportional hazard ratio were used to investigate the relationship between the expression levels of VEGF family genes and patients' overall survival ( Supplementary Table 2 , Supplementary Fig. 1 ). Each VEGF family gene showed significant associations with cancer prognosis in at least four cancers (p < 0.05). The expression of VEGFA , VEGFC , and PGF showed significant associations with poor prognosis in six different cancers (p < 0.05) ( Supplementary Fig. 1 ): VEGFA played a damaging role in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), colon adenocarcinoma (COAD), kidney renal papillary cell carcinoma (KIRP), brain lower grade glioma (LGG), LIHC, and prostate adenocarcinoma (PRAD); VEGFC played a damaging role in HNSC, LGG, lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), mesothelioma (MESO), and stomach adenocarcinoma (STAD); and PGF played a damaging role in adrenocortical carcinoma (ACC), KIRP, LIHC, Rectum adenocarcinoma (READ), STAD, and uveal melanoma (UVM). By contrast, the expression of VEGFB and VEGFD was related to a better prognosis across the three cancers: VEGFB was a favorable prognostic factor for esophageal carcinoma (ESCA), pancreatic adenocarcinoma (PAAD), and sarcoma (SARC); and VEGFD was a favorable prognostic factor for LUAD, PAAD, and SARC. Significant prognostic differences were observed in LGG based on the expression levels of three VEGF family genes. In LGG, high expression of VEGFA and VEGFC was significantly associated with worse prognosis, while high PGF expression was significantly associated with a better prognosis. Moreover, we analyzed the relationship between the tumor stage and the expression of VEGF family genes. Cancers exhibiting a statistically significant difference (adjusted p < 0.05) in at least three VEGF family genes are shown in Fig. 2 . In KIRC, the expression of PGF was significantly associated with the tumor stage ( Fig. 2A ). In KIRP, VEGFA , VEGFC , and PGF were differentially expressed across tumor stages. Except for VEGFB and VEGFD , the genes showed an increasing tendency in gene expression from stages I to IV in KIRP ( Fig. 2B ). In STAD, the expression of VEGFB , VEGFC , and PGF showed the highest expression in stage II ( Fig. 2C ). In Thyroid carcinoma (THCA), most of the VEGF family genes, except VEGFC , were differentially expressed in different tumor stages ( Fig. 2D ). Therefore, the expression of VEGF family genes across different tumor stages may be used to estimate potential cancer progression. Association with hypoxia of VEGF family genes and its targeting miRNAs Hypoxia, a precursor for angiogenesis, plays an important role in cancer progression and affects TME [ 14 ]. We investigated the correlations between the expression of VEGF family genes and hypoxia scores in 20 cancers ( Fig. 3 ). High expression of VEGFA is positively correlated with hypoxia scores in most tumors, indicating a potential correlation with tumor aggressiveness. By contrast, the expression level of VEGFD is negatively correlated with the hypoxia score, suggesting VEGFD is mainly expressed during normoxia. Overall, VEGFA showed strong positive correlations with hypoxia compared to other VEGF family genes ( Fig. 3A – E ). VEGFC showed positive correlations with all hypoxia scores in LUAD ( Fig. 3C ). VEGFD showed strong negative correlations with most of the hypoxia scores in Bladder urothelial carcinoma (BLCA), LUAD, and PAAD ( Fig. 3D ). PGF showed positive correlations with hypoxia scores across most cancers ( Fig. 3E ). Correlation analysis was performed to explore the association between the Buffa hypoxia score and the expression of miRNAs targeting VEGF family genes ( Supplementary Fig. 2 ): Hsa-miR-101-3p targeting VEGFA and VEGFC was the only miRNA that showed a negative correlation with hypoxia in all cancers ( Supplementary Fig. 2A and 2C ); Hsa-miR-130b-5p targeting VEGFB showed positive correlations across most cancers, except for pheochromocytoma and paraganglioma (PCPG) and THCA ( Supplementary Fig. 2B ); Hsa-miR-940 targeting VEGFB was positively correlated with hypoxia in most cancers, except for BLCA and THCA; Hsa-miR-218-5p targeting VEGFC showed negative correlations with hypoxia in 18 cancers ( Supplementary Fig. 2C ); and hsa-miR-335-5p targeting VEGFD was positively correlated with hypoxia in 15 cancers ( Supplementary Fig. 2D ). Immune correlation of VEGF family genes To identify the associations between the expression of VEGF family genes and immune components in tumor, correlation analysis was performed. Across multiple cancers, VEGFB was highly expressed in six immune subtypes than other VEGF family genes ( Fig. 4A ). In BRCA, VEGF family genes except VEGFA showed high expression in C3 and C6 ( Fig. 4B ). In STAD, VEGFD showed the highest expression in C3 ( Fig. 4C ). In testicular germ cell tumors (TGCT), all VEGF family genes showed the lowest expression in C2 ( Fig. 4D ). The TME plays crucial roles in tumor initiation, progression, and metastasis [ 15 ], so we investigated the relationship between the expression of VEGF family genes and the scores related to immune infiltration. Notable positive associations between stromal, immune, and ESTIMATE scores and VEGFC were observed in most cancers ( Fig. 4E – G ). VEGFA and PGF levels were inversely associated with these scores in most cancers. Drug sensitivity of VEGF family genes To investigate the relationship between the responsiveness of more than 200 chemotherapy drugs in NCI60 cancer cell lines and the expression of VEGF family genes, correlation analysis was conducted (p < 0.01) ( Supplementary Fig. 3 ). VEGFA expression was strongly and positively correlated with sensitivity to SAR-125844 (r = 0.66), abiraterone (r = 0.56), BLU-667 (r = 0.56), AZD-3229 (r = 0.56), and itraconazole (r = 0.46) ( Supplementary Fig. 3A ). VEGFC expression was distinctively correlated with good responses to JNJ-3387618 (r = 0.65), JNJ-38877605 (r = 0.57), staurosporine (r = 0.55), BLU-667 (r = 0.51), momelotinib (r = 0.51), dimethylfasudil (r = 0.5), zoledronate (r = 0.47), telatinib (r = 0.48), and dastinib (r = 0.47) ( Supplementary Fig. 3B ). 7–Hydroxystaurosporine showed a negative correlation with VEGFC expression (r = –0.35).

Discussion In this study, we aimed to explore the potential oncogenic roles of VEGF family genes across pan-cancer through sophisticated bioinformatic analyses. We observed heterogeneity in the expression patterns of VEGF family genes across different cancers. Except for CHOL and LIHC, VEGFD was down-regulated in 16 cancers. However, VEGFA and PGF were up-regulated in tumor tissues across most cancers including BRCA and HNSC (p < 0.001). The literature has reported that VEGFA expression was significantly increased in breast cancer and head and neck cancer [ 16 , 17 ]. In survival analysis, the expression of VEGF family genes was closely related to patients' survival; thus, these genes may be potential clinical prognostic indicators. Our findings showed the associations between the high expression of VEGFA , VEGFC , and PGF and poor prognosis across various cancers, suggesting that they may serve as risk factors for tumor progression. Increased expression of VEGFA and PGF was linked to poor prognosis in KIRP and LIHC. There is evidence that serum VEGFA levels are associated with poor prognosis in LIHC [ 18 ]. In addition, increased VEGFA and VEGFC were linked to poor prognosis in LGG. Another study revealed that inhibition of VEGFA prolongs the survival of patients with glioblastoma [ 19 ]. Furthermore, high expression of VEGFC and PGF was correlated with poor prognosis in STAD, supported by Li and Han [ 20 ]. We demo nst rated an association between expression of VEGFB and VEGFD and favorable prognoses in multiple cancers, including PAAD and SARC. Notably, we are the first to demo nst rate these results. Across tumor stages, VEGFA , VEGFC , and PGF exhibited an increasing expression tendency as the tumor stage advanced. In STAD, these genes showed a lower expression in stage I than in the other stages. Because the stage number indicates the extent of cancer spread, these results suggest that the expression of these genes is a clinicopathological marker. Our investigation of this correlation with hypoxia provides insights into the potential role of VEGF family genes in driving malignant processes. For 20 cancers, the expression of VEGFA was positively associated, except for KIRC, PRAD, and THCA. This finding is supported by the literature indicating that hypoxia induces VEGFA expression [ 21 ]. Moreover, PGF exhibits a strong positive correlation with hypoxia in many cancers, including ovarian serous cystadenocarcinoma (OV). Previous study reported that epithelial ovarian cancer patients with high PGF expression show poor chemotherapy response and unfavorable prognosis [ 22 ]. We observed a distinct negative correlation between VEGFD expression and hypoxia across most cancers, but no study has established this finding. Furthermore, we investigated the correlation between hypoxia scores and miRNAs targeting VEGF family genes. Hsa-miR-101-3p targeting VEGFA showed a negative correlation with hypoxia scores across most cancers, including LUAD and LUSC, suggesting its role as a tumor suppressor. This finding was supported by a finding in the literature that hsa-miR-101-3p inhibited VEGFA expression, which mediates invasion of lung cancer cells [ 23 ]. Hsa-miR-101-3p, which also targets VEGFC , was negatively correlated with hypoxia in LIHC. Another study revealed that hsa-miR-101-3p inhibited cell migration by suppressing VEGFC expression in hepatocellular carcinoma [ 24 ]. Moreover, hsa-miR-130b-5p targeting VEGFB exhibited a positive correlation with hypoxia in various cancers including BRCA and LUAD. Its involvement in hypoxia by regulating VEGFB has not been demo nst rated. Consistent with the positive association between hsa-miR-940 expression and the hypoxia score shown in this study, hsa-miR-940 overexpression was correlated with tumor progression in gastric cancer, pancreatic carcinoma, and ovarian cancer [ 25 - 27 ]. We observed a negative correlation between hsa-miR-218-5p expression and hypoxia score in LUAD. Another study demo nst rated that enhanced expression of hsa-miR-218-5p inhibited cell viability and migration in LUAD [ 28 ]. We observed that VEGF family genes were significantly correlated with the immune subtypes. In STAD, the expression of VEGFC and PGF was high in aggressive immune subtype C6 (TGF-β dominant), which is related to poor prognosis. These findings are consistent with our survival results, and the results of another study demo nst rating that hypoxic tumor cells promote TGF-β activation, which has a tumor-promoting effect [ 29 ]. A consistently high expression of VEGFC in stromal, immune, and ESTIMATE scores indicated lower tumor purity. We observed that VEGFC was associated with poor prognosis across multiple cancers. Studies have demo nst rated an association between low tumor purity and poor prognosis across various cancers [ 30 , 31 ]. The association between the VEGF family genes and drug response is also notable. Increased expression of VEGFA and VEGFC enhances sensitivity to various chemotherapeutic drugs. Using integrated bioinformatics analyses, we comprehensively overviewed the roles of VEGF family genes in tumor progression and hypoxia. Because our findings were not validated by independent datasets, further validation using in vitro and in vivo experiments is necessary. The dynamics of gene families vary widely, so interpreting the overall pattern of positive correlations requires caution. Also, some VEGF family genes are included in multiple hypoxia signatures, which could lead to a bias in the correlation between hypoxia scores and expression level of VEGF family genes. Considering that the hypoxia scores were influenced by the expression levels of not only VEGFA but also other hypoxia-related genes, investigating the comprehensive relationship between the hypoxia scores and the VEGF family genes is not devoid of significance. Overall, VEGFD exhibits opposite trend compared to other VEGF family genes. Thus, further research is needed to elucidate the directionality of VEGFD 's behavior and its potential implications in hypoxia and other carcinogenic mechanisms. In this study, we systematically investigated the expression of VEGF family genes and their relationships with patients' survival, hypoxic status, immune subtypes, and drug response in a pan-cancer analysis. Although our findings require further validation from laboratory results, we have provided a detailed overview of the biological functions of VEGF family genes in hypoxia. Thus, we provide insights into the role of VEGF family genes in cancers and provide blueprints for further research on their role in hypoxic TME.

Tumor hypoxia, oxygen deprivation state, occurs in most cancers and promotes angiogenesis, enhancing the potential for metastasis. The vascular endothelial growth factor (VEGF) family genes play crucial roles in tumorigenesis by promoting angiogenesis. To investigate the malignant processes triggered by hypoxia-induced angiogenesis across pan-cancers, we comprehensively analyzed the relationships between the expression of VEGF family genes and hypoxic microenvironment based on integrated bioinformatics methods. Our results suggest that the expression of VEGF family genes differs significantly among various cancers, highlighting their heterogeneity effect on human cancers. Across the 33 cancers, VEGFB and VEGFD showed the highest and lowest expression levels, respectively. The survival analysis showed that VEGFA and placental growth factor ( PGF ) were correlated with poor prognosis in many cancers, including kidney renal cell and liver hepatocellular carcinoma. VEGFC expression was positively correlated with glioma and stomach cancer. VEGFA and PGF showed distinct positive correlations with hypoxia scores in most cancers, indicating a potential correlation with tumor aggressiveness. The expression of miRNAs targeting VEGF family genes, including hsa-miR-130b-5p and hsa-miR-940, was positively correlated with hypoxia. In immune subtypes analysis, VEGFC was highly expressed in C3 (inflammatory) and C6 (transforming growth factor β dominant) across various cancers, indicating its potential role as a tumor promotor. VEGFC expression exhibited positive correlations with immune infiltration scores, suggesting low tumor purity. High expression of VEGFA and VEGFC showed favorable responses to various drugs, including BLU-667, which abrogates RET signaling, an oncogenic driver in liver and thyroid cancers. Our findings suggest potential roles of VEGF family genes in malignant processes related with hypoxia-induced angiogenesis.

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1C1C1012288). Supplementary Materials Supplementary data can be found with this article online at http://www.genominfo.org .

CC BY

no

2024-01-16 23:41:59

Genomics Inform. 2023 Sep 27; 21(4):e44

oa_package/0b/4c/PMC10788353.tar.gz

PMC10788354

38224715

Introduction Liver cancer, a type of carcinoma, has the highest mortality rate in the world each year [ 1 ]. In 2018, there were 841,000 new cases of liver cancer, and the death toll reached 782,000 [ 2 ]. The average incidence of liver cancer and the associated mortality rate can be two to three times higher in men, particularly in certain regions of the world. According to the Global Cancer Statistics (GLOBOCAN) in 2020, liver cancer was ranked as the third most deadly cancer, responsible for 8.3% of all cancer-related deaths. In that year, there were 905,000 new cases of liver cancer, with a mortality rate of 830,000 [ 3 ]. In Indonesia, liver cancer is the second most common cancer among men, with an incidence rate of 12.4 per 100,000 of the population and an average mortality rate of 7.6 per 100,000 [ 4 ]. Factors that contribute to liver cancer include chronic infection with hepatitis B virus and hepatitis C virus, exposure to aflatoxin contamination, alcohol consumption, a history of obesity, type 2 diabetes, and smoking addiction [ 2 ]. Villanueva [ 5 ] notes that additional risk factors may exacerbate the incidence of liver cancer, including an unhealthy lifestyle, geographic conditions, gender, age, family history of the disease, and the extent of liver damage. Liver cancer is also prevalent in regions with high rates of hepatitis B infection. In these areas, the disease often manifests at a younger age, partly because hepatitis B can be transmitted vertically from mother to child during childbirth [ 6 ]. Patients often report symptoms such as fatigue, pain, diarrhea, skin abnormalities, and decreased appetite, all of which can adversely affect their quality of life [ 7 ]. Consequently, the detection of disease symptoms in liver cancer can involve examining DNA. Variations in genes may be linked to the progression and pathogenesis of diseases, including liver cancer. The genome-wide association studies (GWAS) Catalog is a resource that employs a bioinformatics approach to document genetic variations. This database contains search results for single-nucleotide polymorphisms (SNPs) and has identified several variants associated with liver fat content, circulating liver enzymes, and the development of non-alcoholic fatty liver disease, as well as genetic markers useful in predicting disease disorders [ 8 ]. Genetic identification studies in humans aim to identify inherited genetic risk factors for various conditions, including liver cancer. This study used the GWAS catalog database to map genes from genetic variations across several populations that play an essential role in the pathogenesis of liver cancer. The most significant gene variations based on their function in protein changes were further verified.

Methods In this study, we adopted the method used by Ma’ruf et al. [ 9 ] and Puspitaningrum et al. [ 10 ], as depicted in Fig. 1 . Liver cancer-associated SNPs were obtained from the GWAS Catalog database ( http://www.ebi.ac.uk/gwas ; accessed on 15-02-2023). Subsequently, we performed further analysis using HaploReg (version 4.1) applying a p < 10 -8 to account for multiple tests in the GWAS catalog. This threshold is commonly used to identify associations between common genetic variants and traits with adjacent gene expression [ 11 ]. Furthermore, to evaluate the relationships between various genetic variants and gene expression profiles, we conducted an analysis of expression quantitative trait loci (eQTLs) with data sourced from the GTEx Portal database ( http://www.gtexportal.org/home/ ; accessed on 16 Feb 2023), considering gene expression across various tissues in humans. Additionally, we confirmed the identified variants using the Ensembl Genome Browser ( https://www.ensembl.org/index.html ; accessed on 17 Feb 2023). Our study considered allele frequencies in populations from Europe, Africa, America, East Asia, and Southeast Asia. To explore the functionalities of different gene variants, we performed evaluations using the SNP nexus database ( https://www.snp-nexus.org ; accessed on 20 Feb 2023). Furthermore, epidemiological and genomic data on the prevalence of liver cancer rates were obtained from Li et al. [ 12 ]. The prevalence rates and allele frequencies of the variants in multiple continents were evaluated using IBM SPSS Statistics 25.0 (IBM Corp., Armonk, NY, USA) with the Pearson correlation test. After the procedure was evaluated, the p-values were obtained. All plots were created using line charts. A p < 0.05 was considered statistically significant in the current study.

Results and Discussion Identification of genomic variants of liver cancer This study identified SNPs associated with liver cancer from the GWAS catalog. Of these SNPs, 29 were further confirmed through SNP genotyping, as shown in Table 1 . Subsequently, HaploReg version 4.1 was utilized, applying a p-value threshold of <10 -8 based on the number of SNPs obtained. The findings presented in Table 2 indicate an increased risk associated with two genes for liver cancer. The study also analyzed tissue expression impacting liver cancer, with a focus on missense variants of PNPLA3 (patatin-like phospholipase domain-containing 3). Through our integrative bioinformatics approach, we prioritized two variants with missense mutations (rs2294915 and rs2896019) that encode the PNPLA3 gene as biological risk SNPs for liver cancer. Primary liver cancer is a pathological condition characterized by the development of malignant cells within the hepatic tissues. The development of cancer at extraneous anatomical sites that subsequently metastasizes to the liver does not constitute primary liver cancer. Primary liver cancer includes several types, such as hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma, and less common varieties like mixed hepatocellular cholangiocarcinoma, fibrolamellar HCC, and the pediatric neoplasm hepatoblastoma [ 13 ]. Gene expression of PNPLA3 across 10 human tissues The results of PNPLA3 gene expression across 10 human tissues revealed significant functional consequences of genetic variation. The highest levels of PNPLA3 gene expression were observed in the liver, sun-exposed skin (lower legs), non-sun-exposed skin (suprapubic), and adipose-subcutaneous fibroblasts and cell cultures, according to analyses of the 10 human tissues from the GTEx database ( Fig. 2 ). Additionally, we found that the SNP IDs rs2294915 and rs2896019 exhibited similar patterns of gene expression variation in sun-exposed skin (lower legs). Notably, patients with liver cancer often report that their skin appears yellow, which may be related to these findings. Further analysis indicated that the PNPLA3 gene is also highly expressed in suprapubic and underarm skin. Correlation between gene expression of PNPLA3 and eQTLs The study revealed a correlation between the gene expression of PNPLA3 and eQTLs. To identify eQTLs associated with liver cancer gene expression, we utilized the GTEx database. We identified minor alleles that are related to liver cancer, as detailed in Table 3 [ 14 ]. Notably, we discovered that several SNPs, specifically rs2294915 and rs2896019, exhibit high expression in skin tissue. The CC genotype of both rs2294915 and rs2896019 was associated with increased expression in suprapubic and underarm skin compared to the CT and TT genotypes, as shown in Fig. 3 . The research results show that the genomic database could be used to identify gene variations with significant potential in the pathogenesis of liver cancer. Liver cancer is marked by the yellowing of the eyes and skin [ 15 ]. Nessa et al. [ 16 ] note that the severity of liver disease can be gauged by the declining quality of liver function. This quality can be evaluated by measuring total bilirubin levels, serum albumin, and prothrombin time. Allele frequencies of candidate variants in populations in different continents We identified variants associated with liver cancer gene expression and conducted allele frequency analysis across various populations. As indicated in Table 4 , we evaluated the frequency of allele variants in individuals from Europe, America, East Asia, South Asia, and Africa. The allele frequencies for each SNP differed among these populations, as illustrated in Fig. 4 . Both Table 4 and Fig. 4 demonstrate that gene expression levels are higher for populations with increased frequencies of the rs2294915 (C) allele and the rs2896019 (T) allele. Specifically, the gene expression associated with the rs2294915 (C) allele was significantly higher in European and South Asian populations compared to those in America, Africa, and East Asia. Based on these findings, rs2294915 and rs2896019 may be associated with an increased susceptibility to liver cancer, with the highest effect size of -0.50 observed on skin not exposed to sunlight, such as the suprapubic area. Poggiali and Vercelli [ 17 ] describe this condition as being characterized by a disruption in the heme biosynthesis pathway, which is due to decreased activity of hepatic uroporphyrinogen decarboxylase. This disruption leads to an accumulation of light-sensitive by-products, including uroporphyrinogen, resulting in the development of skin fragility and blistering in areas exposed to the sun, as well as impaired liver function. The allele frequencies of the T and G alleles at loci rs2294915 and rs2896019 were significantly lower in African populations compared to those in American, European, and Southeast Asian populations. Overall, the allele frequencies of the variant alleles rs2294915 and rs2896019 suggest they may contribute to the prevalence of variants affecting the gene expression of PNPLA3 . Across human populations, the frequency of the T allele at rs2294915 is associated with high expression of PNPLA3 in liver cancer. This frequency is much lower in African populations (16%) compared to South Asians (25%), Europeans (25%), East Asians (37%), and Americans (49%). Conversely, the frequency of the C allele at rs2296019 is considerably higher in African (84%), European (80%), South Asian (76%), East Asian (64%), and American (56%) populations. Next, we evaluated the association between allele frequency and the prevalence of liver cancer on each continent. Data on liver cancer prevalence were obtained from Li et al. [ 12 , 18 ]. In this context, two SNPs (rs2294915 and rs2896019) were found to be positively correlated with the prevalence rate of liver cancer across multiple continents (Africa, America, East Asia, Europe, South Asia), as determined by Pearson's correlation analysis (p = 0.011) ( Fig. 5 ). Populations with higher frequencies of variant alleles of these polymorphisms are thought to have a higher prevalence of liver cancer. We highlighted that these two variants (rs2294915 and rs2896019) are more frequent in East Asian and African populations, which exhibit higher aggressiveness of liver cancer compared to America, Europe, and South Asia. This study suggests that individuals in East Asian and African populations carrying the variant alleles rs2294915 and rs2896019 may be more susceptible to liver cancer. Patients with liver cancer who also have a history of alcohol abuse, consuming ≥3 drinks per day, have a 16% increased risk of developing liver cancer compared to the general population. Additionally, individuals with diabetes and those with central obesity are at twice the risk of developing liver cancer [ 1 ]. The diagnosis of liver cancer typically involves serological testing combined with imaging techniques, which is the standard approach for detecting liver carcinoma. However, the sensitivity of the commonly used serological test, which is designed to detect alpha-fetoprotein, is only about 60%. Imaging modalities such as magnetic resonance imaging, computed tomography, and ultrasonography demonstrate high levels of sensitivity and specificity in detecting liver cancer, especially in patients with liver cirrhosis [ 19 ]. Variant alleles (rs2294915 and rs2896019) are associated with liver cancer. Populations from Africa, America, East Asia, Europe, and South Asia exhibit associated PNPLA3 expression, which leads to an increased susceptibility to liver cancer. The identification of unique and pathogenic gene variations for a disease is of great interest for both research and clinical validation. These variants provide insights into disease susceptibility and also act as potential diagnostic and prognostic biomarkers [ 20 ]. Furthermore, they can aid in the identification of drug target candidates, an approach referred to as genomic-driven drug repurposing [ 21 ]. We expect that the discovery of candidate gene variations in PNPLA3 will facilitate successful clinical validation, potentially establishing it as a promising diagnostic and prognostic biomarker for liver cancer. It is important to acknowledge that the genetic variants identified in this study as potentially pathogenic are based on preliminary investigations using genomic and bioinformatics databases. While these findings provide crucial insights for future researchers aiming to validate these genetic variants in liver cancer patients, it is important to proceed with caution. We strongly recommend that future research includes additional functional annotations to aid in the prioritization of these pathogenic genetic variants. This study identified genetic variants that influence liver cancer, highlighting the importance of the PNPLA3 gene in liver tissue. Consequently, these population groups exhibit varying susceptibilities to liver cancer based on the associated PNPLA3 expression levels. The observed variations in allele frequencies of the two identified variants, rs2294915 and rs2896019, across populations from Africa, America, East Asia, Europe, and South Asia, significantly impact PNPLA3 gene expression. Our study also demonstrated that these two SNPs (rs2294915 and rs2896019) were positively correlated with the prevalence rate. The positive association of prevalence rates was more frequently observed in East Asian and African populations. The higher the frequency of the variant alleles of these polymorphisms in a population, the higher the estimated prevalence rates. The variants investigated in this study are likely to predispose individuals to liver cancer and could play a role in its progression and aggressiveness. These findings highlight the critical importance of understanding genomic variations for precision medicine and for designing targeted screening strategies for liver cancer across diverse populations on different continents.

Results and Discussion Identification of genomic variants of liver cancer This study identified SNPs associated with liver cancer from the GWAS catalog. Of these SNPs, 29 were further confirmed through SNP genotyping, as shown in Table 1 . Subsequently, HaploReg version 4.1 was utilized, applying a p-value threshold of <10 -8 based on the number of SNPs obtained. The findings presented in Table 2 indicate an increased risk associated with two genes for liver cancer. The study also analyzed tissue expression impacting liver cancer, with a focus on missense variants of PNPLA3 (patatin-like phospholipase domain-containing 3). Through our integrative bioinformatics approach, we prioritized two variants with missense mutations (rs2294915 and rs2896019) that encode the PNPLA3 gene as biological risk SNPs for liver cancer. Primary liver cancer is a pathological condition characterized by the development of malignant cells within the hepatic tissues. The development of cancer at extraneous anatomical sites that subsequently metastasizes to the liver does not constitute primary liver cancer. Primary liver cancer includes several types, such as hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma, and less common varieties like mixed hepatocellular cholangiocarcinoma, fibrolamellar HCC, and the pediatric neoplasm hepatoblastoma [ 13 ]. Gene expression of PNPLA3 across 10 human tissues The results of PNPLA3 gene expression across 10 human tissues revealed significant functional consequences of genetic variation. The highest levels of PNPLA3 gene expression were observed in the liver, sun-exposed skin (lower legs), non-sun-exposed skin (suprapubic), and adipose-subcutaneous fibroblasts and cell cultures, according to analyses of the 10 human tissues from the GTEx database ( Fig. 2 ). Additionally, we found that the SNP IDs rs2294915 and rs2896019 exhibited similar patterns of gene expression variation in sun-exposed skin (lower legs). Notably, patients with liver cancer often report that their skin appears yellow, which may be related to these findings. Further analysis indicated that the PNPLA3 gene is also highly expressed in suprapubic and underarm skin. Correlation between gene expression of PNPLA3 and eQTLs The study revealed a correlation between the gene expression of PNPLA3 and eQTLs. To identify eQTLs associated with liver cancer gene expression, we utilized the GTEx database. We identified minor alleles that are related to liver cancer, as detailed in Table 3 [ 14 ]. Notably, we discovered that several SNPs, specifically rs2294915 and rs2896019, exhibit high expression in skin tissue. The CC genotype of both rs2294915 and rs2896019 was associated with increased expression in suprapubic and underarm skin compared to the CT and TT genotypes, as shown in Fig. 3 . The research results show that the genomic database could be used to identify gene variations with significant potential in the pathogenesis of liver cancer. Liver cancer is marked by the yellowing of the eyes and skin [ 15 ]. Nessa et al. [ 16 ] note that the severity of liver disease can be gauged by the declining quality of liver function. This quality can be evaluated by measuring total bilirubin levels, serum albumin, and prothrombin time. Allele frequencies of candidate variants in populations in different continents We identified variants associated with liver cancer gene expression and conducted allele frequency analysis across various populations. As indicated in Table 4 , we evaluated the frequency of allele variants in individuals from Europe, America, East Asia, South Asia, and Africa. The allele frequencies for each SNP differed among these populations, as illustrated in Fig. 4 . Both Table 4 and Fig. 4 demonstrate that gene expression levels are higher for populations with increased frequencies of the rs2294915 (C) allele and the rs2896019 (T) allele. Specifically, the gene expression associated with the rs2294915 (C) allele was significantly higher in European and South Asian populations compared to those in America, Africa, and East Asia. Based on these findings, rs2294915 and rs2896019 may be associated with an increased susceptibility to liver cancer, with the highest effect size of -0.50 observed on skin not exposed to sunlight, such as the suprapubic area. Poggiali and Vercelli [ 17 ] describe this condition as being characterized by a disruption in the heme biosynthesis pathway, which is due to decreased activity of hepatic uroporphyrinogen decarboxylase. This disruption leads to an accumulation of light-sensitive by-products, including uroporphyrinogen, resulting in the development of skin fragility and blistering in areas exposed to the sun, as well as impaired liver function. The allele frequencies of the T and G alleles at loci rs2294915 and rs2896019 were significantly lower in African populations compared to those in American, European, and Southeast Asian populations. Overall, the allele frequencies of the variant alleles rs2294915 and rs2896019 suggest they may contribute to the prevalence of variants affecting the gene expression of PNPLA3 . Across human populations, the frequency of the T allele at rs2294915 is associated with high expression of PNPLA3 in liver cancer. This frequency is much lower in African populations (16%) compared to South Asians (25%), Europeans (25%), East Asians (37%), and Americans (49%). Conversely, the frequency of the C allele at rs2296019 is considerably higher in African (84%), European (80%), South Asian (76%), East Asian (64%), and American (56%) populations. Next, we evaluated the association between allele frequency and the prevalence of liver cancer on each continent. Data on liver cancer prevalence were obtained from Li et al. [ 12 , 18 ]. In this context, two SNPs (rs2294915 and rs2896019) were found to be positively correlated with the prevalence rate of liver cancer across multiple continents (Africa, America, East Asia, Europe, South Asia), as determined by Pearson's correlation analysis (p = 0.011) ( Fig. 5 ). Populations with higher frequencies of variant alleles of these polymorphisms are thought to have a higher prevalence of liver cancer. We highlighted that these two variants (rs2294915 and rs2896019) are more frequent in East Asian and African populations, which exhibit higher aggressiveness of liver cancer compared to America, Europe, and South Asia. This study suggests that individuals in East Asian and African populations carrying the variant alleles rs2294915 and rs2896019 may be more susceptible to liver cancer. Patients with liver cancer who also have a history of alcohol abuse, consuming ≥3 drinks per day, have a 16% increased risk of developing liver cancer compared to the general population. Additionally, individuals with diabetes and those with central obesity are at twice the risk of developing liver cancer [ 1 ]. The diagnosis of liver cancer typically involves serological testing combined with imaging techniques, which is the standard approach for detecting liver carcinoma. However, the sensitivity of the commonly used serological test, which is designed to detect alpha-fetoprotein, is only about 60%. Imaging modalities such as magnetic resonance imaging, computed tomography, and ultrasonography demonstrate high levels of sensitivity and specificity in detecting liver cancer, especially in patients with liver cirrhosis [ 19 ]. Variant alleles (rs2294915 and rs2896019) are associated with liver cancer. Populations from Africa, America, East Asia, Europe, and South Asia exhibit associated PNPLA3 expression, which leads to an increased susceptibility to liver cancer. The identification of unique and pathogenic gene variations for a disease is of great interest for both research and clinical validation. These variants provide insights into disease susceptibility and also act as potential diagnostic and prognostic biomarkers [ 20 ]. Furthermore, they can aid in the identification of drug target candidates, an approach referred to as genomic-driven drug repurposing [ 21 ]. We expect that the discovery of candidate gene variations in PNPLA3 will facilitate successful clinical validation, potentially establishing it as a promising diagnostic and prognostic biomarker for liver cancer. It is important to acknowledge that the genetic variants identified in this study as potentially pathogenic are based on preliminary investigations using genomic and bioinformatics databases. While these findings provide crucial insights for future researchers aiming to validate these genetic variants in liver cancer patients, it is important to proceed with caution. We strongly recommend that future research includes additional functional annotations to aid in the prioritization of these pathogenic genetic variants. This study identified genetic variants that influence liver cancer, highlighting the importance of the PNPLA3 gene in liver tissue. Consequently, these population groups exhibit varying susceptibilities to liver cancer based on the associated PNPLA3 expression levels. The observed variations in allele frequencies of the two identified variants, rs2294915 and rs2896019, across populations from Africa, America, East Asia, Europe, and South Asia, significantly impact PNPLA3 gene expression. Our study also demonstrated that these two SNPs (rs2294915 and rs2896019) were positively correlated with the prevalence rate. The positive association of prevalence rates was more frequently observed in East Asian and African populations. The higher the frequency of the variant alleles of these polymorphisms in a population, the higher the estimated prevalence rates. The variants investigated in this study are likely to predispose individuals to liver cancer and could play a role in its progression and aggressiveness. These findings highlight the critical importance of understanding genomic variations for precision medicine and for designing targeted screening strategies for liver cancer across diverse populations on different continents.

Liver cancer is the fourth leading cause of death worldwide. Well-known risk factors include hepatitis B virus and hepatitis C virus, along with exposure to aflatoxins, excessive alcohol consumption, obesity, and type 2 diabetes. Genomic variants play a crucial role in mediating the associations between these risk factors and liver cancer. However, the specific variants involved in this process remain under-explored. This study utilized a bioinformatics approach to identify genetic variants associated with liver cancer from various continents. Single-nucleotide polymorphisms associated with liver cancer were retrieved from the genome-wide association studies catalog. Prioritization was then performed using functional annotation with HaploReg v4.1 and the Ensembl database. The prevalence and allele frequencies of each variant were evaluated using Pearson correlation coefficients. Two variants, rs2294915 and rs2896019, encoded by the PNPLA3 gene, were found to be highly expressed in the liver tissue, as well as in the skin, cell-cultured fibroblasts, and adipose-subcutaneous tissue, all of which contribute to the risk of liver cancer. We further found that these two SNPs (rs2294915 and rs2896019) were positively correlated with the prevalence rate. Positive associations with the prevalence rate were more frequent in East Asian and African populations. We highlight the utility of this population-specific PNPLA3 genetic variant for genetic association studies and for the early prognosis and treatment of liver cancer. This study highlights the potential of integrating genomic databases with bioinformatic analysis to identify genetic variations involved in the pathogenesis of liver cancer. The genetic variants investigated in this study are likely to predispose to liver cancer and could affect its progression and aggressiveness. We recommend future research prioritizing the validation of these variations in clinical settings.

CC BY

no

2024-01-16 23:41:59

Genomics Inform. 2023 Dec 29; 21(4):e48

oa_package/8b/36/PMC10788354.tar.gz

PMC10788355

38224714

Introduction With increasing world population, there is a need to improve food security, which calls for targeted actions to achieve zero hunger under the Sustainable Development Goals adopted by the United Nations in 2015. Currently, fish is the primary source of animal protein for one billion people. Global fish production was 214 million tons in 2020; 157.4 million tons was used for human consumption, and an increasing dependence on production from capture fisheries and aquaculture was reported [ 1 ]. Declining fish stocks in oceans, rivers, and lakes pose a threat to people who are dependent on catching fish for their sustenance or are employed in the fishery industry. The efficiency of the aquaculture sector, which contributes significantly to global food production, can be improved through genetic enhancement [ 2 ]. Silver barb ( Barbonymus gonionotus , Bleeker, 1849) is an important food fish in Southeast Asia with high protein and a delicious taste and is a promising target for aquaculture [ 3 ]. Ranked fourth in economic value and third in production weight for both fisheries and culture, the silver barb is among the economically significant freshwater species in Thailand [ 4 ]. It can withstand high stocking densities and attains a marketable size within 3–4 months [ 5 ]. Because female silver barbs grow significantly faster than males, production of all-female silver barbs has substantial economic implications for aquaculture [ 6 ]. The ability to control sex and breeding aids the production of large stocks in hatcheries, particularly in the reliable production of specific family combinations for selective breeding [ 7 ]. Without this ability, farmers have little control over breeding for genetic improvements. The control of sex and reproduction has been the primary enabler in large-scale global industrial aquaculture production. Currently, all-female silver barb offspring can be produced by gynogenesis, whereby the genome of the embryo has exclusively female origin following embryogenesis simulation by a male gamete [ 8 , 9 ]. The identification of monosex female offspring through gynogenesis led to the hypothesis that the sex-determination system (SDS) in the silver barb is XX/XY. However, the molecular basis for this SDS is poorly understood, and no heteromorphic chromosomes have been identified between females and males [ 10 ]. An understanding of the SDS in silver barb is, therefore, an important baseline for future research on evolutionary biology, sex development, and genetic improvement for aquaculture. Advanced high-throughput molecular methods, in combination with next-generation sequencing technologies, such as restriction site-associated DNA sequencing (RAD-seq) comprising double-digest RAD-seq (ddRADseq) and 2b-RAD sequencing, and diversity arrays technology sequencing (DArTseq), have been applied to identify genotypes [ 11 - 14 ]. These methods are effective in identifying sex-linked markers in non-model species using single-nucleotide polymorphism (SNP) loci. Remarkably, DArTseq markers can reveal sex-associated loci, thereby, facilitating the identification of sex-determining regions in cryptic sex chromosomes of non-model species [ 15 - 18 ]. We investigated the SDS of silver barb employing a genome-wide SNP approach using DArTseq from pre-sexed (based on their phenotype) captive-bred individuals. The genetic understanding of the SDS of this cultured species should assist in aquaculture development.

Methods Specimen selection and DNA extraction A full-sib family of silver barb was artificially fertilized and cultured at the Pathum Thani Aquatic Animal Genetics Research and Development Center, Aquatic Animal Genetics Research and Development Division, Department of Fisheries, Ministry of Agriculture and Cooperatives, Thailand. A total of 32 samples (16 males and 16 females) of 4-month-old adults with standard weights of 10–12 g and lengths of 10–15 cm were euthanized and preserved in 95% ethanol. Whole genomic DNA was extracted following the standard salting-out protocol, with slight modifications for different tissues [ 19 ]. High-molecular-weight DNA samples were stored at −20°C until required for the construction of DArTseq library, as described previously [ 20 ]. All experimental procedures were approved (approval No. ACKU63-SCI-007) by the Animal Experiment Committee of Kasetsart University and conducted in accordance with the Regulations on Animal Experiments at Kasetsart University. DArT sequencing and genotyping The DArTseq methodology for sequencing and genotyping by SNP loci was applied following the protocol described by Jaccoud et al. (2001) [ 20 ]. Multiple loci were genotyped using DArTseq (Diversity Arrays Technology Pty Ltd., Canberra, Australia) to identify the SNP loci and silico DArT markers (also called presence/absence [PA] markers, as any variability in the SNP loci generates PA polymorphisms in restriction sites) were used. The data were used to determine the sex-candidate loci in both male and female individuals. Approximately 100 ng of DNA was collected from each specimen to develop the DArTseq arrays. The DNA samples were subjected to digestion and ligation [ 17 , 21 ]. The outputs generated by DArTsoft14 were filtered according to predefined criteria, including reproducibility values (>3.5), average sequence count (sequencing depth > 5), balance of SNP allele counts (>0.9), and call rate (>0.8), as previously described [ 17 ]. Sex-specific and sex-linked loci were identified using SNP and PA marker analyses. For an XX/XY SDS, male-specific data sets were created, with loci sequenced at various percentages (70%, 80%, 90%, and 100%). The loci that passed the 100% filtering were designated as sex-specific, whereas those within the 70%–90% threshold were classified as sex-linked. An opposite and similar approach was used to target loci based on the ZZ/ZW system. The Hamming distance was calculated to determine the number of combined loci between male and female individuals to identify the pairwise differences in SNP and PA loci using the “rdist” function in R version 3.5.1 [ 22 ]. The Hamming distance represents the number of pairwise differences between all individuals across all loci. The Cochran-Armitage trend test (CATT) was used to examine the genetic association between each locus and phenotypic sex in the SNP and PA loci using the “catt” function in the HapEstXXR package of R version 3.5.1. The CATT results were consistent with those of a chi-square test used to examine whether the observed genotype proportions conformed to the expected values. The polymorphic information content (PIC), which is an index for evaluating the informativeness of SNP and PA loci, was calculated for each locus and ranged from 0 (fixation of one allele) to 0.5% (the frequencies of both alleles were equal) [ 22 - 24 ]. The probability of the sex-linked loci showing random associations with sex when using a small sample size was estimated using the formula P i = 0.5 n , where P is the probability for a given locus, i is sex-linked, 0.5 is the probability that either a female is homozygous or a male is heterozygous at a given locus, and n is the number of individuals sequenced at the locus [ 24 ]. The full dataset and metadata of this publication are available from the Dryad Digital Repository. Dataset, https://datadryad.org/stash/share/P6fDtif_Ig3ZLeYfYCc98BUadnpzHBZXkG8wYoNL-w8 ( https://doi.org/10.5061/dryad.hhmgqnkhn .) Comparison of potential sex-linked loci Significant differences among the three groups of sex-linked loci (90:10, 80:20, and 70:30) were analyzed using the chi-squared test and Kruskal-Wallis test for PA loci and the Nemenyi test for SNP loci, using the “PMCMR” package in R [ 22 ]. The mean heterozygosity and standard deviation of the loci were analyzed. All candidate loci were plotted for each individual using the “glPlot” function in the “dartR” package in R [ 22 ]. A visual representation of the results was obtained through a principal coordinate analysis using all groups of sex-linked loci [ 22 , 24 ]. In silico chromosome mapping Owing to the unavailability of a chromosome-level assembly for the silver barb, the sex-candidate loci were aligned to the chromosome-level assembly of the common barbel ( Barbus barbus ) (accession Nos. OW387152–OW387166 and OW387168–OW387202) using NCBI-BLASTn with default parameters [ 25 ]. The output-mapped file was filtered with the most significant hits (identity: >95%; alignment length: >65 bp) and then parsed using custom Geneious Prime 2023.1.2 (Biomatters, Auckland, New Zealand; https://www.geneious.com ) to generate a file format for visualization of the chromosome map. Homology search The sex-candidate loci showing a statistically significant association with the known sex phenotype were subjected to a BLAST search using the National Center for Biotechnology Information (NCBI) database. Homologies between the sex-specific/linked SNP/PA loci and the reference genomes of other teleosts, including Japanese rice fish ( Oryzias latipes , Temminck and Schlegel, 1850; accession No. GCF_002234675.1) [ 26 ], zebrafish ( Danio rerio , Hamilton, 1822; accession no. GCA_000002035.4) [ 27 ], Japanese pufferfish ( Takifugu rubripe , Temminck and Schlegel, 1850; accession No. GCA_901000725.2) [ 28 ], and chicken ( Gallus gallus , Linnaeus 1758; accession No. AADN00000000.5; International Chicken Genome Sequencing Consortium 2004) were investigated. The NCBI database and RepBase version 19.11 (Genetic Information Research Institute, http://www.girinst.org/repbase/ ) were used to search for homologies of all loci using the BLASTn program [ 29 ]. RepBase is a specialized database with repeated or other significant sequences and only reports results with E-values < 0.005 and a query coverage with >55% similarity [ 24 ]. Functional annotation and gene ontology of the silver barb Functional annotation was performed to understand the biological functions of the sex-specific/linked SNP loci. BLASTn was performed with all candidate loci against the reference annotation consisting of the gene dataset of common barbel [ 30 ]. A reference gene dataset was retrieved from the Ensembl database using the Biomart package ( https://www.ensembl.org/index.html ). BLASTn results were generated as a tabular formatted output file, and only significant hits (identity >95% and alignment length >65 bp) were retained. All gene sequences from the reference dataset that corresponded to the region with significant hits were extracted and mapped against the proteome dataset (including total annotated proteins). The proteome dataset was downloaded from UniProtKB/Swiss-Prot [ 31 ]. UniProtKB is a protein database that provides comprehensive and reliable information on protein functions through accurate, consistent, and detailed annotations. Functional annotations and Gene Ontology (GO) enrichment analyses were also performed on the filtered gene hits using ShinyGO (0.77) implemented in the R/Bioconductor packages. The best-matching species genome was used as a reference in the analysis, with standard settings that included a 0.05 false discovery rate (fold enrichment) p-value threshold [ 32 ]. Associated GO terms describing biological processes (BPs), molecular functions (MFs), and cellular components (CCs) were detected by processing the matching transcripts. GO categories were identified using UniProtKB, the Gramene Protein Database (GR_protein), and the Protein Data Bank (PDB).

Results Determination of the sex system and identification of sex-candidate loci in the silver barb A total of 20,129 SNP and 17,025 PA loci were examined in 32 individuals, including 16 males and 16 females. The PIC values for SNP loci ranged from 0.03 to 0.50, with an average of 0.22, while those for PA loci ranged from 0.06 to 0.50, with an average of 0.30. These results indicate that the overall distribution of PIC values was asymmetrical and skewed toward higher values. The number of filtered SNPs and PAs was then compared between male and female groups after filtering. For the XX/XY type, applying a 30:70 (female:male) criterion resulted in 15 SNP and 48 PA loci. ( Fig. 1A and 1B ). These loci were significantly associated with the phenotype based on CATT analysis ( χ 2 = 4.62–16.35, p < 0.05). The Hamming distance within sexes was 0.403 ± 0.018 in males and 0.525 ± 0.018 in females for SNP loci, and 0.463 ± 0.014 in males and 0.487 ± 0.016 in females for PA loci. The between-sex distances were 0.688 ± 0.012 and 0.694 ± 0.009 for the SNP and PA loci, respectively ( Fig. 2A and 2B ). Additionally, filtering using the 20:80 (female:male) criterion revealed 2 SNP loci and 6 PA loci ( Fig. 1A and 1B ). These loci were significantly associated with the phenotype based on CATT analysis ( χ 2 = 10.29–16.35, p < 0.05). The Hamming distance within sexes was 0.342 ± 0.034 in males and 0.575 ± 0.036 in females for SNP loci and was 0.412 ± 0.026 in males and 0.462 ± 0.026 in females for PA loci. The between-sex distances were 0.807 ± 0.018 and 0.769 ± 0.015 for the SNP and PA loci, respectively ( Fig. 2C and 2D ). However, no sex-candidate loci were identified when using the 10:90 or 0:100 (female:male) criteria ( Fig. 1A and 1B ). For the ZZ/ZW type, filtering using the 70:30 (female:male) criterion revealed 6 SNP and 18 PA loci ( Fig. 1A and 1B ). These loci were significantly associated with the phenotype based on CATT analysis ( χ 2 = 5.81–15.24, p < 0.05). The Hamming distance within sexes was 0.449 ± 0.022 in males and 0.365 ± 0.021 in females for SNP loci and was 0.474 ± 0.017 in males and 0.453 ± 0.017 in females for PA loci. The between-sex distances were 0.671 ± 0.014 and 0.668 ± 0.011 for the SNP and PA loci, respectively ( Fig. 2E and 2F ). Moreover, filtering using the 80:20 (female:male) criterion resulted in only one SNP locus and no PA loci ( Fig. 1A and 1B ). This locus was significantly associated with the phenotype based on CATT analysis ( χ 2 = 15.24, p < 0.05). The Hamming distance within sexes was 0.425 ± 0.045 in males, 0.342 ± 0.044 in females, and 0.801 ± 0.025 between the sexes for the SNP loci ( Fig. 2G ). However, no sex-specific SNP/PA loci were found with 90:10 or 100:0 (female:male) criterion ( Fig. 1A and 1B ). The The Kruskal-Wallis test indicated no significant differences in heterozygosity percentages for SNPs in males ( H = 1.82, p = 0.177) or females ( H = 4.74, p = 0.0295) with XX/XY sex-determination. Similarly, for ZZ/ZW sex determination, no significant differences were observed in males ( H = 0, p = 1) and females ( H = 0, p = 1). ( Fig. 3 ). A principal coordinate analysis plot demonstrated a more similar grouping between the sexes ( Fig. 4 ). Random sex-linkage estimation A range of sample sizes and loci were collected from 32 individuals of the silver barb to minimize the probability of selecting less than one spurious sex-linked marker. For the 32 specimens, the P i (i.e., probability of a single locus exhibiting a sex-linked pattern by chance) was 2.33 × 10 -10 based on 37,154 loci (including SNP and PA loci). The expected sex linkage was 8.65 × 10 -6 . The number of random sex-linked markers in the silver barb was lower than the expected values. Chromosome localization of sex-linked loci based on in silico mapping In silico chromosome mapping of all sex-linked loci of the silver barb onto the chromosome-level assembly of common barbel (accession Nos. OW387152–OW387166 and OW387168–OW387202) revealed that 32 of 63 sex-link loci of the silver barb were localized to 22 of 50 chromosomes of the common barbel. Four loci were localized to chromosome 11, whereas chromosome 2, 7, 8, 25, 35, 41, and 44 were mapped with two loci in each. Only one locus each mapped onto chromosome 3, 4 10, 14, 17, 20, 21, 29, 30, 32, 42, 43, 48, and 50 ( Supplementary Fig. 1 ). Homology of putative sex-linked loci Sex-linked loci in male silver barb shared a sequence homology with the Japanese rice fish, zebrafish, Japanese pufferfish, and chicken genomes ( Supplementary Table 1 ). In the global BLAST analyses using the NCBI databases, six of the 63 male-linked loci were homologous with putative genes: HoxAa (homeobox) (E-value 4.00 × 10 -3 , 59% similarity), TEF (transcriptional enhancer factor) (E-value 8.00 × 10 -10 , 66% similarity), APOL3 (apolipoprotein L3) (E-value 5.00 × 10 -8 , 97% similarity), prkra (protein activator of interferon-induced protein kinase EIF2AK2) (E-value 1.00 × 10 -10 , and 97% similarity), snrnp70 (small nuclear ribonucleoprotein U1 subunit 70) (E-value 0.045, 66% similarity), and Nek4 (serine/threonine-protein kinase) (E-value 8.00 × 10 -6 , 98% similarity) ( Table 1 ). Not all the loci were included in the sex developmental pathway. Additionally, 16 male-linked loci showed partial homology with transposable elements (TEs), mostly Mariner/Tc1 and Gypsy ( Table 2 ). Functional classification and enrichment analysis of the silver barb loci Specific SNP loci in the silver barb were subjected to GO enrichment analyses. The GO-enriched categories of BP terms were mainly involved in the regulation of transport and regulation of vesicle-mediated transport, and the MF terms were mostly related with lipid and phosphatidylinositol binding, and the CC terms were mostly connected with plasma membrane region, cell leading edge, and lamellipodium ( Supplementary Fig. 2 ).

Discussion Latest technologies in aquaculture have been developed from extensive to semi-intensive culture systems on a commercial scale; however, further research is required to enhance production and stock quality while improving fish health management [ 2 ]. One major research area is the chromosome-level manipulation for improving aquacultural traits [ 33 - 35 ]. Successful chromosome manipulation in fish species with known SDS has enabled controlled breeding and size dimorphism for efficient husbandry and production management [ 36 ]. Chromosome manipulation is crucial for gynogenesis and enables efficient production and cloning of all-female individuals in fish species like the silver barb. Gynogenesis also serves as a valuable tool for investigating SDS in aquaculture research [ 36 ]. Male heterogamety was observed in silver barb, with 63 male-linked loci exhibiting genome-wide SNP patterns. This suggests an XX/XY SDS in the silver barb, with all male-linked loci located on a putative Y chromosome. Four of the 63 male-linked loci were mapped onto chromosome 11 of the common barbel, and several loci were localized to different chromosomes. This suggests that many male-linked loci were false-positive loci. By contrast, large chromosomal rearrangements were often observed in teleosts, even at the same genus level [ 37 - 39 ]. Silver barb and common barbel are not at the same genus level, and intra- and interchromosomal rearrangements might result in chromosomal linkage reshuffling, whereas about half of the male-linked loci of the silver barb were informatically mapped onto common barbell chromosomes. All male-linked loci might be retained on the same linkage in the silver barb. However, whether the locations of large genomic regions containing the X- and Y-specific fragments are associated with sex chromosome differentiation and sex-determining regions remains unclear. A major challenge in mapping these loci on sex chromosomes is their short sequence generated using DArTseq and diverse genetic backgrounds that give many false-positive signals [ 46 ]. The probability of spurious sex linkage for a single locus in the full data set of 37,154 loci (including SNP and PA loci) was 2.33 × 10 -10 , whereas the expected level of sex linkage was estimated to be 8.65 × 10 -6 . The observed male-linked loci in the silver barb exceeded the expected value in this study. Out of the 63 male-linked loci, six shared partial homology with functional genes. Interestingly, one locus (PA57951108) was homologous with sex chromosomal linkage in amniotes. This result was similar to the comparative homology of sex-specific and linked loci in several teleosts, such as bighead catfish ( Clarias macrocephalus ), snakeskin gourami ( Trichopodus pectoralis ), Siamese fighting fish ( Betta splendens ), and other amniotes, and indicates the possibility of a super-sex chromosome in ancestral amniotes [ 15 , 17 , 18 ]. Convergent evolution is assumed to be the driving force that causes divergence of sex chromosomes among phylogenetically distant or closely related taxa [ 47 , 48 ]. We also detected certain sex-linked loci that showed significantly similar retroelements, such as Mariner/Tc1 and Gypsy, which are frequently distributed on sex chromosomes in Japanese rice fish ( Oryzias latipes , Temminck and Schlegel, 1850) platyfish ( Xiphophorus maculatus , Günther, 1866), pufferfish ( Takifugu rubripes, Temminck and Schlegel, 1850), and tilapia ( Oreochromis niloticus , Linnaeus, 1758) [ 49 - 51 ]. Chromosomal rearrangements mediated by TEs can induce sex chromosome differentiation and repositioning of heterochromatin. Sex chromosomes of different species were enriched in TEs, indicating that the possible initial accumulation of TEs in the Y chromosome during the early stage of sex chromosome differentiation in the silver barb [ 49 , 52 - 55 ]. Only one female-linked locus passed the CATT test, possibly because of partial recombination in the silver barb. Both male- and female-linked loci were occasionally observed in the same silver barb individual but also occurred in different linkage groups ( Supplementary Table 1 ). There are two possible explanations for the coexistence of both male- and female-linked loci: (1) frequent recombination within the regions of homomorphic sex chromosomes [ 56 ], or (2) putative interactions with other minor genes from male-linked loci in the same linkage group with environmental factors such as temperature [ 57 ]. This might locate all male-linked loci in the same linkage group, with a genetics-based sex-determining mechanism involving a major sex-determining region. Other minor genetic or environmental factors cannot be disregarded [ 57 ]. The SDS in teleosts represent a highly dynamic and plastic phenomenon that triggers gonadal development [ 58 ]. This high-level dynamism is very important for sexual reproduction and survival of a species but sex-determination mechanisms are extremely complex and highly variable [ 17 ]. Genomic resources and tools for the silver barb have improved our understanding of sex determination in this fish. Further investigation is needed to explore sex linkage variability in different populations. Challenges include short read lengths in genotyping techniques and random biological variation, which may result in the identification of sex-linked loci outside of the sex-determination regions or even on autosomes, especially when the sample sizes are small [ 59 ]. The XX/XY SDS has implications for sex-controlled breeding in silver barb aquaculture. Various techniques, such as exogenous hormone treatment, chromosome ploidy manipulation, gynogenesis, molecular tools, and hybridization, can be employed to produce monosex populations. These methods offer advantages, including the production of larger silver barb, which commands higher prices. Monosex populations are also associated with reduced variability compared with mixed sex groups [ 8 ]. The ability to control sex and breeding is pivotal for hatcheries to produce large stocks, particularly reliable specific family combinations through selective breeding. Sex-linked genetic markers and marker-assisted breeding techniques play a vital role in selective breeding. They enable the production of single-sex cohorts in species without visible sexual dimorphism until sexual maturity [ 60 ]. In this study, we encountered several challenges and none of the 63 male-candidate loci independently discovered in the silver barb were successfully validated. Few female individuals showed a nonspecific banding pattern, possibly as a result of an unstable primer binding site. Therefore, this method was not effective in confirming the sex-linked markers (data not shown). Genotyping using sequencing technologies, such as DArTseq or RAD-seq, was also not appropriate for PCR-based validation [ 46 , 50 , 61 ]. Failure of PCR can be due to conserved regions near sex-specific restriction sites in both sexes [ 62 ]. Developing alternative PCR-based genotyping tools is necessary to accurately assess and compare sex-linked loci within populations. Methods, such as polymerase chain reaction-restriction fragment length polymorphism or melting curve analysis, offering more sensitive detection, may be suitable for sex validation [ 16 , 46 , 50 , 61 , 63 ]. Extensive analysis of large sample sizes from diverse population groups, together with the development of optimized techniques, can further validate sex-linked markers in the silver barb. The findings of this study together with previous gynogenesis research [ 8 , 9 ] suggest the existence of XX/XY SDS in the silver barb. Data from a variety of trials and other sources indicate that sexual dimorphism increases with size. Female silver barb grows significantly faster than males, providing improved production with higher yields. The maximum gain from monosex culture would be expected in systems where individuals are grown to a large size and/or to maturity if the target market comprises ovary consumers. However, further elucidation of sex-determining genes and sex chromosome linkage groups is required before the silver barb biological constraints are fully understand and before we have a baseline for genetic manipulation in aquaculture. This research ushers in a new era for studying the genetic basis of sexual dimorphism using biotechnological manipulation for sex-controlled breeding.

Visarut Chailertrit and Thitipong Panthum contributed equally to this work. Silver barb ( Barbonymus gonionotus ) is among the most economically important freshwater fish species in Thailand. It ranks fourth in economic value and third in production weight for fisheries and culture in Thailand. An XX/XY sex-determination system based on gynogenesis was previously reported for this fish. In this study, the molecular basis underlying the sex-determination system was further investigated. Genome-wide single-nucleotide polymorphism data were generated for 32 captive-bred silver barb individuals, previously scored by phenotypic sex, to identify sex-linked regions associated with sex determination. Sixty-three male-linked loci, indicating putative XY chromosomes, were identified. Male-specific loci were not observed, which indicates that the putative Y chromosome is young and the sex determination region is cryptic. A homology search revealed that most male-linked loci were homologous to the Mariner/Tc1 and Gypsy transposable elements and are probably the remnants of an initial accumulation of repeats on the Y chromosome from the early stages of sex chromosome differentiation. This research provides convincing insights into the mechanism of sex determination and reveals the potential sex determination regions in silver barb. The study provides the basic data necessary for increasing the commercial value of silver barbs through genetic improvements.

This research was financially supported in part by a Ph.D. Scholarship for Chalermprakiat 70 years of reign under the Agricultural Research Development Agency (Public Organization) (ARDA) and the Royal Golden Jubilee PhD program under the Thailand Research Fund (TRF) and Agricultural Research Development Agency (Public Organization): The Seventieth Anniversary Celebrations of His Majesty's Accession to the Throne Ph.D. Scholarship Programme (HRD6401028) awarded to V.C. (6317400245) and K.S. The High-Quality Research Graduate Development Cooperation Project between Kasetsart University and the National Science and Technology Development Agency (NSTDA) was awarded to T.P. (6417400247) and K.S. The Center of Excellence on Agricultural Biotechnology, Office of the Permanent Secretary, Ministry of Higher Education, Science, Research and Innovation (AG-BIO/MHESI no. 60-003-005) was awarded to K.S. The National Research Council of Thailand (NRCT) (N42A650233); National Research Council of Thailand: High-Potential Research Team Grant Program (N42A660605) awarded to V.C., W.S., S.F.A., E.K., N.M., P.D., and K.S. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank the Pathum Thani Aquatic Animal Genetics Research and Development Center, Aquatic Animal Genetics Research and Development Division (Department of Fisheries, Thailand) for supplying the silver barb specimens. Supplementary Materials Supplementary data can be found with this article online at http://www.genominfo.org .

CC BY

no

2024-01-16 23:41:59

Genomics Inform. 2023 Dec 29; 21(4):e47

oa_package/2d/a9/PMC10788355.tar.gz

PMC10788356

38224712

Introduction Nonalcoholic fatty liver disease (NAFLD) is a prevalent form of chronic liver disease that contributes to metabolic disorders and associated health conditions. In recent years, the incidence of NAFLD has risen, surpassing viral hepatitis as the leading chronic liver disease worldwide. NAFLD severity varies from the milder nonalcoholic fatty liver (NAFL) to the more serious nonalcoholic steatohepatitis (NASH) [ 1 , 2 ]. NASH is characterized by hepatic steatosis accompanied by lobular inflammation and cell death, potentially progressing to fibrosis [ 3 , 4 ], cirrhosis, and even liver cancer. Notably, the degree of liver fibrosis is directly linked to the increased risk of liver cancer [ 5 ]. Consequently, evaluating the stage of liver fibrosis is crucial for the timely intervention in NASH. Liver fibrosis is classified into five stages: nonfibrotic (F0), mild fibrosis (F1), moderate fibrosis (F2), severe fibrosis (F3), and cirrhosis (F4) [ 6 ]. The occurrence and development of NAFLD and NASH are influenced by a range of factors [ 7 , 8 ], including genetic predisposition to obesity, epigenetic modifications, metabolic and signaling pathways in hepatocytes, and cellular interactions within the liver and adipose tissue [ 9 ]. Consequently, there is a need to develop an early noninvasive diagnostic system and an early warning system for disease risk. These would facilitate the identification of susceptibility genes for NASH, thereby assisting in the investigation of its pathogenesis and the development of potential treatments. Weighted gene co-expression network analysis (WGCNA) is a method used to analyze gene expression patterns across multiple samples [ 10 ]. WGCNA clusters genes with similar expression profiles and examines the relationship between these clusters, known as modules, and specific traits or phenotypes. Additionally, it utilizes these modules and associated phenotypic data to identify central, or hub, genes within the modules. Consequently, WGCNA has become a widely employed tool in studies of phenotypic traits and gene association analyses, aiding in the identification of molecular markers or potential therapeutic targets in complex diseases [ 11 , 12 ]. We hypothesized that certain gene modules or hub genes play a significant role in the progression of liver fibrosis. For this study, we selected three sets of NASH data from the National Center for Biotechnology Information (NCBI). We performed WGCNA on the transcriptome data and corresponding liver fibrosis data to investigate the underlying mechanisms of NASH. Furthermore, we proposed that these hub genes may represent viable therapeutic targets for NASH.

Methods Data collection and processing The mRNA expression data utilized in our study, specifically from datasets GSE49541, GSE48452, and GSE167523, were retrieved from the Gene Expression Omnibus database at NCBI [ 13 ]. The GSE49541 dataset comprises expression data obtained through array profiling, focusing on NAFLD in 72 patients. This group included 40 individuals with mild NAFLD (fibrosis stages 0–1) and 32 with advanced NAFLD (fibrosis stages 3–4). The objective was to delineate liver gene expression patterns that differentiate mild from advanced NAFLD and to establish a gene expression profile linked to advanced NAFLD. The GSE48452 dataset also involved expression profiling by array, encompassing 73 human liver samples categorized into four groups: control (C; n = 14), healthy obese (H; n = 27), steatosis (S; n = 14), and NASH (n = 18). Data from the NASH group (N; n = 18), which included four samples with fibrosis stages 3–4 and 14 with fibrosis stages 0-1, were specifically selected for differential gene expression (DEG) analysis. The GSE167523 dataset originates from global RNA sequencing of snap-frozen liver tissue obtained from 98 patients, comprising 48 with mild NAFLD and 50 with NASH, all of whom had biopsy-proven NAFLD. This data was generated using high-throughput sequencing. The GSE49541 dataset was utilized to construct a co-expression network and identify hub genes associated with liver fibrosis in NAFLD. This microarray data provided a gene expression profile of the liver from 32 patients with advanced NAFLD (fibrosis stages 3–4) and 40 patients with mild NAFLD (fibrosis stages 0–1). The GSE49541 dataset underwent independent normalization using robust multiarray analysis (RMA) [ 14 ] at the NCBI, followed by log2 transformation and quantile normalization. To mitigate batch effects, ComBat was applied to the normalized combined dataset. Identification of DEGs DEGs from GSE49541 between patients with advanced and mild NAFLD were identified in the expression data using the "limma" package in R via GEO2R on the NCBI platform [ 15 ]. The significance analysis of microarrays method was employed to detect genes with significant expression changes, applying a false discovery rate of <0.05 and an absolute log2 fold change of ≥0.5. DEGs from GSE48452 and GSE167523 were analyzed in the same manner as described above. Functional enrichment analysis Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of DEGs in various modules were conducted online via the GEne SeT AnaLysis Toolkit ( http://www.webgestalt.org/ ) [ 16 ]. We established an adjusted p-value of <0.05 as the threshold for significance. All findings were visually represented using the "ggplot2" package in R [ 17 ]. WGCNA and co-expression network construction The R package "WGCNA" [ 10 ] was utilized to construct a co-expression network of DEGs using the GSE49541 microarray dataset. A soft-thresholding power of 22, an R 2 cut-off value of 0.85, and a minimum module size of 25 genes were selected for the analysis. The "Bicor" correlation algorithm and a "signed" network type were employed in the network construction. Identification of hub genes In the module-trait correlation analysis, hub genes exhibiting a Pearson correlation value greater than 0.4 and a p-value less than 0.0005 were identified as candidates with a significant correlation with the level of liver fibrosis. Subsequently, these genes were cross-referenced with DEGs from two other datasets (GSE48452 and GSE167523) to select common DEGs that demonstrated the same significant alterations. Gene set enrichment analysis To further investigate the potential roles of the identified hub genes in NAFL fibrosis, gene set enrichment analysis (GSEA) was carried out for each hub gene individually [ 18 ]. The "clusterProfiler" R package was employed to perform the GSEA [ 19 ]. The reference gene set used was h.all.v7.4.entrez.gmt from the Molecular Signatures Database (MSigDB) [ 20 ], and an adjusted p-value of less than 0.05 was set as the filter condition. Statistical analysis The statistical significance of differences between the two groups was assessed using either a nonparametric test or the t-test, depending on the characteristics of the data distribution. All analyses were performed with R software version 4.1.0 (R Foundation for Statistical Computing, Vienna, Austria). p-values less than 0.05 were deemed to indicate statistical significance.

Results DEGs between advanced NAFLD and mild NAFLD A total of 1,359 DEGs, comprising 600 downregulated and 759 upregulated DEGs in GSE49541, were identified by comparing the transcriptomes of liver tissues from patients with advanced and mild NAFLD ( Fig. 1A ). These DEGs were subsequently utilized for WGCNA and the construction of a co-expression network. The correlations between the top 20 upregulated and the top 20 downregulated DEGs are depicted in Fig. 1B . KEGG pathway analysis showed that the upregulated DEGs were predominantly enriched in pathways such as phosphoinositide 3-kinase–Akt signaling, focal adhesion, microRNAs in cancer, cancer pathways, leukocyte transendothelial migration, and actin cytoskeleton regulation. In contrast, downregulated genes were enriched in pathways including fatty acid degradation, peroxisome, and the metabolism of glycine, serine, and threonine, as well as other metabolic pathways ( Fig. 1C ). GO analysis indicated that these DEGs are implicated in biological processes such as extracellular structure organization, regulation of chemotaxis, small molecule catabolic processes, and cellular components including the extracellular matrix, endoplasmic reticulum lumen, and mitochondrial matrix. They are also involved in molecular functions like structural constituents of the extracellular matrix, receptor ligand activity, and cofactor binding ( Fig. 1D ). WGCNA analysis and co-expression network construction We selected a correlation coefficient threshold of 0.85, and the soft-thresholding power was determined to be 22 ( Fig. 2A ). Seven co-expression modules were identified using WGCNA ( Fig. 2B ). While the gray module contained the largest number of genes, it did not include any genes that were significantly correlated. Consequently, the turquoise module contained the majority of significantly correlated genes, with the blue, brown, and yellow modules following in that order ( Fig. 2B ). Module-trait correlations in liver fibrosis and the identification of hub genes The analysis revealed that seven distinct modules were associated with varying degrees of NAFL fibrosis ( Fig. 3A ). The DEGs within the turquoise module exhibited the strongest positive correlation with the most advanced stage of liver fibrosis, whereas the DEGs in the yellow module demonstrated the most pronounced negative correlation. The DEGs in the turquoise, red, brown, and green modules showed increased expression, in contrast to the downregulated DEGs in the blue and yellow modules. The module eigengene adjacency heatmap displayed the gene expression patterns across these modules ( Fig. 3B ). Correlation analysis, as detailed in Table S1 and derived from WGCNA, revealed that genes with high correlation values (Pearson correlation value > 0.7, p < 0.05) in the context of liver fibrosis also exhibited a strong interrelationship ( Fig. 3C ). Consequently, these genes were identified as potential hub gene candidates. Validation and efficacy evaluation of hub genes To further validate the hub genes, we selected two additional transcriptome datasets (GSE48452 and GSE167523) from liver tissues of patients with advanced and mild NAFLD. Upon comparison with the GSE49541 dataset, we identified five key DEGs ( BICC1 , C7 , EFEMP1 , LUM , and STMN2 ) that exhibited consistent and significant upregulation in both datasets ( Fig. 4 ). Moreover, we conducted receiver operating characteristic curve analysis and calculated the area under the curve (AUC) to differentiate between advanced fibrosis (stage 3–4) and mild fibrosis (stage 0–1). The analysis revealed that the AUCs for these five genes were all greater than 0.7 across the datasets GSE49541 ( Supplementary Fig. 1A ), GSE167523 ( Supplementary Fig. 1B ), and GSE48452 ( Supplementary Fig. 1C ). Gene set enrichment analysis GSEA of single genes revealed that the gene sets were enriched in the samples with BICC1 ( Fig. 5A ), C7 ( Fig. 5B ), EFEMP1 ( Fig. 5C ), LUM ( Fig. 5D ), and STMN2 ( Fig. 5E ). While these gene sets showed high expression, others were suppressed, including those involved in fatty acid metabolism and bile acid metabolism—critical pathways in liver metabolism and cholesterol homeostasis. We focused on gene sets associated with immunity for further analysis. We found that two gene sets, specifically those related to the inflammatory response and tumor necrosis factor (TNF)-α signaling via NF-κB, were enriched in samples with elevated expression of BICC1 , C7 , and EFEMP1 . Additionally, gene sets associated with allograft rejection were also enriched in samples with C7 and EFEMP1 , while those related to interleukin (IL)-2-STAT5 signaling were enriched in samples with C7 ( Fig. 6A - C ). Similarly, gene sets linked to allograft rejection, IL2-STAT5 signaling, and TNFα signaling via NF-κB were enriched in samples with LUM ( Fig. 6D ), and those related to allograft rejection and inflammatory response were enriched in samples with STMN2 ( Fig. 6E ).

Discussion NAFLD is the most common chronic liver disease worldwide, encompassing a spectrum of pathological processes from benign hepatic steatosis to NASH, cirrhosis, and potentially hepatocellular carcinoma [ 21 ]. The progression from simple hepatic steatosis to NASH represents a critical juncture in the evolution of severe liver disease. Patients with NASH face a substantially increased risk of liver fibrosis and end-stage liver disease compared to those with simple fatty liver disease [ 22 ]. Consequently, pinpointing genes that predispose individuals to NASH is instrumental for understanding its pathogenesis and for the development of targeted therapies. Recent studies have shown that it is necessary to build gene co-expression networks within the scope of exploratory research. These networks are instrumental in identifying key modules and genes associated with specific diseases. In our study, we employed WGCNA to examine NASH transcriptome data (GSE49541). We discovered that the turquoise module exhibited the most significant positive correlation with NASH and liver fibrosis, whereas the yellow module demonstrated the most significant negative correlation. To further pinpoint hub genes, we compared DEGs from two additional transcriptome datasets (GSE48452 and GSE167523). This comparison revealed five common genes ( BICC1 , C7 , EFEMP1 , LUM , and STMN2 ) that were consistently upregulated. The AUC values for these five hub genes were greater than 0.7 across the datasets, confirming the reliability of our analytical approach. The functions of these five genes are all associated with liver metabolism, NAFLD, NASH, and related conditions. LUM is a novel essential factor in hepatic fibrosis and encodes an extracellular matrix proteoglycan [ 23 ]. It has also been identified as a central gene in the progression of fibrosis in patients with NAFLD [ 24 ]. C7 , which encodes a serum glycoprotein involved in forming a membrane attack complex, has been suggested as a potential biomarker for advanced fibrosis in NAFLD through proteomic screening [ 25 ] and is implicated in the disease's mechanism [ 26 ]. EFEMP1 is recognized as a transcriptomic signature in NASH [ 27 ]. STMN2 has been profiled in early-stage liver fibrosis in patients with chronic hepatitis C virus infection [ 28 ], and its expression has been positively correlated with insulin resistance in NASH [ 29 ]. BICC1 has been identified as a novel prognostic biomarker in gastric cancer, associated with immune infiltrates [ 30 ], and has also been suggested as a diagnostic marker for NAFLD [ 31 ]. GSEA of these five genes further confirmed their roles in liver metabolism. For instance, disruptions in bile acid metabolism can lead to cholestatic liver disease, dyslipidemia, fatty liver disease, cardiovascular disease, and diabetes [ 32 ].

Nonalcoholic fatty liver disease (NAFLD) is a common type of chronic liver disease, with severity levels ranging from nonalcoholic fatty liver to nonalcoholic steatohepatitis (NASH). The extent of liver fibrosis indicates the severity of NASH and the risk of liver cancer. However, the mechanism underlying NASH development, which is important for early screening and intervention, remains unclear. Weighted gene co-expression network analysis (WGCNA) is a useful method for identifying hub genes and screening specific targets for diseases. In this study, we utilized an mRNA dataset of the liver tissues of patients with NASH and conducted WGCNA for various stages of liver fibrosis. Subsequently, we employed two additional mRNA datasets for validation purposes. Gene set enrichment analysis (GSEA) was conducted to analyze gene function enrichment. Through WGCNA and subsequent analyses, complemented by validation using two additional datasets, we identified five genes ( BICC1 , C7 , EFEMP1 , LUM , and STMN2 ) as hub genes. GSEA analysis indicated that gene sets associated with liver metabolism and cholesterol homeostasis were uniformly downregulated. BICC1 , C7 , EFEMP1 , LUM , and STMN2 were identified as hub genes of NASH, and were all related to liver metabolism, NAFLD, NASH, and related diseases. These hub genes might serve as potential targets for the early screening and treatment of NASH.

Supplementary Materials Supplementary data can be found with this article online at http://www.genominfo.org .

CC BY

no

2024-01-16 23:41:59

Genomics Inform. 2023 Dec 29; 21(4):e45

oa_package/9d/38/PMC10788356.tar.gz

PMC10788357

38224716

Introduction Technological advancements and improvements in next-generation sequencing have allowed for the exploration of complex and previously unknown marine microbial communities, which constitute the largest and most stable ecosystem on earth. Studies such as the Tara Oceans project [ 1 ] have enabled the discovery of so-called microbial dark matter [ 2 ] or unculturable microbial communities. The main challenge in metagenomics study is to identify low-abundance microbes, which highly depends on the accuracy and precision of short-reads sequencing platforms. While short reads may introduce sequencing errors, high coverage can compensate these errors in subsequent downstream analysis [ 3 ]. Short read sequencing platform such as Illumina HiSeq3000 platform can generate 1 tera-basepairs (Tbp) of sequence data which corresponds to 3.33 billion paired-end (PE) reads (150 bp) in a single run and is based on sequencing by synthesis chemistry. It has already been the preferred choice for shotgun metagenomics studies due to their affordability and low error rates [ 4 ]. The BGISEQ-500 platform, based on DNA Nanoball Technology, by the Beijing Genomics Institute (BGI) group in 2016, generates 1 Tbp of sequence data which corresponds to 5 million PE reads (100 bp) in a single run while minimizing amplification errors. DNA Nanoball Technology incorporates customized combined probe-anchor synthesis technology with MGI Tech Co., Ltd's proprietary base-calling software. Several studies have compared the BGI’s platform performance with Illumina’s platform in different areas of omics studies such as transcriptome, small RNA sequencing including metagenomics studies [ 5 - 7 ]. One of the key challenges in metagenomics studies utilizing short-read platforms is that short-read sequences often map to multiple species with identical or similar segments in the reference genome [ 8 ]. To address this issue, taxonomic classifiers (bioinformatics tools), utilize specialized algorithms to accurately assign millions of reads generated from short read sequencers to the corresponding taxa [ 9 ]. Taxonomic classifiers such as Kraken2 [ 10 ] use both least common ancestor (LCA) and k-mer approaches to build an indexed database and searches for k-mers in the reads that match against the reference database. Whereas other taxonomic classifiers such as Kaiju [ 11 ] perform maximum exact match against protein databases using Burrows-Wheeler transform. Both k-mer based classifiers are designed for short reads and utilize pseudo-alignment algorithms to match them against a reference database for classification. However, a downside of this method is the reliability of taxonomically annotated reference sequences database as uncharacterized taxa generally lead to insufficient classification at the species level [ 12 ]. Highly accurate relevant reference sequence databases, such as the NCBI RefSeq database [ 13 ] and the MAR databases ( https://mmp2.sfb.uit.no/ ) [ 14 ] can accelerate taxonomic profiling of marine metagenomics reads or contigs. The MAR databases hosted at the Center for Bioinformatics (SfB), The Arctic University of Norway (UiT), a node of ELIXIR Norway, contain marine microbial genome records based on the level of completeness (MarRef v1.5: 1270 manually curated records and MarDb v1.5: 13237 incompletely sequenced marine prokaryotic genomes records including metagenome-assembled genomes [MAGs] and single amplified genomes [SAGs]). These records are taxonomically annotated using both Genome Taxonomy Database (GTDB) [ 15 ] and NCBI, allowing flexibility to use either GTDB taxonomy or NCBI taxonomy identifier (TaxID). Both GTDB and NCBI taxonomy are hierarchically ordered into taxonomic levels or ranks. The most commonly used taxonomic ranks for bacteria include domain/kingdom, phylum, class, order, family, genus, and species. In this study, we provide an extensive comparison of sequencing platforms (HiSeq3000 and BGISEQ-500) using 12 sediment metagenomics samples, utilizing various combinations of taxonomy classifiers with reference databases and assemblers. By doing so, this study aims to provide insights into the advantages and limitations of each platform and contribute to the ongoing efforts to improve and optimize metagenomics research.

Methods Metagenomic DNA extraction The study collected marine sediment samples from 12 locations off the Norwegian coast and metagenomic DNA was extracted using the FastDNA Spin Kit for Soil (MP Biomedicals, California, USA). The DNA samples were sequenced using both HiSeq3000 (Norwegian Sequencing Centre, Oslo, Norway) and BGISEQ-500 (BGI Tech Solutions (Hong Kong) Co., Ltd., Hong Kong, China) platforms. Data available All the sequencing reads generated from both HiSeq3000, and BGISEQ-500 platforms have been deposited in the European Nucleotide Archive (ENA) at EMBL-EBI under accession number PRJEB55540. A copy of the BGISEQ-500 generated sequences has also been submitted to the CNGB Sequence Archive (CNSA) of China National GeneBank DataBase (CNGBdb) with accession number CNP0003834. Normalization and preprocessing of sequence data In this study, we divided each 12 samples into two, treating them as technical replicates (Illumina HiSeq3000: 150 bp PE and BGISEQ-500: 100 bp PE; Illumina, San Diego, CA, USA). To normalize sequence data, the largest dataset from each pairwise technical replicate was normalized (downsampled) to an equal number of bases per sample points for accurate comparison. It was done using reformat.sh of the BBTools suite (sourceforge.net/projects/bbmap/) with the " sbt " option ( sbt : ‘lowest base count of sequences generated among sequencing platforms per sample site’) ( Figs. 1 and 2 ). The normalized or unprocessed reads were then screened for overall sequencing quality using FastQC v0.11.5 [ 16 ] and optical duplicates for Illumina sequences were removed using clumpify.sh (dupedist = 40) of the BBTools package. Adapter sequences were trimmed using bbduk.sh (HiSeq3000 = Nextera adapter sequences, BGISEQ-500 adapter sequences left = ‘ AAGTCGGAGGCCAAGCGGTCTTAGGAAGACAA ’ and right = ‘ AAGTCGGATCGTAGCCATGTCGTTCTGTGAGCCAAGGAGTTG ’) and low-quality bases were filtered out (HiSeq3000: ‘forcetrimleft = 17 ktrim = r minlen = 51 qtrim = r trimq = 20 tbo = t mink = 11 hdist = 1’ and BGISEQ-500: ‘minlen = 51 trimq = 20 forcetrimleft = 3’). Trimmed reads were mapped against PhiX phage sequences using FastQ Screen [ 17 ] to filter any possible contamination in Illumina sequences. Finally, PE reads were reordered using repair.sh and clean reads greater than 51 bases with Phred score > 20 were kept for downstream analysis. Taxonomic classification Taxonomic classification of the preprocessed or clean reads was performed using Kaiju (v1.7.3) and Kraken2 (v2.1.0) against both indexed bacterial MAR (v1.5, June 2020) and RefSeq (July 2020) databases at default parameter settings and thread 15 . The MAR databases differentiate marine microbial genomes based on the level of curatedness. In the current study, both MarRef v1.5 and MarDb v1.5 were merged (here referred to as MAR) and used as the reference databases. The reference database for taxonomic classification was tailored to bacterial protein and nucleotide genome sequences and indexed using Kaiju and Kraken2 respectively. Four indexed classifier-database combinations were created: kaiju-MAR (25 GB), kraken2-MAR (49 GB), Kaiju-RefSeq (31 GB), and kraken2-RefSeq (42.6 GB). Classified reads were imported using the phyloseq package [ 18 ] in R, and the corresponding count values were converted into percentages for both sequencing platforms (12 samples), where 100% refers to the total read count of a sample. Subsequently, the taxonomically classified reads were subjected to Principal Coordinate Analysis (PCoA) analysis using Bray-Curtis dissimilarities at the taxonomic ranks phylum, order, and genus in R with the ordinate function from phyloseq package. Assembly The assembly of both normalized and preprocessed/clean reads from both HiSeq3000 and BGISEQ-500 platforms was performed using MEGAHIT v1.2.9 [ 19 ] and metaSPAdes v3.13.0 [ 20 ], except for the assembly of normalized reads from HiSeq3000 due to high computational requirements. It resulted in 84 combinations of input reads, assemblers, sequencing platforms, and sample points, and each combination was assembled at default k-mer values. Assembly qualities of contigs greater than 500 bp were evaluated using MetaQuast v5.0.2 [ 21 ]. The MEGAHIT assemblies were conducted locally using 40 threads on Intel(R) Xeon(R) Gold 6150 CPU @ 2.70 GHz processors and Intel(R) Xeon(R) Gold 6240R CPU @ 2.40 GHz processors. The metaSPAdes v3.13.0 assemblies were performed on Sigma2 - the National Infrastructure for High Performance Computing and Data Storage in Norway. Supplementary Fig. 1 was generated on relative values (–1 to 1) using the ComplexHeatmap R package [ 22 ]. Relative values were recomputed as mean of assembly statistics from each UnPreprocessed reads-assembler combination relative to average value obtained from all combinations, as described in a previous publication [ 23 ]. An in-house bash script was used to calculate the maximum memory (RAM) utilized and total run-time during both taxonomy classification and assembly.

Results Normalization and preprocessing of sequence data Illumina HiSeq3000 generated a higher number of bases, on average (~36 billion bases and fewer reads ~241 M) than BGISEQ-500 (~32 billion bases or ~322 M reads) at most sample points ( Fig. 2 ). Normalization enabled us to retain ~ 23-38 billion high-quality bases with average Q20 scores of ~99.04% and ~97.25% for HiSeq3000 and BGISEQ-500 generated normalized/unprocessed reads, respectively ( Supplementary Table 1 ). High-quality sequences were characterized by a lack of ambiguous base calls or base-calling errors, represented by an ‘N’. We observed that such errors were almost absent (<0.6%) in BGISEQ-500 reads but ranged from 5-11% at the end of HiSeq3000 reads (8 bp), which were discarded by quality control tools. Moreover, HiSeq3000 reads showed a high amount of Nextera adapter contamination in three out of 12 samples, while the BGISEQ-500 reads were almost free from adapter sequences. The duplication ratio in HiSeq3000 generated reads was slightly higher than that in BGISEQ-500 generated reads ( Supplementary Table 1 ). The GC percentage of HiSeq3000 and BGISEQ-500 generated reads ranged between 52%–56% and 51%–55%, respectively ( Supplementary Fig. 2 ). Finally, the length of preprocessed reads varied between 117–130 bp for HiSeq3000 and ~100 bp for BGISEQ-500. Taxonomic classification The taxonomic classification of preprocessed reads from both sequencing platforms in all samples resulted in 16,667 unique bacterial taxonomic IDs ( Supplementary Table 2.1 ). A significant proportion of taxa (~40.3%) were unique to a particular database, irrespective of the classifier and database type used ( Supplementary Fig. 3 ). The RefSeq database uniquely identified approximately 49.5% (or 8,242 taxa) of total classified taxa. Similarly, the MAR database uniquely contributed significantly to the identification of approximately 40.7% (or 6,796 taxa) of the total taxa. Kraken2, using RefSeq, identified 1,066 taxa (6.4% of total classified taxa) that were unique and not identified by any other classifier-database combination. In contrast, 1,484 taxa or 8.9% of the total classified taxa were identified by all classifier-database combinations. A decline in the percentage of taxonomically classified reads was observed at lower taxonomic ranks, regardless of the sequencing platform, classifier, or database used ( Fig. 3 ). Across all taxonomic ranks and for each sample point, a higher fraction of HiSeq3000 reads were classified relative to BGISEQ-500 reads (average difference of ~1.93%–7.23%), irrespective of reference databases used ( Supplementary Table 2.2 ). Kaiju classified a higher fraction of reads than Kraken2 for all taxonomic ranks (average difference of 22%–26.8% from domain to family , and 9.62%–23.58 % from genus to species ) ( Supplementary Table 2.3 ). The use of the curated marine-specific database (MAR) resulted in more reads being taxonomically classified than RefSeq (average difference of ~6.2%–11.7% from domain to family ), except with Kaiju at genus and species level ( Supplementary Table 2.3 ). However, at the taxonomic rank of genus and species , the percentage of reads classified using Kaiju-MAR declined more than that using Kaiju-RefSeq (average difference of ~1.4%–7.9%) ( Fig. 3 , Supplementary Table 2.3 ). The PCoA of taxonomic profiles showed a clear clustering that correlates to the choice of reference databases and taxonomic classifiers. Approximately 73.9% of variation in the dataset is explained by the choice of reference database, while 14.6% can be attributed to the choice of taxonomic classifier at the species level ( Fig. 4 ). At higher taxonomic ranks, there were no clear separations between the selected reference databases and taxonomic classifiers. The sequencing technology does not seem to contribute to the variations in ordination plot. Assembly We assembled unprocessed and preprocessed/clean reads using two assemblers (MEGAHIT and metaSPAdes) independently, resulting in a total of 84 assemblies from seven categories (un/preprocessed reads, sequencing technology, and assemblers) ( Supplementary Table 3 , Supplementary Fig. 1 ). On average, MEGAHIT with HiSeq3000 unprocessed reads generated the largest and most contiguous assemblies (~866 Mb or ~976 kb contigs), while metaSPAdes using clean BGISEQ-500 reads produced the smallest assemblies (~371 Mb or ~415 kb contigs) ( Fig. 5 ). Both assemblers consistently produced larger assemblies using HiSeq3000 reads, with an average difference of ~390 Mb (MEGAHIT using unprocessed reads), ~164 MB (MEGAHIT using clean reads), and ~116 MB (metaSPAdes using clean reads) compared to BGISEQ-500 reads. The largest contigs in all assembly categories ranged between 35–155 kb, except for outliers at ~192 kb ( Supplementary Fig. 4A ). The GC percentage of assemblies was ~53%–57% for HiSeq3000 and ~48%–56% for BGISEQ-500 ( Supplementary Fig. 4B ). The N50 contig length (>500 bp) remained similar (~0.75–1 kb) in all assemblies, irrespective of assemblers ( Supplementary Fig. 4C ). Computational requirements The computational resources required for classification and assembly were minimally affected by the sequencing platform. The taxonomic classifier Kaiju efficiently utilized all available resources, while Kraken2 used approximately 35.58% of the CPU but classified the dataset 12 times faster than Kaiju ( Supplementary Fig. 5A and 5B ). Peak memory usage for Kaiju varied between ~28–35 GB and ~42–43 GB for Kraken2. MetaSPAdes required significantly higher memory (~515–554 GB) than MEGAHIT (~54–63 GB) for assembling the largest dataset (~32–38 billion bases) while for the smallest dataset (~19–23 billion bases), metaSPAdes and MEGAHIT used ~300 GB and ~35 GB of maximum memory ( Supplementary Fig. 5D ). Peak memory usage and run-time for all assemblies averaged approximately 428 GB or 37.22 h for metaSPAdes, and 46 GB or 6.48 h for MEGAHIT. The assembler run-time performance improved significantly using preprocessed or clean reads by ~45% (MEGAHIT using HiSeq3000), ~25% (MEGAHIT using BGISEQ-500), and ~31% (metaSPAdes using BGISEQ-500) compared to unprocessed reads ( Supplementary Table 3 ).

Discussion Our study compared the metagenomic DNA sequences generated by two sequencing platforms, HiSeq3000 and BGISEQ-500, from 12 samples collected along the Norwegian coast. To evaluate the quality of the generated datasets, we utilized two different reference databases, taxonomic classifiers and assemblers. Both platforms generated an unequal number of reads and base counts, which can vary due to factors such as microbial abundance, sequencing depth, and GC biases [ 24 ]. Library preparation methods specific to each platform can impact read duplication and adapter contamination [ 25 ]. There is also evidence of a platform-dependent GC distribution pattern between the BGISEQ-500 and HiSeq4000 [ 7 ]. To mitigate these limitations and differences, an equal number of bases were extracted from each sample point from both platforms, to normalize the data and facilitate further comparisons. Our analysis encompasses the evaluation of the percentage of reads classified at various taxonomic ranks, assembly statistics, and computational requirements for each platform's generated sequencing reads. Our findings indicate that despite the differences in sequence length (HiSeq3000: 150 bp PE and BGISEQ-500: 100 bp PE), the base quality between these two sequencing platforms is comparable. The absence of adapter sequences in the BGISEQ-500 sequences resulted in a smaller proportion of reads being discarded during subsequent processing stages ( Supplementary Table 1 ). However, a higher percentage of taxonomically classified reads was obtained from the HiSeq3000 platform, with a difference ranging from 1.93% to 7.23% on average, compared to the BGISEQ-500 platform, when evaluated across different taxonomic classifiers and reference databases ( Fig. 3 , Supplementary Table 2.1 ). This discrepancy could be due to a combination of factors, including sequence length, classification algorithms, and reference databases used. Previous research using short Illumina reads indicates a weak correlation between read length and classification success (the probability of correct classification out of total taxonomically classified reads) and for bacteria it remained relatively constant across different read lengths (100 bp and 150 bp) [ 26 ]. Also, Illumina short reads (100 bp and 150 bp) were found to have a constantly higher overall recall (the probability of correct classification out of total reads) for bacteria using Kraken2 [ 26 ]. The difference in the fraction of reads classified between the HiSeq3000 and BGISEQ-500 platforms could be attributed to differences in the classification method employed. Both Kaiju and Kraken2 utilize different approaches to taxonomically classify reads; Kaiju uses a maximum number of exact matches, while Kraken2 identifies fixed-size k-mers of variable length in reads and matches them against indexed databases. Although Kaiju had a slightly longer run-time, it efficiently utilized all computational resources and classified a higher percentage of reads (as shown in Supplementary Fig. 4A ). Unfortunately, it was impossible to calculate the accuracy of the taxonomic classifiers used in this study as it requires simulation studies on known mock communities using reference databases, which was beyond the scope of this paper [ 11 ]. Our analysis showed that using both MAR and RefSeq protein databases was more effective in classifying reads compared to their nucleotide counterparts ( Supplementary Table 2.3 ). This disparity could be attributed to the fact that protein sequences are more robust to nucleotide substitutions and sequencing errors [ 27 ]. Conversely, the nucleotide database showed a difference of 11–24 Gb in bacterial genome records compared to the protein counterpart. Moreover, using the RefSeq database ( bacteria ) as a reference led to a higher maximum memory requirement, possibly due to database composition and diversity ( Supplementary Fig. 5C ). Furthermore, the PCoA plot presented in Fig. 4 provided additional evidence of substantial differences at lower taxonomic ranks between the reference databases. The distinct clustering patterns strongly correlates with the selection of reference databases. Taken together, these results suggest that the taxonomic classification of sequence reads is primarily influenced by the choice of reference database, followed by the taxonomic classifiers and sequencing platforms used. Notably, the PCoA plot illustrates that the two sequencing technologies produced comparable taxonomic profiles. As expected, the fraction of classified reads declines from the highest ( domain ) to the lowest ( species ) taxonomic rank ( Fig. 3 ). The decline is due to a combination of the incomplete annotation of entries in the databases at lower taxonomic ranks (e.g., an entry can have higher taxonomic information e.g., only at domain to family rank), and that the classification algorithms fail to classify reads at lower ranks if reads matches equally well to multiple entries. Similar misclassification at the genus or species level have been previously reported due to bioinformatics contamination, instances where species having a higher average nucleotide identity than the true species [ 25 ] or the absence of closely related genomes in RefSeq which is rare at higher taxonomic ranks [ 28 ]. However, Kaiju address this by utilizing LCA method in cases of equally good matches to multiple taxa, leading to assignment of reads at a higher taxonomic rank. As an example, taxonomic classification using Kaiju against the MAR database gradually declines from domain level with 100% classification to 71% at the family level. However, it drops significantly to 59.27% at the genus level and further to 43.09% at the species level. This drop in classification accuracy could be due to the presence of marine MAGs, SAGs, and incomplete genomes in the MarDb database [ 14 ], which is a component of MAR database. MAG and SAG genomic sequences are assembled from environmental samples and often contain fragments from multiple genomes or exhibit gaps and errors due to the complexities of assembling genetic material from diverse source. The high degree of fragmentation in MAGs and the presence of unknown microbes pose challenges in accurately classifying these microbes, especially at lower taxonomic ranks. The absence of representative taxon nodes for MAGs in the database can further complicate the process. Although, Kaiju using RefSeq protein database, identified approximately 49.5% of the total identified taxa or 8,242 taxa, it remains uncertain whether these classified organisms are exclusively of marine origin. The difference in classified reads using Kaiju-MAR or Kaiju-RefSeq at lower taxonomic rank could result from non-marine strains in RefSeq database, fewer marine bacteria being taxonomically identified at species level in the MAR database or allocation of equally classified reads to higher taxonomic rank using the LCA algorithm by Kaiju. Nevertheless, despite these challenges, Kaiju consistently demonstrated the highest recall with HiSeq3000 generated sequences, except at species level, where the MAR database proved most effective for marine metagenomics samples. Assessing the quality of metagenomics assemblies can be challenging due to the absence of reference genomes representing diverse communities. Our comparative analysis using same base count demonstrated that both assemblers produced larger assembly lengths and total contigs using preprocessed HiSeq3000 reads in majority of sample points. The BGISEQ-500 assemblies exhibited slightly better N50 and L50 contig values, although these statistics can be easily manipulated due to being based on the ordered length of contigs. In addition to our assessment of assembly quality, we compared assemblers which revealed that MEGAHIT generated larger assembly lengths and longer total contigs than metaSPAdes, with an average difference of 2.56%–18.74% and up to 16.55% (using unprocessed BGISEQ-500 reads), 8.5%–19.15% and 6.82%–19.29% (using clean HiSeq3000 reads), and up to 13.49% and upto 11.65% (using clean BGISEQ-500 reads) in all 12 samples ( Fig. 5 ). We employed de Bruijn graph (dBg) based assemblers, which require a selection of k-mer size and can significantly impact the final assembly ( Fig. 5 , Supplementary Fig. 4C and 4D ). The choice of k-mer size influences the complexity of the graphs and affects the ability to resolve repeats, errors, and heterozygosity in the assembly [ 29 ]. Choosing a smaller k-mer size results in more connected graphs, while a larger k-mer size leads to simplified graphs. In our study, we used the recommended default k-mer size to obtain assembly statistics across different sequencing technologies, processed reads, and assembly programs. While both MEGAHIT and metaSPAdes performed comparably in terms of assembly, MEGAHIT was more resource-efficient overall. The peak memory usage for MEGAHIT to assemble 200 million reads or approximately 31 billion bases was 63 GB, making it a preferred option for memory-intensive metagenomics projects. Our findings suggest that both platforms are capable of generating high-quality metagenomic data, but there were some notable differences in their performance. Overall, the choice of sequencing platform should depend on the specific research question and the characteristics of the microbial community being studied. Our study provides valuable insights into the performance of two popular platforms, which can aid researchers in making prior decisions about their sequencing strategies. The study compared the results of two short read sequencing platforms, HiSeq3000 and BGISEQ-500, and we found that they produced comparable results. We also compared different sequencing technologies, taxonomic classifiers, reference databases and assemblers. The findings show that short read sequencing platforms can be used interchangeably in metagenomics studies, without compromising result quality. Our studies show that each sequencing platform has strengths and weaknesses; therefore, the selection of specific platform should be based on the specific research questions and experimental design. For metagenomics analysis the choice of reference database is more essential for taxonomic classification where the sequencing method itself becomes less significant. Finally, taxonomic classifiers and assembly tools have different computational requirements and the availability of resources needs to be taken into account.

Recent advances in sequencing technologies and platforms have enabled to generate metagenomics sequences using different sequencing platforms. In this study, we analyzed and compared shotgun metagenomic sequences generated by HiSeq3000 and BGISEQ-500 platforms from 12 sediment samples collected across the Norwegian coast. Metagenomics DNA sequences were normalized to an equal number of bases for both platforms and further evaluated by using different taxonomic classifiers, reference databases, and assemblers. Normalized BGISEQ-500 sequences retained more reads and base counts after preprocessing, while a slightly higher fraction of HiSeq3000 sequences were taxonomically classified. Kaiju classified a higher percentage of reads relative to Kraken2 for both platforms, and comparison of reference database for taxonomic classification showed that MAR database outperformed RefSeq. Assembly using MEGAHIT produced longer assemblies and higher total contigs count in majority of HiSeq3000 samples than using metaSPAdes, but the assembly statistics notably improved with unprocessed or normalized reads. Our results indicate that both platforms perform comparably in terms of the percentage of taxonomically classified reads and assembled contig statistics for metagenomics samples. This study provides valuable insights for researchers in selecting an appropriate sequencing platform and bioinformatics pipeline for their metagenomics studies.

Illumina HiSeq3000 sequencing was performed by the Norwegian Sequencing Centre ( www.sequencing.uio.no ), a national technology platform hosted by the University of Oslo and Oslo University Hospital and supported by the "Functional Genomics" and "Infrastructure" programs of the Research Council of Norway and the Southeastern Regional Health Authorities. BGI Tech Solutions (Hong Kong) Co., Ltd. provided assistance with sequencing using BGISEQ-500 sequencing platforms, acting as an overseas sample receiving site and temporary storage point. We would also like to acknowledge Dr. Tao Jin for help with sequencing at CNGB. The computations were performed on a local compute cluster and resources provided by Sigma2, the National Infrastructure for High-Performance Computing and Data Storage, Norway. This work was supported by UiT The Arctic University of Norway. Supplementary Materials Supplementary data can be found with this article online at http://www.genominfo.org .

CC BY

no

2024-01-16 23:41:59

Genomics Inform. 2023 Dec 29; 21(4):e49

oa_package/53/fd/PMC10788357.tar.gz

PMC10788358

38224713

Introduction Colorectal cancer (CRC) is among the leading causes of cancer-related death, in which colon adenocarcinoma (COAD) is the major type of CRC [ 1 ]. It ranks as the second most common cancer in women and the third most prevalent in men. Men have approximately 25% higher incidence and mortality rates for CRC compared to women [ 2 ]. The burden of CRC prevalence and mortality is rapidly increasing worldwide, particularly in developed countries. Predictions suggest that by 2030, the global incidence of CRC will rise by 60%, resulting in over 2.2 million new cases and 1.1 million fatalities [ 3 ]. Patients with CRC and distant metastasis often do not respond well to conventional treatment, leading to a poor 5-year survival rate of less than 10% [ 4 ]. Therefore, it is essential to identify accurate and reliable prognostic factors for early CRC diagnosis to improve patient survival rates. Anoctamin 7 (ANO7) belongs to the anoctamin family of Ca 2+ -activated Cl – channels. The anoctamin family has ten isoforms [ 5 ]. Some members of the anoctamin family, like ANO1, have been linked to the pathogenesis of CRC. ANO1 has been identified as a target of honokiol that inhibits the proliferation of CRC cells [ 6 ]. Similarly, Li and colleagues discovered that ANO9 downregulation plays a crucial role in the tumorigenesis and progression of CRC [ 7 ]. ANO7 has been shown to be downregulated in metastatic disease, and reduced protein expression is related to high-grade prostate cancer [ 8 - 10 ]. However, the question of whether ANO7 plays a role in the pathogenesis of CRC remains unanswered. With the advancement of cancer research, the release of multiple omics datasets and user-friendly bioinformatic tools has significantly amplified our analytical capabilities. Notably, The Cancer Genome Atlas (TCGA) provides an extensive repository of genomic and clinical data encompassing various cancer types [ 11 ]. Therefore, in this study, we conducted a bioinformatic analysis based on the TCGA database to attain a more in-depth perspective on the prognostic and functional significance of ANO7 in the context of COAD. Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and the University of Alabama at Birmingham CANcer data analysis Portal (UALCAN) were used to explore the expression of ANO7 and its association with clinicopathologic characteristics of COAD patients. Survival analysis was conducted using GEPIA2, Kaplan-Meier (KM) plotter, and Survival Genie web tools. The GeneFriends, the Database for Annotation, Visualization and Integrated Discovery (DAVID), GeneMANIA, and Pathway Studio were employed to explore the potential role of ANO7 in COAD.

Methods Analysis of differential expression of ANO7 gene in COAD and normal tissues The ANO7 gene expression level in COAD tissue was investigated in comparison to normal tissue using the TCGA-COAD dataset through both the GEPIA2 ( http://gepia2.cancer-pku.cn/ ) [ 12 ] and UALCAN databases ( http://ualcan.path.uab.edu ) [ 13 ]. Within the GEPIA2 platform, the differential expression analysis of the ANO7 gene was conducted across 275 COAD tissues and 41 normal tissues using a one-way ANOVA. In the UALCAN database, the statistical distinction in ANO7 expression was evaluated between 286 COAD tissues and 41 normal tissues using a Student’s t-test with unequal variance. Analysis of association between ANO7 expression and clinicopathological characteristics of COAD patients The UALCAN database was utilized to explore the association between ANO7 mRNA expression and clinicopathological characteristics among a total of 286 COAD patients. These characteristics include age, race, gender, cancer stage, histological subtype, and nodal metastasis status. A statistical comparison was performed using a Student’s t-test with unequal variance within the database. KM survival curve analysis The KM survival curve analysis of COAD patients, based on ANO7 expression, was conducted using several web tools, including GEPIA2, KM plotter ( https://kmplot.com/analysis/ ) [ 14 ], and Survival Genie ( https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/ ) [ 15 ]. In GEPIA2, a division of patients (n = 267) into two groups was performed based on the median expression value, distinguishing between low and high expression. Similarly, KM plotter was employed to perform survival analysis on 304 COAD patients. The "Auto select best cut-off" option was utilized to divide the low and high expression groups. KM curves for patients' overall survival were presented, along with the log-rank p-value and hazard ratio (HR). Additionally, survival analysis was conducted on the Survival Genie platform with a cohort of 453 colon cancer patients. They were categorized into low and high ANO7 expression groups using the martingale residuals method [ 15 ]. Co-expression network and functional enrichment analyses In order to comprehensively explore the potential role of ANO7 in colon cancer, we collected the top 100 genes that displayed a positive correlation with ANO7 (based on the Pearson correlation coefficient, r) in the TCGA-COAD dataset from GEPIA2 for further analyses. A co-expression network of ANO7-correlated genes was built using GeneFriends ( https://genefriends.org/ ) [ 16 ] with a Pearson correlation threshold of 0.7. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using DAVID tool ( https://david.ncifcrf.gov/ ) [ 17 , 18 ]. False discovery rate (FDR) below 0.05 were considered significant. The enrichment results were visualized using Hiplot ( https://hiplot.org ) web tool [ 19 ]. Additionally, molecular interaction network of ANO7-correlated genes mapped into significantly enriched GO biological processes and KEGG pathways was created using Pathway Studio software version 12.5 (Elsevier Inc., Rockville, MD, USA) [ 20 ]. Analysis of association between ANO7 and mucins in COAD An interaction network of ANO7 and mucin (MUC) genes (MUC1 to MUC24) [ 21 ] was constructed using GeneMANIA ( https://genemania.org/ ) [ 22 ]. The correlation between ANO7 and MUC2 gene expressions was analyzed in the COAD-TGCA dataset using GEPIA2. Additionally, KM survival analysis of MUC2 in COAD patients was performed using GEPIA2.

Results Differential expression of ANO7 gene in COAD and normal tissues The expression level of ANO7 gene in COAD and normal tissues was explored in the GEPIA2 and UALCAN databases. The data consistently demonstrated a significant decrease in ANO7 mRNA expression in the COAD samples compared to the normal tissues across both databases ( Fig. 1 ). Association between ANO7 expression and clinicopathological characteristics of COAD patients By utilizing UALCAN, we conducted an investigation into the association between ANO7 mRNA expression and various clinicopathological characteristics among COAD patients. The ANO7 expression demonstrated significant correlations with the patients’ race and histological subtypes. Specifically, ANO7 expression was notably higher in African-American patients compared to Asian patients ( Fig. 2B ). Furthermore, COAD patients diagnosed with mucinous adenocarcinoma exhibited significantly higher ANO7 expression levels compared to those with adenocarcinoma ( Fig. 2E ). No significant associations were observed between ANO7 expression and patient age ( Fig. 2A ), gender ( Fig. 2C ), cancer stages ( Fig. 2D ), or nodal metastasis status ( Fig. 2E ). Association between ANO7 expression and overall survival of COAD patients We performed KM survival analysis for overall survival in COAD patients, categorized into low- and high-ANO7 expression groups, using GEPIA2, KM plotter, and Survival Genie web tools. Across these distinct web tools, the data consistently indicated that COAD patients with low ANO7 expression had significantly shorter overall survival compared to those with high ANO7 expression ( Fig. 3 ). Co-expression network and functional enrichment of ANO7-correlated genes The top 100 genes that exhibited a positive correlation with ANO7 in the TCGA-COAD dataset were selected for subsequent co-expression network and functional enrichment analyses. A list of these ANO7-correlated genes is summarized in Supplementary Table 1 . The results obtained from GeneFriends showed that ANO7 displayed a strong co-expression correlation with kallikrein-related peptidase 3 (KLK3) (r = 0.78) and transmembrane serine protease 2 (TMPRSS2) (r = 0.71) ( Fig. 4 ). Enrichment analysis data highlighted significant enrichments in the GO biological process term "proteolysis" (FDR = 0.038) and the KEGG pathway term "mucin type O-glycan biosynthesis" (FDR < 0.001) ( Fig. 5 , Supplementary Table 2 ). Further analysis using Pathway Studio elucidated a molecular and functional network of ANO7-correlated genes related to proteolysis and mucin dynamics in colon cancer ( Fig. 6 ). Association between ANO7 and MUCs in COAD We further investigated the potential association between ANO7 and MUCs using GeneMANIA and GEPIA2 databases. Among all MUC genes, ANO7 showed a direct interaction only with MUC2, not with other MUCs ( Fig. 7A ). The result from GEPIA2 also indicated a significant correlation between ANO7 expression and MUC2 expression in the TCGA-COAD database ( Fig. 7B ). Following the same trend as ANO7, COAD patients with low MUC2 expression exhibited a notably shorter overall survival compared to those with high MUC2 expression ( Fig. 7C ).

Discussion ANO7 is recognized as a prostate-specific protein. It has been proposed as both a diagnostic and therapeutic target for prostate cancer [ 8 - 10 , 23 ]. Furthermore, a growing body of evidence has recently demonstrated the pathogenic role of ANO7 in several other cancers, including breast cancer, thyroid cancer, and neuroblastoma [ 24 - 26 ]. As a result, ANO7 holds promise as an intriguing target for cancer biomarkers. Our data analysis revealed that ANO7 expression is significantly lower in COAD tissues compared to normal tissues. This reduced ANO7 expression was associated with disease progression, and patients with a lower ANO7 expression level were linked to a poorer prognosis. This observation aligns with prior studies in prostate cancer [ 9 , 10 ], implying that ANO7 could potentially serve as a predictive marker for poor survival among COAD patients. While ANO7 is well-known as an anion channel protein, recent reports have unveiled its involvement in diverse biological processes, including vesicle transport and cell-contact interactions [ 23 ]. However, the functional role of ANO7 in COAD remains largely unknown. In our study, co-expression network analysis showed that ANO7 had a strong co-expression correlation with the proteolytic enzymes KLK3 and TMPRSS2. Enrichment analysis also revealed a significant enrichment of ANO7-correlated genes within the proteolysis pathway. This is consistent with previous data suggesting that proteolysis contributes to extracellular matrix (ECM) degradation, invasion, and metastasis, as well as the malignant transformation of CRC [ 27 ]. Furthermore, KLKs are recognized as hallmarks of cancers [ 28 ]. KLK3, known as prostate-specific antigen (PSA), serves as a possible biomarker for various types of cancers [ 29 - 31 ]. Previous studies have showed that PSA is expressed in colon cancer tissues [ 32 , 33 ] Serum PSA level holds prognostic significance in women with CRC, as patients with low values of percent free PSA exhibited a poor survival outcome [ 34 ]. A recent study has identified ANO7 along with KLK3 in extracellular vesicles isolated from seminal plasma [ 35 ]. Taken together, these findings suggested a promising avenue for further investigating the cooperative roles of ANO7 and KLK3 in the proteolytic process and their potential as diagnostic markers in COAD. According to KEGG pathway analysis, ANO7-correlated genes were significantly enriched in the mucin type O-glycan biosynthesis pathway. The mucin protein family consists of 24 members (MUC1 to MUC24) and plays important roles in various physiologic and pathogenic processes [ 21 ]. Aberrant expression and glycosylation of mucins are linked to CRC development and progression [ 36 ]. Among MUC family members, our interaction network analysis highlighted a potential relationship between ANO7 and MUC2. Their positive co-expression correlation was confirmed in the TCGA-COAD dataset. Low expressions of ANO7 and MUC2 were associated with a poor survival outcome for COAD patients. These findings align with previous studies that reported low MUC2 expression and its association with a poor prognosis in CRC [ 37 - 39 ]. In addition, a previous study has reported negative immunohistochemical expressions of MUC2 and KLK3 in primary signet-ring cell/histiocytoid carcinoma of the eyelid [ 40 ]. These data suggested the potential relationship among ANO7, MUC2, and KLK3. However, the role of ANO7 in the regulation of mucin biosynthesis and these novel connections need further elucidation. Our present study has demonstrated that conducting bioinformatic analyses on publicly available omics datasets can yield valuable insights into the prognostic significance and potential function of ANO7 in COAD. However, it is important to note that our analysis primarily relied on the TCGA dataset. The inclusion of independent cohort studies in future investigations would greatly enhance the robustness of the prognostic significance attributed to ANO7 in COAD. Moreover, further experimental studies are necessary to validate the insights derived from bioinformatics and provide a mechanistic understanding of ANO7 in the context of COAD. Lastly, future research to examine ANO7 protein expression levels in COAD tissues compared to normal tissues would lead to a more comprehensive understanding of the role of ANO7 in COAD and also serve to validate the transcriptomic insights gained from this study. In summary, ANO7 expression was significantly decreased in COAD tissues, and its low expression was associated with poor patient survival. ANO7 may play a role in the regulation of proteolysis and mucin biosynthesis. It may serve as a potential biomarker for COAD.

Chen Chen and Siripat Aluksanasuwn contributed equally to this work. Colon adenocarcinoma (COAD) is the predominant type of colorectal cancer. Early diagnosis and treatment can significantly improve the prognosis of COAD patients. Anoctamin 7 (ANO7), an anion channel protein, has been implicated in prostate cancer and other types of cancer. In this study, we analyzed the expression of ANO7 and its correlation with clinicopathological characteristics among COAD patients using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and the University of Alabama at Birmingham CANcer (UALCAN) databases. The GEPIA2, Kaplan-Meier plotter, and the Survival Genie platform were employed for survival analysis. The co-expression network and potential function of ANO7 in COAD were analyzed using GeneFriends, the Database for Annotation, Visualization and Integrated Discovery (DAVID), GeneMANIA, and Pathway Studio. Our data analysis revealed a significant reduction in ANO7 expression levels within COAD tissues compared to normal tissues. Additionally, ANO7 expression was found to be associated with race and histological subtype. The COAD patients exhibiting low ANO7 expression had lower survival rates compared to those with high ANO7 expression. The genes correlated with ANO7 were significantly enriched in proteolysis and mucin type O-glycan biosynthesis pathway. Furthermore, ANO7 demonstrated a direct interaction and a positive co-expression correlation with mucin 2 (MUC2). In conclusion, our findings suggest that ANO7 might serve as a potential prognostic biomarker and potentially plays a role in proteolysis and mucin biosynthesis in the context of COAD.

This project is funded by National Research Council of Thailand (NRCT) (Grant No. N42A660849) and Mae Fah Luang University. Supplementary Materials Supplementary data can be found with this article online at http://www.genominfo.org .

CC BY

no

2024-01-16 23:41:59

Genomics Inform. 2023 Dec 29; 21(4):e46

oa_package/02/6d/PMC10788358.tar.gz

PMC10788359

38224717

Introduction The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a devastating impact on human health and economic activities around the globe [ 1 ]. The virus, which first emerged in late 2019, quickly spread around the world to become a global pandemic, with cases reported in all corners of the world. As of early 2023, the virus has infected over 650 million people and caused over 6 million deaths, making it one of the deadliest pandemics in human history [ 2 ]. Governments around the world implemented various measures to curb the spread of the virus and protect the general public health. These policies included travel bans, quarantine protocols, closures of educational institutions, and social distancing measures. To evaluate the efficacy of these lockdown measures, a metric known as the Stringency Index (SI) has been employed [ 3 ]. The SI quantifies the degree of strictness of these measures and has been utilized to monitor the effectiveness of the implemented policies in controlling the spread of the virus, as well as to make predictions about the trajectory of the pandemic. In the ongoing effort to combat the COVID-19 pandemic, the emergence of new variants of the virus also presented a significant challenge. These variants which arise due to a genetic mutation, have been observed to exhibit increased transmissibility, altered disease severity, morbidity, and reduced sensitivity to vaccines, raising concerns about their potential impact on the pandemic [ 4 ]. One such variant of concern is the Omicron variant (B.1.1.529), which first emerged in November 2021 and has since spread rapidly to multiple countries [ 5 ]. Among omicron's subvariants, BA.5 has been the most dominant of all the strains, in many countries worldwide until late 2022 [ 6 ]. In addition to the emergence of these variants, the phenomenon of the "waning effect" or "vaccine fade" has been recognized as a contributing factor to the transmission dynamics of COVID-19 [ 7 ]. The waning effect refers to a decline in the level of immunity provided by a vaccine over time, which can occur due to a variety of factors such as the decline of antibody concentrations in the body, loss of immune memory, and the emergence of vaccine-resistant strains. The waning effect can therefore lead to an increased susceptibility to infection and necessitates additional doses for adequate protection. Several studies have been explaining the effect of vaccination in terms of hospitalizations and deaths [ 8 - 10 ] and its effectiveness against the COVID-19 infection, which wanes within a few months of receiving the second dose [ 11 , 12 ]. In a recent study, an additional dose after the second dose restored the vaccine’s effectiveness against COVID-19 [ 7 ]. In this study, we will refer to these additional doses as "booster doses," with the designation applying to any doses administered after the second dose. One of the key challenges in the COVID-19 crisis has been to accurately forecast the spread of the pandemic. Researchers from different fields have contributed to this challenge using various models including statistical models [ 13 - 19 ], machine learning models [ 20 - 25 ], and mathematical models [ 26 - 30 ]. In this study, we evaluated the impact of the waning effect measured using the effective immunity (EI) rate variable, in forecasting the future spread of the SARS-CoV-2 virus in Korea. We believe that the EI rate is a good measure for observing the waning effect, in that the EI rate may decrease over time but the cumulative vaccination rate (VR) always increases with time. The aims of the study include (1) to examine the effect of incorporating the EI rate variable on the prediction accuracy of the models, and (2) to determine the approximate onset time of the waning effect. This can be applied in predicting the next waves of the pandemic. This study employs both statistical and machine learning models to analyze the data and test the proposed objectives. The results of this research could provide valuable insights for decision-makers and public health officials in their efforts to control and manage the spread of COVID-19.

Methods Response variables The COVID-19 data consists of daily series of confirmed cases, death cases, intensive care unit (ICU) patients, VRs according to the number of inoculations (per hundred people), and the SI of South Korea. All variables were downloaded from Our World in Data (OWID) [ 31 ]. The daily confirmed cases and deaths were officially collected through the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University [ 32 ], while the ICU patient data was officially collected by the OWID team. Missing dates of confirmed cases, deaths, and ICU patients in OWID were downloaded from Korea's COVID-19 dashboard [ 33 ]. We used daily confirmed cases, deaths, and ICU patient data from South Korea. We used both raw and smoothed data (a 7-day window is applied to smooth the data). Our train period is from January 1, 2022 to October 24, 2022. Our test period is from October 25, 2022 to November 7, 2022 (14 days). This period was chosen due to the high proportion of daily cases caused by the Omicron variants. EI rate The EI rate is defined for each time point in our analysis and is an integrated measure for the second and booster doses. Being infected also creates a natural immunity in people but the individual data to distinguish whether an individual is infected or not is currently unavailable. Although infection also leads to natural immunity, data to distinguish individual infection status is currently unavailable. where t is any specific date, and V 2 t and V 3 t are the numbers of people who received the second and booster doses of the vaccines, respectively, during the time interval [ t - T , t ]. Here, T indicates the length of days an individual can retain his/her immunity (effective period or effective days) obtained from the second or booster dose before the waning effect of vaccination starts. In other words, it is assumed that the waning effect starts T days after vaccination, regardless of the date of observation. T varies in our study in order to observe varying prediction errors for each value of T of vaccination. According to the literature [ 34 ], this is usually after 90 days but it may vary with the country and type of COVID-19 vaccine received. Therefore, in our study, candidates for T were selected as 30, 60, 90, and 120 days. In South Korea, the booster dose was inoculated approximately three months after the second dose following the government policy, considering a time point t when a person received the first dose of vaccine. Then, we can safely assume there does not exist the same individual in the time interval [ t - T , t ], as long as T ≤90 days. This is because an individual receives the next dose 90 days after the previous dose. Fig. 1 shows how V 2 t and V 3 t are counted for any specific date t . Suppose an individual received her second dose in the time interval [ t - T , t ], the individual will receive the next dose after 90 days. If T ≤90, then she will be counted only once (in V 2 t and not in V 3 t ). Otherwise, if T >90, it is possible she is counted twice (both in V 2 t and V 3 t ). Thus, if we select any T , an individual cannot receive two doses at that time interval. For example, at T = 120, each individual with immunity may appear twice after receiving the next dose 90 days after the previous dose and included in V 2 t and V 3 t (the EI rate is taken as 1.0 in this case). Therefore, the proportion of people with immunity may exceed 1.0, which is unreasonable. In summary, the EI has the advantage that we can simply estimate the proportion of the whole population who has immunity at any given time point without individual data. Covariates and lagging effects The covariates considered in this study include the government SI, Omicron variant BA.5 rate, booster shot rate (BSR), and the EI rate. The SI was obtained from the Oxford COVID-19 Government Response Tracker [ 35 ], BSR from OWID [ 36 ], and the proportion of the Omicron variant BA.5 was downloaded from the CoVariants website [ 37 ] and GISAID [ 38 - 40 ]. The list of covariates is summarized in the table ( Table 1 ). Considering a given response variable as Y t and covariates as X t = ( x 1 t ,..., x Kt ), it is important to note that the effects of vaccination and intervention policies on the spread of COVID-19 may take some time to be observed. Therefore, it would be reasonable to consider this factor when predicting future daily confirmed cases, daily death cases, or ICU patients. We used a total of four lags: 7, 14, 21, and 28 days for SI and BSR in our models as follows: X t-7 + X t-14 + X t-21 + X t-28 . Five different covariate combinations, in addition to the null model (no covariates), were used to predict our response variables. The list of covariate combinations is summarized in the table ( Table 2 ). Models AutoRegressive Moving Average Model AutoRegressive Moving Average (ARMA) models for time series analysis were first suggested in Time Series Analysis: Forecasting and Control [ 41 ]. Since ARMA models could be applied only to stationary time series, multiplicative seasonal Autoregressive Integrated Moving Average (ARIMA) models were developed to utilize differentiation and include seasonality in ARIMA models [ 42 ]. To obtain future predictions, an R package forecast was used for fitting ARIMA and seasonal ARIMA models and the principle of parsimony was applied in this analysis. Instead of using the auto.arima() function in R like in previous studies [ 43 ], we compared Akaike information criterion and Bayesian information criterion values [ 44 ] for all possible seasonal ARIMA models fitted and chose the best model by limiting the orders of models to integer values chosen beforehand. This prevented the overfitting problem. Generalized Additive Model The Generalized Additive Model (GAM) is a regression model that allows the learning of nonlinear relationships between each covariate and mean response E( Y ), using the smooth function f i ( X i ) [ 45 ]. Here, we assumed our response variables followed a Poisson distribution and different smoothing functions f j were used depending on the covariates. For weekdays and dates, cubic splines and P-splines were used, respectively and thin plate regression splines were used for vaccination covariates and SI [ 46 ]. R package mgcv was used for fitting GAM models [ 47 , 48 ]. Time series Poisson Time series Poisson aims to model the conditional mean E ( Y t | F t -1 ) by a process { λ t }, such that E ( Y t | F t -1 ) = λ t . In this study, to consider negative covariate effects, we used a logarithmic link function and the model can be written again as follows: where, F t the history of the joint process { Y t , λ t , X t +1 } and η represents the effects of covariates. We also applied the Poisson assumption for this model, i.e., Y t | F t -1 ~ Poisson ( λ t ). Time Series following Generalized Linear Models (TSGLMs) are introduced in tscount: An R Package for Analysis of Count Time Series Following Generalized Linear Models [ 49 ]. Light Gradient Boosting Machine Light Gradient Boosting Machine (LightGBM) is a gradient boosting decision tree algorithm that can be used for tasks like regression and classification. LightGBM consists of decision trees as weak learners and adds models into the tree using a greedy style approach [ 50 ]. Based on the adaptive boosting algorithm, gradient boosting machines (GBM) can build a strong regression learner by iteratively combining a set of weak regression learners. GBM uses gradient descent for minimizing the loss function of a strong regression learner. To build our lightGBM model, the ‘LightGBM’ package in Python was used [ 51 ]. Bidirectional long short-term memory network To deal with time series data, long short-term memory (LSTM) network was considered as the deep learning approach [ 52 ]. Since LSTM takes only past information when training, we adopted bidirectional LSTM (Bi-LSTM) to consider backward propagation information as well [ 53 ]. The optimal bandwidth of the training period is selected among 7, 14, or 21 which yields the least validation mean squared error. To improve the model performance, the training process was conducted in both forward and backward directions. The model structure considered two hyperparameters: layer number {2, 3} and dropout rate {0, 0.2}. The model was developed in Python version 3.7.6 using Keras (version 2.4.3, https://github.com/keras-team/keras ) and TensorFlow (version 2.3.0, https://github.com/tensorflow/tensorflow ) libraries. Model performance For a given covariate combination and prediction model, performance was measured using the weighted mean absolute percentage error (WMAPE) that measures a model prediction accuracy using the test data. The model and covariate combination with the smallest test WMAPE values is taken as the best for forecasting. WMAPE is defined as follows: where y t and are actual and predicted values, respectively.

Results EI rate improves COVID-19 prediction accuracy For the five models (ARIMA, GAM, TSGLM, LightGBM, and Bi-LSTM) the prediction results for the daily confirmed cases for the vaccination lasting period T = 90, using raw data are summarized ( Table 3 ). The covariate combination numbers of Table 3 are in the same order with Table 2 . We compared covariate combinations SI + BSR and SI + EI. In the same way, covariate combinations SI + BA.5 rate + BSR and SI + BA.5 rate + EI are compared since the former uses BSR with BA.5 rate and the latter uses EI with BA.5 rate. We observed that using EI improves prediction accuracy for covariate combinations SI + EI and SI + BA.5 rate + EI, in comparison to combinations SI + BSR and SI + BA.5 rate + BSR, respectively. For ARIMA and GAM, prediction accuracy improved for combinations SI + EI and SI + BA.5 rate + EI, whereas for TSGLM, LightGBM, and Bi-LSTM, combination SI + EI showed higher prediction accuracy. Among all models, Bi-LSTM with EI as a covariate showed the best prediction. Results for smoothed data using daily confirmed deaths and ICU patients are listed in Application Note. Time to onset of waning effect To find the approximate vaccination lasting time T before the onset of waning effect, we compared WMAPE values of all models using the covariate combinations SI + EI and SI + BA.5 rate + EI with the baseline models (covariate combinations SI + BSR and SI + BA.5 rate + BSR) for various values of T. The test WMAPE values (daily confirmed cases) of combinations SI + EI and SI + BA.5 rate + EI for T = 30, 60, 90, and 120 are summarized in Table 4 . Note that T = 150 is not introduced here since EI exceeds 1.0 (and is considered as 1.0) for the majority of the training period, which indicates EI cannot be a good predictor. Meanwhile, T = 120 is included in the analysis since there exist periods where EI exceeds 1.0, but not as much as when T = 150. Overall, 90 days performs best for both covariate combinations (SI + EI and SI + BA.5 rate + EI). In order of performance, 90, 30, 60, and 120 are appropriate vaccination lasting times to be applied for the EI rate. The mean WMAPE values for all five models for each type of data are summarized in Table 5 . Note that the model average values of Table 4 are in the first column (raw daily cases). For both covariate combinations SI + EI and SI + BA.5 rate + EI, we observed that 90 days applied to the EI rate best reduces prediction error for raw daily cases and deaths. For raw ICU patients, 60 days showed the best performance. For smoothed data, 30 days showed the best performance for daily cases and deaths. 60 days showed the best performance for daily cases and ICU patients. Finally, 90 days performed well for ICU patients.

Discussion The COVID-19 pandemic represents the biggest global shock in decades that affected all major aspects of life [ 54 , 55 ]. Due to a lack of specific therapeutic agents or effective treatment against COVID-19, the outbreak elicited immense global interest in the development and distribution of safe COVID-19 vaccines capable of stopping the spread of COVID-19 disease. The Coalition for Epidemic Preparedness Innovations (CEPI) started working with global health authorities, biotech, governments, and academic collaborators to support the development of vaccines against COVID-19 [ 56 , 57 ]. The COVID-19 vaccine R&D landscape developed at an unprecedented scale and speed in that by December 11, 2020, the U.S. Food and Drug Administration issued the first emergency use authorization for the PfizerBioNTech COVID-19 [ 58 , 59 ]. After that, other countries followed and issued approvals for vaccines like the Moderna vaccine, Oxford-AstraZeneca vaccine, Sputnik V vaccine, and Johnson & Johnson vaccine [ 60 ]. The fast development of COVID-19 vaccines was expected to play the game-changer role in fighting the spread of COVID-19. However, although the vaccines could reduce the severity of COVID-19, they could not stop the spread of the virus permanently [ 61 ]. A vaccinated person could still contract the virus or pass the virus to another individual. Furthermore, one dose of the vaccine could not provide lasting immunity. Second doses and booster shots have to be received by the population to maintain immunity against COVID-19. The emergence of SARS-CoV-2 variants like the Omicron variant also posed a challenge to the efficacy of COVID-19 vaccines. A lot of uncertainties were raised over how long the primary vaccination series would remain effective and the ideal timing for booster doses. Several studies provided robust evidence of the waning effect of vaccine immunity over time [ 7 , 62 , 63 ]. In forecasting future COVID-19 situations, factors such as the waning effect and variants must be considered, thus highlighting the importance of additional doses and government policies. In terms of deciding the optimal time for booster shots before the waning effect occurs rate with only population data in the absence of individual data of vaccinated or infected people. Although studies discovered that immunity obtained by vaccinations may yield more durable protection than natural infection, immunity obtained by being infected still has a significant effect on the duration of immunity levels [ 64 ]. If subject-specific vaccination or infection data is available, there will be an improvement in prediction accuracy. Furthermore, the reinfection rate can be considered to estimate EI more accurately and predict potential waves in the future. While our analysis focused only on South Korea, our method of calculating the EI rate is straightforward and can be applied to other countries. This approach could improve the prediction of future pandemic patterns, including cases, deaths, and ICU patients. When we introduced the EI rate that we defined into each prediction model, the degree of improvement in prediction performance was different. For instance, when predicting raw daily confirmed cases, the GAM showed the most significant increase in performance (test WMAPE decreased from 0.785 to 0.211, an 86% decrease) when utilizing the booster rate. It was the second-best performance following the Bi-LSTM (test WMAPE 0.189). Since these two models can consider the non-linearity between the predictors and response variables, it can be inferred that modeling the nonlinear relationship between EI and response variables may contribute to improved prediction performance. In general, immunity starts waning after vaccination. To model the waning of immunity, we hypothesized that the population loses EI against the SARS-CoV-2 virus after a certain number of days (T days) from the last vaccination. Our models showed the best performance with an EI duration of T = 90 days, which suggests that the immunity waning effect likely starts around 90 days following the last vaccine dose. Thus, although not derived from experiments at an individual level, such as a serological test, we suggest our best-predicted T as evidence to estimate the onset of the waning effect. Understanding this timing is beneficial for healthcare policy decisions, such as establishing guidelines for the administration of booster doses. In conclusion, we can conclude immunity loss from inoculations occurs approximately after three months.Compared to utilizing the original booster shot rate, using the EI rate significantly reduces prediction error for all response variables: confirmed cases, deaths, and ICU patients. Furthermore, even though the most appropriate vaccination lasting time does vary between raw and smoothed data, we have shown that considering 90 days for the South Korean population is a reasonable choice for accurate predictions, especially on confirmed cases and deaths.

Vaccine development is one of the key efforts to control the spread of coronavirus disease 2019 (COVID-19). However, it has become apparent that the immunity acquired through vaccination is not permanent, known as the waning effect. Therefore, monitoring the proportion of the population with immunity is essential to improve the forecasting of future waves of the pandemic. Despite this, the impact of the waning effect on forecasting accuracies has not been extensively studied. We proposed a method for the estimation of the effective immunity (EI) rate which represents the waning effect by integrating the second and booster doses of COVID-19 vaccines. The EI rate, with different periods to the onset of the waning effect, was incorporated into three statistical models and two machine learning models. Stringency Index, Omicron variant BA.5 rate (BA.5 rate), booster shot rate (BSR), and the EI rate were used as covariates and the best covariate combination was selected using prediction error. Among the prediction results, Generalized Additive Model showed the best improvement (decreasing 86% test error) with the EI rate. Furthermore, we confirmed that South Korea’s decision to recommend booster shots after 90 days is reasonable since the waning effect onsets 90 days after the last dose of vaccine which improves the prediction of confirmed cases and deaths. Substituting BSR with EI rate in statistical models not only results in better predictions but also makes it possible to forecast a potential wave and help the local community react proactively to a rapid increase in confirmed cases.

This research was supported by research grants from the Ministry of Science and ICT, South Korea (No.2021M3E5E3081425).

CC BY

no

2024-01-16 23:41:59

Genomics Inform. 2023 Dec 29; 21(4):e50

oa_package/39/dc/PMC10788359.tar.gz

PMC10788360

38224718

Introduction Neoarius is a genus of catfish belonging to the family Ariidae within the order Siluriformes. Currently, it comprises 11 described species distributed in Australia and New Guinea, with conservation status ranging from "least concern" to "vulnerable" according to the International Union for Conservation of Nature Red List (IUCN) [ 1 ]. Among the 11 species that make up the Neoarius genus, six species occur in marine environments, namely Neoarius graeffei , Neoarius leptaspis , Neoarius pectoralis , Neoarius berneyi , Neoarius paucus while the others, such as Neoarius utarus , Neoarius midgleyi , Neoarius utarus , Neoarius latirostris , Neoarius coatesi , Neoarius taylori , and Neoarius velutinus , inhabit freshwater environments [ 2 ]. The reproductive period for these species typically starts in spring, around September, and extends until the end of summer, in February. Notably, N. graeffei employs a rare reproductive strategy known as mouthbrooding, where the eggs are incubated in the mouth of the adult individual until they mature enough to be independent [ 3 ]. The catfish of the Ariidae family have a wide distribution across the globe, being found in various regions and countries such as Brazil, Australia, and New Guinea. They inhabit coastal, estuarine, and large river regions in both tropical and temperate areas. The majority of species have a coastal distribution, but there are also exclusively marine species found at various depths, as well as species occurring in freshwater environments. In species from marine habitats, males exhibit a unique behavior of mouthbrooding, where they incubate the eggs in their mouths. This characteristic sets them apart within the Ariidae family. Currently, the family comprises 156 species distributed among 30 genera. The mitochondrial genome, also known as the mitogenome, consists of a circular extrachromosomal DNA molecule present in the mitochondria. In eukaryotic organisms, the mitochondrial genome has an average size of 16–17 kbp and contains highly conserved genes. In vertebrates, there are a total of 37 genes, including 13 protein-coding genes (PCGs), two rRNA genes, and 22 tRNA genes necessary for the translation of proteins encoded by mitochondrial DNA, in addition to the control region known as the D-loop. Comparing mitochondrial genomes from different groups allows for evolutionary and phylogenetic studies, as there is significant similarity among mitogenomes in closely related taxa. This similarity enables researchers to trace the evolutionary history and relationships between species and understand their genetic diversification over time [ 4 ]. The mitochondrial genome in fishes serves various purposes, such as phylogenetic reconstruction, phylogeography, population migration observation, geographic distribution analysis, genetic diversity analysis among distinct populations, examination of gene order variations, haplotype variations, and gene flow patterns. Therefore, conducting studies involving the mitochondrial genome in fishes, as well as other vertebrate groups, is of great importance [ 4 ]. The objective of this study is to describe the mitochondrial genome of eight out of the 11 existing species within the Neoarius genus, as none of the species currently have their mitogenome characterized. To achieve this, we assembled the mitogenomes of Neoarius berenyi , Neoarius utarus , Neoarius midgleyi , Neoarius graeffei , Neoarius utarus , Neoarius leptaspis , Neoarius paucus , and Neoarius aff. graeffei . Additionally, we conducted a phylogenetic analysis using the PCGs from the assembled mitogenomes, providing new insights into the interspecific phylogenetic relationships within Neoarius.

Methods For the completion of this study, DNA samples from Neoarius species were collected from muscular tissue and sequenced by Iridian Genomics In platform HiSeq x Ten of Illumina. The resulting sequence data were provided by Dr. Ricardo Betancur through Sequence Read Archive (SRA) files hosted on NCBI ( Table 1 ). These files were imported into the Galaxy Europe platform [ 5 ]. Subsequently, we conducted mitochondrial genome assembly using NOVOplasty v4.2 with a K-mer size of 39 [ 6 ]. We utilized sequences from the cytochrome B oxidase gene of the respective species available on GenBank ( Table 1 ) as seeds for the assembly. The circularized sequences were then annotated using the MitoAnnotator software on the MitoFish server [ 7 ]. Finally, a comparative analysis was conducted using BLAST among all Neoarius , Arius , Hypostomus , and Occidentarius mitogenomes included in our study, along with our assembly of N. graeffei , using the BRIG software [ 8 ]. For phylogenetic reconstruction, we manually extracted all 13 PCGs from the eight Neoarius mitogenomes, as well as the PCGs from ten other Siluriformes species available on GenBank ( Supplementary Material 1 ). Individual PCGs were aligned using MEGA 11 software [ 9 ] with the MUSCLE algorithm [ 10 ]. Subsequently, alignments were concatenated using SequenceMatrix v1.7.8 software [ 11 ]. Phylogeny was generated using IQ-TREE web server software [ 12 ], with parameters of 10,000 replicates of Ultrafast Bootstrap iterations and replicates. Tree visualization was performed using the Interactive Tree of Life (IToL) online tool [ 13 ].

Results and Discussion We observed that the mitochondrial genomes have similar characteristics among them. All mitogenomes presented 22 tRNA genes, 13 PCGs, 2 rRNA genes, and a control region called the D-loop, which is consistent with other groups within the same family and even what is typically expected in vertebrates ( Fig. 1 ) [ 4 , 14 - 16 ]. The size of the mitochondrial genomes was also similar, with 16,709 bp for N. berneyi , N. graeffei , N. leptaspis , N. paucus , and N. midgleyi , 16,702 bp for N. utarus , 16,710 bp for N. aff. graeffei RB-2021, and 16,711bp for N. pectoralis ( Supplementary Material 2 ). The complete mitochondrial genomes of N. berenyi , N. midgleyi , N. leptaspis , N. aff. graeffei , and N. paucus showed a CG composition of 45%, while N. utarus , N. pectoralis , and N. graeffei presented 44% of CG content. These calculations were performed using the geecee tool [ 17 ]. The largest gene in the mitochondrial genome was ND5, occupying 5.48% of the entire mitogenome for all species, with a variation of 913 bp and 914 bp. The phylogeny demonstrated a monophyletic grouping among Neoarius species, which could be separated into two distinct clades. One of these clades showed N. berneyi as the sister group to the clade formed by N. graeffei and N. utarus , while in the other clade, we observed, N. midgleyi as the first species to diverge, followed by N. pectoralis , and with N. leptaspis as the sister group to the clade containing N. paucus and N. aff. graeffei ( Fig. 2 ). All internal branches of Neoarius showed high bootstrap values (>90). An interesting observation in our study was that the mitogenomes from the libraries identified as N. aff. graeffei and N. graeffei did not group together and, in fact, each of them fell into one of the two Neoarius subclades, indicating that both samples were extracted from different species within the genus. Few studies have a complete phylogeny of the genus; however, from the limited number of species present in the phylogenetic relationships, we can make some comparisons with the phylogeny observed in the present study, as in the work of Betancur [ 18 ]. In the work of Betancur [ 18 ], a phylogenetic reconstruction of the family Ariidae was conducted using molecular data, including the cytochrome b , ATP synthase subunit 6 and 8 , 12S and 16S ribosomal genes, and the nuclear rag2 gene. It was observed that N. graeffei aligned closely to N. berenyi , but between these two species, it aligned with N. aff. graeffei . However, when considering the overall phylogenetic relationship, the grouping of these two species remains quite similar, with N. utarus included in the same clade [ 18 ]. Another work involving phylogenetic reconstruction of the Neoarius genus is the study by Barathkumar and Thangaraj [ 19 ]. In the study by Barathkumar and Thangaraj [ 19 ], molecular data, specifically the cytochrome oxidase 1 gene, was used to conduct the phylogenetic reconstruction of the families Ariidae, Bagridae, and Plotosidae. Among the Neoarius genus, only N. midgleyi and N. graeffei were present in the study. The phylogenetic relationship revealed a grouping between these two species. Additionally, some species from the Arius genus were also included in the study, but there was no alignment of Neoarius and Arius in the same clade [ 19 ].

Results and Discussion We observed that the mitochondrial genomes have similar characteristics among them. All mitogenomes presented 22 tRNA genes, 13 PCGs, 2 rRNA genes, and a control region called the D-loop, which is consistent with other groups within the same family and even what is typically expected in vertebrates ( Fig. 1 ) [ 4 , 14 - 16 ]. The size of the mitochondrial genomes was also similar, with 16,709 bp for N. berneyi , N. graeffei , N. leptaspis , N. paucus , and N. midgleyi , 16,702 bp for N. utarus , 16,710 bp for N. aff. graeffei RB-2021, and 16,711bp for N. pectoralis ( Supplementary Material 2 ). The complete mitochondrial genomes of N. berenyi , N. midgleyi , N. leptaspis , N. aff. graeffei , and N. paucus showed a CG composition of 45%, while N. utarus , N. pectoralis , and N. graeffei presented 44% of CG content. These calculations were performed using the geecee tool [ 17 ]. The largest gene in the mitochondrial genome was ND5, occupying 5.48% of the entire mitogenome for all species, with a variation of 913 bp and 914 bp. The phylogeny demonstrated a monophyletic grouping among Neoarius species, which could be separated into two distinct clades. One of these clades showed N. berneyi as the sister group to the clade formed by N. graeffei and N. utarus , while in the other clade, we observed, N. midgleyi as the first species to diverge, followed by N. pectoralis , and with N. leptaspis as the sister group to the clade containing N. paucus and N. aff. graeffei ( Fig. 2 ). All internal branches of Neoarius showed high bootstrap values (>90). An interesting observation in our study was that the mitogenomes from the libraries identified as N. aff. graeffei and N. graeffei did not group together and, in fact, each of them fell into one of the two Neoarius subclades, indicating that both samples were extracted from different species within the genus. Few studies have a complete phylogeny of the genus; however, from the limited number of species present in the phylogenetic relationships, we can make some comparisons with the phylogeny observed in the present study, as in the work of Betancur [ 18 ]. In the work of Betancur [ 18 ], a phylogenetic reconstruction of the family Ariidae was conducted using molecular data, including the cytochrome b , ATP synthase subunit 6 and 8 , 12S and 16S ribosomal genes, and the nuclear rag2 gene. It was observed that N. graeffei aligned closely to N. berenyi , but between these two species, it aligned with N. aff. graeffei . However, when considering the overall phylogenetic relationship, the grouping of these two species remains quite similar, with N. utarus included in the same clade [ 18 ]. Another work involving phylogenetic reconstruction of the Neoarius genus is the study by Barathkumar and Thangaraj [ 19 ]. In the study by Barathkumar and Thangaraj [ 19 ], molecular data, specifically the cytochrome oxidase 1 gene, was used to conduct the phylogenetic reconstruction of the families Ariidae, Bagridae, and Plotosidae. Among the Neoarius genus, only N. midgleyi and N. graeffei were present in the study. The phylogenetic relationship revealed a grouping between these two species. Additionally, some species from the Arius genus were also included in the study, but there was no alignment of Neoarius and Arius in the same clade [ 19 ].

Conclusion The mitochondrial genomes of the studied species showed many similarities in terms of size, composition, and nucleotide percentage. Despite their stable organization, the mitogenomes proved to be valuable in understanding the molecular evolution of these eight species belonging to the Neoarius genus. New studies using other sources of data, such as phylogenies based on nuclear loci or even the assembly of mitochondrial genomes from the remaining species, can be applied to fill possible gaps in the knowledge of the group's evolution and gain a better understanding of the speciation process.

The genus Neoarius , known as marine catfish, is a group of the family Ariidae, composed of 10 species found in Oceania. None of the species in this genus have their mitochondrial genome described, which is highly valuable in phylogenetic and molecular evolution studies. For the present work, eight species from the Neoarius genus were selected: Neoarius utarus , Neoarius midgleyi , Neoarius graeffei , Neoarius leptaspis , Neoarius berenyi , Neoarius paucus , Neoarius pectoralis , and Neoarius aff. graeffei . DNA sequences of the eight species were obtained through the NCBI Sequence Read Archive (SRA) database, and the mitochondrial genomes were assembled using the NOVOplasty tool on the Galaxy platform, subsequently annotated with the MitoAnnotator tool. We then utilized the protein-coding genes from the mitogenomes to estimate the phylogenetic relationships within the group, including seven additional mitogenomes available in the NCBI. In all species, the mitochondrial genomes presented 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes, and 1 D-loop.

Supplementary Materials Supplementary data can be found with this article online at http://www.genominfo.org .

CC BY

no

2024-01-16 23:41:59

Genomics Inform. 2023 Dec 29; 21(4):e51

oa_package/e0/9c/PMC10788360.tar.gz

PMC10788361

38224719

Introduction The development of the digital polymerase chain reaction (PCR) method, third-generation PCR equipment, has recently changed the research trend of the existing microbial molecular diagnosis field. Especially, a new digital PCR equipment ‘LOAA (Lab On An Array) digital real-time PCR analyzer (Optolane, Seongnam, Korea)’ has 1,000 times more fluorescence detection sensitivity than quantitative real-time polymerase chain reaction (qRT-PCR), second-generation PCR equipment, and is a high-performance PCR equipment that can detect each PCR amplification reaction in more than 20,000 nano-sized PCR reaction wells present on a single semiconductor chip-based micro electro mechanical system (MEMS) [ 1 , 2 ]. Above all things, unlike qRT-PCR, LOAA digital PCR is very useful in the field of specific pathogens or cancer diagnosis because it has independent ‘absolute gene quantitative analysis systems’ within equipment without a separate standard curve quantification analysis [ 3 , 4 ]. In the case of LOAA digital PCR, about 20,000 PCR reaction wells are distributed on a semiconductor chip, and PCR amplification and fluorescence detection proceeds from 0 or 1 template DNA molecule included per well. This characteristic valid a ‘Poisson distribution’ principle that can calculate positive and negative reactions on PCR amplification detected in each well in detail, enabling absolute quantities in the sample for a specific gene to be identified without a separate standard curve analysis. The formula for absolute quantification method within a sample of a specific gene based on the 'Poisson distribution' principle is as follows: However, although the digital PCR generates such high-efficiency molecular diagnostic outputs, the cost burden of one-time semiconductor-based experimental consumables is high, so if the quality and quality of template DNA are unstable during the experiment, consumer preference may decrease according to the experimental results. For example, metagenomic DNA (mDNA) samples isolated from skin applied in the human skin healthcare field are difficult to derive clear research results because their quantity and quality are often unstable due to various factors (e.g., Whether to wash, use skin care products, UV exposure, and individual living environment) affecting the growth environment of microorganisms on the human skin surface [ 5 , 6 ]. For this reason, the results of publishing research cases related to molecular microbial diagnosis using digital PCR in these unstable template DNA conditions, isolated from human skin, are insufficient, and for digital PCR to be optimized in various research fields in the future, it is necessary to identify these issues. In this study, we aimed the comparing and verifying the quantitative efficiency of Staphylococcus aureus related to atopic disease occurrence within mDNA samples collected from lesions and non-lesions of seven atopic patients using qRT-PCR and digital PCR. We compared the specific gene detection and quantitative efficiency of the two PCR equipment under unstable template DNA conditions to evaluate the applicability of digital PCR to research fields such as skin microbiome studies that are highly affected by template DNA quality. In addition, by comparing the relative frequency difference of S. aureus between lesions and non-lesions skin sites in atopic patients, we demonstrated the reliability of the comparison results of quantitative efficiency for particular microorganisms between the two equipment [ 7 ]. Ultimately, we suggest through this study that digital PCR has high utilization value for various human healthcare industries related to molecular microbial diagnosis.

Methods and Results Particular bacterial species-specific primer and probe sets design method In this study, we tried to verify the detection and quantification efficiency of digital PCR equipment for specific bacterial species within the unstable template mDNA sample. Therefore, for this verification, we selected S. aureus , which is expected to exist on skin sites samples of atopic patients, as a specific bacterial species considering previous studies showing that S. aureus affects the atopic disease [ 8 - 10 ]. First, we designed a S. aureus –specific primer and probe set to detect and quantify a particular bacterial species present within mDNA samples extracted from various microbial pools collected from the surface of human skin, and to compare the detection and quantification efficiency between qRT-PCR and digital PCR. The experimental verification process for the primer and probe set design we conducted is as follows. Bacterial gene selection for targeting particular species The greA gene encodes a transcription elongation factor that affects bacterial gene transcription by regulating gene promoters, thereby regulating the environmental adaptation of bacteria [ 11 ]. In addition, the greA gene is recognized as a bacterial housekeeping gene, which, like the bacterial 16S ribosomal RNA, is an evolutionarily conserved transcription factor widely distributed in prokaryotes [ 12 ]. Retrieval of coding sequence region base information from reference database We obtained sequence information (FASTA format) of the greA gene coding sequence region (CDS) for 22 different S. aureus strains (at the strain level) annotated in the National Center for Biotechnology Information (NCBI) reference database ( Supplementary Table 1 ). This process is essential to improve primer and probe binding accuracy and specificity, as the exact strain information of S. aureus present within the human skin-derived mDNA samples applied in this study is unclear. Selection of target-specific sequence regions for PCR reaction To select primer sequences that could detect all 22 different S. aureus strains, multiple sequence alignment method (MSA) of each CDS information was performed using BioEdit 7.2.5v software ( Supplementary Fig. 1A ). Two consistent regions identified through the MSA method were selected as forward and reverse primer sequences ( Table 1 ). In silico test for pre-validating primer binding specificity We used the Oligo calc ( http://biotools.nubic.northwetern.edu/ ) and ‘Oligo Analysis ( http://www.operon.com/tools/oligo-analysis-tool.aspx )’ open web tools to pre-simulate the suitability of the selected primer pairs for experimental application (including Tm values, GC%, and probability of primer dimer formation). Next, the NCBI nucleotide Basic Local Alignment Search Tool (BLAST) tool was used to confirm species-specificity for each primer sequence and amplification region included in each primer pair ( Supplementary Fig. 1B ). Specific probe design Finally, we designed a specific probe sequence region within between each selected primer sequence ( Table 1 , Supplementary Fig. 1A ). The fluorescent reporter dyes and quencher applied in the probe design were 6-FAM (6-carboxy fluorescein) and SFCQ1 (SFC probe, Cheongju, Korea), which were attached to the 5' and 3' end regions of the selected probe sequences, respectively. Comprehensive molecular genetical validation for primer/probe-specificity To demonstrate the species-specificity of the pre-designed S. aureus –specific primers and probe through experimental validation, we set up a comparison group ( Table 2 ). Information about the comparison group is as follows—positive control-1 (PC1): genomic DNA (gDNA) of a single strain of S. aureus ATCC6538; for gDNA extraction of PC, HiGene Genomic DNA Prep Kit For microorganisms (BIOFACT, Daejeon, Korea) was used, and all experimental procedures were performed according to the official protocol guide provided in the kit; negative control (NC) : ‘Siga-Microbial community DNA mix MBD0026’ contains genomic DNA from 10 bacterial species ( Akkermansia muciniphila , Bacillus subtilis , Burkholderia pyrrocinia , Escherichia coli , Enterococcus faecalis , Pseudomonas aeruginosa , Proteus mirabilis , Proteus vulgaris , Porphyromonas gingivalis , and Salmonella enterica ) are included in uniform proportions within one sample tube (Sigma-Aldrich, St. Louis, MO, USA); positive control-2 (PC2): genomic DNA of the S. aureus ATCC6538 was added to the NC; this control was set up to confirm that the specific-primers within the different microbial gDNA pools specifically bind to S. aureus . Therefore, we validated the experimental suitability (binding sensitivity) of S. aureus –specific primers and probes for application in qRT-PCR and digital PCR through a comprehensive molecular genetic experimental process. The experimental procedure was as follows. General PCR validation for confirming primer binding specificity to S. aureus First, we performed a general PCR validation to confirm that our pre-designed primers specifically bind to the CDS region of the greA gene on the S. aureus genome ( Fig. 1A ). PCR verification confirmed the presence of a DNA amplicon band approximately 146 bp long in PC1 and PC2, and no amplicon DNA was identified in the NC. This shows that the primers we designed bind specifically to S. aureus and do not bind to the NC (T100 Thermal Cycler, Bio-Rad, Hercules, CA, USA). The running condition of the PCR is as follows: pre-denaturation 95.0°C, 5 min, denaturation 95.0°C, 30 s, annealing 59°C, 40 s, elongation 72.0°C, 15 s, final-extension 72.0°C, 30 s, and total PCR cycle was 30. Additionally, we confirmed that specific primers are bound normally to S. aureus genomic DNA within a complex microbial DNA pool through PCR reaction results of PC2 and could confirm the potential applicable for specific detection of S. aureus even within skin-derived mDNA samples to be applied in this study. Optimizing the primer and probe experimental conditions for qRT-PCR and digital PCR Next, to set the optimal experimental conditions of primers and probes for application to qRT-PCR and digital PCR, preferentially, we performed the qRT-PCR validation using PC1 template DNA sample with S. aureus –specific primer, and the primer concentration was set the 25 pmol, probe concentration was set 20 pmol, and 10 pmol conditions, respectively. The qRT-PCR (CFX Opus 96 Real-Time PCE System, Bio-Rad; BioFACT 2× Multi-Star Real-Time PCR Master Mix For Probe, UDG system) experimental conditions were as follows ( Supplementary Table 2 ); pre-denaturation 95.0°C 10 min, denaturation 95.0°C 10 s, annealing/Flour detection 61°C 10 s, elongation 72.0°C 15 s, and total PCR cycle was 45). As a result, the resolution of detection fluorescence value (RFU; relative fluorescence units) for the S. aureus greA gene detected on the probe concentration condition of 20 pmol about PC1 and PC2 samples were found to be higher compared to the 10 pmol concentration condition, confirming that this experimental condition was the most optimal ( Fig. 1B ). Standard curve analysis about positive control ( S. aureus ) using qRT-PCR We performed a standard curve analysis using the Ct value reflected about the positive control to contrast the results of qRT-PCR–based detection and quantification of S. aureus within mDNA samples applied in this study ( Fig. 2 , Supplementary Table 3 ). We performed qRT-PCR in triplicate to confirm the reliability of the standard curve analysis results and performed a standard curve analysis using 10-fold serial-diluted template DNA (PC1) samples (10 1 , 10 0 , 10 -1 , and 10 -2 diluted samples, respectively). Standard curve analysis for PC1 based on qRT-PCR showed that the average Ct values for each dilution factor were 10 ng, 24.67; 1 ng, 28.90; 0.1 ng: 33.20; 0.01 ng, 38.24; and the R2 value of trend line was calculated on the standard curve graph was approximately 0.99. Primer binding specificity cross-validation through Sanger sequencing validation Finally, we performed a Sanger sequencing (ABI 3500 Genetic Analyzer, Thermo Fisher Scientific, Waltham, MA, USA) and NCBI nucleotide BLAST test to verify that the primer designed in this study correctly targeted the S. aureus greA gene CDS region and used it for PCR amplification ( Fig. 1C ). In this verification step, since the PCR amplification region to be identified is too short and unsuitable for conducting the Sanger sequencing, we performed the sequencing process by expanding the gene reading region through the TA cloning method (TOPcloner TA Kit, Enzynomics, Daejeon, Korea [ 13 ]). Competent cells required in the transformation process for gene cloning were performed using DH5α Chemically Competent E. coli (Enzynomics), and white colonies (potentially successful transformation and greA gene ligation) identified in 37°C incubation were selectively harvested and applied for sequencing process. The primer pair applied for Sanger sequencing to read the greA gene amplicon region was the M13 region-specific primer set contained in the TA cloning plasmid vector sequence. As a result, we confirmed from the base-pair sequence reading data that both forward and reverse primer sequence information were included. And then, to verify that the generated sequencing data contained CDS regions (PCR amplicon region) of the S. aureus greA gene, we input the sequencing data into the NCBI nucleotide BLAST search engine and compared it with annotated bacterial classification information within the NCBI reference database. As a result of the BLAST test, we confirmed that only bacterial identification information for S. aureus was matched from the NCBI reference database. We could also confirm that the BLAST test detected various S. aureus strains (at the strain level) rather than a single bacterial strain. This result showed that the S. aureus –specific primer, considered up to the strain level, has broad detection efficiency for various S. aureus strains within any type of clinical sample. Detection and quantification for S. aureus using qRT-PCR method We used human skin-derived mDNA samples as template DNA samples to confirm the efficiency of detection and quantification of specific microbial DNA within low molecule density template DNA using qRT-PCR. For this process, a total of 14 skin-derived clinical samples were obtained from seven patients with atopic dermatitis who visited the medical center (Kyung Hee University College of Medicine, Seoul, Republic of Korea), divided into lesion (case group) and non-lesion (control group) skin sites. Diagnosing atopic diseases of all participants was performed according to a dermatologist’s examination. Approval for the study protocol, informed consent forms, and related supporting documents was granted by the institutional review boards at the Korean Skin Research Center in South Korea (IRB No. HBABN01-220509-HRBR-E0113-01). All mDNA was extracted using the QIAamp PowerFecal Pro DNA kit (Qiagen, Hilden, Germany), and all experimental procedures were performed according to the official protocol guide provided with the kit. The average concentration values of extracted mDNA for each comparison group were checked with the control group 2.05 ng/μL and test group 4.10 ng/μL, respectively ( Supplementary Table 4 ), by using a Thermo Scientific NanoDrop One/Onec Microvolume UV-Vis Spectrophotometer (Thermo Fisher Scientific). Next, we used qRT-PCR to determine the expected microbial frequency of S. aureus present within the 14 mDNA samples with a comparative analysis between groups to confirm the detection and quantification efficiency. The experimental procedure was as follows. Normalization of bacterial quantification within each skin microbiome sample Before the detection and quantitative analysis of S. aureus using qRT-PCR, we performed a qRT-PCR-based standard curve analysis using a primer pair targeting the V5 hyper-variable region included on the bacterial 16S ribosomal RNA (forward primer: 5′-GGATTAGATACCCTGGTA-3′, reverse primer: 5′-CCGTCAATTCMTTTRAGTTT-3′) to standardize the amount of potential bacterial DNA distributed within each 14 mDNA samples to equal condition ( Table 3 , Fig. 3 ). In this process, we normalized the concentration of all mDNAs to 10ng, and then we're going to confirm the uniformity of concentration and reliability of the experiment through standard curve graph analysis. We performed standard curve analysis about expected bacterial DNA quantity by diluting each normalized mDNA through a 10-fold serial dilution method (10 1 , 10 0 , 10 -1 , 10 -2 , respectively). The qRT-PCR experimental condition of standard curve analysis for 14 mDNA samples with bacterial 16S V5 primer pair was as follows: pre-denaturation 95.0°C 10 min, denaturation 95.0°C, 10 s, annealing/Flour detection 60°C, 15 s, elongation 72.0°C, 15 s, and total PCR cycle was 45. As a result, we confirmed that the average Ct values reflecting the potential bacterial DNA concentration for each dilution factor identified within the control group were 10 ng, 25.24; 1 ng, 28.67; 0.1 ng, 31.82; and the r 2 value about the trend line calculated in the standard curve graph was 0.94. In the test group, we confirmed that the average Ct values for each diluted DNA sample were 10 ng, 25.72; 1 ng, 28.70; 0.1 ng, 30.81; and the r 2 value was 0.9166. In the case of the ‘Test-7’ sample, considering that the concentration and quality of mDNA were low and unstable at 0.82 ng (A260/280: 2.37, A260/230: 0.01), we judged that it was difficult to quantify bacterial DNA by qRT-PCR because there were few potential bacterial communities present in this sample. Therefore, through this standard curve analysis, we could confirm that the potential bacterial DNA quantities within the 13 mDNA samples, except for the ‘Test-7’ sample, were equally normalized and suitable for detection and quantification analysis for S. aureus . Evaluation of absolute and relative quantification effect for S. aureus via qRT-PCR We evaluated the absolute and relative quantification effects of S. aureus in the skin microbiome sample through qRT-PCR using S. aureus –specific primer and probe set. Before the experiment, we confirmed that the distilled water used for making the qRT-PCR mixture solution was free of microbial contamination by checking the Ct value: N/A result reflected in the non-template DNA control (NTC). The qRT-PCR amplification conditions applied in this experiment were as follows: template DNA (mDNA) 10 ng; probe concentration 20 pmol, GreA primer concentration 25 pmol (this concentration condition was based on previous experimental results showing the most optimal running condition). As a result, we were not able to detect and quantify S. aureus within both comparison groups, which was not the expected result for this experiment ( Table 4 ). Bacterial DNA normalization results confirmed by standard curve analysis demonstrated that the bacterial DNA in the skin microbiome sample was normalized to approximately the same amount, but due to the unstable quality of the mDNA (low concentration and low purity) and the low frequency of potential S. aureus expected to be present in it. Therefore, we judged that absolute and relative quantification of S. aureus within mDNA samples using the qRT-PCR method could not be meaningfully performed. Quantification of S. aureus within each skin microbiome sample using LOAA digital PCR We evaluated the applicability of the digital PCR platform to the microbial molecular diagnosis field by validating the detection and quantification effect for a proportion of S. aureus , which is expected to be present in each skin microbiome sample set in this study, using LOAA digital PCR equipment ( Table 5 , Fig. 4 ). The experimental group was set in the same as the process of detecting and quantifying S. aureus through the qRT-PCR method. Before conducting the digital PCR reaction for each comparison group, we confirmed that the number of expected copies of the greA gene within S. aureus genomic DNA in the PC1 and NC groups was 69,109 copies/μL and 0.00 copies/μL, respectively. Next, the average copies number of S. aureus greA gene identified in the control and test groups was 6.58 copies/μL and 36.28 copies/μL, respectively. However, in the case of the ‘Tes-7’ sample identified in the qRT-PCR results, it was confirmed that a low number of gene copies was detected, unlike the other mDNA samples in the test group, similar to the ‘16S V5 standard curve analysis’ result ( Table 3 ), which was evaluated to have little bacterial genomic DNA density within this template DNA sample. Additionally, we could confirm that the potential bacterial frequency of S. aureus within the mDNA samples isolated from lesion skin sites of atopic patients was relatively high compared to the non-lesion skin sites. Considering previous studies showing that the dominant rate of S. aureus identified in atopic patients' lesions sites is higher than that of non-lesion sites, we could confirm the reliability of the S. aureus quantitative analysis results between each comparison group derived through LOAA digital PCR [ 14 ].

Methods and Results Particular bacterial species-specific primer and probe sets design method In this study, we tried to verify the detection and quantification efficiency of digital PCR equipment for specific bacterial species within the unstable template mDNA sample. Therefore, for this verification, we selected S. aureus , which is expected to exist on skin sites samples of atopic patients, as a specific bacterial species considering previous studies showing that S. aureus affects the atopic disease [ 8 - 10 ]. First, we designed a S. aureus –specific primer and probe set to detect and quantify a particular bacterial species present within mDNA samples extracted from various microbial pools collected from the surface of human skin, and to compare the detection and quantification efficiency between qRT-PCR and digital PCR. The experimental verification process for the primer and probe set design we conducted is as follows. Bacterial gene selection for targeting particular species The greA gene encodes a transcription elongation factor that affects bacterial gene transcription by regulating gene promoters, thereby regulating the environmental adaptation of bacteria [ 11 ]. In addition, the greA gene is recognized as a bacterial housekeeping gene, which, like the bacterial 16S ribosomal RNA, is an evolutionarily conserved transcription factor widely distributed in prokaryotes [ 12 ]. Retrieval of coding sequence region base information from reference database We obtained sequence information (FASTA format) of the greA gene coding sequence region (CDS) for 22 different S. aureus strains (at the strain level) annotated in the National Center for Biotechnology Information (NCBI) reference database ( Supplementary Table 1 ). This process is essential to improve primer and probe binding accuracy and specificity, as the exact strain information of S. aureus present within the human skin-derived mDNA samples applied in this study is unclear. Selection of target-specific sequence regions for PCR reaction To select primer sequences that could detect all 22 different S. aureus strains, multiple sequence alignment method (MSA) of each CDS information was performed using BioEdit 7.2.5v software ( Supplementary Fig. 1A ). Two consistent regions identified through the MSA method were selected as forward and reverse primer sequences ( Table 1 ). In silico test for pre-validating primer binding specificity We used the Oligo calc ( http://biotools.nubic.northwetern.edu/ ) and ‘Oligo Analysis ( http://www.operon.com/tools/oligo-analysis-tool.aspx )’ open web tools to pre-simulate the suitability of the selected primer pairs for experimental application (including Tm values, GC%, and probability of primer dimer formation). Next, the NCBI nucleotide Basic Local Alignment Search Tool (BLAST) tool was used to confirm species-specificity for each primer sequence and amplification region included in each primer pair ( Supplementary Fig. 1B ). Specific probe design Finally, we designed a specific probe sequence region within between each selected primer sequence ( Table 1 , Supplementary Fig. 1A ). The fluorescent reporter dyes and quencher applied in the probe design were 6-FAM (6-carboxy fluorescein) and SFCQ1 (SFC probe, Cheongju, Korea), which were attached to the 5' and 3' end regions of the selected probe sequences, respectively. Comprehensive molecular genetical validation for primer/probe-specificity To demonstrate the species-specificity of the pre-designed S. aureus –specific primers and probe through experimental validation, we set up a comparison group ( Table 2 ). Information about the comparison group is as follows—positive control-1 (PC1): genomic DNA (gDNA) of a single strain of S. aureus ATCC6538; for gDNA extraction of PC, HiGene Genomic DNA Prep Kit For microorganisms (BIOFACT, Daejeon, Korea) was used, and all experimental procedures were performed according to the official protocol guide provided in the kit; negative control (NC) : ‘Siga-Microbial community DNA mix MBD0026’ contains genomic DNA from 10 bacterial species ( Akkermansia muciniphila , Bacillus subtilis , Burkholderia pyrrocinia , Escherichia coli , Enterococcus faecalis , Pseudomonas aeruginosa , Proteus mirabilis , Proteus vulgaris , Porphyromonas gingivalis , and Salmonella enterica ) are included in uniform proportions within one sample tube (Sigma-Aldrich, St. Louis, MO, USA); positive control-2 (PC2): genomic DNA of the S. aureus ATCC6538 was added to the NC; this control was set up to confirm that the specific-primers within the different microbial gDNA pools specifically bind to S. aureus . Therefore, we validated the experimental suitability (binding sensitivity) of S. aureus –specific primers and probes for application in qRT-PCR and digital PCR through a comprehensive molecular genetic experimental process. The experimental procedure was as follows. General PCR validation for confirming primer binding specificity to S. aureus First, we performed a general PCR validation to confirm that our pre-designed primers specifically bind to the CDS region of the greA gene on the S. aureus genome ( Fig. 1A ). PCR verification confirmed the presence of a DNA amplicon band approximately 146 bp long in PC1 and PC2, and no amplicon DNA was identified in the NC. This shows that the primers we designed bind specifically to S. aureus and do not bind to the NC (T100 Thermal Cycler, Bio-Rad, Hercules, CA, USA). The running condition of the PCR is as follows: pre-denaturation 95.0°C, 5 min, denaturation 95.0°C, 30 s, annealing 59°C, 40 s, elongation 72.0°C, 15 s, final-extension 72.0°C, 30 s, and total PCR cycle was 30. Additionally, we confirmed that specific primers are bound normally to S. aureus genomic DNA within a complex microbial DNA pool through PCR reaction results of PC2 and could confirm the potential applicable for specific detection of S. aureus even within skin-derived mDNA samples to be applied in this study. Optimizing the primer and probe experimental conditions for qRT-PCR and digital PCR Next, to set the optimal experimental conditions of primers and probes for application to qRT-PCR and digital PCR, preferentially, we performed the qRT-PCR validation using PC1 template DNA sample with S. aureus –specific primer, and the primer concentration was set the 25 pmol, probe concentration was set 20 pmol, and 10 pmol conditions, respectively. The qRT-PCR (CFX Opus 96 Real-Time PCE System, Bio-Rad; BioFACT 2× Multi-Star Real-Time PCR Master Mix For Probe, UDG system) experimental conditions were as follows ( Supplementary Table 2 ); pre-denaturation 95.0°C 10 min, denaturation 95.0°C 10 s, annealing/Flour detection 61°C 10 s, elongation 72.0°C 15 s, and total PCR cycle was 45). As a result, the resolution of detection fluorescence value (RFU; relative fluorescence units) for the S. aureus greA gene detected on the probe concentration condition of 20 pmol about PC1 and PC2 samples were found to be higher compared to the 10 pmol concentration condition, confirming that this experimental condition was the most optimal ( Fig. 1B ). Standard curve analysis about positive control ( S. aureus ) using qRT-PCR We performed a standard curve analysis using the Ct value reflected about the positive control to contrast the results of qRT-PCR–based detection and quantification of S. aureus within mDNA samples applied in this study ( Fig. 2 , Supplementary Table 3 ). We performed qRT-PCR in triplicate to confirm the reliability of the standard curve analysis results and performed a standard curve analysis using 10-fold serial-diluted template DNA (PC1) samples (10 1 , 10 0 , 10 -1 , and 10 -2 diluted samples, respectively). Standard curve analysis for PC1 based on qRT-PCR showed that the average Ct values for each dilution factor were 10 ng, 24.67; 1 ng, 28.90; 0.1 ng: 33.20; 0.01 ng, 38.24; and the R2 value of trend line was calculated on the standard curve graph was approximately 0.99. Primer binding specificity cross-validation through Sanger sequencing validation Finally, we performed a Sanger sequencing (ABI 3500 Genetic Analyzer, Thermo Fisher Scientific, Waltham, MA, USA) and NCBI nucleotide BLAST test to verify that the primer designed in this study correctly targeted the S. aureus greA gene CDS region and used it for PCR amplification ( Fig. 1C ). In this verification step, since the PCR amplification region to be identified is too short and unsuitable for conducting the Sanger sequencing, we performed the sequencing process by expanding the gene reading region through the TA cloning method (TOPcloner TA Kit, Enzynomics, Daejeon, Korea [ 13 ]). Competent cells required in the transformation process for gene cloning were performed using DH5α Chemically Competent E. coli (Enzynomics), and white colonies (potentially successful transformation and greA gene ligation) identified in 37°C incubation were selectively harvested and applied for sequencing process. The primer pair applied for Sanger sequencing to read the greA gene amplicon region was the M13 region-specific primer set contained in the TA cloning plasmid vector sequence. As a result, we confirmed from the base-pair sequence reading data that both forward and reverse primer sequence information were included. And then, to verify that the generated sequencing data contained CDS regions (PCR amplicon region) of the S. aureus greA gene, we input the sequencing data into the NCBI nucleotide BLAST search engine and compared it with annotated bacterial classification information within the NCBI reference database. As a result of the BLAST test, we confirmed that only bacterial identification information for S. aureus was matched from the NCBI reference database. We could also confirm that the BLAST test detected various S. aureus strains (at the strain level) rather than a single bacterial strain. This result showed that the S. aureus –specific primer, considered up to the strain level, has broad detection efficiency for various S. aureus strains within any type of clinical sample. Detection and quantification for S. aureus using qRT-PCR method We used human skin-derived mDNA samples as template DNA samples to confirm the efficiency of detection and quantification of specific microbial DNA within low molecule density template DNA using qRT-PCR. For this process, a total of 14 skin-derived clinical samples were obtained from seven patients with atopic dermatitis who visited the medical center (Kyung Hee University College of Medicine, Seoul, Republic of Korea), divided into lesion (case group) and non-lesion (control group) skin sites. Diagnosing atopic diseases of all participants was performed according to a dermatologist’s examination. Approval for the study protocol, informed consent forms, and related supporting documents was granted by the institutional review boards at the Korean Skin Research Center in South Korea (IRB No. HBABN01-220509-HRBR-E0113-01). All mDNA was extracted using the QIAamp PowerFecal Pro DNA kit (Qiagen, Hilden, Germany), and all experimental procedures were performed according to the official protocol guide provided with the kit. The average concentration values of extracted mDNA for each comparison group were checked with the control group 2.05 ng/μL and test group 4.10 ng/μL, respectively ( Supplementary Table 4 ), by using a Thermo Scientific NanoDrop One/Onec Microvolume UV-Vis Spectrophotometer (Thermo Fisher Scientific). Next, we used qRT-PCR to determine the expected microbial frequency of S. aureus present within the 14 mDNA samples with a comparative analysis between groups to confirm the detection and quantification efficiency. The experimental procedure was as follows. Normalization of bacterial quantification within each skin microbiome sample Before the detection and quantitative analysis of S. aureus using qRT-PCR, we performed a qRT-PCR-based standard curve analysis using a primer pair targeting the V5 hyper-variable region included on the bacterial 16S ribosomal RNA (forward primer: 5′-GGATTAGATACCCTGGTA-3′, reverse primer: 5′-CCGTCAATTCMTTTRAGTTT-3′) to standardize the amount of potential bacterial DNA distributed within each 14 mDNA samples to equal condition ( Table 3 , Fig. 3 ). In this process, we normalized the concentration of all mDNAs to 10ng, and then we're going to confirm the uniformity of concentration and reliability of the experiment through standard curve graph analysis. We performed standard curve analysis about expected bacterial DNA quantity by diluting each normalized mDNA through a 10-fold serial dilution method (10 1 , 10 0 , 10 -1 , 10 -2 , respectively). The qRT-PCR experimental condition of standard curve analysis for 14 mDNA samples with bacterial 16S V5 primer pair was as follows: pre-denaturation 95.0°C 10 min, denaturation 95.0°C, 10 s, annealing/Flour detection 60°C, 15 s, elongation 72.0°C, 15 s, and total PCR cycle was 45. As a result, we confirmed that the average Ct values reflecting the potential bacterial DNA concentration for each dilution factor identified within the control group were 10 ng, 25.24; 1 ng, 28.67; 0.1 ng, 31.82; and the r 2 value about the trend line calculated in the standard curve graph was 0.94. In the test group, we confirmed that the average Ct values for each diluted DNA sample were 10 ng, 25.72; 1 ng, 28.70; 0.1 ng, 30.81; and the r 2 value was 0.9166. In the case of the ‘Test-7’ sample, considering that the concentration and quality of mDNA were low and unstable at 0.82 ng (A260/280: 2.37, A260/230: 0.01), we judged that it was difficult to quantify bacterial DNA by qRT-PCR because there were few potential bacterial communities present in this sample. Therefore, through this standard curve analysis, we could confirm that the potential bacterial DNA quantities within the 13 mDNA samples, except for the ‘Test-7’ sample, were equally normalized and suitable for detection and quantification analysis for S. aureus . Evaluation of absolute and relative quantification effect for S. aureus via qRT-PCR We evaluated the absolute and relative quantification effects of S. aureus in the skin microbiome sample through qRT-PCR using S. aureus –specific primer and probe set. Before the experiment, we confirmed that the distilled water used for making the qRT-PCR mixture solution was free of microbial contamination by checking the Ct value: N/A result reflected in the non-template DNA control (NTC). The qRT-PCR amplification conditions applied in this experiment were as follows: template DNA (mDNA) 10 ng; probe concentration 20 pmol, GreA primer concentration 25 pmol (this concentration condition was based on previous experimental results showing the most optimal running condition). As a result, we were not able to detect and quantify S. aureus within both comparison groups, which was not the expected result for this experiment ( Table 4 ). Bacterial DNA normalization results confirmed by standard curve analysis demonstrated that the bacterial DNA in the skin microbiome sample was normalized to approximately the same amount, but due to the unstable quality of the mDNA (low concentration and low purity) and the low frequency of potential S. aureus expected to be present in it. Therefore, we judged that absolute and relative quantification of S. aureus within mDNA samples using the qRT-PCR method could not be meaningfully performed. Quantification of S. aureus within each skin microbiome sample using LOAA digital PCR We evaluated the applicability of the digital PCR platform to the microbial molecular diagnosis field by validating the detection and quantification effect for a proportion of S. aureus , which is expected to be present in each skin microbiome sample set in this study, using LOAA digital PCR equipment ( Table 5 , Fig. 4 ). The experimental group was set in the same as the process of detecting and quantifying S. aureus through the qRT-PCR method. Before conducting the digital PCR reaction for each comparison group, we confirmed that the number of expected copies of the greA gene within S. aureus genomic DNA in the PC1 and NC groups was 69,109 copies/μL and 0.00 copies/μL, respectively. Next, the average copies number of S. aureus greA gene identified in the control and test groups was 6.58 copies/μL and 36.28 copies/μL, respectively. However, in the case of the ‘Tes-7’ sample identified in the qRT-PCR results, it was confirmed that a low number of gene copies was detected, unlike the other mDNA samples in the test group, similar to the ‘16S V5 standard curve analysis’ result ( Table 3 ), which was evaluated to have little bacterial genomic DNA density within this template DNA sample. Additionally, we could confirm that the potential bacterial frequency of S. aureus within the mDNA samples isolated from lesion skin sites of atopic patients was relatively high compared to the non-lesion skin sites. Considering previous studies showing that the dominant rate of S. aureus identified in atopic patients' lesions sites is higher than that of non-lesion sites, we could confirm the reliability of the S. aureus quantitative analysis results between each comparison group derived through LOAA digital PCR [ 14 ].

Discussion The digital PCR platform is spotlighted as third-generation PCR equipment that can absolutely quantify the copy number of a particular gene to be identified within the sample without calculating a separate standard curve [ 15 ]. However, due to the high-cost burden of consumables of digital PCR, consumers’ careful consideration of the quality of DNA samples or primer and probe suitability is required. Therefore, the present study evaluated the application possibility of microbial molecular diagnosis of digital PCR platform by confirming the effect of detection and quantification for specific microorganisms within mDNA samples in unstable conditions. First, we selected ‘ Staphylococcus aureus ’ as a particular microbe, and by designing the S. aureus –specific primer and probe set, we successfully evaluated its high experimental accuracy for targeted-species specificity through comprehensive molecular genetic experimental validation. Additionally, since we designed the primer pair considering the strain level of S. aureus , we suggest that the designed primer can detect a broad range of strain-level single strains present in various types of clinical samples. As a result of comparing the detection and quantification efficiency of S. aureus between qRT-PCR and digital PCR, unlike qRT-PCR, which could not confirm the relative proportion of S. aureus in any mDNA sample, we confirmed that the copy number of S. aureus greA gene was calculated in digital PCR. S. aureus inhabits human skin sites at a high proportion, with an average frequency of 20%–30% (approximately 50%–60% for atopic patients) [ 16 ]. However, we judged that detecting S. aureus , even with qRT-PCR with high fluorescence sensitivity, was challenging because the quality and quantity of the mDNA samples applied in this study were very low. Despite these conditions, we estimated that the semiconductor-based LOAA digital PCR equipment was capable of S. aureus greA gene amplification not detected by qRT-PCR because specific gene amplification is possible for each bacterial genomic DNA within each over 20,000 nano-size PCR well. Additionally, the applicability of digital PCR to microbial-related diagnosis and clinical research for particular diseases was confirmed by validating the relative frequency difference of S. aureus between atopic patients' lesions and non-lesions sites. In summary, we evaluated in this study that digital PCR has a simpler experimental process spent quantifying and detecting specific genes compared to qRT-PCR and is significantly less time-consuming (qRT-PCR takes about 5 h, digital PCR takes about 1 h). Additionally, we verified that digital PCR has excellent performance on equipment in that it enables its independent absolute quantification application. Above all things, we could confirm that gene amplification, detection, and quantification are possible using digital PCR, even within DNA samples with unstable quality and quantity, such as skin-derived mDNA. However, digital PCR has high prices for semiconductor-based PCR response detection chips, limitations of not having more than three multiple fluorescent channel functionality support in equipment, and experimental inefficiency of ‘only one sample per equipment operation.’ However, considering the digital PCR's operating excellence in deriving high-quality output data, we suggest that digital PCR has high potential application value in the microbiome-based human healthcare field if it is used for cross-validation for quantification and detection for specific microorganisms to be identified.

Dongwan Kim, Junhyeon Jeon, and Minseo Kim contributed equally to this work. Accurate and efficient microbial diagnosis is crucial for effective molecular diagnostics, especially in the field of human healthcare. The gold standard equipment widely employed for detecting specific microorganisms in molecular diagnosis is quantitative real-time polymerase chain reaction (qRT-PCR). However, its limitations in low metagenomic DNA yield samples necessitate exploring alternative approaches. Digital PCR, by quantifying the number of copies of the target sequence, provides absolute quantification results for the bacterial strain. In this study, we compared the diagnostic efficiency of qRT-PCR and digital PCR in detecting a particular bacterial strain ( Staphylococcus aureus ), focusing on skin-derived DNA samples. Experimentally, specific primer for S. aureus were designed at transcription elongation factor ( greA ) gene and the target amplicon were cloned and sequenced to validate efficiency of specificity to the greA gene of S. aureus . To quantify the absolute amount of microorganisms present on the skin, the variable region 5 (V5) of the 16S rRNA gene was used, and primers for S. aureus identification were used to relative their amount in the subject’s skin. The findings demonstrate the absolute convenience and efficiency of digital PCR in microbial diagnostics. We suggest that the high sensitivity and precise quantification provided by digital PCR could be a promising tool for detecting specific microorganisms, especially in skin-derived DNA samples with low metagenomic DNA yields, and that further research and implementation is needed to improve medical practice and diagnosis.

This research was supported by Basic Science Research Capacity Enhancement Project through Korea Basic Science Institute (National Research Facilities and Equipment Center) grant funded by the Ministry of Education (Grant No. 2019R1A6C1010033). This study has been done with the participation of undergraduate students working at total-omics analysis research institute of Dankook University. The research institute has been supported by the VIP system as a part of Support Program for University Development 2023 of Dankook University. Following are results of a study on the "Leaders in INdustry-university Cooperation 3.0" Project, supported by the Ministry of Education and National Research Foundation of Korea. Supplementary Materials Supplementary data can be found with this article online at http://www.genominfo.org .

CC BY

no

2024-01-16 23:41:59

Genomics Inform. 2023 Dec 29; 21(4):e52

oa_package/4c/4d/PMC10788361.tar.gz

PMC10788362

0

The launch of a new section of Computational and Structural Biotechnology Journal covering the breath of Nanoscience and Advanced Materials (NAM) provides a unique platform for reporting experimental and computational studies on the exciting science that occurs at the interface between engineered and manufactured materials and living systems across scales. This innovative platform is dedicated to bridging the gaps and fostering intersections between various scientific disciplines such as nanoscience, materials science, chemistry, physics, and biomedical engineering. Our goal is to catalyze scientific knowledge and technological innovation, driving transformative advances in the field of nanomaterials and advanced materials. The fascinating science at the bio-nano interface [1] , [2] , which includes exploration of the protein corona [3] , [4] , biomolecule corona [5] or environmental corona [6] - the layer of biomolecules that overlays a biological identity onto the synthetic identity provided by the chemical composition and morphology of the materials or surfaces, has been the subject of intensive experimental and computational research over the last decade or more [7] , [8] . The role of the bio-nano interface in medicine, agriculture, environmental remediation, sensing, catalysis, and energy capture is increasingly recognized, yet full understanding of the impacts of biomolecule-material interactions for both the biomolecules involved and for the nanoscale or advanced materials remains elusive. Experimental and computational exploration of the bio-nano interface offers enormous opportunities for new insights and new understanding, in a range of important processes such as biofouling, acceptance or rejection of biomaterials and implants, biosensing and more. The role of the biomolecule corona in receptor binding is increasingly understood [9] , providing the key to understanding transport across biological barriers and engagement of biological signalling pathways, including those leading to adverse (health) outcomes [10] . The ability to generate fully computational nanomaterials, for example as digital twins, offers exciting new avenues for in silico assessment of bio-nano interactions and the molecular pathways activated in response to nanotherapeutics, and those activated by nanomaterials identified as foreign bodies resulting from pollution. The NAM section of CSBJ welcomes these advances and more. Beyond bio-nano interactions, the NAM section of CSBJ focuses on advancing the scientific knowledge and technological innovation at the crossroads of nanoscience, materials science, chemistry, physics, and biomedical engineering. The NAM section is more than just a repository for research; it's a hub for pioneering ideas and groundbreaking discoveries. We welcome contributions from diverse spheres, ranging from academia, to regulatory and policy researchers, and industry professionals, each bringing unique insights to our collective understanding of the nanoscale world and its applications. Our section will cover a broad spectrum of topics within nanoscience and advanced materials. These include, but are not limited to: 1. Nanotechnology Applications: From Nanocatalysis to Nanofabrication, and Nanophotonics to Biomedical Nanotechnology, we delve into the myriad applications of nanoscience in various fields, including agriculture and environmental technology. 2. Risk Management and Governance: Emphasizing sustainable, safe design strategies and smart materials, this area explores the intersection of bio-inspired materials and green chemistry, focusing on responsible innovation and governance in nanotechnology. 3. Data and Modeling: With a focus on predictive toxicogenomics, nano(chem)informatics, and multiscale simulations, this domain aims to harness the power of AI, machine learning, and digital platforms to revolutionize our understanding and application of nanomaterials. 4. Risk Assessment and Integrated Approaches: A critical aspect of our section involves comprehensive assessments of hazards, exposure, and risk management in the lifecycle of nanomaterials, underpinned by advanced data management and modeling techniques. The Editor in Chief and Editorial board are looking forward to welcoming submissions covering the full spectrum of topics within the overarching domains of nanoscience and advanced materials, enhancing our understanding of the nanoscale world and its transformative applications. Potential contributors are also welcome to suggest topics for thematic issues and to guest-edit these. For example, the NAMs section of CSBJ is currently accepting submissions for a special issue on “ Applications of Cheminformatics and Machine Learning in Predictive Modelling of Property and Toxicity Endpoints of Nanoparticles ”, which is being guest edited by Prof. Kunal Roy from Jadavpur University, India. If you are working on this topic, please submit your articles by 31st August 2024. We are especially interested in well-executed and well-written no-effects studies, as reporting of the absence of nanomaterials or advanced materials toxicity is critical to the development of balanced predictive models and to developing a representative regulatory framework. Watch out for other exciting topical collections over the coming months. As we embark on this journey, your contributions, insights, and innovations will be the driving force behind the success of CSBJ: Nanoscience and Advanced Materials. We eagerly await your submissions and are excited to see how your work will contribute to this ever-evolving field.

CC BY

no

2024-01-16 23:41:59

Comput Struct Biotechnol J. 2023 Dec 14; 25:1-2

oa_package/43/b3/PMC10788362.tar.gz

PMC10788384

38226359

INTRODUCTION The global population's growth and aging contribute to a heightened incidence of wounds, including those that become infected. 1 Infections within wounds pose a substantial hindrance to the healing process, significantly impeding the transition from the inflammatory phase to the proliferative phase. This obstacle often leads to the persistence of chronic wounds. 2 Management of wound infections has been increasingly complex as the prevalence of antibiotic‐resistant microorganisms continues to rise. 3 The formation of microbial biofilms within wounds not only decreases the effectiveness of antimicrobial treatments but can even thwart their efficacy entirely. The consequences of wound infections place a considerable burden on both patients and healthcare systems alike. 4 , 5 Safeguarding wounds against pathogens stands as a pivotal clinical practice in effective wound management. In this regard, wound dressings assume a critical role in not only preventing but also treating wound infections. 6 The utilization of antimicrobial wound dressings has witnessed a steady rise in their application for both the treatment of infected wounds and the prevention of wound infection. 7 Most commercially available antimicrobial wound dressings contain a variation of silver as the active ingredient. Silver has wide‐spectrum antimicrobial efficacy but there is a growing number of reports indicating that silver may be detrimental to the wound healing physiological processes. 8 , 9 , 10 , 11 , 12 There are two key properties of copper that make it a very attractive option for the management of wounds. First, copper is a potent wide‐spectrum biocide. 13 , 14 The detrimental effects inflicted upon these microorganisms stem from a range of indiscriminate mechanisms. These encompass the permeabilization of their plasma membranes, the peroxidation of membrane lipids, impairment to their nucleic acids, and the disruption of the assembly and functionality of intracellular proteins. 15 The intricate web of multisite, nonspecific copper‐induced damages poses a considerable challenge for microorganisms to evolve a resistance to copper, resulting in a notably low occurrence of copper‐tolerant microorganisms. 15 , 16 Second, and most importantly, copper is an essential trace mineral required for efficient wound healing. 17 , 18 For example, processes such as angiogenesis, proliferation of dermal fibroblasts, the enhanced expression of collagen and elastin fiber secretion by these fibroblasts, and the interlinking of extracellular matrix (ECM) proteins, all require copper. Recently novel wound dressings impregnated with copper microparticles have been approved for the clinical management of acute and chronic wounds by the United States, European, and Israeli regulatory bodies. These dressings possess potent antimicrobial efficacy, 19 and several reports indicate their capacity to enhance wound healing, especially of diabetic ulcers. 20 , 21 , 22 In our rehabilitation center, part of the standard of care of acute and chronic wounds is the use of silver dressings, mainly to protect the wounds from infection. However, in view of the growing evidence that silver dressings may impede the wound healing processes, it was decided to examine the effect of the copper dressings in noninfected wounds treated with silver dressings, but in whom the wounds were not healing or the progression of the wound healing were slow. The current study was devised to examine the efficiency of copper dressing to improve wound healing among patients admitted to a rehabilitation hospital. The goal of this study was to evaluate the effect of the copper dressings in noninfected wounds treated with silver dressings, but in whom the wounds were not healing or the progression of the wound healing were slow. To the best of our knowledge, similar investigations have not been reported in the literature for patients in a rehabilitation setting.

MATERIAL AND METHODS Study group The study group included twenty 18–85 years old patients with pressure ulcers, diabetic ulcers, trauma wounds, or postoperation wounds with wound areas of 2–30 cm 2 . Out of the 20 patients that were recruited, 15 patients completed the study protocol and their data were analyzed. Three patients received antibiotics and two were transferred to a different hospital shortly after their recruitment, all five due to complications not related to the study or the wound. Table 1 summarizes the general characteristics of the 15 patients who finished the study. Ten of the patients were diabetics (mean ± SD % HbA1c of 6.8 ± 0.99 (CI = 0.02)); two of which their diabetes was not fully successfully controlled. Ten of the patients suffered from hypertension and six from peripheral arterial disease (PVD). Nine were smokers and two were receiving immunosuppression medication. All of these patients were treated with Silvercel Hydro (Systagenix) or Aquacel Ag (Convatec), hereafter referred to as “silver dressings,” for at least 3 weeks, but in all of them their wounds did not show clinical improvement or a reduction of at least 50% of the wound area during the silver dressing treatment. All of these patients met the other inclusion and exclusion criteria (Table 2 ). They signed the informed consent form and were recruited to the study. Their wounds were then treated with Antimicrobial Wound Dressings with Copper (MedCu Technologies Ltd.), hereafter referred to as “copper dressings,” for at least 3 weeks. In case there was a clear improvement during the copper dressing treatment, the wounds continued to be treated with the copper dressings until wound closure. Assessments and procedures The silver or copper dressings were pretrimmed to an adequate size and shape based on the wound size and form. After they were applied onto the wound, a secondary dressing was applied on top of the dressings to hold them in place. The silver or copper dressings were replaced every 2–4 days, depending on the amount of wound exudate. The area of the wounds was measured routinely every 7 days during the study by using the wound imaging artificial intelligence system (Tissue Analytics; https://www.tissue-analytics.com/ ). All wounds and surrounding tissues were carefully cleaned and irrigated with sterile sodium chloride solution before taking an image of the wound. The percent reductions as compared with the area of the wounds at the commencement of the treatment with silver or copper dressings were determined using the following formula: If the wound became infected and the patient received antibiotics, the patient was dropped from the trial. The number of infections and adverse reactions were recorded. The study was approved by the Lowenstein Rehabilitation Center IRB (approval # 0002‐20‐LOE) and was registered in ClinicalTrials.gov Protocol Registration and Results System (# NCT04634838; 002‐20‐LOE). Statistics Paired t tests were performed to analyze the impact of two Arms (different treatment periods) on the wound size/area. Our primary objective was to evaluate the disparity between the wound size when the particular treatment was initiated and the endpoint of the wound during that treatment by comparing the change in size, referred to as delta, between “day 0” and “day 25.” We also employed multiple regression analysis to examine the influence of two treatment group (silver vs. copper) on the wound size/area over time. Our objective was to assess the disparity in the rate of wound closure by comparing the slopes of the regression lines between the two treatments. A significance level of 0.05 was selected to determine the statistical significance of the results and all tests were two‐sided. Analyses were performed using JMP® Pro, Version 16.

RESULTS Two patients suffered from two wounds each, and thus 17 wounds were analyzed. All wounds were noninfected as determined by clinical examination. Table 3 describes the wound parameters at the start of the study. Nine of the wounds were post‐op wounds following amputation below the knee, two of which were following trauma. None of the wounds had protruding bones or necrotic tissue. The mean ± SD of the initial wound area was 8.57 ± 6.4, (CI = 0.1) based on the AI software determinations. The period of silver and copper dressings treatment were similar, mean of 25.6 ± 6.6 (confidence interval [CI] = 0.1) and 29.6 ± 11.1 days (CI = 0.16) (mean ± SD; p = 0.21; t test), respectively (Table 4 and Figure 1A ). Comparing a period of 25 days, the mean proportion wound area reduction was ~ 2.4 times higher during the copper dressing treatment than during the silver dressing treatment, 87.35 ± 22.4% (CI = 0.37) versus 37.02 ± 25.11% (CI = 0.33) (mean ± SD; p < 0.001; paired t test; Figure 1B ), respectively. Some representative examples are shown in Figure 2 . It was found that the rate of decrease in wound size was significantly different between the two treatment groups. While the average decline during the silver treatment was 1.2% per day, during the copper treatment the average decline per day was 2.14% (multiple regression; p = 0.002). Ten out of the 15 patients closed their wounds following the copper dressings treatment. Some of the 15 patients responded immediately to the exposure to the copper dressings; six of them were diabetics. Some took them longer to close the wounds (Figure 3 ). Out of the diabetic patients, six closed the wounds completely.

DISCUSSION While silver and copper have wide spectrum antimicrobial properties, as opposed to silver, copper is a trace mineral essential for the normal function of all human tissues. 23 In wounds, copper is involved in many of the wound healing processes, such as angiogenesis, stimulation of secretion of fibrinogen, elastin and collagen by dermal fibroblasts, induction of cell proliferation and re‐epithelization, and migration of skin and stem cells. 24 , 25 , 26 , 27 , 28 , 29 It has been stipulated that in diabetic and other hard‐to‐heal stagnated wounds part of their incapacity to heal or the reason they heal slowly is the low systemic copper that reaches the wound through the integumentary system, 17 and that the external application of dressings that elute copper ions onto the wound may stimulate the stagnated healing processes. 17 , 20 The capacity of copper eluted from copper‐containing dressings to stimulate noninfected wounds as opposed to controlled dressings without an active ingredient or silver‐containing dressings was clearly demonstrated in wounds elicited in genetically engineered mice. 25 This was further substantiated by Das et al., 30 who demonstrated in wild mice that exogenous and endogenous Cu promote wound healing through the endothelial antioxidant‐1 (Atox 1) cytosolic Cu chaperone. Meaningfully, the capacity of copper dressings to stimulate wound healing of noninfected stagnated wounds in diabetic patients was also demonstrated. 22 Several clinical case reports that demonstrated enhanced wound healing of hard‐to‐heal wounds by copper dressings in patients suffering from other etiologies were also reported. 20 , 21 , 31 Coger et al. 32 showed that following wounding there is almost a 40% increase in the copper concentration in the wound in normal healthy rats, indicating that the normal physiological response to wounding, among many processes, is the increased delivery of copper to the wounds. In the wound, numerous intricately balanced mechanisms that drive wound healing and repair rely significantly on their interactions with copper. 17 , 18 , 33 , 34 This encompasses various essential components: platelet‐derived growth factor (PDGF), playing a crucial role in the hemostasis phase of wound healing; vascular endothelial growth factor (VEGF) and angiogenin, pivotal growth factors stimulating angiogenesis, a critical process during the proliferation phase; dermal fibroblasts actively secreting collagens (types I, II, and V), Heat Shock Protein 47 (HSP‐47), and elastin fiber constituents (elastin, fibrillins) throughout the proliferation and remodeling phases; the activity of Lysyl oxidase (LOX) essential for efficient ECM protein cross‐linking between elastin and collagen; maintenance of stabilized skin ECM postformation; differentiation‐induced modulation of integrins by keratinocytes during the remodeling phase; and participation of major protease groups including matrix metalloproteinases (MMPs, primarily MMP‐1, MMP‐2, MMP‐8, MMP‐9) and serine proteases (human neutrophil elastase, HNE) crucial for the wound healing process. It is therefore unsurprising that wound closure is delayed due to copper chelation. 30 Interestingly, Yadav et al. 35 found that in diabetic patients with foot ulcers the serum concentration of copper was lower than in diabetic patients without ulcers. This is in accordance with the notion that a small scratch or wound in a diabetic patient with low copper levels may not heal and become a nonhealing wound, while in patients and individuals with high serum copper concentration the scratch/wound is healed. 17 In the current study, we applied copper dressings in a variety of wounds, mostly in post‐op amputation wounds below the knee. Most of the patients were diabetics, most suffered from hypertension, and many from peripheral arterial disease. Nine out of the 15 patients were smokers, three suffered from cardiovascular disease, two from venous disease or renal disease, and two were taking immunosuppression medication. In all of these patients, the wound‐healing process seemed to be slow when they were managed with silver dressings. This is in accordance with several studies showing that silver may impede the wound healing processes and their benefit in managing wounds and especially of noninfected wounds is questionable. 8 , 9 , 10 , 11 In contrast, the application of the copper dressings had a very positive effect on the wound healing, leading to the eventual closure of the wounds in most of the patients without any adverse effects. No clear correlation between the rate of wound closure and the effect of the dressings could be established, mainly due to the low number of patients studied. Larger studies should be conducted to better decipher why some wounds and/or patients respond better than others to the effect of the copper dressings. While we planned to have a larger number of patients included in the study, we decided to stop the study and manage the wound of our patients only with copper dressings, as we felt it was not ethical to treat our patients with the silver dressings while we were already convinced that the copper dressings had an excellent effect and helped heal the wounds significantly better than the silver dressings.

CONCLUSION The results of this study confirm other clinical case reports showing enhanced wound healing of hard‐to‐heal wounds with copper dressings, both of infected and noninfected wounds. Further studies should be conducted to further support the clinical benefit of using copper dressings instead of silver dressings for the management of acute and chronic wounds. Taken together, the results of the current study clearly support the hypothesis that application of copper dressings in situ onto noninfected wounds results in the stimulation of the wound healing processes in a panel of etiologies.

Abstract Background and Aims Dressings containing silver ions are an accepted and common option for wound treatment. However, some wounds fail to heal at the desired rate despite optimal management. The aim of the study was to examine the effect of copper dressings in noninfected wounds. Methods The study included 20 patients aged 18–85 years with 2–30 cm 2 noninfected wounds treated for 17–41 days with silver wound dressings that failed to reduce by >50% the wound size, who were then treated with copper dressings. Ten patients were diabetics, 10 suffered from hypertension, and six suffered from peripheral vascular disease (PVD). Two patients suffered from two wounds. Most were amputation wounds below the knee. Results Five patients dropped out from the study due to complications not related to the wound. The mean period of silver and copper dressings treatment was 25.6 and 29.6 days, respectively ( p = 0.25; t test). None of the wounds became infected. Comparing a period of 25 days, during the copper dressings treatment, the mean wound area reduction was ~2.4 times higher than during the silver dressing treatment, 87.35 ± 22.4% versus 37.02 ± 25.11% (mean ± SD; p < 0.001; paired t test), respectively. The average decline during the silver and copper treatments were 1.2% and 2.14% per day ( p = 0.002; multiple regression analysis), respectively. Conclusions The enhanced wound healing process observed with the copper dressings may be explained by the integral role of copper throughout all physiological skin repair processes. Silver in contrast has no physiological role in wound healing. The results of our study confirm case reports showing enhanced wound healing of hard‐to‐heal wounds with copper dressings, both of infected and noninfected wounds. Taken together, the results of the current study support the hypothesis that the application of copper dressings in situ for noninfected wounds results in the stimulation of the wound healing processes, as opposed to silver dressings. Gorel O , Hamuda M , Feldman I , Kucyn‐Gabovich I . Enhanced healing of wounds that responded poorly to silver dressing by copper wound dressings: prospective single arm treatment study . Health Sci Rep . 2024 ; 7 : e1816 . 10.1002/hsr2.1816

AUTHOR CONTRIBUTIONS Oxana Gorel : Conceptualization; data curation; formal analysis; investigation; project administration; supervision; writing—review & editing. Irit Kucyn‐Gabovich : Conceptualization; methodology; project administration; data curation; writing. Monza Hamuda and Ilana Feldman were involved in the treatment and management of the patients' wounds. All authors have read and approved the final version of the manuscript. CONFLICT OF INTEREST STATEMENT The authors declare no conflict of interest. TRANSPARENCY STATEMENT The lead author Oxana Gorel affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

ACKNOWLEDGMENTS The authors would like to thank MedCu Technologies for donating the copper wound dressings. DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. O.G. had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis. The individual participant data that underlie the results reported in this article, after deidentification, will be available upon email request from the corresponding author immediately after publication and ending 3 years following publication.

CC BY

no

2024-01-16 23:42:00

Health Sci Rep. 2024 Jan 14; 7(1):e1816

oa_package/77/ba/PMC10788384.tar.gz

PMC10788385

38204385

This time of the year brings a sense of excitement, as various dictionaries announce the ‘Word of the Year’ that marks our preoccupations, curiosity, and reflects our ethos. Although several dictionaries announced words related to the proliferation of artificial intelligence (AI), e.g., hallucination [ 1 ], two major dictionaries selected divergent alternatives. Merriam-Webster selected authenticity [ 2 ] considering the number of lookups but also in relation to a likely “crisis of authenticity” in our era of deepfakes and post-truths [ 3 ]. On a very different tangent, Oxford Word of the Year is rizz , taken from the word charisma and defined as ‘style, charm, or attractiveness; the ability to attract a romantic or sexual partner’ [ 4 ]. As I looked back on the milestones of the Korean Journal of Women Health Nursing (KJWHN), I couldn’t help but ponder how these words might offer a timely message for journal editors and researchers alike. Journal accomplishments This year KJWHN was honored and elated to be indexed in MEDLINE [ 5 ], a major feat for a regional journal in the field of nursing, as only approximately 11% of journals that apply to MEDLINE are accepted [ 6 ]. This is evermore significant as we are also one of a small cadre of nursing journals simultaneously indexed in PubMed Central (PMC) [ 5 ]. Another milestone was publishing a special issue, which was a first for KJWHN. The September 2023 issue focused on “Digital era education for women’s health and wellbeing” ( https://kjwhn.org/current/index.php?vol=29&no=3 ) and covered expert opinion on opportunities and challenges for AI-integrated healthcare and healthcare education [ 7 ], as well as reviews and original research on quality evaluation, digital literacy, and virtual reality use in the classroom. Journal metrics Table 1 presents data on manuscripts submitted to KJWHN as of December 10, 2023. The increase in unsolicited manuscripts, from 63 in 2022 [ 8 ] to 80 in 2023, suggests a boost from being indexed in PMC and the Emerging Sources Citation Index (ESCI) in 2022. A notable increase in international submissions was also seen. However, compared to seven unsuitable manuscripts in 2022 [ 8 ], a substantial increase of 30 manuscripts was also observable this year. These editorial or ‘desk’ rejections were largely due to incongruency with our aims and scope or concerns with high percentages in screening for plagiarism. Related to these increases in numbers, however, the editorial board has experienced challenges with limitations in resources and time, and subsequent fatigue in editors and reviewers. This is likely to have affected the time from submission to acceptance, which was roughly 56 days in 2022 [ 8 ] but lagged slightly to 85 days in 2023. Applying the Words of the Year to scholarly publishing Considering our accomplishments and journal metrics, you could say KJWHN has proven it has rizz enough, evidenced by becoming indexed in MEDLINE and attracting an increase in submissions, especially from overseas. However, our challenge is to stay true to our identity and mission, i.e., striving for an authentic presence as a scholarly journal committed to women’s health nursing. In this line, a continuous challenge is to communicate more effectively with potential authors to recognize the journal’s aims and scope as well as our emphasis on international standards for scholarly work, e.g., advocating the use of reporting guidelines, clinical trial registration for human intervention studies, data sharing statements, etc. [ 8 ]. Another real challenge is to widen the pool of reviewers to facilitate the review process. A strategic plan would include preparing junior researchers as reviewers, showing respect and appreciation for their participation, while monitoring whether reviewers might show signs of reviewer fatigue. I take this opportunity to welcome inquiries about becoming a reviewer or how to improve reviewing skills. Researchers could also apply these two Word of the Year terms to scholarly publications. Firstly, authenticity is central when writing the manuscript for dissemination. Merriam-Webster defines authentic as “not false or imitation; true to one’s own personality, spirit, or character” [ 9 ]. Thus, authentic manuscript writing can be interpreted as being true to the spirit and main message of the study findings. It may be tempting to think research rizz involves verbose writing or strictly following a ‘template-style’ flow of writing, as is often seen in early-stage researchers. It is worthwhile, however, to remember that wordy manuscripts do not necessarily showcase productivity or value; they rather run the risk of being redundant and cliché, and may subsequently end in vague, superficial implications. In other words, be true to your study’s main message and aim for succinctness and clarity. An example is to bring the main research aim and dependent variable to the forefront of the Discussion section, focusing on interpretation and implications, rather than flooding the text with what was already presented in the Results section. Appreciation for 2023 reviewers I wish to acknowledge the following dedicated reviewers who have supported KJWHN this year: Ahn, Suk Hee (Chungnam National University) Bae, Kyungeui (Dongseo University) Chae, Hyun Ju (Joongbu University) Cheon, Suk Hee (Sangji University) Cho, Insook (Inha University) Cho, Ok-Hee (Kongju National University) Choi, Hyunkyung (Kyungpook National University) Choi, Mi Jin (Chodang University) Choi, So Young (Gyeongsang National University) Chung, Chae Weon (Seoul National University) Chung, Mi Young (SunMoon University) Ha, Ju Young (Pusan National University) Han, Jeehee (Chung-Ang University) Haruna, Megumi (University of Tokyo) Hong, Sehoon (Cha University) Huh, Sun (Hallym University) Hwang, Kyung Hye (Suwon Science College) Jang, Hyun-Jung (Catholic Kkottongnae University) Jeong, Geum Hee (Hallym University) Jo, Myung Ju (The Catholic University of Korea) Jun, Eun-Young (Daejeon University) Kang, Saemi (Gyeongsang National University) Kang, Sookjung (Ewha Womans University) Kim, Haewon (Seoul National University) Kim, Hee Kyung (Kongju National University) Kim, Hye Young (Keimyung University) Kim, Hyun Kyoung (Kongju National University) Kim, Jeung-Im (Soonchunhyang University) Kim, Joungyoun (University of Seoul) Kim, Kwang Ok (Dongju College) Kim, Kyungwon (Daegu Haany University) Kim, Miok (Dankook University) Kim, Mi Jong (Hannam University) Kim, Mi Young (Woosuk University) Kim, Moonjeong (Pukyong National University) Kim, Myoung hee (Semyung University) Kim, Su Hyun (Nambu University) Kim, Sun-Hee (Daegu Catholic University) Kim, Sun Ho (Chungbuk National University) Kim, Yoonjung (Konyang University) Kim, Young Man (Jeonbuk National University) Kim, YoungJu (Daejeon Health Institute of Technology) Kim, Yun Mi (Eulji University) Ko, Eun (Sunchon National University) Lee, Ju-Young (The Catholic University of Korea) Lee, Kyoung-Eun (Texas A & M University) Lee, Sun-Kyoung (Seoul Womens College of Nursing) Lee, SunHee (Gimcheon University) Nho, Ju-Hee (Jeonbuk National University) Park, Seo A (Gyeongbuk College of Health) Park, So Mi (Yonsei University Wonju) Seo, Minjeong (Gyeongsang National University) Shimpuku, Yoko (University of Hiroshima) Song, Ju-Eun (Ajou University) Song, Young A (Ansan University) Shin, Gi Soo (Chung-Ang University) Sung, Mi Hae (Inje University) Yeom, Gyejeong (JEI University) Yoo, Hana (Daejeon University) Yoon, Ji Won (Shinhan University) For the “Reviewer of the Year 2023,” the journal congratulates the following reviewers: • Jeung-Im Kim (Soonchunhyang University) • Joungyoun Kim (University of Seoul) • Minjeong Seo (Gyeongsang National University) And special recognition goes to our “Editor’s Pick 2021–2022,” as the most cited manuscripts in the Scopus database for the previous 2 years period. • Lee EH. [Psychometric properties of an instrument 2: structural validity, internal consistency, and cross-cultural validity/measurement invariance]. Korean J Women Health Nurs. 2021 Jun 30;27(2):69-74. Korean. https://www.doi.org/10.4069/kjwhn.2021.05.18 . • Cho KA. Korea’s low birth rate issue and policy directions. Korean J Women Health Nurs. 2021 Mar 31;27(1):6-9. https://www.doi.org/10.4069/kjwhn.2021.02.16 . As we look towards the future, the journal will continue to keep true to our identity and scope, committing to quality, trustworthiness, and communication with potential authors. Please join us in making an impact on women’s health by becoming a reviewer and/or considering the journal for submission of quality studies on women’s health nursing.

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):253-256

oa_package/16/87/PMC10788385.tar.gz

PMC10788386

38204394

Introduction In 2021, the number of deaths in South Korea (hereafter, Korea) reached 317,680, a 4.2% increase from the previous year, reaching its highest level in the past decade [ 1 ]. The suicide rate was 26.0 (the number of deaths per 100,000 population), up 1.2% from the previous year [ 1 ]. Moreover, Korea recorded the highest level, 2.1 times higher than the Organization for Economic Co-operation and Development (OECD) average of 11.1 (the number of deaths per 100,000 standard population) [ 1 ]. In particular, it was reported that the suicide rate of women has been continuously increasing since 2017 [ 2 ]. To reduce suicide, Korea has been establishing the National Suicide Prevention Master Plan every 5 years since 2004 as a national suicide prevention strategy [ 3 ], but it has been ranked first since 2018 among OECD countries [ 4 ]. Statistics Korea reports the results of cause of death statistics every year, but it analyzes and describes suicide as one of several causes of death. According to the 2023 Suicide Prevention White Paper published annually by the Ministry of Health and Welfare and the Korea Foundation for Suicide Prevention, the number of suicide attempts by women is 1.4 times higher than that by men [ 5 ]. Women are reported to be more vulnerable to suicide because they have lower socioeconomic levels than men [ 6 ], such as income, education, and employment, and a higher prevalence of mood and anxiety disorders, including depression [ 7 ]. Therefore, a detailed approach that considers the changing trends in suicide rates and differences in suicide rates by gender and age is needed to develop policies to effectively reduce suicide rates. Thus, this study aims to update Korean women’s suicide death statistics, suicide rate trends, gender- and age-specific suicide characteristics, and suicide means over the past 10 years from 2011 to 2021. The trends identified can provide basic data for policy establishment for suicide prevention at the present time when women face increasing vulnerable factors.

Methods Data sources This study used cause-of-death statistics from Statistics Korea to analyze trends in suicide deaths among Korean women. The cause-of-death statistics were compiled based on death certificates collected by Statistics Korea. In this study, microdata on cause of death statistics from 2011 to 2021 were analyzed through the MicroData Integrated Service of Statistics Korea [ 8 ]. This data includes demographic characteristics of the deceased and detailed causes of death, including external factors (accidents, etc.). To increase the accuracy of causes of death, Statistics Korea reflects administrative records from institutions such as the National Cancer Center, Health Insurance Review and Assessment Service, and the National Institute of Scientific Investigation. Study variables The variables used in this study were total deaths, suicide deaths, suicide death rates, female mortality rates, and means of suicide. Definition of terms Suicide deaths This refers to the act in which an individual, with the intention of causing their own death, deliberately ends their own life using any means or method (in cases where parents commit suicide with young children, the death of young children is classified as homicide rather than suicide) [ 1 ]. Age-standardized suicide death rate The death rate was adjusted to account for the impact of age structure on mortality levels, allowing for mortality comparisons between populations with different age distributions [ 1 ]. Suicide means Among the classification codes according to the Korean Standard Classification of Diseases, the codes of suicide means are further subdivided (X60–X84). They are as follows: hanging (X70); fall (X80); carbon monoxide (X67.0–X67.4); pesticides (X68); drowning (X71); other and unspecified gases (X67.8–X67.9); drugs (X60–X64); and others (X65, X66, X69, X72–X79, X81–X84) [ 1 ]. Statistical methods Data on all deaths were used as the statistical data and analyzed using descriptive statistics and calculations according to the formula based on the definition of terms.

Results In 2021, the number of suicide deaths in Korean men and women reached 13,352, an increase of 157 (1.2%) compared with the previous year, with a suicide rate of 26.0 per 100,000 population ( Table 1 ). The suicide rate peaked at 31.7 per 100,000 population in 2011 and then showed a declining trend for 6 years. However, in 2018, the suicide rate increased again to 26.6 per 100,000 population, temporarily dropping to 25.7 in 2020, but rebounding to 26.0 in 2021. Trends in suicide rates by gender Examining the trend in suicide rates by gender, in 2021, the number of suicide deaths among women reached 4,159, with a suicide rate of 16.2 per 100,000 population, a 1.4% increase from the previous year ( Table 1 ). In the “age-standardized suicide death rate,” which eliminates differences in age structures among nations, women’s suicide rate increased by 2.1% compared with the previous year, indicating a larger increase in suicides in women. The gender-specific suicide rate difference, which was 23.2 per 100,000 population in 2011, decreased to 19.7 in 2021, signifying a gradual increase of suicide among women and a narrowing gender gap in suicide rates. Trends in suicide rates by age Over the past 10 years (2011–2021), the suicide rate for all women has shown an overall downward trend ( Figure 1 ). Compared with 2011, the age-specific suicide rate in 2021 decreased in all age groups over 20 years, with the largest decreases in the 70–79 and over 80 years age groups at 50.5% and 60.0%, respectively. However, compared with 2020, the age-specific suicide rates in 2021 increased to 8.4%, 1.2%, and 7.0% for the under 20, 20–29 years, and 30–39 years age groups, respectively. Since 2018, suicide rates have increased significantly in the 20–29 and 30–39 years age groups. Suicide rates among young women in their 20s and 30s increased markedly in 2020 and 2021, during the coronavirus disease 2019 (COVID-19) pandemic ( Table 2 ). Trends in suicide rates by means In the recent 3-year period (2019–2021), the most common means of suicide for women were hanging (46.9%), falling (24.5%), and carbon monoxide (8.0%) ( Figure 2 ). Drugs (sedative-hypnotic drugs, psychotropic drugs, etc.) and carbon monoxide poisoning are two of the means of women’s suicide that have steadily increased from 2011 to 2021. Specifically, drug use increased 220.5% and carbon monoxide increased 134.3%, whereas pesticide poisoning and hanging decreased significantly to 75.0% and 28.8%, respectively ( Table 3 ).

Discussion The gender ratio of suicide rates has decreased, indicating a relatively higher increase of suicide deaths in Korean women compared with men [ 1 ]. Furthermore, in 2021, the women’s suicide death rate reached 16.2 per 100,000 population, a significant increase of 1.4% from the previous year [ 1 ]. The foreign press concluded that the high suicide rate of young Korean women influenced this trend, noting that Korea’s suicide rate, which had been on the decline over the past decade, began to increase again in 2018, and was the highest among OECD member countries [ 9 ]. In Korean society, women are expected to take on the dual roles of household chores and childcare, while also participating in the workforce. This contradictory situation, coupled with discrimination in the workplace, contributes to an increase in suicide among Korean women [ 9 ]. Analyzing the proportion of non-regular workers in 2022, women accounted for 55.2%, which is 10.4% higher than men, and the proportion of non-regular men and women workers by age group was highest in those 60 years or older (31.3%), followed by 50–59 years (21.1%) and 20–29 years (17.3%) [ 10 ]. During the COVID-19 pandemic, the service industry was particularly devastated, and naturally, young women were inevitably affected [ 10 ]. Even before the pandemic, however, Korean women have been a vulnerable group regarding employment and self-reliance, compared to their male counterparts. During the 2008 financial crisis in Korea, non-regular workers were converted to part-time workers, and women occupied more of the lower-income portion of the workforce; women became assistants and worked mainly in the service sector [ 11 ]. Women are significantly impacted when socioeconomic crises worsen. Pervasive gender discrimination, the instability of female employment, violence against women, the burden of balancing work and family life, and the feminization of poverty have been pointed out as preexisting factors that deteriorate the quality of life of women in Korea [ 12 ]. Specifically, the degradation of the quality of life among young Korean women is attributed to factors such as a lack of career advancement opportunities, gender discrimination, biases, relative deprivation compared to men, economic weakening owing to job disparities or lack of promotions, and domestic violence [ 10 ]. As a countermeasure, suicide prevention policy should focus on changing the overall social atmosphere, gender-discriminatory appearance standards, and the culture that tolerates sexual abuse using hidden cameras. Violence against women in the labor market, such as sexual violence, dating violence, sexual contempt, and bullying should not be condoned [ 13 ]. Enforcing workplace policies that eliminate discrimination can foster women’s independence and hope. Additionally, policies that allow for career breaks during marriage or childcare will enable women to be equal members of society and participants in the labor market, as individuals who work together for social development. Since 2011, the suicide rate for Korean women aged 70 years and older has continued to decline, and the decline is significant. While this is a positive phenomenon, there is still a high rate of suicide among this age group compared with women in other age groups. In this regard, greater attention should be given to older women living alone, especially as Korea has the largest number of poor seniors among OECD countries [ 14 ], and economic differences owing to insufficient income and gender wage gaps have emerged as social problems [ 14 ]. The suicide rate owing to physical disease problems is higher than that of other age groups [ 6 ] and the subsequent economic burden is also a major cause of the high suicide rate [ 6 ]. Despair, loneliness, and the death of a meaningful person or spouse can increase suicide rates among older adults [ 5 , 15 ]. This means that as women’s lifespan increases [ 16 ], the number of older people living alone increases, and the proportion of older women at risk of suicide also increases. In 2020, 35.1% of households with a head of household age 65 years or older were single-elderly households. Of these, 44.1% were in their 70s, and 71.9% were women [ 17 ]. These older adults living alone rated their subjective health negatively, had poorer overall healthcare practices than all older adults, and 44.6% were self-supporting [ 17 ], indicating both economic poverty and healthcare vulnerability. Korean women experience a 1.5 to 2 times higher prevalence of depression than men [ 7 ], a systematic review of suicide among older Koreans living alone reported a high proportion of women aged 70 years and older living alone and found that higher levels of depression and lower levels of social support were associated with a higher risk of suicide [ 18 ]. According to a previous study [ 18 ], depression had the strongest effect on suicidal ideation in older adults, and higher levels of depression were associated with higher levels of suicidal ideation. However, social support from the family had a moderating effect on the relationship between depression and suicidal ideation. This indicates that older people living alone and with limited family support are more likely to be depressed and suicidal. Therefore, there is a need to screen older women for depression and provide them with community-based social support. Currently, Korea is conducting various types of projects for vulnerable populations through integrated health promotion programs. Nurses can promote mental health and counteract the vulnerability among older women living alone, especially through the effective implementation of home-visiting health care programs [ 19 ]. There are multiple factors to consider in the recent increase in suicide rates found among young women in their 20s and 30s, e.g., a steep increase starting in 2018 and a 7.0% increase from 2020 to 2021 in women in their 30s. The relationship between individual unhealthy behaviors, such as smoking and drinking, and suicide risk; and with environmental vulnerability during the COVID-19 pandemic are worth examining. Current smoking prevalence is the percentage of people who smoked five or more packs of cigarettes in their lifetime and are currently smoking. Among Korean men, the current smoking prevalence has continued to decline from 47.3% in 2011 to 31.3% in 2021, whereas it remained similar among women, from 6.8% in 2011 to 6.9% in 2021 [ 20 ]. In particular, Korean women in the 20–40 years age group showed an increasing trend in smoking rates compared with other age groups [ 21 ]. Meanwhile, monthly drinking rates (drinking at least once a month in the past year) for Korean women in 2021 were 60.6% for 19 to 29-year-olds and 56.9% for 30 to 39-year-olds, with more than half of the women reporting daily drinking [ 22 ]. In the 2021 data, women aged 30–39 years reported the highest rate of high-risk drinking, at 13.2%, followed by those aged 19–29 and 40–49 years at 10.7% [ 23 ]. A previous study [ 24 ] that analyzed data from the Korean National Health and Nutrition Examination Survey found that suicidal ideation was 1.56 times higher among alcohol abusers than among moderate drinkers, and 1.34 times higher among current smokers than among nonsmokers. Furthermore, compared with nonsmokers and moderate drinkers, current smokers and alcohol abusers had a 2.13 times higher risk of suicidal ideation and a 3.81 times higher risk of suicide attempts [ 23 ]. Given that smoking and drinking in women have been reported to be significantly associated with the risk of suicide death [ 25 ], the increasing prevalence of smoking and risky drinking in young women may be related to the increasing suicide rate. Therefore, efforts should be made to increase health-promoting behaviors in women. After the COVID-19 pandemic, the issues have been managed through “COVID-19 Women’s Employment Crisis Recovery Measures” [ 26 ], “Elderly Welfare Policy” [ 27 ], but support has been concentrated on women in their 30s and 50s, women who are responsible for caring, and older women. Notably, the large increase in suicide rates among women in their 20s in 2020 and 2021 may reflect the impact of the COVID-19 pandemic in this context, the lack of support for young women aged 20-30 years. The pandemic appears to have negatively impacted women more than men, with women experiencing mental health issues such as loneliness, depression, anxiety, and posttraumatic stress disorder symptoms, as well as an increased risk of violence against women at home and in the workplace [ 28 ]. Loneliness has been reported to be a significant predictor of suicidal thoughts and behavior [ 29 ]. A study on deaths before and after the COVID-19 outbreak in Korea [ 30 ] reported that the actual number of suicides among women and those under the age of 34 in 2020 significantly exceeded the predictions of suicide rates based on pre-COVID-19 data. This supports the notion that the negative impact of the pandemic on women is associated with increased suicide rates among younger women. Furthermore, the number of Korean women in their 20s and 30s who received medical care for depression in the first half of 2020 increased significantly compared to that in 2019 [ 31 ]. Social isolation and loneliness due to social distancing [ 32 ] during a pandemic, such as COVID-19, can have a huge impact on mental health, especially for young women, and efforts should be made to ameliorate this. Drug and carbon monoxide poisoning as a means of suicide among Korean women has steadily increased over the past decade, whereas suicide deaths by pesticide poisoning have decreased significantly. Regulations on the means of suicide, such as the 2012 ban on highly toxic pesticides in Korea [ 33 ], appear to have led to a decrease in actual suicide deaths due to pesticide poisoning. Indeed, the restriction of lethal means of suicide is an important component of suicide prevention strategies, as seen in Denmark [ 34 ] and Switzerland [ 35 ]. The increase in women’s suicide deaths due to drug and carbon monoxide poisoning suggests that women are more likely to choose nondramatic means of suicide as compared to men [ 36 ], especially given the ease with which sedatives and sleeping pills can be purchased online as well as charcoal burning that causes carbon monoxide emission. Korea’s Fifth Basic Plan for Suicide Prevention, established in 2023 [ 33 ], specifies aims to strengthen the management of risk factors in relation to the means of suicide, including places with a high frequency of suicide, suicide-related media reporting, and restricting dangerous and/or lethal means of suicide. Additionally, gender-specific patterns of suicide means should also be considered. This study updates Korean women’s suicide death statistics, suicide rate trends, gender- and age-specific suicide characteristics, and suicide means outcomes for the past decade from 2011 to 2021. The results showed that women in their 20s and 30s and women aged 70 years or older were more at risk of suicide deaths in Korea. In addition, there has been a recent increase in drugs and carbon monoxide as the preferred means of suicide for women. Therefore, more sensitive and responsive policies are needed and the following measures should be considered to reduce the suicide rate among women: improve employment; expand mental health promotion programs to mitigate depression; encourage health-promoting behaviors to reduce alcohol consumption and smoking in women; manage women’s preferred means of suicide, and increase sociocultural intolerance of sexual and dating violence.

Purpose This study aims to analyze the number of suicide deaths in women, trends in suicide mortality, characteristics of suicide by age, and outcomes of suicide means over the past decade (2011–2021) in South Korea. Methods Using cause of death data from Statistics Korea, an in-depth analysis of Korean women’s suicide trends was conducted for the period of 2011–2021. Results In 2021, women’s suicide death in Korea was 4,159, a rate of 16.2 per 100,000 population. The rate increased by 1.4% from the previous year. Since 2011, women’s suicide rate has been on a steady downward trend, but since 2018, it has been on the rise again. Suicide rates among women in their 20s and 30s have increased, especially since the coronavirus disease 2019 pandemic, and suicide rates among women over 70 years remain high. As compared to 2011, pesticide poisoning and hanging among the means of suicide have decreased significantly, while drug and carbon monoxide continue to increase. Conclusion Suicide rates for Korean women in their 20s and 30s have increased significantly in recent years, and those for women over 70 years remain high. Therefore, it is necessary to investigate the causes and establish national policies for targeted management of these age groups, which contributes significantly to the rising suicide rate among Korean women. Summary statement

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):348-356

oa_package/fb/9b/PMC10788386.tar.gz

PMC10788387

38204393

Introduction Endocrine-disrupting chemicals (EDCs) are compounds that interfere with normal hormone function. They are primarily synthesized for industrial solvents, electronics, personal care products, plastics, and pesticides, and they include polychlorinated biphenyls, bisphenol A, phthalates, dioxins, DDT (dichlorodiphenyltrichloroethane), and others [ 1 , 2 ]. Since EDCs are ubiquitous in our living environment, their effects can be seen at all stages of life, including in developing fetuses, and persistent exposure to EDCs and the accumulation of EDCs in the human body can lead to health problems in children and adults [ 1 , 3 ]. Particularly, exposure to bisphenol A and polybrominated diphenyl ethers during pregnancy is associated with intrauterine growth restriction [ 4 ], higher levels of anxiety, depression, aggression, hyperactivity, and behavioral problems in children [ 5 ], and persistent lower cognitive abilities from the ages of 2 to 8 years [ 6 ], as well as lower attention levels and executive functioning at the ages of 9 to 12 years [ 7 ]. More importantly, constant exposure to EDCs in the environment can lead to the early onset of puberty and breast cancer [ 8 ], obesity, diabetes, thyroid dysfunction, and infertility [ 3 , 9 ]. Thus, it is critical to be aware of environmental hazards and the life-long health impacts of EDCs beginning in the early stages of life. In this regard, parents are primarily responsible for protecting children from exposure to EDCs [ 10 ]. As children grow up, parents play multiple roles in the formation of their health behaviors by educating their children, acting as role models, and influencing their cognitive and behavioral characteristics [ 11 ]. Many studies have shown that parenting practices, particularly mothers’ parenting styles, influence their child(ren)'s body weight, diet, physical activity, and eating behaviors [ 12 , 13 ]. Due to the important role of mothers in families and social environments for protecting children from various harmful conditions, mothers should be engaged to and supported to guide children's health practices. Nevertheless, there is little research on the perception of EDCs among mothers, who tend to be children’s primary caregivers. Mothers are known, however, to share information about EDCs through social networking services [ 14 ]. It is important to understand mothers’ real experiences; what and how they are concerned about EDCs, what kind of matters they come across, and how they take care of it during childrearing. Therefore, a qualitative approach was considered appropriate for addressing the aims of this study exploring perspectives and ideas about EDCs among Korean mothers with young children, particularly as primary caregivers. This study aimed to explore the perceptions of EDCs among mothers with young children to provide a basis for parental education to enhance parents’ awareness concerning the risks of EDCs, particularly in a way that meets parents’ needs and expectations concerning childcare.

Methods Design This study used an exploratory qualitative design to explore the perception of mothers with young children about EDCs for their concerns, the issues they faced, and the way they dealt with them. This study adhered to the COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines ( https://www.equator-network.org/reporting-guidelines/coreq/ ). Participants The participants were recruited from three locations in the Kangwon-do area selected through snowball sampling. A director of a local kindergarten was approached by the research team, and then the director as a key person introduced mothers to the study. Considering the distribution of childrens' age, two additional childcare centers were introduced by the key person, then each director of the center allowed the research team to recruit potential participants The mothers were included in the study if they (1) were their child’s primary caregiver, (2) had at least one or more infants, toddlers, or preschoolers, and (3) provided written consent after agreeing to the purpose and processes of the study. There was no specific exclusion criterion for the mothers. Since mothers’ experiences could be influenced by the developmental processes of their children, we decided to explore various experiences of mothers so as not to be biased to a certain gender or age within the age criteria during the recruitment process. The number of study participants in a qualitative study is considered sufficient once the threshold of reliable information is met, and the appropriate number of participants is generally assumed to be 1 to 30 [ 15 ]. A total of 12 mothers were interviewed and included in the final analysis as the data were saturated. Data collection procedure For data collection, initial meetings with possible participants and the research assistant were arranged by the director of the kindergarten and childcare centers. For mothers who agreed to participate, interviews were conducted by the principal investigator on a scheduled date and time in a private room in each institution. A research assistant with a master’s degree was also present in the room to record field notes about the interview environment and the non-verbal behaviors of the participants. Each participant was interviewed once and the each interview proceeded in a comfortable environment where the mothers could share their experiences in as much detail as possible. At the end of the interview, the mothers shared any questions or comments they had. A small gift (worth 25 US dollars) was given to the mothers to express gratitude for their time and cooperation. All interviews were recorded, and the files were transcribed by the research assistant, using identification numbers to anonymize participants. Field notes were also utilized for the data analyses. Each interview lasted for approximately 47 to 60 minutes, with an average of 54 minutes. Interview questions The four main questions were provided as follows; “Would you tell us what you know about EDCs?”, “What do you think about the impact of EDCs on you and your child(ren)?”, “What actions do you take to reduce the health impact of EDCs?”, and “What do you think are the most effective ways to reduce exposure to EDCs?” Data analysis A total of 730 minutes of interviews was transcribed and analyzed according to Graneheim and Lundman’s [ 16 ] qualitative content analysis process method, which proceeded as follows: The researchers initially read the transcribed materials including field notes to get a sense of the whole, then started to mark meaningful phrases and sentences as units of analysis during the second reading. Then we selected meaning units separately and compared the outcomes to confirm the significant meaning units. Next, the selected meaning units responding to the study aim were reviewed and agreed upon regarding their core contents between the authors. Then condensed meaning units were composed and abstracted into subcategories and categories. During the analysis, we continuously discussed interpretations in all steps. Trustworthiness To achieve trustworthiness, we tried to meet the credibility, confirmability, authenticity, dependability, and transferability criteria for qualitative studies [ 16 ]; to ensure credibility, we recruited mothers with young children of infants, toddlers, or preschoolers who were willing to share their experiences according to the aims of the study. In addition, recruitment was continued to include 12 mothers to obtain the richness and saturation of data. For confirmability and authenticity, the analyzed outcomes were verified by three mothers (each one from three age groups: an infant, a toddler, and a preschooler). They confirmed if the reports reflected mothers’ feelings, tones, expressions, and words of their experiences in richer and more vigorous ways. For dependability, we had more than five team meetings to ensure that no errors were made during the analysis, particularly, codes and supporting quotes from the original text were selected to be differentiated among subcategories and categories. In addition, we attempted to avoid any preconceptions and listened to the mothers’ experiences with a nonjudgmental attitude so that the participants would be able to openly express what they wanted to share. To ensure transferability, the selection criteria and characteristics of the mothers were described in the report to provide the content from which the findings could be transferred to other groups of mothers.

Results The general characteristics of the 12 mothers are presented in Table 1 . The average age was 34.3 years (range: 23–41 years), and the average number of children was 1.6 (range: 1–3). In terms of financial status, 11 mothers (91.7%) considered themselves middle-class, and six mothers (41.7%) were employed. Two mothers reported having thyroid disease and asthma, and there were four children diagnosed with precocius puberty or atopic dermatitis diagnosed with precocious puberty and atopic dermatitis, respectively. A total of 288 major statements were identified in the interviews and after repeated reading of transcripts, 87 meaning units were found to be significant. A total of 25 condensed meaning units were then generated based on the interpretation of underlying meanings, which were further categorized into 10 subcategories and four categories. The mothers’ experiences of EDCs defined in the analysis were ‘Knowledgeable yet contrasting ideas regarding EDCs,’ ‘Negative health impact, but more so for children,’ ‘Inaction or trying to minimize exposure,’ and ‘Need for early, reliable resources and social change’ as shown in Table 2 . Knowledgeable yet contrasting ideas regarding endocrine-disrupting chemicals The mothers said that they knew EDCs as substances entering our body through various routes, in addition, some mothers expressed that EDCs were toxins accumulated in the bodies while others perceived EDCs as being harmless as they would decompose in the body. Multiple routes of endocrine-disrupting chemicals entering the body Five condensed meaning units were included in this subcategory. The mothers recognized that EDCs were substances that entered the body through various methods, such as using plastic containers or toys, heating food in disposable containers in the microwave, breathing in fumes from burning substances, and absorbing them through the skin from shampoo and cosmetics in daily life. In addition, they perceived EDCs as something that affected the fetus through the umbilical cord during pregnancy. "It’s in a lot of plastics... the biggest inflow would be through the mouth. Particularly, babies, they take everything to their mouth and suck their toys. I realize it strongly when I hear the news on TV about the detection of EDCs from toys.” (participant 1) “I have heard from mom’s SNS. When we pour hot water in the white Styrofoam of cup noodles and when we put vinyl in the microwave... disposable containers for delivery food... those are all EDCs.” (participant 5) “The smoky smell from something burned... that’s the EDCs. It also exists in the air and enters our body when we breathe.” (participant 7) “It is also in the shampoos and cosmetics we use every day. It can infiltrate through our skin and eyes [laugh].” (participant 8) Contrasting ideas about endocrine-disrupting chemicals In this subcategory, two condensed meaning units were explored. The mothers understood EDCs in a contrasting manner, with some viewing them as something accumulated in the body without being discharged and others believing that they are decomposed in the body. “Since EDCs are chemically generated, detrimental substances will be accumulated in our body if it is heated and transformed into EDCs. Because of environmental pollution, fruits grow deformed, so it is scary if the same thing could happen if EDCs are not eliminated from our body.” (participant 9) “I’ve heard from my husband, a chemistry researcher that all those things accrue in women’s wombs. He always insists not to buy canned products, bleached toilet paper , etc..” (participant 6) “I think we can be immune to EDCs as it is deformed like a virus... Maybe it could also be decomposed in our body if we follow a vegetarian diet.” (participant 1) “How long are we going to live (laugh)... do people live forever if not eating fast foods, if not using cotton sanitary pads? A person who says EDCs are noxious seems to be picky. Eventually, we all die later. I don’t care much about that.” (participant 11) Negative health impact, but more so for children EDCs were believed to induce health problems in mothers and children were seen as more vulnerable to the effects of EDCs. However, some mothers were not concerned about the effects of EDCs on them or their children. They expressed different opinions on the influences of EDCs on health. Causes of health problems for oneself Three condensed meaning units were identified in this subcategory. Eating a large amount of instant food was a trigger for menstrual pain, and contact with EDCs caused allergies, asthma, and skin rashes. In addition, women felt the risk of infertility since they were born with a limited number of eggs, which could be affected by EDCs. The mothers acknowledged the relationship between EDCs and women’s reproductive health issues based on their experiences and allergic diseases associated with the environment. “I ate a lot of cup noodles and instant food when I was in high school and had worse cramping, which I never had before.” (participant 6) “Unlike the first and the second pregnancy, I had trouble having a baby after... I think women would be more vulnerable to infertility than men because ovum is in women’s bodies from birth while sperm is constantly produced, isn’t it?” [nodding and looking at the interviewer] (participant 2) “My asthma gets worse, too, when the air quality is bad, and wouldn’t it make the skin more sensitive?... and it won’t be good for those with weak bronchial tubes...” (participant 4) Higher vulnerability of children to the impact of endocrine-disrupting chemicals Two condensed meaning units reflected the higher vulnerability of children rather than adults. The mothers expressed that their children had a higher chance of being exposed to EDCs as they are going to live in a developed, modern society for a longer time than we adults will live. “Kids are living in an environment with polluted air, vehicle smoke, and manufactured goods... so I think ADHD is increasing now...one of my friend’s kid was also diagnosed with it, kind of bad substances causing issues to the brain....” (participant 12) “I see the difference clearly in my boy. Whenever he eats a lot of snacks, atopy symptoms are spreading under the genital area.” (participant 7) “My daughter (8 years-old) is under treatment for precocious puberty, I found her breast budding one day. I blame myself; she might have had the disease because I gave her instant foods, cup noodles too much.” (participant 3) Optimism about one’s health problems due to endocrine-disrupting chemicals In contrast, the mothers perceived that, since they did not currently have any particular health problems, any health issues from EDCs would be experienced in the distant future, if at all. In addition, they did not believe that adults would experience health issues from EDCs and felt they were far removed from such health problems. “I feel like I won’t have any problem due to EDCs in the short term. If it does, it will be about 20 to 30 years later... around menopause?” (participant 9) “There is nothing I can directly feel. It’s invisible so it seems okay. To be honest, I don’t care...” (participant 8) Inaction or trying to minimize exposure For the question of what the mothers do to protect their health from EDCs, two opposing subcategories were identified. One position indicated keeping the same way of living because of the absence of disease and preference for a more convenient life. The other took actions to avoid exposure to EDCs based on the health problems of their children as well as their own health concerns. Maintaining the easy ways of living Two condensed meaning units were identified under this subcategory. Some felt no need for action since they were not currently experiencing any health problems, while others kept using convenient products despite the harms of EDCs. The mothers were aware of the destructiveness of EDCs, but they did not make any changes in their behavior for various reasons, such as a lack of current health issues, time management, and parenting convenience. “I think I’ll follow the advice only when I start feeling sick [laugh]. I have a habit of not doing something unless it is at hand.” (participant 4) “It is hard to give up or to reduce the use of the microwave or an air fryer. I need those for timesaving when cooking for my baby or family [shamefaced smile].” (participant 11) Taking actions to reduce endocrine-disrupting chemicals exposure based on experiences In this subcategory, two condensed meaning units were identified. The mothers tried to minimize their exposure to EDCs after their children experienced health problems and throughout pregnancy and childbirth. The mothers stated that they acknowledged the health problems of their children due to EDCs and that they took extra care to avoid EDCs that could harm the fetus during pregnancy. “My child has heavy atopic dermatitis, so I try to give as little instant food as possible and to give more homemade foods. It is hard to see him having a hard time because of itching so I try to do my best as a mother.” (participant 3) “I started to be concerned when I got pregnant... so I was especially careful not to use the microwave and plastic containers. Now I wonder about the world our children will live in.” (participant 10) Need for early, reliable resources and social change The mothers expressed three subcategories related to their ideas for reducing their exposure to EDCs’ harms. The younger the child, the better the effects of education, so early education is essential. The mothers perceived that EDCs are associated with environmental pollution, which requires social agreement to establish policies. Finally, the mothers requested practical information for reducing EDC exposure. Early education in children and its ability to spread Two condensed meaning units were identified in this subcategory. The mothers believed early education about EDCs for children would be more effective for spreading information about EDCs and encouraging positive life habits. In addition, they believed that children could motivate their parents to change their behaviors by sharing what they learned. “I’m not interested in learning more about EDCs [quietly] but I think it will be beneficial to teach kids in the school curriculum because learning at a young age is most effective.” (participant 4) “Once they learn, they will point out their moms’ faulty behavior. It will lead the parents to change their behavior... so I think it will be effective to educate the kids.” (participant 6) Social and systemic changes to reduce endocrine-disrupting chemicals Under this subcategory, three condensed meaning units were identified. The mothers believed that government policy and regulation are needed due to the lack of awareness on reducing the consumption of products containing EDCs. In addition, they suggested continuous promotion through social media to raise awareness about EDCs. They also pointed out that environments where people can sell and buy eco-friendly products should be fostered. “People don’t seem to be urgent about EDCs’ risks and say ‘why now?’ That’s why I feel the need for some kind of governmental regulation.” (participant 7) “I think societal awareness is important. Campaigns or social movements are what we need. Since social media is powerful today, information could spread through mom’s cafes or civic groups...” (participant 11) “I hope prices are lowered with more movements for eco-friendly product consumption and with more production of them.” (participant 10) Reliable information applicable to daily life Two condensed meaning units were identified related to this subcategory. The mothers wanted tangible information with scientific evidence to curtail the harms of EDCs, which are invisible toxic substances. Moreover, they wanted practical information that could be applied to their daily lives to reduce exposure to EDCs. They called for specific and realistic alternatives to motivate action. “Notable results of experiments on the impact of EDCs can be effective, like lung cancer photos on cigarette packs. That will be easier to understand, then we would be more careful, wouldn’t we?” (participant 5) “When a person that I know gave me information about avoiding EDCs for cooking, it was useful for me to follow what I had heard.” (participant 11) “Eradicating EDCs would be very unrealistic, so experts could recommend alternatives that are practical...” (participant 1)

Discussion The study explored the perceptions about EDCs from the perspectives of mothers with young children using qualitative content analysis. Exposure to EDCs is known to occur through food, water, dermal contact, and inhalation [ 17 ], and the mothers in this study accurately recognized the transmission routes of EDCs. The mothers in this study, possibly due to their recent experiences of pregnancy and childrearing, were able to identify most of the possible routes of transmission, including the umbilical cord from the mother to the fetus. However, four of the mothers did not believe EDCs caused any bad consequences and decomposed gradually in the body. As suggested in prior literature [ 18 ] perceived EDCs as low risk since they are invisible and ubiquitous in daily life. As most of the mothers correctly perceived, EDCs accumulate and persist in organisms and the environment, and they may cause clinically observable and, when possible, measurable effects [ 19 ]. Thus, the long-term consequence of EDCs must be accurately shared with the public over time. Labeling consumer products with information would be a good way to increase risk perception, which has been observed to be effective in women of childbearing age [ 20 ]. As indicated in a previous study of 406 Korean adults [ 21 ], better knowledge about the environment would influence people to purchase more pro-environmental products. The second distinct perception was about the relationship between EDCs and health problems. The mothers assumed that the vulnerability of children was much higher due to a higher chance of extended exposure to EDCs, which could potentially engage mothers to have more interest in preventive behaviors through future education and intervention. Therefore, it is important to provide information to reproductive aged women concerning the timing of exposure to EDCs, since developing fetuses and neonates are most vulnerable to endocrine disruption [ 22 ]. Indeed, many diseases and disorders are now considered to be related to prenatal exposure to EDCs, such as premature birth [ 23 ], autism [ 24 ], allergies [ 25 ], and congenital abnormalities [ 26 ]. While the mothers acknowledged various health problems due to EDCs, seven of the participants were optimistic that health problems due to EDCs would only happen to them in the distant future. Although EDCs have a very long half-life in the body and their adverse effects manifest at later ages [ 17 ], it is still important for parents to maintain a healthy lifestyle to prevent diseases and to be role models for their children. Above all, optimism hinders people from engaging in preventive health behaviors [ 27 , 28 ]. Thus, strategies need to be devised to minimize inaccurately optimistic views and increase awareness about the potential health consequences of EDC exposure. The extent to which the mothers in this study understood the health impacts of EDCs appeared to correspond to their proactive behaviors to avoid the harms of EDCs. The mothers’ actions to avoid exposure to EDCs mostly related to their children’s health problems, even at the time of pregnancy and childbirth, rather than their own health issues. However, the mothers tended to maintain their lifestyles due to the convenience of using products with EDCs, which was similar to the findings of a study about the attitudes of young adult women in Korea concerning EDCs [ 29 ]. Mothers of young children are generationally accustomed to a high-convenience lifestyle and tend to consume more fast foods or processed foods and disposable products. Unconscious exposure to EDCs occurs through various routes of transmission. In particular, dietary intake accounts for more than 90% of total exposure to EDCs [ 30 ]. Therefore, mothers must understand their own vulnerability and health risks related to EDCs and ultimately make sustainable behavioral changes, especially as the primary caregiver of their child(ren) [ 31 ]. One of the main categories from the interviews with the mothers was that they required various ways to reduce their exposure to EDCs, such as actions based on the precautionary principle, regulatory actions, scientific evidence, and changes in the awareness of the general population about EDCs on social media. These varied demands indicate that detailed and concrete strategies that are applicable at the individual, public, and government levels are needed. Media, which comprise a major source of information, are an important determinant of risk perception [ 18 , 32 ] Media is noteworthy, not only to ensure that the public maintains a positive attitude toward precautionary measures [ 33 ] but also as an easy and effective way to guide the public to improve their knowledge, perception, and behaviors [ 34 , 35 ]. Therefore, media strategies are needed to disseminate how EDCs evoke negative hormonal mechanisms in the human body and how behavioral changes could lead to positive changes to protect people from the harms of EDCs. Our study also found a strong need for early education about EDCs for children to establish positive life habits to prevent EDC exposure. The mothers anticipated more significant educational effects in their children rather than in themselves and expected their children to influence themselves. Life habits developed in early childhood affect the way individuals observe and respond to others’ health habits and can influence that individual’s family members to acquire knowledge, skills, and attitudes to improve their health [ 36 ]. A previous study found that children aged 4 to 5 years who had learned about passive smoking prevention insisted that their family members quit smoking [ 37 ]. Thus, environmental education during early childhood would be an effective strategy for influencing children to grow up with good health habits and also inspire behavioral changes in their parents. Information technology such as virtual reality would be a suitable mode to raise awareness of EDCs as well as to reduce exposure to EDCs. It is possible that mothers with more interest in EDCs could have possibly participated in the study due to their own or their children’s health problems such as asthma, atopic dermatitis, or precocious puberty. Thus, it could be a possible bias and future studies should explore a wider range of perceptions of mothers. In conclusion, mothers in this study were knowledgeable about EDCs and actively needed further education and support. While they tended to focus more on the health impact of EDCs on their children and were optimistic about their health risks, paying less attention to their preventive behaviors. As strategies to prevent exposure to EDCs are urgently needed, prenatal education programs could include the topic of EDC exposure and its health impacts, particularly the routes of exposure not only to the mother but to the fetus. Also, parents and teachers need to be prepared in advance with accurate information and preventive strategies, to enable them to guide their young children to apply awareness, knowledge, and preventive behavioral habits in their daily lives. Overall, education programs to improve the publics general understanding of EDCs and the consequences of EDC exposure for students, health professionals (especially in endocrinology, pediatric, and maternity clinics) and laypersons are needed. Healthcare professionals should also provide the public with practical guidelines for health behaviors related to EDCs. It is also important to keep in mind that this requires political will to limit the use of these chemicals and develop and implement remediation technologies.

Purpose Despite the health impacts of endocrine-disrupting chemicals (EDCs) beginning in the early stages of life, there is little research on the perception of EDCs among Korean mothers, who are primarily responsible for protecting children. This study aimed to explore how mothers with young children perceived EDCs for their concerns, the issues they faced, and the way they dealt with them. Methods An exploratory qualitative design was utilized. Twelve mothers who were recruited from snowball sampling participated in voluntary interviews. Individual in-depth interviews lasting approximately 47 to 60 minutes were recorded and transcribed verbatim. The data were analyzed using qualitative content analysis as suggested by Graneheim and Lundman. Results Four categories, 10 subcategories, and 25 condensed meaning units were identified by interpreting mothers’ underlying meanings. The four categories were ‘Knowledgeable yet contrasting ideas regarding EDCs,’ ‘Negative health impact, but more so for children,’ ‘Inaction or trying to minimize exposure,’ and ‘Need for early, reliable resources and social change.’ Mothers were knowledgeable regarding EDCs and actively needed further education and support. While they tended to focus more on the health impact of EDCs on their children and were optimistic about their health risks, paying less attention to their preventive behaviors. Conclusion Healthcare professionals must consider mothers’ perceptions of EDCs in future education and interventions ensuring EDCs impact on women’s life stages such as puberty, pregnancy, and childrearing. Also preventive strategies that can be applied to their daily lives are needed. Summary statement

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):337-347

oa_package/78/71/PMC10788387.tar.gz

PMC10788388

38204392

Introduction Sarcopenia is one of the diseases that degrade the health-related quality of life (HRQoL) of older adult women and the decrease in muscle mass due to aging is one of the representative changes [ 1 ]. Sarcopenia causes musculoskeletal diseases (e.g. falls and fractures), depression, or cognitive decline. In addition, chronic diseases such as heart failure and chronic obstructive pulmonary disease accelerate muscle loss, resulting in a vicious cycle. This not only has a great impact on the HRQoL but also has become an important public health problem [ 2 ]. The decrease in muscle strength and muscle mass begins at the age of about 40 years, and women in particular lose muscle mass at the same time they experience an increase in abdominal fat due to energy loss caused by aging and hormonal changes caused by menopause [ 3 ]. In an 8-year follow-up of a longitudinal study of aging with a sample of 3,404 people in the United Kingdom, women were at 20% higher risk of developing sarcopenia than men [ 4 ]. In particular, in Asians, women had a higher risk of sarcopenia due to higher body fat ratios than other ethnic groups and increased abdominal obesity [ 5 ]. Therefore, the management and prevention of sarcopenia for older Asian women diagnosed with sarcopenia is an important health problem. Older adult women with sarcopenia have been reported as feeling lonely and depressed due to difficulties and social constraints in daily life related to aging and having suicidal thoughts, which can negatively affect their HRQoL [ 6 ]. In addition, a longitudinal study of 40–44 years-old participants reported that having sarcopenia at baseline was associated with worse scores of HRQoL at follow-up, compared to those without sarcopenia at baseline [ 7 ]. Another study of 4,937 Korean seniors aged 60 years or older found that HRQoL scores were significantly lower for sarcopenic women compared to their nonsarcopenic counterparts [ 8 ]. Moreover, as older adult women have a higher muscle reduction rate than older adult men and a longer life expectancy [ 9 ], they are a vulnerable group that is likely to be in a vicious cycle caused by sarcopenia. The quality of life (QoL) of older people with sarcopenia is also related to mental health, i.e., having sarcopenia was associated with a higher level of depression or anxiety, lower subjective health perception and nutritional status, and poorer QoL [ 10 ]. Moreover, because older people have many diseases, HRQoL was found to be related to the type of health insurance currently subscribed to and whether private medical insurance is available [ 11 ]. A useful model for identifying factors affecting HRQoL was modified by Ferrans et al. [ 12 ] from Wilson and Cleary’s HRQoL model [ 13 ]. This modified HRQoL model offers a framework that integrates the biomedical paradigm focused on the cause of disease and the social science paradigm focused on function and overall well-being. The model explains how HRQoL can be examined in terms of dynamic and multifaceted aspects while explaining the influence on the HRQoL through the following characteristics: individual characteristics, biological factors, symptoms, functional status, general health perceptions, and environmental characteristics [ 12 ]. Therefore, this study aimed to use the model to explore the factors influencing HRQoL in older women with sarcopenia. Previous studies on sarcopenia in elderly women conducted in South Korea (hereafter, Korea) have focused on the effect of sarcopenic obesity on psychological health and QoL [ 6 ], the prevalence and factors related to sarcopenic obesity [ 14 ], and the prevalence of sarcopenia in association with activities of daily living, nutrition, and depression [ 14 ]. However, there are few studies that comprehensively sought to identify factors affecting the HRQoL based on Ferran’s HRQoL model [ 12 ] in older adult women with sarcopenia. Therefore, the current study was conducted to identify factors affecting HRQoL in older women with sarcopenia, to ultimately provide nursing evidence for improving their HRQoL. This study aimed to identify factors influencing HRQoL of older adult women with sarcopenia based on Ferran’s HRQoL model [ 12 ], and the specific purposes are as follows. (1) To identify the general characteristics of older adult women with sarcopenia (2) To investigate the difference in HRQoL according to their general characteristics (3) To determine the factors influencing their HRQoL

Methods Research design This study is a descriptive correlational study conducted to identify factors influencing HRQoL in older adult women with sarcopenia in Korea, analyzing the 8th Korea National Health and Nutrition Examination Survey (KNHANES) 2019 data. This study was described in accordance with the STROBE guidelines ( https://www.strobe-statement.org/index.php?id=strobe-home ). Data sources The 8th KNHANES was conducted in 2019 when the Korea Centers for Disease Control and Prevention conducted a survey of the annual National Health and Nutrition Survey with the approval of the Research Ethics Review Committee. Stratified sampling was done for all Koreans and from the 4,381 women out of 8,110 respondents of the KNHANES, 1,347 women aged 60 years or older were extracted. Subsequently, 290 elderly women with sarcopenia were again extracted. Excluding 148 persons with any missing information on even one of the variables considered in the study, the final analysis was done on a total of 142 elderly women with sarcopenia ( Figure 1 ). Measurement Sarcopenia According to the Asian Working Group for Sarcopenia, sarcopenia is diagnosed based on handgrip strength (HGS), physical performance, and skeletal muscle mass, and a condition in which all three are reduced is classified as severe sarcopenia [ 2 ]. In the current study, sarcopenia is defined as HGS of less than 18 kg in women [ 2 ]. The maximum value of HGS of both hands or one hand measured three times was used. Health-related quality of life The HRQoL was analyzed using the EuroQol-5 Dimension (EQ-5D) instrument developed by the EuroQol Group [ 15 ]. The EQ-5D measures overall health and consists of five dimensions; mobility, self-care, usual activity, pain/discomfort, and anxiety/depression. Items are evaluated in three levels: ‘no problem,’ ‘moderate problem,’ and ‘serious problem’ and analyzed by the EQ-5D index, which is calculated from the prediction formula presented by the Korea Disease Control and Prevention Agency. A weight-adjusted value was calculated as 0 to 1 point and scores closer to 1 indicate better HRQoL. Independent variables Individual characteristics include age, marital status, income level, education level, employment, drinking status, and total sleep duration. Biological function includes disease and comorbidity. Symptoms include subjective perceptions and experiences, such as depression symptoms, suicidal ideation, and subjective stress. Functional status comprises physical, social, and role, such as climbing stairs and working. General health perceptions consist of subjective health evaluation, such as perceived health status. Environmental characteristics include health insurance, and interpersonal relationships, such as health insurance, private insurance, living area, and living type [ 12 ]. Individual characteristics Age, marital status, education level, income level, employment, drinking, and sleep duration were included as the individual characteristics. Age was classified into early older adults aged 60 to 74 years and late older adults aged 75 years or older [ 16 ]. Marital status was classified into married or others, and education level was classified as elementary school or less, middle school, and high school or higher. Household income was classified into three groups according to the instructions for using KNHANES, lower (≤1 million Korean won [KRW]), middle (1–3 million KRW), and upper (>3 million KRW). Employment was classified into yes and no; drinking was classified into drinking and nondrinking; and total sleep duration was classified as 7 hours or more and less than 7 hours. Biological function Biological function includes osteoporosis, diabetes mellitus, body mass index (BMI), and waist circumference. Osteoporosis and diabetes were classified into yes and no, depending on whether they were diagnosed by a doctor. BMI was classified into <18.5 kg/m 2 (underweight), 18.5–22.9 kg/m 2 (normal), 23–24.9 kg/m 2 (overweight), and ≥25 kg/m 2 (obese). Waist circumference was classified by self-report as less than 85 cm (normal) and 85 cm or greater (obesity) [ 17 ]. Symptoms Symptoms included depressive symptoms, suicidal ideation, and perceived stress. Depressive symptom was classified as yes and no for “depression for more than two consecutive weeks,” and suicide ideation were classified as yes and no for “serious suicide ideation over the past year.” Perceived stress was reclassified as “a lot (feeling a lot, feeling very much)” and “a little (feeling a little, feeling little)” about stress when asked about how much stress they felt in daily life. Functional status Functional status included difficulty climbing stairs and difficulty working during the past week. Difficulty of climbing stairs was classified as ‘no difficulty climbing stairs (no),’ ‘some difficulty climbing stairs (mild),’ ‘a lot of difficulty climbing stairs (severe),’ and ‘couldn’t climb stairs (very severe).’ Difficulty of working was classified as ‘no difficulty working (no),’ ‘some difficulty working (mild),’ ‘a lot of difficulty working (severe),’ and ‘couldn’t work (very severe).’ General health perceptions General health perceptions were classified into good (very good, good), ordinary (normal), and poor (very bad, bad) based on the question, “How do you feel about your health in general?” Environmental characteristics Environmental characteristics included health insurance, private insurance, living area, and living type. Health insurance was classified into self-employed, employee, and dependent. The private insurance was classified into yes and no according to membership. The living area was classified into urban and rural, and the living type was classified into alone and together. Statistical analysis The complex sample design was performed in consideration of the sample weight according to the sample design. Stratification variables and colony variables provided by the Korea Centers for Disease Control and Prevention were designated and analyzed. The data was analyzed using IBM SPSS ver. 26.0 (IBM Corp., Armonk, NY, USA), and significance set at p <.05. For participants’ characteristics, frequency and weighted percentage, estimated mean, and standard error (SE) were computed using complex sample frequency analysis. For the difference in HRQoL according to the general characteristics, independent t-tests were performed. Multiple regression analysis was performed for factors influencing HRQoL.

Results Participants’ general characteristics The mean age of the 142 participants was 72.77 years (SE, 0.57), and 51.3% were over 75 years of age. Overall, 72.3% of participants were unemployed and 54.2% were in the lower household income group. Regarding biological function, the most prevalent disease was osteoporosis (38.0%), followed by diabetes mellitus (27.5%). In terms of BMI, most respondents were normal (37.3%), followed by overweight (30.5%), and obesity (29.3%), and 55.7% were obese in waist circumference. Regarding symptoms, 16.1% of participants suffered from depression, 10.0% had experienced suicidal ideation, and 29.6% of participants reported a lot of stress in their daily lives. Regarding functional status, 47.9% and 42.2% of participants experienced mild difficulty climbing stairs and working, respectively, and 51.4% perceived their health status as ordinary. Regarding environmental characteristics, 62.9% of the employed and 58.3% of all participants did not have private insurance, 69.2% lived in urban areas, and 68.5% lived with someone ( Table 1 ). Health-related quality of life according to the general characteristics of older adult women with sarcopenia Married participants had significantly higher HRQoL than those whose status was otherwise (t=10.05, p =.002). In terms of symptoms, those who did not report depression symptoms and suicidal ideation had a higher HRQoL scare than those who did (t=5.02, p =.029; t=6.87, p =.011, respectively). Regarding functional status, those who had no or mild difficulty climbing stairs nor working had a higher HRQoL than their counterparts who had severe difficulty climbing stairs and working (F=8.72, p <.001; F=6.27, p =.001, respectively). In general, those with good or normal health perception showed a higher HRQoL than those with poor perception (F=14.32, p <.001). Regarding environmental characteristics, HRQoL was higher for those with private insurance (t=4.07, p =.048), and those living with someone (t=–3.65, p =.001) ( Table 2 ). Factors influencing health-related quality of life of older adult women with sarcopenia No and mild difficulty in climbing stairs were significantly associated with a higher HRQoL (B=.203, p =.001; B=.209, p <.001, respectively). In working, no and mild difficulty were also significantly associated with a higher HRQoL (B=.254, p =.002; B=.208, p =.013, respectively). Good or normal perceived health perceptions were significantly associated with a higher HRQoL (B=.111, p <.001; B=.087, p <.001, respectively). The explanatory power of these variables’ ability to explain HRQoL in older adult women with sarcopenia was approximately 56% ( Table 3 ).

Discussion Regarding functional status, difficulty working had the greatest impact on the HRQoL of older adult women with sarcopenia. Working not only improves economic status but also self-esteem and QoL for older adult women with sarcopenia [ 18 ]. This may be because self-esteem increases through social ties and role performance; and through working people can feel less lonely or alienated, which may have a positive effect on subjective health awareness [ 19 ]. As the working-age population (15–64 years old) in Korea continues to decline and the older adult population rapidly increases, the possibility for older adult women to work may improve individual QoL and further contribute to sustainable growth in Korean society [ 20 ]. Therefore, community support systems that offer various social entry programs can help to create jobs for older adult women with sarcopenia. Follow-up studies that identify other related factors that affect the HRQoL of older adult women with sarcopenia, and intervention directions are also needed. This study’s finding that HRQoL was higher with no difficulty climbing stairs is supported by a prior study that reported a statistically significant positive correlation between physical fitness variables, including stair climbing, with QoL in Korean low-income elders 65 years or older [ 21 ]. Another study [ 22 ] found that older people participating in a physical activity program including climbing stairs had more muscle strength. In addition to seeking to prevent and manage muscular dystrophy through exercise from middle age, when muscle mass begins to decrease [ 23 ] efforts to guide and educate older adult women with sarcopenia are needed, so that they can continue to practice climbing stairs in their daily lives. Regarding general health perception, high HRQoL was associated with perceiving one’s health condition as good, which is consistent with other studies [ 4 , 24 ]. Perceived health perception is a comprehensive evaluation of one’s health in terms of physical, mental, social, and psychological aspects, and is reported to be closely related to depression and physical activity [ 25 ]. Given that health-promoting programs for older adults resulted in improving perceived health awareness and QoL [ 26 ], active management programs for older adult women with sarcopenia are needed. A limitation of this study was that while sarcopenia should be studied in consideration of time changes to identify causal relationships, because cross-sectional KNHANES data that included HGS measurement were used, it was only possible to identify associated factors. Therefore, it would be beneficial to incorporate sarcopenia measures in future KNHANES data, e.g., physical performance or skeletal muscle mass, especially for high-risk groups. Also, while the revised QoL model describes the effect of individual and environmental characteristics on biological function and the interactions between an individual and their environment, this study did not list the results of these effects and interactions. Despite these limitations, this study is meaningful in that it applied Ferran’s QoL model [ 12 ] to identify the factors influencing the HRQoL of older adult women with sarcopenia. In conclusion, this study’s findings show that it is necessary to actively implement supportive interventions that can reduce difficulties in daily life, such as working and climbing stairs for elderly women with sarcopenia. Findings can be applied by encouraging women to exercise from middle age, when sarcopenia can begin, and assisting older adult women to continue their physical activities. Finally, continuing and expanding sarcopenia measurement in national surveys and the development of interventions and health policies to improve the HRQoL of older adult women with sarcopenia are also needed.

This article is based on the master’s thesis of the first author (Sol Hyun Lee) from Jeonbuk National University. Purpose This study aimed to identify factors influencing the health-related quality of life (HRQoL) of older adult women with sarcopenia. Methods The study was secondary data analysis using data from the 2019 Korea National Health and Nutrition Examination Survey. The final sample consisted of 142 women aged 60 years and older with sarcopenia and were selected from 8,110 women. The participants was analyzed using complex descriptive statistics, independent t-test, and regression. Results In terms of HRQoL, three general characteristics were found to be influential, with an explanatory power of 56.0%: difficulty climbing stairs, difficulty working, and perceived health status. Having no or mild difficulty when climbing stairs (B=.20, p =.001; B=.21, p <.001) and no or mild difficulty when working (B=.25, p =.002; B=.208, p =.013) had a significant effect on HRQoL compared to severe difficulty. Having good or ordinary perceived health status had a significant effect on the HRQoL (B=.11, p <.001; B=.09, p <.001). Conclusion Based on study findings that the HRQoL of older adult women with sarcopenia were influenced by difficulty climbing stairs and working, as well as good perceived health status, healthcare providers should assist elderly women to maintain physical activities in their daily lives. Summary statement

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):328-336

oa_package/dd/b9/PMC10788388.tar.gz

PMC10788389

38204390

Introduction In South Korea (hereafter, Korea), there is a trend towards delayed marriages, resulting in an average age of 33.4 years for first-time mothers in 2021. Furthermore, the percentage of mothers of advanced maternal age, defined as 35 years or older, is 33.8% [ 1 ]. A report from the World Health Organization indicates that mothers aged 35 years and above are at a higher risk of developing gestational diabetes mellitus, pregnancy-induced hypertension, and experiencing premature birth, stillbirth, neonatal death, and congenital malformations compared to women aged 20 to 34 years [ 2 ]. Alongside the increase in advanced maternal age, there has been a significant rise in the number of pregnancies classified as high-risk over the past decade. Specifically, the number has surged nearly sevenfold, from 27,223 cases in 2009 to 145,868 cases in 2018 [ 3 ]. High-risk pregnancies, which pose a threat to the health and life of pregnant women, fetuses, and newborns during pregnancy and childbirth, include factors such as chronic preexisting conditions, advanced maternal age, complications from the current pregnancy, as well as socioeconomic levels, mental health issues, and other considerations [ 4 ]. In high-risk pregnancies, 92.2% of women diagnosed with preterm labor require hospitalization for the sake of the fetus’s well-being [ 5 ]. Even those who receive outpatient care find it challenging to maintain a stable pregnancy, requiring drug therapy and frequent monitoring. This situation can potentially lead both the woman and her partner to experience maladaptive responses to pregnancy [ 6 ]. The often-ambiguous etiology of high-risk pregnancies makes predicting outcomes difficult, and the clarity of treatment results may be compromised [ 7 ]. As a result, high-risk pregnant women face heightened uncertainty as their psychological stability is threatened and stress persists due to concerns about the fetus, anxiety over maintaining the unstable pregnancy, fear of miscarriage, and a lack of information [ 7 ]. However, specialized education and counseling services for these women are limited. Consequently, they may resort to maladaptive coping behaviors, such as self-blame, rumination, and catastrophizing, in response to negative emotional states and uncertain situations [ 8 ]. From a cognitive perspective, coping is recognized as a strategy for regulating emotions, and it is divided into two categories: adaptive coping and maladaptive coping [ 9 ]. Adaptive coping aims to decrease uncertainty and psychological distress in pregnant women, thereby improving their mental health and quality of life (QoL). In contrast, maladaptive coping can lead to increased depression and anxiety, which negatively affects QoL [ 10 ]. Therefore, it is expected that the selection and implementation of appropriate coping strategies will influence the QoL for high-risk pregnant women by maintaining psychological well-being or managing negative emotions [ 9 ]. The factors that influence the QoL for high-risk pregnant women are varied and can have either positive or negative effects. Notable factors that have been reported to significantly impact the QoL for high-risk pregnant women include maternal identity [ 11 ], spousal support [ 12 ], physical symptoms [ 13 ], and depression, anxiety, and fatigue [ 14 ]. These factors represent the physical, mental, and social adaptation levels of the pregnant woman. They can be viewed as the emotional and behavioral characteristics of high-risk pregnant women and are suitable for measurement as an adaptation mode that evaluates individual behavior. However, a review of the literature reveals a gap in research on the QoL and influencing factors for high-risk pregnant women diagnosed with various conditions, as most studies tend to focus on pregnant women with no or minimal health issues [ 15 , 16 ]. Current research on the QoL for high-risk pregnant women has often been limited to specific conditions, neglecting the process-oriented and multifaceted aspects of adaptation while emphasizing physical health and emotional states [ 12 ]. Therefore, from a nursing perspective, it is crucial to gain a comprehensive understanding of the adaptation and QoL of high-risk pregnant women. Identifying relevant factors will provide evidence for nursing interventions aimed at improving their QoL. Research on high-risk pregnancies, guided by Roy’s adaptation theory [ 17 ], has been reported in two international studies. Amanak et al. [ 18 ] examined the influence of this theory on maternal adaptation among women with pregnancy-induced hypertension. Similarly, Widiasih et al. [ 19 ] applied nursing plans and interventions based on the adaptation theory to women experiencing premature rupture of membranes and assessed their impact on these women’s physical and psychological well-being. As pregnancy has been suggested to be a series of responses to individual changes and environmental stimuli [ 20 ]. Roy’s adaptation model [ 17 ] was identified as a suitable theoretical foundation for understanding the QoL of high-risk pregnant women during pregnancy. This theory comprises stimuli, coping mechanisms, adaptation modes, and adaptation. Thus, our model focused on uncertainty, adaptive coping, maladaptive coping, and adaptation modes and the goal of our research was to identify the factors that influence the QoL in high-risk pregnant women. We also aimed to understand the demands related to their QoL. Ultimately, we hope to provide evidence-based data that will help establish intervention strategies to improve the QoL for these women. Purpose The purpose of this study was to construct a hypothetical model explaining QoL in high-risk pregnant women through a literature review of previous studies based on Roy’s adaptation theory [ 17 ], to validate the fit between actual data and the model, and to elucidate the direct and indirect relationships among factors. The specific objectives were as follows: 1) To construct a hypothetical model of QoL in high-risk pregnant women. 2) To validate the fit between the hypothetical model and actual data, presenting a model that explains QoL in high-risk pregnant women. 3) To identify the direct and indirect effects, as well as the total effects, among variables influencing QoL in high-risk pregnant women, thereby confirming the causal relationships among variables. Conceptual framework and hypothetical model of the study The conceptual framework of this study was constructed based on Roy’s adaptation model [ 17 ] and a review of the relevant literature. Roy’s adaptation model posits that humans, as psychosocial beings with physical, emotional, and social dimensions, are at the heart of the adaptation system. Individuals utilize this system to respond and adapt to changes in their environment. Roy and Andrews [ 17 ] define health as the process of becoming an integrated human being. The ultimate goal of nursing, according to this model, is to promote adaptive processes that enhance the interaction between the human system and the environment. This interaction positively impacts health and QoL. In Roy’s adaptation model, stimuli can be internal or external. The outcomes, based on the stimuli input into the individual’s adaptation system and the level of adaptation, are regulated through behavioral responses via cognator and regulator coping processes. The model identifies four modes of adaptation: the physiological mode, self-concept mode, role function mode, and interdependence mode [ 17 ]. These four modes are highly interconnected and act as mediators between the stimuli input into the human system, the coping mechanisms, and adaptation [ 21 ]. The experiences of uncertainty, coping, adaptation mode, and adaptation as perceived by high-risk pregnant women can be understood within the context of Roy’s adaptation theory. In other words, this study views pregnancy as an open adaptive system that is constantly interacting with a changing internal and external environment. High-risk pregnancy, characterized by uncertainty, is seen as stimuli input into this system. The study aims to explain the phenomenon of adaptation to pregnancy through the four modes of adaptation—physiological, self-concept, role function, and interdependence—which are altered through coping. The conceptual framework of this study, based on Roy’s adaptation model is shown in Figure 1 . In this study, high-risk pregnancy is considered as a source of contextual stimuli, as women experience uncertain emotions about maintaining pregnancy and fetal well-being due to the diagnosis of complications related to high-risk pregnancy and a lack of specialized information. This uncertainty is input into our framework. We perceive coping mechanisms as cognitive emotion regulation strategies, where regulatory processes help manage emotions and feelings, thereby influencing psychological well-being. Coping during pregnancy is seen as a combination of adaptive and maladaptive coping. This is viewed as a mechanism that influences the cognitive regulatory processes that high-risk pregnant women use to adapt during pregnancy. This adaptation involves physiological factors, emotional factors, and cognitive regulation processes related to roles and interactions with partners. Adaptation involves four modes. In the physiological mode, the primary demand is physiological integration, taking into account the physical and mental fatigue of high-risk pregnant women [ 22 ]. The self-concept mode is defined as the integration of beliefs about oneself and psychological symptoms at a given point in time [ 20 ]. High-risk pregnant women, compared to low-risk pregnant women, tend to exhibit higher levels of antenatal depression and anxiety related to concerns about maintaining pregnancy and the fetus [ 23 ]. Based on the concept definition of high-risk childbearing adaptation [ 20 ], emotional factors such as antenatal depression and state anxiety are posited to comprise the self-concept mode. The role function mode focuses on the roles individuals occupy in society. High-risk pregnant women, diagnosed with high-risk pregnancy, may experience negative impacts on the process of integrating their identity as mothers, affecting maternal identity acquisition [ 24 ]. Therefore, in this study, we consider the performance of the maternal role and the formation of identity by high-risk pregnant women as factors influencing QoL. The interdependence mode, based on previous research [ 17 ], involves behavioral classifications related to interdependent relationships. In this mode, individuals focus on interactions related to affection, respect, and values. High-risk pregnant women, influenced by spousal support and the quality of marital relationships during pregnancy, are expected to impact their QoL. Therefore, we conceptualize marital adjustment as the interdependence mode. Considering the interrelated nature of these five concepts based on the literature review, we incorporate them into the concept of adaptation used in the model. We define the adaptation level as the QoL to which high-risk pregnant women adapt during pregnancy. Thus, this model focuses on the QoL in high-risk pregnant women. Uncertainty in high-risk pregnant women is established as an exogenous variable, while adaptive coping, maladaptive coping, adaptation mode, and QoL are designated as endogenous variables. The hypothetical model that considers the relationships between these concepts is presented in Figure 2 .

Methods Study design This study used structural equation modeling to construct a hypothetical model explaining QoL in high-risk pregnant women based on Roy’s adaptation model [ 17 ] and previous research. The study is described according to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) reporting guidelines ( http://www.strobe-statement.org ). Participants The selection criteria for this study were primiparous women who were at least 35 years old (advanced maternal age), living with their spouse, had a gestational age between 20 weeks and 37 weeks, and were diagnosed with a high-risk pregnancy by a specialist. The high-risk pregnancy conditions included 19 specific diseases [ 25 ]: preterm labor, postpartum hemorrhage, preeclampsia, premature rupture of membranes, placental abruption, placenta previa, threatened abortion, polyhydramnios, oligohydramnios, antepartum hemorrhage, incompetent internal os of the cervix, pregnancy-induced hypertension, multiple pregnancies, gestational diabetes mellitus, hyperemesis gravidarum, renal disease, heart failure, intrauterine growth restriction, and diseases of the uterus and its appendages. Participants were excluded if they had been diagnosed with cancer or heart disease prior to pregnancy or were currently taking medication for depression. The sample size for this study was determined based on the requirement that 10 to 20 times the number of observed variables is needed for model validation [ 26 ]. Given that there were 20 observed variables in this case, a sample size of at least 300 participants was required. To account for a potential 20% dropout rate, a total of 370 participants were recruited [ 27 ]. After excluding 37 cases (10%) due to unreliable responses, the final study population consisted of 333 participants (100 recruited in person and 233 recruited online), thereby meeting the aforementioned sample size requirements. Study tools Permission to use the measurement tool was obtained through email communication with the tool developers and the authors of the Korean translation before data collection. Adaptation level: Quality of life The Maternal Postpartum Quality of Life Questionnaire (MAPP-QOL), originally developed by Hill and Aldag [ 28 ], and later translated into Korean by Choi et al. [ 29 ], was adapted by our research team to better suit the characteristics of pregnant women. Despite its initial design for postpartum mothers, the questionnaire’s items were found to be relevant to pregnant women, making it an appropriate tool for assessing their QoL. The original 40-item MAPP-QOL comprises five domains: psychological/baby (eight items), socioeconomic (nine items), relational/spouse-partner (five items), relational/family-friends (10 items), and health and functioning (eight items). Modification involved excluding four items specific to postpartum mothers’ experiences: “in the care of the cesarean section or episiotomy site,” “in the assistance with caring for newborns or other children,” “in the time spent with children,” and “in your ability to breastfeed your child.” This modified version underwent a content validity evaluation by three nursing professors and one obstetric nurse. Using a 4-point scale (4, very valid to 1, not valid at all), all items, except one related to “economic ability” with a content validity index below 0.8, were confirmed to have a validity index of 1.0. Subsequently, the modified MAPP-QOL consisted of 35 items across five domains: psychological/baby (eight items), socioeconomic (eight items), relational/spouse-partner (five items), relational/family-friends (seven items), and health and functioning (seven items). The MAPP-QOL assesses the satisfaction and importance of each item on a scale from 1 to 6. According to the scoring method, the total score and subdomain score ranges are calculated, with scores ranging from a minimum of 0 to a maximum of 30 points. A higher score indicates a higher QoL in pregnant women. During its development, the tool demonstrated reliability with a Cronbach’s ⍺ of .96 [ 28 ]; and in this study, the reliability was shown by a Cronbach’s α of .95. The Cronbach’s α values for each subfactor were as follows: psychological/baby, .86; socioeconomic, .87; relational/spouse-partner, .88; relational/family-friends, .85; and health & functioning, .86. Contextual stimuli: Uncertainty Mishel’s Uncertainty in Illness Scale [ 30 ], which was translated into Korean by Chung et al. [ 31 ], was used. This 33-item instrument has four subdomains: ambiguity (13 items), complexity (seven items), inconsistency (seven items), and unpredictability (five items); and an additional item that does not fall within these four subdomains. The scale uses a self-report 5-point Likert scale (1, not at all to 5, very much) and higher scores (possible range, 33–160) indicate a greater level of uncertainty. Cronbach’s α, as a measure of the tool’s reliability, was .91 at the time of its development [ 30 ], and.84 in this study. Coping mechanisms: Coping The Korean version [ 32 ] of the Cognitive Emotion Regulation Questionnaire (CERQ), a cognitive emotion regulation strategy tool developed by Garnefski et al. [ 9 ], was used to measure coping. The CERQ categorizes cognitive coping into nine factors, which are further divided into adaptive coping subfactors, which include putting into perspective, refocusing on planning, acceptance, positive refocusing, and positive reappraisal, and maladaptive coping subfactors, which include self-blame, blaming others, rumination, and catastrophizing. The CERQ consists of 36 items, rated on a 5-point Likert scale (1, almost never, to 5, almost always). Adaptive coping has a possible range of 20 to 100 points, maladaptive coping has a possible range of 16 to 80 points, and each subfactor has a possible range of 4 to 20 points. Higher subfactor scores indicate a higher usage of cognitive strategies. The reliability of the tool, as measured by Cronbach’s α, was .80 at the time of its development [ 33 ] and .86 in this study. The reliability of the subfactors was as follows: putting into perspective, .72; refocusing on planning, .82; acceptance, .62; positive refocusing, .83; positive reappraisal, .78; self-blame, .80; blaming others, .84; rumination, .72; and catastrophizing, .71. Adaptation modes Fatigue This study utilized a score derived from a simplified 10-item fatigue scale. This scale, originally developed by Milligan et al. [ 34 ], was later translated into Korean, modified, and revised by Song [ 35 ]. The tool consists of physical and mental dimensions, each rated on a 4-point Likert scale (1, not at all, to 4, very much). A higher score (possible range, 10–40) signifies a higher level of fatigue. In Song’s study [ 35 ], the Cronbach’s α value was .88, while in this study, it was .86. State anxiety State anxiety was assessed using the State-Trait Anxiety Inventory [ 36 ], which was translated and validated in Korean [ 37 ]. The inventory comprises 20 items, each rated on a 4-point Likert scale (1, not at all, to 4, very much). A higher score (possible range, 20–80) indicates a greater level of state anxiety. The reliability of the inventory was good during its initial development, i.e., Cronbach’s α value of .92 [ 36 ], as well as in this study .92. Antenatal depression The Korean version [ 38 ] of the Edinburgh Postnatal Depression Scale (EPDS) [ 39 ] was utilized to assess antenatal depression which has been confirmed as reliable and valid for antenatal depression as well. The 10-item EPDS assesses depression, anxiety, fear, guilt, and suicidal thoughts. The total score ranges from 0 to 30 points and a cutoff score of 9/10 is used for Korean women, with scores above 10 indicating a higher degree of antenatal depression [ 38 ]. The reliability of the Korean version was good, i.e., Cronbach’s α value of .87 in a prior study [ 38 ], and.81 in this study. Maternal identity Maternal identity scores were derived using a 40-item instrument developed by Kim and Hong [ 40 ]. Twenty items each assess behavioral factors and emotional factors. Each item is rated on a 4-point Likert scale (1, not at all, to 4, very much) and higher scores (possible range, 40–160) suggest a more effective performance of the anticipated maternal role, enhanced interaction between the expectant mother and the fetus, and a positive emotional state [ 40 ]. The tool’s reliability was good, i.e., Cronbach’s α of .92 at development [ 40 ], and .92 in this study. Marital adjustment The Korean adaptation [ 41 ] of the Dyadic Adjustment Scale (DAS) [ 42 ], specifically the abbreviated DAS-10 item version, was used to assess discrepancies between spouses, marital satisfaction, and spousal cohesion [ 41 ]. Of the total score (possible range, 1–51), a cutoff of 32 points is applied, with higher scores signifying greater marital adjustment. In the study conducted by Cho et al. [ 41 ], Cronbach’s α was reported as .83, while in this study, it was found to be .88. General and obstetric characteristics The general characteristics of the participants, such as age, education level, employment status, economic status, and length of marriage, were measured. Obstetric characteristics included gestation period, experience with hospitalization, prenatal education, diagnosis of a high-risk pregnancy, and subjective health status. Data collection Data were collected from October 20, 2021 to February 20, 2022, using both in-person and online methods. The in-person data collection was carried out after explaining the research objectives and securing approval from the directors and nursing staff of two obstetrics and gynecology departments. Posters were displayed in outpatient departments, and the survey took approximately 20 to 30 minutes to complete. Upon completion, each participant placed their questionnaire in a sealed envelope. The collected data were then coded, inputted, and stored in password-protected files. For online data collection, cooperation was obtained from the administrators of a large online community for pregnant women in Korea, known as ‘MomsHolic.’ The researcher posted recruitment posters on the site, and participants who were interested could express their willingness to participate by clicking on a link provided in the research description, as specified by the research administrator. Individual survey links were then sent to these participants for data collection. All participants in the study received a mobile coupon (worth roughly 4 US dollars) as a token of appreciation. Data analysis The data analysis was carried out using IBM SPSS ver. 26.0 and AMOS version 26.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics, including difference tests, correlations, and reliability were done for the participants’ general characteristics and the variables measured. Cronbach’s α was used to assess the reliability of the research instruments. To validate construct validity, model fit, total effects among variables, direct effects, indirect effects, and explanatory power as a structural equation model, we performed exploratory factor analysis and confirmatory factor analysis using the AMOS program. We assessed the normality of the sample through skewness and kurtosis. To check for multicollinearity among the measurement variables, we examined tolerance, variance inflation factor, and Pearson correlation coefficients. The estimation for the structural model assumed multivariate normality and utilized maximum likelihood estimation. We assessed the fit of the hypothesis model using χ 2 , χ 2 /df, goodness of fit index (GFI), standardized root mean square residual (SRMR), root mean square error of approximation (RMSEA), comparative fit index (CFI), the Tucker-Lewis index (TLI), and parsimonious normed fit index (PNFI). To verify the statistical significance of the research model, we used bootstrapping (1,000 iterations) to test the significance of total effects, direct effects, and indirect effects.

Results Differences in quality of life according to participants’ characteristics The mean age of the study participants was 35.29 (±3.72) years, ranging from 26 to 45 years, and the majority (51.1%) were under 35 years old (n=170). Most participants had a college degree (n=299, 89.8%), 58.6% (n=195) reported not having a job, and 39.0% (n=130) had an income of over 6 million Korean won. The mean duration of marriage was 40.33 (±28.01) months, ranging from 3 to 180 months. The participants’ gestational period averaged 28.75 (±4.74) weeks, with 50.5% (n=168) between 20 and 28 weeks and 49.5% (n=165) between 29 and 37 weeks. Among the participants, 35.4% (n=118) reported a history of hospitalization, and 38.1% (n=127) received antenatal education. Regarding high-risk pregnancy diagnoses, 48.6% (n=162) were first-time mothers over 35 years old, followed by 26.1% (n=87) with gestational diabetes mellitus and 21.6% (n=72) with preterm labor. Self-reported health status was perceived as poor by 18.3% (n=61) and average by 46.3% (n=154) ( Table 1 ). Significant differences were observed in the QoL scores based on participant characteristics such as education level, employment status, gestational period, and self-reported health status. Participants who held a college degree demonstrated significantly higher QoL scores (t=–2.53, p =.012). Similarly, those who were employed also had significantly higher scores compared to those who were not (t=2.92, p =.004). Participants at 20 to 28 weeks of gestation had higher QoL scores (t=2.50, p =.013). Furthermore, participants who reported a good subjective health status had significantly higher QoL scores (F=16.89, p <.001) ( Table 1 ). Descriptive statistics and verification of the study variables’ validity The mean total score for QoL was 18.63 (±3.80), indicating an above-average level. The subscale scores were as follows: psychological/baby, 19.03 (±4.48); socioeconomic, 19.00 (±4.60); relational/spouse-partner, 20.99 (±4.58); relational/family-friends, 19.18 (±4.78); and health & functioning, 16.18 (±4.19). Among these, the relational/spouse-partner subscale had the highest score, while health & functioning had the lowest. Uncertainty had a mean score of 91.60 (±14.29), indicating an above-average level. Adaptive coping had a mean score of 79.39 (±10.31), with the following sub-scores: perspective scoring, 15.70 (±2.73); refocus on planning, 16.73 (±2.34); acceptance, 15.88 (±2.22); positive refocusing, 14.94 (±3.06); and positive reappraisal, 16.14 (±2.52). Maladaptive coping had a mean score of 47.32 (±9.63), with the following sub-scores: self-blame, 12.68 (±2.74); blaming others, 9.72 (±3.38); rumination, 13.23 (±3.20); and catastrophizing, 11.69 (±3.31). Fatigue had a mean score of 27.67 (±5.73), state anxiety had a mean score of 44.65 (±10.49), and antenatal depression had a mean score of 10.54 (±5.11), with 57.6% (n=192) scoring 10 or higher. Maternal identity had a mean score of 126.51 (±16.35), and marital adjustment had a mean score of 38.19 (±6.10), both indicating above-average levels ( Supplementary Table 1 ). The correlation coefficient values between the measured variables ranged from r =–.01 to .75, suggesting no issues with multicollinearity ( r >±.90). The variance inflation factors varied from 1.51 to 3.84, all of which were below 10, further indicating no multicollinearity between the measured variables. The average variance extracted for the latent factors in this study ranged from .61 to .94, all-surpassing 0.5, and the composite construct reliability exceeded 0.6, thereby confirming both convergent and discriminant validity ( Supplementary Table 1 ). Upon examining the assumption of multivariate normality for the structural equation model, a multivariate kurtosis index of 69.092 was found, which violated the normality assumption. As a result, the most commonly used maximum likelihood estimation was selected for parameter estimation, and bootstrapping, a beneficial method for analyzing data that deviates from multivariate norms, was chosen. Verification of the fit of the hypothetical model Results of the testing and modification of the hypothetical model The test results of the hypothetical model revealed that the absolute fit indices (χ 2 =405.07, χ 2 /df=3.94, GFI=.90, SRMR=.11, RMSEA=.09), the incremental fit indices (CFI=.92 and TLI=.90), and the parsimonious fit index (PNFI=.90), did not fully satisfy the recommended criteria for absolute fit indices—specifically, this was the case for χ 2 , χ 2 /df, SRMR, and RMSEA. To improve the model fit, we conducted explorations of the relationships between variables and their theoretical foundations. Drawing on previous research that suggests a direct impact of coping on QoL [ 43 ], we added two paths to the hypothetical model: one from adaptive coping to QoL, and another from maladaptive coping to QoL. The final modified model showed adequate absolute fit indices (χ 2 =261.11 [<.001], χ 2 /df=2.69, GFI=.93, SRMR=.05, and RMSEA=.07), incremental fit indices (CFI=.95 and TLI=.91), and parsimonious fit index (PNFI=.47). These results met the adequacy criteria for both the absolute fit indices and the incremental fit indices ( Table 2 ). Results of the effect analysis in the modified model In the modified model’s estimated paths, six out of seven total paths were found to be statistically significant. The coping model revealed significant paths from uncertainty to both adaptive coping (β=–.26, p =.006) and maladaptive coping (β=.68, p =.014). Similarly, in the adaptation mode model, both adaptive coping (β=–.44, p =.018) and maladaptive coping (β=.69, p =.012) demonstrated significant paths. Lastly, in the final QoL model, the adaptation mode (β=–.81, p =.034) and maladaptive coping (β=.46, p =.043) were identified as significant paths. The variable that most significantly influenced the QoL in high-risk pregnant women was the adaptation mode. Both direct and indirect effects were significantly demonstrated by maladaptive coping, while uncertainty showed a significant indirect effect. These factors had an explanatory power of 51%. The variable that had the most profound impact on the adaptation mode in high-risk pregnant women was maladaptive coping. Maladaptive coping displayed a significant direct effect, whereas uncertainty showed a significant indirect effect. These factors exhibited an explanatory power of 79%. Uncertainty in high-risk pregnant women significantly directly affected both adaptive and maladaptive coping. Adaptive coping had an explanatory power of 7%, while that of maladaptive coping was 47% ( Figure 3 , Table 3 ).

Discussion This study constructed a hypothetical model based on Roy’s adaptation theory [ 17 ] and informed by concepts from literature reviews, to elucidate the QoL in high-risk pregnant women. We then tested the model’s adequacy and the significance of its pathways using a sample of 333 high-risk pregnant women. Factors that explained the QoL demonstrated direct effects for adaptation mode and maladaptive coping, and indirect effects for uncertainty, adaptive coping, and maladaptive coping. The results of this study prompt a discussion on variables associated with the QoL in high-risk pregnant women and the implications for their nursing care. Of the primiparous women diagnosed with high-risk pregnancies, their. Approximately half of these high-risk pregnant women were over 35 years old, which is considered advanced maternal age. In 2018, the rate of advanced maternal age pregnancies in Korea was reported to be 31.8% [ 3 ]. The higher rate in this study may be due to the deliberate self-selection of high-risk pregnant women of advanced maternal age. Preterm labor is often reported as a common health issue in high-risk pregnancies [ 4 ]. The high incidence of gestational diabetes mellitus in this study is likely due to the fact that the participants were recruited from outpatient obstetrics and gynecology clinics. Among the participants, 118 (35.4%) had a history of hospitalization, which reflects the efforts of high-risk pregnant women to prevent adverse outcomes related to preterm labor [ 6 ]. However, this could also contribute to an increased burden of pregnancy and uncertainty about the prognosis compared to women with low-risk pregnancies. The percentage of participants who reported poor subjective health status was 18.3%, which is slightly higher than the 16.8% reported for hospitalized high-risk pregnant women [ 44 ] and similar to the 18.4% reported for high-risk pregnant women receiving outpatient care [ 45 ]. When compared to the 15.4% reported in a study on women with low-risk pregnancies [ 46 ], it is clear that women diagnosed with high-risk pregnancies tend to perceive their health status more negatively, regardless of whether they are receiving outpatient or inpatient treatment. The results of this study revealed that the QoL score for high-risk pregnant women averaged 18.63 out of 30 points. This score is comparable to the 18.94 average score of participants who were hospitalized due to preterm labor [ 14 ]. Although it was difficult to find studies using the same tool for direct comparison with low-risk pregnant women, the score was lower than that of mothers without prenatal complications, who averaged 19.64 points [ 47 ]. This suggests that the QoL for high-risk pregnant women may be lower than that for low-risk pregnant women. This conclusion aligns with the findings of systematic literature review studies [ 48 ], which indicate that the QoL for high-risk pregnant women is indeed lower compared to their low-risk counterparts. These results underscore the necessity for medical care and intervention strategies that are specifically designed for the unique circumstances of high-risk pregnant women, going beyond standard therapeutic interventions and health maintenance. Although the initial hypothetical model did not meet the recommended standards, modifications were made to confirm the final model. This revised model achieved the recommended levels with a chi-square to degrees of freedom ratio of 2.69, and both SRMR and RMSEA were below 0.08. GFI, CFI, and TLI values all exceeded 0.90, indicating a good fit [ 26 ]. The modified model demonstrated that factors such as uncertainty, adaptive coping, maladaptive coping, and adaptation mode in high-risk pregnant women accounted for their QoL. Conversely, a structural model study on the health-related QoL in low-risk pregnant women [ 49 ] identified sleep quality, physical activity, and perceived health status as explanatory factors. This highlights the differences in factors that explain the QoL in pregnant women, depending on their risk status. The uncertainty score for participants in this study (91.60 points) was comparable to the score of 97.31 observed in pregnant women hospitalized due to high-risk pregnancies [ 50 ]. Given that the participants in this study were diagnosed with high-risk pregnancies and were receiving both outpatient and inpatient care, the heightened uncertainty can likely be attributed to their high-risk pregnancy diagnosis. This study reinforces the idea that uncertainty influences coping strategies, leading to a decrease in adaptive coping and an increase in maladaptive coping [ 7 ]. However, it was observed in this study that high-risk pregnant women tended to rely more on maladaptive coping than adaptive coping to manage the negative emotions triggered by the high-stress situation of a high-risk pregnancy. This observation is consistent with research that suggests an increase in uncertainty leads to a decrease in adaptive coping and an increase in maladaptive coping [ 51 ]. Moreover, high-risk pregnant women perceived uncertainty as contextual stimuli, which negatively affected their QoL. This finding is in line with research that proposes high levels of uncertainty can cause high-risk pregnant women to harbor negative thoughts about their lives, making it challenging for them to actively cope, and potentially leading to maladaptive outcomes during pregnancy [ 22 ]. The adaptation mode of the participants in this study was analyzed in terms of fatigue, state anxiety, antenatal depression, maternal identity, and marital adjustment. The fatigue score (27.67 points) was comparable to the score of 27.78 points observed in low-risk pregnant women during the later stages of pregnancy [ 52 ]. However, the state anxiety score for high-risk pregnant women (44.62 points) was 1.5 times higher than the score of 29.20 points seen in low-risk pregnant women [ 53 ]. Moreover, the antenatal depression score was 10.54 points, 1.7 times higher than the score of 6.12 points for low-risk pregnant women [ 54 ], suggesting the presence of mild depressive symptoms. The maternal identity score was 126.51 points, lower than the score of 131.15 points for low-risk pregnant women [ 55 ] and comparable to the score of 127.80 points for pregnant women with gestational diabetes mellitus [ 56 ]. This implies that high-risk pregnant women may face challenges in attachment behavior and transitioning to motherhood compared to their low-risk counterparts. The marital adjustment score (38.19 points) was lower than the score of 41.06 points for low-risk pregnant women [ 54 ], suggesting less stability and satisfaction in the marital lives of high-risk pregnant women. If marital relationships are unsatisfactory, it may lead to negative emotions in pregnant women and adversely affect their QoL. Therefore, it is important to understand and consider the aspect of marital adjustment in high-risk pregnant women. Upon examining the factors in the model, it was observed that uncertainty in high-risk pregnant women indirectly impacted their QoL. A study on breast cancer patients reported a significant indirect effect [ 57 ], but additional repetitive research is required to confirm the indirect factors of uncertainty that affect the QoL in high-risk pregnant women. Adaptive coping demonstrated a significant indirect effect, while maladaptive coping was found to have significant direct and indirect effects on the QoL. Considering that adaptive coping is employed to effectively manage physical and emotional well-being, providing information on stress management techniques and high-risk pregnancy could assist in promoting adaptive coping strategies [ 7 ]. Maladaptive coping, a strategy often used by high-risk pregnant women [ 51 ], can intensify negative psychological issues such as anxiety and depression, and hinder the transition to motherhood. Therefore, it is vital to help these women reduce their reliance on such strategies. The adaptation mode was found to have a significant direct effect on the QoL. In this study, the adaptation mode, which includes physiological indicators like fatigue and self-concept indicators such as anxiety and depression, showed a negative correlation with the QoL. Role function indicators like maternal identity and interdependence indicators such as marital adjustment also exhibited a static correlation with the QoL. These findings suggest that the adaptation mode of high-risk pregnant women operates in a mutually related manner, exerting a negative direct effect on the QoL and thus reducing it. This highlights the necessity for a comprehensive perspective on how individuals adapt to various stimuli in their lives. Although the participants experienced high levels of uncertainty, fatigue, anxiety, and depression, their QoL remained above average. This can be attributed to the positive indirect effect of adaptive coping strategies, which were mediated by the adaptation mode. Additionally, the direct effect of maladaptive coping strategies also influenced QoL. This finding is consistent with previous research suggesting that the QoL in high-risk pregnant women is significantly influenced by their coping strategies [ 12 ]. Consequently, it is recommended that nursing interventions be planned to enhance adaptive coping and reduce maladaptive coping strategies, as this could improve QoL for high-risk pregnant women. This study has several limitations, including the use of both in-person and non-in-person data collection methods. The in-person data collection was restricted to outpatient women in a single region, who were recruited through convenience sampling. As such, care should be taken when extrapolating the results of this study to all high-risk pregnant women. The QoL was found to be lower in participants who were high school graduates, unemployed, between 29 and 37 weeks of gestation, and those who reported poor subjective health. However, these factors were not included in the model, so caution is necessary when interpreting the research results. High-risk pregnant women have varying risk factors depending on the type of complication and gestational period. Therefore, it is crucial to analyze changes and causal relationships over time among the various factors that affect QoL. We recommend conducting follow-up studies using longitudinal research to verify the model’s effectiveness in determining the time series effects on QoL throughout pregnancy. In conclusion, this study provided foundational data for the development of nursing interventions aimed at enhancing the QoL for high-risk pregnant women, drawing on Roy’s adaptation theory. It takes into account a range of factors—physical, psychological, social, and environmental—that could potentially impact the QoL of these women. The study identifies significant direct and indirect pathways among factors related to QoL, underscoring the crucial role of uncertainty management in nursing interventions. It also highlights the importance of encouraging adaptive coping strategies and minimizing the use of maladaptive ones, to help high-risk pregnant women adapt and improve their QoL. As findings established the influence of coping mechanisms on QoL in high-risk pregnant women, ongoing education and counseling are essential in clinical environments to help these women adjust to pregnancy and employ adaptive coping strategies, rather than resorting to maladaptive ones. For those high-risk pregnant women who exhibit a low capacity for adaptive coping or a propensity to over-rely on maladaptive coping, the implementation of cognitive-behavioral interventions could enhance their QoL and facilitate their adjustment to pregnancy.

This article is based on the doctoral dissertation of the first author (Mihyeon Park) from Chungnam National University. Purpose This study aimed to develop and validate a structural model for the quality of life (QoL) among high-risk pregnant women, based on Roy’s adaptation model. Methods This cross-sectional study collected data from 333 first-time mothers diagnosed with a high-risk pregnancy in two obstetrics and gynecology clinics in Cheonan, Korea, or participating in an online community, between October 20, 2021 and February 20, 2022. Structured questionnaires measured QoL, contextual stimuli (uncertainty), coping (adaptive or maladaptive), and adaptation mode (fatigue, state anxiety, antenatal depression, maternal identity, and marital adjustment). Results The mean age of the respondents was 35.29±3.72 years, ranging from 26 to 45 years. The most common high-risk pregnancy diagnosis was gestational diabetes (26.1%). followed by preterm labor (21.6%). QoL was higher than average (18.63±3.80). Above-moderate mean scores were obtained for all domains (psychological/baby, 19.03; socioeconomic, 19.00; relational/spouse-partner, 20.99; relational/family-friends, 19.18; and health and functioning, 16.18). The final model explained 51% of variance in QoL in high-risk pregnant women, with acceptable overall model fit. Adaptation mode (β=–.81, p =.034) and maladaptive coping (β=.46 p =.043) directly affected QoL, and uncertainty (β=–.21, p =.004), adaptive coping (β=.36 p =.026), and maladaptive coping (β=–.56 p =.023) indirectly affected QoL. Conclusion It is essential to develop nursing interventions aimed at enhancing appropriate coping strategies to improve QoL in high-risk pregnant women. By reinforcing adaptive coping strategies and mitigating maladaptive coping, these interventions can contribute to better maternal and fetal outcomes and improve the overall well-being of high-risk pregnant women. Summary statement

Supplementary materials Further details on supplementary materials are presented online (available at https://doi.org/10.4069/kjwhn.2023.11.13.1 ).

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):302-316

oa_package/82/2c/PMC10788389.tar.gz

PMC10788390

38204386

Background Approximately 36% of all cancer patients in Korea receive radiotherapy, a key modality of cancer treatment alongside surgery and chemotherapy. Diverse therapeutic techniques have resulted from advances in radiological technology and treatment devices, contributing to the improvement of the quality of treatment and patients’ quality of life. According to 2022 data from the Korea Institute of Radiological Medical Sciences, 7.8% of female patients who underwent radiotherapy in 2019 received treatment for gynecologic cancer. Notably, approximately 98% of brachytherapy procedures were conducted to treat gynecologic cancer [ 1 ]. Radiotherapy for gynecologic cancer, which can involve both teletherapy and brachytherapy, plays a pivotal role in improving treatment outcomes because it targets not only the early stages of the cancer but also advanced lesions for radical, adjuvant, and palliative purposes. This article explores recent developments in radiotherapy, with a particular focus on radiotherapy for gynecologic cancer, and discusses acute and chronic adverse events that may occur during treatment, as well as interventions.

Conclusions As radiotherapy techniques for gynecologic cancer become increasingly sophisticated and varied, the role of radiotherapy in cancer treatment is expanding. While the primary focus used to be on treatment outcomes, there is now a growing interest in the various issues experienced during the cancer survival period posttreatment, as well as symptom management during treatment. Despite the rising demand for care in tumor treatment, very few nursing curricula in Korea include education on radiotherapy, particularly the knowledge necessary for radiation oncology practice. Therefore, consistent efforts are needed to provide updated evidence-based practice, not only in clinical care but also in education.

Latest trends in radiotherapy Radiotherapy aims to maximize treatment effectiveness and minimize side effects by primarily irradiating tumor tissues and limiting radiation exposure to the surrounding normal tissues. Radiotherapy technology has advanced dramatically over the last 20 years, and the effectiveness of concomitant chemoradiotherapy treatment has been proven in a substantial number of studies as presented in a recent systematic review [ 2 ]. Radiotherapy initially involved treatment in a flat, two-dimensional (2D) plane based on 2D imaging centered around tumors. Subsequently, three-dimensional (3D) conformal radiotherapy became available; this method models tumors and the surrounding tissues in three dimensions using computed tomography and magnetic resonance imaging, enabling more precisely targeted treatment. High-precision radiotherapy procedures, such as intensity-modulated radiotherapy (IMRT), respiratory-gated radiotherapy, image-guided radiotherapy, and stereotactic radiotherapy, emerged in the 2000s. Active research is currently underway in the field of concomitant chemoradiotherapy, which combines radiotherapy with cancer immunotherapy [ 3 ]. Furthermore, particle therapies using protons and heavy ion particles, which are recognized for their higher treatment effectiveness and fewer side effects compared to traditional high-energy X-ray therapies listed above, have gained attention in recent years [ 4 , 5 ] ( Figure 1 ). Both therapies utilize subatomic particles, and their utility is based on the ‘Bragg peak,’ a phenomenon where particles penetrate normal tissues in the human body and emit radiation energy only at specific depths where tumor tissues are found [ 6 ] ( Figure 1 ). However, cost-effectiveness should be carefully considered when choosing a treatment modality, since radiotherapy using X-rays has favorable treatment outcomes for gynecologic cancer, while particle therapy is currently offered only at three medical institutions in Korea and heavy ion particle therapy is not covered by insurance. Gynecologic cancer is unlike other malignancies in that it often requires brachytherapy, which involves intravaginal insertion of devices, and the placement of isotopes close to the lesion for treatment, in combination with teletherapy. The advantages of brachytherapy include the delivery of a high dose of radiation due to the proximity of the equipment to the treatment area and the minimization of effects on normal tissues in the bladder and rectum [ 7 , 8 ] ( Figure 2 ). Data reported in 2021, however, showed that the availability of brachytherapy decreased from 84% in 2005 to 78% in 2013 in Korea and the number of medical institutions that offer brachytherapy also declined from 65% in 2006 to 36.8% in 2014 [ 9 ]. Since it is impossible to maintain facilities for brachytherapy available due to low medical reimbursements and challenges in equipment management, patients are often referred to other institutions. Patient care by radiotherapy for gynecologic cancer Unlike chemotherapy, most symptoms related to radiotherapy occur locally in the treatment area and are affected by the method, area, dose, and duration of treatment, as well as the patient’s general condition. In general, radiotherapy for gynecologic cancer involves irradiating the pelvis, and the treatment area can be expanded to the upper abdomen if the paraaortic lymph nodes are included in the treatment. Gastrointestinal symptoms, micturition, and genital disorders can occur due to the treatment. While most symptoms improve substantially within 6 months after the end of treatment, some patients suffer prolonged discomfort due to the persistence of these symptoms [ 10 ]. Gastrointestinal complications Gastrointestinal symptoms caused by radiotherapy for gynecologic cancer include diarrhea, nausea, vomiting, tenesmus, and rectal bleeding. Approximately 30% of patients who undergo pelvic radiotherapy experience acute enteritis accompanied by diarrhea. In 10% of these patients, the symptom persists even after 5 years after treatment completion [ 10 ]. A study that compared existing 3D conformal radiation therapy (CRT) and IMRT reported that grade 3 or more severe diarrhea [ 11 ] occurred significantly more frequently in the 3D CRT group than in the IMRT group (30.6% vs. 5.6%) [ 12 ]. Therefore, IMRT has become the more widely used procedure. Common approaches to acute enteritis include fiber products, antidiarrheal agents, and the supply of fluids and electrolytes through intravenous hydration. For malabsorption due to chronic enteritis, the use of vitamin B12 and cholestyramine for bile salt malabsorption can be actively considered [ 13 ]. Anti-inflammatory agents, intestinal protectants, intestinal antimotility agents, and probiotics are generally used for acute radiation proctitis [ 14 ], and if rectal bleeding persists, endoscopic treatment, such as a sucralfate enema or argon-plasma coagulation, may be required [ 15 , 16 ]. Genitourinary complications The bladder and ureter are inevitably exposed to radiation due to their close proximity to organs affected by gynecologic cancer. In the GOG-99 study, low-grade genitourinary toxicity was reported in approximately 43% of patients following radiotherapy after endometrial cancer surgery [ 10 ]. Symptoms include frequent urination, dysuria, and rarely, hematuria. When these symptoms occur, urinalysis and culture tests are conducted to determine whether the patient has an infection, and medication is then prescribed. If infection is ruled out, ibuprofen and phenazopyridine may be helpful for frequency, and anticholinergics can be helpful for urgency [ 10 ]. If oral medications are not effective, the cystoscopic injection of botulinum toxin A can be attempted [ 17 ]. For hemorrhagic cystitis, which can occur chronically, laser fulguration of ectatic vessels, intravesical alum or formalin, or hyperbaric oxygen may be considered [ 18 ]. Urethral strictures, which may occur in less than 5% of patients, can be addressed by endoscopic dilation or stent placement. While vesicovaginal fistulas are typically managed through simple fulguration and catheter drainage, they sometimes require open surgical repair [ 19 ]. Sexual dysfunction The most frequent complications experienced by gynecologic cancer patients who have undergone pelvic radiotherapy are vaginal stenosis and diminished ovarian function in premenopausal women. These complications can lead to challenges in sexual relationships due to dyspareunia and reduced vaginal discharge, resulting in negative effects on women’s quality of life. The incidence of vaginal strictures due to radiotherapy varies from 1.2% to 88%, depending on the patient’s personal characteristics, treatment method, and dose. Vaginal strictures occur in 50% or more of patients within 3 years after the completion of treatment [ 20 ] ( Figure 3 ). In general, patients undergoing pelvic radiotherapy often experience menopause within 6 months after completing treatment. To alleviate the symptoms of menopause, oral progesterone and/or estrogen with a serotonin-specific reuptake inhibitor can be administered. Vaginal dilators are commonly employed as a treatment for vaginal strictures. Patients are advised to use these dilators for a duration of 10 to 15 minutes, 2 to 3 times per week, for a period of 3 to 12 months posttreatment ( Figure 4 ). In contrast to the past, there is now a rising demand to address sexual issues alongside physical symptoms, with a growing interest in maintaining functionality. Therefore, several models are being proposed to aid in sexual assessment and interventions [ 21 ] ( Table 1 .). Hematologic toxicity High-dose radiotherapy causes chronic myelosuppression and damage to the bone marrow microenvironment, potentially affecting the effectiveness of chemotherapy. A study reported that acute grade 3 (Common Toxicity Criteria version 2.0, National Cancer Institute) or more severe leukopenia occurred in 81% of patients undergoing cisplatin-based pelvic chemoradiotherapy, which included expanded coverage of the para-aortic lymph nodes or common iliac lymph nodes [ 22 ]. Hence, it is necessary to monitor the neutrophil, platelet count, and hemoglobin levels through weekly blood tests. Active interventions should also be implemented, including assessing the risk of infection, based on the severity of the condition. Dermatologic toxicity Most skin reactions to gynecologic cancer radiotherapy are grades 1 to 2, but moderate or more severe skin reactions (grading criteria for radiodermatitis by the Radiation Therapy Oncology Group) are observed in up to 95% of patients with vulvar cancer [ 23 ]. Mild erythema may occur in the vulva, perineum, and inguinal and gluteal folds about 2 to 3 weeks after pelvic teletherapy, and this can be alleviated by using a topical moisturizer. Vulvar cancer patients often have white plaques covering their skin due to the overgrowth of Candida . Wearing loose-fitting, cotton clothing, avoiding heat, and using 1% hydrocortisone cream if pruritis is present may help alleviate this symptom. Late dermatologic effects include hyperpigmentation or hypopigmentation, as well as telangiectasis and textural changes. Lymphatic system dysfunction Lower-extremity lymphedema is a chronic disease that may develop after the treatment of gynecologic cancer. This condition may occur if pelvic lymph nodes are included in the scope of radiotherapy after pelvic lymph node dissection during surgery. It is of the utmost importance to detect and address lymphedema early, as it can be irreversible depending on its severity. The initial assessment often relies on self-reports; thus, it is essential that patients receive prior education on lymphedema. This education should cover prevention strategies, measurement techniques, and methods for massaging the lymph nodes. Radiation oncology nurses play a crucial role in addressing the side effects caused by radiotherapy in clinical practice. Hence, they should be able to predict the likelihood of treatment-related adverse events based on a fundamental understanding of radiotherapy. They should also be educated in advance on how patients and their caregivers can respond to changes and self-manage, in addition to providing direct nursing interventions for adverse events. Furthermore, they should conduct evidence-based assessments, be knowledgeable of symptom management, and share the information with their teammates as part of a multidisciplinary approach. The role of radiation oncology nurses as patients’ supporters and educators will make a significant contribution to improving treatment adherence among patients undergoing radiotherapy.

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):257-262

oa_package/b2/54/PMC10788390.tar.gz

PMC10788391

38204391

Introduction The human papillomavirus (HPV), which is primarily transmitted through sexual contact, has been recognized as a significant cause of cervical cancer [ 1 ]. To date, more than 200 types of HPV have been identified [ 2 ], with high-risk strains such as HPV-16 and HPV-18 being strongly linked to genital cancers, especially cervical cancer [ 3 ]. According to data from the Korea Central Cancer Registry in 2022 [ 4 ], cervical cancer constituted 1.2% of all cancer cases in Korea in 2020, ranking as the 10th most common cancer among women. The 2021 Cancer Trends Report from the National Cancer Center [ 5 ] indicates that each year, over 3,000 Korean women are diagnosed with cervical cancer, leading to approximately 900 deaths. Over 95% of these cancers have been connected to HPV [ 6 ], and nearly 100% of invasive cervical cancer cases are associated with HPV infection [ 7 ]. Preventive behavior refers to actions taken by individuals who perceive themselves to be healthy in order to detect or prevent disease before symptoms appear [ 8 ]. It is of the utmost importance to increase the intention to engage in cervical cancer preventive behavior among HPV-infected women. HPV vaccination and regular screening are essential preventive measures against cervical cancer [ 9 ]. The vaccine is effective in preventing new HPV infections, even after initial exposure, but it cannot cure existing infections or related diseases [ 6 ]. It is also important to avoid smoking, which is a known risk factor, and to be cautious with long-term use of oral contraceptives, as they can increase the risk of cervical cancer by 1.2 to 1.5 times [ 9 ]. Additionally, limiting the number of sexual partners and consistently using condoms during intercourse are recommended [ 1 ]. Research has indicated that various factors, including perceived benefits and the severity of health beliefs related to vaccination, contraceptive use, and HPV testing experience, enhance cervical cancer prevention behaviors among nurses [ 10 ]. A study focusing on nursing students found that those with a higher intention to engage in cervical cancer preventive behavior were more likely to participate in cervical cancer screening [ 11 ]. Furthermore, research involving Korean women in their 20s revealed that more conservative sexual attitudes were associated with increased preventive behavior [ 12 ]. In a study on female university students, higher levels of self-efficacy and fear were associated with a stronger intention to engage in preventive behavior [ 13 ]. Providing information about cancer to foster positive attitude changes has been shown to be an effective strategy for promoting the practice of cervical cancer prevention behaviors [ 14 ]. Research indicates that greater knowledge about cervical cancer is associated with more consistent engagement in preventive behavior [ 15 ]. However, despite the importance of intending to engage in such behaviors, adult Korean women generally possess limited knowledge about the disease. For instance, only 41.7% are aware of the connection between HPV infection and cervical cancer [ 16 ], and even nurses’ understanding of HPV is notably deficient [ 10 ]. Women who test positive for HPV often experience significant anxiety and uncertainty due to the associated risk of developing cervical cancer [ 17 ]. This anxiety extends to concerns about the potential effects on pregnancy and childbirth [ 18 ]. Studies involving gastric cancer and hemodialysis patients have demonstrated that uncertainty can influence the intention to engage in preventive behavior, with greater uncertainty correlating with a reduction in health-promoting actions [ 19 ]. Additionally, hemodialysis patients tend to show lower adherence to prescribed sick role behaviors when they face greater uncertainty and have a more serious perception of their illness [ 20 ]. However, research has yet to explore the impact of uncertainty on the intentions of HPV-infected women to engage in preventive behavior. Self-efficacy is a critical factor in increasing the intention to engage in preventive behavior [ 21 ]. It influences not only health-promoting actions but also acts as an essential bridge between knowledge and behavior [ 22 ]. Elevated self-efficacy is associated with improved health behaviors, and interventions designed to boost self-efficacy can lead to positive behavioral modifications, ultimately enhancing health outcomes [ 23 ]. Moreover, heightened self-efficacy correlates with more regular participation in cervical cancer prevention behaviors [ 24 ] and has been recognized as a mediator in developing the intention to prevent cervical cancer [ 13 ]. Therefore, this study aimed to assess the levels of cervical cancer and HPV knowledge, self-efficacy, and uncertainty in HPV-infected women, as well as their effects on the intention to engage in cervical cancer preventive behavior. The goal was to provide foundational data that could inform the development of programs to improve the intention of HPV-infected women to engage in cervical cancer preventive behavior. The purpose of this study was to identify factors influencing HPV-infected women’s intention to engage in cervical cancer preventive behavior. These behaviors are defined as voluntary and diligent actions aimed at cancer prevention. The study had the following specific aims: first, to investigate how participants’ characteristics influence their intention to engage in cervical cancer preventive behavior; second, to assess levels of intention, cervical cancer knowledge, HPV knowledge, self-efficacy, and uncertainty among participants; third, to identify correlations between these variables and preventive behavior intention; and fourth, to determine the factors that influenced participants’ intentions to engage in such behaviors.

Methods Research design The purpose of this descriptive correlational study was to identify factors influencing the intention to engage in cervical cancer preventive behavior among women infected with HPV. This study adhered to the STROBE reporting guidelines ( https://www.strobe-statement.org/ ). Participants This study enrolled adult women between the ages of 20 and 65 years who tested positive for HPV at the obstetrics and gynecology department of a general hospital in Changwon, Korea. Participants were selected through convenience sampling and included those who could communicate in Korean, understood and consented to the study’s objectives, and were reachable within one week of receiving their HPV test results. Women diagnosed with carcinoma in situ or cervical cancer were excluded from the study. The required sample size was calculated using G*Power 3.1.9.2, based on a previous study [ 25 ]. The parameters set for the calculation included a significance level of .05, a medium effect size of .15, a power of 80%, and nine predictors: cervical cancer knowledge, HPV knowledge, uncertainty, self-efficacy, smoking, age at first sexual intercourse, number of sexual partners, condom use, and HPV vaccination. The calculation indicated that a sample size of 114 would be sufficient for multiple regression analysis. To account for a potential 20% dropout rate, the study aimed to enroll 143 participants. Ultimately, the final analysis was conducted on 129 cases after excluding 14 responses deemed inadequate. Instruments All tools in this study were used after receiving approval via e-mail from the corresponding developer and translator. A structured questionnaire with 99 items was used, covering topics such as the intention to engage in cervical cancer preventive behavior, cervical cancer knowledge, HPV knowledge, uncertainty, self-efficacy, and both general and HPV-related characteristics. Intention to engage in cervical cancer preventive behavior The intention to engage in cervical cancer preventive behavior was assessed using a tool developed by Ko [ 26 ], drawing on the study of Yoo et al. [ 27 ] on the intention to prevent novel flu and Han’s research [ 28 ] on early cancer screening promotion messages targeting Korean and Japanese women aged 30 to 59 years. This instrument consists of six items, each addressing a distinct aspect of cervical cancer prevention: seeking information about prevention, consulting with a physician, undergoing regular screenings, recommending screenings to others, getting vaccinated, and advocating for HPV vaccination for others. Responses are measured on a 5-point Likert scale, ranging from 1 (“strongly disagree”) to 5 (“strongly agree”), where higher scores reflect a stronger intention to engage in preventive behavior. For this study, the mean scores were calculated, with possible values ranging from 1 to 5. The tool demonstrated high reliability, with Cronbach’s α of .88 in the initial study [ 10 ] and .81 in the current study. Cervical cancer knowledge Cervical cancer knowledge was assessed using a tool modified and expanded by Kim and Park [ 29 ], based on the study of Lee and Lee [ 30 ]. This instrument comprises eight items: four addressing the risk factors for cervical cancer, one regarding its incidence, one concerning symptoms, one related to diagnosis, and one about prognosis. Responses were categorized as “true,” “false,” or “do not know.” Correct responses were awarded 1 point, while incorrect or “do not know” answers received no points. A higher aggregate score, ranging from 0 to 8, reflected a more comprehensive understanding of cervical cancer. At the time of its development, the tool demonstrated a Cronbach’s α of .83 [ 29 ], and in this study, the Kuder-Richardson Formula 20 (KR-20) reliability coefficient was .61. Human papillomavirus knowledge HPV knowledge was assessed using a 20-item tool developed by Kim and An [ 31 ]. This tool encompasses a range of topics, including the association between HPV and cervical cancer, symptoms of HPV, the distinction between low-risk and high-risk types, correlations with latency periods, prognosis, and immunity, the ages at which HPV is most prevalent, modes of transmission, methods of examination and diagnosis, strategies for prevention and treatment, and the risk of congenital infections. The scoring approach mirrored that of the cervical cancer knowledge assessment, with scores ranging from 0 to 20, where higher scores indicated a more comprehensive understanding of HPV. The reliability of the instrument at the time of its development [ 31 ] was reflected by a Cronbach’s α of .87, and in the current study, the KR-20 reliability coefficient was .84. Uncertainty The Mishel Uncertainty in Illness Scale Community Form (MUIS-C) [ 32 ], as translated by Chung et al. [ 33 ], was utilized to measure uncertainty. This instrument comprises 23 items categorized into four subdomains: ambiguity, complexity, inconsistency, and unpredictability. Respondents rate each item using a 5-point Likert scale, where 1 signifies “not at all” and 5 indicates “very much.” Higher scores denote increased uncertainty. In the analysis, average scores were calculated, with possible values ranging from 1 to 5. The MUIS-C’s original reliability was reported with Cronbach’s α values ranging from .91 to .93 [ 32 ]; Cronbach’s α was .85 in the study by Chung et al. [ 33 ], and it was .82 in the current study. Self-efficacy Self-efficacy was measured using a Korean version of a 24-item health management self-efficacy scale, which was translated and subjected to factor analysis by Lee et al. [ 34 ]. This adapted version originated from the 28-item scale developed by Becker et al. [ 35 ]. The scale encompasses six subdomains: exercise management (eight items), disease management (four items), emotional management (three items), nutrition management (three items), stress management (three items), and health behavior management (three items). Responses are scored on a 5-point Likert scale, ranging from 1 (“strongly disagree”) to 5 (“strongly agree”), with higher scores denoting increased self-efficacy. For this study, the mean scores were calculated, which could vary from 1 to 5. The reliability of the instrument was confirmed with a Cronbach’s α of .91 in the study by Lee et al. [ 34 ] and .92 in the current study. General and human papillomavirus-related characteristics The general characteristics of the participants included seven items: age, marital status, educational level, job, average monthly household income, drinking, and smoking. HPV-related characteristics included 11 items: menopause status, age at first sexual intercourse, number of sexual partners during lifetime, current condom use, frequency of sexual intercourse, frequency of Pap tests, HPV vaccination status, induced abortion, childbirth, cervical cancer test results, and HPV types. Data collection Women who visited the obstetrics and gynecology outpatient clinic and tested positive for HPV were recruited for the study between February and April 2023. The researcher explained the purpose of the study and the survey details over the phone to potential participants. After participants agreed to take part in the study, an online survey link was sent to them. The online survey began with a description of the study, and clicking “agree” was considered to indicate consent. Participants who completed the survey received a mobile beverage coupon worth 4 US dollars as a token of appreciation. Data analysis IBM SPSS for Windows ver. 27.0 (IBM Corp., Armonk, NY, USA) was used to analyze the data. The general and HPV-related characteristics of participants were analyzed using frequency, percentage, and mean with standard deviation. We examined differences in knowledge of cervical cancer and HPV, levels of uncertainty, self-efficacy, and the intention to engage in cervical cancer preventive behavior according to these characteristics. This examination was conducted using the t-test and analysis of variance, with subsequent post-hoc analysis performed using the Scheffé test. To analyze the levels of knowledge about cervical cancer and HPV, uncertainty, self-efficacy, and the intention to engage in cervical cancer preventive behavior, we employed the mean and standard deviation. Pearson’s correlation coefficients were utilized to explore the relationships between knowledge of cervical cancer and HPV, uncertainty, self-efficacy, and the intention to engage in cervical cancer preventive behavior. Finally, multiple regression analysis was applied to identify factors that influenced the intention to engage in cervical cancer preventive behavior.

Results Differences in cervical cancer preventive behavior intentions based on general and human papillomavirus-related characteristics The average age of the participants was 37.96±9.31 years. Among them, 84 individuals (65.1%) were married, with the most common level of education being a bachelor’s degree or higher, as reported by 58 participants (45.0%). A significant majority, 97 participants (75.2%), were employed. The average monthly household income was 4.84±2.94 million Korean won, which is approximately 3,657.05±2,224.10 US dollars. Alcohol consumption was reported by 78 participants (60.5%), while 115 (89.1%) indicated that they were nonsmokers ( Table 1 ). In terms of HPV-related characteristics, 118 of the participants (91.5%) were premenopausal. The average age of first sexual intercourse was 20.80±3.09 years, with 39 participants (30.2%) reporting their first sexual encounter before the age of 20 years. The average number of lifetime sexual partners was 4.74±4.20, with the most common response being one partner, as reported by 24 participants (18.6%). A majority, 95 (73.6%), did not use condoms, and the most frequently reported frequency of sexual intercourse was less than once a month, at 48.1%. Regarding preventive health measures, 45 (34.9%) of the participants underwent annual Pap tests, and 66 (51.2%) had received HPV vaccinations. A total of 90 participants (69.8%) reported no history of induced abortion, and high-risk HPV types were detected in 66 participants (51.2%) ( Table 1 ). The intention to engage in cervical cancer preventive behavior showed significant relationships with the following factors: age at first sexual intercourse (F=7.38, p =.001), HPV type (F=4.79, p =.010), vaccination status (t=3.19, p =.002), and condom use (t=3.03, p =.003). According to the Scheffé post-hoc test, participants who first engaged in sexual intercourse before the age of 20 years or between the ages of 20 and 24 years had a higher intention for such behavior than those who were 25 years or older at the time of first sexual intercourse. Participants with high-risk HPV types or a combination of high- and low-risk types exhibited higher intentions than those with only low-risk types. Furthermore, those who had been vaccinated or used condoms showed a greater intention to engage in cervical cancer preventive behavior ( Table 1 ). Levels of intention to engage in cervical cancer preventive behavior, cervical cancer knowledge, human papillomavirus knowledge, uncertainty, and self-efficacy Participants exhibited a high intention to engage in cervical cancer preventive behavior, with an average score of 4.43±0.65 on a 1 to 5 scale. Knowledge of cervical cancer was somewhat above average, scoring 4.87±1.86 on a 0 to 8 scale. HPV knowledge was moderate, with an average score of 10.04±4.36 on a 0 to 20 scale. The level of uncertainty was slightly below average at 2.42±0.52 on a 1 to 5 scale, while self-efficacy exceeded the average, registering at 3.90±0.70 on a 1 to 5 scale ( Table 2 ). Correlations between intention to engage in cervical cancer preventive behavior, cervical cancer and human papillomavirus knowledge, uncertainty, and self-efficacy The intention to engage in cervical cancer preventive behavior was positively associated with both HPV knowledge (r=.22, p =.012) and self-efficacy (r=.42, p <.001). Knowledge about cervical cancer was positively correlated with HPV knowledge (r=.63, p <.001) and inversely correlated with uncertainty (r=–.21, p =.016). Furthermore, HPV knowledge was negatively correlated with uncertainty (r=–.21, p =.015), and uncertainty was inversely related to self-efficacy (r=–.33, p <.001) ( Table 3 ). Factors influencing the intention to engage in cervical cancer preventive behavior Multiple regression analysis was used to identify factors that influence the intention to engage in cervical cancer prevention behaviors. The independent variables considered were age at first sexual intercourse, HPV type, vaccination status, condom use, and knowledge of cervical cancer and HPV, as well as levels of uncertainty and self-efficacy. Categorical variables such as age at first sexual intercourse (with ≥25 years as the reference), HPV type (with low-risk as the reference), vaccination status (with unvaccinated as the reference), and condom use (with non-use as the reference) were dummy-coded for analysis. The Durbin-Watson statistic was 1.643, suggesting the absence of autocorrelation in the residuals. Furthermore, the standardized residuals fell within the range of 3, indicating a normal distribution of errors. Multicollinearity was not a concern, as indicated by tolerance values between .346 and .873 and variance inflation factors ranging from 1.146 to 2.893. The analysis identified several significant factors that influence the intention to engage in cervical cancer preventive behavior for cervical cancer. These factors, in order of significance, included self-efficacy (β=.46, p <.001), first engaging in sexual intercourse before the age of 20 years (β=.45, p <.001) or between the ages of 20 and 24 years (β=.29, p =.018), infection with both high- and low-risk HPV types (β=.26, p =.019), infection with high-risk HPV types alone (β=.26, p =.026), and vaccination (β=.21, p =.007). Consequently, higher self-efficacy, earlier age at first sexual intercourse, and infection with high-risk HPV types or both high- and low-risk types, as opposed to only low-risk types, along with being vaccinated, significantly increased the intention to engage in cervical cancer preventive behavior. Collectively, these factors accounted for 34.6% of the variance in the intention to engage in cervical cancer preventive behavior ( Table 4 ).

Discussion This study aimed to assess the levels of cervical cancer and HPV-related knowledge, self-efficacy, and uncertainty among women infected with HPV, as well as the factors influencing their intention to engage in cervical cancer preventive behavior, with the goal of developing programs to increase such intentions in HPV-infected women. The results indicated that self-efficacy, age at first sexual intercourse, HPV infection type, and vaccination status were all significant determinants of their preventive behavior intention. In this study, participants demonstrated higher cervical cancer knowledge scores than those reported in similar studies using the same assessment tool. For instance, a study involving nursing students [ 11 ] reported scores of 4.83 for those who had undergone a Pap test and 3.98 for those who had not. In contrast, female university students scored 3.74 in another study [ 36 ]. Likewise, the HPV knowledge scores of participants in this study exceeded those found in other research: 2.74 for married immigrant women [ 37 ], 5.33 for female university students [ 36 ], and 7.98 for nurses [ 10 ]. The elevated level of knowledge among HPV-infected women in this study may be attributed to their heightened interest in HPV and cervical cancer, which likely motivates them to actively seek information from various sources, including medical professionals. However, given the potential risk of cervical cancer in HPV-infected women, their knowledge level, while comparatively high, is still not sufficient. Therefore, systematic education focused on HPV management and cervical cancer prevention for HPV-infected women is necessary. This study found that participants had an average uncertainty score of 2.42 out of a possible 5 points, reflecting a moderate degree of uncertainty. This finding aligns with results from previous research using the same measurement tool, which reported scores of 2.47 in gastrectomy patients with gastric cancer [ 19 ], 2.67 in patients undergoing hemodialysis [ 20 ], and 2.52 in female thyroid cancer patients [ 38 ]. However, there is a scarcity of research on uncertainty in women infected with HPV. Given the unpredictable nature of treatment outcomes and the potential progression to cervical cancer, it is crucial to alleviate uncertainty in these women. Providing education about HPV and cervical cancer can play a significant role in this effort by offering accurate knowledge and information. The average score for the intention to engage in cervical cancer preventive behavior among the study participants was 4.43. Although there are no directly comparable prior studies focusing on HPV-infected women, similar research utilizing the same measurement tool has yielded varying results. In Ko’s study [ 26 ], women between the ages of 20 and 50 years had an average score of 3.62. A separate study involving nurses reported an average score of 3.55 [ 10 ], and female university students scored an average of 4.25 in research conducted by Nguyen and Lee [ 13 ]. Compared to these outcomes, the intention of HPV-infected women in the current study to participate in preventive behavior seems to be relatively high. The factors influencing the intention to engage in cervical cancer preventive behavior were self-efficacy, age at first sexual intercourse, HPV type, and vaccination status, listed in order of impact. Previous research [ 39 ] has shown that self-efficacy exerts a stronger influence on health-promoting behaviors, preventive behavior, and sick role behaviors than other variables. It also affects university students’ intentions to adopt preventive behavior for emerging infectious diseases [ 40 ]. In a study with female university students, Nguyen and Lee [ 13 ] identified self-efficacy as a mediating factor for the intention to practice cervical cancer prevention. Similarly, Ma et al. [ 24 ] found self-efficacy to be a highly influential factor among Chinese individuals in their twenties. This study corroborates these findings, highlighting self-efficacy as the most significant factor, in line with numerous previous studies. These results indicate that confidence in one’s ability to take appropriate action in specific situations can significantly affect the willingness to engage in health-promoting behaviors. Consequently, it is essential to develop strategies that enhance self-efficacy to increase women’s intention to engage in cervical cancer preventive behavior, particularly among those infected with HPV. Regarding the HPV-related characteristics of the participants, initiating sexual intercourse between the ages of 20 and 24 years, or before the age of 20 years, being infected with high-risk HPV or both high- and low-risk types, and receiving the HPV vaccine were all identified as factors influencing the intention to engage in cervical cancer preventive behavior. However, the limited amount of prior research on HPV-infected women makes direct comparisons with these findings challenging. Since 2016, Korea has implemented the Healthy Women’s First Step Clinic Program since 2016, providing free HPV vaccinations to 12-year-old female adolescents [ 41 ]. In general, receiving the complete vaccine series before becoming sexually active is the most effective method for preventing cervical cancer. Nevertheless, vaccination remains beneficial for those who are sexually active, already infected with HPV, or older, as it can prevent new HPV infections and reinfection with existing HPV strains, thereby reducing the risk of cancer [ 6 ]. Therefore, it is imperative to provide HPV-infected women with accurate information about cervical cancer prevention, educate them on specific preventive actions, and emphasize the importance and benefits of HPV vaccination. HPV infection is the most direct and significant cause of cervical cancer among its various causes. Women who test positive for HPV often face psychological and social challenges, including shock, confusion, anxiety, and fear of the disease [ 41 ]. However, cervical cancer can be prevented through regular screenings, HPV vaccination, and adherence to sexual health preventive behavior. Early detection and treatment are key to reducing mortality rates [ 9 ]. Therefore, it is vital to promote the intention to engage in cervical cancer preventive behavior among women with HPV. This study highlights the importance of boosting self-efficacy and developing effective educational programs for prevention. Furthermore, because HPV is a sexually transmitted infection, it is particularly important to address infected women’s negative emotions and the societal stigma associated with HPV. Such efforts will contribute to the creation of a supportive environment, encouraging these women to actively engage in cervical cancer preventive behavior. Interestingly, this study found that knowledge of cervical cancer and HPV did not significantly influence participants’ intention to engage in cervical cancer preventive behavior. This finding aligns with previous research [ 12 , 26 ] indicating that knowledge alone is not sufficient to motivate preventive behavior. Additionally, these findings suggest that, while knowledge is a necessary component for increasing cervical cancer preventive behavior, knowledge alone is insufficient to induce the intention to engage in such behavior. While the KR-20 reliability score for the cervical cancer knowledge tool in this study was low (.61), it was still identified as influential. Consequently, there is a need for further development of a more reliable cervical cancer knowledge tool for future research. This study included a wide range of participants, ranging from women newly diagnosed with HPV or those with a relatively brief infection duration, to women with a history of HPV infection who were undergoing regular follow-up over a prolonged period. However, a limitation of this study is the lack of consideration for the duration of the participants’ HPV infection. Research on diabetes patients [ 42 ] has shown that the length of time since diagnosis is associated with statistically significant differences in self-care behaviors. Specifically, patients who had been diagnosed with diabetes for over 10 years exhibited better self-care practices than those diagnosed for less than five years. Consequently, future studies should take the time since diagnosis into account. Another limitation of the study is the difficulty of generalizing the findings to all women affected by HPV, as the sample consisted solely of HPV-infected women from a single general hospital in a specific region. Therefore, further research is needed to investigate the timing and duration of HPV infection across a broader demographic. Additionally, follow-up studies are essential to create and validate effective cervical cancer prevention programs tailored to women with HPV infection. Most HPV research in Korea has centered on specific groups such as nurses, university students, and unmarried women. However, there has been a notable lack of investigation into the lived experiences of women who have contracted HPV. This study holds significance as it sheds light on the motivations behind cervical cancer preventive behavior in women with HPV. These insights provide crucial foundational data that will inform the creation of effective cervical cancer prevention programs.

Purpose This study investigated the influence of cervical cancer knowledge, human papillomavirus (HPV) knowledge, self-efficacy, and uncertainty on the intention to engage in cervical cancer preventive behavior in HPV-infected women. Methods This descriptive correlational study was conducted among 129 adult women aged 20 to 65 years who received positive HPV results at a general hospital in Changwon, Korea. The dataset was analyzed using descriptive statistics, the independent t-test, analysis of variance, the Pearson correlation coefficient, and multiple regression. Results The mean score for the intention to engage in cervical cancer preventive behavior was high (4.43±0.65). This intention was significantly different according to age at first sexual intercourse (F=7.38, p =.001), HPV type (F=4.79, p =.010), vaccination (t=3.19, p =.002), and condom use (t=3.03, p =.003). The intention to engage in cervical cancer preventive behavior showed significant, weak-to-moderate positive correlations with HPV knowledge (r=.22, p =.012) and self-efficacy (r=.42, p <.001). Self-efficacy (β=.46, p <.001), first sexual intercourse at >20 years (β=.45, p <.001), first sexual intercourse at 20-24 years (β=.29, p =.018), HPV high- and low-risk group infection (β=.26, p =.019), HPV high-risk group infection (β=.26, p =.026) and vaccination (β=.21, p =.007) significantly influenced the intention to engage in cervical cancer preventive behavior. These variables explained 34.6% of variance in this intention. Conclusion It is necessary to develop a program that effectively conveys accurate information about cervical cancer prevention to HPV-infected women and helps them enhance self-efficacy to boost the intention to engage in cervical cancer preventive behavior. Summary statement

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):317-327

oa_package/b4/43/PMC10788391.tar.gz

PMC10788392

38204389

Introduction According to guidelines from the Centers for Disease Control and Prevention (CDC), all women with the potential to bear children should consume 400 μg of folic acid daily, starting at least 1 month before pregnancy and continuing until 3 months into pregnancy. This is to prevent fetal neural tube defects, including spondyloschisis, anencephaly, and cephalocele [ 1 ]. The prevalence of neural tube defects varies across regions as defined by the World Health Organization. A systematic review conducted in 2016 reported incidences of 21.9 per 10,000 people in the East Mediterranean region, 15.8 in Southeast Asia, 11.7 in Africa, 11.5 in the Americas, 9.0 in Europe, and 6.9 in the West Pacific region [ 2 ]. With its vast size, China exhibits varying incidences of neural tube defects across different regions. Higher rates are observed in the northern and western parts, while lower rates are seen in the southern and eastern regions. Although the average incidence in Mainland China is 6.18 per 10,000, a closer look at each region reveals the following: in North China, the Inner Mongolia Autonomous Region has an incidence of 20.1 per 10,000, and Shanxi Province has 16.07 per 10,000. In East China, Anhui Province has 10.65 per 10,000. Northwest China has an average incidence of 20 per 10,000, with Gansu Province showing an incidence of 39.51 per 10,000. These findings can be attributed to factors such as the ecological environment, economic development, and the standard of the healthcare system [ 3 ]. There appears to be a need for studies that identify the factors influencing the reduction of neural tube defect incidence, with the aim of mitigating their negative effects. While the exact cause of neural tube defects remains unknown, a deficiency in folic acid during pregnancy is considered a significant factor. Research indicates that consuming folic acid during pregnancy can prevent between 50% and 70% of fetal neural tube defects [ 4 ]. Despite global initiatives promoting the prevention of neural tube defects through adequate folic acid intake, a study by Chitayat et al. [ 5 ] suggests that the rate of effective folic acid consumption is low, resulting in insufficient prevention of these defects. Effective folic acid intake is defined as the prevention of neural tube defects in women of childbearing age by consuming 400 μg of folic acid, starting at least 1 month before pregnancy and continuing until 3 months after pregnancy [ 1 ]. In this study, effective folic acid intake was specified as follows: (1) a daily intake of 400 μg of folic acid, (2) beginning 1 month prior to pregnancy, (3) continuing until 3 months post-pregnancy, and (4) when the correct intake of folic acid occurs on 80% or more of the total number of days [ 1 , 6 ]. Most previous studies on the four criteria for effective folic acid consumption in various countries did not clearly define the exact period of intake. In studies carried out in China, it was found that between 7.9% and 32.7% of women began taking folic acid prior to pregnancy [ 7 , 8 ], 55.7% started 2 months post-pregnancy [ 7 ], and 14.3% took it from 3 months pre-pregnancy until 3 months post-pregnancy [ 9 ]. In terms of folic acid intake prior to pregnancy in other countries, 20.5% of Japanese women began 1 month before pregnancy [ 10 ], and 11.7% of Italian women did the same [ 11 ]. In Korea, 24.6% of women started taking folic acid before pregnancy, regardless of the specific period [ 12 ], while 24.7% of Irish women [ 13 ] and 30% of American women [ 14 ] followed suit. In contrast, between 54.9% and 74.9% of Italian women began their folic acid intake after pregnancy [ 11 , 15 ], and 47.2% of Italian women took a daily dose of 400 μg [ 15 ]. These findings illustrate the patterns of folic acid consumption among pregnant women in Northwest China and other parts of the world. Few studies, whether in China or elsewhere, have specified the exact period of intake. The rate of intake before pregnancy was relatively low, with most participants beginning their folic acid regimen after becoming pregnant. While previous studies have reported the rate of folic acid intake at various stages before and after pregnancy, few have addressed the overall effective intake rate. Therefore, this study aimed to investigate the extent to which the criteria for effective intake are being met by pregnant women in China. Furthermore, it is crucial to provide Chinese women with education on proper folic acid consumption to improve their understanding of effective folic acid intake and encourage its use. Folic acid knowledge refers to the awareness that folic acid belongs to the vitamin B complex, and that an adequate amount of folic acid in the body can help prevent significant congenital defects in the fetal brain and spine. It also involves knowing that a daily dose of 400 μg of folic acid is necessary from 1 month before pregnancy until 3 months after pregnancy [ 1 ]. Existing research on folic acid knowledge reveals that 58.3% of pregnant women in China were aware that folic acid intake is necessary to prevent neural tube defects. However, only 15.6% knew the correct intake period for folic acid, and 36.7% knew the accurate dosage [ 16 ]. Studies have shown that 56.4% of pregnant women in Korea and 85.4% in Ireland were aware that folic acid helps prevent neural tube defects [ 12 , 17 ]. Additionally, 32.2% of pregnant women in Japan knew the exact dosage of folic acid [ 10 ]. In summary, the level of folic acid knowledge among pregnant women in China appears to be similar to that of pregnant women in Korea, particularly regarding folic acid’s role in preventing neural tube defects. It is also comparable to the knowledge level among pregnant women in Japan concerning the dosage of folic acid. Although there was no comparison group for the intake period of folic acid, it was found that few women had accurate knowledge of this aspect. An analysis was conducted to determine the correlation between knowledge of folic acid and its intake. The results revealed that pregnant women who understood the role of folic acid in preventing neural tube defects were 2.64 times more likely to consume folic acid compared to those who were unaware of its benefits [ 10 ]. This suggests that simply being aware of the need for folic acid can influence its actual consumption. Given that accurate knowledge about folic acid can potentially enhance its effective intake, this study aimed to further investigate this correlation. Upon investigating other factors that influence folic acid intake, it was observed that in both China and other countries, certain factors were associated with a higher rate of folic acid consumption. These factors included being aged 30 years and above [ 10 , 13 , 18 ], having a higher level of education [ 18 - 20 ], earning a higher income [ 20 , 21 ], residing in cities [ 19 ], suffering from chronic diseases [ 11 , 22 ], planning pregnancies [ 19 , 22 ], being a married woman [ 11 , 21 ], having given birth [ 11 , 13 , 21 ], and having undergone infertility treatment. A review of the above references shows that most existing studies have only incorporated certain criteria when defining effective folic acid intake. These studies have investigated the current state of folic acid consumption and analyzed its alignment with the understanding of folic acid. Therefore, this study aimed to evaluate the status of effective folic acid intake among pregnant women in China, in line with the four guidelines issued by the CDC. Furthermore, the study investigated women’s understanding of folic acid and the impact that this knowledge has on effective folic acid consumption. Ultimately, the findings are hoped to contribute to improving effective folic acid intake rates through these investigations.

Methods Study design This cross-sectional survey study sought to examine the intake of folic acid and knowledge about folic acid among pregnant women in China and explore the influence of folic acid knowledge on effective folic acid intake. Participants This study included women who were at least 12 weeks pregnant and were patients at Yantai Yuhuangding Hospital in Shandong, China. The participants were selected through convenience sampling. The study was based on previous research, which found that 42% of participants had taken folic acid prior to pregnancy [ 23 ]. An odds ratio (OR) of 2.64 was established, with a confidence level of 0.05 and a test power of 0.8, using G*power 3.1. The minimum sample size was calculated to be 134, but we anticipated a dropout rate of 20%, so the final sample size was set at 161. After data collection, it was found that a total of 154 women had completed the survey. However, after excluding 10 participants who did not complete the survey faithfully and four who had not taken folic acid, the total number of participants used in the survey analysis was 140. Instruments After preparing the questionnaire and consent form in Korean, the researchers enlisted the help of a specialized agency for translation and reverse translation. This resulted in the final version of the tool, which was written in Chinese. The validity of this final questionnaire was subsequently assessed by two nursing educators who were proficient in both Chinese and Korean. Furthermore, a preliminary survey was carried out with three pregnant women living in China and no difficulties in understanding or completing the survey were found. Thus, items were deemed satisfactory for the main survey. Effective folic acid intake Effective folic acid intake was assessed based on the following criteria: (a) whether the daily intake of folic acid was 400 μg (yes/no), (b) whether folic acid was consumed starting from 1 month prior to pregnancy (yes/no), (c) whether folic acid was consumed during the first 3 months of pregnancy (yes/no), and (d) whether folic acid was consumed at least 24 days in a month (yes/no). A total score of 4 points indicated effective intake, while a score ranging from 0 to 3 points was considered indicative of ineffective intake. Folic acid knowledge We utilized nine items from the CDC’s 10-item questionnaire related to folic acid knowledge ( https://www.cdc.gov/ncbddd/folicacid/quiz.html ), after making necessary revisions. Each item was answered with either a “yes” or “no,” with correct responses earning 1 point and incorrect responses earning 0 points. The total score, which could range from 0 to 9, served as an indicator of the respondent’s knowledge of folic acid; a higher score signified greater knowledge. The Cronbach’s α for this knowledge tool is .65. Folic acid intake A questionnaire was developed based on Bai et al.’s study [ 24 ]. It comprised 18 items, which included questions about whether the respondent had taken folic acid, the first and last instances of folic acid intake, the total daily amount of folic acid consumed, and the specific content of the folic acid taken. General characteristics The general characteristics of the participants were collected using eight items: age, ethnicity, city residency, education level, spouse’s education level, occupation, spouse’s occupation, and monthly family income. The obstetric characteristics of the participants were as follows: the date of their last menstrual period, history of miscarriage, history of abortion, history of infertility, and whether the pregnancy was planned. Data collection Data were collected from November 2021 to May 2022. A research assistant, who had previously worked as a nurse in China and had undergone training with the researchers, was responsible for data collection at Yantai Yuhungding Hospital in Shandong, China. Participants were recruited by scanning a QR code on a flyer posted in the hospital, which led them to the study’s information sheet. If a participant agreed to take part in the study, she proceeded to complete the online questionnaire. The information sheet outlined the study’s content, purpose, and data anonymity, and it also stated that participants could withdraw at any point during the study if they chose not to continue. If a participant clicked “do not agree,” the survey automatically ended. Completing the online questionnaire took approximately 10 minutes. As a token of appreciation, each participant received a mobile coffee coupon worth 3 US dollars. Data analysis Data were analyzed as follows using IBM SPSS for Windows vers. 24.0 (IBM Corp., Armonk, NY, USA). The general and obstetric characteristics of the pregnant women were analyzed using frequency, percentages, mean, and standard deviation. Differences in effective folic acid intake according to folic acid knowledge were analyzed using the t-test and the chi-square test. Finally, logistic regression analysis was conducted to identify factors influencing folic acid intake.

Results Characteristics of participants The mean age of the 140 participants was 31.56±3.88 years (range, 21–41 years). In terms of education, 67.9% of the participants held university degrees, and 89.3% were employed. Among the participants’ spouses, 67.1% held university degrees, and 97.9% were employed. Sixty percent of the participants were experiencing their first pregnancy. A smaller portion (8.6%) had previously experienced a miscarriage. Additionally, 30.7% had undergone an abortion. Notably, 82.9% of all participants had planned their pregnancies ( Table 1 ). Status of effective folic acid intake Of the total participants, 16.4% (23 individuals) met all four criteria for effective folic acid intake, while the remaining 83.6% (117 individuals) did not. When we analyzed the intake outcomes based on these four criteria, we found that (1) 72.2% (104 individuals) began taking folic acid prior to pregnancy, (2) 70.8% (102 individuals) continued taking folic acid up to 3 months post-pregnancy, (3) only 36.8% (53 individuals) consumed the recommended daily dose of 400 μg of folic acid, and (4) 78.6% (110 individuals) took the supplement for at least 24 days in a month, which equates to 80% of the month. As these figures indicate, the criterion with the lowest adherence was the correct daily dosage of folic acid ( Figure 1 ). Among the participants who did not meet the criteria for effective folic acid intake, 25.8% (36 individuals) consumed folic acid from 1 month prior to pregnancy until 3 months post-pregnancy, for at least 24 days each month. This group represented the majority. They were followed by 12.9% (18 individuals) who consumed folic acid from before pregnancy for at least 24 days each month, 12.2% (17 individuals) who consumed folic acid until 3 months post-pregnancy for at least 24 days each month, and 6.5% (nine individuals) who consumed 400 μg of folic acid daily from before pregnancy until 3 months post-pregnancy. Among the participants with ineffective intake who underwent surgery, 2.1% (three individuals) did not meet any of the four criteria for effective folic acid intake. Differences in folic acid knowledge according to effective folic acid intake The mean score for participants’ knowledge of folic acid was relatively high, at 5.61±2.18 out of a possible 9 points. The statement that received the highest rate of correct responses was “the easiest way to get the right amount of folic acid every day is to take 400 μg of synthetic folic acid,” with 79.3% (111 individuals) of participants responding “yes.” Conversely, the statement with the lowest rate of correct responses was “folic acid is a B vitamin,” with only 50.7% (71 individuals) of participants responding “yes.” Upon analyzing the variance in folic acid knowledge based on effective folic acid intake, it was found that the group with effective folic acid intake scored higher in folic acid knowledge compared to the group with ineffective folic acid intake (t=4.10, p <.001). Among the items related to folic acid knowledge, participants who were aware that “women of childbearing age should consume 400 μg of folic acid every day” (χ 2 =10.95, p <.001), understood “ways to be sure that you are getting enough folic acid every day” (χ 2 =10.71, p <.001), knew “what are spina bifida and anencephaly” (χ 2 =3.98, p <.005), and recognized that “the easiest way to get the right amount of folic acid every day is to take 400 μg of synthetic folic acid” (χ 2 =4.49, p <.005), were more likely to exhibit effective folic acid intake ( Table 2 ). Influencing factors on effective folic acid intake To identify the factors that influence the effective intake of folic acid among pregnant women, we conducted a binomial logistic regression analysis. This analysis used significant variables derived from a cross-tabulation analysis, which examined potential differences based on general and obstetrical characteristics. However, our analysis revealed that these characteristics did not significantly impact the effective intake of folic acid among pregnant women ( Table 1 ). We found that a higher score in folic acid knowledge (OR, 1.74; 95% confidence interval [CI], 1.29–2.35) was associated with effective folic acid intake. Notably, participants who understood that “women of childbearing age should consume 400 μg of folic acid daily” (OR, 14.77; 95% CI, 1.93–113.35) and knew “ways to be sure that you are getting enough folic acid every day” (OR, 5.74; 95% CI, 1.84–17.90) were more likely to effectively consume folic acid. However, when we adjusted the ORs using the characteristics found to be significant in effective folic acid intake, we did not identify any significant determinants ( Table 3 ).

Discussion This study is the first, to our knowledge, to examine the status of effective folic acid intake and investigate its relationship with folic acid knowledge, in line with the four criteria set by the CDC’s folic acid intake guidelines. Our findings indicate that the rate of effective folic acid intake, based on these four guidelines, was 16.4%. This is significantly higher than the 4.82% rate of effective folic acid intake among pregnant women in China, as reported in a 2011 study. In that study, women consumed 400 μg of folic acid at least 5 days a week, starting 1 month before pregnancy and continuing until 2 months after conception [ 24 ]. This increase may be attributed to an actual rise in folic acid intake among pregnant women in China, a result of a policy that provided folic acid free of charge to boost intake rates [ 25 ]. However, the rate of effective intake remains relatively low. This study can be compared to others that only adopted some of the criteria for effective folic acid intake. In 2017, the rate of effective folic acid intake, defined as consumption from 3 months before pregnancy until 3 months after pregnancy, was examined in Tianjin City. The rates of folic acid intake were found to be 14.4%, respectively [ 26 ]. In 2014, the rate of effective folic acid intake, defined as consumption from 3 months before pregnancy for at least 24 days a month, was analyzed in Shanxi Province. The rate of folic acid intake was found to be 14% [ 6 ], a figure similar to the intake rate in this study. All participants had taken folic acid at some point, but only a small proportion continued to take it from before conception through pregnancy. This finding is consistent with a study conducted overseas [ 27 ] and suggests that the participants’ lack of knowledge about the precise period for folic acid intake contributes to the low rate of effective folic acid intake. In this study, 72.2% of participants reported taking folic acid for at least 1 month prior to pregnancy. This is significantly higher than the 24.7% rate reported in Cawley et al.’s study [ 13 ] involving pregnant women. To determine if there is a correlation between a participant’s level of education and the rate of folic acid intake, further studies are needed. This aligns with a previous study suggesting that a participant’s education level influences the rate of folic acid intake before pregnancy [ 26 ]. In this study, it was observed that 70.8% of participants continued taking folic acid up to 3 months post-pregnancy. This rate is comparable to the 66.1% reported in a study conducted with pregnant women in China [ 16 ]. This suggests that the “Health Guidelines for Preconception and during Pregnancy,” a public initiative launched in China in 2011 [ 28 ], has successfully raised awareness about the importance of folic acid intake among women. Consequently, most women now understand the need to take folic acid during pregnancy. Approximately 36.8% of the women in this study reported taking a daily dose of 400 μg of folic acid, a rate similar to the 47.2% reported in a study conducted with women in Italy [ 15 ]. This suggests that over half of the participants are unaware of the recommended daily dose of folic acid. According to a study by Maraschini et al. [ 15 ], only 8.0% of all participants received education on the correct dosage of folic acid prior to pregnancy, and 13.7% received such education during pregnancy. This underscores the fact that the importance of the correct dosage is not sufficiently emphasized in education about folic acid intake. Among the participants in this study, 78.6% reported taking folic acid for at least 24 days each month. This rate is similar to the 81.6% reported in a previous study conducted in China [ 23 ]. This suggests that the majority of women consistently take folic acid daily once they start. In summary, while pregnant women in China were cognizant of the need to take folic acid up to 3 months post-pregnancy, and understood the frequency of its intake, they did not meet the recommended daily intake of 400 μg, starting at least 1 month prior to pregnancy. For effective folic acid consumption, individuals must strive to meet all these criteria in their daily routines. To boost the prevalence of effective folic acid consumption, several countries, including the United States, have instituted and enforced folic acid fortification policies. These policies promote the consumption of grain products fortified with folic acid. However, according to a meta-analysis by Toivonen et al. [ 29 ], there is no discernible difference in the incidence of neural tube defects between countries that have implemented folic acid fortification policies and those that have not. While county-level policies are necessary to increase the rate of effective folic acid intake, it appears that individual awareness of the importance of folic acid consumption, and the personal initiative to include it in one’s diet, are even more critical. Turning to knowledge, the mean score for folic acid knowledge among the pregnant women participating in the study was 5.61 out of a possible 9 points. Two items had a correct response rate of 70% or higher, three items had a rate of 60% or higher, and four items had a rate of 50% or higher. This indicates that the overall understanding of folic acid is relatively high among the participants. However, further education is necessary on the items that scored lower to ensure accurate comprehension. These items included: “folic acid is a B vitamin,” “ways to be sure that you are getting enough folic acid every day,” “what are spina bifida and anencephaly,” and “a woman should be taking folic acid if she is planning a pregnancy, is capable of becoming pregnancy, even if she is not planning a pregnancy, or thinks she might become pregnant sometime in the future.” Additionally, the statement “women of childbearing age should consume 400 μg of folic acid daily” did not receive a high rate of correct responses. Given that this item also had the lowest adherence rate in the folic acid intake survey conducted as part of this study, there is a clear need for increased awareness and emphasis on this point. The binomial logistic analysis revealed that participants with a more comprehensive understanding of folic acid were more likely to exhibit effective folic acid intake. This finding aligns with a survey conducted among pregnant women and those who had recently given birth in China. In this survey, women who understood the importance of folic acid during pregnancy and its role in preventing neural tube defects showed better adherence to folic acid intake [ 30 ]. Consequently, it is crucial to enhance folic acid knowledge to increase the rate of effective folic acid intake. The role of nurses, who are often the primary source of this knowledge, is also of paramount importance. Research indicates that the rate of folic acid intake among pregnant women and women of childbearing age increases when clinical staff provide brief, 30 to 60-second explanations about folic acid [ 31 ]. Therefore, nurses, who are tasked with educating these women, should emphasize the correct method of folic acid intake and instruct on how to effectively incorporate it into their routine. In this study, factors such as the participant’s monthly income, education level, employment status, multiparity, miscarriage history, and whether the pregnancy was planned did not significantly influence effective folic acid intake. This finding contrasts with the study by Kim et al. [ 12 ] in Korea, which found that higher income, higher education level, and employment were associated with increased folic acid intake. It also differs from the study by Nilsen et al. [ 11 ] in Italy, which reported that primiparous women had a higher rate of effective folic acid intake. Specifically, our study found that whether a pregnancy was planned did not impact effective folic acid intake. This is in contrast to findings from Ireland, where women with planned pregnancies had a higher rate of folic acid intake [ 13 ]. The discrepancy may be due to the small sample size of our study and the fact that the majority of respondents reported having planned pregnancies, leading to oversampling. Furthermore, our study applied strict criteria for measuring effective intake, as opposed to the simple confirmation of intake used in previous studies. This could also account for the observed differences. In conclusion, the significant correlation between demographic and obstetrical characteristics and folic acid intake reported in previous studies was not observed in our study. This may be due to our smaller sample size, uneven distribution of demographic and obstetrical characteristics, and different method of measuring effective folic acid intake. Therefore, the relationship between demographic and obstetrical characteristics, including planned pregnancies, and effective folic acid intake should be re-evaluated in future studies with larger sample sizes. The limitations of this study include the absence of a nationwide sample because it focused only on one specific area in China. In addition, it considered all four criteria of effective intake, making it difficult to compare the study directly with existing studies. Nonetheless, this study provides meaningful results because it analyzed all four criteria of effective folic acid intake, pinpointing the specific reasons for unsuccessful implementation. Moreover, the study illustrates that to enhance the rate of effective folic acid intake, women of childbearing age need to cultivate an interest in folic acid consumption, a preventive strategy against neural tube defects. It underscores the necessity for comprehensive education on the precise dosage and duration of folic acid intake. We anticipate that this survey will offer participants the chance to proactively adopt effective folic acid intake practices in the future. Based on the findings of this survey, future education on effective folic acid intake should take into account the following considerations. While most pregnant women are aware of the need to take folic acid, they may not be fully informed about the necessity of adhering to all four guidelines for effective intake, including its role in preventing neural tube defects. It is particularly important to emphasize that folic acid should be taken at least 1 month prior to pregnancy and that the recommended daily dosage for nonpregnant women is 400 μg. There is an urgent need to educate women about folic acid, including its benefits and effective usage, for the betterment of women’s health. This education should be delivered in a clear and easily comprehensible manner. Future research should aim to validate the impact of this education on the understanding and effective consumption of folic acid. It should also reexamine the relationship between effective intake and demographic characteristics not previously investigated in this study. Furthermore, it appears necessary to monitor compliance with specific criteria for folic acid consumption through a mobile application.

Purpose This study aimed to investigate the current status of effective folic acid intake and the level of folic acid knowledge of Chinese pregnant women and to analyze the relationship between effective folic acid intake and folic acid knowledge. Methods From November 2021 to May 2022, 140 pregnant women at Yantai Yuhuangding Hospital in the Chinese province of Shandong, answered questions about their general characteristics, folic acid intake, and folic acid knowledge. The data were analyzed using the t-test, chi-square test, and logistic regression analysis, and were presented with frequency with percentage or mean±standard deviation. Results Only 16.4% of the pregnant women (n=23) took folic acid effectively, using the following four criteria. Of all pregnant women who took folic acid, 72.2% took folic acid starting 1 month before pregnancy, 70.8% took folic acid up to 3 months after pregnancy, 36.8% took 400 μg every time, and 78.6% took folic acid more than 24 days every month. The score for folic acid knowledge was relatively high (5.61±2.18 on a scale of 0–9). A higher folic acid knowledge score correlated with more effective folic acid intake (t=4.10, p <.001). Conclusion Our study shows that the current recommendations to prevent neural tube defects through effective folic acid intake supplementation are not being fully implemented in China. Furthermore, folic acid knowledge was positively correlated with the effectiveness of its intake. Future education related to effective folic acid intake should emphasize the four methods of effective folic acid intake, especially regarding the recommended dose of 400 μg every time. Summary statement

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):291-301

oa_package/5a/26/PMC10788392.tar.gz

PMC10788393

38204388

Introduction During pregnancy, women undergo unique physiological, psychological, and social changes. They are exposed to a considerable amount of visible and potential stress, which can make them more susceptible to depression and anxiety [ 1 ]. Before the outbreak of the coronavirus disease 2019 (COVID-19) prenatal stress, encompassing general worries and fears about pregnancy, was reported as being more prevalent among pregnant women with a history of mental illness, those who were younger, or those with lower incomes and educational levels [ 2 ]. However, during the COVID-19 pandemic, even pregnant women without these risk factors appeared to have experienced high levels of prenatal stress, and some exhibited symptoms of dissociative disorder and posttraumatic stress disorder (PTSD) [ 2 ] . There was also a significant increase in depression and anxiety disorders during the pandemic, which indicates that the psychological impact of the pandemic appeared to have been a threat to all pregnant women, not just those with vulnerable characteristics [ 2 ]. The decline in mental health among women during pregnancy can be attributed to several factors, such as the unknown effects of COVID-19 on the health of both the mother and fetus, changes and restrictions in prenatal checkup routines and service facilities, and isolation from social support networks due to social distancing measures [ 3 ]. Recent research suggests that increased stress during pregnancy and prenatal depression, particularly during a pandemic, can disrupt the maternal-fetal bond [ 4 ]. This heightened stress can trigger an overactive response in the fetus, leading to an excessive release of stress hormones in the mother. This, in turn, activates the immune system, potentially causing issues with inflammation and immune regulation [ 5 ]. Consequently, this can result in adverse birth outcomes, such as preterm birth or the delivery of babies that are small or of low birthweight for their gestational age [ 3 ]. During the pandemic, pregnant women reported significantly elevated stress levels compared to the period before. Their depression was intensified by the fear of infection and a lack of adequate support during childbirth [ 6 ]. Prior research has identified marital satisfaction as a significant determinant of prenatal depression [ 7 ]. Lower marital satisfaction has been linked to heightened prenatal depression and a reduction in healthcare practices during pregnancy [ 8 ]. Prenatal depression is also affected by gestational age, with physical and mental stress escalating in the third trimester. This demonstrates the need for meticulous management of prenatal depression, taking into account the gestational week. Improving behaviors related to pregnancy healthcare can serve as an effective strategy for reducing prenatal depression. The frequency of breakfast consumption, sleep duration, and drinking habits all have an impact on prenatal depression; thus, a diet rich in vitamins and increased physical activity are recommended during pregnancy [ 9 ]. Even amidst a pandemic, participating in online fitness classes can increase physical activity levels, thereby bolstering pregnant women’s resilience against prenatal depression. Moreover, factors associated with physical activity and sleep during pregnancy play a significant role in managing pandemic-related stress, underscoring the importance of reinforcing healthcare practices among pregnant women [ 10 ]. Prenatal education can improve the healthcare practices of pregnant women, instilling a sense of preparedness for pregnancy and parenthood. This not only boosts their confidence in childbirth but also mitigates prenatal depression and wards off postpartum depression [ 11 - 13 ]. Prenatal education must evolve to meet the times and the specific needs of pregnant women. However, traditional approaches often overlook the individual circumstances of pregnant women and tend to generalize their experiences [ 14 ]. COVID-19 has been linked to significant changes in the mental health, quality of life, attitudes, and lifestyle of pregnant women. There has been a notable increase in stress and depression during this period. Social distancing measures have curtailed their physical activities during leisure time, leading to an increase in time spent at home. Furthermore, there has been a heightened interest in the complications, epidemiology, and treatment of infectious diseases such as COVID-19 [ 15 ]. Consequently, this study aims to assess the current state of prenatal education and the impact of pandemic-related pregnancy stress and healthcare practices on prenatal depression. The goal is to provide foundational data and evidence to develop intervention strategies for prenatal education that can enhance mental health and healthcare practices among pregnant women. The specific aims of this study were as follows: 1) To examine the general and obstetric characteristics of pregnant women and their prenatal education during the COVID-19 pandemic 2) To assess the levels of pandemic-related pregnancy stress, healthcare practices, and prenatal depression during the COVID-19 pandemic 3) To analyze the differences in these factors among pregnant women based on their general, obstetric, and prenatal education characteristics 4) To investigate the correlation between these characteristics, pandemic-related stress, healthcare practices, and prenatal depression 5) To determine the factors associated with prenatal depression among pregnant women during the COVID-19 pandemic

Methods Research design This cross-sectional, correlational study aimed to investigate the impact of prenatal education characteristics, pandemic-related pregnancy stress, and pregnancy healthcare practice behaviors on prenatal depression during the COVID-19 pandemic. This study adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines ( https://www.strobe-statement.org ). Participants Women aged 18 years or older, who were pregnant during the COVID-19 pandemic were recruited via online community posts through convenience sampling. The third trimester (28 weeks or more) was selected for participant selection, based on prior research [ 16 ] that indicated a higher prevalence of prenatal depression during this stage of pregnancy. The decision to concentrate on this group was further substantiated by the results of the Ministry of Health and Welfare's National Mental Health Survey for the second quarter of 2022. This survey showed a significant surge in depression rates during the COVID-19 outbreak in December 2021, with rates ranging from 18.1 to 22.8%, representing a more than fivefold increase from 2019 [ 17 ]. Therefore, it was deemed necessary to investigate depression in pregnant women during this critical period. Women who had difficulty with Korean language literacy or were under 28 weeks of pregnancy were excluded. The sample size was determined using the G*power 3.1.9.2 program, with a significance level of 0.05, a medium effect size of 0.15, a power of 0.85, and 15 predictors related to prenatal depression, general, obstetric, and prenatal education characteristics and the minimum sample size was determined to be 153 participants. The target was set at 180 participants to account for a potential 15% dropout rate [ 18 ]. As there were no incomplete or insufficient responses, the final analysis was conducted with a sample size of 180 (100%). Instruments Prenatal depression The investigators obtained permission to utilize the Korean version [ 19 ] of the Edinburgh Postnatal Depression Scale (EPDS) [ 20 ]. Although the EPDS tool was initially created to evaluate postnatal depression, it has been validated for use in measuring depression during pregnancy [ 21 ]. The tool is comprised of 10 items, each rated on a 4-point Likert scale. It evaluates symptoms such as depression, anxiety, and suicidal ideation experienced in the past week. Responses range from "not at all" (0 points) to "very much" (3 points). With the exception of items 1, 2, and 4, all items are scored in reverse. Higher scores (possible range: 0-30) indicate more severe prenatal depression and the cutoff for depression in Korean women was scores of 10 or higher [ 21 ]. The reliability was confirmed by a Cronbach's α value of .85 in a prior study with Korean women [ 19 ] and .86 in the present study. Pandemic-related pregnancy stress The Pandemic-related Pregnancy Stress Scale (PREPS) utilized in this study was adapted from the scale originally developed by Preis et al. [ 22 ] and subsequently translated into Korean by Kim and Heo [ 23 ], with the developer's permission. The scale comprises two subdomains: “perinatal infection stress (3 items)” and “preparedness stress (4 items).” Each item is rated on a 5-point scale (1 not at all, to 5 very much) and higher scores (possible range: 7-35) indicate greater pandemic-related pregnancy stress. Cronbach's α values for the original scale ranged from .68 to .86 [ 22 ]. The overall reliability of the seven items in the Korean version Cronbach's α of .87, with subdomain values ranging from .81 to .85 [ 23 ]. Cronbach's α was .92 for this study, with subdomain values between .85 and .91. Pregnancy healthcare practice behavior The 20-item Prenatal Healthcare Behavior Scale, originally developed by Wang et al. [ 24 ]and later revised and supplemented by Wang and Kim [ 25 ], was adapted with the developers' permission. The adapted version comprises 17 items in the following six subdomains: medication management (3 items), physical care/hygiene (4 items), prenatal care/education (2 items), activity/rest (3 items), nutrition management (3 items), and mental health (2 items). Each item is scored on a 5-point scale (1 not at all, to 5 very well) and higher scores (possible range: 17-85) indicate a higher level of pregnancy healthcare practice behavior. In previous research [ 25 ], Cronbach's α was .72, while in the current study Cronbach's α was .83. General, obstetric, and prenatal education characteristics General characteristics encompassed age, marital status, family structure, marital satisfaction, job loss, and income changes resulting from the COVID-19 pandemic. Obstetric characteristics included gestational age, prenatal checkups, parity, planned pregnancy, smoking and drinking habits during pregnancy, method of conception, high-risk pregnancy status, preferred sex of the fetus, desired childbirth method, alterations in childbirth plans due to the COVID-19 pandemic, self-quarantine experiences during pregnancy, changes in prenatal checkups, and COVID-19 diagnoses during pregnancy. Finally, prenatal education characteristics centered on the need for and interest in prenatal education, methods of acquiring prenatal information during pregnancy, preferred prenatal education methods and modes, changes in prenatal education participation due to the COVID-19 pandemic (including reasons for these changes), and the receipt of prenatal education during the pandemic. This last category also included reasons for not receiving education (if applicable), satisfaction with the received prenatal education, the number of prenatal education classes attended, and whether the participant was accompanied by a husband or guardian, if any. Data collection The data were collected via an online survey from July 5 to 15, 2022. The survey was disseminated through internet communities in Korea focused on pregnancy preparation, childbirth, and childcare. Emails were dispatched to the coordinators of these online communities, soliciting their help in data collection. An announcement about the survey, along with a link to the online questionnaire, was posted on the community boards. Access was granted only to those who agreed to participate in the study. Both the community boards and the online questionnaire clearly stated that participants could withdraw from the study at any time. Agreement to participate voluntarily, after reading the relevant information in the online questionnaire, was a prerequisite for participation in the study. The survey took approximately 15 minutes to complete. As a token of appreciation, participants who completed the survey received a mobile beverage voucher (worth approximately 5 US dollars) via text message within 14 days of completion. Data analysis SPSS for Windows ver. 27.0 (IBM Corp., Armonk, NY, USA) was used to analyze the data. Pregnant women’s general and obstetric characteristics, prenatal education characteristics, pandemic-related pregnancy stress, pregnancy healthcare practice behaviors, and prenatal depression during the COVID-19 pandemic were analyzed using frequency analysis and descriptive statistics. The differences in these factors among pregnant women based on their general, obstetric, and prenatal education characteristics were analyzed using the t-test, analysis of variance, the Mann-Whitney U-test, and the Kruskal-Wallis test, with post-hoc tests conducted using the Scheffé test. The correlations among these characteristics, pandemic-related stress, healthcare practices, and prenatal depression among pregnant women were analyzed using Pearson correlation coefficients. The factors that influenced prenatal depression among pregnant women during the COVID-19 pandemic were identified using multiple regression analysis.

Results General, obstetric, and prenatal education characteristics of participants Table 1 presents the general, obstetric, and prenatal education characteristics of the 180 participants. The average age of the participants was 32.22±2.86 years. A significant majority, 156 participants (86.7%), reported no job loss, while 127 participants (70.6%) indicated no change in their income due to the COVID-19 pandemic. The median gestational age of the participants was 31 weeks and 6 days. Most participants (n=156, 86.7%) did not alter their childbirth plans due to the pandemic and 119 participants (66.1%) did not undergo self-quarantine during their pregnancy. Furthermore, 134 participants (74.4%) reported no changes to their prenatal checkups, and 153 participants (85.0%) were not diagnosed with COVID-19 during their pregnancy. The most popular method of obtaining prenatal information was through the internet (blogs, online communities, YouTube), reported by 152 participants (84.4%) through multiple responses. Knowledge transfer and practice education were identified as the most preferred types of prenatal education by 140 participants (77.8%). Of the 46 participants (25.6%) who experienced changes in their prenatal education due to the pandemic, 29 (63%) stated that these changes were due to schedule alterations or cancellations by educational institutions, based on multiple responses. Among all participants, 96 (53.3%) received prenatal education during this period. Of the remaining 84 participants (46.7%) who did not receive education, the most frequently cited reason was “restrictions on gatherings due to social distancing,” reported by 45 participants (53.6%) through multiple responses. Pandemic-related pregnancy stress, pregnancy healthcare practice behavior, and prenatal depression The participants’ pandemic-related pregnancy stress was 24.50±6.37 (3.50±0.91 out of 5 points), which indicates a high level of stress. The mean score for preparedness stress (14.22±3.88; point average, 2.03±0.55) was slightly higher than for perinatal infection (10.29±3.09; point average, 1.47±0.40) ( Table 2 ). The overall mean score for pregnancy healthcare practice behavior was also high, at 67.07±9.20 (3.95±0.54 out of 5 points). The average score for prenatal depression was 8.85±5.31 and 91 participants (50.6%) fell within the normal range (0-9, mean, 4.51±3.12) whereas 89 participants (49.4%) were categorized as having depression (score of 10 or greater; mean, 13.28±2.86) ( Table 2 ). Differences in pandemic-related pregnancy stress, pregnancy healthcare practice behavior, and prenatal depression according to the participants’ characteristics The method of pregnancy (natural or not; Z=–2.01, p =.045) and changes in the childbirth plan due to the COVID-19 pandemic (Z=–3.62, p <.001) were identified as statistically significant factors influencing pandemic-related pregnancy stress, based on the obstetric characteristics. Regarding prenatal education characteristics, the need for prenatal education (χ 2 =22.51, p <.001), the preferred method of prenatal education (χ 2 =9.41, p =.009), modifications in prenatal education participation due to the COVID-19 pandemic (F=5.54, p =.005), and receiving prenatal education during the COVID-19 pandemic (t=3.49, p =.001) were also found to have statistically significant associations with pandemic-related pregnancy stress. Post-hoc analysis revealed that those who experienced changes in prenatal education due to the COVID-19 pandemic exhibited higher levels of pandemic-related pregnancy stress than those who did not ( Table 3 ). Based on the general and obstetric characteristics of the participants, several factors were found to significantly influence pregnancy healthcare practice behaviors. These factors include marital status (Z=–3.07, p =.002), family type (χ 2 =7.17, p =.028), marital satisfaction (χ 2 =18.94, p <.001), and changes in income due to the COVID-19 pandemic (t=2.13, p =.035). Other influential factors included prenatal checkup (Z=–4.28, p <.001), planned pregnancy (t=2.94, p =.004), smoking during pregnancy (Z=–2.62, p =.009), drinking during pregnancy (Z=–3.54, p <.001), high-risk pregnancy (Z=–2.46, p =.014), and experience of self-quarantine during pregnancy (t=–2.59, p =.010). In terms of prenatal education characteristics, the desired method of prenatal education (χ 2 =16.38, p <.001), the preferred mode of prenatal education (χ 2 =13.21, p =.001), changes in prenatal education participation due to the COVID-19 pandemic (F=3.41, p =.035), and receiving prenatal education during the COVID-19 pandemic (t=2.67, p =.008) were also found to have a significant impact on pregnancy healthcare practice behaviors. Post-hoc analysis revealed that participants who did not experience changes in prenatal education demonstrated higher levels of pregnancy healthcare practice behaviors than those who did ( Table 3 ). Statistical analysis revealed the following characteristics that were likely to significantly impact prenatal depression: family type (χ 2 =11.84, p =.003), marital satisfaction (χ 2 =11.79, p =.003), job loss due to the COVID-19 pandemic (Z=–2.21, p =.027), and changes in income as a result of the pandemic (t=–3.35, p =.001). Other influential factors were prenatal checkups (Z=–2.73, p =.006), whether the pregnancy was planned (t=–2.25, p =.026), alcohol consumption during pregnancy (Z=–2.48, p =.013), the desired sex of the fetus (t=–2.54, p =.012), and the preferred method of childbirth (χ 2 =6.37, p =.041). The experience of self-quarantine during pregnancy (t=3.26, p =.001) and changes in prenatal checkups due to the pandemic (t=2.27, p =.024) also showed a high likelihood of affecting prenatal depression. In terms of prenatal education characteristics, the preferred mode of prenatal education (χ 2 =6.79, p =.034) had a statistically significant association with prenatal depression ( Table 3 ). Correlations among the participants’ characteristics and main variables Prenatal depression in pregnant women showed a slight positive correlation with both gestational age (r=.18, p =.019) and stress related to the pandemic (r=.27, p <.001). Conversely, it demonstrated a moderately strong negative correlation with behaviors related to pregnancy healthcare practices (r=–.42, p <.001) ( Table 4 ). Factors associated with prenatal depression during the COVID-19 pandemic To identify factors influencing prenatal depression, we dummy-coded general and obstetric characteristics that demonstrated significant impacts. These included family type, marital satisfaction, job loss, changes in income, prenatal checkups, planned pregnancy, alcohol consumption during pregnancy, desired sex of the fetus, preferred childbirth method, self-quarantine experience during pregnancy, and changes in prenatal checkups. Additionally, the preferred mode of prenatal education, which fell under prenatal education characteristics, was also included. Alongside these, we included gestational age and key variables such as pandemic-related pregnancy stress and pregnancy healthcare practice behaviors, both of which showed a correlation with prenatal depression. As a result, a total of 15 independent variables were analyzed in the multiple regression analysis using the enter method. Moreover, the dummy variable for the preferred childbirth method (cesarean section) demonstrated multicollinearity with a tolerance limit value of 0.06 and a variance inflation factor (VIF) value of 18.04. This was also the case for the variable for the preferred childbirth method (natural delivery), which had a tolerance limit value of 0.06 and a VIF value of 17.93. Consequently, the dummy variable with the higher VIF value—specifically, the preferred childbirth method (cesarean section)—was removed prior to conducting the multiple regression analysis ( Table 5 ). The tolerance limit values for the independent variables fell within a range of 0.52 to 0.91, while the VIF values varied between 1.10 and 1.91. This suggests that multicollinearity was not an issue. The Durbin-Watson statistic registered at 1.81, nearing the standard of 2, but not approaching 0 or 4, thereby affirming the independence of errors. The resulting multiple regression model proved to be significant (F=7.14, p <.001), with the 15 independent variables accounting for 38.2% of the variance. Multiple regression analysis indicated that pandemic-related pregnancy stress (t=4.70, p <.001), marital dissatisfaction (t=3.66, p <.001), pregnancy healthcare practice behavior (t=–3.31, p =.001), being part of a weekend couple (t=2.84, p =.005), and advanced gestational age (t=2.32, p =.022) were all significant predictors of prenatal depression. This suggests that pregnant women who experienced higher levels of pandemic-related stress, marital dissatisfaction, and lower engagement in pregnancy healthcare practices, those who were part of a weekend couple, and those with a higher gestational age were more likely to experience prenatal depression. During the COVID-19 pandemic, it was found that among the variables influencing prenatal depression, pandemic-related pregnancy stress (β=.29) had the most significant impact.

Discussion The present study found that 49.4% of pregnant women experienced prenatal depression, as determined by a score of 10 or higher on the K-EPDS. This rate aligns with a previous study [ 26 ] conducted during the COVID-19 pandemic, which reported a high prevalence of 56.3% using the same tool and criteria. This high prevalence sharply contrasts with a 21.1% rate found in a pre-pandemic study [ 27 ] in Korea, suggesting a significant increase in prenatal depression during the pandemic. The current study identified various risk factors for prenatal depression, each with a distinct impact. These factors include family type, marital satisfaction, prenatal checkups, planned pregnancy, alcohol consumption during pregnancy, desired sex of the fetus, and preferred childbirth method. These findings align with previous research [ 28 , 29 ] on Korean pregnant women. Additionally, this study incorporated COVID-19-related variables such as job loss, changes in income, self-quarantine experience, and alterations in prenatal checkups, all of which were found to influence prenatal depression. Prior research [ 30 ] has underscored that prolonged self-quarantine and disrupted prenatal care due to the pandemic can exacerbate prenatal depression. The severity of depression significantly increased in both pregnant and nonpregnant women when self-quarantine exceeded 50 days. This highlights the need for policy discussions about suitable self-quarantine durations for pregnant women and the importance of monitoring their mental health during repeated outbreaks. Consequently, follow-up studies on prenatal depression based on the duration of self-quarantine are crucial. Moreover, 25.6% of participants experienced changes in their prenatal checkups due to the COVID-19 pandemic, and these women reported higher levels of prenatal depression than those who did not experience changes. However, another study [ 31 ] found that 37.1% of pregnant women were unable to receive regular checkups due to the pandemic, a rate higher than that observed in this study. Unplanned changes or cancellations in prenatal checkups can leave pregnant women feeling unprepared for childbirth, which can negatively impact their mental health and potentially lead to anxiety, stress, and both prenatal and postnatal depression [ 32 ]. Therefore, it is crucial to emphasize the importance of consistent prenatal checkups during infectious disease outbreaks to help pregnant women maintain their mental health. This study also discovered that pregnant women reported increased levels of prenatal depression during the COVID-19 period when they encountered heightened pandemic-related pregnancy stress, diminished marital satisfaction, insufficient pregnancy healthcare practices, were part of a weekend couple, and were at a more advanced gestational age. These variables accounted for 38.2% of the variation in prenatal depression. Drawing on these findings, this study examined the influence of each factor on prenatal depression, proposed policy implications to tackle these issues, and suggested practical solutions for pregnant women. Pandemic-related stress during pregnancy was identified as the most significant factor contributing to an increase in prenatal depression, a finding that aligns with previous research [ 6 , 33 ]. This specific type of stress, distinct from typical pregnancy stress, emerged as a major predictor of prenatal depression during the pandemic in this study. Notably, the incidence of prenatal depression was found to be twice as high during the pandemic as compared to pre-pandemic levels, suggesting that the pandemic itself has intensified depression symptoms. Moreover, both objective stressors, such as changes in prenatal checkups, financial difficulties, and unemployment, and subjective stressors, such as fear of COVID-19 infection and limited support during childbirth, have contributed to the heightened depression among pregnant women. In particular, higher levels of subjective stress were closely associated with more severe depression symptoms [ 6 ]. Additionally, variations in pandemic-related pregnancy stress were observed in relation to changes in childbirth plans due to the pandemic and pregnancies resulting from infertility treatments. This observation aligns with previous studies that employed similar methodologies [ 22 , 34 ]. Pregnant women infected with COVID-19 faced limited childbirth options, which escalated their fear and stress, potentially leading to PTSD [ 35 ]. Therefore, it is crucial to ensure that pregnant women have the right to make choices during childbirth in order to reduce stress during such crises. Women who became pregnant through infertility treatments experienced intense stress from the onset of their pregnancy. Concerns about treatment interruptions and delays during the pandemic [ 36 ], as well as the potential for decreased fertility due to infection [ 37 ], further exacerbated their depression and stress [ 36 ]. In response, policy discussions are needed to ensure the continuity of infertility treatments through medical insurance [ 36 ] and to incorporate prenatal care into emergency medical systems during pandemics. Previous research has shown that stress associated with childbirth and postpartum care significantly impacts prenatal depression during a pandemic [ 33 ]. Therefore, it is imperative to expand support and resources in prenatal care systems and to enhance pregnant women’s capabilities through prenatal education [ 33 ]. In addition, mindfulness interventions, particularly those delivered via mobile apps, have proven effective in reducing stress and alleviating prenatal depression during prolonged periods of infectious disease outbreaks. These interventions also provide high accessibility to mental health information and are well-accepted by pregnant women [ 38 ]. Therefore, developing digital health stress management programs that are readily available to pregnant women at any time and place, would be helpful in preparation for recurring infectious diseases. In the current study, the second most influential factor on prenatal depression during the pandemic was identified as pregnancy healthcare practice behavior, aligning with previous research [ 10 , 39 ]. The extent of these behaviors appears to be influenced by factors such as marital status, family structure, marital satisfaction, self-quarantine experience during pregnancy, and income changes due to the COVID-19 pandemic. These factors are also linked to the social support provided by family members, suggesting that their emotional and material assistance significantly impacts how pregnant women manage their healthcare practices during the pandemic. Typically, pregnant women receive more social support from family and relatives than from friends. Adequate family support has been shown to positively influence health-promoting behaviors [ 40 , 41 ], a finding supported by prior research. This study also discovered that pandemic-related income changes affected pregnancy healthcare practice behaviors. This aligns with another study [ 40 ] that found insufficient income negatively impacts women’s health-promoting behaviors. Moreover, a household trend survey in Korea [ 42 ] confirmed that the pandemic has led to a decrease in income and an increase in unemployment, which in turn influences changes in household income. Therefore, identifying the material, emotional, and economic support available to pregnant women from family and friends during a pandemic situation and establishing measures to ensure that pregnant women can avoid deficiencies during self-quarantine and maintain their healthcare practices, can be helpful preventive measures against prenatal depression. In this context, promoting healthcare practices among pregnant women during the pandemic is of particular importance. For instance, providing virtual reality-based prenatal group exercise programs tailored to their altered lifestyles can positively impact their bonding with other pregnant women [ 43 ]. Prenatal depression was significantly influenced by marital satisfaction, which aligns with previous research [ 7 ]. Lower marital satisfaction, which often results in less support from husbands, has been reported as associated with an increase in prenatal depression [ 7 ]. This study also found that being a weekend couple, as opposed to living in a large or nuclear family, seemed to result in less support from husbands, which in turn influenced prenatal depression. However, a pre-COVID-19 study [ 7 ] found that prenatal depression was twice as prevalent in large families living with parents compared to nuclear families. This suggests the need for further research on family size and weekend couples, especially during pandemic situations. Given that an increase in domestic conflicts and violence were attributed to factors such as unemployment, school closures, and social isolation during the pandemic [ 44 ], such factors may likely influence pregnant women's marital satisfaction and should be considered for future research. Finally, this study identified a correlation between advanced gestational age and prenatal depression, a finding that aligns with prior research [ 16 ]. All participants in this study were in their third trimester and exhibited an increase in prenatal depression as their gestational age progressed. Given that the third trimester is a crucial phase for the onset of prenatal depression, largely due to heightened physical and psychological stress [ 16 ], greater attention is required as pregnancy progresses, to facilitate early identification and efficient treatment of prenatal depression. The current study revealed a relatively high level of pandemic-related pregnancy stress, and subscores of 2.03 for stress related to preparedness and 1.47 for perinatal infection. Using the same measurement, higher average scores were reported in prior studies: a US study [ 22 ] reported an average score of 3.36 for both subcategories, while an Italian study [ 45 ] reported scores of 2.75 and 2.59 for preparedness and perinatal infection stress, respectively. Interestingly, participants in our study experienced less pandemic-related pregnancy stress. This discrepancy may be due to the timing of the study. The US study [ 22 ] was conducted during a period of rapidly increasing COVID-19-related deaths [ 46 ], and the Italian study [ 45 ] took place during a second wave of the pandemic. In contrast, our study in Korea was carried out during a phase of relaxed social distancing measures [ 17 ] and COVID-19 transitioning to an endemic phase. This context may account for the lower stress levels observed among our Korean participants compared to those in the previous studies. This also suggests that as time passed, the level of stress experienced during the pandemic gradually decreased, indicating that people have been adapting to the new normal [ 47 ]. However, it is important to note that the various traumas experienced during the pandemic could potentially lead to depression or post-pandemic stress disorder even after the pandemic has ended [ 48 ]. Therefore, despite the lower levels of pandemic-related pregnancy stress observed among pregnant women in Korea, it is premature to be complacent, monitoring the trends of pregnancy stress as the pandemic concludes and in the subsequent periods would be beneficial. The high level of pregnancy healthcare practice behaviors in this study (67.07 points) is comparable to the level reported in a pre-COVID-19 study in Korea [ 25 ], which recorded an average score of 63.47 to 65.32 using the same evaluation tool. Contrary to expectations that social distancing and isolation would decrease pregnancy healthcare practice behaviors, no such reduction was observed. Interestingly, pregnant women who did not experience social distancing exhibited higher healthcare practice behaviors than those who did. Moreover, women who received prenatal education during the COVID-19 pandemic demonstrated superior healthcare practices compared to those who did not. However, considering that only 33.9% of participants experienced social distancing and 53.3% received prenatal education during the pandemic, these factors did not significantly impact the overall level of the behaviors. Pregnant women who receive professional prenatal education, equipped with accurate prenatal knowledge, can enhance their self-care abilities and healthcare practice behaviors. While face-to-face education was previously the standard, recent advancements in digital technology and the proliferation of infectious diseases have led to the introduction of web- or mobile-based prenatal education programs [ 25 , 49 ]. In light of this, the aim of this study was to investigate the evolving needs and current status of prenatal education for pregnant women during the pandemic. Despite social distancing, self-quarantine, and public facility closures, 53.3% of participants had attended at least one prenatal education session. This is similar to the 53.7% reported in a pre-pandemic study [ 50 ]. Regardless of the outcome, a significant 87.2% of participants expressed a need for prenatal education, a figure that substantially exceeds the participation rate. The average interest in prenatal education was around 8 out of 10 points, indicating a significant surge in demand during this period. The primary reasons for not receiving prenatal education were “social distancing” and a “lack of information about when and where the education was available,” suggesting that pandemic-related restrictions were the main obstacles to receiving education. The internet emerged as the primary source of prenatal information for pregnant women during the COVID-19 pandemic, accounting for 84.4% of all information sources, compared to 30.0% before the pandemic [ 51 ] and 82.4% just prior to the pandemic [ 52 ]. This indicates an increased dependence on the internet for information. During the pandemic’s peak in Korea, there was a significant decrease in the number of patients and visits to hospitals or clinics compared to the period before the outbreak. This led to a potential decrease in health services provided by primary healthcare facilities [ 53 ], and pregnant women may not have received sufficient prenatal information from health professionals, leading to a natural increase in their reliance on the internet. However, the reliability of internet information can be questionable [ 54 ], and the information available may not always cater to the specific needs of pregnant women [ 55 ]. Therefore, it is crucial to devise policy-level strategies to improve the digital health literacy of pregnant women. This will enable them to effectively search for, understand, and assess the reliability of online prenatal information [ 56 ]. Given the recurring nature of infectious diseases, it is imperative for clinical experts to focus on developing strategies that can positively influence pregnant women’s reliance on the internet for prenatal information. This study also found that the level of prenatal depression was associated with the desired prenatal education mode. Pregnant women who favored face-to-face prenatal education exhibited higher instances of prenatal depression. This can be attributed to the fact that these women seek more than just information from their education; they also crave empathy and emotional support, which they find through bonding with other expectant mothers in similar circumstances [ 55 ]. However, online prenatal education may not provide the same opportunities for forming these emotional connections, potentially leading to feelings of isolation [ 57 ]. Before the pandemic, prenatal education in Korea was primarily conducted in person at public health centers. While online prenatal education can serve as an effective intervention for prenatal depression during a pandemic, it may not fully address the psychological and emotional needs that are met through social interactions. Consequently, further research is needed to develop effective online prenatal education programs that can be utilized during pandemic conditions. Based on the findings of this study, the factors that significantly impacted prenatal depression included pandemic-related pregnancy stress, marital satisfaction (or lack thereof), pregnancy healthcare practices, family type (specifically, weekend couples), and gestational age. However, as this study focused solely on women in their third trimester, the results may not be directly applicable to those in their first or second trimesters. Additionally, the survey used to assess prenatal education was conducted in a straightforward question-and-answer format, which limited the ability to provide a comprehensive overview of prenatal education practices during the pandemic. The factors associated with prenatal depression also had a relatively low explanatory power of 38.2%. This could be due to the fact that unlike previous research conducted in Korea during the pandemic [ 16 ], this study did not specifically analyze pregnant women with a history of depression or those currently experiencing depression during pregnancy. Despite these limitations, the study’s significance lies in its examination of the changing phenomena by analyzing each variable of pandemic-related pregnancy stress and pregnancy healthcare practices in relation to the characteristics of pregnant women and their prenatal education. The study also provides foundational data for the development of various prenatal education programs aimed at promoting mental health in pregnant women in preparation for future infectious diseases. It further underscores the need for strategies to reduce pregnancy stress and improve pregnancy healthcare behaviors. In conclusion, prenatal depression among pregnant women during pandemics like COVID-19 is a serious issue that necessitates immediate evaluation and treatment. Because prenatal depression often intensifies in the later stages of pregnancy, interventions that are both timely and tailored to the pregnancy stage are essential. It is critical to acknowledge stress and healthcare practice behaviors as significant influences on prenatal depression during the COVID-19 pandemic. Therefore, monitoring and managing these factors among pregnant women is crucial, particularly in the face of recurring infectious diseases. Consequently, national and healthcare policies, as well as active interventions, are required to address these issues.

Purpose This study investigated the effects of prenatal education characteristics, pandemic-related pregnancy stress, and health behaviors during pregnancy on prenatal depression in pregnant women during the coronavirus disease 2019 (COVID-19) pandemic. Methods The participants were 180 pregnant Korean women, recruited from internet communities for pregnancy preparation, childbirth, and childcare, from July 5 to 15, 2022. The collected data were analyzed using the t-test, analysis of variance, the Mann-Whitney U-test, the Kruskal-Wallis test, and multiple regression analysis. Results The scores for pandemic-related pregnancy stress (24.50±6.37) and health behaviors during pregnancy (67.07±9.20) were high. Nearly half of the participants (n=89, 49.4%) presented with prenatal depression, with scores of 10 or greater. Prenatal depression had a positive correlation with gestational age (r=.18, p =.019) and pandemic-related pregnancy stress (r=.27, p <.001), and a negative correlation with health behaviors during pregnancy (r=–.42, p <.001). The factors associated with prenatal depression were pandemic-related pregnancy stress (t=4.70, p <.001), marital satisfaction (dissatisfied) (t=3.66, p <.001), pregnancy healthcare practice behaviors (t=–3.31, p =.001), family type (weekend couple) (t=2.84, p =.005), and gestational age (t=2.32, p =.022). The explanatory power of these variables was 38.2%. Conclusion Since participants had a high level of prenatal depression during the pandemic, and infectious diseases such as COVID-19 may recur, strategies should be developed to improve pregnant women’s mental health with consideration of the unique variables that are relevant in a pandemic. It is also necessary to develop efficient online prenatal education programs that can be implemented even in special circumstances such as social distancing, and to evaluate their effectiveness. Summary statement

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):274-290

oa_package/68/9e/PMC10788393.tar.gz

PMC10788394

38204387

Introduction Since South Korea’s total fertility rate dropped below the replacement level of two children per woman in 1985, it has fluctuated between one and just under two. In 2008, the rate was 1.19, but it reached a historic low of 0.92 in 2019, followed by 0.78 in 2022. The number of births in 2022 was particularly low at 249,100, making it a challenge to sustain numbers in the 300,000 range [ 1 ]. The domestic number of births also saw a significant decline of 37% from 434,169 in 2015 to 273,292 in 2020. Meanwhile, the number of obstetrics and gynecology hospitals and maternity hospitals—key facilities for childbirth—initially increased from 13 to 20, but then dropped to 15 by 2020. Furthermore, the number of births in maternity hospitals fell from 1,676 in 2013 to just 668 in 2020 [ 2 ]. This decline has put the profession of midwives, who focus on childbirth preparation, in jeopardy. Midwives are specialized healthcare professionals who have been instrumental in improving public health and promoting healthy lifestyles through guidance on childbirth, as well as prenatal and neonatal care [ 3 ]. Their responsibilities encompass childbirth preparation, managing the various stages of labor (stages 1 through 4), providing postpartum care for newborns, and performing resuscitation on infants who experience asphyxiation. In the realm of postpartum care, midwives oversee breastfeeding support and care for high-risk postpartum conditions. For newborns, they conduct health assessments and offer education and counseling [ 4 ], thereby extending the scope of maternal nursing. Midwives have also been at the forefront of advocating for natural childbirth methods, minimizing unnecessary medical interventions, and empowering women to take charge of their bodies during labor, which contributes to more positive childbirth experiences [ 5 ]. However, South Korea’s record-low fertility rate has led to a situation where midwives are unable to fulfill their vital roles, putting them at risk of losing their jobs and highlighting the need to reassess their professional roles. In various countries, in anticipation of changes in childbirth environments, guidelines for midwifery practices have been developed to explore the expanded roles of midwives across multiple aspects. In Sweden, midwives have broadened their scope of responsibilities to include tasks such as dressing cesarean section incisions, as well as duties related to family planning and counseling adolescents [ 6 ]. In the United Kingdom, midwives address health issues including domestic violence, sexual assault, mental disorders, and substance abuse. They conduct home visits, monitor the health and safety of children, assess parenting skills, and provide referrals to relevant agencies when intervention is necessary [ 7 ]. Canadian midwives offer pregnancy and parenting services, facilitate information exchange among expectant mothers, and integrate these efforts into the local community [ 8 ]. These countries emphasize the importance of expanding the scope of midwives’ roles to include the responsibilities typically associated with specialized nurses, underscoring the capability of midwives as healthcare professionals who can provide primary nursing care. By standardizing midwifery practices and extending the unique responsibilities of midwives to serve all community members, these nations are establishing a healthcare system where midwives can effectively perform specialized roles. Anticipating changes in the role of midwives in Korean society, we examined the actual tasks performed by midwives. Our study involved analyzing job experiences in maternity hospitals [ 5 ], developing guidelines for community-based midwives [ 9 ], and researching job satisfaction among midwives in both hospitals and maternity hospitals [ 10 , 11 ]. Additionally, we have investigated ways to expand the role of midwives through studies on strengthening the midwifery training system [ 12 ] and broadening their scope of practice [ 13 ]. Midwives are healthcare professionals capable of independently conducting medical procedures in maternity hospitals [ 3 ], and as nurse-midwives, they also fulfill a dual role in nursing and medical procedures within obstetrics and gynecology-related healthcare settings. Consequently, by examining the perceptions of nurses and midwives, we aim to compare the perceived importance and actual frequency of midwives’ roles to identify areas that may require modification and enhancement [ 14 ]. Through this research, we aim to provide foundational data by identifying the perceived differences in the roles of midwives between nurses and midwives themselves. This data will help to broaden the scope of midwives’ roles in the community, in accordance with the responsibilities outlined in medical laws for midwifery and health guidance for pregnant women and newborns [ 3 ]. Furthermore, we plan to delineate areas where the expansion of midwives’ roles is warranted. The purpose of this study was to identify the perception and performance of midwives’ roles among midwives and nurses, with the ultimate goal of finding strategies for expanding the roles performed by midwives. The specific objectives were as follows. 1) To understand the perception and performance of midwives’ roles among midwives and nurses. 2) To compare differences in the perception and performance of midwives’ roles among midwives. 3) To explore the relationship between the perception and performance of midwives’ roles among midwives and nurses.

Methods Study design This study employed a descriptive correlational research design to assess the perception and performance of midwives’ roles among midwives and nurses. The structure and content of this study are described following research reporting guidelines, adhering to the order of the STROBE checklist ( https://www.strobe-statement.org/ ). Participants The study participants comprised midwives enrolled in the Korean Midwifery Association, as well as midwives and nurses (non-midwives) employed at two women’s specialty hospitals in Daegu and at two university hospitals that have introduced women’s healthcare services in the Gyeonggi region. Eligibility was determined based on understanding and acceptance of the study’s purpose. The specific inclusion criteria were as follows. 1) Hold a license as a midwife or nurse (non-midwife). 2) Clearly understand the researcher’s explanations and agree to participate in the study. The specific exclusion criteria were as follows. 1) Individuals with health conditions preventing them from reading and understanding the study questionnaire. 2) Individuals with self-reported diagnoses or experiences of depression or other mental health disorders, making their judgment unclear. 3) Individuals with a nursing license but no work experience. The sample size for the study was calculated using G*Power version 3.15. Drawing from a prior investigation into the roles of hospital and maternity hospital midwives [ 15 ], the required sample size for two groups was determined based on an independent t-test. With a significance level set at 0.05, a medium effect size of 0.15, and a desired statistical power of 0.80, the minimum number of participants needed was 168. This study’s participants were drawn from two regions and four medical institutions, as well as from the 677 registered members of the Midwives Association. Given that a previous study on midwife core competency development, which included 681 midwives, yielded only 20% usable data [ 4 ], we aimed to include a comparable 20% of the registered midwives in the association for our sample. This approach resulted in a target group of 130 midwives and a total of 260 participants. Ultimately, 243 participants’ data were included in the final analysis. Study tools Perception of midwives’ roles The tool designed to assess the perception of midwives’ roles included 64 items across eight sub-domains and was originally developed by Yu [ 15 ]. We obtained permission from the developer to use the tool, which we then modified and expanded to meet the specific objectives of our study. To evaluate the content validity of the tool, we conducted a comprehensive review of both domestic and international literature on the roles of midwives, analyzed the job descriptions provided by the Korean Midwives Association, and sought content validity confirmation from three professors with expertise in women’s health nursing and 10 seasoned midwives, each with over a decade of experience. Following these steps, the tool was refined to contain 60 items within seven domains: antenatal care (18 items), intrapartum care (15 items), psychological support (three items), postpartum care (five items), neonatal care (five items), women’s health care (nine items), and management (five items). These domains were selected to gauge the perceived importance of each role. The tool employed a 5-point Likert scale, ranging from “not important” (1 point) to “very important” (5 points), allowing for total scores between 60 and 300. A higher score reflected a greater perceived importance of the role. In prior research, the tool demonstrated a Cronbach’s α value of .92 [ 15 ]. In the current study, the Cronbach’s α value reached .99, indicating excellent internal consistency. The Cronbach’s α values for the individual domains were as follows: antenatal care, .97; intrapartum care, .95; psychological support, .98; postpartum care, .98; neonatal care, .98; women’s health care, .98; and management, .95. Role performance of midwifery The tool for assessing the performance of midwives’ roles included the same items as the role perception tool developed by Yu [ 15 ]. Its content validity was established through a review of both domestic and international literature on midwives’ roles, as well as the job analysis table provided by the Korean Association of Midwives. This tool employs a Likert 5-point scale, with responses ranging from “always do” (5 points) to “never do at all” (1 point). The total score can range from 60 to 300, with higher scores indicating a greater frequency of role performance activities as perceived by the respondents. In previous research, the Cronbach’s α was reported as .92 [ 15 ], while in the current study, it was found to be .97. The Cronbach’s α values for each domain were as follows: antenatal care, .95; intrapartum care, .90; psychological support, .96; postpartum care, .94; neonatal care, .94; women’s health care, .87; and management, .87. General characteristics General characteristics included age, education level, occupation, type of workplace, workplace location, and work experience, comprising six items in total. Data collection Data collection occurred between April 1 and June 25, 2021. The study was advertised on the Korean Midwifery Association’s bulletin board and nurses and midwives who were attending continuing education sessions at hospitals in Gyeonggi Province and Daegu were also invited to participate. Data collection at hospitals required obtaining permission from the institutions and making in-person visits. The researcher detailed the study’s objectives to the participants, provided them with the opportunity to review the survey, and collected signed consent forms from those who chose to participate. Completing the survey took roughly 10 to 15 minutes, and participants received small gifts (hand sanitizer and masks for coronavirus disease 2019 [COVID-19] protection) upon completion. The completed surveys were immediately collected and securely stored in a location accessible only to the researcher. Data analysis The collected data were analyzed using IBM SPSS for Windows, ver. 20.0 (IBM Corp., Armonk, NY, USA). Differences in the perception of midwives’ roles between midwives and nurses, as well as differences in frequency of role performance, were analyzed using the independent sample t-test. Differences in the perception and performance of midwives’ roles among midwives were analyzed using the independent sample t-tests, and in cases where homogeneity of variance was not supported, Welch-Aspin test values were utilized. The relationship between the perception and performance of midwives’ roles among midwives and nurses was assessed using Pearson correlation coefficients.

Results General characteristics of participants Among the 243 participants, there were 79 midwives (11.7% of 677 registered midwives) and 164 nurses (non-midwives). The average age of the midwives was 46.0 years, compared to 38.2 years for the nurses. The largest age group for both the midwives and nurses was those in their 40s, representing 41.8% and 34.1% of their respective groups. Regarding educational attainment, the majority of midwives were 4-year university graduates (41.8%) and graduate school graduates (38.0%). In contrast, the nurses were predominantly 4-year university graduates (48.2%) and vocational school graduates (31.1%). The midwives were predominantly employed in general hospitals, clinics, tertiary hospitals, and private practices. The nurses most commonly worked in tertiary hospitals and general hospitals. When it came to professional experience, the largest group of midwives had 10 to less than 20 years of experience (40.5%), while the largest group of nurses had less than 10 years of experience (37.1%) ( Table 1 ). Perception of midwives’ roles among midwives and nurses For the perception of midwives’ roles midwives scored 208.74 points and nurses scored slightly higher at 235.05 points. In an analysis of average scores by area, midwives had the highest role perception score for antenatal care (3.55±1.45), followed in descending order by intrapartum care (3.54±1.25), and postpartum care (3.54±1.60). Nurses had the highest role perception score for neonatal care (4.26±1.01), followed in descending order by postpartum care (4.22±1.02), and psychological support for changes (3.80±0.98). In antenatal care, both midwives and nurses identified referring high-risk pregnant women to a specialist (3.71±1.72 and 4.83±1.01, respectively) as the most important role of a midwife. Midwives, however, placed more emphasis on fetal heart auscultation (3.68±1.74) and assessing fetal movement (3.67±1.67), while nurses focused on educating about pain management during childbirth (4.31±0.97) and referring to a specialist upon detecting abnormal conditions in pregnant women (4.30±1.02). During intrapartum care, both groups agreed that referring to a specialist in cases of abnormal labor and dystocia (3.71±1.69 and 4.43±1.01, respectively) was an important role of midwives. Midwives gave higher priority to performing maternal cardiopulmonary resuscitation (3.80±1.59), whereas nurses emphasized the importance of family support in implementing intrapartum pain management (4.31±0.99). In providing psychological support for changes, midwives viewed offering emotional support to prevent postpartum depression (3.52±1.62) as their primary role. Nurses, in contrast, saw informing and counseling about postpartum depression reactions (4.33±0.99) as the most important. For postpartum care, education and counseling on postpartum care (3.58±1.67) were seen as essential by both midwives and nurses. Midwives added early detection, diagnosis, and treatment of postpartum complications (3.61±1.64) to their list of roles, while nurses focused on educating about prevention and self-care methods for postpartum complications (4.29±1.04) and the immediate reporting of symptoms (4.27±1.05). In neonatal care, assessing newborn health (3.65±1.75 and 4.42±1.04, respectively) and providing education and guidance on breastfeeding (3.57±1.72 and 4.25±1.09, respectively) were recognized as midwife roles by both midwives and nurses. Regarding women’s health care, counseling and referring sexual violence victims to specialized agencies (3.28±1.59 and 3.55±1.28, respectively) were considered primary midwife roles by both midwives and nurses. Midwives also included education on normal adolescent menstruation and healthy lifestyle patterns (3.29±1.59) as part of their role, while nurses considered counseling on premarital pregnancy and referrals to specialized agencies (3.57±1.25). In management, document management (3.53±1.72 and 3.81±1.21, respectively) and environmental management (3.47±1.69 and 3.80±1.20, respectively) were prioritized as primary midwife roles by both midwives and nurses ( Table 2 ). Frequency of midwives’ role performance as perceived by midwives and nurses The perceived frequency of role performance was reported to be 181.69 points by midwives and 201.10 points by nurses. When examining the average scores by area, midwives ranked their role performance frequency in the following order: neonatal care (3.29±1.38), antenatal care (3.19±1.05), intrapartum care (3.19±0.78), and postpartum care (3.19±1.25). Conversely, nurses ranked midwives' role performance frequency as follows: neonatal care (3.74±1.13), postpartum care (3.59±1.15), antenatal care (3.53±0.92), and intrapartum care (3.44±0.93). In antenatal care, both midwives and nurses reported frequently performing roles such as assessing fetal movement, with midwives scoring 3.74±1.13 and nurses scoring 3.80±1.32. Midwives also identified fetal heart auscultation (3.58±1.75) and education on the importance of antenatal examinations and counseling (3.39±1.50) as key roles. Nurses, on the other hand, emphasized the frequent use of intrapartum pain control (3.87±1.15) and the referral of high-risk pregnant women to specialists (3.86±1.22). During intrapartum care, both groups noted a high frequency of role performance in using Doppler for fetal heart rate measurement, with midwives scoring 3.65±1.68 and nurses scoring 3.93±1.28. Midwives added intravenous injection for vascular access in emergencies (3.53±1.63) as an additional role, whereas nurses focused on supporting and encouraging mothers and families using pain control methods (3.94±1.12) and providing emergency treatment and referrals to specialists for abnormal labor and dystocia prediction (3.93±1.27). In the realm of psychological support for changes, midwives prioritized providing care to prevent postpartum depression (2.90±1.32), while nurses placed importance on informing mothers and families about postpartum psychological changes, including depression (3.45±1.23). Postpartum care engaged in education and counseling was common in both groups, with midwives scoring 3.42±1.55 and nurses scoring 3.70±1.25. Similarly, in neonatal care, both groups reported high role performance frequency in assessing newborn health, with midwives scoring 3.49±1.75 and nurses scoring 4.02±1.20. In women’s health care, midwives frequently performed roles such as early diagnosis of uterine cancer through Pap tests (2.56±1.47), education and management of elderly women (2.44±1.37), and participation in community programs or research (2.44±1.47). Nurses reported a high frequency of counseling and guidance on adolescent sexual education (2.69±1.23) and education on normal adolescent menstruation and healthy lifestyle patterns (2.67±1.22). In management tasks, both midwives and nurses indicated a high frequency of role performance in document management, with midwives scoring 3.05±1.59 and nurses 3.39±1.30, and in environmental management, with midwives scoring 2.87±1.50 and nurses 3.40±1.30 ( Table 3 ). Difference in midwives’ perception and performance of midwives’ roles The gap between midwives’ role perception and their performance was 27.05 points, with higher role perception than role performance. When examining the average scores by domain, the greatest disparity between perception and performance was observed in women’s health care, with a difference of 0.84 points. This was followed by psychological support during changes at 0.68 points, management at 0.55 points, antenatal care at 0.36 points, intrapartum care at 0.35 points, postpartum care at 0.35 points, and neonatal care at 0.24 points, as detailed in Table 4 . Correlation between midwives’ role perception and role performance There was a moderate positive correlation between midwives’ role perception and role performance (r=.617, p <.001), as well as between nurses’ role perception and role performance (r=.648, p <.001). Both midwives and nurses had higher scores for role perception than for role performance.

Discussion In terms of the importance of the seven areas of midwives’ roles, midwives prioritized antenatal care as the most crucial role, followed by intrapartum care and postpartum care. In contrast, nurses perceived neonatal care as the most important role of midwives, followed by psychological support for changes and postpartum care. There were differences in the ranking of the importance of midwives’ roles between midwives and nurses. However, regarding the frequency of role performance, both midwives and nurses reported high frequencies for neonatal care and postpartum care. In antenatal care, nurses recognized the importance of educating expectant mothers on various topics, including antenatal examinations, breast care, nutrition, personal hygiene, and the significance of prenatal education. They also provided counseling on methods for pain control during childbirth, discussed the roles of family members, and assessed the emotional well-being and potential high-risk states of pregnant women, reporting any concerns to a specialist. This underscores the educational responsibilities of midwives, aligning with research that confirms their active engagement in these antenatal educational activities [ 16 ]. In Sweden, midwives play a comprehensive role in antenatal care, which extends to conducting ultrasounds, health assessments, and providing guidance on exercise and nutrition. They also offer parenting education, thereby enhancing women’s nursing competencies through the promotion of education, information, and overall health [ 6 ]. This broad scope of practice highlights the critical educational function of midwives in antenatal care and corroborates the findings of this study [ 17 ]. In managing labor, nurses acknowledged the significant role of midwives in various tasks, including administering intravenous injections, utilizing labor-inducing agents and uterine contraction stimulants, providing pain relief medication, monitoring fetal heart rates, promoting and facilitating intrapartum pain control educating patients about antibiotic use, and consulting with specialists in cases of abnormal childbirth and dystocia. Apart from intravenous injections, midwives are also recognized for performing house calls to adjust episiotomies for childbirth. These responsibilities, with the exception of administering analgesics, are typically included in midwifery care for natural childbirth at maternity centers [ 9 ]. Midwives advocate for hospital births to provide multidimensional care. In instances of abnormal childbirth and dystocia, they collaborate with specialists to transfer patients to the hospital, ensuring the safety of natural childbirth [ 16 ]. Although labor management is closely associated with midwifery as defined by medical laws, the ability to perform these roles is hindered by declining birth rates [ 1 ] and an increase in hospital deliveries [ 2 ]. Consequently, there is a pressing need to evaluate the role of Korean midwives in labor management and consider ways to expand their responsibilities. Regarding psychological change support, nurses perceived midwives as playing a more crucial role than how midwives perceived it themselves in educating mothers and families about postpartum depression, as well as in counseling, care, early detection, and referral to specialists. This perception is reinforced by the fact that, in Sweden, midwives are tasked with responsibilities related to postpartum depression [ 6 ], and in the United Kingdom, they address health issues associated with mental disorders [ 7 ]. The awareness of healthcare professionals regarding the management of psychological changes could provide a foundation for broadening the scope of midwives’ roles in Korea. In postpartum care, healthcare professionals recognize that midwives play a multifaceted role. This included family planning, providing education on postpartum care, preventing and managing postpartum complications, educating patients about the symptoms of complications, and facilitating the early detection, diagnosis, and treatment of these complications. Furthermore, midwives were also recognized as being responsible for offering family planning counseling and educating new mothers on recognizing complication symptoms and the importance of reporting them. In neonatal care, healthcare professionals recognized midwives’ roles in assessing newborn health, educating parents on breastfeeding, providing guidance on formula feeding, advising on neonatal infection management, and counseling on infant safety. It is understood that midwives fulfill these responsibilities, with the exception of breastfeeding education and guidance. The areas of postpartum and neonatal care are encompassed within the broader scope of maternal health and well-being as defined by medical law [ 3 ]. This is true not only for midwives in Korea but also for their international counterparts who have long been engaged in these practices. For instance, in Sweden, midwives carry out these duties in maternity centers, whereas in the United Kingdom, they make home visits to assess parenting skills and offer support. In Canada, midwives play a pivotal role in fostering communication among expectant mothers within the community, and in Turkey, they leverage expertise and scientific platforms to implement these services, demonstrating a diversity of methods even within similar roles [ 18 ]. The fact that different countries adopt various strategies to enhance the effectiveness of comparable roles underscores the importance of continuous professional development for Korean midwives. This need is particularly pressing in light of the recent COVID-19 crisis and the advent of the “new normal,” as well as the challenges presented by a declining birth rate. In the realm of women’s health care, nurses viewed midwives as pivotal in educating and guiding adolescents about normal menstrual cycles and healthy lifestyles. They are also seen as key providers of counseling and guidance on adolescent sexual education and as first responders in offering support to victims of sexual violence, including making referrals to specialized institutions. When it comes to management, nurses noted that midwives play a more significant role in environmental management than the midwives perceive themselves to have. Women’s health care is an integral part of primary healthcare. This is consistent with the duties of Swedish midwives, who provide sexual education to elementary students and adolescents, offer guidance on contraception, counsel on mental health disorders, and assist with issues of maladjustment in school life [ 6 ]. Furthermore, the roles of United Kingdom midwives in managing health issues related to domestic violence, sexual violence, mental disorders, and substance abuse are in line with the findings of this study [ 7 , 19 ]. Environmental management refers to healthcare professionals taking into account the hospital setting when considering patient care. Park et al. [ 18 ] suggested that the choice of expectant Korean mothers to deliver in hospitals is influenced by factors such as access to modern medical equipment and rigorous infection control, rather than the childbirth expertise of midwives. Despite this preference, satisfaction with hospital medical services remains low. Women are increasingly opting for maternity centers over hospitals to avoid issues like meconium-stained amniotic fluid, trauma, infection, and other health complications associated with hospital births. Additionally, maternity centers are favored for their more humane approach and fewer unnecessary interventions, allowing women to play a more active role in their childbirth experience [ 20 ]. This trend underscores the effective environmental management by midwives and showcases their professional expertise. Kim and Kang [ 21 ] corroborated these observations, noting that midwives place great trust in their professional organizations and public services. They value autonomy and self-regulation and have a strong sense of purpose, which contributes to higher job satisfaction compared to hospital nurses. Midwives exhibited discrepancies between their perceived roles and their actual practices across the seven domains, with the most pronounced gaps noted in the management of women’s health and the care for psychological changes. The scope of women’s health care encompassed a range of services, including adolescent health education, sexual education, counseling for premarital pregnancy, support for single mothers, assistance for victims of sexual violence, menopause education, uterine cancer screening, management of elderly women’s health, and involvement in community programs. In the realm of psychological change care, midwives were expected to offer emotional support, counsel for postpartum depression, and facilitate the early detection and referral of postpartum depression symptoms. The management of women’s health was deemed the least important and least frequently performed task, suggesting a scarcity of opportunities, which aligns with Yu’s findings [ 15 ]. However, this contrasts with the situation in Sweden and the United Kingdom, where midwives actively engage in both women’s health management and psychological change care [ 6 , 7 ]. Benchmarking against these countries suggests that it is necessary to expand the roles of Korean midwives in women’s health management and psychological change care. Lastly, the analysis of the correlations between the scores for role perception and role importance indicated that for both nurses and midwives, a higher perception of the importance of midwives’ roles was associated with higher scores for role performance. This suggests that the more midwives recognize the significance of their roles, the more frequently they perform those roles, effectively defining the scope of their responsibilities. Furthermore, since nurses perceived the roles of midwives as more important than the midwives did themselves, it is recommended that future initiatives to broaden the scope of midwives’ roles should build upon this recognition of their importance. This study confirmed the perceived importance and performance levels of midwives’ roles as evaluated by both nurses and midwives. The higher scores assigned to midwives’ role perception and performance by nurses, as opposed to midwives themselves, suggest a need to explore new roles for midwives. This need arises particularly as they face challenges in role performance due to declining birth rates. By acknowledging the differences in role perception and performance, midwives have the opportunity to broaden their scope beyond the traditional focus on pregnant women and newborns. They can extend their services to include families and community residents, offering comprehensive health management, education, counseling, health assessments, health promotion, disease prevention, treatment, and rehabilitation within primary healthcare. Additionally, they can support psychological change management and women’s healthcare. By capitalizing on the strengths of nurse-midwives, they are well-positioned to assume diverse roles in the post-COVID-19 era in Korea. Despite the global shortage of midwives and the clear need for midwifery training, Korea is facing challenges due to having only four institutions that offer midwife training [ 22 ]. Consequently, the training of midwives is a difficult endeavor, and even those who are trained struggle with a decreasing number of job opportunities. Although there is a general overlap between the roles of midwives and nurses worldwide, Korean midwives have traditionally concentrated exclusively on childbirth and providing health and care guidance to pregnant women and newborns. This specialization has highlighted the necessity for an evolution in the midwife’s role. Furthermore, given the significance of broadening the midwife’s role in women’s health care—especially against the backdrop of falling birth rates—there is an imperative for programs that enhance the recognition and importance of the midwife’s role. To reinforce the essential role of midwives and broaden their responsibilities, our findings support benchmarking the roles of midwives across different countries globally. Future research that investigates the specific duties of midwives in each nation could also aid in enhancing the scope of midwifery in Korea.

Purpose This study aimed to identify the perceptions, importance, and performance of midwives’ roles among midwives and nurses in Korea. Methods A descriptive correlational design was employed. Data were collected from 164 nurses and 79 midwives from April 1 to June 25, 2021. Midwives enrolled in the Korean Midwifery Association and nurses and midwives from two hospitals each Daegu and Gyeonggi Province in Korea were invited to participate. The independent t-test, chi-square test, the Welch-Aspin test, and Pearson correlation coefficient were used for analysis. Results The midwives’ role perception score (3.47±1.46) was lower than that of nurses (3.95±0.85), and the midwives’ role performance score (2.98±0.83) was also lower than that of nurses (3.34±0.89). Significant differences were observed between midwives and nurses in their perception and performance of roles related to prenatal management, childbirth management, management of psychological changes, postpartum management, and newborn care. Higher role perception and performance among midwives were linked to the management of psychological changes and women’s health, indicating potential areas for future development. Conclusion The study results suggest directions for developing new roles for midwives. It is necessary to find a way to expand the field of midwives in public health by benchmarking the roles of midwives in various countries. Summary statement

CC BY

no

2024-01-16 23:42:00

Korean J Women Health Nurs. 2023 Dec 31; 29(4):263-273

oa_package/8f/b6/PMC10788394.tar.gz

PMC10788397

38225938

Discussion Although fluorescein angiography still represents the gold standard to make diagnosis of PDR, the introduction of new wide – field OCTA devices has provided a great support in daily clinical practice, performing even more detailed exams, with no dye injection. 1 Until a few years ago, only low resolution images, focused on central 3 mm, were available, while nowadays, we can benefit of wide – field high definition scans and of single automated montage of multiple OCTA scans. 2 , 3 , 4

Conclusion In our view, in the near future, PDR diagnosis would be easily performed with more advanced wide – field OCT – Angiography devices, which would permit to highlight even the smallest microvascular changes.

Keywords

Case report A 58-year-old male patient, suffering from type 2 diabetes mellitus, referred our center because of vitreous hemorrhage in the right eye (RE) due to florid proliferative diabetic retinopathy (PDR). The patient underwent a complete ophthalmological examination of the left eye (LE), comprehensive of best correct visual acuity, slit lamp examination, dilated fundus evaluation, retinography, fluorescein angiography (FA), optical coherence tomography (OCT) and wide field OCT – Angiography (OCTA) montage of 5 OCTA volume scans (12 × 12 mm) (PLEX® Elite 9000 2.1; Carl Zeiss Meditec, Dublin, CA, USA). Wide – field OCTA was almost comparable to FA in detecting the main PDR features, such as diffuse non perfusion areas (ischemic) in the mid periphery, associated with severe neovascularizations on the disc (NVD) and elsewhere (NVE) ( Fig. 1 , Fig. 2 ). Pre-retinal hemorrhage and neovascular proliferative arcades were evident as well. However, vascular architecture, easily evaluable on OCTA image, was not well-defined on FA, due to dye leakage. Intravitreal injection of anti – VEGF (vascular endothelial growth factor) and photocoagulation laser treatment of the retinal ischemic areas were performed in LE. Patient consent A written consent to publish this case report has been obtained from the patient. Financial disclosure The authors have no financial disclosure to declare. Authorship All authors attest that they meet the current ICMJE criteria for Authorship. CRediT authorship contribution statement Maria Cristina Savastano: Conceptualization, Data curation, Formal analysis, Supervision, Writing – original draft, Writing – review & editing. Claudia Fossataro: Conceptualization, Data curation, Formal analysis, Investigation, Validation, Writing – original draft, Writing – review & editing. Stanislao Rizzo: Conceptualization, Data curation, Investigation, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment The authors want to thank Marta Migliorati for performing the image acquisition. The authors want to thank ERA-NET NEURON (NEURON-066 Rethealthsi) for research support.

CC BY

no

2024-01-16 23:42:00

Am J Ophthalmol Case Rep. 2023 Dec 18; 33:101976

oa_package/83/b5/PMC10788397.tar.gz

PMC10788399

38226033

Background This database was created as part of a study whose purpose is to determine the photovoltaic potential, which in turn will allow estimating the agrivoltaic potential of the region [1] , [2] , [3] . This analysis was done considering the traditional periods of crops in the region and the photovoltaic potential determined using these data. The results of this analysis will allow decisions to be made about economic and energy use in agricultural regions with similar characteristics [4] . Also giving double use to farmland and taking advantage of the photovoltaic potential of the region [ 5 , 6 ]. Where you can combine the double use of land for cultivation, power generation. In addition to the advantage that areas protected from the sun represent for crops [ 7 , 8 ].

Experimental Design, Materials and Methods The database presented in this research was obtained from a public database belonging to the Yaqui River irrigation district ( http://www.dryaqui.org.mx/drrymet/dashboard ), which is continuously monitored through 21 weather stations. The database originally contains 11 variables of which 4 are of interest, date, time, temperature, solar radiation, and relative humidity, so initially the data is filtered, Fig. 2 . From the original data source, the filtering is carried out in two stages. First, the records are adjusted to a time interval of 5:30 a.m. to 7:30 p.m., because in this range there is significant solar radiation for the analyzed region. Second, filtering is required that data is in the appropriate ranges for the variables that correspond in this case: That is radiation from 0 to 1367 W/m 2 , Fig. 3 . Once the data has been exported and corrected, a selection is made taking only the hours where there is an acceptable level of solar radiation. Since the measurements of the meteorological stations are not standardized, since they carry out a sample every ten minutes from the start time, these can differ in minutes, so a data selection method was carried out based on the following algorithm, Fig. 4 . For the daily average radiation, Fig. 5 . First, it is necessary to establish the average daily radiation available for the region by periods according to the traditional crops of the region where it will be used [9] . The maximum radiation values correspond to the October-February period with values near 900 W/m 2 and daily radiation values of 5.059 KW/m 2 (values lower than those reported in the NEREL radiation maps [10] , where values are estimated greater than 5.4 KW/m 2 ). Finally, with the databases is obtained the daily average of solar radiation, relative humidity and temperature, using for these periods and variants with the main crops of the region for the las 3 years., Fig. 6 .

The adequate records of climatological variables, especially temperature and radiation, constitute the basis to be able to determine the photovoltaic and agrivoltaic potential of a region, for this purpose, the data collected must be extremely precise, so it is required that they be focused, current and reliable, to have an adequate estimation. This paper presents the dataset used to estimate the photovoltaic potential of the Yaqui Valley, Sonora, México, for agrivoltaic systems, with the objective of determining the photovoltaic energy generation capacity. Specific records of temperature, radiation and humidity variables obtained from 21 meteorological stations distributed in the Yaqui Valley are used to determine the photovoltaic potential in relation to planting surfaces and commercially available agrivoltaic technologies. To do this, the data was filtered, grouped, and normalized according to the ranges of the variables required for the analysis, this data comprise the last three years. Keywords

Specifications Table Value of the Data • This dataset provides climate records over three years for the region that can be used by other researchers to carry out all kinds of statistical analysis. • Data corresponding to solar radiation, temperature and humidity is required to be accurate, due to the large size of the facilities and the amount of investment, that can generate high expectations in the return of capital, which could not be achieved if there were made an overestimation of the photovoltaic or agrivoltaic capacity. • The data and records presented in this study involve, in addition to temperature, humidity and solar radiation, records of wind speed and direction, barometric pressure, dew point and rainfall, which can be used by other researchers to carry out all types of statistical analysis. • This paper presents data and records that can be compared with values derived from satellite observations to analyze their variability. For example, that presented by the National Renewable Energy Laboratory (NREL). • This dataset is used to determine the photovoltaic potential of the Yaqui Valley region, with which the analysis of the feasibility of implementing agrivoltaic systems can be carried out, for which an analysis of the variables of temperature, radiation, and relative humidity. • The data originally collected belongs to the Yaqui River Irrigation District, which has 21 meteorological stations strategically distributed in the region, carrying out permanent monitoring. This dataset is publicly accessible. Data Description The data was collected from the 21 meteorological stations distributed along the Yaqui Valley Fig. 1 , are in turn distributed in 21 compressed files with a .rar extension, within these are the data collected by the weather stations from February 2020 to February 2023, separated into three main periods, from February 22 to June 21, June 22 to October 21 and finally from October 22 to February 21. The data set is divided in these three main periods, according to the traditional planting periods of the Yaqui Valley. This is done for each year included, so in total the .rar file contains 9 folders in csv format, comma separated values, which contain separate information of 11 variables, columns from a to k, indicating date (dd:mm:yy), time (h:m:s), temperature (°C), rain (mm), relative humidity (%), barometric pressure (mmHg), solar radiation (W/m 2 ), wind speed (Km/hr), wind direction ( o N), wind gust (Km/hr), dew point (°C), these Headers are originally displayed in Spanish [9] . Limitations Basically, the limitations consist of the fact that not all the stations worked continuously during the entire period analyzed, some are of more recent installation and others presented some damage on specific days and sometimes anomalous values appear. Ethics Statement The authors declare that we did not conduct human or animal experiments, that we did not gather social media data, and we had (or did not need) permission to use the primary data sources. CRediT authorship contribution statement José Ruelas: Conceptualization, Methodology, Validation, Investigation. Flavio Muñoz: Conceptualization, Validation, Data curation, Software, Investigation. Juan Palomares: Conceptualization, Data curation, Investigation, Validation, Software. José Castro: Conceptualization, Data curation, Investigation.

Data Availability Replication data for Photovoltaic energy estimation for the Yaqui Valley, Sonora, México (Original data) (Dataverse). Acknowledgment None. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CC BY

no

2024-01-16 23:42:00

Data Brief. 2023 Dec 16; 52:109983

oa_package/3e/e9/PMC10788399.tar.gz

PMC10788401

38226254

Introduction The coil embolization imposes a comparatively reduced physical burden on the patient when compared with surgical clipping; however, the notable concerns encompass recanalization and the necessity for subsequent aneurysm retreatment [ 1 , 2 ]. Previous studies have observed recanalization in approximately 10 %–25 % of coil embolic aneurysms during follow-up [ 3 ]. Based on hemodynamic parameters from computational fluid dynamics (CFD), quantified models have been developed to predict aneurysmal growth, rupture, and recanalization [ 4 , 5 ]. In previous studies, both spatiotemporally averaged and maximal definitions for the hemodynamic parameters were found to build predictive models for aneurysm recanalization. One study developed a predictive parameter by combining maximal and average hemodynamic, morphological, and clinical scalars [ 6 ]. Another study revealed significant differences in spatiotemporally averaged aneurysmal residual flow volume and maximal force between recanalized and stable aneurysms after coil embolization [ 7 ]. Recent studies have conducted a comprehensive analysis of the risk factors for aneurysmal recanalization using a virtual post-coiling model (VM) created by cutting the aneurysm from the pre-coiling model [ 1 , 2 , 8 , 9 ]. In comparison with other researched morphological and hemodynamic parameters, pressure difference (PD) in VM was the strongest predictor of aneurysmal recanalization. However, the spatiotemporal characteristics of hemodynamic parameters have not been considered by these models. The present study aimed to examine the influence of spatiotemporal hemodynamic characteristics on predictive accuracy. We identified 14 spatiotemporal features from each hemodynamic parameter, resulting in a total of 91 spatiotemporal hemodynamic features. We assessed the predictive performance of the identified features for aneurysm recanalization using univariate and multivariate analyses.

Method Patients Definitions of recanalized/stable aneurysms and the inclusion criteria of patients could be found in our previous works [ 1 , 2 , 8 , 9 ]. The final analysis included a cohort of 66 intracranial aneurysms derived from 65 patients who underwent endovascular treatment for aneurysms within the timeframe of January 2007 to December 2020, comprising nine recanalized aneurysms and 57 stable aneurysms. Post-treatment, the enrolled patients underwent systematic biannual follow-ups utilizing magnetic resonance angiography. In instances where magnetic resonance imaging raised suspicion of recanalization, confirmation was sought through digital subtraction angiography. Endovascular intervention was administered as dictated by clinical necessity. Fluid dynamic analysis The methodology for conducting CFD based on medical imaging can be found in our previously published studies [ 1 , 2 , 8 , 9 ]. Two complete cardiac cycles, equivalent to a duration of 1.8s, were computed and employed as the basis for this study. Features deviation Morphological parameters were assessed utilizing 3D-RA data, encompassing measurements of the maximum size, neck width, height, as well as the area of the posterior communicating (Pcom), aneurysm neck and inlet [ 1 , 10 ]. Aspect ratio was defined as the quotient of the maximum perpendicular height to the neck diameter [ 11 , 12 ]. Bottleneck factor was defined as the ratio of the dome width to the neck diameter [ 13 ]. Size ratio was defined as the ratio of the maximum aneurysm height to the parent vessel diameter [ 14 ]. Area ratio was articulated as the proportion of the aneurysm neck area to the area of the aneurysm inlet within the parent artery [ 15 ]. VER was represented as the proportion of the aneurysm volume to the volume occupied by the coil [ 16 ]. Dimensionless hemodynamic parameters were employed in the analysis, enabling the construction of a model that was not contingent on patient-specific inflow rates [ 1 , 2 , 6 , 8 ]. Hemodynamic parameters in pre-coiling model included velocity in aneurysm dome (volvel), wall shear stress (WSS), static pressure (P) and dynamic pressure (Pdyn) at aneurysm neck plane, which were normalized using surface-averaged velocity, WSS and P at aneurysm inlet in parent artery. Inflow rate ratio (FR) was defined as the ratio of the inflow rate at the neck plane to the flow rate at the inlet plane [ 1 ]. In VM, PP was defined as pressure change between aneurysm neck and inlet, whereas pressure difference (PD) was delineated as the quotient of PP to Pdyn at the inlet of the aneurysm, as described by following equation (Eqn. (1) ): where v inlet and P inlet indicated spatiotemporally averaged velocity and pressure at the aneurysm inlet plane; ρ is the blood density, 1100 kg/m 3 [ 1 , 2 , 6 , 8 ]. In this study, we established 14 spatiotemporal features for each hemodynamic parameter as shown in Table 1 . Spatial features were defined using spatially averaged or maximal hemodynamic values, denoted as X ave and X max , where X represented volvel, PD, P, PP, Pdyn, and WSS. On the other hand, FR was solely defined as a mass flow rate variable over time. Fig. 1 A-F depict the temporal profiles of X ave and X max for one patient, revealing that both profiles exhibited a similar trend, but with quantitative differences. To capture the temporal characteristics of the data, we derived seven features (a, median, min, max, std, q1, and q2), as illustrated in Fig. 2 . Statistical analysis All continuous parameter values were presented in the format of mean ± standard deviation. The Levene test was employed to evaluate the equality of variances between the two groups with continuous variables [76,77]. Differences in variables between the two groups were examined using Welch's t -test in the case of data with unequal variance, or t -test for data with equal variance. For categorical variables, the assessment of significant differences between groups was conducted using a chi-square test. A significance level of P-value <0.05 was applied to establish statistical significance. The statistical analyses were conducted utilizing Scipy (version 1.9.3) [ 17 ]. Predictive models and evaluation To assess the predictive capacity of the 91 derived spatiotemporal hemodynamic features, we conducted both univariate predictor (UP) and multivariate logistic regression (LR) analyses. In the UP analysis, we employed receiver operating characteristic curve (ROC) analysis to ascertain the optimal cut-off value for each feature. In the LR analysis, we initially conducted univariate LR analyses for each spatiotemporal feature. Variables demonstrating a level of significance with P-value <0.05 were retained. Furthermore, we computed Variance Inflation Factor (VIF) values to assess multicollinearity among the selected variables from the univariate LR analysis [ 18 ]. Variables with a VIF exceeding 10 were deemed indicative of multicollinearity and excluded from the analysis [ 6 , 19 ]. The subsequent multivariate LR analysis utilized the selected variables from the multicollinearity assessment. We implemented a stepwise selection approach guided by P-values, wherein variables for the multivariate LR analysis were iteratively assessed until achieving a P-value of less than 0.05. Additionally, we conducted the Hosmer-Lemeshow goodness-of-fit test for the final model. Logistic classification algorithms face challenges in learning when certain classes significantly outnumber others [ 20 ]. To address this imbalance, we applied the synthetic minority oversampling technique (SMOTE) to harmonize the class distribution within the dataset [ 21 ]. Prior to model training, all parameters were subjected to normalization to achieve a standard deviation of 1 and a mean value of zero. To account for the imbalanced nature of the dataset, we incorporated the area under the precision-recall curve (AUPRC) alongside the area under the receiver operating characteristic curve (AUROC) as a comprehensive metric for performance assessment [ 22 ]. The predictive models were both trained and assessed using the open-source Scikit-learn library (version 1.0.2) [ 23 ].

Results Statistical analysis for patient population The patient characteristics for each group are detailed in Table 2 . No statistically significant differences were observed in age, aneurysm locations, gender distribution or rupture status between the two groups. Statistical analysis for hemodynamic and morphological data A parametric test was conducted on both morphological and hemodynamic features to identify the variables that exhibit statistical significance, as presented in Supplementary Table 1 . Table 3 presents the mean and standard deviation values of the morphological and hemodynamic features that displayed statistical significance between recanalized and stable groups. The recanalized group showed higher mean values for all significant morphological parameters in comparison to the stable group. The spatiotemporal hemodynamic features derived from identical parameters displayed variations in mean values and standard deviations. Spatially averaged features derived from FR, volvel, and PD demonstrated significant differences between the two groups, whereas P-, PP-, Pdyn-, and WSS-related features did not show significant differences. Furthermore, the recanalized group demonstrated higher mean values for FR and PD-related features, whereas all volvel-related features exhibited lower mean values in recanalized aneurysms compared to the stable group. Predictive model a) UP analysis Performance of UP for aneurysm recanalization using all 91 spatiotemporal hemodynamic features is shown in Supplementary Table 2 . Among these parameters, PD-related features exhibited the highest performance and occupied the top nine positions in terms of AUROC value. Notably, spatially averaged features outperformed spatially maximal features, with eight out of top ten features being spatially averaged. PD ave,q1 demonstrated the highest AUROC value of 0.747, with sensitivity and specificity values of 0.889 and 0.614, respectively, at the optimal cut-off point. Other top-performing features included PD ave,a , PD ave, median , PD ave,q2 , PD ave,max , PD max,std , PD ave,min , PD ave,std , PD max,max and P ave,min , with AUROC values ranging from 0.743 to 0.641. The lowest AUROC was observed for volvel ave,min , with a value of 0.224. Table 4 presents the results of pairwise comparisons conducted between the 14 spatiotemporal features for each hemodynamic parameter. We found that 22 pairs exhibited a significant difference in AUROC value with a P-value <0.05, despite being extracted from one identical hemodynamic parameter. The predictors that showed such significant difference were derived from volvel, P, and PP. b) LR analysis First, we conducted a univariate LR analysis on all 91 features, as shown in Supplementary Table 3 , revealing 42 features with P-values less than 0.05. To select features with low multicollinearity, we performed a VIF analysis on these 42 parameters, resulting in a selection of eight parameters with VIF <10 as listed in Supplementary Table 4 . Subsequently, we performed multivariate LR analysis and stepwise selection using these eight parameters, ultimately selecting Area Ratio, volvel ave,q1 , PD ave,min , and PD ave,std as the most effective factors for predicting recanalization, as presented in Table 5 . PD ave,std exhibited the lowest P-value of 8.172E-07. The Hosmer-Lemeshow goodness-of-fit test yielded a significant result (P-value of 0.909) for the final model, indicating that the model demonstrated a valid and accurate prediction of recanalization outcomes. c) Performance evaluation We conducted ROC and PRC analysis on the optimal UP (PD ave,q1 ) and LR model, as shown in Fig. 3 A and B, respectively. The results are detailed in Table 6 . Although PD ave,q1 was the most effective UP with an AUROC value of 0.747, it was inferior to the result obtained from LR model, which achieved a higher AUROC value of 0.890 with specificity and sensitivity values of 0.877 and 0.719, respectively. Furthermore, a statistically significant discrepancy in AUROC values was noted between the two models, with a P-value below the threshold of 0.05. Additionally, the LR model exhibited a significantly superior AUPRC value of 0.903 compared to the UP model's AUPRC value of 0.385, with a P-value less than 0.05.

Discussion This study compared the performance of predictive models based on UP and LR using 91 spatiotemporal features derived from seven hemodynamic parameters. The results of UP showed a wide range of AUROC values (ranging from 0.224 to 0.747) for different spatiotemporal hemodynamic features. Notably, 22 pairs of features demonstrated significant differences in AUROC values with P-value <0.05, even though they were derived from the same hemodynamic parameter. Among the examined parameters, PD was found to have the highest performance, with PD ave,q1 being the strongest UP with AUROC/AUPRC values of 0.747/0.385, yielding sensitivity and specificity value of 0.889 and 0.614 at the optimal cut-off value, respectively. The LR model further improved the prediction performance, having AUROC/AUPRC values of 0.890/0.903. At the optimal cut-off value, the LR model achieved a specificity of 0.877, sensitivity of 0.719, outperforming the UP model. Identifying the factors that contribute to intracranial aneurysm recanalization is crucial for physicians. However, contradictory findings have been reported due to uncertainties in CFD, including inaccurate geometry, missing boundary conditions, and unclear model parameters [ [24] , [25] , [26] , [27] , [28] , [29] ]. The impact of spatiotemporal definition on the uncertainty has not been thoroughly investigated. Our study revealed that the spatiotemporal definition method employed for hemodynamic parameters had a substantial impact on the performance of predictive models. This finding led to the hypothesis that distinct spatiotemporal features might be associated with different pathologies of aneurysm recanalization. For instance, the identification of volvel max,max as a significant risk factor suggested that an elevated velocity at a specific spatial and temporal point might contribute to an increased likelihood of aneurysm recanalization. Conversely, the identification of volvel ave,max as a risk factor indicated that a high velocity throughout the aneurysm dome at a particular time point might be associated with the occurrence of recanalization. Similarly, the identification of volvel max,a as a risk factor signified that a high velocity at a specific point over time might be associated with an increased risk of aneurysm recanalization. On the other hand, the identification of volvel ave,a as a risk factor suggested that a high velocity throughout the aneurysm dome over time might significantly influence the likelihood of recanalization. This study observed the prevalence of spatial averaging over maximizing in both UP and LR analyses: (1) eight of top ten most effective UP; (2) five in seven hemodynamic features selected by VIF analysis; (3) all three hemodynamic features in the final LR model were spatially averaged. It suggested that a higher velocity/pressure difference distributed throughout the aneurysm dome/neck might pose a greater risk for aneurysm recanalization compared to a high velocity/pressure difference localized to a single location. Furthermore, this superiority of spatial averaging might also be attributed to the inherent robustness of this method in processing hemodynamic parameters. Validation studies of in vitro , in vivo and multi-modalities, indicated that global data, such as flow patterns and spatially averaged hemodynamic parameters, showed higher robustness than point-wise data, especially under complex flow conditions [ [30] , [31] , [32] , [33] , [34] ]. Flow disturbances and irregularities result in irrelevant data, which indicates that averaged data are superior to point-wise data [ 30 , 33 ]. Compared to spatial characteristics, temporal characteristics preferred to be described with multiple features: (1) various PD temporal features occupied top ten best UPs; (2) temporal features except averaged and maximum remained after univariate logistic and VIF analysis; (2) the final LR analysis selected two types of temporal features derived from PD, namely, std and min. Recently, time series data was utilized to develop prediction models for cardiovascular diseases [ 35 , 36 ]. However, only physiological time series, such as blood pressure, heart rate and ECG were used. Our study indicates that the temporal characteristics of hemodynamic parameters derived from transient CFD simulations could offer clinically interpretable and significant information for identifying patients with a high likelihood of recanalization. To further investigate the potential of these time series features, we plan to extract more hemodynamic features in 3D space and time using deep learning and analyze additional features in the frequency and wavelet domains using a larger dataset [ 9 , [35] , [36] , [37] , [38] ]. The process of deriving spatiotemporal features resulted in a rapid increase in the number of features, which in turn led to increased complexity of the classifiers and overfitting caused by irrelevant and meaningless data [ 39 ]. To address this issue, we focused on selecting only the most significant and non-multicollinear features to improve model performance. The resulting LR model achieved satisfactory results on the current dataset, with an AUROC value of 0.890. In future research, we plan to examine additional significant features for predicting aneurysm recanalization and evaluate the model on a larger and external dataset. Currently, there are two primary methods for acquiring hemodynamics data from patients in clinical settings: CFD or non-invasive measurements using techniques such as 4D-Flow MRI or Transcranial Doppler Ultrasound [ 40 , 41 ]. The utilization of CFD has been limited in clinical practice due to its intricate processing requirements and time-consuming calculations. Among the experimental methodologies, only 4D-Flow MRI furnishes comprehensive volumetric data pertaining to time-resolved flow patterns [ 42 ]. In addition, 4D-Flow MRI enables relatively faster acquisition of patient-specific hemodynamics without the need for simplifying model parameters and boundary conditions, in contrast to the CFD method. Although 4D-Flow MRI exhibits lower resolution in small cerebral arteries, recent advancements in data assimilation techniques have demonstrated promising outcomes in enhancing the resolution of 4D-Flow MRI. As a result, it holds significant potential as an approach for obtaining spatiotemporal hemodynamic features in clinical practice in the foreseeable future [ 42 , 43 ]. The study confirmed again the superior performance of PD over other hemodynamic parameters, as nine out of the top ten UPs with the highest AUROC values and two of the three hemodynamic features selected by LR model were derived from PD. Additionally, the study enhanced the predictive performance of PD by exploring the impact of spatiotemporal characteristics, ultimately identifying PD ave,q1 as the most robust predictor with AUROC value of 0.747. In contrast, the previously published parameter PD max,max demonstrated a lower AUROC value of 0.649 [ 1 , 2 , 8 ]. This study did not consider the coiling configuration. The coil surface was depicted as a planar and rigid structure; in contrast, clinical reality often involves a textured coil surface that facilitates blood permeation into the coil mass. Further investigation is needed to integrate the realistic coil surface obtained through advanced techniques such as silent magnetic resonance angiography into the analysis [ 44 ]. The technique SMOTE was applied to rebalance the data by resampling minority cases. While SMOTE has found application in numerous medical studies, it is important to acknowledge that this method generates synthetic samples, potentially introducing an influence on the outcomes [ [45] , [46] , [47] ].

Conclusion The study demonstrated that the model performance in predicting aneurysm recanalization was significantly influenced by the spatiotemporal characteristics of hemodynamic parameters. PD ave,q1 was the strongest UP. The performance of LR model was enhanced by incorporating multiple features to describe temporal characteristics and utilizing spatial averaging. This enhanced predictive model holds clinical promise for non-invasively predicting recanalization following coil embolization in patients.

Purpose Hemodynamics play a key role in the management of cerebral aneurysm recanalization after coil embolization; however, the most reliable hemodynamic parameter remains unknown. Previous studies have explored the use of both spatiotemporally averaged and maximal definitions for hemodynamic parameters, based on computational fluid dynamics (CFD) analysis, to build predictive models for aneurysmal recanalization. In this study, we aimed to assess the influence of different spatiotemporal characteristics of hemodynamic parameters on predictive performance. Methods Hemodynamics were simulated using CFD for 66 cerebral aneurysms from 65 patients. We evaluated 14 types of spatiotemporal definitions for two hemodynamic parameters in the pre-coiling model and five in virtual post-coiling model (VM) created by cutting the aneurysm from the pre-coiling model. A total of 91 spatiotemporal hemodynamic features were derived and utilized to develop univariate predictor (UP) and multivariate logistic regression (LR) models. The model's performance was assessed using two metrics: the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). Results Different spatiotemporal hemodynamic features exhibited a wide range of AUROC values ranging from 0.224 to 0.747, with 22 feature pairs showing a significant difference in AUROC value (P-value <0.05), despite being derived from the same hemodynamic parameter. PD ave,q1 was identified as the strongest UP with AUROC/AUPRC values of 0.747/0.385, yielding sensitivity and specificity value of 0.889 and 0.614 at the optimal cut-off value, respectively. The LR model further improved the prediction performance, having AUROC/AUPRC values of 0.890/0.903. At the optimal cut-off value, the LR model achieved a specificity of 0.877, sensitivity of 0.719, outperforming the UP model. Conclusion Our research indicated that the characteristics of hemodynamic parameters in terms of space and time had a significant impact on the development of predictive model. Our findings suggest that LR model based on spatiotemporal hemodynamic features could be clinically useful in predicting recanalization after coil embolization in patients, without the need for invasive procedures. Keywords

Limitations First, this study involved a cohort of 65 patients. Future steps will encompass an expanded analysis with a larger patient cohort for further evaluation. Second, given its retrospective nature, subsequent research should focus on a prospective study involving a comprehensive cohort covering all types of aneurysms to validate the predictive effectiveness of the developed models. Third, the present study did not account for fluid-solid interaction between vessel walls and blood. Finally, uniform boundary conditions were applied to all patients. Future investigations will explore the feasibility of integrating patient-specific boundary conditions derived from advanced modalities such as 4D-Flow MRI or Transcranial Doppler Ultrasonography to enhance accuracy. Ethics approval The retrospective study protocol received approval from the Ethics Committee of Kanazawa University (Approval No. 1781). Given the retrospective nature of clinical data collection, the requirement for written informed consent was waived. Nevertheless, all patients retained the prerogative to withdraw their participation from the study at any given point in time. Grant support This work was partially supported by JST SPRING (Grant Number JPMJSP2135 to L.J.) and The 10.13039/501100001691 Japan Society for the Promotion of Science ( 10.13039/501100001691 JSPS ) KAKENHI (Grant Numbers C–16K10783 to K.M.) CRediT authorship contribution statement Jing Liao: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing - original draft, Writing - review & editing. Kouichi Misaki: Data curation, Funding acquisition, Project administration, Resources, Supervision, Validation, Writing - review & editing, Software. Tekehiro Uno: Data curation, Resources. Iku Nambu: Data curation, Resources. Tomoya Kamide: Data curation, Resources. Chen Zhuoqing: Conceptualization, Investigation, Methodology. Mitsutoshi Nakada: Data curation, Funding acquisition, Project administration, Resources, Software, Supervision. Jiro Sakamoto: Project administration, Resources, Supervision. Declaration of competing interest This work was partially supported by 10.13039/501100002241 Japan Science and Technology Agency Support for Pioneering Research Initiated by the Next Generation ( JST SPRING) (Grant Number JPMJSP2135 to L.J.) and The 10.13039/501100001691 Japan Society for the Promotion of Science ( 10.13039/501100001691 JSPS ) KAKENHI (Grant Numbers C–16K10783 to K.M.) The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary data The following is the Supplementary data to this article.

CC BY

no

2024-01-16 23:42:00

Heliyon. 2023 Dec 20; 10(1):e22801

oa_package/5a/5d/PMC10788401.tar.gz

PMC10788402

38226036

Background Giant clams (Tridacninae) are iconic reef dwellers that fulfil critical ecological roles in tropical coral reef communities [2] . They also serve as ultra-high-resolution bioarchives to reconstruct past oceanographic conditions in tropical regions, where instrumental records are lacking [3] . Increased understanding of the microstructural and crystallographic architecture of giant clam shells is fundamental to provide information on biomineralization and skeletal organization in changing oceanic conditions [4] . In this dataset, one objective was to focus on the optimization of EBSD data quality for aragonitic giant clam shells by providing detailed information on EBSD data collection and post-processing steps. A second objective was to provide characterization of microstructure and crystallographic texture in two giant clam species frequently used for (paleo)environmental study ( T. squamosa; H. hippopus ).

Experimental Design, Materials and Methods Sample preparation Two modern giant clam shells, T. squamos a (fluted giant clam) and H. hippopus (bear paw clam) were collected from Darvel Bay (4° 51′ 57.2328′′ N, 118° 11′ 34.8864′′ E; 4° 58′ 57.684′′ N, 118° 21′ 42.5268′′ E respectively) within the Coral Triangle region of northeast Borneo (Sabah, Malaysia) in April 2019. The exterior of one valve of each shell was thoroughly rinsed and scrubbed to remove dirt and debris, before being air-dried. Afterward, valves were cut into ∼1–2 cm thick slices along the axis of maximum growth (longitudinal from umbo to upper shell margin) ( Fig. 1a ) with a HC Evans and Son (Eltham) LTD circular saw (250 mm blade, 1 mm thickness). Thin sections (∼60 μm thickness) cut perpendicular to the direction of growth were prepared from slices ( Fig. 1b ). One side of each cut slice was ground flat using silicon carbide 1000 grit. The slices were then washed, dried and stuck to 28×48 mm frosted glass slides using Araldite 2020 epoxy resin. Excess sample was cut from the slides leaving a 500–1000 μm slice stuck to the glass. Slides were then lapped on a Logitech LP50 lapper using 600 silicon carbide grit to leave samples at a thickness of 100 μm. Afterward, the slides were lapped by hand using 1000 silicon carbide grit until the required sample thickness had been reached. Slides were washed in an ultrasonic bath and samples polished on a Logitech PM5 lapper with 0.3 μm aluminum oxide. After polishing slides, they were again washed in an ultrasonic bath. SEM Polished sections of T. squamosa and H. hippopus were etched with 0.5% HCl for 15 s to improve visibility of biominerals and then rinsed for 1 min with deionized water. To dry samples, a canister of compressed air was sprayed gently across the surface of sections. Afterward, samples were sputter coated with a 20 nm thick layer of gold-palladium alloy (Au-Pd) using a BIO-RAD SC500 sputter coater at the School of Earth and Environmental Sciences, Cardiff University. A Zeiss Sigma HD field emission gun scanning electron microscope (FEG-SEM) at the School of Earth and Environmental Sciences, Cardiff University, was used under high vacuum for the characterization of aragonitic microstructures with focus on the inner shell layer of sections. The entire height of the inner layer of sections was examined with SEM for preliminary identification of microstructure across the whole surface (an area with height ∼30 mm, length ∼1 mm). The following SEM parameters were used to obtain in-lens secondary electron (SE) images of different microstructures ( Fig. 2 ): 10 kV accelerating voltage, final aperture size 30 μm with a nominal beam current of 210 pA, working distance ∼9.5 mm, pixel dwell time 10 μs. EBSD Areas of thin sections selected for crystallographic and textural characterization with EBSD were based on prior microstructural identification with SEM. Sections were repolished and subjected to several sequential mechanical grinding and polishing steps, including a final polish with Logitech SF1 Polishing Suspension of colloidal silica using a Logitech PM5 automatic polisher (70 rpm rotation, 2 × 10 min cycles). Afterward, copper tape was applied in a rectangle around selected areas of samples for mapping to eliminate electron charging within the high-vacuum SEM chamber. Samples were coated with a thin uniform layer (3 nm) of carbon [5] using a Agar Turbo Carbon Coater. Fraction of the indexed pattern for aragonite (%) was tested with varying layers of carbon thickness between 2 and 6 nm, but 3 nm provided the strongest diffraction signal with negligible charging of the sample. EBSD mapping was carried out using a Zeiss Sigma HD FEG-SEM equipped with a Nordlys-2 EBSD detector at the School of Earth and Environmental Sciences, Cardiff University. In the SEM, samples were tilted at an angle of 70° at ∼10 mm working distance with ∼193–194 mm detector insert distance. Diffraction patterns were collected at a resolution of 0.5 μm step size, 20 kV accelerating voltage, 60 μm aperture in high current mode with a 2.7 nA nominal beam current and 2 × 2 camera (320×240 pixels) binning. Total acquisition time was 27 h for SS01BSN and 12 h for SS02BCT, with map dimensions of 1024×768 pixels and 681×510 pixels respectively. Exposure time was 96.8 ms for SS01BSN and 127.58 ms for SS02BCT. Electron backscatter patterns were indexed using Oxford Instruments AZtec 6.0 software. Parameters chosen for the indexing of the aragonite unit cell were the OINA database a = 4.9614 Å, b = 7.9671 Å, c = 5.7404 Å space group 62 Pmcn [6] . Aragonite indexed with the OINA database provided pole figures with a preferred crystallographic orientation of the 001 axis orthogonal to growth lines. EBSD post-acquisition refinement Post-acquisition refinement to optimize index rates of aragonite was performed on data with EBSD patterns stored at indexing using AZtec 6.0 software (Oxford Instruments). Maps were reanalyzed changing the number of reflectors, band detection mode, Hough resolution and area of interest (AOI). Manual selection of the number of reflectors (i.e. list of Kikuchi bands to be considered in the indexing process) within the OINA and HKL databases ranged between 2 and 82 reflectors ( Fig. 3 ). The relationship between fraction of indexed pattern for aragonite (%) and reflectors peaked at 67 reflectors in the OINA database, which increased indexing by 6 % compared to default selection of 49 reflectors while keeping mean angular deviation (MAD) under 1° ( Fig. 3 , Fig. 4 ; Table 1 in data repository). Refined accuracy band detection mode compared to routine Hough-based indexing further increased indexing by 1–3 %. Manual alteration of Hough resolution and area of interest (AOI) did not change the percentage of indexed pattern for aragonite. EBSD data analysis Data analysis was carried out in MTEX toolbox 5.7.0 for MATLAB R2022b [7] . Grains were reconstructed using a threshold angle of 2° Minimum grain size was set to 3 pixels in comparison to 10 pixels previously used for giant clam aragonite [8] because grain sizes were notably small (under 1 μm) in some areas. Points with mean angular deviation (MAD) over 1° were discarded and remaining grain boundaries smoothed. Zero solutions, that is missing data from parts of the sample that showed an absence of diffraction, were not interpolated to avoid over-simplification of the dataset in the presence of small grains. EBSD band contrast images, EBSD color-coded orientation maps (inverse pole figure maps) and pole figures for T. squamosa and H. hippopus were assembled using MTEX and are provided in Fig. 5 , Fig. 6 , Fig. 7 . Pole figures were plotted on a lower hemisphere projection in the YX projection plane, with spread of the poles controlled by half-width [9] . An optimal half-width of approximately 4° for the data was computed based on the mean orientation of grains using the kernel function for orientation distribution function (ODF) estimation. Crystallographic co-orientation strength is presented as multiple of uniform density (MUD) values extracted from pole figures. The strength of the crystallographic preferred orientation is derived from the maximum intensity of contoured pole figures. MUD statistically measures sharpness of texture and a strong crystal co-orientation will have a higher MUD value than a low or random co-orientation (e.g. [9 , 10] ).

This article provides novel data on the microstructure and crystallographic texture of modern giant clam shells ( Tridacna squamosa and Hippopus hippopus ) from the Coral Triangle region of northeast Borneo. Giant clams have two aragonitic shell layers—the inner and outer shell layer. This dataset focuses on the inner shell layer as this is well preserved and not affected by diagenetic alteration. To prepare samples for analysis, shells were cut longitudinally at the axis of maximum growth and mounted onto thin sections. Data collection involved scanning electron microscopy (SEM) to determine microstructure and SEM based electron backscatter diffraction (EBSD) for quantitative measurement of crystallographic orientation and texture. Post-acquisition reanalysis of saved EBSD patterns to optimize data quality included changing the number of reflectors and band detection mode. We provide EBSD data as band contrast images and colour-coded orientation maps (inverse pole figure maps). Crystallographic co-orientation strength obtained with multiple of uniform density (MUD) values are derived from density distributed pole figures of indexed EBSD points. Raw EBSD data files are also given to ensure repeatability of the steps provided in this article and to allow extraction of further crystallographic properties for future researchers. Overall, this dataset provides 1. a better understanding of shell growth and biomineralization in giant clams and 2. important steps for optimizing data collection with EBSD analyses in biogenic carbonates. Keywords

Specifications Table Value of the Data • This dataset provides characterization of the microstructure and crystallographic texture of the shells of two species of giant clam (Tridacna squamosa; Hippopus hippopus). These data are necessary for understanding shell growth and biomineralization mechanisms in the fields of structural biology and (paleo)environmental reconstruction. • These data provide an optimized method and guide for accurate and precise EBSD data collection in biogenic carbonates such as bivalves and corals. This method is applicable to samples with biomineral crystal sizes down to 1 μm. • The dataset can benefit those who wish to improve and optimize EBSD data quality when determining crystallographic orientation in biogenic carbonates. • Future researchers may use the raw EBSD data provided [1] to extract further textural and crystallographic properties of the giant clam shells. For example, the data may be used to investigate grain boundary misorientation and provide advanced characterization of material properties. Data Description Microstructure and crystallographic texture data for the shells of the giant clams T. squamosa and H. hippopus is presented herein. A schematic overview of sample preparation is given in Fig. 1 —shell valves were sectioned longitudinally along the maximum growth axis, cut into ∼1–2 cm thick slices and mounted onto glass slides for preparation of thin sections. SEM in-lens secondary electron high-resolution images used for microstructural characterization of the material are presented as TIFF images. Fig. 2 focuses on the microstructure of the inner shell layer at a micro- to nanoscale, showing daily growth lines intersecting a complex crossed-lamellar microstructure ( Fig. 2b ) and paired daily growth lines that consist of a prismatic layer adjacent to smaller crystals ( Fig 2c ). Fig. 3 , Fig. 4 show post-acquisition refinement of EBSD pattern indexing using varying numbers of reflectors (i.e. list of Kikuchi bands to be considered in the indexing process) and different band detection approaches (i.e. refined accuracy versus Hough-based band detection). EBSD band contrast images are presented with associated pole figures as TIFF images ( Fig. 5 ), where dark pixels represent poor pattern quality and bright pixels represent high pattern quality. EBSD preferred crystallographic orientation (CPO) data are represented as color-coded orientation maps (TIFF images) and are shown with corresponding contoured pole figures in Figs. 6 , 7 . Pole figures are a stereographic projection of aragonite planes with axes defined by an external reference frame (X, Y, Z correspond to E-W, N-S and out of plane respectively), showing clustering of points around specific direction(s) (i.e. pole maxima). The strength of the CPO is quantified using multiple of uniform distribution (MUD) values, which is derived from the maximum intensity of contoured pole figures ( Figs. 6 , 7 ). Orientation maps are colored according to the inverse pole figure (IPF) color key for aragonite referenced to the Y direction of the external reference frame, where similar colors relate to similar orientations. A tabulated version of post-acquisition indexing optimization is presented in Table 1, included in the Mendeley Data Repository as a .XLSX file. The repository also contains raw SEM EBSD files (.CRC, .CPR, .txt) for T. squamosa and H. hippopus , along with a sample script (.M, .txt) with code showcasing EBSD data analysis and plotting in MTEX toolbox 5.7.0 for MATLAB R2022b. The files stored within the data repository are: • SS02BCT.CRC: Raw EBSD dataset file for Tridacna squamosa (SS02BCT) • SS01BSN.CRC: Raw EBSD dataset file for Hippopus hippopus (SS01BSN) • SS02BCT.CPR: Raw EBSD dataset file for Tridacna squamosa (SS02BCT) • SS01BSN.CPR: Raw EBSD dataset file for Hippopus hippopus (SS01BSN) • SS02BCT.txt: Raw EBSD dataset file for Tridacna squamosa (SS02BCT) • SS01BSN.txt: Raw EBSD dataset file for Hippopus hippopus (SS01BSN) • EBSD_Tridacnidae.M: Code for EBSD data analysis and plotting. • EBSD_Tridacnidae.txt: Code for EBSD data analysis and plotting. • Reflectors.XLSX: Table of post-acquisition reanalysis of EBSD patterns stored at indexing using manual selection of reflectors. Limitations The limitation of this dataset is that the EBSD data were generated from a singular specimen of each species investigated. This may hinder the reliable interpretation of MUD values to understand the variety of crystal co-orientation strength that exists between species. However, the primary aim of this study was to provide reproducible steps for future researchers, which we have laid out in this article. By providing these steps and raw EBSD data files, we suggest future researchers add more samples to further capture diversity in crystallographic features. Ethics Statement The authors state that the present work meets the ethical requirements for publication in Data in Brief. Human or animal experiments were not conducted and social media data was not collected. CRediT authorship contribution statement Kimberley Mills: Conceptualization, Methodology, Investigation, Visualization, Writing – original draft. Duncan D. Muir: Conceptualization, Methodology, Investigation, Writing – review & editing. Anthony Oldroyd: Resources, Writing – review & editing. Eleanor H. John: Conceptualization, Writing – review & editing. Nadia Santodomingo: Resources, Funding acquisition. Kenneth G. Johnson: Resources, Funding acquisition. Muhammad Ali Syed Hussein: Resources. Sindia Sosdian: Conceptualization, Writing – review & editing, Funding acquisition.

Data Availability Microstructure and crystallographic texture data from modern giant clam shells (Tridacna squamosa and Hippopus hippopus) (Original data) (Mendeley Data). Acknowledgments Thanks to the Borneo Marine Research Institute (University Malaysia Sabah) for hosting our research and Dominic Monteroso (Darvel Bay Diving Centre) for assistance with fieldwork. Thanks to Allia Rosedy and Zarinah Waheed for help with sample collection, permits application, and other key research and logistic aspects of the project. Giant clams are CITES appendix II listed species and shells were permitted accordingly for export purposes. Funding: The funding agency 10.13039/501100000270 NERC (UK National Environmental Research Council) through the Project “Reef refugia out of the shadows: dynamics of marginal coral reef ecosystems over the past 30 million years in the Coral Triangle” [NE/R]11044/1] and the 10.13039/100014013 UKRI project EP/V520834/1. Kimberley Mills is a PhD researcher funded by 10.13039/501100000270 NERC GW4+ . This study was performed under Access Licence JKM/MBS.1000- 2/2 JLD.7(161) granted by the Sabah Biodiversity Conservation Centre (SaBC) and Research Permit UPE 40/200/193533 granted by the Economic Planning Unit, 10.13039/501100004725 Ministry of Economic Affairs , Malaysian Government. This is Cardiff EARTH CRediT Contribution 14. Declaration Competing of Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CC BY

no

2024-01-16 23:42:00

Data Brief. 2023 Dec 14; 52:109947

oa_package/d8/2b/PMC10788402.tar.gz

PMC10788405

38225980

Introduction Minocycline is a broad-spectrum antibiotic agent with an antiinflammatory activity frequently used in dermatology. 1 , 2 , 3 , 4 The notable efficacy and favorable safety profile of minocycline have made it a preferred choice primarily for treating acne and various other dermatological conditions, often necessitating long-term administration to achieve optimal outcomes. 4 Despite the manifold advantages of minocycline therapy, the emergence of cutaneous hyperpigmentation as an infrequent yet consequential adverse effect poses a distinct challenge. This unwanted pigmentation is a well-documented, dose-dependent side-effect appearing most commonly in sun-exposed areas, mucosa, teeth, and sclera. The pathophysiologic causes of this hyperpigmentation are believed to result from its metabolites being deposited in the dermis of affected skin, and inflammation causing epidermal melanin to also be deposited in the dermis. The chronic photoactivation of these constituents likely contributes to the formation of this drug-induced pigmentation cascade. 5 We present a case series of patients with minocycline-induced skin pigmentation treated with a both nanosecond-domain and picosecond-domain lasers using a variety of wavelengths. Finding the optimal combination of lasers and treatment parameters often requires multiple test spots, and changes to the treatment regimen once pigmentation response reaches a plateau with a given device or treatment regimen. Furthermore, a noticeable adjustment in the wavelength will be observed during the subsequent treatment sessions, with the intention of maximizing efficacy.

Discussion Drug-induced hyperpigmentation has been representing 10% to 20% of reported cases of acquired hyperpigmentation. 5 Among the various medications associated with the development of drug-induced hyperpigmentation, minocycline is frequently reported as an agent. However, it is important to note that only up to 15% of patients using minocycline may experience pigmentation issues. 2 , 5 Minocycline-induced pigmentation (MIP) can manifest as a consequence of long-term minocycline therapy, believed to stem from the deposition of insoluble minocycline complexes, pigmented or reactive metabolites, elevated melanin levels, or a combination thereof. 4 Among the 4 recognized types of MIP, type I is the most prevalent and is characterized by the presence of blue-black macules primarily within the scarring regions, notably acne scars, predominantly located on the face ( Fig 8 ). This type is postulated to result from the formation of iron chelates involving minocycline. In contrast, type III is the least common variant and manifests as a muddy brown pigmentation known as the “dirty skin syndrome” within sun-exposed areas, typically observed on the face. This type is thought to arise from heightened melanin levels in the epidermis and dermal macrophages. Notably, a newly reported type of pigmentation, type IV, shares similarities with type III but is limited to scars, encompassing both sun-exposed and protected areas of the body. 2 , 3 , 6 , 7 The initial approach to managing drug-induced hyperpigmentation involves discontinuation of the causative agent and exploration of alternative treatment options, aiming to partially or completely resolve this complication. Historically, quality-switched lasers such as Alexandrite, Ruby, and Nd:YAG nanosecond lasers have been the favored modality for addressing this condition. 8 We hold the belief that both nanosecond and picosecond-domain lasers demonstrate effective results in addressing drug-induced pigmentation. Although they have proven their effectiveness in managing hyperpigmentation, it is important to acknowledge that pigments resulting from the same drug can exhibit varying responses in different patients. In comparison to picosecond lasers, Q-switched lasers, sometimes, might have certain limitations, as they frequently necessitate multiple treatment sessions and could lead to incomplete outcomes. 2 , 4 , 7 , 8 , 9 , 10 The exact mechanism behind the efficacy of picosecond lasers in treating minocycline pigmentation remains poorly understood. However, one proposed hypothesis for their superiority over Q-switched lasers is the significantly shorter pulse duration, which is less than the thermal relaxation time of the target chromophore. This same mechanism also accounts for the enhanced response of tattoo ink as a target chromophore to picosecond lasers when compared with Q-switched lasers. Although Q-switched lasers deliver energy to a target chromophore in nanoseconds (1 billionth of a second), picosecond lasers do so in picoseconds (1 trillionth of a second). The shorter pulse durations may create a variance in photoacoustic effect in addition to the photothermal effect. For selective photoacoustolysis to take place, the pulse duration must be equal to or less than the acoustic diffusion time of the target chromophore, representing another potential mechanism through which picosecond lasers may exhibit greater efficacy with specific chromophores compared with nanosecond lasers. 9 Within our case series, the first patient exhibited the most pronounced response to the 730 nm wavelength compared with the other wavelengths tested. The 730 nm, 246 ps Ti:sapphire lasers on the market emit picosecond-domain pulses and offer a peak power of 0.41 GW. This short pulse duration is advantageous for targeting smaller cytoplasmic granules while minimizing photothermal effects, which may contribute to a decreased risk of adverse effects. 8 Moreover, the superior response observed with the 730 nm wavelength, in contrast to other wavelengths employed in our case, may be attributed to its higher peak power or its ability to effectively target chromophores at appropriate depths within the dermis and basement membrane of the epidermis. 11 In this case series, we have observed an inconsequential response to the implementation of the Q-switched laser in the 2 patients under investigation. However, it is crucial to highlight that a subset of patients with MIP, as documented in existing literature, has demonstrated remarkable outcomes when treated with the Q-switched Nd:YAG laser. 2 The efficacy of this treatment approach could be attributed to various factors, including the depth and density of the deposited pigments, the individual’s unique skin reactivity to the medication or its metabolites, and other incompletely understood mechanisms. We believe based on our experience that switching devices can result in faster clearance once maximal fluences, wavelengths and pulse durations reached with a given device.

Conclusion Our case series presents the first documented instance of successful treatment of minocycline-induced hyperpigmentation utilizing a 730 nm wavelength Ti:sapphire picosecond-domain laser. This remarkable finding highlights the potential significance of picosecond-domain lasers as a valuable addition to the therapeutic armamentarium for managing challenging and recalcitrant cases of cutaneous hyperpigmentation arising as an adverse effect of medication, such as MIP. Furthermore, the utilization of the 730 nm wavelength in our cases, which emits the shortest picosecond-domain pulse currently available in the market, highlights the potential benefits of ultrashort pulse durations in achieving superior outcomes with minimal photothermal effects. Remarkably, certain patients exhibit diverse responses to varying wavelengths and pulse durations. Intriguingly, the Q-switched laser, characterized by its nanosecond pulse duration, has demonstrated comparable efficacy to picosecond lasers in certain cases, albeit the reasons behind this phenomenon remain elusive. Continued research and investigation are warranted to optimize treatment protocols further, deepen our understanding of the underlying mechanisms, and refine patient selection criteria. This endeavor will lead to the provision of more effective and personalized interventions for resolving minocycline-induced hyperpigmentation, empowering dermatologists to offer their patients improved outcomes and enhanced well-being.

Key words Abbreviations used minocycline-induced pigmentation neodymium:yttrium-aluminum-garnet

Patient 1 A 71-year-old woman with Fitzpatrick skin type I and a history of acne scaring presented to our clinic with gradual onset of diffuse, brown, symmetric hyperpigmentation predominantly in the sun-exposed areas her face, developing over the course of 2 to 3 years. She had been taking minocycline to treat acne vulgaris for 30 years before her presentation, with a daily dose of 100 mg. One year before presenting to our practice, her minocycline treatment has been stopped, and the patient underwent a solitary 1064 nm neodymium:yttrium-aluminum-garnet (Nd:YAG) Q-switched laser procedure at an external facility, but no noticeable improvement was observed. On examination, light brown and slate-gray hyperpigmented patches were predominantly observed on the temples, nose, chin, cutaneous lips, and lateral cheeks, without involvement of the mucosa or nails ( Fig 1 ). Based on the patient’s medication history and clinical examination findings, the patient was diagnosed with minocycline-induced hyperpigmentation. To ascertain the optimal treatment parameters for this patient, test spots using 4 different lasers were performed. Because the patient reported that they had no improvement after treatment with a 1064-nm, nanosecond-domain laser and so many other options were available, this laser was not included in the test spots. Test spots were administered with: a picosecond-domain 1064 nm laser (PicoWay, Candela Medical Corporation) using 3.2 J/cm 2 with a 4-mm spot, a laser-pumped Ti:sapphire picosecond-domain laser emitting 730-nm (PicoWay, Candela Medical Corporation) using 1.8 J/cm 2 and a 3 mm spot, a 755-nm alexandrite picosecond-domain laser (PicoSure, Cynosure, LLC) using 6.4 J/cm 2 fluence and a 2 mm spot, and a 785-nm Ti:sapphire picosecond-domain laser (PicoWay, Candela Medical Corporation) using 1.4 J/cm 2 and a 3 mm spot ( Fig 2 ). The efficacy of the test spots was evaluated 1 month after treatment, and the test site treated the 730 nm, Ti:sapphire laser-pumped-laser handpiece with a fluence of 1.8 J/cm 2 , and a 3 mm spot exhibited the most favorable response ( Fig 2 ). Following administration of 4% topical lidocaine cream (LMX4, Ferndale Laboratories Inc Company) for 45 minutes, the areas of the face evidencing minocycline pigmentation were treated with a single pass the 730 nm, Ti:sapphire laser with a fluence of 1 J/cm 2 and a 4 mm spot. Immediate white frosting of the pigmented areas was observed as the desired end point. Immediately after treatment, the treated areas demonstrated transient erythema and mild edema, which improved within a few hours after treatment by patient report. Three treatments were administered at 6 to 8 week intervals resulting in pigment clearance ( Fig 1 ). Patient 2 A 72-year-old man with Fitzpatrick skin type II, who had been taking minocycline intermittently for decades to treat rosacea, presented for treatment of progressive darkening of the central face. The patient had been taking a daily dose of 100 mg of minocycline during rosacea flare-ups for over 10 years, followed by 3 days per week as maintenance therapy for the next 20 years. Approximately 1 year before presentation, the patient noticed a gradual gray discoloration of his nose and perioral region, and was advised by his dermatologist to discontinue his minocycline. On presentation, the patient was examined using a cross-polarized, magnifying headlamp (v600, Syris Scientific), revealing slate-gray pigmentation involving the nose and upper cutaneous lip, consistent with minocycline pigmentation ( Fig 3 ). The oral mucosa and nails, were not involved. The patient was taking no other medications. Following administration of topical 4% lidocaine cream (LMX4, Ferndale Laboratories Inc Company) the patient was treated with a nanosecond-domain, Q-switched 1064 nm laser with a fluence of 6.6 J/cm 2 , and a 5 mm spot size, with minimal improvement noted 2 months after treatment ( Fig 4 ). For his second treatment, a picosecond-domain, Ti:sapphire, 785 nm laser (PicoWay, Candela Corporation), was selected using a fluence of 0.8 J/cm 2 , and a spot size of 4 mm on the nose, and 1.4 J/cm 2 with a of 3 mm spot on the upper lip. Significant improvement was seen 2 months after this treatment ( Fig 5 ). Two months later a second treatment was administered using the Ti:sapphire, 730 nm, picosecond laser (PicoWay, Candela Corporation) with a fluence of 1.8 J/cm 2 and a 3 mm spot, resulting in dramatic clearing of the pigment 5 months after his final treatment ( Fig 6 ). Patient 3 A 66-year-old woman with Fitzpatrick skin type II presented with a prolonged history of minocycline usage, resulting in pigmentation affecting the nose and both upper and lower cutaneous lips. Notably, minocycline has been discontinued several months before her initial consultation at our facility. She was treated to all areas of pigmentation on her face with a 1064 nm, Q-switched Nd:YAG laser (Con-Bio RevLite SI, Cynosure, Inc) using a fluence of 6 J/cm 2 and a 4 mm spot. Three months later, a second treatment was administered using 7 J/cm 2 for the nose and upper cutaneous lip, and 4 J/cm 2 on the lower cutaneous lip, with a 4 mm spot. Four months later, the patient received a third treatment with the same device using 8 J/cm 2 and a 4 mm spot. With decreasing pigmentation after each treatment, the subsequent treatments require using a higher fluence to achieve the same tissue end point of immediate whitening. Five-years after the final treatment the patient presented for treatment of an unrelated condition and demonstrated long-term improvement ( Fig 7 ). Conflicts of interest None disclosed.

CC BY

no

2024-01-16 23:42:00

JAAD Case Rep. 2023 Nov 30; 43:62-68

oa_package/9a/57/PMC10788405.tar.gz

PMC10788406

38043604

Introduction Cognitive decline ranges from the minimal decline that is associated with normal aging to dementia. In between these 2 extremities, Mild Cognitive Impairment corresponds to an intermediate stage [ 1 ]. With an overall prevalence of Mild Cognitive Impairment worldwide assessed at 15.6 % in 2022 and an estimated 57.4 million cases of dementia worldwide in 2019 [ 2 ], cognitive decline represents a major health issue. Moreover, this burden will be of even greater concern in the future, with a projection of 152.8 million cases of dementia in 2050 [ 3 ]. Although no effective treatment is available to counteract dementia progression [ 4 ], ≤40% of dementia could be prevented or delayed if addressing modifiable risk factors [ 5 ]. Growing evidence from in vitro or in animal models and from individual epidemiologic studies in healthy adults highlights cues of association between nutrition and cognitive function through several mechanisms, including inflammation, oxidative stress, and control of other risk factors [ 6 ]. Dairy products may have anti-inflammatory and neuroprotective properties [ [7] , [8] , [9] ]. In addition, dairy products might lower the risk of cardiovascular and metabolic disease [ 10 , 11 ], which are known risk factors for cognitive impairment and dementia [ 12 ]. Nevertheless, on a meta-analytical level, the association between dairy intake and cognitive function has not been robustly illustrated yet. Previous systematic reviews and meta-analyses have led to conflicting trends [ 13 , 14 ]. On the one hand, the meta-analysis by Wu et al., (2016) [ 14 ], including 3 cross-sectional and 4 cohort studies, found that high milk consumption was associated with decreased risk of cognitive disorders [odds ratio (OR): 0.72; 95% confidence interval (CI): 0.56, 0.93]. However, this result was treated with caution in the perspective of many limitations of the study, which were principally the large heterogeneity (I 2 : 64%) because of the type of outcome and characteristics of participants. As a matter of fact, the authors reported a stronger negative association with no heterogeneity (I 2 : 0%) in subjects with Alzheimer’s disease compared to cognitive impairment/decline and overall dementia and in Asian and African populations compared to Caucasian. On the contrary, the more recent systematic review and meta-analysis by Lee et al., (2018) [ 13 ] identified 1 randomized controlled trial (RCT) and 7 observational cohort studies. Because of limited reported data, the meta-analysis was conducted only among 3 observational cohort studies. Although the authors reported no association between dairy intake and cognitive decline, their results were in the opposite direction to those of Wu et al. [ 14 ], with a higher risk of cognitive decline with higher dairy intake (relative risk: 1.21; 95% CI: 0.81, 1.82, for the highest compared with the lowest intake, I 2 : 64%). Because additional prospective studies on dairy and cognition have been recently published [ [15] , [16] , [17] , [18] , [19] ], and no dose-response meta-analysis is available, we decided to carry out a new meta-analysis. We also decided to take into account all dairy foods as 1 food group and, whenever possible, subgroups of dairy products, dose-response relationship, geographic differences, and length of follow-up, which could have led to high heterogeneity in previous meta-analyses. The objective of this systematic review and meta-analysis was to summarize the literature on the association between dairy and cognitive decline or incident dementia and to explore the shape of the association using, whenever possible, dose-response nonlinear modeling.

Methods The protocol was registered with the International PROSPERO with the registration number CRD42020192395 and adhered to the PRISMA [ 20 ]. Literature search We conducted a comprehensive literature search in cooperation with an experienced medical information specialist in Embase.com (Elsevier), Medline (Ovid), Cochrane Central Register of Controlled Trials (Wiley), Cochrane Database of Systematic Reviews (Wiley), Web of Science Core Collection (Clarivate) and Google Scholar, from inception up to 11 July 2023 (last date searched) to identify all prospective observational studies and RCTs that reported data on usual dairy intake at baseline, with prospective follow-up data on cognitive decline or incidence dementia among adults. The search strategy combined terms related to dairy intake (among others, dairy products, milk, yogurt, butter, cheese, cream, whey, casein, and lactalbumin) and cognitive decline (dementia, memory disorder, cognitive defect, Alzheimer’s, and neuro-degenerative disease). No date limits were applied. The full search strategies in all databases are provided in Supplementary Material 1 . In addition, we reviewed reference lists of included studies to retrieve additional relevant articles. We removed duplicate records using Deduklick (Risklick), a fully automated deduplication algorithm [ 21 ]. The results of the searches were uploaded into Rayyan ( https://www.rayyan.ai ) [ 22 ] for title/abstract screening and full-text evaluation. Study selection and data extraction Two reviewers (FV and TF) independently screened the titles and abstracts of the retrieved studies to exclude articles that did not meet the eligibility criteria. Then, they retrieved full texts of the potentially eligible studies and again assessed their eligibility independently. We included studies only in English and in peer-reviewed journals. We excluded studies that recruited only subjects with chronic conditions (e.g., diabetes, hypertension, metabolic syndrome, dyslipidemia, etc.), cross-sectional studies, and studies with a follow-up of <6 mo. For RCTs, we additionally required that studies have a nondairy or low-dairy control group (i.e., not only comparing different dairy products). We also excluded studies that used nonbovine or human milk interventions. We recorded reasons for exclusion in the full-text screening ( Supplementary Material 2 ). Any disagreement between the authors regarding the eligibility of a study was resolved through discussion with a third reviewer (POC-B). We illustrated the selection process in a PRISMA flow diagram. Two reviewers (FV and TF) independently extracted multiple fields based on the following categories: general study information (authors, journal, year of publication, and title), study design (country of origin, setting, sample size, and follow-up time), participant characteristics [age, sex, body weight, and BMI (in kg/m 2 )], exposure (dietary assessment and type of dairy), outcome assessment method (cognitive decline or incident dementia), outcome data (effect estimates with measures of variation and covariates). When a study reported stratified analysis only divided by characteristics of the study population (e.g., apolipoprotein E status) or type of outcome (e.g., Alzheimer’s disease and non-Alzheimer’s disease diagnosis), we combined their results using a fixed-effects model and then included them into the analysis comparing the highest compared with the lowest exposure (e.g., forest plots). Conversely, when including study results in the dose-response analysis, we had to consider them as strata-specific study results. From observational studies, we extracted the outcome data from the most adjusted multivariable models. We extracted relative risk or hazard ratio along with 95% CIs for dichotomous outcomes and mean differences and standard deviation/standard error for continuous outcomes. Finally, we asked the authors of 4 studies [ [23] , [24] , [25] , [26] ] to give us further information on the median dose or ranges in each category or to clarify the definition of serving size. However, we did not receive additional information. Data synthesis and analysis We performed pairwise meta-analyses for all exposures and outcomes using a restricted maximum likelihood random-effects model [ 27 ]. We planned to analyze observational studies separately from RCTs. For dichotomous outcomes (cognitive decline or dementia), we computed the summary risk ratio (RR). Results are presented for the combined outcome (i.e., cognitive decline or dementia incidence), and we performed stratified analysis whenever possible (see below subgroup analyses). We have focused our description and interpretation of the results on assessing the size of point estimates and their statistical precision (CIs) measures without P value fixed cutpoints [ [28] , [29] , [30] ]. We assessed the potential nonlinear relationship through the estimation of a dose-response relationship between dairy intake (measured as the amount in grams/day or frequency in times/day) and cognition. For each exposure category, we assigned the mean or median intake along with the RR and the CI, the number of cases, and of person-years. When means or the median were not available, we used the midpoint of each intake category. For open-ended categories, we used a value 20% lower or higher than the boundary values as performed in other fields [ [31] , [32] , [33] ]. For 1 study [ 15 ] reporting mean dairy intake in g/1000 kcal/d for each category, we used the mean kcal of the same category to calculate the value in g/d. We used a restricted cubic spline function with 3 knots at fixed cutpoints (10th, 50th, and 90th percentiles) using a restricted maximum likelihood random-effects model [ 34 ], assessing the presence of a linear trend [ 35 ]. We also presented the results as RR and relative 95% CIs comparing the highest compared with the lowest exposure category in forest plots. Subgroup and sensitivity analyses Whenever possible, we conducted subgroup analysis by type of dairy product, mean age (<65 compared with ≥65 y), sex, region of origin (Asia, Europe, and Oceania), length of follow-up (<10 compared with ≥10 y), and excluding studies at high risk of bias to reveal potential sources of heterogeneity. In addition, we performed a meta-regression analysis using cognitive function (cognitive decline or dementia incidence) as the dependent variable and the length of follow-up as an independent variable in an adjusted model for potential confounders. We tested heterogeneity among studies using the I 2 test and by visual inspection of the forest plots. We interpreted I 2 values of ≤25%, between 25% and 50%, and above 50% as “low,” “moderate,” and “high” heterogeneity between studies, respectively. We also computed the τ 2 to assess the between-study variance and reported the 95% prediction intervals to evaluate the effect size variation of a future new study. In the nonlinear analysis, we also assessed the variation across individual study results, showing the study-specific trends using predicted curves [ 36 ]. We used Stata-MP version 18.0 (StataCorp LLC, 2023) for all statistical analyses, specifically the “meta,” “mkspline,” and “drmeta” routines. Quality assessment We assessed the quality and risk of bias of the included studies with the Nutrition Quality Evaluation Strengthening Tools, specially developed for dietary methods assessment [ 37 ]. We used the version for cohort studies that consists of 4 domains related to the cohort selection, comparability, ascertainment of the outcomes, and nutrition specific. The overall rating is expressed as poor (most criteria are not met, leading to a high risk of bias), neutral (most criteria are met and are of little or no concern), and good (almost all criteria are met, leading to a low risk of bias). Study quality was evaluated by 2 reviewers (FV and NO), and discrepancies in each domain were resolved with the help of a third author (TF) in case of disagreements. We used Egger’s test and funnel plot to visually assess the indication of publication bias [ 38 ].

Results The systematic search identified 3663 records ( Figure 1 ), and 1 additional article was retrieved through reference list scanning. After removing duplicates, we screened 2299 records, of which 2253 were excluded based on title and abstract screening. We retrieved 46 full-text articles for evaluation. We excluded 31 articles based on the eligibility criteria: population with chronic conditions ( n = 3), not evaluating milk or dairy ( n = 12), follow-up duration <6 mo ( n = 6), cognitive decline or dementia not the outcome of interest ( n = 1), no results available ( n = 1), not in English language ( n = 1), cross-sectional studies ( n = 5), not peer-reviewed ( n = 1), and same cohort as another included study ( n = 1). We included the remaining 15 studies, all with prospective cohort design and including a total of 312,580 participants ( Table 1 ). Participants mean age ranged from 53 [ 17 ] to 91 y [ 16 ] at baseline. In the study by Yamada et al. 2003 [ 26 ] in the Adult Health Follow-Up study, participants were 30 y and older [ 26 ]. Seven studies were from Europe [ 16 , 18 , 25 , [39] , [40] , [41] , [42] ], 6 studies from Asia [ 15 , 17 , 19 , 24 , 26 , 43 ], 1 from Australia [ 23 ], and 1 from the United States [ 44 ]. Participants were followed for a minimum of 4.8 y [ 23 ] to a maximum of 30 y [ 26 ] with a median follow-up of 11.4 y. Among the selected studies, 5 studies included the outcome of dementia incidence using International Classification of Diseases 8-10 or Diagnostic and Statistical Manual-IIIR/Diagnostic and Statistical Manual-IV criteria [ 16 , 18 , 26 , 39 , 43 ], and 10 studies evaluated cognitive function [ 15 , 17 , 19 , [23] , [24] , [25] , [40] , [41] , [42] , 44 ]. Most studies evaluated cognitive function with the Mini-Mental State Examination [ 16 , 17 , 19 , [23] , [24] , [25] , 41 ], whereas others used other neuropsychological tests [ [40] , [41] , [42] , 44 ]. Six studies used food frequency questionnaires [ [15] , [16] , [17] , 25 , 39 , 41 , 43 , 44 ], including between 26 [ 16 ] and 188 [ 35 ] food items. Other studies used dietary records [ 18 , 24 , 40 ], dietary history [ 42 ], or other questionnaires [ 19 , 23 , 26 ]. Although 2 studies only evaluated milk intake (high fat [ 23 ] or total [ 44 ]) and 1 cheese intake [ 39 ], most studies evaluated total dairy intake [ [15] , [16] , [17] , [18] , [19] , 24 , 25 , [40] , [41] , [42] , 45 ]. The selection of covariates for adjustment was diverse; most studies adjusted their results for age, sex, education, physical activity, BMI, and previous comorbidities. Almost all studies adjusted their results for total calorie intake, except those without a full dietary assessment [ 16 , 19 , 23 , 26 ]. Moreover, some studies adjusted their outcomes for additional nutritional factors, for example, fruit/vegetable intakes [ 15 , 17 , 18 , 39 ] or “healthy” dietary patterns [ 17 , 40 , 43 ], among others. The assessment with the Nutrition Quality Evaluation Strengthening Tools revealed that out of 15 studies, there were 1 poor, 10 neutral (67%) and 4 good studies. Even if none of the studies assessed if the exposure difference was maintained over the study period, 14 out of 15 were rated as good in the nutrition domain. The main risk of bias came from the comparability domain because few of them reported the baseline differences between those lost to follow-up and the included participants, compared how many participants were lost to follow-up in each exposure group, or performed repeated measurements of the nutritional aspect under study. The detailed results are available in Supplementary Table 1 . The dose-response analyses ( Figure 2 ) included 10 studies that had sufficient information on the consumption of dairy products by increasing quantity [ 15 , 17 , 18 , [41] , [42] , [43] ] or by increasing frequency [ 16 , 17 , 19 , 26 , 39 ] in relation to cognitive decline or dementia. When assessing the quantity of consumption, we observed a nonlinear association, with an initial decline in risk until 150 g/d (RR: 0.88; 95% CI: 0.78, 0.99), after which a slight change in direction was observed. We found an almost linear negative association when we considered the frequency of consumption (RR for linear trend 0.84; 95% CI: 0.77, 0.92 for 1 time/d increase of dairy products). The results of the combined outcome (i.e., dementia or cognitive decline) showed that the highest intake of dairy products compared to the lowest intake has no association with cognitive decline or dementia (RR: 0.94; 95% CI: 0.82, 1.07) with high heterogeneity (I 2 : 69.2%) and between-study variance (τ 2 : 0.03) as showed by the wide prediction intervals (95% CI: 0.61, 1.45) ( Supplementary Figure 1 ). For the outcome cognitive decline, we were able to combine 7 of the 9 studies [ 17 , 19 , [23] , [24] , [25] , 41 , 42 ]: we observed no associations of the highest compared with the lowest dairy intake on cognitive decline (RR: 1.01; 95% CI: 0.86, 1.20) with high heterogeneity (I 2 : 73.5%) and between-study variance (τ 2 : 0.03) and wide prediction intervals (95% CI: 0.60, 1.72). Only 2 studies reported continuous results for cognitive function [ 40 , 44 ] and total dairy intake using linear regression analysis; thus, a meta-analysis with risk estimates was not possible. For the outcome of incident dementia, we identified 6 studies [ 15 , 16 , 18 , 26 , 39 , 43 ]. We observed a decreased risk of dementia with the highest intake of dairy compared with the lowest intake (RR: 0.83; 95% CI: 0.67, 1.03), although characterized by high heterogeneity (I 2 : 63.0%) and between-study variance (τ 2 : 0.04) leading to wide prediction intervals (95% CI: 0.44, 1.59) ( Supplementary Figure 1 ). In subgroup analyses, we observed that part of the heterogeneity could be explained by sex as studies carried out in both males and females reported inverse association (RR: 0.85; 95% CI: 0.78, 0.93) also characterized by negligible heterogeneity (I 2 : 2.6%, τ 2 : 0.00), whereas the studies reporting sex-specific results showed very heterogeneous and imprecise positive (in males) or null (in females) associations ( Supplementary Figure 2 ). The dose-response meta-analysis restricted to such studies carried out in both sexes [ 15 , 17 , 41 , 43 ] showed a nonlinear association, although imprecise because of the lower number of studies, with a nadir at 100–150 g/d ( Supplementary Figure 3 ). Stratified analysis by age at recruitment of study participants showed lower risk in studies considering younger subjects <65 y (RR: 0.88; 95% CI: 0.76, 1.01) also characterized by limited heterogeneity (I 2 : 24.3%, τ 2 : 0.01) compared to studies recruiting older subjects ≥65 y (RR: 0.95; 95% CI: 0.75, 1.21, I 2 : 77.4%, τ 2 : 0.08) ( Supplementary Figure 4 ). In the subgroup analyses by region of origin ( Figure 3 ), there was a reduced risk of cognitive decline or dementia with the highest dairy intake compared with the lowest dairy intake in the studies from Asia (RR: 0.83; 95% CI: 0.75, 0.92, I 2 : 0.0%, τ 2 : 0.00) [ 15 , 17 , 19 , 24 , 26 , 43 ]. Conversely, we found no association between dairy and cognitive decline or incident dementia among studies from Europe (RR: 1.01; 95% CI: 0.86, 1.19, I 2 : 41.6%, τ 2 : 0.02) [ 16 , 18 , 25 , 39 , 41 , 42 ] and higher risk with the highest intake compared with the lowest dairy intake in 1 single study from Oceania (RR: 1.75; 95% CI: 1.17, 2.62). In the analysis investigating different types of dairy products ( Supplementary Figure 5 ), we found an inverse association with cognitive decline or dementia when all dairy types are considered (RR: 0.89; 95% CI: 0.83, 0.95, I 2 : 0.33%, τ 2 : 0.00). Conversely, the association with specific dairy products was very heterogeneous and inconsistent as it was reported in a lower number of studies, with the exception of milk and cheese intake alone, investigated in 5 and 4 studies and reporting both null associations, respectively. The dose-response meta-analysis by dairy type ( Figure 4 ) was feasible for these latter subgroups. The analysis showed a null association with milk consumption ≤0.3 times/d, whereas a negative association emerged for high intakes. Conversely, the association seemed to be nonlinear for cheese consumption, with lower risk at 0.3 times/d and null/positive association at higher intakes. The sensitivity analysis excluding the 1 study judged at possible high risk of bias [ 23 ] suggests a stronger negative association between dairy intake for cognitive decline or dementia outcome (overall RR: 0.90; 95% CI: 0.82, 1.00) with decreased heterogeneity (I 2 : 44.7%) and lower study variance (τ 2 : 0.01) despite the still wide prediction intervals (95% CI: 0.69, 1.18) ( Supplementary Figure 6 ). In addition, the association became slightly negative for cognitive decline (RR: 0.94; 95% CI: 0.83, 1.07). Conversely, the dose-response meta-analysis did not change as the 1 study at high risk of bias was excluded, already not reporting exposure doses of dairy intake. Stratified analysis by duration of follow-up (<10 y and ≥10 y) showed little influence on the overall estimate ( Supplementary Figure 7 ). Similarly, the meta-regression analysis for increasing years of length of follow-up adjusting for potential cofounders based on previous stratified analyses (i.e., sex, age category at recruitment, and region of origin) showed almost negligible association with risk of cognitive decline or dementia incidence (beta regression coefficient: –0.005; 95% CI: –0.023 to 0.014) ( Supplementary Figure 8 ). Assessment of small-study bias showed low effects, with symmetry of funnel plot and low effect-based Egger’s test (slope: –0.17; 95% CI: –2.78 to 2.44) ( Supplementary Figure 9 ). Assessment of study-specific curves showed higher variation in studies using quantity compared to frequency of consumption of dairy intake ( Supplementary Figure 10 ) when considering overall dairy products. Conversely, stratified analysis by dairy types showed high variation in both studies measuring milk and cheese intake using frequency of consumption ( Supplementary Figure 11 ).

Discussion This systematic review and meta-analysis identified 15 prospective observational studies involving >300,000 participants. Results suggest that dairy might be associated with a lower risk of cognitive decline or dementia but that there may be differences by sex, age, region of origin, level of intake, and type of dairy products. To our knowledge, we are the first study to evaluate dose-response relationships in a meta-analysis of dairy and cognition, suggesting a nonlinear relation with lower risk at ∼150 g/d of overall dairy intake. Our subgroup analyses suggest that this could mainly be explained by differences in the level of intake and type of dairy products. As a matter of that, the intake of dairy products greatly varies across the included studies, mainly depending on the region of origin. Considering only studies in Asia, the highest dairy intake was associated with a much-reduced risk of cognitive decline or dementia and low heterogeneity compared with European studies. Among European studies, there was no association between dairy intake and cognitive decline or dementia. In contrast, the single study conducted in Oceania reported a higher risk of cognitive decline with the highest dairy intake compared to the lowest, although such a study was deemed at high risk of bias, thus limiting the reliability of such results. Similar results were reported in the 2016 meta-analysis by Wu et al. [ 14 ], wherein the stratified analysis by race, studies conducted among Asians had a 43% lower risk of cognitive disorders with higher dairy intakes, whereas for those conducted in Caucasians, there was no association. Divergent results between Asian and European countries have also been reported for stroke [ 46 ]. The amount and types of dairy consumption between regions were considerably higher in studies carried out in European countries, with mean value between 170–711 g/d, than studies in Asian countries where total mean dairy intake ranged between 29–165 g/d. Despite the “Westernization” of Asian diets, populations in Asian countries, in general, still consume lower quantities of dairy products [ 47 ]. Also, in Asian countries, recommendations for dairy intake range between 1–4 servings/d, whereas in Europe, they are slightly higher at 2–4 servings/d [ 48 ], and milk is consumed more frequently than other dairy products [ 46 , 49 ]. Dairy is a heterogeneous food group including fermented or nonfermented foods and differing in nutrients such as fat and sodium. Stratified analysis by dairy type suggested an inverse linear relation when milk intake was considered only, whereas the shape of the association seemed to be nonlinear for cheese intake. In the study by Kesse-Guyot et al. [ 40 ], total dairy intake was not associated with any of the cognitive outcomes; milk intake was associated with worse verbal memory, and yogurt and cheese were associated with better verbal memory in some models. In particular, the study reported detrimental of dairy products effects on working memory performance at intakes higher than recommended, possibly supporting the U-shape association we noted in the dose-response meta-analysis. Unfortunately, we were not able to perform additional analyses for other dairy types because of a limited number of studies. It is noteworthy that in the 2 studies investigating the relation between dairy desserts, a detrimental association was found with 30% higher odds of cognitive decline [ 42 ] and lower scores for both working and verbal memory [ 40 ]. It should be noted that guidelines for dairy intake rarely include dairy desserts, being generally included in sweets products as they may contain high amounts of sugar [ 50 , 51 ]. Overall, these results suggest that the different types of dairy can have opposite effects on cognition. Dairy is also a heterogeneous food group regarding the fat content. We were not able to stratify results by the amount of fat in dairy products (full-fat compared with low-fat products). Two previous studies suggested that the fat content of milk might be associated with worse cognition [ 23 , 42 ]. In line with the results by Vercambre et al. 2009 [ 42 ] (France), where dairy desserts and ice cream were associated with worse cognition, in the study by Almeida et al. 2006 [ 23 ] (Australia), higher intakes of “full-cream dairy” were associated with worse mental health outcomes. The study by Petruvski-Ivleva et al. 2017 [ 44 ] (United States) reported that higher total milk intake was associated with greater cognitive decline, and whereas they did not report stratified results, ≤75% of participants reported skim/low-fat milk intake, in contrast to the 2 previous studies. Therefore, the role of high fat compared with low-fat dairy is still controversial and should be further evaluated. Dairy products are rich in proteins, minerals, vitamins, and essential amino acids that have been directly or indirectly associated with cognitive function [ 52 , 53 ]. Previous studies have shown the beneficial effects of some dairy products, in particular fermented products, on cardiovascular disease or diabetes [ 10 , [54] , [55] , [56] ], which could be mediators of the associations between dairy intake and cognitive decline [ 57 ]. Fermented dairy products have anti-inflammatory components that can affect the risk of dementia [ 7 , 9 , 58 , 59 ]. However, the high fat content in some dairy products can affect cognition negatively through hyperinsulinemia, endothelial damage, oxidative stress, and inflammation [ 53 , 60 , 61 ]. In a study about fat intake at midlife and cognitive decline that did not qualify for our review (as it reported only fat intake from foods, but not food intakes), high saturated fat intake from milk products and spreads was associated with poorer cognitive outcomes and the results did not change after adjusting for several cardiovascular risk factors and diseases [ 61 ]. In addition, calcium content may greatly vary among different types of dairy products with possible effects on oxidative stress as both consumption of dairy products and calcium intake have been associated with higher glutathione peroxidase in the brain, suggesting possible protective mechanisms of such detrimental association [ 62 ]. Concomitantly, lower intake of dairy products could be associated with a specific dietary pattern, rich in plant-based foods and low in saturated fats, which have been shown to positively modulate the inflammatory and immune response and to decrease the risk of neurocognitive impairments and eventually the onset of dementia [ 63 ]. For instance, higher adherence to the Mediterranean diet was associated with a positive effect on cognitive decline [ 64 ]. The Japanese-style diet has been associated with a lower risk of cardiovascular disease, stroke, or heart disease mortality [ 65 ]. However, according to the 2016 Japanese National Health and Nutrition Survey, consumers of a nondairy diet were less likely to meet dietary requirements, whereas dairy consumers were more likely to exceed the recommendations for saturated fat [ 66 ]. In fact, studies that took into account other food groups or dietary patterns that could affect the relationship between dairy consumption and cognitive function found no associations [ 17 , 18 , 39 , 40 , 43 , 44 ]. In our search, we did not identify any RCT evaluating the effect of dairy on cognition, probably because of our strict inclusion criteria regarding dairy and cognitive assessments, as well as the duration of the intervention longer than 6 mo. Given that we present only results from observational studies, interpreting the results regarding cause and effect between dairy and cognition should be done carefully. Most of the studies adjusted for sex, age at recruitment, physical activity, smoking status, BMI, educational level, and past major cardiovascular events (stroke, coronary artery disease, and myocardial infarction) or related risk factors (hypertension, dyslipidemia). Some of them failed to adjust for total calorie intake [ 17 , 19 , 26 ], depression or psychological distress [ 17 , 24 , 25 , 41 , 42 ], and cancer [ [15] , [16] , [17] , 24 , 41 , 45 ]. However, we cannot discard that the observed association is affected by residual confounding. In addition, dietary assessments were heterogeneous regarding the type of questionnaires used, definitions of dairy intake, and recall timeline. In addition, each study defined the outcome for cognition differently, which may be the main challenge when interpreting the results of our review. Many studies used nonspecific global screening tools, many of which could have demographic biases if they have not suitably validated in representative populations. Regarding the optimal dairy intake that can be associated with greater cognitive health, our dose-response analysis for the continuous intake of dairy products suggests a nonlinear association with nadir at 150 g/d of dairy intake. For example, this would be equivalent to consuming 1 yogurt or 1 glass of milk/d, corresponding to 125–200 g/4.4–7 oz of yogurt or 200–250 mL/6.8–8.5 oz of milk/d according to Food-Based Dietary Guidelines in Europe [ 67 ]. This is in line with the mean dairy intake in Japan among milk consumers (∼160 g) [ 66 ] but lower than the mean intake in Europe, where 91.6% consume 2 or more dairy servings per week in older adults [ 68 ]. However, these results should be interpreted with caution. The included studies used a variety of categories of milk intake (“times per week,” “times per day,” “g/d,” “serving/d,” “high/low intake,” “tertiles,” etc.). Many studies did not report exact doses for “servings” and “time”; therefore, only a limited set of studies could be included in this analysis. Because most studies reported only 1 measurement of diet, this might not reflect long-term consumption patterns. The lack of multiple dietary assessments hampered the evaluation of possible changes of time of dairy intake. Even though some studies suggest that the recall of past dairy intake may be more reliable because of stable consumption [ 69 , 70 ], more recent prospective studies assessing dairy product consumption over the life course are needed to evaluate dairy consumption changes. By including prospective studies of long duration, we aimed to include subjects whose diet was monitored long before cognition was assessed. However, we cannot discard differential measurement error because of the recall bias, as early symptomatology of cognitive decline could have affected the way people report their diet or their dietary choices [ 71 ]. Deteriorating cognition could also impact food selection or dietary behaviors. However, most of the studies have a low prevalence of cognitively impaired subjects [ 17 , 26 , 40 ] or excluded them in the analysis [ 18 , 19 , 24 , 25 , 41 , 43 ], and for most studies, there were many years between dietary and cognitive assessments in many studies. In our review, the stratified analysis by duration of follow-up showed only a slight reduction of risk of cognitive decline with the highest dairy intake in studies of >10 y of follow-up that was also consistent with the meta-regression analysis, suggesting a slightly negative association with increasing follow-up duration. In the future, biomarkers of dairy intake could help prevent recall errors and multiple assessments of dietary habits [ 72 ]. In this review, our focus was specifically on studies conducted in relatively healthy populations and for primary prevention of cognitive decline. Consequently, we deliberately excluded studies involving only patients with conditions such as diabetes, hypertension, and other chronic diseases. The association between hypertension [ 73 ], diabetes [ 74 ], or metabolic syndrome [ 75 ] and dementia has been extensively studied, and these conditions are considered to be modifiable risk factors for dementia in contemporary guidelines [ 5 ]. Healthcare professionals are actively encouraging patients to modify their lifestyles as part of their clinical management [ 76 ]. In the context of cognitive decline and dementia, dietary modifications among these patients are actually for secondary rather than primary prevention. Therefore, dietary recommendations to prevent dementia among patients with chronic diseases at high risk of dementia might be different than the recommendations to the general population. Considering that studies conducted among patients usually recruit from hospitals, it’s essential to acknowledge that hospitalization can impact dietary recall and potentially influence recent dietary habits. Thus, dietary questionnaires collected during or close to a hospital stay may not accurately represent an individual’s typical long-term dietary exposure. Most importantly, dietary modifications to prevent further consequences of other chronic conditions might lead to reverse causation. As the prevalence of chronic disease is very high in Western populations such as the United States population, being in the order of >10% for diabetes, nearly 50% for hypertension, and 40% for metabolic syndrome [ 77 ], the results and the findings of our meta-analysis would not be automatically and directly applicable to a substantial part of the population, limiting the generalizability of our results. Future studies should evaluate in detail the role of dairy intake on cognition among people with comorbidities such as diabetes and other populations at high risk of dementia. As strengths of our study, we included only prospective studies and planned several subgroup analyses to address the heterogeneous results of the previous literature. However, we acknowledged that some amount of heterogeneity was still present in stratified analyses, probably linked to the different types of dairy products or to the method of outcome assessment characterized by high variation across studies and countries. Compared to previous meta-analyses of prospective observational studies on dairy intake and cognitive decline, we additionally included 5 recent studies and 2 older studies that were not included in the 2 previous meta-analyses [ 13 , 14 ], with the opportunity to implement several stratified analyses showing the effect modification of sex, region of origin, and especially types of dairy products. Nonetheless, the number of studies in some of them was still limited, with consequent high heterogeneity. In addition, restricting our analysis to individuals without (known) chronic diseases would have limited the external validity of our findings but may have increased the internal validity by avoiding the risk of reverse causation linked to dietary advice in participants with chronic disease, thus reducing the risk of bias in exposure assessment. Our exclusion criteria allow us to focus on the long-term effects of usual dairy intake and prevent potential recall bias. However, this led to not including RCTs as they were of too short duration. In addition, because of the small number of studies reporting continuous effects and stratified analyses by type of dairy, we could not conduct relevant stratified analyses. In conclusion, the results from our systematic review and meta-analysis suggest a potential negative association of dairy intake on dementia, with regional differences. Future studies should evaluate the role of specific types of dairy products on cognition, focusing on potential differences in dairy types, intake levels, and population characteristics.

FV and TF shared the first authorship. Dairy intake may influence cognition through several molecular pathways. However, epidemiologic studies yield inconsistent results, and no dose-response meta-analysis has been conducted yet. Therefore, we performed a systematic review with a dose-response meta-analysis about the association between dairy intake and cognitive decline or incidence of dementia. We investigated prospective studies with a follow-up ≥6 mo on cognitive decline or dementia incidence in adults without known chronic conditions through a systematic search of Embase, Medline, Cochrane Library, Web of Science, and Google Scholar from inception to 11 July 2023. We evaluated the dose-response association using a random-effects model. We identified 15 eligible cohort studies with >300,000 participants and a median follow-up of 11.4 y. We observed a negative nonlinear association between cognitive decline/dementia incidence and dairy intake as assessed through the quantity of consumption, with the nadir at ∼150 g/d (risk ratio: 0.88; 95% confidence interval: 0.78, 0.99). Conversely, we found an almost linear negative association when we considered the frequency of consumption (risk ratio for linear trend: 0.84; 95% confidence interval: 0.77, 0.92 for 1 time/d increase of dairy products). Stratified analysis by dairy products showed different shapes of the association with linear inverse relationship for milk intake, whereas possibly nonlinear for cheese. The inverse association was limited to Asian populations characterized by generally lower intake of dairy products, compared with the null association reported by European studies. In conclusion, our study suggests a nonlinear inverse association between dairy intake and cognitive decline or dementia, also depending on dairy types and population characteristics, although the heterogeneity was still high in overall and several subgroup analyses. Additional studies should be performed on this topic, including a wider range of intake and types of dairy products, to confirm a potential preventing role of dairy intake on cognitive decline and identify ideal intake doses. This review was registered at PROSPERO as CRD42020192395. Keywords Abbreviations confidence interval odds ratio randomized controlled trial risk ratio

Author contributions The authors’ responsibilities were as follows – POC-B: designed the study with feedback from NR, MV, and CDG; DK-H: prepared the literature search; FV and TF: conducted the systematic review and selected of the articles, with feedback from POC-B; FV and NO: performed the risk of bias assessment with feedback from TF; FV and TF extracted data for analysis; TF: conducted all statistical analyses; FV, TF, and POC-B: interpreted the results with feedback from all authors and wrote the first draft of the manuscript; POC-B: had primary responsibility for final content, and all authors: read and approved the final manuscript. Conflict of interest The authors report no conflicts of interest. Funding This systematic review and meta-analysis is funded by the SNF-project grant 204967 “Prospective international study of dairy and inflammation on cognitive decline” (PI: PC-B), which also funds NO. TF and MV were supported by the grant “Dipartimenti di Eccellenza 2018–2022” to the Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia from the Italian Ministry of University and Research. TF is supported by grants PRIN 2022 (no. 2022MHMRPR) and PRIN 2022 PNRR (no. P20229KSXB) from the Italian Ministry of University and by grant FAR2023 from the University of Modena and Reggio Emilia . Data availability Data described in the manuscript, code book, and analytic code will be made available upon request, pending application and approval of the corresponding author.

Supplementary data The following is the Supplementary data to this article:

CC BY

no

2024-01-16 23:42:00

Adv Nutr. 2023 Dec 1; 15(1):100160

oa_package/b3/4d/PMC10788406.tar.gz

PMC10788408

38142636

Introduction Migraine is the second cause of disability worldwide. 1 A small, yet undefined proportion of individuals with migraine experiences disabling attacks that acute and preventive strategies fail to control. These individuals have resistant or refractory migraine depending on the number of unsuccessful preventive treatments. Reviewing the clinical scenarios, mechanisms, and therapeutic strategies specific to resistant and refractory migraine is especially timely given the availability of new drugs for individuals with resistant migraine and advancements in the migraine field that might promote the understanding, prevention, and treatment of refractory migraine. Search strategy and selection criteria We selected references by searching PubMed, the Cochrane library, MEDLINE, and Embase and for manuscripts published in English between Jan 1, 2013, and June 31st, 2023. We used the term “migraine” combined with the terms “resistant”, “refractory”, “prevention”, “failure”, “disabling”, “debilitating”, “neurophysiology”, “neuroimaging”, “magnetic resonance imaging”, “electroencephalogram”, “diet”, “exercise”, “sleep”, “neuromodulation”, and “behavioural therapy”. We included original data, meta-analyses, consensus statements, guidelines, reviews, comments, and opinions dealing with difficult-to-treat migraine, resistant or refractory migraine. The final reference list was based on the relevance to the topic. We prioritised publications within the last 5 years. Definitions At variance with previous definitions of difficult-to-treat migraine 2 , 3 , 4 , 5 , 6 ( Fig. 1 ), which defined a single clinical entity, the European Headache Federation (EHF) definitions of 2020 distinguished resistant from refractory migraine, based on the failure of ≥3 classes of preventive drugs for resistant migraine and failure of all classes of preventive drugs for refractory migraine. 7 Resistant migraine can evolve into refractory migraine as more preventive treatments fail. Treatment failure is defined either as a lack of efficacy after trying a drug class for an adequate duration at an adequate dose, intolerable adverse events, or contraindication. Contraindication is included among the possible causes of medication failure as it forces the individual not to take the medication and is, therefore, not different from intolerance. The available classes, doses, and durations of preventive treatments were coded in the 2020 EHF definition together with contraindications. Of note, medication classes could be trialled in any order, without distinction into first or second lines. In both resistant and refractory migraine, individuals have ≥8 monthly days of debilitating headache for at least 3 and 6 months, respectively. 7 The presence of debilitating headache days implies that treatment of acute attacks is also unsuccessful in individuals with resistant or refractory migraine. Individuals with either high-frequency episodic migraine (EM) or chronic migraine (CM) can have resistant or refractory migraine ( Fig. 2 a). The presence of medication overuse (i.e., overuse of symptomatic treatments for migraine) does not exclude any of the diagnoses, but documented acute drug withdrawal attempts are mandatory to diagnose refractory migraine. 7 Notably, the EHF definitions consider the residual number of monthly headache days, irrespective of the reduction in monthly migraine or headache days obtained with preventive treatments. Individuals with ≥30% or ≥50% reduction in monthly migraine or headache days experience in some cases substantial residual migraine days ( Fig. 2 b).

Conclusions Treatment-related and individual factors might lead an individual with migraine to a resistant form, still treatable with specific drugs, or a refractory form, that cannot be managed satisfactorily with any treatment. Individuals with resistant or refractory migraine should be referred to expert headache care; in those with resistant migraine the preferential approach includes migraine-specific medications, while those with refractory migraine should receive a multidimensional approach in which pharmacological and non-pharmacological treatments are coupled with management of behavioural and psychological factors. In theory, managing migraine in its early years can prevent resistance and refractoriness. Development of personalised tools to predict refractoriness is a research priority that might finally lead to the development of targeted strategies changing the course of the disease.

Summary Migraine is a leading cause of disability worldwide. A minority of individuals with migraine develop resistant or refractory conditions characterised by ≥ 8 monthly days of debilitating headaches and inadequate response, intolerance, or contraindication to ≥3 or all preventive drug classes, respectively. Resistant and refractory migraine are emerging clinical definitions stemming from better knowledge of the pathophysiology of migraine and from the advent of migraine-specific preventive treatments. Resistant migraine mostly results from drug failures, while refractory migraine has complex and still unknown mechanisms that impair the efficacy of preventive treatments. Individuals with resistant migraine can be treated with migraine-specific preventive drugs. The management of refractory migraine is challenging and often unsuccessful, being based on combinations of different drugs and non-pharmacological treatment. Future research should aim to identify individuals at risk of developing treatment failures, prevent the condition, investigate the mechanisms of refractoriness to treatments, and find effective treatment strategies. Keywords

Epidemiology Given the recency of definitions of resistant and refractory migraine, the epidemiology of those conditions has not been systematically explored. Resistant and refractory migraine are expected to be rare in the general population, but frequent in headache centres. An international survey showed that individuals with resistant migraine were seen at least weekly by 11/83 (13%) of physicians in general primary care or neurology, 34/71 (48%) of those with a special interest in headache care, and 92/123 (75%) of physicians in headache specialist centres; the corresponding proportions for refractory migraine were 7/83 (8%), 16/71 (23%) and 57/123 (46%) respectively ( Fig. 2 c). 8 Clinical features Resistant and refractory migraine can be present in high-frequency EM or CM and in individuals with and without medication overuse. Resistant migraine might become treatable when a more effective or tolerable preventive treatment is started. In clinical practice, treatment consisting of oral agents not specific to migraine had failed in most of the individuals with resistant migraine. In fact, reimbursement policies restrict the use of monoclonal antibodies (mAbs) targeting the calcitonin gene-related peptide (CGRP) pathway to individuals with prior treatment failures and the use of onabotulinumtoxinA is limited to CM. Resistant migraine can also progress to refractory migraine in case of insufficient response to escalation treatments. Many individuals with resistant or refractory migraine become frustrated in their long journey of misdiagnoses, unnecessary investigations, and ineffective treatments. 9 Fig. 3 reports some factors that might predispose to treatment refractoriness. Those factors are not directly linked to resistance to preventive treatments; nevertheless, they are risk factors for migraine worsening and chronification, which is a form of migraine progression. Pain-related comorbidities such as fibromyalgia, irritable bowel disease, and complex regional pain syndrome are associated with central sensitisation to pain. 10 Studies are needed to investigate how these pain-related comorbidities affect resistance to treatments. Psychiatric comorbidities could favour progression to CM through hyperactivity of the limbic system, which is implicated in the regulation of both behaviour and pain perception. 11 Stress can decrease response to acute treatments, 12 thus, leading to medication overuse. Pain catastrophising, feelings of helplessness, and ruminative thinking are also more pronounced in individuals with migraine—and mostly CM—compared with those without migraine, 13 which might favour nocebo effect. Head trauma has also been associated with the transformation of EM into CM with medication overuse. 14 Low socioeconomic status and income, and poor social support could contribute to migraine chronification 15 and thus to migraine worsening which might confer resistance to treatments. Basis for resistance and refractoriness Treatment failure in migraine can derive from lack of efficacy, poor tolerability, and loss of treatment effect ( Fig. 3 ). Lack of efficacy and tolerability of migraine preventive drugs can be related to the lack of specificity of oral treatments that have unclear mechanisms of action. This issue is at least in part overcome by recent migraine-specific preventive agents such as CGRP-mAbs and gepants. Specifically, CGRP-mAbs inhibit CGRP signalling, in the case of erenumab, by binding to the extracellular domain of the CGRP receptor (CGRPr) or, in the cases of fremanezumab, galcanezumab, and eptinezumab, by preventing the interaction between CGRP and its receptor. 16 Gepants peripherally bind to the extracellular domain of CGRPr and are subsequently internalised along with CGRPr blocking its endosomal residual action. 17 Regarding efficacy, the estimated therapeutic gain of oral preventatives compared with placebo ranges from −0.4 to −1.5 monthly headache days, 18 whereas CGRP-mAbs led to a reduction of 2–3 monthly migraine days (MMDs) compared with placebo. 19 Placebo response was also higher for injectable CGRP-mAbs compared with oral drugs, resulting in a overall greater benefit in clinical practice. However, even individuals with a high response to preventive treatments might still have a remarkable residual disease burden. Indeed, the ESTEEMen study reported that among individuals having 50–74% reduction in MMDs after erenumab treatment, approximately one quarter still had 8-14 residual MMDs. 20 Regarding tolerability, individuals with migraine have a high risk for adverse effects to preventive drugs. One study showed that topiramate led to more adverse events in individuals treated for migraine than in those treated for epilepsy. 21 Nocebo effect is a potential explanation for the excess of adverse events, 22 possibly triggered by central sensitisation 23 or to the low expectancy of benefit from non-specific drugs. A combination of poor efficacy and poor tolerability determines poor adherence to preventive treatments, which is estimated as 25% at six months and 14% at 12 months for oral drugs. 24 A third reason for treatment failure—together with poor efficacy and tolerability—is loss of treatment effect over time, a phenomenon observed for oral migraine preventatives and yet understudied. Loss of treatment effect can derive from treatment-dependent and treatment-independent mechanisms. Treatment-dependent mechanisms include pharmacokinetic and pharmacodynamic tolerance, by which the mechanisms leading to migraine adapt themselves and escape the action of drugs, and drug-induced disease progression, by which the repeated administration of drugs can trigger migraine worsening. Treatment-independent mechanisms include an initial placebo effect that is lost over time, spontaneous fluctuations in migraine course that lead to disease progression despite the use of preventive drugs, inaccurate recall of treatment effects, and drug delivery problems resulting in poor quality of the drugs. 25 Pathophysiology Resistant migraine may be interpreted as a pure failure of migraine preventive treatments, while refractory migraine likely implies changes in sensory processing and neurotransmitters that are still unknown. The pathophysiological study of resistant and refractory migraine currently lacks direct evidence. Studies in CM may shed some light into the mechanisms that drive refractoriness, assuming that high frequency and resistance to treatments are both signs of migraine progression. Notably, whole-genome sequencing found no genetic variants associated with CM, 26 suggesting that migraine chronification—and potentially refractory migraine—is caused by environmental rather than genetic factors. The trigeminal system, including the peripheral innervation of the intracranial vasculature and meninges and its central input to the trigeminocervical complex (TCC), is important in migraine pathophysiology. 27 From the TCC, sensory information is transmitted to the thalamus, sensory cortex, and multiple other cerebral areas that elaborate head pain. The hypothalamus is also implicated in migraine pathophysiology: hyperactivation of the anterior hypothalamus has been linked to migraine chronification due to hyperactivation of the limbic system. 28 Interestingly, the hypothalamus hosts different neuropeptide systems, including orexins, oxytocin, neuropeptide Y, and pituitary adenylate cyclase activating protein (PACAP), which modulate neural function. 29 We can speculate that altered connectivity between the hypothalamus and the limbic system contributes to the development of resistant and refractory migraine via those neuropeptides. Central sensitisation, one of the driving factors of CM, lowers the threshold for trigeminal activation. 30 Sustained neural activation events like central sensitisation might lead to the development of neuroplastic changes including structural remodelling of synaptic contacts on spinal dorsal horn neurons, reorganisation of cortical sensory maps, and increased activation of emotional networks in the brain. 31 A MRI study revealed diffusion abnormalities in the thalamus, caudate, putamen, pallidum, amygdala, brainstem, and cerebral white matter of individuals with refractory migraine compared with headache-free controls. 32 However, the study could not pinpoint specific alterations that are unique to refractory compared with non-resistant migraine. The activity of the amygdala, one of the key components of the limbic system, has been implicated in the development of nocebo responses 33 which can be common in individuals with refractory migraine. 7 No molecular biomarker is available to predict refractory migraine or the risk for it. CGRP levels are higher in individuals with CM compared to those with EM or healthy controls. 34 However, CGRP is not the sole driver of disease worsening. Dopaminergic dysfunction might be a driver of migraine refractoriness, as suggested by the efficacy of olanzapine in individuals for whom CGRP-mAbs have failed. 35 Increased glutamatergic transmission is also known to drive central sensitisation 36 and could thus be a potential mechanism leading to resistance to treatments. Additionally, the endocannabinoid anti-nociceptive and anti-inflammatory system might be less functional in individuals with CM compared with those with EM. 37 Other systems involved in migraine worsening include the kappa opioid receptors, 38 the K ATP receptors, 39 and prolactin. 40 Although those dysfunctions have not been specifically linked to resistance to treatments, they are linked to migraine worsening and could be potential pharmacological targets. Treatment The treatment of resistant and refractory migraine requires careful clinical assessment of the individual, optimisation of acute and preventive treatment, management of comorbidities, and psychological support ( Fig. 4 ). An important step is proper communication. Individuals with resistant migraine should be reassured on the treatable nature of their condition, while those with refractory migraine should be provided with reasonable goals, taught to accept their diagnosis and to cope with the disease. Correct communication should also relieve the frustration of individuals experiencing multiple treatment failures and medical evaluations. When assessing treatment failures, clinicians should assess the individuals’ attitudes towards preventive treatments together with their actual effects. Individuals with migraine might be dissatisfied about treatments and develop nocebo. 22 They might be reluctant to take preventive treatments mostly developed for other indications and might underestimate the effectiveness of their treatments due to low expectations of efficacy. Possible reasons to contraindicate preventive treatments should also be carefully reviewed and not overestimated. Acute treatments and medication overuse In resistant or refractory migraine, suboptimal response to acute treatments may increase the risk for medication overuse. Opioids have poor evidence of efficacy in migraine and are associated with a high risk of overuse. 41 They therefore should be avoided in individuals with previous experience of failed treatments. 42 Ditans (molecules targeting the 5-HT1F receptor inhibiting the release of CGRP from presynaptic neurons) and gepants are suitable for individuals not responding to triptans (5-HT1B/D receptor agonists). 43 Animal evidence suggests that gepants present a low risk of medication overuse. 44 However, we have no strong data on the risk of overuse of ditans and gepants in clinical practice as they are still to be widely employed. When overuse occurs, withdrawal and detoxification should be considered. There are different detoxification protocols, all focused on withdrawal and education on the relevance and consequences of overuse. 45 Psychiatric or physical comorbidities, poor psycho-social environment, relapse after a previous detoxification treatment, and daily use of acute treatments deserve attention as they are associated with failure of withdrawal schemes. 46 Randomised controlled trials (RCTs) suggest combining acute medication withdrawal with preventive treatments. 47 , 48 Preventive treatment Individuals with resistant and refractory migraine can be treated with pharmacological and/or non-pharmacological options. Pharmacological options can be used either as single treatments or in combination. Non-pharmacological options should be part of the overall management of migraine but represent a pillar in the treatment of resistant and refractory migraine. Those interventions include behavioural therapies—including lifestyle adaptations–and neuromodulation. A useful strategy is to encourage positive expectations on treatments that can modulate pain and analgesic treatment effects. 49 Pharmacological options for resistant migraine Individuals with resistant migraine with a failure of oral preventatives can be managed with onabotulinumtoxinA—for CM only—and drugs antagonising the CGRP pathway. The reason for intending these treatments as “second-line” is only based on their cost as there are no clinical or pharmacological reasons for distinguishing several lines of migraine treatments. Although not specifically tested in RCTs, in clinical practice onabotulinumtoxinA has been reserved to individuals with CM and failure of oral drugs, in whom it proved high effectiveness and tolerability. 50 RCTs of CGRP-mAbs were the first to prove the efficacy of migraine prevention in individuals with prior preventive treatment failures ( Table 1 ). 51 , 52 , 53 , 54 Coupled with their high tolerability and adherence rate, CGRP-mAbs are a mainstay in the treatment of resistant migraine. Real-world studies confirmed CGRP-mAbs effectiveness and safety in individuals with many preventive treatment failures, mostly diagnosed with CM and medication overuse, and with severe migraine-related disability. 55 , 56 In these studies, the proportion of individuals reporting a ≥50% reduction in MMDs from baseline—a common efficacy outcome in clinical studies–ranged between 30% and 51% at 3 months. 55 , 56 No clear correlation exists between the number of prior preventative failures and response rate: a subgroup analysis of the FOCUS trial of fremanezumab reported a decrease in placebo response but not of drug efficacy among patients who had higher numbers of treatment failures 57 ; conversely, real-world evidence suggests that a high number of preventive treatment failures might predict non-response to CGRP-mAbs. 58 , 59 Rimegepant and atogepant–oral drugs antagonising the CGRP pathway—proved superior over placebo in reducing MMDs and in ≥50% response rate in individuals with EM or CM 60 , 61 , 62 , 63 and up to four preventive treatment failures. OnabotulinumtoxinA and drugs antagonising the CGRP pathway could help overcome tolerability issues associated with oral treatments and therefore increase adherence. Both CGRP-mAbs and onabotulinumtoxinA have a very low proportion of discontinuation for lack of efficacy or adverse events 50 , 51 , 52 , 53 , 54 , 64 ( Table 1 ). The HER-MES double-blind RCT proved the higher tolerability of and adherence to erenumab over topiramate. 65 Gepants also did not lead to more adverse events than placebo in RCTs. 60 , 62 The loss of treatment effect over time with oral agents might in theory be counteracted by dose increase, switch to another drug, or drug combination to regain therapeutic benefit, but the effectiveness of those strategies is not proven by literature data. Notably, the available data do not indicate a loss of treatment effect over time with drugs antagonising the CGRP pathway. 66 Pharmacological options for refractory migraine For individuals with refractory migraine, pharmacological options should be part of a multidisciplinary approach. Given the numerous treatment failures, clinicians should avoid the stress and negative expectations caused by continuing treatment attempts and focus on person-centred care. Combined pharmacological treatments might represent a possible strategy for individuals with a partial or inadequate response. Case series and retrospective studies showed possible efficacy of dual therapy with onabotulinumtoxinA and CGRP-mAbs in individuals who had not responded to all or most of the available treatments. 67 Behavioural therapies Behavioural therapies have not been specifically tested in resistant or refractory migraine. RCTs 68 , 69 revealed that there is a synergistic, not just additive, benefit of a combination of pharmacologic treatment and behavioural therapy. Current use of behavioural therapies in patients with refractory migraine is limited by lack of evidence regarding efficacy and limited availability in headache centres, due to lack of personnel and resources. Neuromodulation Among neuromodulation techniques, occipital nerve stimulation (ONS), spinal cord stimulation (SCS), transcutaneous vagal nerve stimulation (tVNS), and single-pulse transcranial magnetic stimulation (sTMS) have been tested in individuals with refractory migraine. ONS bases its rationale on the convergence of the greater occipital nerve on the same second order neurons within the TCC. RCTs proved the superiority of ONS to sham in 50% reduction of headache days per month, pain intensity, 70 and disability 71 in individuals with refractory CM, even if at the expense of adverse events, including minor infections and lead migration. tVNS, which non-invasively targets the cervical branch of the vagus nerve using a small handheld device to stimulate the nerve in the region of the neck, is thought to activate low-threshold myelinated A-fibres, producing an antinociceptive effect on the second-order neurons of the spinothalamic and spino-reticular tracts within the TCC. However, the EVENT RCT did not show efficacy of the treatment in individuals with CM. 72 sTMS applies single magnetic pulses inducing small electric currents in the occipital cortex. A real-world evidence clinical audit in the UK investigated daily sTMS application in individuals with at least three failures of established migraine preventive treatment over the course of 12 months. At 3 months, there was a median reduction of 5.0 monthly headache days compared to baseline (from 18.0 to 13.0 days), with 93/153 (60%) individuals achieving at least a 30% reduction in monthly migraine days. At 12 months, 69 (45%) of patients continued to have a sustained response to sTMS. 73 SCS involves implanted electrical leads positioned epidurally at the C2 vertebral level. High-frequency paraesthesia-free stimulation (10 KHz) sends mild electrical pulses to the epidural space, which is thought to modulate nociceptive transmission at the level of second order neurons in the TCC. Real-world studies showed a long-term (>1 year) decrease in the number of MMDs and improved quality-of-life scores. About half of participants converted from CM to EM. 74 , 75 Adverse events include lead migration and infections. Taken together, neuromodulation approaches to refractory migraine reported mixed results in observational studies and small RCTs. It should be noted that studies of neuromodulation are small and including individuals in larger real-world studies and/or RCTs would be reasonable. Non-invasive techniques are widely applicable, while invasive techniques should be reserved to individuals with refractory migraine in the largest headache centres with multidisciplinary care and high-resource settings. Combinations between pharmacological and neuromodulation treatments could be considered in individuals with refractory migraine. Other therapies Other therapeutic approaches—both pharmacological and non-pharmacological—are used in migraine prevention and their use in individuals resistant to other treatments should be considered. Among pharmacological interventions, occipital or multiple cranial nerve blocks with local anaesthetics and/or steroids 76 and intravenous infusions of anaesthetic agents such as lidocaine 77 are often used to block severe migraine and facilitating long-term prevention. Among non-pharmacological approaches, physical therapy 78 should be mentioned. Although not specifically tested in individuals with resistant or refractory migraine—and despite their overall low level of evidence—the use of those treatments could be considered in individuals with failure of all the other available treatments. For those poorly studied treatments, n-of-1 trials in which a single individual takes both the active drug or placebo in a sequential fashion could help providing preliminary efficacy data and developing new treatment protocols. Outstanding questions The main outstanding questions for the understanding of resistant and refractory migraine refer to its identification, management, and pathogenesis. Resistant and refractory migraine represent the progression of more manageable forms of migraine. Therefore, identifying the drivers of that progression is key to prevent their onset. Epidemiological studies specifically addressing the impact of resistant and refractory migraine and their trajectories over time are advisable in the future. The role of risk factors and triggers that can impact on resistant and refractory migraine also needs to be better understood. New tools are needed to better predict the development of resistant or refractory migraine at the individual level; artificial intelligence is being used to develop predictive models for that purpose. 79 Regarding management, future research should focus on preventing treatment refractoriness. The use of specific migraine preventive agents in the early stages of progression might in theory prevent resistant or refractory forms. Solid evidence is still needed in the field; however, real-world data suggest that individuals with a shorter duration of CM respond better to onabotulinumtoxinA than those with longer disease duration. 80 The early use of migraine-specific preventive treatments is limited due to reimbursement and accessibility issues; future policy changes may help tackle resistant and refractory migraine. A German study showed that erenumab use was more effective when reimbursed after only one prior preventive treatment failure than under stricter reimbursement conditions. 81 At the same time, non-pharmacological approaches to migraine should be encouraged in an early phase of the disorder to prevent the onset of resistance to treatments; further RCTs on those approaches are warranted. A further open question regarding the treatment of individuals with refractory migraine is the role of combined preventive treatments. The combination of treatments with peripheral actions—targeting the CGRP pathway—with those directly targeting the CNS might decrease both peripheral and central sensitisation and provide advantage in individuals with refractory forms. An alternative avenue for the development of new treatments is the improvement of established preventative drugs, including recombinant botulinum toxins 82 and TMS stimulation protocols utilising theta burst stimulation. 83 RCTs could also be specifically designed for individuals with resistant or refractory migraine and test higher doses or longer duration of current treatments. Future research in the field of resistant and refractory migraine should also focus on contextual effects of treatments. The placebo effect is an issue in RCTs while it could be cultivated and enhanced in clinical practice as it increases the benefit of open-label treatments. On the other hand, nocebo effect should be avoided to enhance treatment adherence. Communication skills should be nurtured by clinicians addressing individuals with resistant and refractory migraine to help manage the placebo and nocebo effects. Besides, the future definitions of resistant and refractory migraine should better consider failure of acute treatments. Efforts are ongoing to provide detailed definitions of failure to acute medication 43 to be added to the definitions of resistant and refractory migraine. Notably, with the advent of gepants, CGRP inhibition is becoming the basis for both acute and preventive treatment of migraine and the same drug could be used for both purposes, 62 , 84 possibly leading to changes in migraine treatment approaches. Lastly, there is a need for improvement in pre-clinical and translational research on the pathogenesis of resistant and refractory migraine. Currently, preclinical models of migraine focus on the generation of attacks, but not on the factors impairing response to preventive treatments. The PACAP, dopaminergic, glutamatergic, and endocannabinoid systems may represent interesting targets for the development of future preventive drugs. New preventive drugs targeting pathophysiological mechanisms will likely reduce the number of individuals with refractory migraine. Contributors SS conceived and structured the review and supervised the whole project. RO and EDM drafted the first manuscript. SS, APA, TPJ, and MTM contributed to parts of the manuscript and revised the first draft for intellectual content. All authors read and approved the final version of the manuscript. Declaration of interests RO reports consulting fees from Teva, direct payments from Teva, Eli Lilly, Novartis, AbbVie, and Pfizer, support for attending meetings and/or travel from Novartis and Teva, participation to advisory boards from Eli Lilly, and other support from Novartis and Allergan-AbbVie; he is a Junior Editorial Board member of The Journal of Headache and Pain. SS reports grants from Novartis and Uriach, consulting fees from Abbott, Allergan, AbbVie, Novartis, Teva, Eli Lilly, Pfizer, Lundbeck, Novo Nordisk, and AstraZeneca, direct payment from Abbott, Allergan-AbbVie, Novartis, Teva, Eli Lilly, Pfizer, Lundbeck, Novo Nordisk, and AstraZeneca, support for attending meetings and/or travel from Eli Lilly, Novartis, Teva, and Lundbeck, receipt of equipment from Allergan-AbbVie and Novo Nordisk; she is President Elect of the European Stroke Organisation and Editor-in-Chief of Cephalalgia. APA received grants or contracts from Brain Research UK, Medical Research Council, Medical Research Foundation, Rosetrees, and Migraine Trust, consulting fees from Eli Lilly and AbbVie, direct payment from Eli Lilly, AbbVie, eNeura, Autonomic Technologies, and Novartis, participation to advisory boards from Eli Lilly and AbbVie; she is Chair of the Communications Committee of the International Headache Society and Chair of the Headache SIG of the British Pain Society. TPJ reports grants from the European Regional Development Funds (ERDF), Innovation Fund of the Federal Joint Committee (Germany) and Novartis; compensation from Allergan, Abbvie, Chordate, Grünenthal, Hormosan, Lilly, Lundbeck, Novartis, Pfizer, Teva and Sanofi for consultant services and/or speaker honoraria; he is President of the German Migraine and Headache Society and member of the Educational Committee of the German Pain Society. EDM and MTM report no conflict of interest.

Acknowledgements We thank Dr Alexis George for the contribution to the “Behavioural therapies” section of this work. We used BioRender to create the figures: BioRender.com. The Authors received no funding for the present manuscript.

CC BY

no

2024-01-16 23:42:00

eBioMedicine. 2023 Dec 23; 99:104943

oa_package/76/12/PMC10788408.tar.gz

PMC10788422

38225977

Introduction With approximately 18% of effective playing time spent in high-intensity skating activities, performance in ice hockey is a combination of short bouts of explosive and powerful movements cumulating in high energetic demands ( 1 ). The ability to skate and accelerate at higher speeds distinguishes the best young players ( 2 ). Improving sprinting ability off the ice during off-season is important as it may improve skating performance in-season ( 3 ). Developing the anaerobic system is also important as this metabolic system assumes 69% of energy costs during competition ( 4 ). To develop both of these capacities, strength and conditioning coaches turn to combinations of various off-ice methods, such as strength exercises, heavy resisted sprints, repeated sprints, and high-intensity training ( 5 – 9 ). However, the concurrent use of all these training methods during off-season presents periodization challenges that may hinder strength/power and anaerobic gains ( 10 , 11 ). In recent years, analysis of the sprint force–velocity ( F – V ) profile has gained popularity among researchers and practitioners who have turned toward this evaluation method to efficiently individualize training prescriptions ( 12 , 13 ). The procedure gives an overall view of the strength/power/velocity capabilities of an athlete (defined in Table 1 ) during sprinting tasks by following the time–velocity curve of their center of mass ( 14 ). The mechanical capabilities evaluated using this method for a given athlete are compared with those of an optimal profile ( 12 , 15 ). In fact, Morin and Samozino ( 15 ) have demonstrated that theoretical maximal force ( F 0 ) translates to shorter distance sprint performance (<20 m), whereas theoretical maximal velocity ( V 0 ) translates to longer distance sprint performance (>30 m). Available research including ice hockey players focused mainly on associations between sprinting F – V , skating F – V , vertical jump performance, and skating performance. Perez et al. ( 16 ) explored the associations between both profiles and jumping, running, or skating performance with 17 French national team female players (mean age, 21.6 ± 3.4 years). They demonstrated that maximal theoretical power ( P max ) displayed the strongest associations with the three performance indicators (| r | ranging from 0.81 to 0.92; p < 0.001). Other work including ice hockey players was used to confirm the validity and reliability of the method on the ice, this time with French elite female players and Finnish elite male junior players ( 17 – 19 ). To our knowledge, F – V data for highly trained adolescent ice hockey players have yet to be published. As the physical and physiological performance does not linearly change during the critical stage of adolescence ( 20 – 22 ), studying these age groups is important. Understanding the links between sprinting F – V and a wider set of physical or physiological markers such as anaerobic capacity could guide the decisions of the practitioners during off-season. In other sports, some work has linked sprint mechanical capabilities to anaerobic capacities. The results with rugby sevens players and soccer players consistently showed that the ability to efficiently generate force at high velocities (e.g., V 0 and D rf ) was impaired while the ability to efficiently generate force at low speeds (e.g., F 0 and Rf max ) remained constant during repeated sprints ( 23 , 24 ). In both cases, linear sprints were used during the repeated-sprint test even though team sports performance includes much shorter sprints and multiple changes of directions ( 25 ). In addition to such limitations, the links between mechanical capabilities during an independent maximal sprint test and repeated-sprint ability were not reported. Given the widespread use of anaerobic capacity tests during off-season testing of ice hockey players ( 25 , 26 ), a better understanding of the associations between sprinting F – V and common anaerobic capacity tests could help practitioners narrow down the preferred and most effective training methods during off-season. Hence, this study aimed to explore associations between sprinting F – V mechanical capabilities and anaerobic capacities of 15- to 17-year-old male and female ice hockey players. Two specific objectives arise from this study. First, this study explores how the mechanical capabilities of sprinting F – V are related to the variables from anaerobic tests used in ice hockey (e.g., the Wingate and a repeated-sprint ability test with a 180° turn). Second, this study explores the differences between male and female players. Based on the previous results by Perez et al. ( 16 ), it was hypothesized that P max shows the strongest associations with the different variables of both anaerobic tests. It was also believed that V 0 shows stronger associations with the Wingate given the time needed to reach peak power (around 7 s) and F 0 shows stronger associations with the repeated sprints due to the included change of direction in this study. Finally, given that female athletes tend to have more force-oriented profiles ( 27 , 28 ), it was hypothesized that F 0 plays a more important role in the anaerobic performance for this population.

Methods Participants Every spring, the Quebec Ice Hockey Federation invites the most promising players (men and women) to development camps. Invitations are based on the performance of players during the regular season. Among these invited players, the best will be part of the team competing at the national level. In the summer of 2022, 42 men and 42 women were invited to a summer camp launching off-season training for players. Various physical and physiological abilities were tested. Goaltenders were excluded from the study design given the unique nature and demands of their position ( 29 ). Injured players or players who were unable to complete the entire testing protocol were also excluded from the study. Finally, 36 men (age = 15.1 ± 0.2 years, stature = 177.5 ± 6.4, mass = 70.6 ± 8.4) and 34 women (age = 16.5 ± 0.7 years, stature = 167.3 ± 5.5, mass = 65.4 ± 7.0) participated in the study. Given their training status and preparation for national-level competitions, the participants are classified as highly trained athletes ( 30 ). Post hoc power analysis for between-groups comparisons and correlations was computed using G*Power v.3.1.9.7. Statistical power for the smallest observed effect size (0.67) at a significance level of α = 0.05 was 0.8 for both methods. This study was approved by the ethics board of the researchers’ institution (CER-21-278-07.29). Following the rules and regulations of our country and province, only written consent from players was obtained. Article 21 of the Civil Code of Quebec stipulates that “Consent to research that could interfere with the integrity of a minor may be given by the person having parental authority or the tutor. A minor 14 years of age or over, however, may give consent alone if, in the opinion of the competent research ethics committee, the research involves only minimal risk and the circumstances justify it.” Study design Male and female players were tested on two separate consecutive days, following similar procedures (e.g., Day 1 = men, Day 2 = women). The players were divided into two subgroups alternating between physical testing and team meetings. The testing protocol of the camp consisted of anthropometric measurements, strength, speed, agility, power, anaerobic capacity, and mobility. These physical parameters were collected via various tests: stature, mass, grip strength, chin-ups, bench press, standing long jump, countermovement jump, 30-s Wingate anaerobic test (WAnT), 30-m sprint, 5-10-5 shuttle run, and repeated anaerobic sprint test with a 180° change of direction [repeated-sprint anaerobic (RSA)]. The tests were divided into two sessions. For the morning session, the players were divided into five groups alternating between one agility and five muscular tests. The WAnT was done at the end of the session. The players then had 3 h before the afternoon session. During this session, they completed the 30-m sprint followed 15 min later by the RSA. Horizontal F – V profile To determine the individual F – V of each player, the players ran two 30-m sprints. The method has an “acceptable” intraday and inter-day reliability [intraclass correlation coefficient (ICC) ≥ 0.75 and coefficient of variation (CV) ≤ 10%] ( 14 ). Before the sprints, the players started in a feet supported crouched position and stood still until instructed to run by the research assistant. They were given 3- to 4-min rest between trials. Instant velocity over the sprinting distance was collected at 46.875 Hz using a Stalker ATS II (Stalker Sport, Richardson, TX, USA). The radar was placed 3 m behind the starting line and 1 m aboveground approximately at the height of the center of mass of the players. Following protocols and guidelines established by Samozino et al. ( 14 ), raw velocity data were first imported into R studio. Then, data prior to the start and after the maximal velocity plateau were discarded. The remaining data were fitted with a mono-exponential function, and mechanical variables were calculated ( 14 , 18 ). An optimal profile at 10 m ( S fvopt ) was computed following the proposed methods by Samozino et al. ( 31 ). To improve reliability, the average values of both trials were used for further analyses ( 32 , 33 ). Wingate To evaluate anaerobic capacity, the WAnT was used. The WAnT is a popular test that measures the power production of a player throughout a 30-s bout. The validity and reliability of the test to evaluate the anaerobic capacity of ice hockey players were confirmed ( 34 , 35 ). The test was completed on an air-braked cycle ergometer (Wattbike Pro/Trainer, Nottingham, UK, 2022), which was also validated in a previous study ( 33 ). The test started with a 5-min warm-up on a cycle ergometer with a resistance of 75 W and a cadence of 85 revolutions per minute (rpm). For the last 6 s of each minute, the players were asked to sprint. A 3-min rest period was given before the start of the test. After the WAnT, a 2-min cooldown was given. Peak power, relative peak power, average power (e.g., average power exerted during the test), relative average power, anaerobic capacity (e.g., the sum of average values recorded in each of six 5-s blocks), and anaerobic fatigue (e.g., drop-off in power from the highest to the lowest 5-s block represented as a percentage) were extracted directly from the Wattbike cycle ergometer console and used for analysis. Repeated-sprint ability To evaluate the anaerobic capacity of the players in a more practical approach, a RSA test with a 180° change of direction (RSA) was designed. In practice, the available space was limited and imposed constraints for the chosen test format in line with guidelines by Kyles et al. ( 25 ). The players ran 20 m and then changed direction to run back 20 m. The players completed six sprints and had 30 s to complete a sprint and start the next. This procedure was validated previously with cohorts of soccer players ( 36 ) and chosen to introduce a change of direction component, which is important for the performance in team sports such as ice hockey. Sprint times were collected using Swift (Swift Performance, Northbrook, IL, USA) single-beam laser timing gates placed on the starting line. The players started 30 cm behind the gates. The best time between the first two sprints, total time, and a fatigue index were used for analysis. The fatigue index was computed following the recommendations of Glaister et al. ( 37 ) by using the percentage decrement score [100 × (total sprint time ÷ ideal sprint time)] − 100, where the ideal sprint time = number of sprints × fastest sprint time. The results for two female players and seven male players were excluded from final analysis as they did not perform their best sprint in the first two trials, which could indicate the use of a pacing strategy ( 24 ). Statistical analysis Descriptive statistics for sprinting F – V , Wingate, and RSA are presented in Table 1 . Normality assumptions for each variable were confirmed by verifying the skewness and kurtosis of each distribution. To compare male and female players, independent Student t -test were computed with Cohen's D to estimate effect sizes. The reliability of F – V mechanical capabilities with adolescent ice hockey players was confirmed by computing ICCs and CV for both trials. All variables had ICC values ≥ 0.90 and CV ≤ 10% ( 38 ). To explore relations between the F – V and anaerobic capacity of the players while controlling for sex differences, partial Pearson correlation coefficients for pooled data and Pearson correlation coefficients for individual sex (e.g., men and women) were calculated. As recommended by Hopkins et al. ( 38 ), the magnitude of Pearson's correlation coefficients ( r ) was considered trivial ( r < 0.10), small ( r = 0.10–0.29), moderate ( r = 0.30–0.49), large ( r = 0.50–0.69), very large ( r = 0.70–0.89), nearly perfect ( r = 0.90–0.99), and perfect ( r = 1.00). Statistical analyses were conducted using SPSS version 28.0 (IBM Corporation, Armonk, NY, USA).

Results Associations between F – V mechanical capabilities and anaerobic capacities Partial Pearson's correlation coefficients suggest that F 0 had a small association with the relative peak power ( r = 0.26, p = 0.049) of the WAnT and was moderately associated with total time ( r = −0.32, p = 0.012) and best time ( r = −0.33, p = 0.10) of the RSA. V 0 and P max were moderately associated with peak power ( r = 0.43 and 0.35, p < 0.001 and p = 0.006), relative peak power ( r = 0.49 and 0.44, p < 0.001), average power ( r = 0.30, p = 0.019 and 0.018), and anaerobic capacity ( r = 0.37 and 0.32, p = 0.003 and 0.012) of the WAnT and were largely associated with total time ( r = −0.65 and –0.57, p < 0.001) and best time ( r = −0.70 and −0.60, p < 0.001) of the RSA. Rf max was moderately associated with the relative peak power ( r = 0.33, p = 0.011) of the WAnT and had small associations with total time ( r = −0.26, p = 0.049) and best time ( r = −0.27, p = 0.035) of the RSA. S fv and D rf were not associated with the WAnT or the RSA. Differences between male and female players As shown in Table 2 , independent Student t -tests demonstrated that male players were taller and heavier and performed better than female players in all variables except for S fv and D rf . F 0 , S fv , and Rf max of the male players were not associated with WAnT or RSA variables. V 0 was moderately associated with peak power ( r = 0.34, p = 0.037) and relative peak power ( r = 0.34, p = 0.045) in the WAnT and was largely associated with total time ( r = −0.59, p < 0.001) and best time ( r = −0.64, p < 0.001) in the RSA. P max was not associated with variables from the WAnT, but was moderately associated with total time ( r = −0.41, p = 0.028) and largely associated with the best time ( r = −0.53, p = 0.003) in the RSA. D rf was moderately associated with total time ( r = –0.39, p = 0.036) in the RSA. S fv and D rf of the female players were not associated with WAnT or RSA variables. F 0 was moderately associated with relative peak power ( r = 0.34, p = 0.047), relative average power ( r = 0.34, p = 0.050) of the WAnT, and total time ( r = −0.45, p = 0.010) and best time ( r = −0.40, p = 0.022) of the RSA. V 0 was largely associated to relative peak power ( r = 0.62, p < 0.001), moderately associated with peak power ( r = 0.47, p = 0.005) and anaerobic capacity ( r = 0.39, p = 0.022) of the WAnT, and largely associated with total time ( r = −0.75, p < 0.001) and best time ( r = −0.78, p < 0.001) of the RSA. P max was largely associated with relative peak power ( r = 0.53, p = 0.001), moderately with relative average power ( r = 0.38, p = 0.026) of the WAnT, and largely associated with total time ( r = −0.68, p < 0.001) and best time ( r = −0.66, p < 0.001) of the RSA. Rf max was moderately associated with relative peak power ( r = 0.48, p = 0.004), relative average power ( r = 0.38, p = 0.025) of the WAnT and with total time ( r = −0.43, p = 0.013), and best time ( r = −0.45, p = 0.011) of the RSA. Partial correlations and correlations for male and female players for F 0 and V 0 are illustrated in Figures 1 , 2 to express the main differences between the sexes.

Discussion The relevance of F – V athlete profiling has emerged over the last decade. However, little is known about its associations with physical attributes that require high-intensity efforts, such as anaerobic capacities. Considering the importance of such qualities to excel in ice hockey, a deeper understanding of these associations is helpful for strength and conditioning coaches to optimize performance. This paper was the first to explore the associations between sprinting F – V mechanical capabilities and anaerobic capacities of highly competitive adolescent male and female ice hockey players. The general aim of this study was to widen current knowledge around sprinting F – V and its links with anaerobic capacities measured threw common tests. Previous work analyzing the sprinting F – V of ice hockey players was fairly limited focusing more on the validity and reliability of the method with a limited number of subpopulations, that is, female French senior to junior national teams and male players from elite Finnish leagues ( 16 – 19 ). The first objective of this study was to explore how the mechanical capabilities of sprinting F – V were related to variables from common anaerobic tests such as the Wingate and repeated-sprint test. To provide a complete observation of these associations, three main hypotheses were proposed. The first hypothesis was that P max would show the strongest associations with the different variables of both anaerobic tests, V 0 would show stronger associations with the cycling test, and F 0 would show stronger associations with the repeated-sprint ability. When considering results for pooled data, P max was associated with anaerobic power and anaerobic capacity in both tests yet appeared stronger for the running test (moderate associations for peak power, relative peak power, and average power in the WAnT vs. large associations for total time and best time in the RSA). Unlike initially hypothesized, V 0 showed the strongest associations with performance in both tests, correlating largely with the RSA and moderately with the WAnT. In contrast, F 0 showed few associations to the Wingate with a small association to relative peak power and moderate associations with the RSA. The initial hypothesis was based on the proposed interpretations of Morin and Samozino ( 15 ) and only focused on an analysis of the tasks used in this study. However, these interpretations were majorly based on the observations with elite-level athletes. The different playing levels and ages of participants from this study probably influenced the associations observed in this study. The second objective of this study was to explore differences between male and female players. The hypothesis was that F 0 would exhibit stronger associations with performance in female athletes as they tend to have more force-oriented F – V profiles ( 27 , 28 ). Our results confirmed this hypothesis as associations between F 0 and performance in both anaerobic tests were only present for the female players (see Figures 1 , 2 ). The cycling performance and repeated-sprint performance of male players in this study were mainly determined by V 0 . Given their young age, F 0 may not have been fully developed at the moment of testing ( 22 ) and could explain the observed differences with female players. Previous work by Perez et al. ( 16 ) highlighted the absence of associations between the actual F – V and performance of an athlete as observed in this study. To our knowledge, this study was the first to include the computation of S fvopt and FV imb. in the evaluation of the sprinting F – V with ice hockey players. Looking at Figure 3 , both groups show a force deficit which may explain the large associations between V 0 and RSA performance. The appearance of associations with F 0 for female players could be attributed to the portion of players with a velocity deficit (bottom quartile of female box plot). Nonetheless, practitioners training sprint ability and anaerobic capacities concurrently should choose training methods according to the sex of players. Highly trained female players may benefit from methods including explosive exercises at low and high velocities while highly trained male players in the age range of this study could focus more on developing maximal velocity. Jiménez-Reyes et al. ( 12 ) categorized exercises according to the desired training focus for enhanced jumping performance. Similarly, practitioners could use resisted sprints for an emphasis on low velocities ( 5 ) and flying sprints to train at higher velocities to enhance sprint performance. Although this study adds to available knowledge regarding sprinting F–V profiling in ice hockey, certain limitations persist. First, while the reliability of the computation method by Samozino et al. ( 14 ) has been reported with youth athletes ( 22 ), no validation of the method has been published. The sprinting mechanics of teenage ice hockey players are different from elite adult sprinters. However, participants in this study have exhibited lower mechanical characteristics than higher-level athletes in previous studies ( 17 – 19 ). Given velocity follows the same mono-exponential function in youth ( 22 ) and aerodynamics included in the method adjusts to the stature and mass of each individual ( 14 ), there are a few reasons that the method should not be valid with this study population. Second, the observational design of this study does not confirm the causal effects of the different sprinting F – V variables on anaerobic performance. The type and strength of associations could be explained by the theoretical basis presented by Morin and Samozino ( 15 ) and previous observations. However, further research should focus on interventions demonstrating the advantages of individualized training based on the F – V as this would yield the best practical applications ( 12 , 39 ). Third, this study only considered off-ice data that were collected during off-season. Prediction of skating abilities from off-ice activities or the transfer of such activities to skating performance and anaerobic capacities on the ice remains unclear. For example, Perez et al. ( 16 ) demonstrated that sprinting and skating F – V were not correlated. Ultimately, the goal of ice hockey training is to maximize performance on the ice. In this regard, developing research designs that allow the evaluation of the transferability of off-ice attributes to on-ice performance is a key concern for stakeholders overseeing the development of highly competitive ice hockey players. Comparing the skating F – V and anaerobic capacities of players on the ice would allow for a better understanding of determinant indicators in ice hockey and designing efficient training programs.

Conclusion This research provides a deeper understanding of underlying associations between the sprinting F – V and anaerobic capacities of highly trained adolescent male and female ice hockey players. Pooled data demonstrated that the ability to apply force at low and high velocities are determinant for anaerobic performance on a cycle ergometer and repeated-sprint ability including changes of direction. A separate analysis of male and female players demonstrated that determinant mechanical capabilities of sprinting vary according to sex. Specifically, the cycling and repeated-sprint performance of younger male players could be mainly determined by the ability to apply force at high velocities, whereas the ability to generate force at slow speeds may be of added importance for female players. Practitioners must understand that determinant mechanical capabilities of sprinting for anaerobic performance may be different for male and female athletes and training priorities may change accordingly.

Edited by: Jeppe Foged Vigh-Larsen, University of Southern Denmark, Denmark Reviewed by: Jean Romain Riviere, Université Savoie Mont Blanc, France Christopher Kirk, Sheffield Hallam University, United Kingdom Introduction Sprinting ability and anaerobic capacities are the determinant variables of the performance of ice hockey players. Recent research in sprinting showed the existence of distinct force–velocity ( F – V ) profiles, but the link between these profiles and anaerobic capacities remains unclear. This study explores the associations between F – V variables and anaerobic capacities among cohorts of highly trained adolescent ice hockey players. Methods Data from 36 men (age, 15.1 ± 0.2 years) and 34 women (age, 16.5 ± 0.7 years) were collected during off-season camps. All athletes completed a 30-m sprint test, a Wingate anaerobic test (WAnT), and a repeated-sprint anaerobic (RSA) test. F – V variables were calculated from the 30-m sprint test. Partial Pearson correlation coefficients for pooled data and Pearson correlation coefficients for individual male and female datasets were calculated. Results Among the F – V variables, maximal theoretical velocity and power were moderately to largely associated with WAnT and RSA performance (| r | = 0.30–0.70). Maximal theoretical force was moderately associated with the RSA ( r = −0.32 to −0.33). Discussion The results indicate the importance for highly trained adolescent players to be able to apply force at high velocities to maximize anaerobic capacities. Important differences between male and female players suggest training priorities may differ according to sex.

Acknowledgments The authors wish to thank the players who participated in this study and the staff of Hockey Quebec for their collaboration during the planning and execution of testing. Data availability statement The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Ethics statement The study involving humans was approved by Comité d'Éthique de la recherche avec des Êtres Humains UQTR. The study was conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was obtained from participants but was not required from the participants' legal guardians/next of kin because the project was approved by the ethics committee, which follows the rules and regulations of our country and province. Article 21 of the Civil Code of Quebec stipulates that “Consent to research that could interfere with the integrity of a minor may be given by the person having parental authority or the tutor. A minor 14 years of age or over, however, may give consent alone if, in the opinion of the competent research ethics committee, the research involves only minimal risk and the circumstances justify it.” Author contributions JG: Conceptualization, Formal analysis, Methodology, Software, Writing – original draft, Writing – review & editing. PP: Data curation, Investigation, Writing – original draft. JB: Conceptualization, Data curation, Methodology, Project administration, Resources, Writing – original draft. JL: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Publisher's note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

CC BY

no

2024-01-16 23:42:01

Front Sports Act Living. 2023 Dec 12; 5:1258497

oa_package/77/34/PMC10788422.tar.gz

PMC10788423

0

Introduction Creating and maintaining talented labor is a priority for any organization, and forensic laboratories are no exception. One of the four goals in the National Institute of Justice's (NIJ) Strategic Research Plan is to “cultivate a diverse and highly skilled workforce” [ 1 ]. This plan acknowledges the importance of workforce development to support successful forensic work. There is a clear need to grow our personnel and attract new hires. Demand for forensic scientists is expected to increase “much faster than average” over the coming years [ 2 ]. Laboratories need to be prepared to meet increased requests for forensic services or risk backlogs and other operational issues. As current practitioners are aware, forensic science is a demanding occupation. The pressures for many start early with challenging coursework in college, continues in the application process with lengthy background investigations, and persists through their career. The behind-the-scenes demands while working in the field include testifying in a court of law, performing proficiency tests, adhering to strict accreditation and quality assurance requirements, involvement in distressing casework, the knowledge that analysis will impact an individual's life, and possibly freedom, and expectations to continue training and improvement. This entire time, ethical standards must be continuously maintained. In recent years, the New York State Police Crime Laboratory System (NYSP CLS) has experienced a decline in the number of applicants for forensic positions. This has been seen across the country with a 4% decrease in law enforcement employment, including both sworn officers and non-sworn employees, between March 2020 and August 2022 [ 3 ]. An obvious factor is the inability for many government laboratories to offer salaries that can compete with private industry. Additionally, many forensic positions require candidates to pass a comprehensive background investigation. The applicants that do make it through the application process are a large investment– a year of training can cost $100,000 or more. Thus, retention of scientists is vital to the success of an organization. Since careers in forensics are still appealing, laboratories can employ strategic initiatives to recruit and maintain top applicants. Recruitment of potential applicants starts with engaging high school [ 4 ] and college students so that they can learn more about a career in forensics early in their academic careers. There are many benefits to students participating in these types of recruitment activities such as seeing what an average workday looks like and learning the specific educational requirements for a discipline they might be interested in. This experience is valuable because, for many students, their sole impression of forensic science is based on inaccurate entertainment media depictions. As these representations are rarely authoritative, definitive, or correct, it is helpful for students to see what a real career in forensics is like before they make a commitment, and a forensic laboratory makes an investment. Partnering with higher education institutions is mutually beneficial to both the laboratories and the academic institutions [ 5 ]. While many forensic programs aim to prepare students for a career in the field, some still do not adequately cover specific aspects of the job, including required coursework [ 6 ]. By partnering with a college or university, a laboratory can inform them of the coursework they view as most needed in new hires. Enrolling in a Forensic Science Education Programs Accreditation Commission (FEPAC) accredited school or program ensures that a program includes necessary forensic science educational requirements and recognition for adherence to those standards [ 7 ]. However, even FEPAC accredited programs do not address the gap that still exists between undergraduate curriculum and the reality of working in a forensic lab [ 8 ]. There has been previous discussion about rethinking forensic coursework to focus on this issue [ [9] , [10] , [11] , [12] ], and here we provide an additional approach. For students interested in undergraduate or graduate research, laboratory staff can develop programs such as an internship to aid in laboratory activities, like validation, database building, or research work. This relationship is symbiotic as the students gain experience working on real-world projects while the laboratory gains man-hours to help complete them while also enriching the applicant pool. Besides recruiting applicants, it is also important to develop the skills of existing laboratory employees. Presenting information to students and faculty provides scientists with public speaking experience, which is critical in a profession that requires regular courtroom testimony. Mentoring college students allows employees to hone mentoring and leadership skills, in addition to the benefits of mentoring for the students [ 13 ]. Lastly, working with universities to develop and validate methods offers opportunities to engage in project design and execution. All of these elements combine to create a program that provides real value to the forensic community but can also increase employee job satisfaction by diversifying job duties and allowing a structure for outreach and enrichment.

Methods The NYSP CLS developed the Forensic Investigative Curriculum (FIC) School educational outreach initiative to provide students with more information about forensic science careers. The program is designed to have scientists, students, and professors meet several times per college semester, with each meeting focused on a different discipline within forensic science. Local colleges and universities host FIC School events at their facilities, allowing students and educators from multiple institutions to gather. After an initial general introductory session about the CLS and information pertaining to pursuing a career in forensic science, subsequent presentations provide more detailed information about the various laboratory disciplines represented in the CLS. These presentations include Biological Sciences (DNA), Seized Drugs (Drug Chemistry), Toxicology, Firearms, and the Forensic Identification Unit (Latent Prints). Presentations were given by the scientists and professionals that work within each forensic discipline, and provide an overview of the discipline, what a ‘day in the life’ of a scientist might look like working in the laboratory, and information for students about any specific degree, coursework, or certifications that are recommended or required. After each lecture session, students were provided the opportunity to meet with forensic scientist mentors representing the various disciplines during the Mentor Mixer informal meet and greet session. These sessions also empowered students to make informed decisions regarding their own academic and professional paths while also networking with other students and faculty from other institutions. During the final session of the semester, the FIC School program culminates with a presentation about Quality Assurance in the laboratory and a tour of the Forensic Investigation Center, which is offered to students by invitation only. To be invited to tour the laboratory, students must have attended at least two of the informational sessions. During the tour, students and educators are guided through the laboratory and are provided demonstrations of various tools and techniques used by some of the sections, given the opportunity to see typical casework evidence items, and interact with the scientist performing their duties. With an hour of professional development workshop in each month of the semester for the mentors, professional forensic scientist students gain experience with Mentorship, Leadership, Communication, Presentation Skills, Team Dynamics and Effective Meetings. This training enriches their professional skillset with tools to effectively mentor students and apply to career development and even promotional opportunities. Most professional development content offered to forensic scientists is technical in nature and honing in on soft or “essential” skills sets the professional development in this program apart. By developing better mentors, the project develops more effective ways to deliver valuable information to the students and to better find the combination of interest and aptitude to guide their career path. The monthly time expectations of scientist mentors is the 1.5-h session with the students, the 1-h leadership program, and up to an additional 1 h to prepare presentations, tour demonstrations, or work on planning other aspects of the program. There is minimal impact to the caseload of each forensic scientist. Virtual mentor sessions were explored during the first semester of the pilot program but were not as successful as expected. Students were offered opportunities to sign up for one-on-one or small group sessions to speak directly (via a virtual platform) with a forensic science professional to answer any questions they had about their degree path or a career in a specific forensic discipline. Participation in the virtual mentoring was minimal, attributed to the FIC School program being so new; however, this approach is something that may be explored again for inclusion in future FIC School programs. To promote the FIC School program, a brochure was created to describe the Crime Laboratory System and sections of the laboratory and introduce the educational outreach program. Additionally, a flyer was created to outline important FIC School event information, such as session dates and locations. The flyer also includes a unique QR code linking users to the FIC School's own web page. The brochure and flyer are used for distribution to our current educational partners and also to other colleges, universities, and even high school Science, Technology, Engineering, and Math (STEM) programs to promote future educational partnerships. The FIC School web page ( https://sites.google.com/view/ficschool ) was created to keep interested students and educators up to date with the program's scheduled events and provide links to relevant forensic-related publications and resources, as well as current job offerings at the New York State Police. The website provides hyperlinks to the FIC School program's intake form for interested students to enroll in the program, a survey for students to submit following completion of the program, current employment postings within the laboratory, and provides brief introductions to each of the forensic science professionals involved in the pilot program. Local news media outlets and school media departments that featured the FIC School during the various presentation sessions are also displayed on the web page for future students to view. Each laboratory section represented in the program was responsible for creating and presenting a brief but detailed 15–20-min lecture about their discipline. Content covered the basics of the discipline, such as what the forensic scientists in that discipline were responsible for analyzing, the basic overview of analytical test methods, equipment used in analysis, and general educational requirements to hold the position of forensic scientist or laboratory technician. After the lecture portion of the session, students were able to speak with the mentors in a one-on-one (or realistically two or three-on-one) informal setting. NYSP CLS management met with educators to align educational programs with forensic discipline requirements and seek projects for collaboration. Students used questions provided by the program as a starting point for discussion, however, those discussions quickly morphed into detailed dialogue about the mentors’ experiences in entering the field of forensic science. Mentors detailed their educational journey as well as their professional timeline in the laboratory. The students overwhelmingly had the same general question – “What does a day in the life of a forensic scientist look like?” This became the basis for the pilot year program. Forensic professionals also participated in a forensic leadership development program delivered by The College of Saint Rose, one of the academic partners. The leadership program was a pilot program that spanned eight months and was designed by an employee at The College who was previously employed as a forensic scientist by the NYSP CLS. The program tested four different learning modalities during the first semester: 1) In-person. 2) Hybrid. 3) Virtual. 4) Asynchronous. Learning topics were selected by NYSP CLS management: 1) Mentorship/coaching (in-person), 2) Communication (virtual and asynchronous), and 3) Presentations/public speaking (in-person and asynchronous). Each topic included a total of 60 min of learning content.

Results and discussion The Forensic Outreach concept has the potential to leverage the NYSP CLS scientific expertise and infrastructure with educational institutions and, eventually, with private industry to create a unique partnership to develop new analytical methods and technologies while enhancing educational opportunities. The Educational Outreach Initiative began by canvassing laboratory staff who had volunteered for a mentor role, and they advised that dispelling common misconceptions of the field should be a focus of the program. Many students understood that there was a disconnect between the Hollywood version of forensic science and the real-life version. However, they didn't know quite where to draw the line of distinction between reality and television. Mentors tailored their lecture sessions to outline the basic concepts of the discipline as well as illustrate job duties that occur daily. A total of 18 students participated in the fall 2022 semester of the FIC School, and 16 in the spring semester. Evaluation of the Educational Outreach Initiative was conducted through feedback from the students, the academic institutions, media news coverage, and laboratory personnel. Students completed an anonymous electronic survey evaluating the components of the outreach initiative that they participated in. Results of the electronic survey are listed in Table 1 . All the survey respondents rated the presentations by the scientific professionals as excellent. Of the students involved in the outreach initiative, over 91% rated the Mentor Mixers as excellent, further indicating the mentor mixers as a valuable opportunity for them. The opportunity for one-on-one conversations with the forensic professionals provided students with a platform to ask their own questions and learn exactly from the experts what their duties include. Additional feedback from the mentor mixers included how valuable the interaction and speaking with the laboratory staff was, learning more about the forensic industry, and hearing what the laboratory staff enjoy most about their jobs as well as the challenges they face. These components of the program were identified as very beneficial by the students. Students found the virtual meetings to be beneficial due to the targeted information they received from the laboratory staff during the interaction in a more private and personal setting. Virtual sessions were found to benefit those students who were shy and not as comfortable with the in-person group setting. The most successful session of the FIC School was the interactive laboratory tour and section demonstrations. The students were separated into three different groups consisting of seven to eight students per group. In the fall 2022 session, the mentors from the seized drugs section of the laboratory demonstrated analysis of a mock case in real-time with the students. This interaction allowed the students a glimpse of what the daily activities of a forensic scientist in seized drugs looks like and get a better idea if the seized drugs discipline would be a career of interest for them. In the spring 2023 session, the bioscience casework section held a detailed demonstration for the students. Again, emphasis was placed on demonstrating the various aspects of a ‘day in the life’ of a forensic scientist assigned to bioscience. Unanimously, the students rated the laboratory tour and demonstrations as excellent. Individual evaluations of the participating students were also positive and showed growth among many of the students. One student, currently in his second year at Hudson Valley Community College (HVCC) majoring in Chemistry, was a very shy and reserved individual at the beginning of the mentor program. At each event, he grew more comfortable in approaching the mentors and participating in the Q&A sessions. He was also an active participant in the virtual mentor sessions. By the end of the third session, this student participated in two interviews with the local television news stations. Several other students showed growth, too, becoming more comfortable talking to the forensic laboratory professionals. The mentorship program provided sufficient information to allow students to decide if the field of forensics is the field of science they want to enter and make their career. The laboratory tours and demonstrations were valuable for the students, providing them with applied knowledge and understanding of each section and which discipline they may be interested in joining. Local news media stations attended the laboratory tour and demonstration event to promote the partnership between local colleges and the NYSP CLS and educate the community. News reporters interviewed both students and mentors about the benefits of the partnership. The feedback and interviews were positive and, in return, enhanced the undergraduate forensic programs at each of the academic institutions. The program has created a positive relationship between the forensic laboratory and the professors at the academic institutions who partnered with the CLS to host the Educational Outreach Program. The professors value the real-life insight into the crime laboratory environment and the insider advice that the mentors provide to the students. Professors with scientific expertise in forensic science related topics have the additional benefit of developing research initiatives in partnership with the forensic laboratory. Educational institutions that participate in the program establish connections with the laboratory mentors to offer targeted advice to the students to help them succeed in obtaining jobs in the forensic field, which is often highly competitive. In the end, both the laboratory and the schools benefit. The program connects students with mentors but also gives mentors the opportunity to evaluate potential candidates for employment and hone professional skills, such as presenting and coaching/mentoring. Increased exposure to forensic scientists, administrators, and their experience assists educators in building their programs. The mentors can help guide and shape the students as they work to complete their education, suggest relevant coursework to take in addition to their regular graduation requirements, and also advise the students on possible internship projects and opportunities. Discussions regarding future program options and improvements include expanding the potential collegiate partnerships and opening the program up local accelerated high school forensic science and STEM students. Mentors learned how to better communicate information to the younger demographic as well as strengthen their public speaking skills overall. This is a benefit for both seasoned forensic professionals and new hires. Participating in the Educational Outreach Program was rewarding and energizing for the mentors. Oftentimes, it is easy to become entrenched in the daily routine. However, taking time to interact and connect with the students and professors was a unique opportunity for the mentors to remember why they entered the field of forensic science in the first place. The students and professors were very enthusiastic in their participation in the program. The mentors felt appreciated and fulfilled as they were able to share their passion and knowledge. Many of the mentors strived to be the ideal mentor – as they wished had existed when they were in school. The entire project has been very well received by the public. The Educational Outreach team has been featured in the school news at all the current partner institutions - College of Saint Rose, State University of New York (SUNY) at Albany, and Hudson Valley Community College. Local news channels also visited during the two laboratory tour days. All of this exposure will increase awareness of the program and a better understanding of the field. Ideally, the program can reach more students who may not know much about forensic science and entice them to embark on this morally rewarding scientific career. The electronic survey also asked the students to identify areas of improvement for the program. Students expressed their desire for additional information and demonstrations about fingerprinting and other sections within the laboratory, in addition to the chemistry and biology sections. Additional feedback for improvement included a request for longer mentor mixer Q&A sessions, more in-depth presentations explaining the daily duties of the laboratory staff, as well as longer live demonstrations. Further recommendations from students included adding additional laboratory mentors to the program. Some students would like to have interactive time in the laboratory shadowing laboratory staff throughout their workday in addition to internship opportunities. However, crime laboratories are generally understaffed and operating with a casework backlog of some extent. Taking time away from casework is a “hard sell” especially when there is no immediate payoff to the laboratory. The second hurdle is the extensive background check required to allow the intern into the section/laboratory unescorted. For the NYSP, that background check is costly, lengthy, and sometimes difficult to pass for prospective employees let alone student interns. Often, the length of the background check process will exceed the length of the internship itself. This is not ideal for many students who do not want to or cannot wait that long to begin an unpaid internship. Lastly, there is limited or no funding to support internships. Instrumentation, reference materials, and equipment are costly. To divert any of these items from casework is problematic. However, partnering with colleges and universities can help to solve many of these problems. A proposal is being developed to enter a remote internship in partnership with the various schools that have worked with the NYSP CLS in the Educational Outreach Program. In the proposal, the school will provide the equipment and instrumentation onsite and the professor can supervise the students in their research. The research topic(s) will be of interest to the laboratory - students can focus on an area of research or validation that the laboratory has a need for but lacks the time and/or additional personnel to pursue. Students could come onsite to the laboratory to run final testing once the validation has been planned and tested at the school. One limitation of this concept is that schools may not have the exact same instrumentation as the NYSP CLS or have the correct license for controlled and/or dangerous substances at their institution. Short term in-laboratory work can be supervised without detriment to the forensic laboratory section. This also negates the need for a lengthy background check process. In the above example, the forensic laboratory has minimal resources invested into the internship but can then use the research project to design an abbreviated validation study that can then be used to generate and implement a procedure for the specific type of analysis. The Educational Outreach team has also been able to brainstorm ideas to assist with employee recruitment and retention that are valuable to the Human Resources department. Working with Human Resources, the team hopes to reduce as many barriers as possible to the employment process. As mentioned previously, the existing background process is extensive and exigent. Often, there is little to no communication to the applicant once the process begins. With team input, laboratory leadership has suggested a more open dialogue with candidates to provide updates throughout the hiring process. Also suggested is a portal or other mechanism of information sharing where the candidate can see the steps needed to gain employment, where they are in the process, and what remains. Both initiatives have been well received and are now being met by an informational fact sheet both read and provided to prospective employees. The website/portal is a larger project that will take more time but can be augmented in the interim by individual outreach to candidates and greater contact via email. It has also been documented that many candidates are lost during the hiring process. The team has also suggested that Human Resources deploy an anonymous survey to find out why candidates terminate the process prematurely so the organization can work to fix any shortcomings in the hiring process. An additional proposal for the creation of a mailing list where prospective employees can sign up to be notified of new job postings has been accepted and will be implemented. While those technological advancements are in discussion and development, the team has been able to add the mailing list to the Educational Outreach web page to bridge the gap. The entire Educational Outreach Program has been tailored to benefit the students. The NYSP is committed to the recruitment and retention of valuable, dedicated employees. The goal of the Educational Outreach Program is to interact with driven and motivated STEM students early on in their academic career and guide them into the forensic science career path. The program goals for future improvement are to interact with the students as early on as possible – the team has decided to expand the second year of the program to include select high school students. Senior undergraduate students and graduate students will be given priority to work with the laboratory on collaborative projects that can act as relevant experience for the students as they apply for forensic jobs. The Educational Outreach team is building lasting relationships with the students who will be able to contact their mentors for guidance as they look for employment and beyond as they eventually become colleagues in the same field. The forensic laboratory also benefits from having extended contact with a student to better evaluate a student's potential for long term employment, as well as provide further instruction and one-on-one mentorship within the laboratory setting. The purpose of the NYSP strategic plan is “to attract and retain diverse and highly skilled talent, develop leaders, and maintain public trust and instill confidence in the agency”. Furthering the goal of the strategic plan, the Educational Outreach team proposed that the laboratory staff an exhibit at the 2023 Great New York State Fair. While staffing for this event was made available to all NYSP laboratory employees, the main contingents are also mentors through the Educational Outreach Program. This event will increase public knowledge of the laboratory, clarify some of the mysticism surrounding forensics, and hopefully encourage more quality students to pursue a forensic science career path.

Results and discussion The Forensic Outreach concept has the potential to leverage the NYSP CLS scientific expertise and infrastructure with educational institutions and, eventually, with private industry to create a unique partnership to develop new analytical methods and technologies while enhancing educational opportunities. The Educational Outreach Initiative began by canvassing laboratory staff who had volunteered for a mentor role, and they advised that dispelling common misconceptions of the field should be a focus of the program. Many students understood that there was a disconnect between the Hollywood version of forensic science and the real-life version. However, they didn't know quite where to draw the line of distinction between reality and television. Mentors tailored their lecture sessions to outline the basic concepts of the discipline as well as illustrate job duties that occur daily. A total of 18 students participated in the fall 2022 semester of the FIC School, and 16 in the spring semester. Evaluation of the Educational Outreach Initiative was conducted through feedback from the students, the academic institutions, media news coverage, and laboratory personnel. Students completed an anonymous electronic survey evaluating the components of the outreach initiative that they participated in. Results of the electronic survey are listed in Table 1 . All the survey respondents rated the presentations by the scientific professionals as excellent. Of the students involved in the outreach initiative, over 91% rated the Mentor Mixers as excellent, further indicating the mentor mixers as a valuable opportunity for them. The opportunity for one-on-one conversations with the forensic professionals provided students with a platform to ask their own questions and learn exactly from the experts what their duties include. Additional feedback from the mentor mixers included how valuable the interaction and speaking with the laboratory staff was, learning more about the forensic industry, and hearing what the laboratory staff enjoy most about their jobs as well as the challenges they face. These components of the program were identified as very beneficial by the students. Students found the virtual meetings to be beneficial due to the targeted information they received from the laboratory staff during the interaction in a more private and personal setting. Virtual sessions were found to benefit those students who were shy and not as comfortable with the in-person group setting. The most successful session of the FIC School was the interactive laboratory tour and section demonstrations. The students were separated into three different groups consisting of seven to eight students per group. In the fall 2022 session, the mentors from the seized drugs section of the laboratory demonstrated analysis of a mock case in real-time with the students. This interaction allowed the students a glimpse of what the daily activities of a forensic scientist in seized drugs looks like and get a better idea if the seized drugs discipline would be a career of interest for them. In the spring 2023 session, the bioscience casework section held a detailed demonstration for the students. Again, emphasis was placed on demonstrating the various aspects of a ‘day in the life’ of a forensic scientist assigned to bioscience. Unanimously, the students rated the laboratory tour and demonstrations as excellent. Individual evaluations of the participating students were also positive and showed growth among many of the students. One student, currently in his second year at Hudson Valley Community College (HVCC) majoring in Chemistry, was a very shy and reserved individual at the beginning of the mentor program. At each event, he grew more comfortable in approaching the mentors and participating in the Q&A sessions. He was also an active participant in the virtual mentor sessions. By the end of the third session, this student participated in two interviews with the local television news stations. Several other students showed growth, too, becoming more comfortable talking to the forensic laboratory professionals. The mentorship program provided sufficient information to allow students to decide if the field of forensics is the field of science they want to enter and make their career. The laboratory tours and demonstrations were valuable for the students, providing them with applied knowledge and understanding of each section and which discipline they may be interested in joining. Local news media stations attended the laboratory tour and demonstration event to promote the partnership between local colleges and the NYSP CLS and educate the community. News reporters interviewed both students and mentors about the benefits of the partnership. The feedback and interviews were positive and, in return, enhanced the undergraduate forensic programs at each of the academic institutions. The program has created a positive relationship between the forensic laboratory and the professors at the academic institutions who partnered with the CLS to host the Educational Outreach Program. The professors value the real-life insight into the crime laboratory environment and the insider advice that the mentors provide to the students. Professors with scientific expertise in forensic science related topics have the additional benefit of developing research initiatives in partnership with the forensic laboratory. Educational institutions that participate in the program establish connections with the laboratory mentors to offer targeted advice to the students to help them succeed in obtaining jobs in the forensic field, which is often highly competitive. In the end, both the laboratory and the schools benefit. The program connects students with mentors but also gives mentors the opportunity to evaluate potential candidates for employment and hone professional skills, such as presenting and coaching/mentoring. Increased exposure to forensic scientists, administrators, and their experience assists educators in building their programs. The mentors can help guide and shape the students as they work to complete their education, suggest relevant coursework to take in addition to their regular graduation requirements, and also advise the students on possible internship projects and opportunities. Discussions regarding future program options and improvements include expanding the potential collegiate partnerships and opening the program up local accelerated high school forensic science and STEM students. Mentors learned how to better communicate information to the younger demographic as well as strengthen their public speaking skills overall. This is a benefit for both seasoned forensic professionals and new hires. Participating in the Educational Outreach Program was rewarding and energizing for the mentors. Oftentimes, it is easy to become entrenched in the daily routine. However, taking time to interact and connect with the students and professors was a unique opportunity for the mentors to remember why they entered the field of forensic science in the first place. The students and professors were very enthusiastic in their participation in the program. The mentors felt appreciated and fulfilled as they were able to share their passion and knowledge. Many of the mentors strived to be the ideal mentor – as they wished had existed when they were in school. The entire project has been very well received by the public. The Educational Outreach team has been featured in the school news at all the current partner institutions - College of Saint Rose, State University of New York (SUNY) at Albany, and Hudson Valley Community College. Local news channels also visited during the two laboratory tour days. All of this exposure will increase awareness of the program and a better understanding of the field. Ideally, the program can reach more students who may not know much about forensic science and entice them to embark on this morally rewarding scientific career. The electronic survey also asked the students to identify areas of improvement for the program. Students expressed their desire for additional information and demonstrations about fingerprinting and other sections within the laboratory, in addition to the chemistry and biology sections. Additional feedback for improvement included a request for longer mentor mixer Q&A sessions, more in-depth presentations explaining the daily duties of the laboratory staff, as well as longer live demonstrations. Further recommendations from students included adding additional laboratory mentors to the program. Some students would like to have interactive time in the laboratory shadowing laboratory staff throughout their workday in addition to internship opportunities. However, crime laboratories are generally understaffed and operating with a casework backlog of some extent. Taking time away from casework is a “hard sell” especially when there is no immediate payoff to the laboratory. The second hurdle is the extensive background check required to allow the intern into the section/laboratory unescorted. For the NYSP, that background check is costly, lengthy, and sometimes difficult to pass for prospective employees let alone student interns. Often, the length of the background check process will exceed the length of the internship itself. This is not ideal for many students who do not want to or cannot wait that long to begin an unpaid internship. Lastly, there is limited or no funding to support internships. Instrumentation, reference materials, and equipment are costly. To divert any of these items from casework is problematic. However, partnering with colleges and universities can help to solve many of these problems. A proposal is being developed to enter a remote internship in partnership with the various schools that have worked with the NYSP CLS in the Educational Outreach Program. In the proposal, the school will provide the equipment and instrumentation onsite and the professor can supervise the students in their research. The research topic(s) will be of interest to the laboratory - students can focus on an area of research or validation that the laboratory has a need for but lacks the time and/or additional personnel to pursue. Students could come onsite to the laboratory to run final testing once the validation has been planned and tested at the school. One limitation of this concept is that schools may not have the exact same instrumentation as the NYSP CLS or have the correct license for controlled and/or dangerous substances at their institution. Short term in-laboratory work can be supervised without detriment to the forensic laboratory section. This also negates the need for a lengthy background check process. In the above example, the forensic laboratory has minimal resources invested into the internship but can then use the research project to design an abbreviated validation study that can then be used to generate and implement a procedure for the specific type of analysis. The Educational Outreach team has also been able to brainstorm ideas to assist with employee recruitment and retention that are valuable to the Human Resources department. Working with Human Resources, the team hopes to reduce as many barriers as possible to the employment process. As mentioned previously, the existing background process is extensive and exigent. Often, there is little to no communication to the applicant once the process begins. With team input, laboratory leadership has suggested a more open dialogue with candidates to provide updates throughout the hiring process. Also suggested is a portal or other mechanism of information sharing where the candidate can see the steps needed to gain employment, where they are in the process, and what remains. Both initiatives have been well received and are now being met by an informational fact sheet both read and provided to prospective employees. The website/portal is a larger project that will take more time but can be augmented in the interim by individual outreach to candidates and greater contact via email. It has also been documented that many candidates are lost during the hiring process. The team has also suggested that Human Resources deploy an anonymous survey to find out why candidates terminate the process prematurely so the organization can work to fix any shortcomings in the hiring process. An additional proposal for the creation of a mailing list where prospective employees can sign up to be notified of new job postings has been accepted and will be implemented. While those technological advancements are in discussion and development, the team has been able to add the mailing list to the Educational Outreach web page to bridge the gap. The entire Educational Outreach Program has been tailored to benefit the students. The NYSP is committed to the recruitment and retention of valuable, dedicated employees. The goal of the Educational Outreach Program is to interact with driven and motivated STEM students early on in their academic career and guide them into the forensic science career path. The program goals for future improvement are to interact with the students as early on as possible – the team has decided to expand the second year of the program to include select high school students. Senior undergraduate students and graduate students will be given priority to work with the laboratory on collaborative projects that can act as relevant experience for the students as they apply for forensic jobs. The Educational Outreach team is building lasting relationships with the students who will be able to contact their mentors for guidance as they look for employment and beyond as they eventually become colleagues in the same field. The forensic laboratory also benefits from having extended contact with a student to better evaluate a student's potential for long term employment, as well as provide further instruction and one-on-one mentorship within the laboratory setting. The purpose of the NYSP strategic plan is “to attract and retain diverse and highly skilled talent, develop leaders, and maintain public trust and instill confidence in the agency”. Furthering the goal of the strategic plan, the Educational Outreach team proposed that the laboratory staff an exhibit at the 2023 Great New York State Fair. While staffing for this event was made available to all NYSP laboratory employees, the main contingents are also mentors through the Educational Outreach Program. This event will increase public knowledge of the laboratory, clarify some of the mysticism surrounding forensics, and hopefully encourage more quality students to pursue a forensic science career path.

Conclusions The novel Educational Outreach Initiative and FIC School program created several avenues of outreach and growth to NYSP CLS staff and aspiring forensic scientists. The FIC School supported outreach and recruitment efforts of appropriately qualified candidates. Accreditation requirements are very specific regarding the academic requirements to qualify as a forensic scientist. It is ultimately the academic institutions’ responsibility to be aware of these requirements and to ensure that their curriculum includes the required coursework and laboratory components. As such, it is a major advantage to an academic institution to be able to participate in programs such as the FIC School program designed by the NYSP CLS forensic scientists. Most forensic laboratories operate within a government agency and must adhere to strict practices that dictate local, state, and federal recruitment and hiring. Recruiting and retaining top talent is challenging in an ever-evolving competitive market and it takes an enormous quantity of resources to achieve. Active recruitment implemented through the novel FIC School program addresses these challenges by: 1) Working with academic institutions to encourage that their curriculum encompasses accreditation requirements and standards, including the FBI QAS for DNA testing laboratories. 2) Exposing students (and potential candidates for employment) to crime laboratory work, offering real-world insights. 3) Early and repeated exposure to the forensic laboratory fosters a collaborative relationship between the laboratory and the academic community, laying the groundwork for a recruitment pipeline. Direct engagement between forensic scientists and science students provides a unique vantage point for the students to understand more of the nuances of the forensic profession. Students are exposed to the day-to-day realities of working in a forensic laboratory, including quality control, accreditation, evidence handling, triage of evidence, report writing and reviews, and courtroom testimony. Laboratory work within a paramilitary organization requires an appropriate combination of personality and skillset to maintain high quality work in such a regimented environment. Students can learn these important nuances early on and gauge whether it is the right fit for them. A better understanding of forensic laboratory work amongst the student population also strengthens the applicant pool when forensic positions open. The result is a better fit between the applicant and forensic employer and better quality and quantity of applicants, guided by early involvement through educational outreach.

Skills and knowledge gaps frequently exist between forensic educational programs and practical forensic laboratory needs. An educational outreach project involving three post-secondary academic institutions and a large multidisciplinary forensic laboratory was created to provide lectures to students, enable mentorship with forensic scientists, and provide an interactive experience within the forensic laboratory. Mentorship mixer exercises encouraged meaningful interactions between students and scientists, creating opportunities for practical discussion on employment requirements, optimal class selections based on students’ interests and forensic science requirements, and better understanding of the daily tasks and duties of operational forensic scientists. Feedback from students, professors, and forensic mentors have resulted in program improvements which will inform the educational outreach initiative going forward, including broader community outreach. Keywords

Educational outreach and incubator concept proposal Goals The partnership between the NYSP CLS and the academic institutions aims to increase the quality and quantity of applicants for laboratory employment. Various methods have been explored to attempt to bridge the gap between the forensic laboratory and post-secondary science educational programs. Leading laboratories should be innovating and researching in addition to maintaining a quality caseload output. However, finding resources with which to research and innovate when personnel are busy with a demanding caseload is a constant challenge. This partnership targets broad-reaching benefits for: 1) Students, by enhancing the students' technical skills by providing direct access to laboratory techniques. 2) Forensic laboratories, by providing more resources. 3) Academic Programs, by refining class topics and content towards those applicable to and in use by forensic laboratories. 4) Academic Research, by improving focus of research projects through exposure to real-world applications in forensic science. 5) Scientific community as a whole, through meaningful collaborations that lead to impactful publications and presentations. CRediT authorship contribution statement Ray Wickenheiser: Conceptualization, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing. Amanda Cadau: Writing – original draft, Writing – review & editing. Claire Muro: Writing – original draft, Writing – review & editing. Samantha Whitfield: Writing – original draft. Carrie McGinnis: Writing – original draft, Writing – review & editing. Lola Murray: Writing – original draft. Melissa France: Writing – original draft. Lyn Niles: Writing – original draft. Donna Barron: Writing – original draft. Lori Valentin: Conceptualization, Writing – original draft. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements The authors wish to gratefully acknowledge the support of the New York State Police, the College of St. Rose, Hudson Valley Community College, SUNY Albany, our Forensic Investigation Center mentor colleagues and the participating students who have made the inaugural year of this program a success.

CC BY

no

2024-01-16 23:42:01

Forensic Sci Int Synerg. 2023 Dec 17; 8:100448

oa_package/6b/d5/PMC10788423.tar.gz

PMC10788424

38226024

Introduction Over 700 different species of bacteria, fungi, viruses and protozoa have been discovered in the oral cavity [ 1 ]. These species interact with each other in various communities, collectively known as the oral microbiota. In a healthy environment, the oral microbiome is in balance with its host. However, dysbiosis occurs when pathogenic microorganisms increase in relative number due to a change in the oral environment of the host [ 2 ]. Factors that are associated with oral dysbiosis include poor oral hygiene, smoking, diet, genetics and impaired salivary function [ 3 ]. This can result in oral diseases such as caries, gingivitis and periodontitis. The bacterium most often associated with periodontitis is Porphyromonas gingivalis [ 4 ]. P. gingivalis is a strictly anaerobic, Gram-negative bacterium [ 4 , 5 ]. In addition to periodontitis, P. gingivalis has been associated with systemic diseases such as atherosclerosis, rheumatoid arthritis and Alzheimer's disease, where P. gingivalis was detected in the arterial wall, synovium and brain, respectively [ [6] , [7] , [8] ]. One of the major virulence factors of P. gingivalis are the gingipains [ 9 ]. These proteases are either specific for arginine (Rgp) or lysine (Kgp). They aid in the survival of P. gingivalis within the host, but also increase its pathogenicity by degrading host extracellular matrix and adhesion molecules that are essential for the integrity of host tissue barriers; and degrading cytokines that are required for the host immune response. Gingipains can be secreted, expressed on the surface of the bacterium, or released by outer membrane vesicles into the surrounding microenvironment [ 10 ]. As P. gingivalis has been associated with various systemic diseases, it needs to translocate the oral mucosa and other tissue barriers. One of these mechanisms could be via the interaction with other microorganisms that are present in the oral cavity [ 11 ]. Candida albicans is commonly found in the oral cavity of healthy individuals and is known to interact with various bacteria [ 12 ]. It is a polymorphic yeast, meaning it has various morphologies depending on environmental conditions. In the oral cavity of healthy individuals, C. albicans is commonly present in its yeast morphology (oval-shaped unicellular fungus). However, C. albicans is an opportunistic pathogen and when the immune system of the host is impaired the fungus can increase in relative numbers and form hyphae that have the ability to invade the mucosal tissue of the oral cavity. This results in oropharyngeal candidiasis, more commonly known as oral thrush [ 13 ]. C. albicans has been observed to interact with various bacterial species, which can occur at different levels [ 14 ]. In metabolic interactions, Candida -mediated oxygen removal is important. This could create a niche for P. gingivalis to survive in the oral cavity [ 15 ]. In physical interactions, research has shown that various oral bacteria will adhere to the hyphae of C. albicans [ 14 , 16 ]. These physical interactions commonly involve the hyphae-associated proteins: specific surface proteins that are expressed on the hyphae of C. albicans , different than when it is in yeast form. Examples of these proteins are members of the agglutinin-like sequence (Als) family Als1 and Als3, Hyphal wall protein 1 (Hwp1) and Cell wall adhesion protein 1 (Eap1). All these proteins are specifically expressed on the cell wall of the hyphae and are involved in adhesion of C. albicans to biotic and a-biotic surfaces [ 17 ]. Both metabolic and physical interactions between P. gingivalis and C. albicans may increase the ability of P. gingivalis to invade the host. The aim of the current research was to characterize the interaction between P. gingivalis and C. albicans and to study its effect on the survival of P. gingivalis . First, in a planktonic (free-living) culture it was found that P. gingivalis was able to survive in the presence of C. albicans , even when cultured aerobically. Second, in a dynamic flow system P. gingivalis was shown to adhere to the hyphae of C. albicans and an insight is given into the molecular mechanism of adhesion. And lastly, images of a mixed-species biofilm with both P. gingivalis and C. albicans show the physical interactions of these two microorganisms more clearly.

Materials and methods Strains and growth conditions For this research, two different strains of P. gingivalis and C. albicans were used, a high virulent and a low virulent strain for each microorganism. P. gingivalis W83 is more virulent than ATCC 33277. W83 has a K1 type polysaccharide capsule and 33277 has no capsule [ 18 , 19 ]. The strains have different major fimbriae: P. gingivalis ATCC 332777 has minor fimbriae, unlike P. gingivalis W83 [ 20 ]. C. albicans SC5314 is more virulent than ATCC 10231, as SC5314 grows longer hyphae that can invade tissue structures, while ATCC 10231 is non-invasive [ 21 ]. P. gingivalis W83 and ATCC 33277 were grown on Anaerobic Blood Agar (ABA), which consists of Tryptic Soy Agar (TSA, Becton Dickinson, Franklin Lakes, USA) supplemented with 5 % defibrinated sheep blood (Biotrading, Mijdrecht, the Netherlands), 2 mg/mL glucose (Merck), 5 μg/mL hemin (H, Sigma-Aldrich, St. Louis, USA) and 1 μg/mL menadione (M; Vitamin K, Sigma-Aldrich). Pre-cultures were inoculated overnight in Brain Heart Infusion (BHI, Becton Dickinson) supplemented with H/M. P. gingivalis cultures were incubated at 37 °C under anaerobic conditions: 10 % H 2 , 10 % CO 2 , 80 % N 2 . C. albicans was grown on TSA at 30 °C. Pre-cultures were inoculated overnight in BHI at 30 °C, under aerobic conditions, while shaking at 150 rpm. All microorganisms used are listed in Table 1 . Planktonic co-culture of P. gingivalis and C. albicans P. gingivalis W83 and ATCC 33277 and C. albicans SC5314 pre-cultures were diluted in BHI + H/M to a final optical density measured at 600 nm (OD 600 ) of 0.01 and 0.1, respectively. These OD 600 values equate to approximately 10 8 colony forming units (CFU) per mL for P. gingivalis and 10 6 CFU/mL for C. albicans. Heat-killing of C. albicans was performed at 80 °C for 15 min and Antimycin A (Sigma-Aldrich) was added to a final concentration of 10 μM. Antimycin A is an inhibitor of the classical respiratory pathway in mitochondria of C. albicans and blocks the majority of mitochondrial oxygen consumption [ 26 ]. The cultures were incubated statically at 37 °C, either aerobically or anaerobically. Before incubation and after 48 h, 10 μL samples were taken from each culture and a serial dilution was made. 10 μL of each dilution was spotted on ABA plates and incubated anaerobically for 5–7 days for CFU counting. The CFU were detectable if there were 5 of more CFU per droplet (equating to 500 CFU/mL). If there were less than 5 CFU present, it was determined to be under the detection limit. Determination of gingipain activity To determine the gingipain activity an assay was performed using gingipain-specific fluorogenic substrates, BikKam 14, specific for Kgp, and BikKam 16, specific for Rgp, essentially as described elsewhere [ 27 ]. In short, P. gingivalis and C. albicans were co-cultured as described above. After 48 h, the samples were centrifuged for 1 min at 21300× g and the supernatant was collected. 50 μL of each supernatant sample was added in black clear-bottom 96-well plates (Greiner, Alphen aan den Rijn, the Netherlands). The fluorogenic substrates were diluted in Tris buffered saline (TBS) and 50 μL was added to the samples with a final concentration of 16 μM. Plates were read for 2 h at 37 °C, with 1 min intervals on a microplate reader (Spectramax M2, Molecular Devices, San Jose, USA) at an excitation wavelength of 485 nm and emission wavelength of 530 nm. Protease activity was determined by calculating the relative fluorescence per minute (RF/min) of the initial linear part of the curve that resulted from the kinetic measurement, as described elsewhere [ 27 ]. If a sample showed an RF/min value of 5 or higher, it was considered positive for gingipain activity. Real-time analysis of P. gingivalis adhesion to C. albicans The Bioflux Z1000 setup is as described previously [ 16 ]. Briefly, the channels of 48-well microfluidics plates (Fluxion Biosciences, Alameda, USA) were coated for 30 min with pre-warmed 10 % fetal bovine serum (FBS, Sigma-Aldrich) in phosphate buffered saline (PBS) using a flow rate of 0.5 dyne/cm 2 . C. albicans pre-cultures were diluted to an OD 600 of 0.25 in Yeast Nitrogen Base pH 7.0 supplemented with 0.5 % glucose (YNB, Becton Dickinson). C. albicans suspensions were added to the outlet well of the microfluidics plates and with a flow of 0.5 dyne/cm 2 the channels were filled with cells. The flow was stopped for 30 min to allow the C. albicans to adhere to the surface and afterwards additional YNB was added to the inlet well and flowed at a rate of 0.5 dyne/cm 2 for 2.5 h to allow hyphae formation. P. gingivalis W83 and ATCC 33277 pre-cultures were diluted to an OD 600 of 0.2 and centrifuged for 1 min at 21300× g . They were stained with a 5 nM solution of carboxyfluorescein succinimidyl ester (CFSE, Sigma-Aldrich) in PBS for 30 min at 37 °C. After staining, the cells were washed twice with PBS. The CFSE-labeled P. gingivalis were added to the inlet wells after hyphae were formed and flowed in the channel at a rate of 0.5 dyne/cm 2 . Images were acquired at three random positions with hyphae in the channel every 5 min for 2 h, using a Axio Observer Zeiss Z1 microscope (Zeiss, Oberkochen, Germany). Using a 20× objective, brightfield and green fluorescent illumination (Excitation filter: 405/30 Emission filter: 520/40) were used to visualize C. albicans and CFSE-labeled P. gingivalis , respectively. Image analysis was performed using ImageJ (version 1.53e) [ 28 ]. Per experiment, each condition was performed in duplicate and three positions were imaged per channel, resulting in 6 time-lapses per condition. All results are based on the average of each of the 6 time-lapses in three independent experiments. After 1 h, the total number of hyphae in the image were counted and the number of hyphae that had visible fluorescent P. gingivalis attached was assessed. Then, of these hyphae that had fluorescence, the relative number of P. gingivalis was determined by digitally drawing the outline of the hyphae as a region of interest (ROI) and quantifying the mean fluorescence using ImageJ (version 1.53e). The fluorescent intensity value of the background was subtracted to correct for the fluorescent P. gingivalis that are not adhering to the hyphae. Mixed-species biofilm formation and scanning electron microscopy (SEM) For the acquisition of SEM images, the biofilms were grown on polystyrene squares cut from a 24-well cell culture plate. The surfaces were sterilized using 80 % ethanol, air-dried and placed in a sterile 24-well plate. Pre-cultures of P. gingivalis and C. albicans were diluted in 10 % BHI + H/M to an OD 600 of 0.2 and 0.1, respectively. C. albicans suspensions were added and was allowed to adhere for 90 min at 37 °C. After adherence, the polystyrene surfaces were washed with PBS and the P. gingivalis suspension was added. The surfaces were incubated at 37 °C on a shaking plate for 1 h. The surfaces were washed with PBS again, before adding 10 % BHI + H/M medium. The plates were incubated aerobically at 37 °C for 48 h, with a medium change after 24 h. After incubation, the biofilms were processed for scanning electron microscopy (SEM) analysis, as follows: Samples were washed with PBS and fixed in 2 % glutaraldehyde (Sigma-Aldrich) overnight. The samples were then dehydrated with an ethanol series (35 %, 50 %, 75 %, 95 %, 100 %, 100 % v/v) and air-dried using hexamethyldisilane (HMDS; Sigma-Aldrich). Lastly, the samples were sputter-coated with gold before SEM analysis (EVO LS15, Zeiss, Oberkochen, Germany). SEM has been used previously as a method to assess the wear of tooth surfaces [ 29 ]. Statistical analysis All statistical analyses were performed using GraphPad Prism version 8.1.0 for Windows, GraphPad Software, San Diego, California USA, www.graphpad.com . Statistics shown in the graphs were performed via one-way repeated measures ANOVA and post-hoc Tukey test (table shown in S1). Error bars show the standard deviation (SD).

Results P. gingivalis survives in aerobic conditions in the presence of viable C. albicans To evaluate the influence of C. albicans on the growth of P. gingivalis , co-cultures were grown and viability of P. gingivalis was determined by CFU counting. For both P. gingivalis strains W83 and ATCC 33277, the presence of C. albicans , either viable or heat-killed, did not affect growth in anaerobic conditions compared to P. gingivalis alone ( Fig. 1 A and B). In contrast, aerobic conditions resulted in decreased viability of P. gingivalis as compared to anaerobic conditions. The CFU has decreased to below the detection limit, indicating bacterial cell death. The decrease in viability that occurred when culturing P. gingivalis alone aerobically compared to anaerobically is not occurring when viable C. albicans is present. This is seen for both P. gingivalis strains tested. This effect did not occur when in the presence of heat-killed C. albicans . In addition, viability was decreased by addition of Antimycin A, an inhibitor of oxidative phosphorylation, thereby reducing oxygen consumption by C. albicans [ 15 ]. P. gingivalis W83 showed lower viability in aerobic conditions compared to P. gingivalis ATCC 33277, when comparing the P. gingivalis cultured with live C. albicans to inoculation density (different for each strain, solid line in Fig. 1 A and B). No differences in the growth of C. albicans were observed in the conditions where live C. albicans was present (data not shown). The presence of living C. albicans increases gingipain production Following the finding that C. albicans facilitates the survival of P. gingivalis in aerobic conditions, it was investigated whether this also affected the virulence of P. gingivalis. As an indicator for virulence, the gingipain activity was determined by assessing the degradation of fluorogenic substrates specific for either Kgp or Rgp ( Fig. 2 ). For strain W83 of P. gingivalis , gingipain activity was measured after culturing under anaerobic conditions, with a significant increase in activity when live C. albicans was added compared to P. gingivalis alone ( Fig. 2 A, C). Under aerobic conditions, there was only positive gingipain activity (above the threshold of 5 RF/min) in the presence of live C. albicans . These activities were noted for both Kgp and Rgp activity. For P. gingivalis strain ATCC 33277, comparable results have been found as of P. gingivalis W83 ( Fig. 2 B, D). One difference is that under aerobic conditions, the gingipain activity is still present upon addition of Antimycin A, which was not seen for W83. To summarize, the presence of C. albicans not only facilitates the survival of P. gingivalis under aerobic conditions, but the gingipain activity of P. gingivalis is also retained. Als3 and Als1 mediate the adhesion of P. gingivalis to C. albicans hyphae The results of the metabolic analysis could be explained by a physical interaction between P. gingivalis and C. albicans . This was investigated using a dynamic flow system, used to study adherence of P. gingivalis to the hyphae of C. albicans over time. Adherence occurred within 1.5 h ( Fig. 3 , S2, S3 ). The bacterium appeared to cluster on the hyphae, with P. gingivalis ATCC 33277 showing this effect more predominantly than P. gingivalis W83 ( Fig. 3 ). The hyphae of C. albicans ATCC 10231 were shorter than for C. albicans SC5314, but the level of P. gingivalis adherence was similar for the two C. albicans strains. Two strains of C. albicans were used to determine whether the length of the hyphae would have an influence on the ability of P. gingivalis to adhere, and to exclude the possibility that this effect is strain-specific. In addition, the mechanism of adherence of P. gingvialis to C. albicans was investigated. Absence of cellwall proteins Als1, Hwp1 and Eap1 did not affect adherence of P. gingivalis ( Fig. 4 ). For the Als3 mutant, the adherence was reduced and for the Als1,3 double mutant even less adherence was observed. For the Als1,3 double mutant, the amount of hyphae that had P. gingivalis attached to it was significantly reduced ( Fig. 4 B, D) compared to the wild type (WT, SC5314). This was the case for both strains of P. gingivalis (W83 and ATCC 33277). In addition, it was found that deletion of Als3 seemed to have a significant reduction on the amount of adhesion of P. gingivalis per hyphae and that this effect was increased when both Als1 and Als3 were absent ( Fig. 4 C, E). The variability in the measured values is much higher for P. gingivalis ATCC 33277 than for P. gingivalis W83. Biofilm formation To investigate the adhesion in more detail, mixed-species biofilms of C. albicans and P. gingivalis were grown on polystyrene surfaces to investigate the ability of P. gingivalis to attach to a C. albicans biofilm. SEM analysis show adherence of P. gingivalis W83 ( Fig. 5 A) and ATCC 33277 ( Fig. 5 B) to both yeast and hyphae of C. albicans . In Fig. 5 A, it can also be seen that P. gingivalis adheres to each other, and not only to the hyphae. SEM images of a biofilm of only C. albicans is shown in Fig. 5 C.

Discussion The oral microbiome is a complex, diverse and dynamic biological system [ 1 ]. The microorganisms are constantly interacting with each other and with the host, which might influence the pathogenicity of certain species. The aim of this study was to characterize how the interaction between P. gingivalis and C. albicans could influence survival and virulence of P. gingivalis under aerobic conditions, conditions that prevail in the body of the host. When elucidating the mechanism of such interactions, these pathways of entry into the body could lead to a novel concept of the pathogenesis of P. gingivalis associated periodontitis. The current study has shown that the interaction of P. gingivalis with C. albicans allows for the anaerobic bacterium to survive in an aerobic environment. In addition, it is indicated that P. gingivalis retains its virulence, as shown by the activity of its secreted gingipains. There is a physical interaction between these two microbes which is mediated by the Als1 and Als3 proteins of C. albicans, where it can be suggested that Als1 is able to partially take over the function of Als3. In addition, these microorganisms can form mixed-species biofilms to which P. gingivalis can adhere and grow. In a planktonic aerobic culture, it was found in the current study that P. gingivalis can only survive in the presence of live C. albicans . The explanation for this is that the survival of P. gingivalis is due to the oxygen consumption by C. albicans , which creates an environment with low oxygen levels in which P. gingivalis can survive and grow [ 15 , 30 ]. This same principle has been shown in previous research, for other anaerobic bacteria, e.g. Bacteroides fragilis, Clostridium perfringens, Cutibacterium acnes, and Clostridioides difficile (previously Clostridium difficile ) [ [31] , [32] , [33] ]. Previous research by Bartnicka et al. has resulted in similar finding as the current study [ 30 ]. Both this previous research and the current study show that C. albicans can create a hypoxic environment to protect P. gingivalis against oxygen. It is postulated in that previous study that this is due to oxygen consumption by C. albicans . The current study adds on this by showing that inhibition of oxygen consumption by Antimycin A reduces the effect, confirming their hypothesis. This allows C. albicans to be a vector for anaerobic bacteria to survive and leads to the hypothesis that C. albicans could aid P. gingivalis to invade the host tissue [ 34 ]. One of the major virulence factors of P. gingivalis is the gingipain family of proteases. The measured gingipain activity showed a difference between the fluorogenic substrates used. This can be explained by the fact that both substrates contain an additional lysine residue, next to the 2 lysine or 2 arginine residues [ 27 ]. This means that the degradation of the Rgp-specific substrate is partially caused by the Kgp activity as well as the Rgp activity, meaning it is less specific for only Rgp. This explains why the gingipain activity of Rgp seems so much higher than Kgp. As the results of the two separate substrates show the same trend, it can be concluded that the different conditions in which P. gingivalis was cultured had similar effects on the activity or expression of both gingipains. In addition, the gingipain activity of the different cultures followed a similar trend as the survival of P. gingivalis , with two exceptions. First, it was found that for only P. gingivalis W83, the degradation of fluorogenic substrates by gingipains was increased in anaerobic conditions in the presence of live C . albicans . This effect was not due to increased number of P. gingivalis bacteria, as the number of viable bacteria were found to remain similar for all cultures in anaerobic conditions. This suggests that C. albicans had a positive influence on the production or activity of gingipains by P. gingivalis , although only for P. gingivalis W83. This increased gingipain activity in the presence of C. albicans has been shown before, but only for Rgp and not Kgp [ 35 ]. This indicates that the interaction with C. albicans can aid the bacterium in its pathogenicity. Whether this phenomenon also occurs in the oral cavity is unclear, as other microorganisms might also influence the gingipain activity by rendering the gingipains inactive. Second, P. gingivalis ATCC 33277 provides more gingipain activity in the presence of Antimycin A than P. gingivalis W83, which shows no gingipain activity at all under these conditions. As mentioned before, it was found that P. gingivalis ATCC 33277 tended to aggregate more than P. gingivalis W83. This also explains the higher variability of the measured values for P. gingivalis ATCC 33277 when quantifying the adherence to C. albicans hyphae. The aggregation of this strain might have an influence on the fact that ATCC 33277 seems to be slightly more aerotolerant than W83. However, this specific phenomenon needs to be researched as there are no studies yet available that have investigated this. Another limitation of this study is that out-of-focus hyphae are difficult to trace, using the image analysis setup developed for this study. This might create bias in the data, and therefore it is not completely quantitative. However, a clear trend can be seen and the results of the analysis clearly correlate with the images provided. The current study shows that adhesion for P. gingivalis is mediated by both Als3 and Als1 proteins of C. albicans. The absence of Als1 alone did not result in a reduction in adherence, but there was a significant difference in adherence when both Als1 and Als3 were absent. This suggests that Als1 is able to partially take over the function of Als3, with regard to binding to P. gingivalis . Previous research has shown that Als3 is involved in the mechanism adhesion of not only P. gingivalis , but also the adhesion of Staphylococcus aureus to hyphae of C. albicans [ 16 , 36 ]. However, in the current study it was found that Als1 was also involved in the mechanism of adhesion, which is something that has not been studied before for P. gingivalis. Other previous research has shown that the presence of C. albicans is necessary for S. aureus to disseminate to the bloodstream, and that this is likely mediated by macrophages that phagocytose the bacteria and relocate to the lymph nodes [ 37 ]. A similar mechanism might occur for P. gingivalis , as it was found in another study that P. gingivalis can survive within macrophages and exit them at a later stage [ 20 ]. However, the abundance of adhesion seems much higher in the case of S. aureus [ 16 ] . In addition, previous research found that C. albicans facilitates P. gingivalis invasion of gingival epithelial cells and fibroblasts [ 38 ]. More research is needed to confirm whether adhesion to C. albicans could also be a way for P. gingivalis to disseminate. Again, the study by Bartnicka et al. shows similar results as the current study, namely that the adhesion of P. gingivalis to C. albicans is mediated by Als3 [ 30 ]. The previous study used purified fungal proteins, whereas the current study used whole and live C. albicans cells. Observing the interaction between two microorganisms on a whole cell level gives a more complete view, while the approach of the previous research is limited to observing only one fungal protein at a time. This is shown in the current study, as it was found that Als1 is also involved in the interaction between C. albicans and P. gingivalis , in addition to Als3. In the current study was found that adherence to the hyphae of C. albicans has a positive influence on the growth of P. gingivalis , but only for P. gingivalis W83. There have been studies before that have observed a mixed biofilm of C. albicans and P. gingivalis [ 30 , 36 , 39 ]. However, none have shown microscopic images using SEM where the adhesion of P. gingivalis to the hyphae of C. albicans is physically visible. In previous research, P. gingivalis has been observed as a rod-shaped bacterium [ 40 ]. However, in other studies, P. gingivalis has also been found as coccobacilli [ 41 , 42 ]. Adherence to C. albicans and the concentration of heme in the environment were found to an influence on P. gingivalis morphology [ 43 ]. P. gingivalis is mainly found in the gingival sulcus of people suffering from periodontitis, which is an environment with low oxygen [ 44 ]. Traditional treatment for periodontitis involves scaling and root planing, which disrupts the biofilm, potentially introducing oxygen into the environment. The current study has shown that the presence of C. albicans protects P. gingivalis against the oxygen, allowing it to survive, increasing its risk to invade the tissue and infiltrate the bloodstream. Of interest, similar studies on C. albicans and Staphylococcus aureus also indicated decreased susceptibility to antibiotics in co-cultures. This should be investigated in the future as antibiotic treatment following scaling and root planning is a common strategy [ 45 ]. In conclusion, this study shows that P. gingivalis survives and stays virulent in aerobic conditions when in the presence of C. albicans . The interaction with C. albicans could be a relevant mechanism for P. gingivalis to circumvent the aerobic environment of the host. Furthermore, it was found that Als1 and Als3 of C. albicans are involved in the interaction between the two microorganisms. This interaction leads to an increase in survival and virulence of P. gingivalis in oxygen-rich environment, which could be important for the pathogenicity of P. gingivalis . In addition, the adherence to C. albicans hyphae could provide an anchor point for P. gingivalis to colonize the oral cavity. These results emphasize the importance of interaction between different microbes in promoting survival, virulence and attachment of anaerobic pathogens. This could be essential in facilitating their penetration into the environment of the host.

In the oral cavity Candida albicans interacts with many oral bacteria, including Porphyromonas gingivalis , both physically and metabolically. The aim of this in vitro study was to characterize these interactions and study their effects on the survival of P. gingivalis . First, metabolic interactions were evaluated by counting the colony forming units (CFU) after co-culturing. The results indicated that the anaerobic bacterium P. gingivalis survives under aerobic conditions when co-cultured with C. albicans . This is due to the oxygen consumption by C. albicans as determined by a reduction in survival upon the addition of Antimycin A. By measuring the protease activity, it was found that the presence of C. albicans induced gingipain activity by P. gingivalis , which is an important virulence factor. Adherence of P. gingivalis to hyphae of C. albicans was observed with a dynamic flow system. Using various C. albicans mutants, it was shown that the mechanism of adhesion was mediated by the cell wall adhesins, members of the agglutinin-like sequence (Als) family: Als3 and Als1. Furthermore, the two microorganisms could be co-cultured into forming a biofilm in which P. gingivalis can survive under aerobic culturing conditions, which was imaged using scanning electron microscopy. This study has further elucidated mechanisms of interaction, virulence acquisition and survival of P. gingivalis when co-cultured with C. albicans . Such survival could be essential for the pathogenicity of P. gingivalis in the oxygen-rich niches of the oral cavity. This study has emphasized the importance of interaction between different microbes in promoting survival, virulence and attachment of pathogens, which could be essential in facilitating penetration into the environment of the host. Keywords

Funding details This project is funded by the faculty of Dentistry, Academic Centre for Dentistry in Amsterdam, University of Amsterdam and Free University of Amsterdam. Disclosure statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. CRediT authorship contribution statement Caroline A. de Jongh: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft. Floris J. Bikker: Conceptualization, Funding acquisition, Supervision, Writing – review & editing. Teun J. de Vries: Conceptualization, Funding acquisition, Supervision, Writing – review & editing. Arie Werner: Methodology, Visualization, Writing – review & editing. Susan Gibbs: Conceptualization, Funding acquisition, Supervision, Writing – review & editing. Bastiaan P. Krom: Conceptualization, Funding acquisition, Supervision, Writing – review & editing. Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary data The following are the Supplementary data to this article: Data availability Data will be made available on request. Acknowledgements The authors thank prof P. van Dijck for kindly providing C. albicans mutants and Wendy Kaman for providing the protocol and materials for the gingipain activity assay. Purchase of the Bioflux Z1000 system was made possible by a grant from the Division for Earth and Life Sciences (ALW) with financial aid from the Netherlands Organization for Scientific Research (NWO) with reference number 843.13.006.

CC BY

no

2024-01-16 23:42:01

Biofilm. 2023 Dec 17; 7:100172

oa_package/29/7e/PMC10788424.tar.gz

PMC10788429

38226216

Introduction Loneliness: a public health problem Loneliness is a serious public health problem. It leads to a higher risk of premature death and the onset and progression of a range of physical and mental health problems, such as cardiovascular diseases, infectious diseases, and depression [ [1] , [2] , [3] , [4] ]. During the COVID-19 pandemic, social distancing measures to contain SARS-CoV-2 transmission have led to a reduction in daily contact and an increased risk of loneliness [ [5] , [6] , [7] ]. Globally, loneliness is widespread, with some countries reporting that up to one in three older people feel lonely [ 8 ]. In the Netherlands, the percentage of adults who experienced loneliness in 2022 was 49 % [ 9 ]. Loneliness also imposes a heavy financial burden on society, as it directly or indirectly results in increased healthcare costs [ 10 , 11 ]. Dimensions of loneliness Loneliness is defined as “the unpleasant experience that occurs when a person's network of social relationships is deficient in some important way, either quantitatively or qualitatively” [ 12 ]. Weiss differentiated between social and emotional loneliness with social loneliness defined as “the absence of a broader group of contacts or an engaging social network (e.g., friends, colleagues, and people in the neighborhood)”, whereas emotional loneliness is defined as “the absence of an intimate relationship or a close emotional attachment (e.g., a partner or a best friend)” [ 13 ]. Instruments to assess loneliness usually do not distinguish between the two types, yet a validated questionnaire to assess both dimensions of loneliness is the De Jong Gierveld scale [ 14 ]. Social networks in relation to loneliness and preventive strategies To address loneliness implies that we acknowledge that loneliness is related to both the structure and function of a social network, in addition to other types of relevant personal, social, and structural factors. Most previous studies assessing social network aspects in relation to loneliness have emphasized social network size (a structural social network aspect), demonstrating a link between fewer social contacts (small network size) and loneliness [ 15 , 16 ]. Interventions to curb loneliness will first need to identify the crucial network aspects and use these to either prevent loneliness or alleviate its consequences. Most previous interventions have focused on promoting social interactions. Yet, merely increasing the number of social relationships that a person has, is usually not effective in social and emotional loneliness [ 17 ]. Not commonly, other structural or functional network aspects are identified. Yet, a richer description of social networks based on various structural and functional aspects can be useful in the search for effective targets for the prevention of loneliness. Social networks, in which an individual is embedded, can be composed of many or few relationships, and multiple types of relationships, supports, and modes of contact [ 18 ]. Most studies examining loneliness included a limited set of such social network metrics or evaluated only ‘single’ network aspect. Though recommended is to evaluate structural and functional social network aspects jointly when assessing loneliness [ [19] , [20] , [21] ], most studies also lacked such evaluation of a combination of network aspects. As a result, in-depth knowledge of which social network aspects are most important in loneliness, in particular, emotional and social loneliness is scarce [ 22 ]. Structural social network aspects beyond the number of network members (network size) Structural social network aspects include network diversity (multiple types of social relationships), network density (how well network members are connected to each other), homogeneity in terms of age and sex, geographical proximity, living alone, and mode of contact [ 18 ]. Few studies examined these other structural network aspects; family-focused (less diverse) social networks were associated with loneliness among older adults, whereas having a larger share of friends in the network was inversely associated [ 23 , 24 ]. People with more social network members in the neighborhood are less likely to be lonely, as these network members can meet up more easily [ 25 , 26 ]. Not just a lack of geographical proximity among network members, but also living alone increases the risk for loneliness [ 22 , [27] , [28] , [29] ]. Functional social network aspects Functional social network aspects include social support from network members, such as informational, emotional, and practical support [ 18 ]. Social support may facilitate an adequate response to a possible stressful event and thereby avoiding a physical stress response or illness [ 30 ]. Lack of emotional support is associated with loneliness [ 31 ]. Also, the type of supporting relationships (family versus non-family members) was associated with the risk of emotional loneliness [ 32 ]. Social support roles have changed during the COVID-19 pandemic as people had fewer emotional or practical supporters, but also people had to depend more on their family members or neighbors for various types of support [ 33 , 34 ]. Social connectedness During the COVID-19 pandemic, people felt less connected with family and friends [ 35 ]. Social connectedness or the subjective feeling of being embedded within a social network is important for well-being. Feeling less connected might contribute to feelings of loneliness [ [36] , [37] , [38] ]. Sex differences Previous research focusing on loneliness has established sex differences. Many studies report that women are more likely to be lonely compared to men [ [39] , [40] , [41] ]. Possible explanations for this difference can be attributed to sociodemographic and health-related factors. Some studies established that practical educational level and a relatively worse health status in women in their studies resulted in reduced social interactions, and exacerbating loneliness [ 38 , 42 , 43 ]. A few studies established that men were more likely to be lonely, especially at younger age [ 44 ]. Some studies also distinguished the two dimensions of loneliness showing that women were more likely to be emotionally lonely whereas men were more likely to be socially lonely [ 45 , 46 ]. Moreover, sex differences are also visible in the structure and function of social networks of men and women. Women tend to have larger and more diverse social networks and receive more and different types of social support compared to men [ 34 , 47 , 48 ]. The present study The Social Network Assessment in Adults and Elderly (SaNAE) study assesses social networks in relation to health. The objective of the current study is to jointly evaluate a range of structural and functional social network aspects for their association with loneliness. Specifically, the health outcomes of both social and emotional loneliness were evaluated separately among older adults during the COVID-19 pandemic. These associations are examined for men and for women, as previous studies have revealed distinct sex differences [ 22 , 34 , 43 ]. Doing so reveals possible key social network targets for preventive strategies in men and women for the identification of social and emotional loneliness and for the prevention or alleviation of loneliness.

Methods Ethical statement This study was approved by the Medical Ethical Committee of the University of Maastricht (METC 2018–0698, 2019–1035, and 2020–2266). Participants gave electronic informed consent. Study design and population This cross-sectional study used data from the Dutch SaNAE cohort ( www.sanae-study.nl ), measured in August–November 2020 using an online questionnaire. The SaNAE study was started in 2019 and included 5144 participants who were independent-living Dutch adults aged 40 years or older [ 49 ]. In August–November 2020, 5001 participants were invited for a follow-up questionnaire of whom 67 % (n = 3505) responded. Respondents were slightly older (mean difference 1.8 years, p < 0.001) and slightly more theoretically educated (χ 2 = 20.884; df = 2; p < 0.001) compared to non-responders but did not differ in sex or network size (p > 0.05). Respondents without missing data on variables of interest in this study were included in further analyses (n = 3396). Moderate or severe emotional and social loneliness (outcomes in analyses) Loneliness was assessed using the six-item De Jong Gierveld Loneliness Scale [ 14 ]. The six-item scale can be used to measure unidimensional loneliness, but also to measure social and emotional loneliness. Three items for social loneliness included ‘There are plenty of people I can rely on when I have problems’, ‘There are many people whom I can trust completely’, and ‘There are enough people I feel close to’. The three items for emotional loneliness included ‘I experience a general sense of emptiness’, ‘I miss having people around’, and ‘I often feel rejected’. Answer categories included totally agree, agree, neutral, disagree, and totally disagree. The answer categories neutral, disagree, and totally disagree were counted for social loneliness while the answer categories neutral, agree, and totally agree were counted for emotional loneliness. A score of zero or one was defined as ‘not lonely’ whereas a score of two or three was defined as ‘(moderately/severely) lonely’ [ 46 ]. Reliability tests were performed calculating Cronbach's alpha coefficients for social and emotional loneliness items separately. Social network aspects (independent variables) Social network aspects were measured using a name-generator questionnaire. Participants were asked to provide names of family members, friends, acquaintances, and other persons who are important to them or provide social support. Additional information about network members was asked using name interpreter items. A more detailed description can be found elsewhere [ 34 , 49 ] and in Supplementary Table 1 . We include a range of structural and functional metrics ( Supplementary Table 1 ). Statistical analyses Descriptive analyses were used for sociodemographic characteristics and social network aspects of the study population. All analyses were performed for the outcome variables: social and emotional loneliness. All analyses were stratified by sex. Various multivariable logistic regression analyses models were constructed which also included the confounding variables: age, educational level, level of urbanization, and comorbidities (Type 2 Diabetes Mellitus, asthma/COPD, and cardiovascular diseases). Models (0) were created for each social network aspect separately as independent variable adjusted for confounding variables (results not presented). Models (I) were created including all social network aspects that were statistically significant from Models (0), using stepwise backward selection and also included potentially confounding variables. Models (II) additionally included social network size. Finally, for emotional loneliness as an outcome, models (III) included a variable social loneliness (as an independent determinant) since social loneliness was expected to be (in part) in the pathway between network aspects and emotional loneliness ( Fig. 1 ). Before the models were built, multicollinearity between social network aspects was ruled out (correlation analyses: all correlations <0.7). A p -value <0.05 indicated statistical significance. All analyses were performed using IBM SPSS Statistics (version 27.0). Sensitivity analyses Sensitivity analyses were performed to assess the outcomes of social and emotional loneliness when based on a different cut-off value of one and higher to reflect lonely versus not lonely (rather than the main analyses that focused on moderate/severe loneliness).

Results Study population Of all participants, 55 % were men, and 43 % of the participants had a theoretical educational level. The mean age was 65 years ( Table 1 ). Moderate/severe social and emotional loneliness Of the men, 20 % (367/1874) were socially lonely and 25 % (476/1874) were emotionally lonely. Of the women, 16 % (249/1522) were socially lonely and 31 % (479/1522) were emotionally lonely. Men were more likely to be socially lonely compared to women [aOR: 1.24, p < 0.05] whereas women were more likely to be emotionally lonely compared to men [aOR: 1.50, p < 0.001]. 10 % (189/1874) of the men and 11 % (174/1522) of the women were both socially and emotionally lonely. Among the socially lonely men, 52 % (189/367) were also emotionally lonely ( Fig. 1 A). For socially lonely women, this was 70 % (174/249) ( Fig. 1 B). Social network structure in people who are moderately/severely lonely Men Of socially lonely men, 50 % had four or fewer network members. For 33 %, their social network was composed of only family members; 20 % had diverse social networks including family members, friends, and acquaintances who know each other (well) ( Table 2 ). Of emotionally lonely men, 37 % had four or fewer network members. For 19 %, the social network included only family members; 30 % had diverse networks. Women Of socially lonely women, 39 % had four or fewer network members. For 25 %, their social network was composed of only family members; 34 % had diverse social networks including family members, friends, and acquaintances who know each other (well) ( Table 2 ). Of emotionally lonely women, 23 % had four or fewer network members. For 11 %, the social network included only family members; 42 % had diverse networks. Social network aspects associated with moderate/severe social loneliness Men In model I, independently associated with social loneliness was having less diverse and less dense social networks, a larger proportion of network members living in the same house or living far away, living alone, not participating in work, not being a member of a music organization, having fewer emotional supporters and feeling less connected with friends, and feeling more connected with neighbors ( Table 3 ). After adding network size (model II), all these social network aspects, except social network size and not being a member of a music organization, remained associated. Women In model I, independently associated with social loneliness were having less diverse and less dense social networks, living alone, not being a member of a sports club, having fewer informational supporters, and feeling less connected with family and neighbors. After adding network size (model II), all these social network aspects remained associated. Smaller social network size was also associated with social loneliness ( Table 3 ). Social network aspects associated with moderate/severe emotional loneliness Men In model I, independently associated with emotional loneliness were having less diverse and less dense social networks, contacting a larger proportion of network members exclusively online, living alone, membership of a religious group, feeling less connected to friends, people from work and the city, and feeling more connected with friends, and the country. After adding network size (model II), all these social network aspects remained associated, except for network diversity and density. After adding social loneliness (model III), all social network aspects remained associated, except feeling more connected to the country. Social loneliness was also associated with emotional loneliness ( Table 4 ). Women In model I, independently associated with emotional loneliness were less diverse and less dense social networks, living alone, not participating in work, having fewer emotional supporters, and feeling less connected with friends, people from work, and the city, and feeling more connected with people from work. After adding network size (model II), all these social network aspects remained associated except feeling more connected to people from work. Smaller network size was also associated. After adding social loneliness (model III), all social network aspects remained associated except network size and diversity and density. A visual overview of all associations between social networks and social and emotional loneliness is available in Fig. 2 A,B. Sensitivity analyses showed similar results for the observed associated network aspects, when using another cut-off value (≥1) for both social and emotional loneliness ( Supplementary Tables 2 and 3 ).

Discussion This detailed evaluation of loneliness in Dutch adults aged 40 years and older, uniquely evaluated the structure and function of social networks and did so in relation to social loneliness as well as emotional loneliness. Of men, 20 % and 25 % were (moderately/severely) socially and emotionally lonely, respectively. Of women, 16 % and 32 % were (moderately/severely) socially and emotionally lonely, respectively. More than half of the people who were socially lonely, also were emotionally lonely. A sizeable proportion (19%–24 %) ‘only’ were emotionally lonely. By evaluating a wide range of structural and functional social network aspects, jointly, this study was able to identify the most important social network aspects for men and women, and for the two dimensions of loneliness. These insights can be further used to address of relevant social network aspects and strategies to prevent or alleviate loneliness. Loneliness is a profoundly unpleasant experience and not merely defined by either a structural or functional social network aspect. This experience can certainly be more than ‘just’ the lack of the number of relationships or lack of social support. Striking differences were observed for social or emotional loneliness in this respect as well. Men and women in the current study were more (moderately/severely) socially lonely when their social network was less diverse (e.g., family-centered), in line with previous studies [ 15 , 16 , 23 , 24 ], or less dense (friends and family clustered less). Also, a smaller network size was associated with social loneliness (women only) in line with previous studies [ 31 ]. Further, men and women were more likely to be socially lonely when they lived alone. Living alone is a well-known factor in loneliness and other adverse health outcomes [ [27] , [28] , [29] , 40 ]. Also important in social loneliness were feeling less connected to friends, fewer emotional supporters (for men only), fewer informational supporters (for women only), and not having a club membership. Men and women were (moderately/severely) lonely when they also felt socially lonely, when they lived alone, when a larger proportion of their network members was contacted exclusively online (for men only), or when having fewer emotional supporters (for women only). Various metrics have been shown to be important in previous studies [ 22 ], while this study thus also revealed novel insights. Important to highlight is that less diverse and less dense social networks likely posed a risk for social or emotional loneliness in men and women, regardless of the number of social relationships a person has. This has implications for assessing social network structure in relation to health, indicating the importance of taking network diversity and density into account. Also notable was that women who had fewer informational supporters and men who had fewer emotional supporters were more likely to be socially lonely, indicating that men and women may have different needs for social support from their social network. Previous studies have already established sex differences in the type of social support and type of social relationships providing support, with women receiving more emotional support from different types of relationships [ 34 , 47 ]. Finally, online contact (for men) was detrimental to emotional loneliness, highlighting the value of in-person contact which was also observed in a qualitative study [ 50 ]. Physical contact with social network members was reduced and (temporarily) replaced with online contact during the COVID-19 pandemic [ 34 ]. Especially those who live alone were affected by these measures since online contact among individuals who live alone was in previous studies with negative emotions and loneliness [ 51 , 52 ]. Online contact might not be a full substitute for in-person contact [ 53 ] and it has been demonstrated to decrease the level of feeling connected to others, which in turn negatively impacts health [ 35 ]. Social participation was also linked to social loneliness, as women in the current study who did not have a sports club membership more often were lonely. Previous studies have reported that women who exercise with others may do so for motivation and social conviviality [ 54 ], and exercising together stimulates them to exercise more frequently [ [55] , [56] , [57] ]. Men in this study who were members of religious groups were more likely to be emotionally lonely, and the reasons are unknown and could be a topic of further study. Interestingly, men who were retired were more likely to be socially lonely and women who were unemployed were more likely to emotionally lonely. A possible explanation could be that women receive more social support from coworkers compared to men, and are more likely to consider their coworkers as their friends [ 58 ]. Implications To curb trends in loneliness is a key public health priority. This means to better identify relevant social network aspects in loneliness and to better use these insights for designing strategies to prevent or alleviate loneliness. The current study provides insight into possible targets for the identification of loneliness and strategies to prevent or to alleviate loneliness. These results stress the importance of looking beyond the number of social relationships and consider the rich variety of social network aspects. Moreover, this rich variety of social network aspects for social and emotional loneliness differ for men and women. Therefore, sex differences should be taken into account in preventive strategies. Examples for better identification include a small network size, but also less diverse relationships as well as employment status and living alone, factors that may serve as indicators to recognize possible loneliness. Targeting social loneliness may also in part target emotional loneliness, but not completely as different social network aspects are important for both constructs. In line with the work of Holt-Lunstad, we suggest that future research should focus on the development of social connection guidelines including the social network aspects identified in the current study [ 59 ]. Examples for preventive strategies focused on network structure could be to help people to expand their network by adding new network members to also create a more diverse social network, and by strengthening connections between social network members to increase density. Club memberships (e.g., sports or music organizations) should be promoted and facilitated to enable people to meet new people in leisure activities. Strategies should further build on strengthening social network function for social support in existing social network members and relevant support in new members. This means that strategies should primarily focus on the social environment rather than only the individual living in it. Strengths and limitations A strength of the current study is that we used a large cohort study that uniquely and jointly assessed various structural and functional social network aspects in men and women, in combination with health outcomes such as social and emotional loneliness. To assess the social network aspects, a name generator questionnaire with name interpreter items was used, which is a useful method for measuring social networks in online surveys extracting large and diverse networks [ 60 ]. Furthermore, we evaluated the social network aspects separately for social and emotional loneliness and thereby identified which aspects are most important for each type of loneliness. Some limitations should be mentioned. Different answer categories for the De Jong Gierveld scale were used. Instead of three answer categories: ‘yes’, ‘more or less’, and ‘no’, a five-Likert scale was used “totally agree – agree – neutral – disagree – totally disagree”. Reliability tests to determine internal consistency reliability for social and emotional loneliness items were performed. Items showed high internal consistency. (social loneliness items: α = 0.911, and emotional loneliness items: α = 0.794). Furthermore, due to the cross-sectional design of the current study, no conclusions can be drawn on the causality of the effects.

Conclusion Our current study assessed structural and functional social network aspects associated with (moderately/severely) social and emotional loneliness for men and women separately and established that diverse and dense social networks and emotional and informational social support are key factors associated with social and emotional loneliness. Other relevant determinants were geographical proximity, mode of contact, club membership, employment status, living alone, and social cohesion. Preventive strategies to alleviate or prevent loneliness should focus on both structural and functional network aspects, need to look beyond the number of social relationships and promote diverse and supporting social relationships.

Background Loneliness is a serious public health problem. This became even more visible during the COVID-19 pandemic. Yet, the key social network aspects contributing to loneliness remain unknown. Here, we evaluated social network structure and function and associations with (moderate/severe) social and emotional loneliness in older adults. Methods This cross-sectional study includes online questionnaire data (SaNAE cohort, August–November 2020), in independently living Dutch adults aged 40 years and older. For the separate outcomes of social and emotional loneliness, associations with structural social network aspects (e.g., network diversity - having various types of relationships, and density - network members who know each other), and functional social network aspects (informational, emotional, and practical social support) were assessed and risk estimates were adjusted for age, educational level, level or urbanization, comorbidities, and network size. Multivariable logistic regression analyses were stratified by sex. Results Of 3396 participants (55 % men; mean age 65 years), 18 % were socially lonely which was associated with a less diverse and less dense network, living alone, feeling less connected to friends, not having a club membership, and fewer emotional supporters (men only) or informational supporters (women only). 28 % were emotionally lonely, which was associated with being socially lonely, and more exclusively online (versus in-person) contacts (men only), and fewer emotional supporters (women only). Conclusion Network structure and function beyond the mere number of contacts is key in loneliness. Public health strategies to prevent loneliness in older adults should be sex-tailored and promote network diversity and density, club membership, informational and emotional support, and in-person contact. Keywords

Data availability statement The dataset supporting the conclusions of this article is available upon request. Data contains potentially identifying and sensitive information of respondents. Due to the General Data Protection Regulation, it is not allowed to distribute or share any personal data that can be traced back (direct or indirect) to an individual. Moreover, publicly sharing the data would not be in accordance with participant consent for this study. CRediT authorship contribution statement Lisanne CJ. Steijvers: Writing – original draft, Visualization, Methodology, Formal analysis, Conceptualization. Stephanie Brinkhues: Writing – review & editing, Visualization, Supervision, Methodology, Formal analysis, Conceptualization. Bianca Suanet: Writing – review & editing. Mandy MN. Stijnen: Writing – review & editing. Christian JPA. Hoebe: Writing – review & editing, Supervision. Nicole HTM. Dukers-Muijrers: Writing – review & editing, Visualization, Supervision, Methodology, Formal analysis, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary data The following is the Supplementary data to this article.

CC BY

no

2024-01-16 23:42:01

Heliyon. 2023 Dec 16; 10(1):e23734

oa_package/2a/b8/PMC10788429.tar.gz

PMC10788430

38226362

Background It is estimated that cerebrovascular disease (CVD) is a contributing factor in about 70 % of dementia cases, while it is the major or only etiological factor in 15–25 % cases [1] . Vascular contributions to cognitive impairment and dementia (VCID), which covers the spectrum of cognitive impairment attributable to CVD, is therefore the second leading cause of dementia after Alzheimer's disease (AD) [2] . AD and CVD frequently co-occur in older people and have additive and possibly interactive effects [ 3 , 4 ]. Neuropathological features of CVD including white matter changes have also been shown to independently predict cognitive decline and dementia [5] . It is also recognised that VCID is amenable to prevention strategies since many of the vascular risk factors are eminently preventable [6] . Despite the promise of a preventable dementia that VCID offers, research into this disorder has lagged that into AD. There are several possible reasons for this discrepancy: the discourse around AD has captured the public's and funders’ imaginations such that AD has become synonymous with dementia; the focus in relation to CVD has been greatly on stroke and not the other vascular pathology contributing to cognitive impairment; VCID has a diverse set of underlying pathologies and mechanisms that lead to research fragmentation; and biomarkers for VCID have been slow to develop. The time for a reset appears to have arrived. A major scientific statement on VCID was released in 2011 [7] and a significant translational ‘Think Tank’ on VCID met in 2015 [8] , both examined the state of the science in this field. The National Institute of Health, USA, published a framework for advancing research in the cerebrovascular biology of cognitive decline in 2016 [9] . The World Health Organization recently published the Blueprint for Dementia Research [10] and identified VCID as an area requiring greater focus. A key recommendation from all these efforts was a greater need for large and collaborative effort. Researchers around the world appeared to have paid heed, and large number of national and international collaborations have emerged with a focus on VCID. In this paper, we survey some of the salient collaborations that are ongoing or have been recently completed, and examine their potential to contribute knowledge, develop interventions, provide data for sharing, and build capacity.

Method Collaborations included were identified by literature search (Pubmed, published 2015–2023), direct approach to principal investigators/key contacts, and chain-referrals from these contributors. Initiatives were included if they met the criteria of 1) focused on VCID, 2) collaborative either national or international and 3) ongoing or recently completed. While this list cannot be considered to be exhaustive, the authors believe it represents a substantive overview of international collaborative research into VCID. The list will require periodic updating. Information included in this paper was obtained from direct communication with key contacts, publications and/or consortia websites. See Fig. 1 for avenues to obtain further information.

Future recommendations and conclusion This paper presents an overview of recent significant collaborative initiatives in VCID. Although our understanding and appreciation of VCID has grown immensely from these and other efforts, there is clearly a need for increased research effort in this field. One area we have identified for improvement is consistency amongst terminology and protocols in this field. Although there have been harmonisation attempts such as STRIVE, FINESSE, HARNESS, VICCCS, and the ongoing VCD-CRE Delphi there are still preferences of terminology and protocols which complicate the interpretation and comparison of data across studies. This paper identified numerous studies which are focusing on biomarkers and pathology of cSVD. This may help to uncover the relationship between physiology and phenotype for both clinical manifestations of cSVD and cognitive decline. Future research should build on these findings to explore new diagnostic and therapeutic options. The inclusion of risk factors in several studies in this paper has helped to understand the contributions to cSVD development and progression, and to identify individuals at risk of developing VCID. An expansion of this would be the investigation of the impact of exposure to risk factors during different periods of life. Investigating the influence of early-, mid- or late-life risk exposure could inform diagnosis and management of VCID. While there are efforts to include diversity in VCID research, this paper also indicates the underrepresentation of participants and researchers from several backgrounds, particularly African and Asian countries, in these large-scale efforts. We hope that this survey will help galvanize further national and international collaborative initiatives to better address the significant global health burden that is VCID.

Highlights • This paper summarises 24 large-scale collaborations into vascular contributions to cognitive impairment and dementia (VCID). • Current research focuses on the mechanisms of action, means of prevention, and treatment of VCID. • There have been previous and are ongoing consensus efforts focused on harmonising approaches for management of VCID and standardising terminology. • Data sharing has become more common and accessible, using online data platforms such as Dementias Platform United Kingdom and Australia. • The globalisation of VCID research is working towards increased awareness and understanding through large-scale multi-disciplinary collaborative efforts, which will inform future research and hopefully improve the management of VCID worldwide. Cerebrovascular disease is the second most common cause of cognitive disorders, usually referred to as vascular contributions to cognitive impairment and dementia (VCID) and makes some contribution to about 70 % of all dementias. Despite its importance, research into VCID has lagged as compared to cognitive impairment due to Alzheimer's disease. There is an increasing appreciation that closing this gap requires large national and international collaborations. This paper highlights 24 notable large-scale national and international efforts to advance research into VCID (MarkVCID, DiverseVCID, DISCOVERY, COMPASS-ND, HBC, RHU SHIVA, UK DRI Vascular Theme, STROKOG, Meta VCI Map, ISGC, ENIGMA-Stroke Recovery, CHARGE, SVDs@target, BRIDGET, CADASIL Consortium, CADREA, AusCADASIL, DPUK, DPAU, STRIVE, HARNESS, FINESSE, VICCCS, VCD-CRE Delphi). These collaborations aim to investigate the effects on cognition from cerebrovascular disease or impaired cerebral blood flow, the mechanisms of action, means of prevention and avenues for treatment. Consensus groups have been developed to harmonise global approaches to VCID, standardise terminology and inform management and treatment, and data sharing is becoming the norm. VCID research is increasingly a global collaborative enterprise which bodes well for rapid advances in this field. Keywords

Collaborations to understand disease mechanisms and develop biomarkers for VCID National collaborations Biomarkers for Vascular Contributions to Cognitive Impairment and Dementia (MarkVCID) MarkVCID is a USA-based consortium that identifies and validates biomarkers involved in the pathophysiology underlying cerebral small vessel disease (cSVD)-related VCID. MarkVCID2 extends MarkVCID1 [11] , [12] , [13] , to establish biomarkers for incorporation into cSVD-VCID clinical trials for subject selection and study outcomes. MarkVCID2 will enrol 1800 participants to complete clinical validation studies, prioritizing individuals with cognitive complaints and/or early impairment. Biomarker kits which will undergo clinical validation include MRI- and plasma-based measures [14] , [15] , [16] , and combinations of MRI-and plasma-based measures. MarkVCID2 will categorise participants as progressed or non-progressed cSVD/VCID at the three-year follow-up visit and estimate sensitivity and specificity of baseline biomarker measures to identify future cSVD/VCID progression. The consortium will also analyse change in the candidate biomarkers for their validity as efficient outcome markers. Biomarker kits will be available for use in cSVD-VCID interventional trials to predict likelihood of worsening of the vascular component of VCID, and to streamline trials to test novel vasculoprotective treatments. Diverse Vascular Contributions to Cognitive Impairment and Dementia (DiverseVCID) The impact of vascular disease on dementia risk may be exacerbated in African/Black and Hispanics/Latino Americans, who are at greater risk for vascular disease [17] and for whom vascular disease may have greater impact in dementia [18] , [19] , [20] . The USA-based DiverseVCID project aims to recruit 2250 diverse at-risk older Americans with subjective cognitive complaints, to participate in a 6-year study involving cognitive assessment, blood analysis (DNA and biomarkers) and neuroimaging. The goals of this study are to: (1) identify the extent and characteristics of white matter injury that influence cognitive and health outcomes; (2) evaluate mechanisms of progression of white matter injury on cognition and health outcomes; and (3) build and validate a predictive risk model for patients with white matter lesions to improve precision medical management and planning, for clinical care and inclusion criteria for future therapeutic studies. Determinants of Incident Stroke Cognitive Outcomes and Vascular Effects on RecoverY (DISCOVERY) The USA DISCOVERY Network investigates mechanisms of susceptibility and resilience to post-stroke cognitive impairment (PSCI) and dementia to develop potential targets for personalized medicine and reduce post-stroke burden [21] . This prospective, multi-centre, observational collaboration is enrolling 8000 ischemic and haemorrhagic stroke patients without dementia during their acute hospital admission for two-year minimum follow-up. Participants will undergo serial cognitive evaluations and functional post-stroke assessments, while subsets of participants will additionally undergo research-based MRI, positron emission tomography scans, genetic/genomic and fluid biomarker testing. Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) The Canadian COMPASS-ND cohort study aims to discover and validate new risk factors and biomarkers of neurodegenerative disorder progression [22] . COMPASS-ND has enrolled 1772 individuals with memory concerns (153 VCID and 108 mixed dementia including VaD). Participants underwent comprehensive neurological and neuropsychological (follow-up at two years) assessment, and completed questionnaires on diet, lifestyle habits, social networks and caregiving, as well as objective vision and hearing assessment, research brain-MRI, and biospecimen collection (blood, urine, saliva, and stool). Plasma amyloid beta and phosphorylated tau testing is underway. A comprehensive online database of risk factors, clinical measures, blood analyte measures and MRI outcomes has been created for use by external researchers. An initial evaluation (200 subjects) found that covert cerebrovascular disease on neuroimaging was common in many of the cognitive disorders [23] . Heart Brain Connection (HBC) The Dutch HBC consortium was developed to explore the role of haemodynamic abnormalities along the heart-brain axis in VCID including the aetiology, assessment, and management of VCID with roots in clinical care [24] . HBC1 has been extended into HBC crossroads (HBCx) which is addressing additional haemodynamic factors, including blood pressure, cerebrovascular reactivity, valvular, rhythm, and endothelial abnormalities. Epidemiological, clinical, and autopsy studies have shown that haemodynamics and cardiovascular disease in VCID [25] , [26] , [27] need to be considered in the context of common comorbidities, in particular AD. HBCx have explored cerebral amyloid in patients with cardiovascular disease [28] , to inform the AMYCODE study. HBC is addressing cerebral haemodynamics and cognition in patients undergoing transcatheter aortic valve implantation [29] in the CAPITA study. In cSVD, HBC have supported evidence of blood pressure pattern variability; cardiac and aortic measures of hypertensive exposure on cardiovascular MRI also related to cognitive impairment [30] ; small vessel visualisation with 7T MRI; and coagulation blood-based biomarkers. In November 2022, the first Heart Brain Clinic formally opened at the Amsterdam University Medical Centre. RHU SHIVA The French RHU SHIVA consortium combines academic and clinical experts with industry partners to focus on VCID resulting from cSVD under three main themes: (1) diagnosis stratification; (2) molecular mechanisms; and (3) therapeutic implications. The consortium is organised into six non-discrete cSVD work packages including imaging biomarkers for diagnosis and characterization; multiomics biomarker signature; biological mechanisms and putative biotargets; personalised early risk prediction of cSVD complications; preventative management and ethical implications; and project management and dissemination. SHIVA, in conjunction with the CHARGE consortium, recently published the first genomic study on perivascular space burden, as a marker of cSVD, providing novel insight into the significance of perivascular space and potential for therapeutic avenues [31] . SHIVA also prioritises education, having hosted seven scientific mini symposia to-date. UK Dementia Research Institute (UK DRI) Vascular Theme The UK DRI involves 750 researchers and over 50 support staff to investigate dementia-related neuropathologies. The UK DRI Vascular Theme focuses on vascular contributions to dementia, e.g., mechanisms behind vascular and blood-brain barrier (BBB) dysfunction and the role of glial cells in vascular dysfunction. The Vascular Theme also prioritises education on vascular causes of neurodegeneration through meetings and workshops on research strategy, priorities, and approaches, and through the national early career researcher network, managed by UK DRI. The Vascular Theme searchable database includes 14 potential vascular models for dementia research, with input from DPUK and others, expected to be accessible in early 2024. Methods for monitoring early detection were piloted in the Rates, Risks and Routes to Reduce Vascular Dementia (R4VaD) study [32] . R4VaD also generated the ordinal cognitive assessment used in the LACunar Intervention Trial 2 (LACI-2 [33] ) to demonstrate benefits of repurposed vascular drugs in reducing VCI. Examples of Vascular Theme member publications, in collaboration with others include studies of cSVD [ 31 , 34 ] and dementia [35] , [36] , [37] . Table 1 indicates for each collaboration, the year of establishment, whether it is national (multi-site) or international, and website address, if applicable. International collaborations A significant challenge in research is obtaining large-enough cohort sizes to address the gaps in scientific knowledge. International consortia, supported by data-sharing platforms act as a means of amalgamating similar studies to pool datasets to enable powerful statistical analyses and meaningful output. These consortia often allow access for relevant researchers to obtain subsets of data upon justifiable request. They also promote a collaborative research community and facilitate capacity building in less resourced environments. The distribution of collaborations is visually represented in Fig. 2 . Stroke and Cognition Consortium (STROKOG) STROKOG is an international collaboration of post-stroke/ transient ischemic attack or high vascular risk studies with cognitive decline or impairment as an outcome. STROKOG was established to harmonise data [38] and to conduct joint analyses on VCID. STROKOG aims to identify risk and protective factors for VCID across geographical regions and ethnic groups, with the intent that STROKOG findings help guide and optimize preventative strategies and health policy internationally. STROKOG currently includes 38 study cohorts from 18 countries and 5 continents. STROKOG data have shown that 44 % of stroke survivors in hospital-based stroke cohorts had impairment in global cognition [39] ; stroke survivors experience faster cognitive decline than stroke-free controls from 1 to 3 years after onset [40] ; and diabetes but not prediabetes is associated with poorer cognitive performance in patients 3 to 6 months post-stroke [41] . From 2023, STROKOG will also include intervention studies that aim to reduce the impact of cerebrovascular disease. Meta VCI map The Meta VCI Map international consortium is a collaborative platform developed for meta-analyses on strategic lesion locations for VCID. The platform integrates neuroimaging data on vascular brain injury, in particular infarcts and white matter hyperintensities (WMH), and cognitive data from large multicentre population-based and cohort studies [42] . Meta VCI Map projects include infarct lesion symptom mapping, involving 13 cohorts, including over 3000 patients with ischemic stroke and cognitive testing within 15 months post-stroke. This led to the first comprehensive map of strategic infarct locations associated with risk of PSCI [43] ; sex differences in PSCI [44] ; WMH burden impact; and other multimodal prediction studies, also considering the role of disconnection [45] . Memory clinic studies of strategic WMH locations involving 11 cohorts (over 3500 patients) with MRI and cognitive testing have led to findings suggesting the WMH impact on cognition is location-dependent, primarily involving four strategic white matter tracts [46] , as well as projects considering WMH distributions and aetiology. Finally, population studies of strategic WMH locations involving 15 cohorts (14,876 individuals) with MRI and cognitive data are currently being analysed. International Stroke Genetics Consortium (ISGC) The ISGC was created by 16 investigators, with the aim of progressing stroke genetics research, through working groups, educational proceedings and supporting research. Currently, research supported by the ISGC focuses on the genetics, physiology, and outcomes of stroke including cognition and functioning. The ISGC hosts 6-monthly international workshops and has expanded to include over 200 stroke genetic researchers from approximately 40 countries (6 continents), with investigators and participants from diverse backgrounds. Projects developed and supported by the ISGC include MEGASTROKE, GIGASTROKE, GISCOME, GENISIS, and MRI-GENIE. The ISGC is structured into working groups such as the Cognitive Working group, established in 2019 with the aim of advancing understanding of the genetic underpinnings of PSCI and VCID. Key projects include Ibiostroke and CANVAS and will include data from DISCOVERY. Notable publications include the identification of shared genetic risk for ischaemic stroke and AD [47] , genome-wide association studies [ 48 , 49 ] and meta-analyses identifying genetic determinants of stroke risk to inform drug targets [50] . Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA)- Stroke Recovery The ENIGMA consortium brings together neuro-genetic researchers within 50 working groups including Stroke Recovery. ENIGMA-Stroke aims to improve understanding of post-stroke brain changes relative to functional outcomes and recovery [51] by: (1) creating a worldwide network of stroke neuroimaging centres focused on understanding neural mechanisms of stroke recovery; (2) computing and analysing metrics of brain shape, volume, wiring and function post-stroke; (3) identifying structural and functional differences in post-stroke brain outcomes and exploring the relation between these measures and functional outcomes and/or recovery and rehabilitation; and (4) developing collaborations and infrastructure for novel stroke brain-behaviour analyses. ENIGMA-Stroke have released open-source datasets where permissible by local ethics boards, such as a recently shared dataset of 1279 stroke MRIs with manually segmentation lesion masks [52] . Although initial work focused on post-stroke sensorimotor outcomes [53] , [54] , [55] , current research explores neural associations with post-stroke on cognition, mood, and language as well as the effects of therapeutic approaches, exercise and sleep on stroke outcomes. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium The international CHARGE consortium was formed to facilitate genome-wide association study meta-analyses and replication opportunities among multiple large and well-phenotyped longitudinal cohort studies [56] . CHARGE is responsible for 262 publications since its inception. CHARGE is structured around approximately 40 working groups. The neurology group (NeuroCHARGE) coordinates large consortia to investigate stroke, dementia including biomarkers, cognition function, and neuroimaging outcomes. SVDs@target The SVDs@target international collaboration, coordinated by Ludwig-Maximilians-University Munich, Germany, was established to identify mechanisms of SVD and validate these mechanisms through intervention, ultimately with the goal of reducing cSVD burden and preventing stroke and dementia. SVDs@target used animal models and human subjects to assess blood pressure variability and microvessels; BBB integrity and perivascular flow; microvascular matrisome and vascular integrity; inflammatory mechanisms and validated these findings through interventions in animal models and patient cohorts. Some key findings have included novel neuroimaging markers of cSVD using 7 Tesla MRI [57] , collocation of SVD brain lesions with high BBB leakage [58] , and implications of focal vessel-clusters in white matter identified using susceptibility-weighted imaging in cSVD [59] . BRain Imaging, cognition, Dementia and next generation GEnomics: a Transdisciplinary approach to search for risk and protective factors of neurodegenerative disease (BRIDGET) BRIDGET is an international collaborative effort, led by the University of Bordeaux, of research into neuroimaging, cognition and genomics of brain ageing. This was separated into two task forces in key domains: genomic and epigenomic analysis, and neuroimaging. These task forces operated three work packages: (1) identify genetic variants associated with structural makers of brain ageing; (2) explore lifetime determinants of brain ageing via longitudinal profiling of genomic, epigenomic and environmental markers; and (3) clinical and functional significance of genetic determinants for structural brain ageing, with a focus on cSVD. BRIDGET has now been completed; however, the data collected are still being analysed in conjunction with ongoing initiatives. Some key BRIDGET publications have identified loci for WMH volume in older adults [60] , suggested distinct causes for periventricular and deep WMH [61] , and indicated novel genetic variants in Alzheimer's disease which are involved in the immune response and transcriptional regulation [62] . Disease-specific collaborations There is growing interest in the most common monogenic form of cSVD, Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) [63] . The following emerging initiatives focus on CADASIL as a model for investigating VCID. CADASIL Consortium This North America-based CADASIL Consortium is recruiting a longitudinal cohort of 400 adult participants with CADASIL NOTCH3 mutations (family history and/or genetic testing) and 100 non-carrier controls. Clinical, neuroimaging, and molecular phenotyping, including AD biomarkers, will be acquired across twelve sites with established CADASIL clinics to characterize the biological and clinical course from the pre-symptomatic stage through dementia. The CADASIL consortium aims to replicate previous findings of specific NOTCH3 mutations which manifest more severe CADASIL [64] , and other findings, to help provide families with accurate prognostics. Additionally, the Consortium aims to provide standardization of CADASIL methods and measures for worldwide collaboration. Computerized assessments will be implemented to facilitate cross-site reliability for future large collaborative rare disease studies. All biofluids will be stored for current and future biomarker discovery and validation studies. Next-generation genomic analyses will be shared for ongoing advancement of VCID to better understand lifestyle and environmental contributions to outcomes in cerebrovascular diseases. CADASIL Registry in East Asia (CADREA) CADASIL is known to vary in its symptom profile and severity in relation to the specific NOTCH3 mutation present. Notably, some mutations, such as NOTCH3 p.R544C and p.R75P are seen only in East Asia. CADASIL with the p.R544C mutation (0.9 % in general population) usually does not cause migraine [65] and the p.R75P mutation (20 % of Japanese CADASIL) have been reported to not show white matter lesions in the temporal pole, considered a specific imaging finding in Western patients [66] . In Japan, a phase II study, the AMCAD (Adrenomedullin for CADASIL), has been conducted with 60 CADASIL patients and the results are currently being analysed, but moving to large-scale phase III poses challenges. The East Asian CADASIL cohort (CADREA) formed by researchers in Japan, Korea and Taiwan [67] will aid in appropriate diagnosis and prognosis of CADASIL and the development of future treatment options. This consortium aims to recruit 1000 individuals to accumulate longitudinal data on the genotype and phenotype (cognitive function, imaging findings) of CADASIL patients, which will form the basis for future pivotal studies. AusCADASIL To date there have been no large-scale Australian studies of CADASIL. The AusCADASIL collaboration was recently established to examine the clinical features and longitudinal course of CADASIL. This cohort will acquire clinical, neuroimaging, blood, and retinal phenotyping and extensive neuropsychological profiling to determine early markers and progression of CADASIL. This study also aims to determine the pathogenic variants in the NOTCH3 gene in Australian patients, and the influence of different spectra of NOTCH3 variants on the clinical phenotype of CADASIL. AusCADASIL utilises a multidisciplinary team with varied expertise to contextualise the findings within the Australian health system. The study will be completed across five centres in three states in Australia with an anticipated 150 NOTCH3 positive individuals (confirmed CADASIL, suspected CADASIL-either NOTCH3 positive or symptomatic) and equivalent NOTCH3 negative healthy controls without cognitive decline. This study also aims to serve as a resource for CADASIL research in Australia by providing educational materials for participants, carers, and family members. AusCADASIL will store fluid samples in the Centre for Healthy Brain Ageing Research BioBank for further future analysis. Data-sharing platforms To extend the benefit of research beyond the investigators involved in a study or a collaboration, sharing of data with external researchers is increasingly supported by funding bodies and the investigators themselves. Several platforms have been developed to facilitate this process and promote easy and equitable access, while protecting privacy. While none of these platforms is exclusively for VCID, two platforms that support VCID studies are listed. Data-driven collaborative efforts are listed in Table 2 . Dementias Platform United Kingdom (DPUK) DPUK is a data-driven platform [68] that convenes experts in academia, pharmaceutical industry, and charities to improve dementia detection, treatment and prevention by providing access to findings, technology, and volunteers [ 69 , 70 ]. DPUK prioritises collaboration, with strong links to its Australian counterpart- DPAU -, as well as the Korean Dementia Research Centre and the Alzheimer's Disease Data Initiative (ADDI). To date there have been 1500 outputs from DPUK activities including: 26 academic, industry and third sector partners with over 1000 cohort access requests resulting in 250 research publications including over 50 cohort studies and research data for 3.5 m people. DPUK continues to accelerate progress in research on all types of dementia, including VCID, and support the translation of basic science into practice through three main pathways: repository of dementia-optimised cohort data (DPUK Data Portal), engine for matching public volunteers to the most appropriate new research studies (the Trials Delivery Framework), and programme of cutting-edge experimental medicine (the Experimental Medicine Incubator). Recently, DPUK in conjunction with the UK DRI and the British Heart Foundation, addressed the shortfalls of understanding of VCID being largely driven by limited VCID models and studies, and outlined recommendations for improving future research [71] . Dementias Platform Australia (DPAU) DPAU is a data sharing platform led by the University of New South Wales Centre for Healthy Brain Ageing (CHeBA), established with Monash Secure eResearch Platform and DPUK. DPAU hosts data from international longitudinal and cross-sectional studies of brain ageing and enables researchers to explore and identify relevant studies, apply for data access, and analyse data in a secure, remote environment. DPAU enhances data discovery functionality, provides high-quality data curation, mediates data access via an auditable process adaptable for compliance with relevant governance requirements, provides secure data transfer, reduces the need for continued data transfer between research groups, and provides virtual data analysis workspaces. Currently, DPAU is onboarding the 44 COSMIC consortia cohort-studies [72] from 33 countries, and hopes to expand to include more studies, such as those in STROKOG [38] and other ageing studies. DPAU applies a standard data ontology to DPAU studies, with the aim to enable platform interoperability with other data initiatives including DPUK and the ADDI. DPAU aims to expand to include imaging and genetics data in addition to current data. Table 2 . Data and analysis status, and processes for data access by external researchers. Current data collection includes direct from participants, increasing availability of online data, or onboarding more member studies, as appropriate. Development of international consensus criteria and guidelines International collaboration requires the standardisation of terminology, criteria and procedures so that exchange of ideas and materials can be facilitated. A number of consensus-building and harmonisation efforts have taken place in relation to VCID. Some examples are given below. STandards for ReportIng Vascular changes on nEuroimaging (STRIVE) The STRIVE initiative [73] aimed to address the issue of variable terminology in cSVD neuroimaging. The STRIVE working group consists of experts in cSVD research, particularly but not limited to neuroimaging, from around the world. STRIVE aims to clarify definitions of cSVD features on neuroimaging and to promote consistent and unbiased use of agreed-upon consensus terminology. STRIVE also provides recommendations for image acquisition and analysis. The STRIVE initiative was extended into STRIVE-2 [74] to reflect on the original terminology and update it where necessary, focusing on new information that has emerged since STRIVE-1. Of note, STRIVE-2 added quantitative imaging of brain structure and vascular function. The current manuscript also highlights unresolved issues that require further research and provides guidance for the evaluation of emerging cSVD markers and methods. HARmoNizing brain imaging mEthodS for vaScular contributions to neurodegeneration (HARNESS) The HARNESS initiative [75] was established to create a framework for developing neuroimaging biomarkers of cSVD, reviewing the status of emerging neuroimaging biomarkers of cSVD, and developing and implementing standardized acquisition protocols. The 70 members of this multidisciplinary group from 29 institutions in 12 countries have participated in 11 working groups and an in-person meeting. A framework for validation was developed, followed by technical validation, biological validation and finally qualification of real-world feasibility and cost effectiveness. The validity of existing biomarkers was reviewed, with the best current evidence for lacunes, infarcts, WMH, cerebral microbleeds, atrophy, and diffusion tensor imaging being documented [ 76 , 77 ]. The HARNESS website disseminates standardised MRI acquisition protocols, and downloadable software packages for analyzing cSVD lesions, case report forms, and scales. The website will be periodically updated with new lesion types, acquisition parameters, and software packages. Creating a central image repository was explored but was not considered feasible due to costs involved in obtaining institutional review board approvals, legal agreements between institutions, and hosting the database. Framework for Clinical Trials in Cerebral Small Vessel Disease (FINESSE) FINESSE [78] was developed to address concerns regarding trial methodology in cSVD under the auspices of the International VASCOG Society. Experts in cSVD trials were designated a particular work package: study populations, inclusion and exclusion criteria; clinical end points; cognitive testing; imaging markers; fluid biomarkers; or novel trial designs including Mendelian randomization. These working groups reviewed, discussed, and considered the literature to produce recommendations which then met whole-group consensus via a Delphi approach. The results of FINESSE included recommendations for cSVD trial design, and perspectives regarding effectiveness of currently available cardiovascular interventions in cSVD as compared to other strokes. Vascular Impairment of Cognition Classification Consensus Study (VICCCS) VICCCS-1 [79] Delphi compiled responses from international VCID researchers regarding the merits and limitations of over 10 publications that proposed VCID subtype approaches and nomenclature. A 67 % agreement threshold from 98 to 153 respondents (from 27 countries) over the survey rounds resulted in redefining classification of mild and major VCID and subtypes, and identified priorities for future research. VICCCS-2 [80] Delphi evaluated VCID diagnostic assessment utility for use in clinical settings. VICCCS-2 compiled responses from 65 to 79 respondents over 6 successive survey rounds, culminating in endorsement for the standardized research use of the National Institute of Neurological Disorders-Canadian Stroke Network (NINDS-CSN) recommendations for neuropsychological and imaging assessments for VCID diagnosis. VICCCS-2 also revised diagnoses of mild and major forms of VCID based on research advances and DSM-V updated guidelines. Vascular Contributions to Dementia- Centre of Research Excellence (VCD-CRE) Delphi The VCD-CRE Delphi study aims to update the earlier criteria for the diagnosis of vascular cognitive disorders (i.e., VASCOG; [81] ), which have been well-validated against other diagnostic criteria [82] and have served as a standard to determine the prevalence of PSCI [83] . This update (VASCOG-2) will improve criteria usability, harmonisation, and VCID diagnostic sensitivity in accordance with research advancements. A parallel Delphi aims to develop a harmonised neuropsychological test battery for cognitive changes associated with vascular cognitive disorders by consolidating the NINDS-CSN Vascular Cognitive Impairment Harmonization Standards [84] , with other harmonisation efforts [85] and introducing flexible assessment modes. The Delphi surveys will be completed by clinicians, researchers, or clinician-researchers with experience in the assessment of cognitive decline, specifically vascular cognitive disorders. Each Delphi involves three rounds of online surveys and expert meetings. Data collection is expected to be completed by December 2023. The goal is that VASCOG-2 and the harmonised neuropsychological assessment battery become the standards for future VCID diagnosis and assessment. This initiative is under the aegis of the International VASCOG Society. CRediT authorship contribution statement Danit G Saks: Writing – review & editing, Writing – original draft, Project administration, Methodology, Formal analysis, Data curation, Conceptualization. Eric E Smith: Writing – review & editing, Writing – original draft, Methodology, Data curation, Conceptualization. Perminder S Sachdev: Writing – review & editing, Writing – original draft, Supervision, Methodology, Funding acquisition, Formal analysis, Data curation, Conceptualization. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary materials Acknowledgments The following individuals kindly provided information on the initiatives they lead or are a part of: Sarah Bauermeister, Adam Bentvelzen, Geert Jan Biessels, Amy Brodtmann, Rory Chen, Mat J Daemen, Charles DeCarli, Marco Duering, Israel Fernandez Cadenas, Myriam Fornage, John Gallacher, Michael D Geschwind, Steven M Greenberg, Masafumi Ihara, Patrick Kehoe, Sook-Lei Liew, Jessica W Lo, Axel Montagne, Jane S Paulsen, Sarmi Sri, Herpreet Singh, Paul Thompson, Joanna M Wardlaw, Bradford Worrall. More information is included in the Supplement.

CC BY

no

2024-01-16 23:42:01

Cereb Circ Cogn Behav. 2023 Dec 14; 6:100195

oa_package/fd/73/PMC10788430.tar.gz

PMC10788433

38226267

Introduction 770 million infections and 6.96 million deaths worldwide were caused by the SARS-CoV-2 pandemic between December 2019 and the end of September 2023 [ 1 ]. Comprehensive measures were established in most parts of the world to contain the contagions, with often far-reaching restrictions on social life, as well as university and work settings. Both the health care system as a whole and the medical education of students and young physicians have also been challenged by university closures, widespread conversion to online teaching formats, changing working conditions, and increased risk of SARS-CoV-2 exposure in the work environment [ 2 , 3 ]. Fear of one's own potential infection or transmitting COVID-19 to relatives and varying availability of protective equipment at work or study sites, as well as changing personal and professional circumstances, are potential stressors and place prospective and practicing physicians in a vulnerable position [ 4 ]. The impact of SARS-CoV-2 infection on physical health has been the focus of several studies, with concurrent consideration of potential consequences for psychological well-being. A scoping review of 34 studies revealed a range of symptoms including fatigue, arthralgia, pain, and reduced physical capacity, as well as depression, and anxiety after COVID-19 in the general population. Here, the women surveyed showed higher scores concerning anxiety and depression [ 5 ]. Prior to the COVID-19 pandemic, doctors were already a highly mentally burdened group. Before the outbreak of the COVID-19 pandemic, the aggregated prevalence of depression or depressed symptoms among doctors was 28.8% [ 6 ] compared to 9.2% in the general population [ 7 ] with considerable in-between-study variability, which is potentially due to variations in survey techniques and questionnaires. Female physicians appear to be at a greater risk for suicide when compared to the general female population [ 8 ]. Various meta-analyses of studies conducted during the pandemic on the prevalence of mental distress among healthcare workers (HCW) yielded pooled prevalence scores for anxiety of 25.8% among physicians [ 9 ] and 23.2% among HCW [ 10 ], and pooled prevalence scores for depression of 20.5% in physicians [ 9 ], and 22.8% [ 10 ], or 24% in HCW [ 11 ]. Another review described high prevalence rates of anxiety and depression among surveyed HCW, with several studies showing that women had more symptoms of anxiety as well as higher severity for depressive symptoms [ 12 ]. German medical students showed significant increases in depressive symptoms and loneliness during the COVID-19 pandemic [ 13 ], as well as greater study-related worries early on [ 14 ]. Risk factors for higher stress levels and a decreased well-being were female gender [ [15] , [16] , [17] ], a subjectively lower social status [ 16 ], and a younger age [ 18 ]. Also among HCW, in addition to female gender and inadequate protection against COVID-19 infection, younger age is a risk factor for anxiety and depression [ 12 , 19 ]. Therefore, young female physicians in their first years of practice and female medical students are expected to be particularly vulnerable. It is therefore to be feared that the two and a half years of daily study and work under the changed conditions and potential burdens may have adverse effects on the mental health of medical students and physicians, particularly for women in their early years of practicing medicine. To assess how the COVID-19 pandemic differed in affecting the mental health of women and men, this anonymous online survey asked both medical students and young physicians of different specialties about their life quality during the COVID-19 pandemic, in order to identify potential risk groups and stressors and to evaluate the need for support and prevention measures at the faculties and workplaces.

Material and methods Study population The information was obtained by administering a confidential online questionnaire to participants at the Mannheim Medical Faculty of the University of Heidelberg and the Wuerzburg Medical Faculty during the period of December 01, 2021, to March 31, 2022. Medical studies in Germany are carried out in six-year terms and consist of preclinical and clinical phases, which culminate in a practical year. In this study, all medical students as well as young physicians already in practice for up to 10 years after completing medical studies were eligible to participate in the survey. This enabled participants up to 45 years of age to take part in the study. Participants were recruited through the student deans' offices and student councils at the respective universities, as well as calls for participants from the various hospitals and secretariats of the different specialties via email and public relations. All survey participants provided informed consent prior to their participation. The survey was conducted utilizing SoSci.surveys software (version 3.2.40-im SoSci Survey GmbH, Munich, Germany). The study received approval from the Ethics Committee II of the Mannheim Medical Faculty at the University of Heidelberg (file number: 2021-645), as well as the Ethics Committee of the University of Wuerzburg (file number 2021-120901). Additionally, the study was registered with the German Registry for Clinical Studies (DRKS-ID: DRKS00028984). For the subject to be examined, the data of both students and physicians were taken into account, resulting in an analysis of the entire data set (N = 668). For further research, respondents were also divided into subgroups by sex, women (N = 484) and men (N = 184). Due to a small subsample (N = 3) compared to the other sexes, individuals with diverse gender were excluded in this analysis. Survey procedure A total of 668 participants were included in the survey. The survey consisted of validated questionnaires and self-generated queries. Participants were asked socio-demographic questions regarding their age, gender, family income, and family status. Moreover, they provided feedback on the availability of protective equipment at their workplace or university (rated on a 5-point scale ranging from “not at all sufficient” to “completely sufficient”), as well as their perceived level of threat in regard to the COVID-19 pandemic on individual, national, and global levels (rated as “low,” “medium,” or “high”). Additionally, participants reported their levels of anxiety and burden caused by the pandemic, as well as the impact on their family, social, and professional lives (rated as “positive,” “negative,” or “neutral”). Participants retrospectively assessed their subjective anxiety, burden, and impairment during seven distinct time periods throughout the pandemic from spring 2020 to fall 2021. They utilized categorical questions with either 3 or 5 level choices. Furthermore, they were asked about any pre-existing psychiatric condition with the options of “yes” or “no”. The study assessed changes in anxiety and depression symptoms using the well-validated German version of the Hospital Anxiety and Depression Scale (HADS) [ 20 ], along with the WHO Quality of Life BREF (WHOQOL BREF) [ 21 ]. Current quality of life was evaluated with reliability values ranging between α = 0.57 and α = 0.88. Statistical analysis IBM SPSS version 27 (IBM Corporation, Armonk, NY, USA) [ 22 ] was utilized for statistical calculations, employing a 2-sided significance level of α = 0.05 for all tests. Frequency distributions were presented as absolute case numbers and percentage frequencies for the entire sample and two subgroups (women vs. men). The non-parametric Friedman test determined variations in personally perceived anxiety and burden from spring 2020 to fall 2021. The total and subsample scores of HADS-A/D before (bo) and after (ao) pandemic onset were analyzed through paired-sample T-tests. For testing significant differences, independent samples t-tests were used to compare life quality mean scores (WHOQOL BREF) between women and men. To assess the impact of variables such as age, pre-pandemic mental illness, protective equipment availability, mean anxiety, mean burden, and changes in HADS sum score on the quality of life of both students and physicians, a multifactorial ANOVA was performed. Additionally, we conducted further multifactorial ANOVA analyses to determine the variables that affect participants' quality of life across the five domains of the WHO QOL BREF. Specifically, we performed separate ANOVAs for male and female subgroups.

Results Sample description Complete data from 668 students and physicians were included in the analysis. The sample primarily consisted of females (n = 484, 72.5%) with ages ranging from 18 to 42 years. Table 1 presents a summary of sociodemographic data and COVID-19 specific inquiries for the whole study population and gender subgroups. Subjectively perceived anxiety Between the seven measurement times, differences in the subjects’ subjectively perceived anxiety for the entire sample (Friedman test: Chi 2 (6) = 827.31, p < 0.001 , n = 668) as well as the subsamples of women (Chi 2 (6) = 633.06, p < 0.001 , n = 484) and men (Chi 2 (6) = 198.87, p < 0.001 , n = 184) (see Fig. 1 ) were detected. Overlapping with the COVID-19 incidence pattern, anxiety scores showed a wave-like pattern, increasing in the fall, winter, and spring and decreasing in the summer. For a comprehensive analysis, please refer to the online supplement, which includes a complete table of post-hoc Dunn-Bonferroni tests comparing each measurement time point. Subjectively perceived burden A wave-like pattern in subjective perception of burden was observed. The Friedman test demonstrated a significant difference between all seven time points of measurement, including the sample as a whole (Chi2(6) = 565.11, p < 0.001, n = 668), as well as the subsamples of women (Chi2(6) = 446.78, p < 0.001, n = 484) and men (Chi2(6) = 124.35, p < 0.001, n = 184) (see Fig. 2 ). Depression score progression over time Mean scores for depression and anxiety on the HADS scale significantly increased in the total sample comparing scores before (bo: M = 7.66, SD = 5.29) to after (ao: M = 16.36, SD = 8.21) the onset of the COVID pandemic (t(667) = −32.29, p.001). A subscale analysis of the HADS scale showed a significant increase from before (bo: M = 2.25, SD = 2.73) to after (ao: M = 5.41, SD = 4.31) the onset of the pandemic for the depression subscale (HADS-D) (t(667) = −32.18, p.001) as well as for the anxiety subscale (HADS-A) from before (bo: M = 5.41, SD = 3.22) to after (ao: M = 9.36, SD = 4.60) the onset of the pandemic (t(667) = −27.74, p < 0.001). It is noteworthy that only 8.8% of all participants met the cut-off of 15 for a clinically significant value prior to the onset of the pandemic, while 49.1% met the cut-off after the onset. The depression and anxiety subscales showed a similar pattern with a cut-off of 8 for a clinically evident value (depression: before onset - 4.2% ≥ 8, after onset - 31.1% ≥ 8; anxiety: before onset - 15.7% ≥ 8, after onset - 54.2% ≥ 8, refer to Fig. 3 for details). Difference in change in depression scores according to gender Male participants displayed a comparatively smaller escalation in their depression scores after the pandemic outbreak in contrast to the female participants. This divergence was statistically significant for the HADS full scale (m: M = 7.48, SD = 7.29; w: M = 9.17, SD = 6.79, t(666) = 2.802, p = 0.005), along with its anxiety (m: M = 3.41, SD = 3.86; w: M = 4.15, SD = 3.56, t(666) = 2.312, p = 0.021) and depression (m: M = 4.07, SD = 3.97; w: M = 5.02, SD = 3.73, t(666) = 2.880, p = 0.004) subscales (refer to Fig. 4 ). Effects of the pandemic on quality of life Table 2 shows the participants' subjective assessment of quality of life across different dimensions of the WHOQOL BREF, including the total sample, men and women two years after the pandemic onset. In the domain social relationships, female participants scored significantly higher than male participants (t(666) = 2.471, p = 0.014, |d| = 0.214). Conversely, in the psychological quality of life domain, male participants scores significantly higher than female participants (t(666) = −2.695, p = 0.007, |d| = 0.233). Among the subsamples for overall quality of life (t(302.44) = −0.834, p = 0.405), physical quality of life (t(666) = −1.373, p = 0.170), and environmental quality of life (t(666) = 0.372, p = 0.710) there was no significant difference. Factors influencing quality of life during the pandemic The presence of a prior mental illness (F(1,658) = 18.184, p < 0.001, ηp2 = 0.027), differences in depression scores before and after the onset of the pandemic (F(1,658) = 109. 825, p < 0.001, ηp2 = 0.143), the mean burden (F(1,658) = 8.693, p = 0.003, ηp2 = 0.013), and the presence of infection protection equipment (F(1,658) = 4.048, p = 0.045, ηp2 = 0.006) significantly impacted the global quality of life. Lower life quality scores were found to have a correlation with a history of mental illness (B = −9.993, t(666) = −4.264, p < 0.001), as well as higher burden scores (B = −4.602, t(666) = −2.948, p = 0.003) and greater differences in depression scores (B = −1.258, t(666) = −10.480, p < 0.001). Additionally, less adequate protection equipment against infection was linked to worsened quality of life (B = 1.622, t(666) = 2.012, p < 0.045). Sex ( p = 0 . 267), age ( p = 0 . 668), working with COVID-19 patients vs. not dealing with them ( p = 0 . 505), and mean anxiety ( p = 0 . 251) did not significantly correlate with overall quality of life. Factors influencing the WHO QOL BREF domains by sex during the pandemic In order to determine the individual factors influencing the different domains of quality of life of the WHO QOL BREF for the two subgroups women vs. men, multi-factorial ANOVAS were calculated separately for the sexes and the domains ( Table 3 ). Differences in the frequency of the influencing factors, as well as different distributions in the different domains between the two sexes were revealed. This was also evident in the two domains of the WHOQOL BREF showing a significant difference in the quality of life between the women and men surveyed (psychological and social relationships). The multifactorial ANOVA for the psychological domain showed that for both women and men, the presence of a prior mental illness (w: F(1,476) = 38.732, p < 0 . 001, ηp 2 = 0.075; m: F(1,175) = 4.529, p = 0 . 035, ηp 2 = 0.025), mean burden (w: F(1,476) = 4.239 , p = 0 . 040, ηp 2 = 0.009; m: F(1,175) = 5.796, p = 0 . 017, ηp 2 = 0.032) and the difference in depression scores before and after the onset of the pandemic (w: F(1,476) = 109.968, p < 0 . 001, ηp 2 = 0.188; m: F(1,175) = 29.278, p < 0 . 001, ηp 2 = 0.143) were relevant factors for the quality of life. In addition, for women, higher anxiety scores (F(1,476) = 4,133, p = 0 . 043, ηp 2 = 0.009; B = −3.805, t (483) = -2.033, p = 0 . 043) and lower age (F(1,476) = 5,265, p = 0 . 022, ηp 2 = 0.011; B = 0.377, t (483) = 2.295, p = 0 . 022) resulted in lower psychological quality of life scores. In contrast, the men's analysis of variance revealed that the presence of infection protection equipment (F(1,175) = 4.668, p = 0.032 , ηp 2 = 0.026) significantly affected men's psychological quality of life, with infection protection equipment rated as insufficient (B = 3.280, t(182) = 2.160, p = 0.032), resulting in lower values. Regarding social relationships, a previous psychiatric disease (w: F(1,476) = 18.130, p < 0.001, ηp2 = 0.037; m: F(1,175) = 6.062, p = 0.015, ηp2 = 0.033) and the difference in depression scores before and after the pandemic (w: F(1,476) = 44.079, p < 0.001, ηp2 = 0.085; m: F(1,175) = 12.586, p < 0.001, ηp2 = 0.067) in both subgroups significantly reduced quality of life. In addition, for women, infection protection equipment subjectively rated as less adequate (F(1,476) = 4,675, p = 0 . 031, ηp 2 = 0.010; B = 2.211, t (483) = 2.162, p = 0 . 031) led to lower social quality of life scores. Among men, lower age (F(1,175) = 7,129, p = 0.008, ηp 2 = 0.0.39; B = 0.788, t (182) = 2.670, p = 0 . 008) was associated with lower social quality of life scores.

Discussion The evolution of the HADS over the course of the pandemic shows different dynamics according to sex. It is known, that there was a pre-existing “sex gap” in depression and anxiety symptoms already prior to the outbreak of the pandemic, though this is surely not the only explanation for the sex differences assessed in our study [ 24 ]. A complicating factor may be that female study participants reported lower average perceived COVID-19 protective equipment than male study participants, which may result in additional stress. In addition, women have a lower psychological quality of life as measured by the WHO QOL-BREF. In studies of the general population, other factors that negatively influenced anxiety and depression in women during the COVID-19 pandemic were higher stress levels and more worries about the virus, both health-related and financial. In addition, women were more likely to worry about possible COVID-19 infection in family members or loved ones [ 25 ]. The significantly higher QOL domain social relationships scores among female participants fits with previous findings that women tend to have social networks with fewer but stronger ties [ 26 ]. Overlapping with the German COVID-19 incidences, our survey revealed periodic fluctuations in self-reported anxiety and personal burden, with higher levels of both during the colder seasons, particularly among women. The increase of values in the measurement time point “spring 2020” has also been observed in other publications among HCW [ 10 , 27 ] and coincides with the generally increased subjectively perceived anxiety and stress caused by COVID-19 in the German general population [ 28 ]. It should be noted that for the measurement time point “spring 2021,” i.e., a good year after the outbreak of the pandemic, a decrease in perceived anxiety compared with the previous measurement time point “winter 2020” can be observed, although the COVID-19 incidence in spring reaches similar peak values as in winter 2020 [ 23 ]. This can partly be explained by the approval of three vaccines for COVID-19 in December/January 2021 by the European Medicines Agency. In the spring of 2021, a large proportion of medical staff, including residents and young doctors, had the opportunity to be vaccinated against COVID-19, which could have led to a reduction in anxiety. In general, we found a significant increase in depression and anxiety scores after the pandemic outbreak. According to the results of the HADS items, about half of the subjects showed a clinically conspicuous depression score in the course of the pandemic. This contrasts with previous international reviews in which just over 20% of subjects had clinically salient depression scores [ 10 , 29 ], as well as studies in the German general population in which only 23% of women and 21% of men had clinically salient HADS scores [ 30 ]. Here, the different origin of the data is probably of significance. For example, the primary studies were mainly conducted in Asia or outside Europe. Finally, it is important to consider the age structure of this survey, which, with an average age of 24.4 years, is significantly younger than the age structure in the German population [ 31 ]. Psychological distress from the COVID-19 pandemic was empirically shown to be greater in younger individuals [ 28 ]. This is in accordance with our here presented study data. In our study, predictors of lower quality of life were pre-existing mental illness, higher difference in depression scores, higher burden scores, and inadequate COVID-19 protective equipment. Here, the presence of infection protection equipment is consistent with findings from others, as in both the past MERS and SARS epidemics and the COVID-19 pandemic, direct work with affected patients and the circumstances of that work are relevant to susceptibility to depressive and anxiety symptoms [ 32 ]. Looking at the factors influencing quality of life in each WHOQOL BREF domain in a sex comparison, it seems striking that the presence of a previous mental illness tends to be a risk factor on quality of life more often in women than in the men (w: 4/5 domains, m: 2/5). Furthermore, mean anxiety did not prove to be a significant influencing factor in any of the domains for the male respondents, whereas it had a significant main effect on quality of life in three of the five domains for the female respondents. The reason for this can only be speculated. It may be that women experience more anxiety than men, regardless of the pandemic [ 33 ]. Furthermore, the gender care gap could have an impact on this. For example, women in Germany perform on average 52% [ 34 ] more care work, such as child rearing, nursing or housework, than men. The largest gap, with a difference of more than 2 h of daily work, can be observed in age groups in their early and mid-30s, which made up a notable proportion of the participants in this study. Evidence suggests that this preexisting disparity was exacerbated by the Covid 19 pandemic. For example, women were more likely to have to forego employment to provide care work than men [ 35 ]. Measures that explicitly focus on the situation of working women, such as more flexibility in their employment could provide significant assistance to a vulnerable group and help to decrease extra-professional duties. The study has several limitations. The most important confounding factor is the retrospective nature of the survey. There is no guarantee that participants can accurately recall how they felt at seven earlier points in time. In addition, the survey was conducted over a period of several months, so the circumstances under which the survey was completed could vary among study participants. In particular, the omicron variant of SARS-CoV-2, which became widespread in late 2021, may have influenced study participants’ perceptions and therefore a bias can be supposed. Furthermore, the survey was only conducted at two medical faculties. Therefore, data cannot be extrapolated to all young medical students and physicians in Germany and elsewhere, as there were significant differences in COVID-19 incidence and preventive measures in different German states and medical schools. Another limitation of this study is the analysis of data from only two genders, male and female, owing to a small number of individuals with diverse gender (N = 3) and the statistical exclusion of these individuals. Future research should include all genders if sufficient case numbers can ensure statistical accuracy. In our study, we found that the female sex was overrepresented (72.5%) compared to the gender distribution of all medical students in Germany (65.13% female; 34.87% male; [ 36 ]) and practicing physicians (49.9% women among all physicians and psychotherapists in 2021) [ 37 ]. In summary, the survey data revealed an enormous pattern of stress among trainees and young medical staff due to and during the COVID-19 pandemic. Furthermore, clear differences, which probably go beyond the pre-existing “sex gap”, were observed between the female and male study participants. Therefore, the COVID-19 pandemic not only perpetuated the sex gap between men and women in terms of depression and anxiety symptoms, but also seemed to exacerbate it. In addition, our data confirmed that medical personnel are more psychologically stressed than the general population. Based on our data, support and prevention measures seem to be important, especially for vulnerable groups such as young medical students and physicians with a special focus on women.

Shared first authorship. Background Healthcare workers and medical students faced new challenges during the COVID-19 pandemic. Processes within many hospitals were completely disrupted. In addition, the face to face teaching of medical students was drastically reduced. Those at risk of developing mental health problems appear to be younger health care workers and women. Objective To investigate potential COVID-19 pandemic-related gender differences in psychological distress among medical students and physicians in their first years of practice. Design and setting An anonymous survey was carried out online between December 1, 2021, and March 31, 2022, at the Mannheim Medical Faculty and the Würzburg Medical Faculty, Germany, after obtaining informed consent. Primary outcome measures were changes in anxiety and depression symptoms using the Hospital Anxiety and Depression Scale (HADS), and changes in participants' current quality of life using the WHO Quality of Life BREF. Results The results show wave-like courses for perceived anxiety and burden overlapping with the course of the COVID-19 incidence. In comparison to men, women showed a significant higher increase in HADS ( p = 0.005 ) and a reduced life quality ( p = 0.007 ) after COVID-19. Both sexes showed different frequencies of the factors influencing quality of life, with the presence of a previous mental illness and mean anxiety having a significant higher negative impact in women. Conclusion Future and young female physicians reported a disproportionate higher burden during COVID-19 compared to their male colleges. These observations suggest an increased need for support and prevention efforts especially in this vulnerable population. Keywords

Data availability statement The raw data supporting the conclusions of this article will be made available by the authors on request. CRediT authorship contribution statement Marie Halfmann: Writing – original draft, Visualization, Investigation, Formal analysis, Data curation. Noah Castioni: Writing – original draft, Validation, Formal analysis, Data curation. Lea Wetzel: Writing – review & editing, Software, Methodology, Formal analysis, Data curation, Conceptualization. Anne Koopmann: Writing – review & editing, Supervision, Investigation, Conceptualization. Sarah König: Validation, Supervision, Resources, Formal analysis. Astrid Schmieder: Writing – review & editing, Validation, Supervision, Project administration, Funding acquisition, Formal analysis, Data curation, Conceptualization. Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Astrid Schmieder reports administrative support, article publishing charges, and equipment, drugs, or supplies were provided by Clinic for Dermatology, Venereology and Allergology, University Hospital Wuerzburg, Germany. Astrid Schmieder reports a relationship with Clinic for Dermatology, Venereology and Allergology, University Hospital Wuerzburg, Germany that includes: employment.

Supplementary data The following are the Supplementary data to this article:

CC BY

no

2024-01-16 23:42:01

Heliyon. 2023 Dec 19; 10(1):e23727

oa_package/fa/97/PMC10788433.tar.gz

PMC10788434

38226289

Introduction Corona Virus Disease (Covid-19) has spread throughout the world rapidly starting from the end of December 2019. It has infected millions of people around the world and can cause death. Therefore, this problem is designated as a global pandemic by World Health Organization [ [1] , [2] , [3] , [4] , [5] ]. Such problematic condition is included in the category of non-natural disasters with the category of disease outbreaks. Therefore, knowledge of disaster management is needed to reduce the possibly hazardous impact of the disaster by immediately reacting during and after the disaster along with taking steps to recover from it [ 6 ]. Knowledge of disaster management plays an important role by ensuring the availability and access to disaster so that more accurate and reliable information is available. Disaster management is an essential knowledge given to the community [ 7 ]. Therefore, it is important to embrace knowledge, access, use, and distribution of decision quality as a form of disaster response [ 8 ]. The involvement of various sectors through public coordination is important to reduce risks after disasters [ 9 ]. This includes the roles and responsibilities of national and local governments in collaboration with relevant stakeholders including public and private sectors [ 10 ]. In fact, disaster management is multi-sectorial, multi-stakeholder, and multi-hazard, so that the key to success is good coordination and command [ 11 ]. However, sometimes coordination has complex problems and is not easy to solve individually. Consequently, partnerships and collaborations must be taken into account in conducting disaster management [ 12 ]. Good disaster management is not only in emergency phase but also before and after disaster occurred [ 13 ]. Since 2007, Indonesia has implemented a law to regulate disaster management covering disaster preparedness, early warning, and disaster mitigation [ 14 ]. Disaster preparedness is undertaken to minimize the adverse effects of hazards through effective prevention, rehabilitation, and recovery measures to ensure timely and effective arrangement and delivery of aid and assistance after a disaster [ 15 ]. In a sociological perspective, disaster is often understood based on people's perceptions and are closely related to emotional experiences when their survival is threatened. Therefore, it is categorized as part of socio-cultural context of community experiencing threats [ 16 ]. On March 15, 2021, additional cases were still increasing amounted of 120,399,298 confirmed positive cases, 2,664,622 deaths, and 96,944,566 recovered cases. The United States still became the country with the highest number of cases in the world, with 30,080,223 confirmed cases, 547,191 deaths, and 22,168,542 recovered cases [ 17 ]. Table 1 portrays 10 countries with the highest number of Covid-19 infection cases as of March 15, 2021. In regard to Table 1 , public health control measures to limit the global spread of the virus must be implemented [ 18 ]. It is important to limit human-to-human transmission in order to reduce secondary infections among nearby people and medical personnel and to prevent stronger transmission and international spread [ 19 ]. Based on the previous management of MERS and SARS, WHO recommends reducing the risk of transmission of acute respiratory infections by avoiding close contact with people suffering from acute respiratory infections, washing hands frequently after direct contact with infected people or environment, and avoiding direct contact with livestock and wild animal. In addition, patients with symptoms of acute respiratory infections must have cough etiquette by maintaining distance, coughing and sneezing using a tissue or cloth, and benefitting health facilities (i.e. hospital [ 20 ]. Experience from the early phase of SARS-Cov-2 pneumonia greatly highlights the early detection and isolation of SARS-Cov-2 pneumonia cases [ 21 ]. These steps are taken in an effort to identify cases and contacts occurring in the United States as appropriate assessment and treatment of travelers arriving from China mainland to America [ 22 ]. Various policies have been implemented by the affected countries such as the implementation of Lockdown, limiting public transportation, canceling social activities, staying at home and maintaining distance, delaying school activities, using delivery services, and implementing clean and healthy lifestyle [ 23 ]. Until March 14, 2021, Indonesia was still in the process of fighting the disease outbreak and there had been 1,450,132 confirmed cases out with 131,828 active cases, 39,339 deaths from 59,564 suspects, and 1,278,965 recovered cases from 73,460 specimens [ 24 ]. Table 2 shows the ten provinces with the number of Covid-19 cases by March 14, 2021. At East Java Province, Gresik is in the sixth place with total cases of 5311 confirmed positive cases, 69 cases hospitalized, 4891 cases recovered, and 351 cases died [ 25 ]. The data contribute to the spread of Covid-19 in Gresik, namely adding 4 confirmed positive cases from the previous total of 5,307, adding 1 death case from the previous total of 350, and adding 9 recovered cases from the previous total of 4882 as of March 19, 2020. So, there are additional confirmed positive, died, and recovered cases within a day in Gresik [ 26 ]. Various efforts to suppress the spread of the virus are still being carried out from all community levels because the virus is still contributing to massive destruction [ 27 ]. One of them is the implementation of Large-Scale Social Restrictions (LSSR) in accordance with the Regulation of the Minister of Health of the Republic of Indonesia Number 9 of 2020 as an implementation of Law Number 6 of 2018 concerning Health Quarantine, namely in article 2 paragraph 1, article 3, and article 4 paragraph 1, 2.3 [ 28 ] and the issuance of the Decree of the Chief of Police Number: Mak/2/III/2020 concerning Compliance with Government Policies in Handling the Spread of the Corona Virus (Covid-19). Gresik Regency carried out various efforts to prevent the spread of Covid-19 including LSSR and implementing Community Activities Restrictions Enforcement (CARE) as evidenced by the issuance of a letter numbered 360/12/437.96/2021 regarding the implementation of the Java Bali CARE on January 9, 2021 and Circular Letter Number 1 of 2021 concerning the Enforcement of Restrictions on Community Activities to Control the Spread of Covid-19 19 in Gresik on January 10, 2021 in accordance with the Presidential Instruction of the Republic of Indonesia Number 6 of 2020 concerning Increasing Discipline in Enforcement of Health Protocol Laws in the Prevention and Control of Covid-19 during the Implementation of Community Activity Restrictions Enforcement (CARE) [ 26 ]. Based on this policy, the applied norms during the implementation of LSSR are that all people are required to implement 3 M health protocol (e.g. wearing masks, washing hands with soap, and maintaining distance) and 3T (e.g. testing, tracking, and treatment) for medical personnel, government, and other institutions in accordance with the Regulation of the Minister of Health of the Republic of Indonesia Number 9 of 2020 concerning LSSR Guidelines. In a year, there has been a change in policy along with the increase in positive confirmed cases that eventually implement the newest 5 M health protocol namely wearing masks, washing hands with soap, maintaining distance, staying away from crowds, and limiting mobilization and interaction [ 18 , 19 , 22 , 23 ]. This study was conducted during the implementation of LSSR to CARE in Gresik, from May 2020 to January 2021. It was observed that there were no significant changes related to awareness of disaster response in implementing health protocols. This was indicated by the red status of the Covid-19 distribution zone. In addition, several violations were found such as not using a mask when doing activities outdoor, ignoring social distancing, and crowding in public places. There, moreover, were still parties who did not believe in the existence of Covid-19 and not few of them thought that this outbreak was God's destiny. On the other hand, educating society has been carried out by local governments through task forces in each region starting from the small scale (e.g. RT/RW). The education is conducted through social and electronic media. A joint operation between Indonesian Army and National Police aims to enforce health protocols and limit community activities. However, in reality, violations are still existing. This is interesting to analyze regarding the construction built by the community as a conscious effort to respond to disasters in the midst of a pandemic and the dominant factors that affect the Covid Task Force in educating and enforcing rules during LSSR to CARE in Gresik. Research related to people's responses to Covid has already been carried out. Rahmanti examines the public responses to the Government's policies on handling Covid [ 29 ]. The study shows that the trend of public sentiment is gradually shifting from “negative” to “positive” due to the government alertness and the spread of the disease which is starting to be controlled. The announcement of the Government's policy regarding the “new normal” issue received a positive response from the majority of Twitter social media users. Hamdi explained in his research that when the Indonesian Government closed mosques and large gatherings, the Tabligh Jamaat (Islamic Organization) saw Covid-19 as not a very dangerous thing [ 30 ]. They considered Covid-19 to be an anti-Islamic conspiracy. So they carry out the same worship activities as before Covid, namely gathering and preaching. Existing research focuses more on government policies and societal responses. Research that examines people's self-awareness of the dangers of Covid has not been studied. It is important to this study to understand how self-awareness results in a person's attitudes and actions in complying with health protocols and adherence to strict regulation. This research is limited to awareness of community disaster response (Covid in the view of the Gresik community, awareness of complying with health protocols, awareness of complying with activity restriction policies) during the implementation of LSSR and CARE. The obtained data were analyzed using Social Construction Theory of Peter L. Berger and Thomas Luckman. This theory explains that the analysis of social reality is built in two ways namely redefining between reality and knowledge and seeing society as an objective and subjective reality. In other words, individual is the shaper of society and society is also the shaper of the individual. In addition, this theory also explains a dialectical process that includes three simultaneous moments, namely externalization (adjustment to the socio-cultural world as a human product), objectification (interaction with the intersubjective world that is institutionalized), and internalization (individuals identified with institutions). Social organization of which the individual is a member is used to form a construct of reality [ 31 ].

Methods This study used a descriptive qualitative research method to describe the object of research in the form of written or spoken words from people and observed behavior [ 32 ]. The focus of this study was the construction built by the community as a conscious effort to respond to disasters in the midst of a pandemic as well as analyzing the dominant factors affected the Covid Task Force in educating and enforcing rules during LSSR to CARE in Gresik. The subjects of this study were those who were affected by the implementation of LSSR to CARE. Eight informants were selected through snowball sampling technique, whose social backgrounds were varied encompassing educators, community leaders, religious leaders, medical personnel, and general public. This study was carried out in Gresik during the implementation of PSSB until CARE, starting from May 2020 to January 2021. The reason for choosing the area was not only based on the risk of spreading Covid-19 in Gresik, but there were also violations related to social distancing policy such as recitations around the village, crowding in public places, holding wedding receptions exceeding the stipulated invitation quota, doing activities outside the home without wearing a mask, and vacationing in high-risk areas. Data were collected by using in-depth interviews, questionnaires, and observations. The informants had understood the purpose of the study and had asked for confidentiality. In qualitative study, there was modeling that started from the process of categorizing the data sequence and organizing the data into one pattern, category, and large description unit, which further gave a significant meaning to the analysis. It also included explaining the pattern of description and looking for relationships between the dimensions of the description [ 32 ]. Data analysis and interpretation were carried out with a deep understanding of community construction as a form of awareness in understanding social reality. The construction included the emergence of the Covid Task Force (Satgas), society versus health protocol, the dialectic of health protocols in Gresik to build public awareness in the midst of a pandemic. Those three aspects of the community construction was referred to the dominant factors affecting the Covid Task Force in educating and enforcing rules during the implementation of LSSR to CARE in Gresik.

Results and discussion Community disaster response awareness in the midst of the implementation of LSSR to CARE could be analyzed through construction built on knowledge and reality about disaster response and the spread of Covid-19. Based on the formation of the construction, it allowed the public to raise awareness in accordance with the thing being constructed, as well as the impact that appeared on the awareness that the community had made in dealing with the pandemic. The informants used in this study came from different socio-cultural backgrounds and were proven by their social status in society. So that, the construction was built from the community as the shaper of individual and the individual as the shaper of community [ 31 ]. Covid construction until the emergence of Covid Task Force ( Satgas ) The construction of Covid in this study began with community's knowledge of disaster response including 1) believing as a preventive measure when a disaster occurred, 2) the government's response in preventing disasters, 3) activities carried out by the community individually and in groups as a form of sensitivity and conscious effort when a disaster occurred or as an anticipation of the unexpected impact, and 4) did not really understand the disaster response in detail. Based on the knowledge of disaster response, it could be seen that there were two construction groups related to disaster response, namely knowing disaster response and not knowing disaster response. Groups who had good knowledge of disaster response could understand disaster response as a form of sensitivity, conscious effort, and active participation of the community as individuals and groups in dealing with disasters that occurred. Meanwhile, the group who did not know about disaster response understood that disaster response was not important to know. During the Covid-19 pandemic, this group was more interested in information related to the economy than information related to norms that applied during the pandemic. The construction formed related to disaster response affected the community's construction of the current Covid-19 outbreak. This was due to the fact that handling during the pandemic included preparedness that must be carried out by all elements of society. In fact, the constructions built by the community related to Covid-19 were based on information obtained, habits, and the environment. Community's construction based on the information obtained showed that people who updated information about Covid-19 had a high level of vigilance compared to those who were less updated. This could be proven from the questionnaires distributed in the community showing that around 45 % of the informants admitted to updating information on Covid-19, 20 % did not update the information very much, and the rest 35 % admitted that they did not update the information. Informants who chose to update Covid-19 information thought that this disease outbreak was dangerous for human safety and health, so it was important to monitor developments starting from the number of confirmed cases, the symptoms caused, the distribution in their area, and the rules implemented during the outbreak. Such conditions were depicted in the following excerpts from interviews with the informant. Informants who chose not to update Covid-19 information thought that simply knowing Covid-19 information was a better action so that they were not too afraid of the situation. This reality was reflected in the following interview excerpt. Informants who chose not to update information related to Covid-19 assumed that Covid-19 was a God's destiny and reminder for all humans, so that Covid-19 information became less important to know. They got focused on the economic life of the family as the impact felt during the pandemic. This reality was reflected in the following excerpts from the interview answers. The construction that the community understood related to Covid-19 actually confirmed Berger's idea that conveyed that a construction built from knowledge became a picture of reality occurred and individual knowledge was seen as a picture of objective reality in itself [ 33 ]. This knowledge was reflected when individuals constructed Covid-19 as an objective reality. Based on the construction differences existed in the community and the addition of confirmed cases that continued to occur, the government had formed a task force for educating the public regarding the prevention and control of Covid-19 through health protocols and handling the spread of Covid-19. Government policies starting from the implementation of 3 M, 3 T, and 5 M were a form of norms and culture that must be instilled during the pandemic. Further, there would be no misunderstanding of the information received and obtained by the public. The Task Force ( Satgas ) served as the second guard after health workers and was formed on a macro (national) to micro (RT/RW) scales. At the micro level, the Task Force was responsible to establish a Covid post, conduct raids (sweeping) targeting mass crowds in village areas, coordinate with health workers if there were confirmed cases, and sterilize public places (e.g. schools, places of worship) [ 26 ]. This reality was revealed from the statement of the Covid Task Force in the following village. Active community participation was an important element after good cooperation between the community and the Task Force in preventing the spread of Covid-19 through implementing health protocols. In fact, this reality was reflected in the expression of one of the informants.

Results and discussion Community disaster response awareness in the midst of the implementation of LSSR to CARE could be analyzed through construction built on knowledge and reality about disaster response and the spread of Covid-19. Based on the formation of the construction, it allowed the public to raise awareness in accordance with the thing being constructed, as well as the impact that appeared on the awareness that the community had made in dealing with the pandemic. The informants used in this study came from different socio-cultural backgrounds and were proven by their social status in society. So that, the construction was built from the community as the shaper of individual and the individual as the shaper of community [ 31 ]. Covid construction until the emergence of Covid Task Force ( Satgas ) The construction of Covid in this study began with community's knowledge of disaster response including 1) believing as a preventive measure when a disaster occurred, 2) the government's response in preventing disasters, 3) activities carried out by the community individually and in groups as a form of sensitivity and conscious effort when a disaster occurred or as an anticipation of the unexpected impact, and 4) did not really understand the disaster response in detail. Based on the knowledge of disaster response, it could be seen that there were two construction groups related to disaster response, namely knowing disaster response and not knowing disaster response. Groups who had good knowledge of disaster response could understand disaster response as a form of sensitivity, conscious effort, and active participation of the community as individuals and groups in dealing with disasters that occurred. Meanwhile, the group who did not know about disaster response understood that disaster response was not important to know. During the Covid-19 pandemic, this group was more interested in information related to the economy than information related to norms that applied during the pandemic. The construction formed related to disaster response affected the community's construction of the current Covid-19 outbreak. This was due to the fact that handling during the pandemic included preparedness that must be carried out by all elements of society. In fact, the constructions built by the community related to Covid-19 were based on information obtained, habits, and the environment. Community's construction based on the information obtained showed that people who updated information about Covid-19 had a high level of vigilance compared to those who were less updated. This could be proven from the questionnaires distributed in the community showing that around 45 % of the informants admitted to updating information on Covid-19, 20 % did not update the information very much, and the rest 35 % admitted that they did not update the information. Informants who chose to update Covid-19 information thought that this disease outbreak was dangerous for human safety and health, so it was important to monitor developments starting from the number of confirmed cases, the symptoms caused, the distribution in their area, and the rules implemented during the outbreak. Such conditions were depicted in the following excerpts from interviews with the informant. Informants who chose not to update Covid-19 information thought that simply knowing Covid-19 information was a better action so that they were not too afraid of the situation. This reality was reflected in the following interview excerpt. Informants who chose not to update information related to Covid-19 assumed that Covid-19 was a God's destiny and reminder for all humans, so that Covid-19 information became less important to know. They got focused on the economic life of the family as the impact felt during the pandemic. This reality was reflected in the following excerpts from the interview answers. The construction that the community understood related to Covid-19 actually confirmed Berger's idea that conveyed that a construction built from knowledge became a picture of reality occurred and individual knowledge was seen as a picture of objective reality in itself [ 33 ]. This knowledge was reflected when individuals constructed Covid-19 as an objective reality. Based on the construction differences existed in the community and the addition of confirmed cases that continued to occur, the government had formed a task force for educating the public regarding the prevention and control of Covid-19 through health protocols and handling the spread of Covid-19. Government policies starting from the implementation of 3 M, 3 T, and 5 M were a form of norms and culture that must be instilled during the pandemic. Further, there would be no misunderstanding of the information received and obtained by the public. The Task Force ( Satgas ) served as the second guard after health workers and was formed on a macro (national) to micro (RT/RW) scales. At the micro level, the Task Force was responsible to establish a Covid post, conduct raids (sweeping) targeting mass crowds in village areas, coordinate with health workers if there were confirmed cases, and sterilize public places (e.g. schools, places of worship) [ 26 ]. This reality was revealed from the statement of the Covid Task Force in the following village. Active community participation was an important element after good cooperation between the community and the Task Force in preventing the spread of Covid-19 through implementing health protocols. In fact, this reality was reflected in the expression of one of the informants.

Conclusion As a conclusion, first, socially, the community has not taken the dangers of Covid-19 seriously, which is proven by violations of the rules when implementing LSSR and CARE. For instance, people have not implemented 5 M properly. Second, there is an inconsistency between knowledge and social reality related to disaster response as the first step to construct something important in everyday life. On the other hand, many people are aware of the dangers of Covid-19, but they have not shown good awareness. Third, the dialectical process of social construction theory by Peter L. Berger and Thomas Luckman shows that the community has not implemented a disaster-aware culture by obeying the rules as a socio-cultural product of the inter subjectivity. Fourth, the socio-cultural environment determines a person's construction to carry out self-identification, self-interaction, and adjustment to social changes that occur in daily life, especially in the face of the Covid-19 pandemic. Its relation in shaping individual and collective consciousness has hampered the responsibilities carried out by the Task Force. It is proven that during a year of the spread of Covid, Gresik still becomes the top 10 areas with the highest confirmed Covid-19 cases in East Java Province. In the context of the Gresik community, the religious approach is important as an instrument for forming self-awareness. This religious approach involves involving religious leaders as a model for complying with health protocols and government regulations. Based on previous findings by Ref. [ 43 ], actions that can be taken to reduce the spread of COVID-19 are campaigning for public awareness, testing policies, and maintaining social distancing. in addition, according to Ref. [ 44 ], pharmaceutical and non-pharmaceutical measures also have a great impact in reducing the spread of Covid-19 such as restrictions on community mobility, financial assistance for poor families, providing free vaccines and vitamins. The novelty of this research is the finding that theological elements play a role in controlling Covid-19, this finding requires the importance of government policies in disaster management with various approaches, namely social, cultural, health, security, politics and also religion. Based on the results of this study, it is necessary to conduct further research related to the model of improving people's healthy lifestyles with multiple approaches. In the early stages, the research focused on the theological approach.

This study aimed to analyze the community's disaster response awareness during the Covid-19 pandemic during the implementation of The Large-Scale Social Restrictions (LSSR) in Gresik. Self-awareness was observed using Peter L. Berger and Thomas Luck man's Social Construction Theory through a dialectical process of internalization, objectification, and externalization. The results showed that there had been no good awareness in efforts to prevent the spread of Covid-19 in Gresik. Socially, the community had not taken the dangers of Covid-19 seriously. There was also an inconsistency between knowledge and reality related to disaster response. In coping with the dialectical process, the community had not implemented a disaster-aware culture by obeying the existing regulations. At least, the sociocultural environment determined a person's construction for self-identification, interaction, and adjustment to the social changes that occurred. Hence, the sociocultural construction of the community had never made the disease outbreak a serious problem and considered it as well as God's reminder even though infected cases continued to increase. A situation was indeed difficult for the Task Force to succeed in the Large-Scale Social Restrictions (LSSR) to Community Activities Restrictions Enforcement (CARE) suppressed the increase of Covid-19 positive cases in Gresik, Indonesia. This research sees that the government's policies in handling Covid- 19 are not enough, it needs more optimal involvement of community and religious leaders, to provide education on the importance of maintaining health protocols and building self-awareness of the dangers of Covid. Keywords

Society and health protocol The implementation of health protocols in the community rose various problems. On the one hand, they must implement health protocols starting from wearing masks, washing hands with soap, maintaining distance, staying away from crowds, and limiting mobility and interaction. However, this situation created uncertainty, confusion, and shock as a result of the emergency spread of Covid-19 [ 34 ]. Wearing a mask The first health protocol focused on wearing a mask. The reason for wearing mask was in accordance with the results of research conducted by experts in the world regarding the rapid spread of Covid through air [ [35] , [36] , [37] ]. The reality regarding the use of masks showed that people had not fully accepted the new habit because it was contrary to the culture of the people who were not used to doing activities by wearing masks. Sociologically, this happened because the habitus that went on in their social life did not claimed that using masks was part of the efforts to maintain health. So, when there was a sudden change in the events of the Covid-19 pandemic, it created chaos and culture shock in the community because they were not used to it and there were no culturally binding rules to use it. However, on the other hand, they had the obligation to use it as an effort to prevent and spread Covid-19. Cultural shock could be seen from the response of the community who considered that the new habit was contrary to the habit in their social environment and was reflected in the informant here. This statement was confirmed by the Covid-19 Task Force in the village. This showed that people's knowledge depended on the culture developed by the surrounding environment. According to Berger, this condition was an intersubjective experience referred to the dimensions of the structure of general awareness towards individual awareness in the midst of integrated and interactive social situations [ 31 ]. This was because individuals in society had become an inseparable part and their reactions were part of response to what they thought and the surrounding environment. Washing hands Washing hands was not a new thing in Gresik's social environment. This was due to the fact that the people had a culture of washing their hands as a form of cultural ritual when visiting religious tourism sites, ablution, and rituals before and after eating. However, in reality, there is a gap between the existing culture and new habits in the midst of a pandemic. Several informants in this study stated that such conditions were recognized as differences. The difference lied in the knowledge built on the habit of washing hands. Washing hands in the middle of a pandemic was understood as an ordinary ritual, not something new, so people had a tendency to ignore the warning to wash hands. Meanwhile, washing hands was carried out as a form of cultural ritual when visiting religious graves. This was reflected in the statement of the informants. This statement was confirmed by the Covid Task Force who stated that there was a different perspective between the culture practiced by the community for a long time and the new habits to prevent the spread of Covid-19 in Gresik. This reality showed that knowledge about the importance of public awareness to obey the rules applied during the pandemic was still not implemented properly. In this case, the role of the Covid Task Force was to regulate changes in values and norms that applied in society due to the pandemic. The goal was to raise public awareness in obeying the rules. In addition, the reality formed in social construction showed the existence of individual cognitive work to interpret the world of reality existed as a result of social relations between individuals and their surrounding environment. In addition, individuals built their own knowledge of the reality they saw based on pre-existing knowledge structures. In this case, humans were said to be social beings, therefore, every statement must be proven true and the key to true knowledge was facts [ 38 ]. For this reason, reality and knowledge could not be separated in analyzing social construction problems in life. Social culture Social culture referred to health protocols covering maintaining distance, staying away from crowds, and limiting mobilization and interaction. The term social culture was chosen to represent the health protocol, while at the same time showing that the socio-cultural community could not be separated from the protocols to support the Task Force to prevent the spread of Covid-19 in Gresik. From May 2020 to January 2021, Gresik government had implemented Large-Scale Social Restrictions (LSSR) and the Community Activity Restrictions Enforcement (CARE). Unfortunately, violations still happened with common reasons such as ignorance, inadvertence, and discomfort, especially for the case of social distancing, avoiding crowds, limiting mobilization and interaction. For those who did violations, the condition was not one of the cultures in their daily lives. Many of them, for instance, gathered in coffee shops, cafes, and other crowded places. This was confirmed by the Task Force when accompanying judicial operations with Indonesian National Army -Indonesian Republic Police, Transportation Agency, Civil Service Police Unit, and medical officers at a coffee shop. In addition, there were still some recitations that did not apply social distancing. There were also people who held weddings that exceeded the invitation quota. This reality was obtained based on field and media observations as well as the interview results. Such conditions indicated that the community was adjusting to new rules. For Berger, this process was classified as an externalization construction process, meaning that society as subjective and objective stakeholder had a role to adapt to the socio-cultural aspect as a human product. The adjustment in relation to efforts to prevent the Covid-19 pandemic was conducted by implementing wearing masks, washing hands with soap, maintaining distance, staying away from crowds, and limiting mobilization and interaction during LSSR to CARE. Humans made such rules in an effort to realize social order. The existing violations were considered as the inability of the community to face and adapt to the rules used to maintain social order. Therefore, the problem of change was in the process of externalization. People who used to being in order did not mind the social changes occurred, but those on the contrary still made deviations to adjust to their social roles. In other words, violations continued to occur. In fact, the informant RN also experienced difficulties in adjusting to the rules. Dialectic of health protocol in Gresik There were three dialectical components in Peter L. Berger's social construction namely internalization, objectification, and externalization. The dialectic of health protocols was reflected as follows. a. Internalization The internalization process that emerged as a form of self-identification with socio-cultural was originated from public knowledge about Covid and disaster response efforts manifested in the active participation to assist medical personnel and the government in overcoming Covid-19 by complying and implementing health protocols. For Berger, this process contained the construction of knowledge as a picture of the reality and individual knowledge was seen as a picture of the objective reality [ 33 ]. This knowledge was reflected when individuals constructed Covid-19 as an objective reality. b. Objectification The objectification process that emerged as an awareness made to other parties (Covid Task Force) and adjustment to the rules applied in society was realized through self-interaction with socio-cultural aspect to face Covid-19 pandemic. This process included changes in habitus or habits carried out by the community. Before this outbreak, people did not have strict rules regarding wearing masks when leaving the house, coughing and sneezing etiquette according to the rules, carrying out a clean and healthy lifestyle, and washing hands regularly. However, after this outbreak emerged, people faced a situation that changed their habituation by applying what they were not used to doing. c. Externalization The process of externalization appeared as a form of adjustment to the socio-cultural aspect as a human product. This was realized through adjustments to the current rules such as conducting 5 M health protocol to prevent the spread of Covid-19. Through this dialectical process, community's disaster response awareness in dealing with the Covid-19 pandemic could be initiated such as by wearing masks, maintaining social distance, washing hands according to suggested procedures, and applying good coughing and sneezing etiquette. All these processes were parts of the objective and subjective dimensions, because society was a cultural product of society itself (the existence of inter subjective relationships) and human existence as well as the creator of their own world be [ 31 ]. Based on the findings and the dialectical process occurred, it was found that the dominant factor that influenced the Covid Task Force in educating and enforcing the rules during the LSSR to CARE in Gresik was the strong socio-cultural factors adopted by most people. They thought that this outbreak emerged as a reminder, warning, and destiny from God. So that, the efforts of the Covid Task Force to carry out education (e.g. wearing masks, washing hands, etc.) and policies related to preventing the spread of the virus were hampered by these factors. Thus, the relationship between individuals and their institutions was a dialectic (intersubjective) expressed in three moments: society as a human product; society as an objective reality, and human as a social product. This dialectic was mediated by experience and roles that represented individuals in an institution [ 39 ]. Referring to the dialectic, the COVID-19 pandemic could not be separated from the theological debate about destiny. The theme of destiny gave dissimilarities to a person's behavior in responding to the pandemic and had an impact on compliance with health protocols. A person who ignored health protocols during a pandemic was motivated by the theological belief that God had arranged life and death, including the presence of Covid. As a result, a person thought that they did not need to wear a mask, wash hands, and keep a distance, and so on. Social and religious activities presented by many people without heeding the health protocols were still ongoing. The reason was the belief that efforts to comply with health protocols were useless if in the end God determined someone's destiny. Such society's conception, if traced, led to the understanding of destiny in the perspective of theology. The Jabbariyah perspective held that the will or action was carried out by force (fatalism) because God had determined their destiny. Humans were passive and did not have the ability to change their destiny. Consequently, the Covid-19 pandemic was believed to be a disease made by God, a warning from God. A person would be exposed to Covid when God determined so, even though he had strictly adhered to health protocols. Similarly, a person would die when God predestined. The impact of this understanding was the neglect of the government's regulations. In regard to the Qadariyah perspective, they relied on human ability to deal with problems without God's intervention. Humans were active so that the will absolutely depended on human free will and free act. In this context, the Covid-19 pandemic was understood as a factual reality that was dangerous and led to a human-made disaster. Consequently, individuals obeyed health protocols [ 40 ]. In addition to these two understandings, there was also a group of people who had a progressive theological understanding that prioritized preventing the occurrence of human dangers over other benefits. This progressive theology was based on the principle of Al-dharuriyah al-khamsah, the goals of Islamic law covering preserving religion, soul, reason, offspring, and property. Covid 19 threatened human life, therefore, the benefit of the soul must be prioritized. The influence of Jabbariyah ideology encouraged counterproductive behavior towards efforts to cheese the spread of the corona virus. While the influence of Qadariyah's understanding was enough to help prevent the further spread of the Corona virus. Meanwhile, the influence of progressive Islamic theology encouraged productive behavior by being actively involved in carrying out social transformation in efforts to prevent and control Covid-19 [ 41 ]. From a historical perspective, pandemics had occurred among Muslims in the era of Prophet Muhammad. The Prophet's pandemic prevention and control was explained in the hadith “When you hear of a plague in an area, then don't enter it. But if a plague occurs in the area you are in, then do not leave that place.” [ 42 ]. This hadith was relevant to Covid-19 mitigation, such as lockdown, self-quarantine, self-isolation, staying at home, maintaining distance, Large-Scale Social Restrictions (LSSR), and Enforcement of Community Activity Restrictions Enforcement (CARE). The discourse on the Covid-19 pandemic associated with awareness of disaster response ultimately narrowed how an individual was able to have a dialogue between himself and the sociocultural aspect, as well as a dialogue between his theological conceptions and the social reality faced. Individuals were in objective and subjective reality. During the pandemic, there was a set of rules that served as guidelines for preserving social order for the sustainability of human life. However, even though the rules in the social structure were restrictive, there were many violation of health protocols. Violations of these rules were caused by inconsistent processes of individual externalization or individuals’ incapacitation to apply the rules to maintain social order. Ethics statement This study was reviewed and approved by Institution of Research and Community, Universitas Negeri Surabaya, with ethics approval reference [Number: 108065/UN38.III.I/TU.February 00, 2023]. Data availability statement All the raw sequence data in this study are available at https://ourworldindata.org/covid-cases or https://www.kompas.com/tren/read/2021/03/15/095100365/update-corona-dunia-15-maret--120-juta-kasus-covid-19-10-negara-dengan?page=all for Table 1 and available at https://infeksiemerging.kemkes.go.id/situasi-infeksi-emerging/situasi-terkini-perkembangan-coronavirus-disease-covid-19-15-maret-2021 for Table 2 . Funding This research received no external funding. CRediT authorship contribution statement Sarmini: Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Conceptualization. Faridatul Lailiyah: Writing – review & editing, Visualization, Resources, Methodology, Formal analysis, Data curation. Suprapto: Writing – review & editing, Writing – original draft, Visualization, Supervision, Resources, Methodology, Conceptualization. Mutimmatul Faidah: Writing – review & editing, Writing – original draft, Resources, Data curation, Conceptualization. Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Sarmini Sarmini reports administrative support, article publishing charges, and writing assistance were provided by State 10.13039/501100012696 University of Surabaya . Sarmini Sarmini reports a relationship with State 10.13039/501100012696 University of Surabaya that includes: employment and non-financial support. Sarmini has patent issued to State University of Surabaya/Universitas Negeri Surabaya. The Author Declare, there is no conflict of interest If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CC BY

no

2024-01-16 23:42:01

Heliyon. 2023 Dec 20; 10(1):e23880

oa_package/cd/78/PMC10788434.tar.gz

PMC10788437

38142637

Introduction Refractory respiratory failure is the leading cause of death in patients critically ill with COVID-19 1 and immune-mediated acute lung injury rather than direct cytotoxic effects of SARS-CoV-2 infection appears central to disease severity. 2 Characterisation of the host immune response at the lung tissue level using multimodal approaches is critical to understanding disease pathophysiology. 3 Diffuse alveolar damage (DAD) is the predominant histological pattern in post-mortem lung tissue (PMLT) from cases of acute severe COVID-19 4 and is considered a characteristic feature. DAD is routinely divided by pathologists into an acute exudative phase (EDAD), which may progress to a proliferative and organising phase (ODAD). 5 DAD stages frequently coexist within a single patient 6 as a temporally heterogeneous pathology. Alternate patterns of lung tissue damage are also recognised, 7 including superimposed bacterial bronchopneumonia (BRON), 5 pulmonary oedema consistent with acute cardiac failure (PO-ACF) 8 and invasive pulmonary mycosis (IPM). 9 How these different phases of DAD and the alternate patterns of lung injury influence the nature of the immune response is currently unclear. Immune-mediated acute lung injury rather than the direct cytotoxic effects of SARS-CoV-2 infection itself appears to be central to severe or fatal COVID-19, evidenced by a topological dissociation between inflammatory and viral-positive areas, 2 reduced or absent virus in late disease 10 , 11 and that therapeutically, the inflammation-modulating glucocorticoid dexamethasone provides a significant mortality reduction in severe disease. 12 The systemic immune response in COVID-19 shows major shifts in lymphoid and myeloid compartments as blood signatures of severe disease 13 and the ‘competent’ immune profiles associated with mild COVID-19. 14 However, these studies provide mere inferences to the cellular responses and architectural injury hidden at the tissue level where the end organ dysfunction occurs and detailed immunophenotyping of affected tissue is required to complete the picture. 15 , 16 , 17 A suite of advanced pathology techniques were utilised early in the pandemic to dissect the shifts in immune and structural cells in COVID-19 post-mortem lung tissue (PMLT). 3 Major emerging themes included a significant macrophage infiltration, expansion of T and B lymphocytes and mesenchymal and fibroblastic proliferation 15 , 18 and intriguingly a topological dissociation between inflammatory and viral-positive areas. 2 Published analyses of COVID-19 PMLT have significant limitations due to indiscriminate comparison of control tissue with an undifferentiated amalgam of COVID-19 ‘diseased tissue’. 3 Furthermore, the metric commonly used to quantify immune cells in lung tissue, namely cells per unit area of tissue section , generally expressed as ‘cells/mm 2 ’ 15 , 18 , 19 , 20 can be confounded by changes in airspace contributions to section area. In this paper, we studied lung tissue from a cohort of 40 people who died with severe COVID-19 and analysed pathologist-guided lung tissue regions of interest (ROIs) representing the distinct temporal stages of DAD as well as alternate COVID-19-related disease patterns.

Methods Tissue bank assembly and cohort description Lung tissue was obtained via autopsy by the Letulle method from three United Kingdom Tissue Biobanks from individuals with clinical and microbiological evidence that COVID-19 disease was the primary precipitant of death with a period of recruitment from of 1 year from April 2020 to April 2021. Data collection and analysis extended from April 2021 until December 2022. Sample size was determined by tissue donor availability from these biobanks, with all cases available being included. All patients were confirmed SARS-CoV-2-positive by reverse transcription polymerase chain reaction (RT-PCR) of nasopharyngeal and/or direct lung tissue swabs at autopsy. We included a cohort of 40 adults, whose clinical metadata was obtained from electronic medical records and post-mortem reports ( Fig. 1 , Table 1 , Tables S1 and S2 ). Metadata included basic subject demographics, prevalence of comorbidities, clinical course and exposure to medications which was defined as any treatment with a corticosteroid, antibiotic or therapeutic anticoagulant prior to death. Architecturally preserved control tissue, henceforth referred to as ‘PRESneg’ was obtained from unused lung donors which did not proceed to transplantation (n = 2). Two cases of disease-free control lung tissue were obtained from donor lungs not used in transplantation where the donor's next of kin consented for use for NHS REC approved research. Tissue section preparation and ROI selection Formalin-fixed paraffin-embedded (FFPE) lung tissue blocks from multiple lung regions were serially cut and mounted onto slides. Formalin fixation was for 72 h as per local protocols given the biohazard risk associated with lung tissue from patients with COVID-19. Multiple lung blocks were taken from each patient to provide ample tissue for analysis, with number taken at the discretion of pathologists from each centre, ranging from 2 to 11 per patient (median = 7). Lobe selection for block curation was also at the pathologist's discretion however multiple pulmonary lobes were represented in all cases. The H&E-stained primary slide from each serial deck was scanned onto the open-source digital online pathology platform OMERO (‘The Open Microscopy Environment’). ROIs were selected under guidance of a consultant histopathologist with cardiothoracic expertise with sizes ranging from 0.25 mm 2 (500 μm × 500 μm) to 1 mm 2 (1000 μm × 1000 μm). ROI classifications included the temporal phases of DAD, bronchopneumonia (‘BRON’), pulmonary oedema consistent with acute cardiac failure (‘PO-ACF’) and invasive pulmonary mycosis (IPM). ROIs were also selected from DAD-free, ‘preserved’ regions of lung tissue from these individuals who were SARS-CoV-2 infected (titled PRESpos), as well as from donors who were SARS-CoV-2 negative (PRESneg). DAD was divided based on published histological criteria 21 into exudative DAD (EDAD), organising DAD (ODAD) and mixed (or ‘intermediate’) diffuse alveolar damage (‘MDAD’). Of these criteria, selection was weighted by a primary ‘hallmark’ characteristic in the context of secondary supportive features ( Table S3 ). Manufacture of control tissue MicroArray (TMA) material To provide positive and negative staining controls for all 40 antibodies in our panel as well as provide empirical controls for batch effects we prepared FFPE Tissue MicroArrays (TMAs) blocks, composed of human tonsil tissue, as well as both SARS-CoV2-infected (BetaCoV/England/2/2020, obtained from the UK Health Security Agency)) and uninfected Vero E6 cells. SARS-CoV-2 is a Hazard Group 3 pathogen (Advisory Committee on Dangerous Pathogens, UK), as such infections were performed in a dedicated Containment Level 3 (CL3) facility by trained personnel as described in Hatton et al. (2021). 22 Vero E6 cells were commercially-obtained (ATCC Cat# CRL-1586, RRID:CVCL_0574) with short tandem repeat testing confirming authenticity and purity as well as Mycoplasma testing performed by the vendor. Vero E6 cells were seeded in a 175 mL flask until 90% confluent then infected with 1.5 × 10ˆ6 PFU/mL of SARS-CoV-2 diluted in 2% FCS DMEM. The inoculum was removed after 2 h and replaced with 30 mL of warm 2% FCS DMEM. After 72 h, supernatant was collected and centrifuged at 2000 rpm for 30 min at 4′C. Supernatant was removed and the pellet was then resuspended in 4% formaldehyde for 1 h at RT. Cells were then spun at 500g for 5 min and resuspended in 70% alcohol solution/IMS. Cell pellets were processed and paraffin embedded at the Novopath Research Service (NovoPath, Department of Pathology, Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK). 2 mm cores from paraffin embedded SARS-CoV-2 infected Vero E6 cells were embedded alongside 2 mm cores of uninfected Vero E6 cells and Tonsil tissue, to produce a control tissue microarray block that was mounted on super frost slides and processed/stained alongside each batch of patient samples. Antibody panel design, conjugation and antigen retrieval for imaging mass cytometry analysis The 40-plex antibody panel identifying the immune, signalling and stromal components in the surrounding microenvironment of COVID-19 post-mortem lung tissue is described in Table S4 . Antibodies were commercially available with the exception of anti-B7 and anti-C3-30 obtained and previously validated by academic collaborators. 23 All antibodies used in this study were pre-validated for performance using Tris EDTA pH9 “Heat-Induced Epitope Retrieval” (HIER) two colour immuno-fluorescence (IF) and conjugated (where necessary) to lanthanide metals and fully validated. Metal tags were paired with antibodies based on the relative staining intensity of each marker as determined by IF following the rules of “best practice” for CyTOF panel design 24 using the Maxpar X8 metal conjugation kit following manufacturer's protocol (Standard Biotools, CAT#201300). Antibodies conjugated to platinum isotopes 194 Pt and 198 Pt were conjugated as described in Mei et al., 2015. 25 Conjugation success was determined by measuring antibody recovery post-conjugation, metal addition by binding the antibody to iridium labelled antibody capture beads AbCTM Total Antibody Compensation Beads (Thermo Fisher, USA, CAT#A10513) and acquiring on a Helios system (Standard Bio-tools, USA), and finally a retained ability to recognise antigen post-conjugation using either a two layer IF or directly by IMC using the Hyperion imaging module (Standard Bio-Tool) connected to the Helios. Hyperion (IMC) set up, quality control (QC) and sample acquisition Prior to each slide acquisition, the Hyperion Tissue Imager was calibrated/QC'd to achieve reproducible sensitivity based on the detection of 175 Lutetium by ablating a single multi-element-coated “tuning slide” (Standard Biotools, USA) using the manufacturer's “auto tune” application. After tuning, TMA control and experimental slides were loaded onto the Hyperion system to create Epi-fluorescence panorama images of the tissue surface and regions of interest (ROI) were set based on OMERO annotations. A small region of tonsil tissue was targeted to test that the chosen laser power was able to ablate the entire tissue depth. First, three 0.25 mm 2 ROIs, one per TMA control, were ablated followed by ROIs from the post-mortem cases with ROI sizes ranging from 0.25 to 1 mm 2 . Ablations were performed at 200Hz laser frequency to create a resultant MCD file containing all data from all ROIs for a given slide/case. MCD files were then opened in MCD Viewer software (Standard Bio-Tools) to perform a qualitative, visual QC of the staining intensity and pattern with the initial IF images as a benchmark. All images were exported as 16-bit single multi-level TIFFs using the “export” function from the “file” menu. For efficiency, all open collection channels from the experimental acquisition template (in this case, 60, including several “Blank” channels for QC purposes) from all ROIs were left selected and any image/channel removal was dealt with later in the analysis. The multi-level 16-bit TIFF images were then input into our OPTIMAL pipeline 26 for data exploration at the single cell, spatial level. Cell segmentation, feature extraction, parameter correction/normalisation and FCS file creation Cell segmentation was performed as per the OPTIMAL pipeline 26 using Ilastik. Output nuclear probability maps were input into CellProfiler to segment cell nuclei, that in turn acted as seeds for cell segmentation using a propagation algorithm based on the EPCAM signal ( Figure S1 ). Single cell objects were measured for mean intensity in each of the labelled channels and corrected for metal signal “spillover” according to a previously described approach. 27 An arcsinh transformation cofactor (c.f.) of 1 was applied to all metal signal parameters. Batch effect correction was performed using Z-score normalisation on the arcsinh c.f. 1 transformed data ( Figure S2 ). We also added additional metadata to the files such as batch number, to be accessible and plot–able parameters for subsequent analysis. Final matrix data was converted to FCS file format within the MATLAB pipeline. Visualisation, clustering and spatial exploration of single cell IMC data FCS Express software (Version 7.14.0020 or later, Denovo software by Dotmatics, USA) was used as outlined in the OPTIMAL method. 26 Briefly, the FCS files created from the segmentation pipeline of each ROI were loaded as a single merged file. Gates were created on batch, biobank source, pathology class etc. to aid with meta-analysis. SARS-CoV-2 spike and nucleocapsid protein expression was determined for each of the 8 pathology classes on a per cell basis using histogram displays, and the population means were compared to the SARS-CoV-2 infected and mock infected Vero E6 cell TMA controls. Single cell data structure for all 38 positive signals ( arcsinh c.f. 1 transformed and Z score normalised) was displayed by creating a PacMap dimensionality reduction plot as described previously. 26 To identify resident cell types and states the same 38 transformed and normalised metal parameters were used as input in to the FLOWSOM clustering algorithm as outlined previously. 26 , 28 The default 100 SOMs (clusters) were merged using a hierarchical approach to 40 consensus SOMs (cSOMS). The 40 cSOMs were further merged to 25 final “tier 2” clusters based on expert annotation and a priori knowledge from heat map interrogation. “Tier 2” clusters were then merged to 10 “high level” cell types denoted as “tier 1”. Spatial neighbourhood analysis for tier 1 and tier 2 clusters was performed as outlined in Hunter et al. (disc outgrowth of 5 pixels and 100 iterations of randomly mapping cells back on to the segmentation maps). 26 This was dependent on the scale of the number of nearest neighbours considered. Statistically significant interactions between cell types were determined by comparing spatial cell iterations and those obtained by the random permutations of the cell positions. If differences were detected in the original data compared to a 90% confidence interval of the random iterations, then a significant difference (interaction or avoidance) was listed for that cell type. Statistically significant interactions between cell types were determined by comparing each cell type's nearest neighbour phenotypes to that expected if the cells in that field of view were randomly positioned. This is carried out using a Monte Carlo simulation which takes the identical number of cell phenotypes and positions them randomly at cell positions in the field of view, each cell's nearest neighbour phenotypes are then calculated. We carried out 100 iterations of this procedure and a significant difference (interaction or avoidance) is detected in the original data compared to a 90% confidence interval of the random iterations for each field of view. The heatmap shows the fraction of the fields of view where that interaction was determined to be significant. A 90% confidence interval allows more permissive measurement of possible interactions of lower frequency cell types and accounts for the variability across ROIs. This analysis workflow is based on a tested approach 26 optimised on tonsillar tissue with known structure and cellular interactions. These positive, neutral, and negative interactions were then averaged to create the overall heatmap for the condition (i.e., pathology, region, etc.). These interactions were assessed across all 8 pathology classes. Airspace correction and normalisation of cell counts by tissue area The metric commonly used to quantify immune cells in lung tissue, namely cells per unit area of tissue section , generally expressed as ‘cells/mm 2 ’ 15 , 18 , 19 , 20 can be confounded by changes in airspace contributions to section area. To compensate for the confounding effect of airspace obliteration, we developed a correction method to standardise cellularity when describing distinct lung cell signatures in COVID-19 PMLT. For each ROI, the percentage of airspace was determined using the following equation (1): where ca = the area of each single cell in each ROI in μm 2 and ROI = the area of the imaged ROI in mm 2 . Furthermore, the area of cellular tissue in mm 2 (first part of Equation 1 above) was used to normalise all cell counts to account for any artificial increases due to tissue collapsing into the imaged ROI due to loss of air gaps (henceforth referred to as airspace correction ). Statistics GraphPad Prism version 9.5.0 was used for all statistical analyses. For differential analysis of cell counts and percentages at tier 1 and tier 2, data distribution was first assessed by the Shapiro–Wilk normality test. The non-parametric Kruskal–Wallis one way analysis of variance test was next performed. Dunn's tests were used for post-hoc pairwise comparisons with each P value adjusted to account for multiple comparisons with a family-wise alpha threshold and confidence level of 5. Results were therefore considered statistically significant where P < 0.05. Graphical data generated by GraphPad Prism 9.5.0 was represented in the format of median, interquartile range (IQR) and range. Ethics Human samples used in this research project were partly obtained from the Newcastle Hospitals CEPA Biobank and their use in research is covered by Newcastle Hospitals CEPA Biobank ethics—REC 17/NE/0070. Control samples used in this research project were also obtained from this source and covered for use by REC 16/NE/0230. Additional human samples used in this research project were obtained from the Imperial College Healthcare Tissue Bank (ICHTB). ICHTB is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Imperial College Healthcare NHS Trust and Imperial College London. ICHTB is approved by Wales REC3 to release human material for research (22/WA/0214). Additional human samples used in this research project were obtained from the ICECAP tissue bank of the University of Edinburgh. ICECAP is approved by the East of Scotland Research Ethics Service to release human material for research (16/ED/0084). Work on these samples at the University of York was approved by the Hull York Medical School Ethics Committee (20/52). Human samples from all centres were obtained with written next of kin consent. Role of funders Funders did not have any role in the study design, data collection, data analyses, interpretation or writing of reports.

Results Demographics and clinical features Lung tissue was analysed from 40 individuals who died with severe COVID-19 (8F/32M). Median age at death was 72 years (IQR = 61.5–79.75 years), with 28/40 (70%) dying in hospital and 12/40 (30%) dying in the community. Median duration of illness was 12 days (IQR = 8.75–22.25 days; duration of illness data known in 35/40 cases). 30/40 (75%) died in the ‘first wave’ of the pandemic (before 1st October 2020) and 10/40 (25%) died in the ‘second wave’ defined by increasing predominance of the alpha (B.1.1.7) variant. 29 None were vaccinated against SARS-CoV-2. Autopsy was performed between same-day and seven days (median = 3 days) after death. All were SARS-CoV-2 positive by RT-PCR on pharyngeal or direct lung sampling. The cause of death in all cases was deemed primary respiratory failure with severe COVID-19 as the major antecedent cause (with or without superimposed bacterial or fungal infection) in all but two cases where heart failure with severe COVID-19 as the major antecedent cause occurred. Table 1 , Table S1 and Figure S1 show cohort demographics, comorbidities and disease characteristics. Spike and nucleocapsid proteins have previously been detectable in COVID-19 PMLT analysed by IMC. 15 However, using single cell expression data in positive and negative infected cultured cells as controls, we did not detect spike or nucleocapsid protein in any of the pathology phenotypes ( Figure S3 ). This could be related to insufficient sensitivity of IMC analysis or support a ‘hit and run’ hypothesis whereby immunopathology is topically dissociated from virus. 2 Histopathological assessment reveals pathological heterogeneity Regions of interest (ROIs) were selected representing the temporal phases of DAD and alternate pathological patterns as shown in Fig. 1 . DAD was the commonest histopathological phenotype, identified in 29/40 cases (73%). Of these, 17 patients (59%) showed DAD in different evolutionary phases, indicating significant intra-patient temporal heterogeneity. 7 cases were predominantly BRON, 3 cases PO-ACF and one case IPM. The three cases which were predominantly PO-ACF were deemed to have died following heart failure with severe COVID-19 as the major antecedent cause. A total of 345 ROIs were selected for analysis. The number of ROIs selected in each pathological pattern is found in Table S2 . There were no patients who were SARS-CoV-2 positive who did not have any lung tissue pathology. Single cell analysis reveals that airspace obliteration not increased cellularity, defines DAD progression 345 ROIs, covering ∼195 mm 2 lung tissue area, were ablated by imaging mass cytometry and single cell analysis was performed using the OPTIMAL approach 26 ( Fig. 2 a, Figure S1 ). The pipeline included normalisation for batch effect from both run and tissue source ( Figure S2 ). This process generated a total output of ∼901k single cells ( Fig. 2 b). Statistical analyses of cellularity comparing distinct pathology types was performed using total cells normalised to area of each ROI (Kruskal–Wallis test, significant where P < 0.05) ( Fig. 2 c). There were significant increases in cellularity as the temporal phases of DAD progressed from preserved tissue, and BRON had the highest. However, it was unclear whether increased cellularity in DAD was related to actual cellular influx, or airspace obliteration leading to an increase of tissue within the ROI, or a combination of both. For example, Fig. 2 d demonstrates striking loss of airspace across DAD progression. To account for this, we normalised cell counts by actual cellular tissue area by airspace correction, as opposed to ROI area. Fig. 2 e demonstrates the effect of airspace correction in nullifying the increased cellularity previously seen across DAD, indicating that this was confounded by airspace obliteration. Notably, time to post-mortem had no influence on overall cell density when comparing ROIs from ‘early’ cases (≤3 days, n = 24) to ‘late’ cases (>3 days, n = 16) (data not shown). Increases in mononuclear phagocytes and lymphocytes and not neutrophils define the immune signature of COVID-19 DAD progression Our high-level (Tier 1) analysis of immune and structural cells generated 10 consensus clusters ( Fig. 3 a, Figure S4 ), which were substantially discrete when mapped back to a PacMap dimensionality reduction plot ( Fig. 3 b). We analysed pathology phenotypes for their Tier 1 immune cell airspace-corrected cellularity ( Fig. 3 d and e) and proportions ( Figure S5a ) (Kruskal–Wallis test, significant where P < 0.05). Neutrophils, alongside a modest rise in mononuclear phagocytes, were seen in BRON but not DAD. Mononuclear phagocyte and lymphocyte infiltration represent the predominant immune cell hallmarks of COVID-19 DAD, with both showing increased proportions and airspace-adjusted cellularity as DAD evolved ( Fig. 3 c and d). Lymphocyte increases involved both CD4+ and CD8+ T cells and B-cells/plasma cells. Analysis of neutrophils with cells/mm 2 tissue prior to airspace correction was misleading, as this metric suggested an increase in DAD classes compared to PRESneg ( Figure S6 ). However, when applying proportion and airspace-adjusted cellularity metrics, no clinically meaningful differences in neutrophils were seen across any of the temporal phases of DAD and when compared with preserved tissue. Subgroup analysis was next performed with a focus on EDAD ROIs, with data points coded by sex, ethnicity, pandemic wave and age (<70 vs ≥70 years old). When our PacMap dimensionality reduction plot was coloured for these demographic differences, no clear difference in data spread was seen ( Figure S7 ). Comparisons between airspace-corrected cellularity were made for neutrophils, MnPs, T cells and B cells/plasma cells coded for sex, ethnicity, pandemic wave and age demonstrated only subtle differences including increased neutrophils and T cells in second wave compared to first wave EDAD ROIs which might be biologically meaningful if there was a difference in strain between waves and increased T cell infiltration in male compared to female EDAD ROIs which is less likely to be biologically meaningful. No differences were seen between the <70 and ≥70-year-old age cut-offs). Progressive loss of alveolar epithelial cells (AECs), vascular endothelial and lymphatic endothelial cells is seen in progressive COVID-19 DAD A reduction in numbers of AT1 cells from PRESneg to EDAD and from EDAD to ODAD was identified ( Fig. 3 e). AT2 cells maintained stable proportions with respect to preserved tissue however there was a meaningful decrease in MDAD and ODAD compared to PRESneg. Vascular endothelial cells and lymphatic endothelium also decreased as DAD progressed. Fig. 3 c shows raw IMC images and cluster maps for Tier 1 populations in all pathology classes, visually displaying variations in immune and structural populations. Individual immune cell phenotypes characterise temporal phases of the COVID-19 DAD continuum We next used a 38-marker panel with the FLOWSOM algorithm to identify 25 “Tier 2” clusters and used a Z score normalised heat map to annotate the cell types and states (see Fig. 4 a). We then focused on the PRES and DAD groups and the airspace-corrected cellularity metric, making comparisons between pathology groups (Kruskal–Wallis test, significant where P < 0.05). Figures S8–S10 contain analyses by other metrics. With respect to adaptive immune cells ( Fig. 4 b), the rises in lymphocytes seen in Tier 1 analysis were accounted for by increased memory CD4+ T cells, memory CD8+ T cells, CD4+ T cells, B cells and plasma cells. Plasma cell infiltration was particularly marked as DAD progressed which is highly biologically relevant. With respect to innate immune cells, although total neutrophil infiltration is not a hallmark of COVID-19, two phenotypic subsets of neutrophils characterised by interferon signalling (IFITM3 HI and STING HI ), MHC class I antigen presentation (beta-2 microglobulin HI ) and neutrophil-extracellular traps were markedly increased as DAD progressed as shown in Fig. 4 c. An inflammatory subset of mononuclear phagocytes (IL1R HI , IL6R HI and HLA-DR HI ) also increased in number from PRESneg to EDAD and again from EDAD to ODAD. A second cluster of macrophages, phenotypically consistent with M2 polarisation (CD206 HI ) were increased from PRESneg to DAD phases. No further increases were noted between EDAD, MDAD and ODAD, perhaps suggesting an exhausted reparative process. Amongst the structural clusters ( Fig. 4 d), we observed an AT1 and a CD4+ T cell cluster with markers suggestive of activated complement activity (C3–30 HI and B7 HI ) that were elevated in EDAD compared to PRESneg and ODAD. SARS-CoV-2 can activate the complement system via the classical, lectin and alternative pathways or indirectly through endothelial injury and thromboinflammation 30 and our results suggest a biologically plausible association with AT1 cells and a CD4+ T cells especially during early DAD. A subset of AT2 cells is seen falling as disease progresses which may indicate a known transition process to an AT1 phenotype to replace those lost in the tissue. 31 Critical immune cell interactions are established early, prior to overt tissue damage Analysis of cellular neighbourhoods at Tier 1 immune cell level is showed in interaction/avoidance heat maps for PRES and DADs ( Fig. 5 ). All other pathologies are shown in Figure S11 for Tier 1 and in Figure S12 for Tier 2. Quantitative comparison of a select group of highly biologically relevant interactions highlighted in Fig. 5 are shown in Figure S13 . Marked differences occurred between PRESneg and PRESpos, suggesting critical interactions are established early, prior to overt tissue damage. Notably, in PRESpos, neutrophils appear to interact more with AT2 cells, the primarily infected cell in lung tissue in previous literature, 32 and less with AT1 cells. The most striking specific difference was an increased interaction between neutrophils with interferon signalling and MHC class I antigen presentation markers and AT2 cells ( Figure S12 ). Additionally, we noted mononuclear phagocytes interacted more with both neutrophils and T cells consistent with innate-adaptive crosstalk ( Figure S13 ). Myeloid dysregulation has emerged as a major theme of severe or progressive COVID-19 and previous work reports both co-localisation of and crosstalk between cytotoxic CD8+ T cells with mononuclear phagocytes and neutrophils in areas of severe tissue damage. 33 Other marked interactions included neutrophils (interferon signalling) and mononuclear phagocytes with inflammatory markers (IL1R HI , IL6R HI and HLA-DR HI ) ( Figure S12 ). Compared to PRESneg tissue, PRESpos tissue showed increased interactions between or memory CD8+ T cells and a repair subset of macrophages (CD206 HI ) ( Figure S12 and S13 ). M2 macrophages are known for their roles in tissue repair and reduce inflammation via suppression of effector T cells, 34 indicating this process may start early, prior to overt tissue damage. Finally, B cells seemed to interact more with vascular endothelial cells in PRESpos compared to PRESneg, which may indicate early diapedesis and recruitment of antibody producing cells ( Figure S12 ). A more consistent interactome existed when comparing the DAD tissue phenotypes, however several notable changes were observed including 1) B cells/plasma cells increasing their interactions with mononuclear phagocytes and 2) T cells increasing their interactions with NK cells ( Fig. 5 , Figure S13 ).

Discussion In this study, we present a comprehensive assessment of the immune cell signature and structural cell composition in lung tissue from fatal COVID-19. Our data places particular emphasis on spatial and temporal differences in the heterogeneous patterns of tissue injury. We show that the pathological evolution of DAD, the archetypal lung pattern in COVID-19, is characterised by sustained increases in mononuclear phagocytes and lymphocytes without a shift in overall neutrophil counts but with shifts in functional neutrophil subsets. Within the structural compartments, there is a loss of AECs and endothelial cells. We confirm that significant airspace obliteration accompanies DAD progression and show this is a significant confounder in measuring relative and absolute cellularity in diseased lung tissue. Finally, critical immune and structural cell interactions occur prior to overt tissue injury. The major immune cell shifts detected in the COVID-19 lung have been significant macrophage infiltration, expansion of T and B lymphocytes and mesenchymal and fibroblastic proliferation. 15 , 18 However, interpretation of high resolution molecular pathology studies on COVID-19 PMLT has, to date, been limited by lack of discrimination between histologically different regions of interest 3 in highly heterogeneous tissue. 3 , 8 , 9 , 35 Rather, COVID-19 PMLT has hitherto been classified as ‘early’ or ‘late’ disease by chronological duration of illness, 15 by comparison of viral negative and viral positive areas, 36 , 37 by provision of an inflammation severity score, 2 severity of tissue injury 33 or simply being compared generally/collectively with non-infected control tissue. 19 Our approach is instead based on the temporal phases of COVID-19 DAD evolution rooted in standardised pathological terminology first established by Katzenstein et al. in the 1970's. 38 Erjefalt et al. (2022), using a multiplex immunohistochemistry platform also used the approach of discriminating between exudative, intermediate and organising DAD. 18 Their results are consistent with our findings showing macrophages, B cells and both CD4+ and CD8+ T lymphocytes gradually increasing as DAD progresses. Our findings confirm that mononuclear phagocyte infiltration is a major hallmark of COVID-19 lung tissue, proven across multiple modalities. 15 , 18 Alongside a depletion of lung resident alveolar macrophages, there is a concurrent accumulation of pro-inflammatory mononuclear phagocytes which are peripherally recruited given correlation with cells in corresponding peripheral blood samples. 39 Macrophage populations expressing pro-fibrotic genes similar to those found in idiopathic pulmonary fibrosis also accumulate. 40 We observed progressive infiltration of both an inflammatory subset of monocyte/macrophages (IL1R HI , IL6R HI and HLA-DR HI ) as well as a CD206 HI monocyte/macrophage subset most likely to represent tissue repair macrophages with M2 polarisation 41 as DAD progresses. The inflammatory group increased their interactions with interferon-responsive neutrophils early in disease progression, prior to overt tissue damage. This is interesting as prior imaging mass cytometry work noted a neutrophil pocket in an area with strong viral staining. Whilst this was in an area of severe tissue damage which were characterised partly by CD68+ macrophage infiltration, we may be detecting an early response signal. 33 It is reasonable to hypothesise that select neutrophil populations respond early to viral presence and interact with mononuclear phagocytes to prime or augment their response thus establishing areas of severe tissue damage. The repair group of mononuclear phagocytes also interact with T lymphocytes early in disease progression, prior to overt tissue damage. This may implicate early innate-adaptive crosstalk in the establishment of the repair process. These early interactions may be critical in establishing dysregulated inflammatory responses and the over-zealous, deleterious repair processes which seem to be driven by macrophages. Proactive targeted modification of such interactions at disease detection may have some clinical application, if not for COVID-19 then for other viral illnesses which can lead to ARDS. Clinical implications likely transcend the lungs given mononuclear phagocyte infiltration in COVID-19 has been observed in other tissues ranging from the heart 42 where they may be directly recruited by SARS-CoV-2-infected cardiomyocytes 43 and even to perivascular niches in brain tissue. 44 Similarly, our data shows that a second immune signature of COVID-19 DAD progression is a progressive infiltration of lymphocytes. 18 This rise was accounted for by naïve and memory CD4+ T cells, memory CD8+ T cells, B cells and plasma cells. T cells, similar to monocytes/macrophages are thought to have dual roles in COVID-19, from a protective response in mild to moderate disease to a dysregulated one in severe cases. 45 Lung resident and infiltrating B cells and plasma cells have received significantly less attention than T cells, although SARS-CoV-2-specific B cells have certainly been found in lung and lung-associated lymph nodal tissue. 46 Increased B lymphocytes in COVID-19 BALF correlate with evidence of severe disease. 47 Early recruitment and diapedesis of B lymphocytes/plasma cells is suggested from our results given their increased interaction with vascular endothelial cells in COVID positive compared to COVID negative tissue with preserved lung architecture. As DAD progresses however, there is continued plasma cell infiltration and increased B cell/plasma cell interactions with mononuclear phagocytes which may indicate a role in disease progression. Lung tissue is inherently collapsible and subject to both anatomic variation in inflation as well as variance in tissue preparation for histological sectioning. Whilst attempts at standardisation by post-mortem lung formalin insufflation have previously been described, 48 their routine use is impractical and unlikely to standardise inflation unless volume and pressure is personalised to the height and sex of the donor. In our study, all autopsies were performed under strict biohazard precautions meaning removal of the whole lungs and insufflation was also contraindicated. Variability in alveolar filling is notable across disease processes such as COVID-19 where alveolar type II cell destruction results in reduced surfactant production and reduced surface tension; airspace occlusion by oedema/haemorrhage/fibrin balls/neutrophil extracellular traps; and increased connective tissue production and contraction 49 can all contribute. Underpinning our data is the ability to quantify absolute and relative cellularity in the PMLT. However, the conventional measure of cellularity, cells/mm 2 of section area, used is confounded by variations in the area of sections occupied by airspace both in diseased and healthy lung. We showed that COVID-19 DAD progression is characterised by significant airspace obliteration, as reported in prior literature. 49 Using the conventional metric of cells/mm 2 , alveolar epithelium and vascular endothelium increased throughout DAD. An increase in alveolar cells was unexpected given SARS-CoV-2 infects them 32 and induces injury 38 and apoptosis. 50 However, application of an airspace correction factor showed a more plausible decline in alveolar epithelium as DAD progresses. A similar effect was also true of vascular endothelial cells. Application of an airspace correction factor showed a decline in vascular endothelium as DAD progresses. Whereas, the existing literature seems conflicted with observations of endothelialitis and endothelial apoptosis in COVID-19 PMLT 51 but also increased vascular density, enhanced angiogenic gene expression and neoangiogenesis by intussusceptive angiogenesis. 52 , 53 However, we are not the first to report a loss of endothelial cells specifically within areas of DAD 18 and certainly disruption of the barrier function contributes to the formation of pulmonary oedema through outward movement of fluid and macromolecules. 54 This discrepancy may be explained by mosaicism in vascular remodelling or damaged endothelial cells being undercounted by imaging mass cytometry. Regardless, this work confirmed that using cells/mm 2 is subject to an artefact from progressively obliterated airspaces and increased cellular tissue in the region of interest. To our knowledge, correcting for airspace is rarely used despite providing valuable information and should be considered for analysis of pliable tissue. We suspect it is most appropriately used in disease processes where airspace variability is secondary to primary airspace obliteration such as with progressive DAD rather than bronchopneumonia in which neutrophils invade the alveolar space. It may also be used to correct inflation/deflation artefact where insufflation is not or cannot be used. Another limitation of airspace correction lies is that non-cellular space is not exclusively air and includes other non-cellular material such as oedema. This study had several additional limitations. Clinical data available varied due to different collection across the three contributing biobanks; additionally, a subset died in the community with limited information prior to death; time to post-mortem varied and a level of tissue degradation might have occurred; though our control tissue appeared histologically normal, it was obtained from declined donor lungs and therefore by definition deemed unsuitable for transplant; due to the scarcity of organ donor lungs during the study period owing to the pandemic stage only two control donors were utilised however this was mitigated by using 15 ROIs from each donor; our antibody panel was not designed to target markers of fibrosis; there was no capability to confirm the specific SARS-CoV-2 variant each person was affected by therefore generalisability to current or future variants may be limited; finally, there would be a significant amount of confounding in this study which could not be controlled for example in hospital-based care where various treatments may have affected the immune response. In summary, we have presented a comprehensive assessment of the cellular signature of COVID-19 DAD progression using an airspace correction method to normalise cell counts and account for a progressive march towards airspace obliteration. Sustained increases in MnPs and lymphocytes and a loss of AECs and endothelial cells are the hallmark of COVID-19 DAD progression and although neutrophils were overall stable, there is a shift in several functional subsets. Finally, we performed a neighbourhood analysis focussed on the distinct temporal phases of DAD progression and identified that critical immune cell interactions occur early in the disease process, prior to overt tissue damage.

Denotes equal contribution by authors. Summary Background Lung damage in severe COVID-19 is highly heterogeneous however studies with dedicated spatial distinction of discrete temporal phases of diffuse alveolar damage (DAD) and alternate lung injury patterns are lacking. Existing studies have also not accounted for progressive airspace obliteration in cellularity estimates. We used an imaging mass cytometry (IMC) analysis with an airspace correction step to more accurately identify the cellular immune response that underpins the heterogeneity of severe COVID-19 lung disease. Methods Lung tissue was obtained at post-mortem from severe COVID-19 deaths. Pathologist-selected regions of interest (ROIs) were chosen by light microscopy representing the patho-evolutionary spectrum of DAD and alternate disease phenotypes were selected for comparison. Architecturally normal SARS-CoV-2-positive lung tissue and tissue from SARS-CoV-2-negative donors served as controls. ROIs were stained for 40 cellular protein markers and ablated using IMC before segmented cells were classified. Cell populations corrected by ROI airspace and their spatial relationships were compared across lung injury patterns. Findings Forty patients (32M:8F, age: 22–98), 345 ROIs and >900k single cells were analysed. DAD progression was marked by airspace obliteration and significant increases in mononuclear phagocytes (MnPs), T and B lymphocytes and significant decreases in alveolar epithelial and endothelial cells. Neutrophil populations proved stable overall although several interferon-responding subsets demonstrated expansion. Spatial analysis revealed immune cell interactions occur prior to microscopically appreciable tissue injury. Interpretation The immunopathogenesis of severe DAD in COVID-19 lung disease is characterised by sustained increases in MnPs and lymphocytes with key interactions occurring even prior to lung injury is established. Funding 10.13039/100014013 UK Research and Innovation / 10.13039/501100000265 Medical Research Council through the 10.13039/501100023449 UK Coronavirus Immunology Consortium , Barbour Foundation , 10.13039/501100017475 General Sir John Monash Foundation , 10.13039/501100000774 Newcastle University , 10.13039/100010089 JGW Patterson Foundation , 10.13039/100010269 Wellcome Trust . Keywords

Contributors Luke Milross MD : conceptualization, formal analysis, investigation, data curation, writing—original draft, visualisation; Bethany Hunter : methodology, validation, formal analysis, investigation, data curation, writing—original draft, visualisation; David McDonald PhD : formal ani.ealysis, investigation, data curation, writing—review & editing; George Merces PhD : methodology, software, formal analysis, data curation, writing—review & editing; Amanda Thomson : validation, writing—review & editing; Catharien M.U. Hilkens : data curation, writing—review & editing; John Wills PhD : software, formal analysis, writing—review & editing; Paul Rees PhD : software, formal analysis, writing—review & editing; Kasim Jiwa : resources, writing—review & editing; Nigel Cooper : resources, writing—review & editing; Joaquim Majo : cenceptualization, methodology, formal analysis, data curation, writing—review & editing; Helen Ashwin : data curation, writing—review & editing; Christopher JA Duncan DPhil : resources, validation, writing—review & editing; Paul M Kaye PhD : conceptualization, methodology, writing—review & editing; Omer Bayraktar PhD : conceptualization, methodology, writing—review & editing; Andrew Filby PhD : conceptualization, methodology, software, validation, formal analysis, investigation, resources, data curation, writing—original draft, writing—review & editing, visualisation, supervision, project administration; and Andrew J. Fisher PhD FRCP : conceptualization, methodology, formal analysis, resources, writing—original draft, writing—review & editing, supervision, project administration. Luke Milross, Bethany Hunter, David McDonald, George Merces, Andrew Filby and Andrew J. Fisher were involved in verification of the underlying data. All authors read and approved the final version of the manuscript. Data sharing statement The datasets generated for this study are available on reasonable request through contact to the following address: andrew.filby@newcastle.ac.uk . Declaration of interests L Milross was supported by a General Sir John Monash Scholarship awarded by the General Sir John Monash Foundation and a Vice-Chancellor's Global Scholarship from Newcastle University in support of a Master of Research in Immunobiology at Newcastle University. A Thomson was supported by funding from the JGW Patterson Foundation. C. J. A. Duncan was supported by a Wellcome Clinical Research Career Development Fellowship (211153/Z/18/Z).

Supplementary data Acknowledgements This work was partly funded by UKRI/ 10.13039/501100000265 Medical Research Council through the 10.13039/501100023449 UK Coronavirus Immunology Consortium (UK-CIC) as well as the Barbour Foundation. The authors would like to acknowledge the tissue donors and their families for their contribution to medical science, NOVOPATH for the supply and preparation of the tissue used in this study and other members of the NU-FCCF and BioImaging Unit for helpful discussions. Finally, we thank Catherine F. Hatton and Jarmila S. Spegarova for providing SARS-CoV-2 infected material as well as the NU-Infectious Diseases Facility (IDF) for providing an excellent and approved environment to work at level three pathogen containment.

CC BY

no

2024-01-16 23:42:01

eBioMedicine. 2023 Dec 23; 99:104945

oa_package/40/38/PMC10788437.tar.gz

PMC10788446

38226281

Introduction Metal-orgnaic frameworks (MOFs) are constructed by combining metal ions and organic linkers to form porous extended networks of different topologies [ 1 , 2 ]. The wide range of metal nodes and organic linkers, as well as the possibility of post-modifications, have resulted in the development of hundreds of thousands of MOFs structures [ 3 ]. Due to their unique characteristics, such as permanent porosity, controllable pore size and functionalization, good chemical and mechanical stability, MOFs have been employed as adsorbents [ 4 ], catalysts [ [5] , [6] , [7] ], supercapacitors [ 8 ] and drug delivery vehicles [ 9 ]. As adsorbents, MOFs showed high adsorption capacities for gaseous molecules (e.g. carbon dioxide, methane and hydrogen) [ 10 ], heavy metals (e.g. mercury, cadmium and lead) [ 11 ] and the separation of gases and other contaminants from different environments [ 12 , 13 ]. Among the large number of reported MOF structures, UiO-66 which is based on hexanuclear [Zr 6 O 4 (OH) 4 ] 12+ clusters connected to twelve other clusters via the bridging terephthalate linkers, is one of the most thermally and chemically stable MOFs [ 14 ]. UiO-66 and its functionalized derivatives have gained a lot of attention and were used in heterogeneous catalysis, gas separation and storage and water remediation. One of the derivatives, UiO-66(NH 2 ), which incorporates amine units in the backbone of the framework showed enhanced adsorption and catalytic properties compared to UiO-66 [ [15] , [16] , [17] , [18] ]. In addition to the amine functional groups, these UiO-based structures are characterized by the presence of structural defects which originate from the addition of monocarboxylates acids employed as modulators during the crystal synthesis. The modulators which compete with the organic linkers could be removed from the clusters through thermal activation, leading to the formation of structural defects. The latter demonstrated positive impact on the properties of UiO-66 structures, especially in applications such as catalysis and adsorption [ 19 , 20 ]. Therefore, investigating the characteristics of the surfaces of these frameworks such as the nature and distribution of functional groups, defects, surface energy and morphology is necessary to understand their behavior when they are in contact with gases, liquids or other environments. Molecular interactions at the surface of the solid are linked to the surface physicochemical properties which can be analyzed by the determination of the wettability and the calculation of the surface energy via values of contact angles of liquids deposited on the surface [ 21 ], calorimetry of adsorption and immersion of solids in a liquid medium [ 22 ], adsorption gas and the interpretation of adsorption isotherms whether obtained by static or dynamic methods. Spectroscopic methods, whether infrared, solid-state NMR or electron spectroscopy (ESCA) provide also information about a surface layer of a certain thickness [ 23 , 24 ]. An interesting field of application of MOF materials is their use in different types of chromatography, such as liquid [ 25 ] and gas phase chromatography [ 26 , 27 ]. For example, the separation of different mixtures of analytes, such as those of xylene isomers [ 28 ], n-alkanes [ 29 ], polychlorinated biphenyls [ 30 ], polycyclic aromatic hydrocarbons and branched alkanes [ 31 ] by MOF-based capillary GC has been demonstrated. Recently, MOFs crystals were employed as the stationary phase in inverse gas chromatography (IGC) at infinite dilution. The aim was not the separation process of the analytes but to study the physico-chemical and surface properties of the MOF through its interaction with probe molecules of different physical and chemical properties [ 32 ]. Indeed, IGC at infinite dilution helped in the determination of the surface energy parameters, in addition to the London dispersive surface energy and specific free variables through the injection of probe molecules at infinite dilution of different polarities and topologies [ 33 ]. In this study, IGC at infinite dilution was employed to investigate the surface properties of UiO-66(NH 2 ) crystals. This involved examining the dispersive surface energy of UiO-66(NH 2 ), investigating the specific interactions with polar probes, and estimating the Lewis acid-base parameters of the UiO-66(NH 2 ) structure. Furthermore, the obtained data were compared with those previously calculated for UiO-66 to understand the effect of the amine groups as well as the defect number on their surface energy and acid-base behavior.

Methodology Materials Zirconium chloride (ZrCl 4 , 98 %) and acetic acid (C 2 H 4 O 2 , 99 %) were purchased from Acros Organics. 2-Aminoterephthalic acid (C 8 H 7 NO 4 , 99 %) was purchased from Sigma Aldrich. The organic solvents at highly pure grade (99 %) were purchased from Fisher Scientific. General synthesis procedure of the UiO-66(NH 2 ) based MOFs The synthesis of UiO-66-(NH 2 ) particles was obtained by dissolving 617 mg of 2-Aminoterephthalic acid (3.4 mmol) and 795 mg of Zirconium chloride ZrCl 4 (3.4 mmol) in 250 mL of dichloromethane (DCM). The mixture was placed in a 500 mL autoclavable reagent bottle before being placed in a sonicator at room temperature. 15 mL of acetic acid was added to the resulting mixture before being placed back into the sonicator. After homogenization of the mixture, the bottle was tightly closed and placed in a preheated oven at 120 °C for 21 h. The obtained solution was then transferred to a falcon tube and the yellow precipitate was collected by centrifugation. The resulting MOF crystals was washed by dimethylformamide (DMF) for five consecutive times over three days then exchanged with DCM for three days. After removing the DCM by centrifugation and washing, the UiO-66-(NH 2 ) particles were putted in a vacuum oven at 150 °C overnight for thermal activation. The obtained crystals were characterized by PXRD, SEM, TGA and BET techniques and compared with previously reported samples of UiO-66-(NH 2 ) [ 34 ]. Methods of inverse gas chromatography The methods used in IGC are the same used in another study on UiO-66 [ 34 ] such as: the dispersive and non-dispersive parameters of adsorption based on Fowkes relation and developed by Dorris-Gray and Hamieh model, and the methods of Saint-Flour Papirer, Donnet et al. and Brendlé-Papirer. By using the above methods and molecular models, we were able to estimate the dispersive surface energy of UiO-66(NH 2 ) surface, the Gibbs free energy of solvents adsorbed on the solid particles, the specific variables of adsorption and the Lewis enthalpic and entropic acid base constants of UiO-66(NH 2 ).

Results and discussion Structural characterization of UiO-66(NH 2 ) catalyst The PXRD pattern of the synthesized UiO-66(NH 2 ) nanocrystals was recorded and compared to the simulated pattern ( Fig. 1 ). It showed narrow and sharp peaks that are in good agreement with the calculated one, which demonstrates the high crystallinity and the phase purity of the synthesized MOF. The SEM images of the synthesized crystals revealed also that UiO-66(NH 2 ) sample was pure with homogeneous truncated octahedral shaped crystals of around 100 nm. This crystal shape is typical for UiO-based MOF structures ( Fig. 2 ) [ 14 , 34 ]. The nitrogen sorption isotherm of the activated MOF showed an isotherm of type I which is consistent with the microporous nature of MOFs and depicting a monolayer adsorption on their surface ( Fig. 3 ). The calculated Brunauer–Emmett–Teller (BET) surface area was 703 m 2 /g and the pore volume was 0.478 cm 3 /g, which are in agreement with the reported values and lower than those of non-functionalized UiO-66 crystals [ 35 ]. This is probably due to the amine groups of the linker that are blocking the pores as it can be seen in the pore size distribution which reveals that the functionalized UiO-66 has smaller pore sizes compared to the non-functionalized ( Fig. S1 ) [ 36 ]. The thermogravimetric analysis (TGA) curve of UiO-66(NH 2 ) was measured and it showed ( Fig. 4 ). Three phases of weight loss could be distinguished. The first weight loss occurs approximately between 35 °C and 100 °C, where the adsorbed water on the surface of the MOF is volatized. The second weight loss is usually attributed to the removal of the monocarboxylate ligands and to the dehydroxylation of the zirconium clusters, and it extends from 100 °C till T link indicated in Fig. 4 . T link is the temperature after which the weight loss is attributed to the combustion of the linker. The third major weight loss in the TGA curve is assigned to the destruction of the framework of the MOF by the combustion of the organic linker. The change in the mass of the sample is attributed to the combustion of the linker which is determined and measured against the theoretical one. The difference between the theoretical and experimentally estimated mass loss is attributed to the presence of defects in the structure. In this method, it is assumed that 6(ZrO 2 ) is the only solid combustion product obtained for UiO-66 and their functionalized version. The combustion of the standard UiO-66 samples is given in the following equation: Theoretically, the weight loss plateau is the ratio of the molar mass of the hydroxylated UiO-66 to that of the 6 ZrO 2 . We first start by Normalizing the TGA curve to get a final weight percent at the end equal to 100 %, then the theoretical weight loss could be calculated given the following formula: where. : is the theoretical weight loss plateau of the studied hydroxylated MOF structure. : is the molecular weight of 6 ZrO 2 (g/mol). : is the final value of the weight-loss which is set to be 100 % in the normalized curve. However, the experimental weight loss plateau is the horizontal line that passes through the intercept between the TGA curve and vertical line at the temperature indicated T link . T link is the temperature after which the weight loss is attributed to the combustion of the linker. The value for is thus obtained experimentally from the TGA results. The theoretical weight loss attributed to one linker is the difference between the theoretical weight loss plateau and the final weight loss obtained divided by the theoretical number of linkers in the cluster. is thus calculated given the following formula: Where is the theoretical number of linkers per hydroxylated Zr 6 unit. Since the theoretical weight loss attributed to each linker is known, the actual number of linkers could be calculated as the ratio of the experimental and theoretical weight losses attributed to the linker, which is expressed as follows: The number of missing linkers, is then expressed as the difference between the theoretical number of linkers , and the experimental number of linkers . The number of missing linkers per cluster was estimated to be 1.56, which is higher than what we obtained for our previously reported UiO-66. All the characteristics extracted from the TGA, BET and SEM analysis were summarized in Table 1 and compared with our previously studied non-functionalized UiO-66 [ 35 ]. Surface properties of UiO-66(NH 2 ) catalyst surface by IGC Gas chromatograph conditions The experimental conditions of the IGC technique used in this study are similar to that used in our previous study [ 34 ]. The column was filled by 170 mg of UiO-66(NH 2 ) solid particles. The gas flow rate was optimized at 30 mL/min. The column temperatures were 220–270 °C, varied in 5 °C steps. The net retention volume was calculated by using the classical thermodynamical relations. The specific free enthalpy of adsorption Two methods were used in literature to determine the free enthalpy of adsorption of adsorption of organic solvents on the solid surfaces. They are represented by their reference states: Kemball and Rideal state [ 36 ] and De Boer et al. state [ 37 ]. In this study, we used the first state of Kemball and Rideal. The specific variables of adsorption such as the specific free enthalpy, enthalpy and entropy of adsorbed molecules on UiO-66(NH 2 ) were determined in the temperature interval [493.15K, 543.15K] with the help of molecular models and IGC methods. The dispersive surface energy of UiO-66(NH 2 ) The methods used to estimate the dispersive surface energy of UiO-66(NH 2 ) were based on the Fowlkes's classic relation. Nine methods were used: two based on Dorris-Gray relation, one used our model and six methods used the various molecular models of the surface area of n-alkanes. Hamieh et al. method [ 38 , 39 ] took into account the molecular models of n-alkanes and polar molecules as well as the variations of the surface area as a function of the temperature. The above methods and models were applied to determine the values of of UiO-66(NH 2 ) powder at different temperatures ( Fig. 5 ). The curves of Fig. 5 proved a decreasing variation of the dispersive surface energy of UiO-66(NH 2 ) solid particles against the temperature. The more accurate model used for the determination of is that proposed by Hamieh et al. [ 35 ]. The results of Fig. 5 showed that the curve representing Hamieh model can be considered as the average mean curve proving the important effect of the temperature on the surface area of organic solvents. The linear variations of were given on Table 2 , satisfying the following relation: Where a and b are respectively given by: and . The values of the dispersive surface entropy of UiO-66(NH 2 ) vary from model to another. The largest value was obtained with the spherical model that also gave the highest value of the extrapolated dispersive surface energy . On Fig. 6 , The values of and of UiO-66(NH 2 ) showed similar increase between their respective representative curves. The lowest values were obtained for Gray method and geometric model; whereas, the highest values were observed with the spherical model that overestimated the surface energy for the different used models. The highest values of and (in absolute value) are obtained successively for models taking into account the thermal effect such as Redlich-Kwong model and Hamieh models. The deviation of the spherical model is certainly due to the fact of the overestimation of the surface are of molecules. Fig. 5 , Fig. 6 and Table 2 showed closer similarity between Redlich-Kwong, Hamieh and Dorris-Gray-Hamieh models. In fact, these three models used the thermal effect on the surface areas of n-alkanes with more accurate estimation when using Hamieh model which determined more accurately the surface areas of molecules. By applying Hamieh model, we obtained the variations of of UiO-66(NH 2 ) particles: Determination of the specific free energy and acid-base properties of UiO-66(NH 2 ) particles On Tables S1–S10 , we gave the obtained variations of the specific free energy ( ) of adsorption of the polar molecules on UiO-66(NH 2 ) surface by using the three methods of Brendlé-Papirer [ 40 ], Donnet et al. [ 41 ] and Saint-Flour-Papirer [ 42 ] and the other models [ 39 ]. Tables S1–S10 allowed to obtain the linear relations of the specific free enthalpy ( ) as a function of the temperature relative to the various polar molecules by using the different IGC models and methods. The values of ( ) presented on these Tables, at a fixed temperature, vary from one model to another. These variations can be in certain models three times higher than the other methods or models. The curves plotted on Fig. 7 for dichloromethane and chloroform showed the large difference between the values of the specific free energy of an organic probe when the applied model changed. IGC is considered to be an excellent technique to characterize the solid substrates, however, large differences between the obtained values of the specific parameters of adsorption of polar solvents on a solid surface at fixed temperature were observed. In fact, only Hamieh model proved its validity in the determination of both the dispersive surface energy and specific variables of adsorption. This is due to the fact that the thermal effect on the surface area was taken into account by this model. In literature, many scientists neglected the effect of the temperature on the value of the surface area of organic molecules and consequently, the determination of the specific free enthalpy and the dispersive surface energy of materials were not accurate. In our study, Hamieh model was demonstrated to be the most accurate method followed successively by the methods of Saint-Flour Papirer, Donnet et al. and Brendlé-Papirer. Enthalpic acid base constants In order to compare between the various IGC methods used in this study, the values of the specific enthalpy ( and specific entropy of adsorption ( of organic molecules on UiO-66(NH 2 ) solid particles were given in Table 3 , Table 4 . These results gave different values of the specific enthalpy and entropy according to the used IGC method. The same difficulties previously encountered with the values of the specific free enthalpy were also observed here with the values of ( and ( . The previous conclusion about the accurate results of Hamieh model is also valid in this case. The large differences between the obtained values of ( and ( depending on the chosen method or model led to different values of the Lewis acid-base constants and then different characteristics for the same solid substrates. To clarify this, the evolution of and as a function of were plotted in Fig. 8 , Fig. 9 for the various methods or models. The obtained results were summarized in Table 5 and showing the different values of the enthalpic acid base constants and and entropic acid base parameters and according to the used IGC method. Table 5 proved the higher acidic character of UiO-66(NH 2 ) crystals in Lewis terms according to Hamieh model. These values are in agreement with the previous work on this defected MOF as catalyst for esterification reactions which require an acidic behavior of the MOF surface [ [35] , [36] , [37] , 43 ]. The defected nature of this MOF was also highlighted by the TGA analysis showing 1.56 missing linkers per cluster resulted in the creation of Lewis acid sites on the Zr-clusters. The acidic character of UiO-66(NH 2 ) was also proved by all IGC used methods or models with an advantage to Hamieh model taking into account the thermal effect. Comparison with UiO-66 In a previous study [ 35 ], Hamieh model was employed to estimate the specific parameters, Lewis Acid-Base constants and of UiO-66. The obtained equation of UiO-66 solid surface is given below against the temperature: Hamieh et al. [ 35 ] also showed the acidic character of UiO-66 surface and determined its acid and base constants: In this study, we proved that the presence of amine groups in UiO-66 decreased the specific surface area, pore volume and particle size, but also increased the number of defects in cluster. The determination of of UiO-66(NH 2 ) by using Hamieh model gave the following relation: By comparing the two MOFs UiO-66 and UiO-66(NH 2 ), It can be clearly noticed that the surface energy of UiO-66(NH 2 ) is greater than that for UiO-66 for all molecular models used. The introduction of NH 2 groups in the backbone of the UiO-66 structure resulted in an increase in the London dispersive surface energy. The constants and of UiO-66(NH 2 ) were determined: In terms of acidity, we observed that the acid character is greater than the basic character for both MOFs. By comparing the acid-base constants of these two MOFs, we notice that the acid constant for UiO-66(NH 2 ) is clearly greater than that of UiO-66. The ratio between the two acid constants is given by: The above ratio greater than 1 is certainly due to the fact that the number of defects in the structure of UiO-66(NH 2 ) is greater than that in UiO-66, therefore, the number of acid sites in UiO-66(NH 2 ) is greater than that in UiO-66, for this we notice that the acidity of UiO-66(NH 2 ) is greater than that of UiO-66. At the level of basicity, we notice that the basic character at the level of UiO-66(NH 2 ) is even greater than in UiO-66. The ratio between the two basic constants is given by: This is due to the basic functional group NH 2 which is present in the structure of UiO-66(NH 2 ). The NH 2 groups of UiO-66(NH 2 ) have increased the basicity constant. The Lewis acid base sites of UiO-66(NH 2 ) have both increased with respect to UiO-66.

Results and discussion Structural characterization of UiO-66(NH 2 ) catalyst The PXRD pattern of the synthesized UiO-66(NH 2 ) nanocrystals was recorded and compared to the simulated pattern ( Fig. 1 ). It showed narrow and sharp peaks that are in good agreement with the calculated one, which demonstrates the high crystallinity and the phase purity of the synthesized MOF. The SEM images of the synthesized crystals revealed also that UiO-66(NH 2 ) sample was pure with homogeneous truncated octahedral shaped crystals of around 100 nm. This crystal shape is typical for UiO-based MOF structures ( Fig. 2 ) [ 14 , 34 ]. The nitrogen sorption isotherm of the activated MOF showed an isotherm of type I which is consistent with the microporous nature of MOFs and depicting a monolayer adsorption on their surface ( Fig. 3 ). The calculated Brunauer–Emmett–Teller (BET) surface area was 703 m 2 /g and the pore volume was 0.478 cm 3 /g, which are in agreement with the reported values and lower than those of non-functionalized UiO-66 crystals [ 35 ]. This is probably due to the amine groups of the linker that are blocking the pores as it can be seen in the pore size distribution which reveals that the functionalized UiO-66 has smaller pore sizes compared to the non-functionalized ( Fig. S1 ) [ 36 ]. The thermogravimetric analysis (TGA) curve of UiO-66(NH 2 ) was measured and it showed ( Fig. 4 ). Three phases of weight loss could be distinguished. The first weight loss occurs approximately between 35 °C and 100 °C, where the adsorbed water on the surface of the MOF is volatized. The second weight loss is usually attributed to the removal of the monocarboxylate ligands and to the dehydroxylation of the zirconium clusters, and it extends from 100 °C till T link indicated in Fig. 4 . T link is the temperature after which the weight loss is attributed to the combustion of the linker. The third major weight loss in the TGA curve is assigned to the destruction of the framework of the MOF by the combustion of the organic linker. The change in the mass of the sample is attributed to the combustion of the linker which is determined and measured against the theoretical one. The difference between the theoretical and experimentally estimated mass loss is attributed to the presence of defects in the structure. In this method, it is assumed that 6(ZrO 2 ) is the only solid combustion product obtained for UiO-66 and their functionalized version. The combustion of the standard UiO-66 samples is given in the following equation: Theoretically, the weight loss plateau is the ratio of the molar mass of the hydroxylated UiO-66 to that of the 6 ZrO 2 . We first start by Normalizing the TGA curve to get a final weight percent at the end equal to 100 %, then the theoretical weight loss could be calculated given the following formula: where. : is the theoretical weight loss plateau of the studied hydroxylated MOF structure. : is the molecular weight of 6 ZrO 2 (g/mol). : is the final value of the weight-loss which is set to be 100 % in the normalized curve. However, the experimental weight loss plateau is the horizontal line that passes through the intercept between the TGA curve and vertical line at the temperature indicated T link . T link is the temperature after which the weight loss is attributed to the combustion of the linker. The value for is thus obtained experimentally from the TGA results. The theoretical weight loss attributed to one linker is the difference between the theoretical weight loss plateau and the final weight loss obtained divided by the theoretical number of linkers in the cluster. is thus calculated given the following formula: Where is the theoretical number of linkers per hydroxylated Zr 6 unit. Since the theoretical weight loss attributed to each linker is known, the actual number of linkers could be calculated as the ratio of the experimental and theoretical weight losses attributed to the linker, which is expressed as follows: The number of missing linkers, is then expressed as the difference between the theoretical number of linkers , and the experimental number of linkers . The number of missing linkers per cluster was estimated to be 1.56, which is higher than what we obtained for our previously reported UiO-66. All the characteristics extracted from the TGA, BET and SEM analysis were summarized in Table 1 and compared with our previously studied non-functionalized UiO-66 [ 35 ]. Surface properties of UiO-66(NH 2 ) catalyst surface by IGC Gas chromatograph conditions The experimental conditions of the IGC technique used in this study are similar to that used in our previous study [ 34 ]. The column was filled by 170 mg of UiO-66(NH 2 ) solid particles. The gas flow rate was optimized at 30 mL/min. The column temperatures were 220–270 °C, varied in 5 °C steps. The net retention volume was calculated by using the classical thermodynamical relations. The specific free enthalpy of adsorption Two methods were used in literature to determine the free enthalpy of adsorption of adsorption of organic solvents on the solid surfaces. They are represented by their reference states: Kemball and Rideal state [ 36 ] and De Boer et al. state [ 37 ]. In this study, we used the first state of Kemball and Rideal. The specific variables of adsorption such as the specific free enthalpy, enthalpy and entropy of adsorbed molecules on UiO-66(NH 2 ) were determined in the temperature interval [493.15K, 543.15K] with the help of molecular models and IGC methods. The dispersive surface energy of UiO-66(NH 2 ) The methods used to estimate the dispersive surface energy of UiO-66(NH 2 ) were based on the Fowlkes's classic relation. Nine methods were used: two based on Dorris-Gray relation, one used our model and six methods used the various molecular models of the surface area of n-alkanes. Hamieh et al. method [ 38 , 39 ] took into account the molecular models of n-alkanes and polar molecules as well as the variations of the surface area as a function of the temperature. The above methods and models were applied to determine the values of of UiO-66(NH 2 ) powder at different temperatures ( Fig. 5 ). The curves of Fig. 5 proved a decreasing variation of the dispersive surface energy of UiO-66(NH 2 ) solid particles against the temperature. The more accurate model used for the determination of is that proposed by Hamieh et al. [ 35 ]. The results of Fig. 5 showed that the curve representing Hamieh model can be considered as the average mean curve proving the important effect of the temperature on the surface area of organic solvents. The linear variations of were given on Table 2 , satisfying the following relation: Where a and b are respectively given by: and . The values of the dispersive surface entropy of UiO-66(NH 2 ) vary from model to another. The largest value was obtained with the spherical model that also gave the highest value of the extrapolated dispersive surface energy . On Fig. 6 , The values of and of UiO-66(NH 2 ) showed similar increase between their respective representative curves. The lowest values were obtained for Gray method and geometric model; whereas, the highest values were observed with the spherical model that overestimated the surface energy for the different used models. The highest values of and (in absolute value) are obtained successively for models taking into account the thermal effect such as Redlich-Kwong model and Hamieh models. The deviation of the spherical model is certainly due to the fact of the overestimation of the surface are of molecules. Fig. 5 , Fig. 6 and Table 2 showed closer similarity between Redlich-Kwong, Hamieh and Dorris-Gray-Hamieh models. In fact, these three models used the thermal effect on the surface areas of n-alkanes with more accurate estimation when using Hamieh model which determined more accurately the surface areas of molecules. By applying Hamieh model, we obtained the variations of of UiO-66(NH 2 ) particles: Determination of the specific free energy and acid-base properties of UiO-66(NH 2 ) particles On Tables S1–S10 , we gave the obtained variations of the specific free energy ( ) of adsorption of the polar molecules on UiO-66(NH 2 ) surface by using the three methods of Brendlé-Papirer [ 40 ], Donnet et al. [ 41 ] and Saint-Flour-Papirer [ 42 ] and the other models [ 39 ]. Tables S1–S10 allowed to obtain the linear relations of the specific free enthalpy ( ) as a function of the temperature relative to the various polar molecules by using the different IGC models and methods. The values of ( ) presented on these Tables, at a fixed temperature, vary from one model to another. These variations can be in certain models three times higher than the other methods or models. The curves plotted on Fig. 7 for dichloromethane and chloroform showed the large difference between the values of the specific free energy of an organic probe when the applied model changed. IGC is considered to be an excellent technique to characterize the solid substrates, however, large differences between the obtained values of the specific parameters of adsorption of polar solvents on a solid surface at fixed temperature were observed. In fact, only Hamieh model proved its validity in the determination of both the dispersive surface energy and specific variables of adsorption. This is due to the fact that the thermal effect on the surface area was taken into account by this model. In literature, many scientists neglected the effect of the temperature on the value of the surface area of organic molecules and consequently, the determination of the specific free enthalpy and the dispersive surface energy of materials were not accurate. In our study, Hamieh model was demonstrated to be the most accurate method followed successively by the methods of Saint-Flour Papirer, Donnet et al. and Brendlé-Papirer. Enthalpic acid base constants In order to compare between the various IGC methods used in this study, the values of the specific enthalpy ( and specific entropy of adsorption ( of organic molecules on UiO-66(NH 2 ) solid particles were given in Table 3 , Table 4 . These results gave different values of the specific enthalpy and entropy according to the used IGC method. The same difficulties previously encountered with the values of the specific free enthalpy were also observed here with the values of ( and ( . The previous conclusion about the accurate results of Hamieh model is also valid in this case. The large differences between the obtained values of ( and ( depending on the chosen method or model led to different values of the Lewis acid-base constants and then different characteristics for the same solid substrates. To clarify this, the evolution of and as a function of were plotted in Fig. 8 , Fig. 9 for the various methods or models. The obtained results were summarized in Table 5 and showing the different values of the enthalpic acid base constants and and entropic acid base parameters and according to the used IGC method. Table 5 proved the higher acidic character of UiO-66(NH 2 ) crystals in Lewis terms according to Hamieh model. These values are in agreement with the previous work on this defected MOF as catalyst for esterification reactions which require an acidic behavior of the MOF surface [ [35] , [36] , [37] , 43 ]. The defected nature of this MOF was also highlighted by the TGA analysis showing 1.56 missing linkers per cluster resulted in the creation of Lewis acid sites on the Zr-clusters. The acidic character of UiO-66(NH 2 ) was also proved by all IGC used methods or models with an advantage to Hamieh model taking into account the thermal effect. Comparison with UiO-66 In a previous study [ 35 ], Hamieh model was employed to estimate the specific parameters, Lewis Acid-Base constants and of UiO-66. The obtained equation of UiO-66 solid surface is given below against the temperature: Hamieh et al. [ 35 ] also showed the acidic character of UiO-66 surface and determined its acid and base constants: In this study, we proved that the presence of amine groups in UiO-66 decreased the specific surface area, pore volume and particle size, but also increased the number of defects in cluster. The determination of of UiO-66(NH 2 ) by using Hamieh model gave the following relation: By comparing the two MOFs UiO-66 and UiO-66(NH 2 ), It can be clearly noticed that the surface energy of UiO-66(NH 2 ) is greater than that for UiO-66 for all molecular models used. The introduction of NH 2 groups in the backbone of the UiO-66 structure resulted in an increase in the London dispersive surface energy. The constants and of UiO-66(NH 2 ) were determined: In terms of acidity, we observed that the acid character is greater than the basic character for both MOFs. By comparing the acid-base constants of these two MOFs, we notice that the acid constant for UiO-66(NH 2 ) is clearly greater than that of UiO-66. The ratio between the two acid constants is given by: The above ratio greater than 1 is certainly due to the fact that the number of defects in the structure of UiO-66(NH 2 ) is greater than that in UiO-66, therefore, the number of acid sites in UiO-66(NH 2 ) is greater than that in UiO-66, for this we notice that the acidity of UiO-66(NH 2 ) is greater than that of UiO-66. At the level of basicity, we notice that the basic character at the level of UiO-66(NH 2 ) is even greater than in UiO-66. The ratio between the two basic constants is given by: This is due to the basic functional group NH 2 which is present in the structure of UiO-66(NH 2 ). The NH 2 groups of UiO-66(NH 2 ) have increased the basicity constant. The Lewis acid base sites of UiO-66(NH 2 ) have both increased with respect to UiO-66.

Conclusions The specific free energy, enthalpy and entropy of adsorption of polar organic solvents adsorbed on UiO-66(NH 2 ) surface were evaluated by using ten different IGC methods and models included Hamieh model that took into account the thermal effect. The seven molecular models were used to determine the dispersive component of the surface energy of UiO-66(NH 2 ) solid particles. The results obtained by applying Hamieh model showed a strong acid character of the used MOF with an acid base ratio greater than 2. The same result was observed with the entropic acid base constant. One obtained the equation of the dispersive surface energy against the temperature: The comparison between the obtained results with UiO-66(NH 2 ) and that of UiO-66 surface led to conclude that the presence of amine groups in the backbone of the framework decreased the specific surface area, the pore volume and the particle size, but increased the dispersive surface energy and the acid base character of the MOF structure.

Amino-functionalized metal organic frameworks (MOFs) have attracted much attention for various applications such as carbon dioxide capture, water remediation and catalysis. The focus of this study is to determine the surface and Lewis's acid-base properties of UiO-66(NH 2 ) crystals by the inverse gas chromatography (IGC) technique at infinite dilution. The latter was applied to evaluate the dispersive component of the surface energy by using thermal model and several molecular models. The obtained results proved that decreases when the temperature increases. The best results were achieved by using the thermal model that takes into account the effect of the temperature on the surface areas of the organic molecules. We also observed a decrease of the Gibbs surface free energy of adsorption by increasing the temperature of the different organic solvents. The polar interactions of UiO-66(NH 2 ) were obtained by using the methods of Saint-Flour Papirer, Donnet et al., Brendlé-Papirer and the different molecular models. The Lewis's acid base constants and were further calculated by determining the different variables of adsorption of the probes on the solid surface and the obtained values were 1.07 and 0.45 for and respectively, with an acid-base ratio ( K A /K D ) of 2.38. These values showed the high acidic surface of the solid substrate; whereas, the values of the entropic acid base parameters, , and respectively equal to , and , also highlighted the important acidity of UiO-66-(NH 2 ) surface. These important findings suggest that the surface defects (missing linkers and/or clusters) in UiO-66(NH 2 ) are the main determining factor of the acid-base properties of UiO-66 based structures. Graphical abstract Highlights • Several IGC methods and models were used to determine of a UiO-66(NH2). • Hamieh model taking into account the thermal effect gave the more precise results. • The London dispersive surface energy and specific free variables were determined. • The UiO-66(NH2) surface exhibited higher acceptor character. • The addition of amine groups in UiO-66 decreased the surface energy but increased the acid-base behavior. Keywords

Ethical approval This article does not contain any studies with human participants performed by any of the authors. Data availability statement Data are included in the article and in supplementary material. CRediT authorship contribution statement Ali Ali-Ahmad: Writing – review & editing, Writing – original draft, Validation, Methodology, Investigation, Formal analysis. Tayssir Hamieh: Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization. Thibault Roques-Carmes: Writing – original draft, Validation, Supervision, Methodology, Investigation, Formal analysis, Conceptualization. Mohamad Hmadeh: Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization. Joumana Toufaily: Writing – original draft, Validation, Supervision, Resources, Project administration, Investigation, Funding acquisition, Formal analysis, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary data The following is the Supplementary data to this article:

CC BY

no

2024-01-16 23:42:01

Heliyon. 2023 Dec 17; 10(1):e23839

oa_package/08/d9/PMC10788446.tar.gz

PMC10788447

38226274

Introduction In an ever-evolving market driven by technological advancements and increasing consumer purchasing power, the pursuit of novel products and services remains constant. However, the path to success in New Product Development (NPD) projects is often fraught with challenges, leading to failure either during the later stages of development or upon commercialization. These failures are frequently rooted in the crucial initial stages of NPD, commonly known as the front end [ 1 ]. Failure of a product refers to the state or circumstance of not fulfilling the intended objective or expectations of the intended audience. Product failures occur when a new product fails to generate sufficient revenue following its launch, resulting in its eventual downfall. When a product does not pay its costs and marketing expenses, it is considered a tremendous failure. Typically, a product's failure occurs during its utilisation period [ 2 ]. Numerous factors are identified in the literature that contribute to product development failure, with an insufficient customer focus often standing as a primary concern. The best defensive strategy is to cater to consumer wants and needs. Products that do not satisfy a specific consumer demand struggle to outcompete established brands. Ineffective communication strategies supporting the launch of a new product often lead to its downfall. A product is likely to be perceived as unique if it performs a new function or an old function in a unique way, or if it holds a competitive edge in pricing and performance. Effective customer-centric companies have systems and processes in place to capture diverse customer requirements, transforming them into robust specification requirements that can guide the NPD team. Product failure can stem from inadequate marketing planning. Effective positioning and marketing are crucial for conveying the product's benefits and competitive edge [ 3 ]. An ineffective marketing strategy can lead to the product's downfall if it fails to guide potential customers through the various stages of the buying process [ 4 ]. Despite careful planning and strategizing, a product may still fail if the marketing budget falls short or the execution of the marketing plan is flawed. Success in the market is largely determined by optimal product launch timing. Anticipating and capitalizing on market opportunities before competitors is crucial. While being first-to-market isn't always advantageous, excessive delay or ill-timed launch may result in decreased customer demand by the time the product enters the commercialization phase [ 5 ]. It's often seen that companies launch unfinished products out of fear of falling behind, resulting in iterative versions with minor enhancements. Besides that, product failure often stems from technical product defects. Overengineering may provide a technological advantage but can also result in high costs to both the company and the consumer, thereby giving competitors an upper hand. While it's important to address technical flaws, this shouldn't come at an exorbitant cost. The repercussions of poor quality can outweigh the advantages of a new product launch, potentially inflicting devastating damage on the product's or company's brand [ 6 , 7 ]. This paper is set out to identify and scrutinize the pivotal factors and challenges related to new product development. Consequently, the study poses two research questions, 1. What are the factors that lead to successful product development? 2. What internal and external obstacles are encountered in the product development process? To comprehensively answer these research questions, the study sets forth two primary objectives: the first objective is to explore the critical success factors in product development. This objective involves in-depth analysis and examination of various critical success factors influencing the outcome of product development projects. By understanding these factors, organizations can improve their NPD processes and enhance their chances of creating successful products. The second objective is to explore anticipated challenges in product development. This necessitates the identification and analysis of internal and external hurdles encountered during the different stages of product development. Understanding these challenges will help organizations anticipate and overcome potential obstacles, ensuring smoother product development processes. This study aims to shed light on the critical factors and challenges influencing new product development success. By answering the research questions and meeting the research objectives, the study seeks to contribute valuable knowledge to the field and offer practical guidance to companies engaged in product development activities. With a comprehensive understanding of the complexities and nuances involved in NPD, organizations can effectively navigate the landscape and increase their chances of creating successful products that resonate with customers and thrive in the market.

Materials and methods Research design In addition to conducting literature research, this study incorporates a one-to-one interview with the CEO of a Malaysia-based company who plays a pivotal role in the success of the firm's product and service development. The one-to-one interview method is widely utilized for data collection purposes. Individual interviews are recognized as a valuable approach for gathering comprehensive and in-depth data, providing valuable insights into individuals' perceptions, understandings, and experiences related to a specific phenomenon [ 62 ]. Data collection Data was collected through an interview with Protenga, a leading insect-based company originating in Singapore and now operating from a pilot facility in Malaysia. Since its inception in 2018, Protenga has garnered international acclaim, carving a niche for itself as a frontrunner in Malaysia's insect industry. The interviewee, Leo Wein, serves as both the CEO and founder of Protenga. With substantial experience in introducing new products and services to mature markets, Mr. Wein's insights are crucial to this research. As the primary informant for the company, he was the solitary participant in the interview. Given the safety precautions necessitated by the Covid-19 pandemic, the interview was conducted virtually. A comprehensive questionnaire containing 24 items was emailed to Mr. Wein. The objective of this set of questions was to comprehend the strategies Protenga employed to surmount the hurdles encountered during its nascent stage, and how it successfully launched innovative products into the marketplace. Data analysis The analytical framework for this study will rely on thematic content analysis to dissect the data obtained from the interview. Thematic analysis is a method used in qualitative research to analyze data and identify patterns or themes within it. It is considered a foundational component of qualitative research [ 63 ]. Beyond the thematic analysis of primary interview data, the secondary data is organized in a tabulated form with checkboxes in each column. Each area is labeled according to the source of the research paper, and the record consists of a list of aspects mentioned in the publications. By utilizing checkboxes, it becomes possible to determine the variables that were most frequently mentioned as important factors in the success of new product development. Background of protenga Protenga, established in 2016 and headquartered in Singapore, operates from its pilot facility in Johor, Malaysia. The company specializes in the breeding, farming, and production of products derived from the Black Soldier Fly (BSF). In a discussion with Leo, the founder and CEO of Protenga, he delineated the company's aspiration to address the global environmental crisis. Portraying Protenga as a firm that merges insect technology with nutrition, Leo emphasized the deployment of technologically advanced insect farming systems to promote circular nutrient systems. This allows Protenga to manufacture eco-friendly protein for animal feed, as well as pet food. The company's innovation stems from its use of the BSF lifecycle, establishing a symbiotic relationship between these insects and humans. As Leo elucidated during the interview, these insects have a dual role in the ecosystem - decomposing organic matter at the end of its life cycle and serving as a food source for other creatures. Inspired by this inherent circularity, Protenga developed technology to bring this natural cycle into the human food system. Their aim is to harness this technology to produce sustainable and high-quality feed and food products. Protenga businesses Protenga has diversified its portfolio to include three key products: fertilizer, protein, and oil. These are derived from various life cycles and processes at the company's Black Soldier Fly (BSF) farm, yielding versatile products applicable to industries such as agriculture, livestock, and aquaculture. Protenga's pricing strategy is tailored to each customer order. Products are benchmarked against market equivalents, such as fish meal (RM 4-6 k), fish oil (RM 4-6 k), and composted poultry manure (RM 400–800). Operating as an integrated entity, Protenga covers the entire value chain, from primary resource production to supplying finished products. Their latest venture, YumGrubs, operates on a Business-to-Consumer/Direct-to-Consumer (B2C/D2C) model, directly selling their fast-moving consumer goods (FMCG) to end users. To reach their target market, digital marketing, e-commerce platforms, and content/social marketing strategies are leveraged. In terms of their Business-to-Business (B2B) offerings, Protenga adheres to traditional marketing strategies, with an emphasis on nurturing personal customer relationships which fosters trust and facilitates the formation of enduring business partnerships.

Results Applying the thematic analysis initially resulted in the identification of 13 potential themes. However, after thoroughly examining the interview content and correlating the context with the proposed themes, the number was refined down to five key themes as below. For better illustration, please see Fig. 1 . Innovative idea In response to the question, ‘What opportunity did you identify that motivated the inception of an insect-based business?’, the CEO articulated: ‘I envisioned an opportunity to design a technology that would render this natural insect-driven process amenable to the human food system, thus facilitating the production of sustainable, high-quality food and food products.’ Innovations in technology usher in new product development opportunities. The implementation of state-of-the-art technology is integral to the successful creation of superior products. The CEO concurs, asserting that the firm is offering solutions to global issues such as food shortage and excessive waste: ‘Indeed, our approach contributes to circular economy solutions within the food system.' Placement of a structured NPD process The responsibility of management in relation to the venture team is to architect the NPD framework, guidelines, and benchmarks. This strategic planning facilitates clarity for team members regarding their roles and how to navigate the NPD process. Since 2016, Protenga has executed meticulous and organized research and development in fields encompassing biology, entomology, engineering, technology, and of course, business development. The CEO affirmed: “Our production system is grounded in extensive basic and applied research conducted since 2016.” NPD approaches should underscore quality throughout the rollout phase. Moreover, these procedures must display flexibility, with the capability to merge phases, execute them simultaneously, or eliminate them upon thoughtful consideration. Involvement of cross-functional teams In response to inquiries about his management style, the CEO revealed that they have established leadership principles at Protenga. ● Utilizing Insects to Our Advantage ● Initiating Actions and Valuing Independence ● Balancing Freedom and Responsibility ● Prioritizing Purpose, Humbling Ego From these principles, they have fostered an encouraging, inclusive, and results-oriented team culture. The CEO further elaborated, ‘We are accountable to each other, maintaining transparency and honesty in our communication.’ Cross-functional venture teams often operate with a degree of autonomy, displaying a mix of entrepreneurial attributes that enhance each other, thereby boosting process performance and outcomes. The variety of perspectives inherent in cross-functional collaboration promotes innovation. Challenges: internal challenges In response to the query regarding current challenges that require future amelioration, the CEO stated, “We have a competitive stance overall. However, being based in Malaysia, we encounter market access hurdles, for instance, to the EU, which we need to tackle in cooperation with the relevant authorities. We are still evolving and enhancing; hence our production volumes require a significant increase to reach their full potential." For a nascent company like Protenga, constrained resources undoubtedly pose one of the greatest hurdles to scaling up production. This is not only from a financial perspective but also considering intangible assets of the company, such as employee skill sets and human resources. External challenges In discussing the challenges encountered during the export process, the CEO highlighted the complexity of differing rules and regulations imposed by various countries. What is permissible in one country may not necessarily be acceptable in another. It is therefore vital to understand the laws stipulated by the importing country to facilitate a seamless transaction. In terms of licenses obtained by Protenga, given its production of consumable goods, the CEO confirmed, “We hold a Malaysian manufacturing license, production license for each product, sales license, and local business license. Additionally, we've acquired several free sale certificates for export." In regards to the attitudes of Malaysians and the government towards food scarcity and excessive waste, and the actions the CEO might suggest, he said, “I'm not in a position to judge the level of seriousness attributed to these issues. However, I do see certain initiatives and policies being developed or already in place, which is promising. For instance, the government agency BioEconomy Corp is fostering the agtech and biotech field in Malaysia. Yet, we certainly hope to see more meaningful and impactful adoption of these initiatives. For instance, mandatory food waste segregation could be a significant step towards a sustainable food system, but we are still a considerable distance from that in Malaysia." Food scarcity and excessive waste are globally critical issues, and Malaysia should give them due attention before its too late. In Europe, government approval has been granted for the use of insect proteins in pig and poultry production [ 64 ]. However, no such rules exist in Malaysia permitting the use of processed protein in any industry [ 65 ]. highlighted the challenges of producing insects for human consumption, emphasizing that stringent food safety and standard protocols must be followed. The establishment of a food-grade production facility for insect protein can be costly, and compliance certification presents a significant hurdle. Given the substantial investment and lower demand, many insect growers continue to produce animal feed and fertilizer. Therefore, if one were to produce insects fit for human consumption, food safety control is crucial, requiring the prudent handling of non-contaminated food surplus and the elimination of food waste as feed. Table 1 represents the distribution of these critical success factors in the chosen research papers. These factors are arranged in descending order, from the most frequently discussed to the least. Top management commitment during the new product development (NPD) process emerged as the most frequently discussed factor. It is highlighted in all five selected papers, emphasizing the crucial role that top management's involvement plays in providing professional insights during the NPD process. Four factors - specific goals and milestones, cross-functional team participation, talented team members with relevant NPD experience, and a clearly defined product concept - tie for the second most frequently discussed topics, appearing in four out of the five papers. Three papers highlighted the importance of fostering an entrepreneurial culture and including user and customer participation in the NPD process. Alignment of NPD activities with overarching strategy and the availability of financial reports were each cited twice across the papers. Finally, factors such as a structured NPD process, efficient intra-organizational communication, a focus on innovation and unique ideas, and the pace of the NPD process were each mentioned once in the studied papers. Factors and challenges for product development are illustrated in Fig. 1 below.

Conclusions The complexities of NPD are multifaceted and cannot be underscored enough. Through our investigation, it has become evident that a successful NPD strategy isn't solely contingent on a firm's internal strategies, processes, or cross-functional collaborations. Instead, it is intricately interwoven with a multitude of external factors that can, and often do, influence the trajectory of a product's development and its subsequent market performance. Our research reveals that internal challenges such as communication barriers across functions, temporary team membership, fluid team boundaries, and structural issues within organizations can pose substantial impediments to the effective execution of NPD. These internal dynamics, although within a firm's control, require careful orchestration and a strategic alignment of team objectives with the broader organizational goals. Conversely, external challenges, often outside the direct influence of organizations, add layers of complexity to the NPD process. Constraints related to price-income levels in target markets, technological and developmental disparities in certain regions, and limited financial resources in developing economies serve as poignant reminders that product development doesn't operate in a vacuum. Companies, especially those with a global reach, need to be astutely aware of these challenges, anticipating them and strategically pivoting when necessary. Furthermore, our findings point towards the significance of acknowledging the unique variables intrinsic to different sectors within the business landscape. The challenges, risks, and potential rewards of NPD can vary dramatically from one sector to another. Hence, a one-size-fits-all approach may not yield the desired results across diverse industries. For businesses striving to master their NPD endeavors, our research offers both a cautionary tale and a roadmap. While the path to successful product development is fraught with challenges both anticipated and unforeseen, firms equipped with a comprehensive understanding of these challenges are better poised to navigate them effectively. This study accentuates the need for organizations to adopt a holistic perspective on NPD, one that harmoniously integrates internal strategies with a keen awareness of the external environment.

New product development (NPD) frequently encounters failures, whether during the development phase or in the subsequent commercialization stage. These failures can often be attributed to root causes originating in the early stages of NPD, known as the front end. This study aims to investigate the factors that contribute to NPD success and the challenges faced by firms throughout the development process. To achieve this objective, an in-depth qualitative approach utilizing interviews was employed to explore the internal and external factors influencing NPD success. Additionally, the study aims to identify specific challenges encountered by firms during the NPD process. The identification of these factors and challenges are crucial for companies as it can lead to long-term cost savings. The findings of this study have broad implications for firms regardless of their product plans. By adopting the derived approach, companies can effectively navigate the product development process and gain insights into the potential challenges associated with introducing a new product into an existing market. As customer preferences evolve with technological advancements, the barriers and challenges faced by new products entering established markets also increase. Therefore, firms that incorporate the results of this study into their product development practices across various industries can avoid pitfalls and achieve greater efficiency in terms of time and costs. This research sheds light on critical areas that contribute to successful product development and provides valuable guidance for firms striving to excel in their NPD endeavors. Keywords

Success factors for NPD Top management commitment Top managers or decision-makers are the ones who give a green or red light when a proposal is presented. This is the very first stage of product development that involves getting approval from the top management. If top management is closely involved in the early stages of NPD, the impetus behind new product ideas is greater. Senior management has the ability to offer resources and clarify project goals. For instance, senior managers must act as process supporters in approving, allocating, and directing the flow of the process [ 8 ]. Individual actions that cross functional boundaries can be coordinated by management. The importance is highlighted in a paper by Ref. [ 9 ] where they investigated the Hong Kong toy sector. The critical success factors (CSFs) were examined in the four stages of the NPD process, and significant success factors were divided into four groups according to their implementation and significance. During phase I of the process of developing a new toy, it was observed that top management support and capital backing were two amongst the most frequently employed CSFs [ 9 ]. In the product development phase II, senior management commitment is still among the most widely adopted CSFs. Involvement of cross-functional team Front-end success has been characterized as requiring cross-functional collaboration [ 10 ]. One possible explanation is that cross-functional collaboration facilitates thorough analysis and reduces front-end volatility. Another possibility is that concept selection is usually conducted in meetings including representatives from various departments in the company [ 11 ]. In such gatherings, cross-functional collaboration facilitates concept assessment. Several scholars have looked at different types of cross-functional collaboration. The R&D and marketing interaction, according to Ref. [ 12 ], is the most likely instance of cooperative interdependence during the early stages of NPD. These two regions are in charge of product definition and concept, which are then distributed to the rest of the company's activities and departments. Process and manufacturing design should collaborate early in the process of NPD to ensure that the suggested items can be manufactured [ 13 , 14 ]. [ 15 ] found that the strength of NDP processes in the food business is largely dependent on customer involvement, exchange of information with internal and external stakeholders, and the importance of having a well-defined NPD process strategy and operational thinking. Placement of structured NPD process The importance of client interaction in the early stages of NPD is debatable. Some observers say, for example, that customers rarely offer corporations substantial or diversified information. However, the production of incorrect product is one of the main causes of NPD failure [ 8 ]. Paying close attention to the market's new requirements can give businesses ‘first-movers' advantage, which translates to high product success rates in the face of low competition. Teams that do not integrate client feedback into their product development efforts are likely to fail. Before starting product creation, companies should investigate the expectations and requirements of the client. Before you take any large steps in business, make sure there is a market for what you are selling. There are no sales if there are no customers. Market research is a method of collecting data and information about your target audience in a methodical manner. It helps in determining the viability of your product or service before launching it on the market. It also offers you a sense of what is hot in the business and what drives consumers to convert and buy. As a result, you can plan your product or service's roadmap. Venturing into the digital space of online customer reviews [ 16 ], harness the power of business intelligence to decipher and decode consumer sentiments. Their findings illuminate the myriad factors that shape consumer perceptions, drawing attention to the significance of online feedback in the product development landscape. In an era where digital voices resonate loudly, their methodology offers a compelling lens to view and evaluate customer preferences. Project management capability The project manager is responsible for the project's progress through its different stages, one of which is the beginning stage, which is divided into several goals to be achieved. A project manager seeks assistance, makes resource requests, and handles technological and organizational challenges. At successful firms, project managers are responsible for all of these responsibilities, according to Ref. [ 17 ]. Project managers are also responsible for defining goals, prioritizing work, and providing leadership on the front end. Product definitions are influenced by project managers. Although no comprehensive study of the characteristics of good front-end project management has yet been conducted, existing research indicates that front-end activities can vary substantially in terms of sequencing, amount of similarity, and duration of the relative period [ 18 , 19 ]. This requires the front-end project manager to possess a wide range of skills. Innovative ideas and service innovation Offering a synthesized overview of new service development literature, Kitsios and Kamariotou, (2020) provide valuable insights into the trajectory and nuances of service-centric innovation. By mapping the extensive landscape, their work acts as a compass, directing firms to the key considerations, challenges, and opportunities inherent in the service development domain. According to Ref. [ 20 ], technological advances enable the development of novel products. However, as a result of this evolution, it is difficult to generate new ideas for the organization. Nonetheless, capitalizing on recent technological advancements is critical to the successful production of a noble product [ 21 ]. Not only should ideas disrupt established paradigms, but product representations of these concepts must really bring value to customers to sell [ 21 ]. In the realm of service innovation [ 22 ], emphasize the critical role of digitization in shaping the innovation process. Their investigation spotlights both areas ripe for exploitation and avenues that beckon deeper exploration. With the digital landscape evolving at an unprecedented rate, the paper underscores that the key to effective service innovation lies in leveraging digital tools and platforms, aligning strategies with emerging technological trends, and recognizing the transformative potential of digitization. Prior to producing a unique product description, the team gathers market needs from a range of sources [ 23 , 24 ]. Finally, a prototype concept idea is designed, allowing companies to assess whether extra work is required. If the choice is made to proceed, the first product concept enables the development phase's activities to be prioritised [ 12 , 17 ]. A drawing, a diagram, a prototype, or a mock-up can all be used to show an early concept for a product development [ 25 ]. Challenges Internal challenges: complexity of teams’ project Organizations form teams when a single individual or a group of individuals working sequentially cannot adequately complete tasks in a timely manner. To develop new products, teams must navigate an unfamiliar environment fraught with high levels of uncertainty, which serve as crucial drivers of group success [ [26] , [27] , [28] ]. On the other hand, when ambiguity and uncertainty are significant, team performance can deteriorate. According to Ref. [ 27 ], the contributing factor of ambiguity is twofold: the platform and the market. The first refers to the degree of ambiguity present during the project's design process, whilst the latter refers to the level of uncertainty created by ambiguity over the product's client desires. According to Ref. [ 29 ] advocated regular discussion and courteous engagement, along with other things, to combat individuals' tendency to withdraw from teamwork under stressful conditions. On the other hand, setting acceptable communication styles within authorized teams can be difficult. Numerous interpersonal factors, not the least of which are those related to diversity, lead to the next issue. Internal challenges: communicating across functions While team cross-functionality can produce a range of beneficial outcomes when implemented according to the procedures mentioned in the preceding section, existing research indicates that achieving those outcomes is not simple. Functional variety, according to two distinct assessments of the literature, has a harmful effect on team performance in general, but especially during times of crisis and upheaval [ 30 , 31 ]. Apart from impairing team effectiveness, complexity has been linked to increased levels of discontent, attrition, sick absence, commitment, and workplace stress [ 32 ]. Their emphasis on team culture is very appropriate. Prior work by current authors and others established the crucial importance of the personal and social environment [ [33] , [34] , [35] ]. Meaningful demographic contrasts elicit judgements about an individual's perceived significance, aptitude, and potential to effectively respond to the job [ 36 ]. When these perspectives are wrong or out of control, they obstruct cross-functional learning and collaboration. Due to judgement errors, systems of influence and deference emerge within the team, limiting the supply of job knowledge [ 37 ]. Less honoured team members, who are more likely to experience decreased psychological safety [ 35 ], decreased self-efficacy, and a diminished sense of importance to the team and its task become less engaged in team tasks [ 35 , 38 ], and thus engage in less team-learning behavior [ 33 , 34 , 39 ]. Internal challenges: temporary team membership Teams are project-based in a wide variety of fields, including research and new product development. When a project or field of inquiry presents itself, organization members are chosen based on their unique capacity to assist the endeavor. Certain members of the team will work on a project until it is completed, and then move on to the next one that requires their specialised skillset; others will work on the project for a shorter period of time. Individuals may collaborate on several projects with different people, depending on the organizational objectives. This flexible structure enables projects to be staffed by the most qualified professionals. At the same time, the transient character of the team might be troublesome; members must get to know one another before they can operate well as a team [ 40 ]. Consistent team participation, according to research, increases instructional and intrateam interaction [ 41 ]. Individuals who function in teams for an extended period of time, up to three years [ 42 ], become more efficient, most likely because teammates develop “transactive memory” [ 43 ]. Longevity is crucial for cross-functional collaboration in particular [ 44 ]. discovered that social tenure had a moderating effect on the link between diversity and conflict, with conflict being smaller in varied teams with a longer team duration. [ 32 ] discovered that group longevity modifies the connection of diversity to organizational performance in a more recent study. As a result, firms tend to be forced to make a trade-off when utilizing short, project-based teams. On the other hand, they enable the application of the highest level of knowledge to every project. On the other hand, the frequency and duration of these proposal teams preclude the development of familiarity and understanding that comes with team longevity. Internal challenges: fluid team boundaries One reason for categorising a group of individuals as a “functional team” is to ensure that the group is “anchored,” which means that each member's role is explicitly expressed and acknowledged [ 45 ]. Individuals who work in constrained teams are more likely to have comparable time allocations than members of ad hoc teams. This enclosure generates a sense of shared identity, cohesiveness, and purpose, all of which contribute to the urge for cooperative behavior [ 46 , [46] , [47] , [48] ]. Two issues arise with NPD teams. To begin with, the advantage of cohesion has restrictions. Members can become so self-absorbed that they lose sight of the outer world and their own connections, compromising team effectiveness. Both environmental [ [49] , [50] , [51] ] and border [ [52] , [53] , [54] , [55] ] perspectives assert that external contact with individuals outside the team makes a significant contribution to team performance [ 55 ]. established that, while correlation was used to determine that communication has no effect on team performance, interteam communication does. Second, NPD teams rarely operate within defined exact parameters and adhere to consistent time restrictions. Typically, NPDs are made up of a core set of members who are fully responsible for group performance and depend on others to fill temporary team positions. As [ 33 ] illustrates, an NPD team may include core members from advertising, product engineering, and manufacturing, as well as part-time members with finance or legal expertise. Emphasizing on full squad participation for activities that are organically smaller than core duties is inefficient, which is why only a few NPD teams embody the “real team” notion, hence raising the coordination barrier in favour of more efficient resource utilisation. Internal challenges: organizational structure Numerous organizations fail to develop structures that support the success of teams [ 56 ]. Certain organizational structures, such as individual-based awards and department-based sharing of benefits, work against teamwork [ 57 ]. Numerous team failures are attributed to inconsistencies in task–reward structures [ 58 ]. To maximise performance and productivity, the interrelation of incentives should match the complexity of tasks [ 59 ]. Individuals or departments' contributions to the final product are barely distinguishable in the ideal form of teamwork, and as a result, all individuals should get equal credit for their team's play. This does not stop the team's “star” members from receiving further individual recognition [ 15 ]. To foster cooperation, however, organizational rewards must be pervasive, acknowledged, and appreciated such that the message communicated to team members is coherent [ 60 ]. Regardless of the fact that service innovation has a favorable influence on team performance, many firms set performance evaluation and rewards on an individual basis [ 59 ]. This may encourage team members to prioritise individual achievement and credit over collective goals, particularly when they conflict [ 61 ]. described a new product development team in which an engineer was responsible for utilizing cutting-edge technological innovation and the marketer was responsible for establishing connections with clients to identify their desires for the new product. Although these foci were consistent with the values and incentives of their functional divisions, they impeded team achievement. Therefore, the challenge to cooperation is that it operates within an environment that promotes personal achievement, but strives for collective success. External challenges: price-income levels The size of their markets justifies international firms' spending in research and development, which results in numerous new product/service developments. When these firms attempt to introduce these new products/services in poor nations, they frequently retain the majority of the product/service attributes, resulting in costs that are relatively costly for the majority of developing country consumers. In the majority of developing countries, only roughly 5–10 % of households are categorised as middle class [ 13 ]. Except for China and India, middle-class markets are typically modest. A high price may imply that the product is too advanced for the customer's needs. As a result, it may drive potential consumers to seek more relevant alternatives. External challenges: technological-developmental issues Generally, developing countries lack a strong technology foundation and trained scientists. Due to a lack of funding, many countries have very few research universities, which contributes to the shortage of highly trained scientific experts [ 13 ]. Technology is the catalyst for innovation. When a technical base is lacking, including trained researchers and funding, new product development is difficult. It is difficult for multinational corporations to justify investing in human and financial capital just for the purpose of developing products for underdeveloped countries. As a result, these corporations tend to concentrate their efforts on developing products/services for developed countries on markets capable of supporting these breakthroughs and frequently overlook developing markets. Often, technological flaws in the product are the fundamental reason for its failure. Designers and product technologists are capable of overengineering even the most sophisticated laboratory instruments. This benefits the company's technical advantage over competitors. However, an “over-engineered” product is costly for the company and ultimately for the customer, since competitors gain an edge over the “over-engineered” product. Although technical deficiencies must be remedied, the cost of doing so should not be unacceptably high. External challenges: capital constraints Financial resources are often limited in developing countries, with the available capital primarily directed towards economic development rather than investment in products and services. International corporations primarily generate their revenues from large industrialized markets, making it challenging to justify allocating funds for research in capital-scarce developing nations. Executives of international companies in these countries often face budget constraints for research and development due to the high costs and scarcity of capital. Consequently, these leaders tend to focus their efforts on cost reduction in areas such as manufacturing, shipping, marketing, and customer service []. Innovative organizations encounter financial barriers when it comes to investing in innovation due to externalities, informational asymmetries, and challenges related to appropriability of returns on R&D investments. These factors contribute to higher costs associated with R&D investments, leading to underinvestment in innovation activities. The cost disparity between external and internal costs can further exacerbate this underinvestment, along with limitations in liquidity. Consequently, some innovative ventures may be halted, delayed, or abandoned due to insufficient financial resources. Conceptualization of findings & contributions to NPD Dual-domain model of NPD challenges One of the distinctive contributions of this paper is the identification and classification of challenges into two distinct domains: Internal and External. The Dual-Domain Model underscores the multifaceted nature of NPD, suggesting that companies must be adept at navigating challenges both from within their organizational structures and from the broader external business environment. The NPD continuum of collaboration This paper highlights the varying degrees of collaboration within NPD teams, from cross-functional collaboration to the dynamic nature of team boundaries. This continuum showcases that collaboration isn't binary; it's a spectrum. At one end, we have fixed, cross-functional teams, and on the other, fluid teams with changing membership. Recognizing where a team stands on this continuum can offer insights into potential challenges and the strategies needed to address them. The sector-specific lens NPD doesn't operate in a silo; its success and challenges are inherently tied to the sector it belongs to. By emphasizing the need to understand sector-specific variables, this paper proposes that NPD strategies must be tailored, adaptive, and sector-aware. This brings forth the idea that generalized NPD strategies might be less effective than previously thought. The NPD success factors This paper not only identifies challenges but also alludes to critical success factors. By juxtaposing challenges against success factors, we propose the NPD success model. This model can serve as a diagnostic tool for firms, helping them identify areas of strength and potential pitfalls based on internal dynamics and external market conditions. The external challenge Our findings unearth external challenges. While external factors such as technological-developmental issues can pose challenges, they can also serve as opportunities for firms to innovate and lead. Recognizing and acting upon these paradoxical opportunities can be a game-changer for firms in the NPD realm. The organizational inertia dilemma While organizational structures provide stability, they can also hinder agility, especially in the dynamic world of NPD. This paper surfaces the tension between stability and agility, suggesting that companies need to strike a balance. Too much rigidity can stifle innovation, while excessive flexibility can lead to a lack of direction. By conceptualizing the findings in the manner above, this paper not only provides an in-depth understanding of NPD but also advances the discipline by offering novel frameworks and perspectives (see Fig. 1 ). These insights, grounded in rigorous qualitative analysis, have the potential to reshape how academics and practitioners approach NPD in the future. Implications Businesses seeking to launch new products in the market should pay close attention to certain key factors. These encompass the dedication of upper management throughout the new product development (NPD) process, participation of cross-functional teams, implementation of a structured NPD procedure, and a strong emphasis on innovation and unique ideas. Upper management's involvement is pivotal, as they provide valuable insights and demonstrate a keen understanding of emerging market trends and opportunities. Capitalizing on these opportunities offers a competitive edge, as customers will discover your product before similar products from competitors. Establishing customer loyalty is fundamental to maintaining market competitiveness. Further, it's the duty of top management to outline essential performance indicators and milestones to monitor progress, thereby offering a comprehensive picture of areas needing improvement. A shared objective of launching a product that caters to consumer needs should unite all departments and staff. Occasionally, conflicts may emerge as employees focus on their individual departmental goals. For example, while the finance department might aim to cut costs, the research team may need substantial investment in machinery or research and development. Even though the ultimate aim is to launch a new product, day-to-day objectives can differ across departments. It's crucial that each team or department is ready to support others when necessary. As technology progresses, consumer demand for novel products is increasing. Major problems require innovative answers. With growing consumer buying power, they're drawn to products that engage their interest. Ideally, these products should be fresh, unique, and offer value at a reasonable price. Creating an innovative and cost-effective new product poses a significant challenge for businesses. Therefore, firms must cultivate a culture that encourages employees to tackle problems from various perspectives, thereby boosting their ability to deliver innovative solutions that add to the company's value. Limitations and recommendations Merely depending on the frequency of CSFs appearing in literature to demonstrate their significance in the efficiency of NPD isn't enough. It's essential to cite real-world examples from various sectors to authentically demonstrate their global success potential. Numerous factors contribute to new product failures, including problems with the front-end activities of NPD. These can include poor handling of research results [ 17 ], erratic decision-making, and the high complexity and ambiguity that arise from competing organizational pressures. By addressing these issues, this paper aims to assist managers and their teams in pinpointing the factors that enhance the efficiency of front-end NPD operations. While this research primarily scrutinizes internal factors that influence corporate-level new product success, it offers limited insights into how external factors can boost success rates. Considering the gaps in literature regarding NPD front-end success, it's important to further explore this domain. This requires a comprehensive understanding of the front end, including its initiation, features, conclusion, and processes. For instance Ref. [ 17 ], define the beginning of the front end as the moment when firms identify an opportunity in a semi-formal manner, suggesting that the idea—perhaps originated from an individual—needs to be communicated within the company. The incorporation of external idea sources, such as consumers and suppliers, is considered part of the front end. Although this perspective is vital, our model doesn't incorporate it; instead, it concentrates on business management. Concerning methodology, the study includes only one respondent who also serves as the company's key informant. A more comprehensive and conclusive approach would involve multiple respondents, such as department heads, to gather more detailed and specific interview responses. Additionally, there are limited resources for examining the internal and external challenges encountered in product development. Moreover, the research discusses product development factors and challenges as a whole, without detailing strategies specific industries could implement to enhance their success probabilities. Unfortunately, no research paper can assure that adhering to the suggested steps will guarantee success in product development. This research underscores the need to take into account both internal and external factors in corporate-level product development. Simply focusing on internal dynamics may not be enough, as external influences can markedly affect the success or failure of product development. Moreover, the case study's focus on a single sector may not fully encompass the broad spectrum of sectors in the business landscape, each with its distinct variables impacting the outcome of new product development. The link between fundamental success determinants and project-specific success variables remains under-explored. In organizations with a culture that encourages creativity, idea refinement might unfold in innovative ways, especially when developing radically new products, even without early customer engagement or proactive environmental scanning. It remains to be clarified how the success characteristics outlined in the theoretical framework correspond with such activities and how iterations progress as a result of these actions. Future directions of study In future research, we advocate for a deeper exploration into sector-specific challenges and success factors in NPD. Such nuanced insights could further empower organizations to tailor their product development strategies in alignment with the unique demands and opportunities presented by their respective sectors. Besides that, one of the emergent concerns in the field of NPD, as underscored by recent literature, is the phenomenon of “Over-Featuring"—the inclination to develop products and services that exceed the genuine requirements of users, surpass market demands, and potentially strain organizational resources [ 66 ]. This trend, while rooted in the desire to offer superior value, can inadvertently lead to the creation of products that are too complex, costly, or misaligned with user needs, resulting in potential NPD failures. To counteract the challenges of Over-Featuring, future research should delve into the integration of Agile methodologies and Design Thinking. Both approaches emphasize iterative feedback and user-centricity, which can ensure products remain aligned with market needs and resonate with users. Declarations All authors listed have significantly contributed to the development and the writing of this article. Request for publication consent Request for permission to include company name and other information that was collected during the interview has been granted by Protenga Sdn. Bhd. For publication purposes. Funding statement The authors would like to express their sincere gratitude to the Asia Pacific University of Technology and Innovation (APU) for their generous sponsorship of the Article Processing Charges (APC) associated with the publication of this paper. This support has been instrumental in enabling the dissemination of our research findings to a wider audience. We deeply appreciate Asia Pacific University's commitment to fostering academic and scientific research. Data availability statement Data included in article/supp. material/referenced in article. No additional information is available for this paper. CRediT authorship contribution statement Mohammad Falahat: Writing – review & editing, Validation, Supervision, Conceptualization. Shyue Chuan Chong: Validation, Methodology, Formal analysis. Cindy Liew: Writing – original draft, Resources. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment The authors express their deep appreciation to Mr. Leo Wein, Director of Protenga Sdn. Bhd. (Company Registration Number: 201801004055, 1266069-U), for his valuable support in this project.

CC BY

no

2024-01-16 23:42:01

Heliyon. 2023 Dec 17; 10(1):e23763

oa_package/88/f9/PMC10788447.tar.gz

PMC10788449

38226249

introduction The study of the effects of tip leakage flow in turbo-machines has undoubtfully been one of the major topics that have concerned the minds of great scientists of the aforementioned field. In turbo-machines, tip leakage flow, caused by the pressure difference of suction and pressure surface of the blade, is unfavorable because of its adverse effect on pressure loss and blade exit wakes. The interaction of the tip leakage flow and the mainstream, or the shock wave in transonic compressors would worsen the case. Cascade studies showed promising results when blade tip treatments were used. Winglets, which have been widely used in aircraft wings, have also proven to be beneficial in the compressor flow field and performance. Squealer tip is another passive control technique for turbine and compressor blades, aiming to alter the flow structure and extract better performance from the machine. Cavity-type squealer tips in turbines have been presented in the industry to reduce the tip leakage loss in axial turbines [ 1 , 2 ]. The squealer tip effect on the design and off-design performance of the compressor has been of great importance for researchers [ 3 , 4 ]. In 2016, Han Shaobing and Zhong Jinjun, numerically studied the effects of pressure and suction side winglets on the overall performance, flow structure, and stability of NASA rotor-37 blade. With a small penalty in efficiency, they reached a 33.74 stall range extension using a pressure side winglet, while the pressure side winglet was proven to be ineffective in their research. The alleviation of the interaction between tip leakage flow and shock waves was perceived to be the main reason for the mentioned performance improvement [ 5 ]. Squealer tips are indicated to be beneficial even in centrifugal compressors. In 2017, Riccardo Da Soghe et al. published their results of the study of the effects of squealer impellers on the performance of a centrifugal compressor. They found that the implementation of squealer tip impellers positively impacts performance. In high flow coefficients, the squealer tip was proven to be more effective than the part load conditions [ 6 ]. In 2022, a cavity-type squealer on transonic centrifugal compressor impellers and its effects on aerodynamic performance and stall margin were analyzed by Zamiri et al. They reported that a proper cavity depth could make a 0.32 % gain in efficiency at the design point and a 1.02 % improvement in stall margin [ 7 ]. In 2017, Shivaramaiah et al. numerically investigated the effects of four different winglet configurations added to the compressor blade tip. They tried two winglets on the pressure side of the blade, one fully covering the blade tip chord and the other only to 50% of the blade tip chord, and the same approach was conducted to the suction side. The results indicated that winglets can alter spanwise blade loading, besides increasing the stage total pressure ratio. In their research, the stall margin was found to decrease reportedly because of more blockage towards the trailing edge in the tip region [ 1 ]. Fei Zeng et al. developed a method to experimentally analyze squealer tip effects in turbines, considering the relative motion of the casing, which plays a vital role in the flow structure. They also considered how incidence angle variation affects performance. A method for using low-speed experimental results to study high-speed turbines was proposed and a cavity-type squealer-tipped blade was analyzed as a test case in the experimental setup [ 2 ]. High-pressure turbine blade tips are highly sensitive to small geometry variations. In 2021 J. Vieira and a group of researchers at Oxford University, aimed to study the aero-thermal effects of welding bead on a squealer-tipped turbine blade which is effective on engine performance. In their research, they surveyed flow structures and vortices in leakage flow when a squealer is present [ 8 ]. Q. Zhao et al., in 2021 employed a tip winglet to the NASA rotor-37 blade to numerically investigate its effects on flow stability. Four tip treatment configurations were used in this research. The results showed a decrement of leakage flow in the blade tip in the pressure side tip winglet configuration, but an increment in the suction side tip winglet configuration. With no penalty in efficiency, they experienced an 11 % increase in stall margin, while the suction side configuration resulted in a 17 % decrease in stall margin, with significant deterioration of flow characteristics and structure [ 9 ]. Oxford University researchers in 2021, implemented a multi-objective genetic algorithm to optimize squealer tip geometry for a turbine cascade to analyze cooling effects. Aerodynamic efficiency, film cooling effectiveness, and the variation of blade surface temperature were the main objectives to be optimized [ 10 ]. W. Xu and his colleagues have recently studied how a winglet in a compressor tip would affect the performance and flow structure of a transonic compressor. They studied the exploit of winglets in different tip clearances in their research project, besides studies of the effect of the winglet height. The weakening of the kinetic energy of tip leakage flow and suppression of leakage vortex, which in this case helps to reduce the total pressure loss, were the major results of the research. They experienced a 3.3% and a 13.4% decrease in loss and leakage flow in the optimal geometry. They could also show that, with increasing tip clearance, the suppression effect of winglets increases first and then gradually decreases [ 11 ]. In this research, a comprehensive and innovative method for the geometry generation of squealer-tip in both suction and pressure surfaces of an axial compressor rotor blade has been described. In this method, two splines are used to produce the squealer depth of the suction and pressure surfaces, which enables the designer to automatically produce various types of squealer curves using a few control points. The tip clearance value was kept constant to better investigate the role of the squealer in performance. A control point has also been used to enable changing the height of the squealer in the spanwise direction within predefined limits. To investigate the effect of the squealer in choke, design, and near the stall zones, the research was carried out using Taguchi's orthogonal array, and the feasible areas of aerodynamic improvement were identified and the results of the database were used to train artificial neural networks. Coupling of the genetic algorithm and artificial neural networks finally resulted in the optimal squealer geometry, based on various performance parameters. The obvious results of this research are the simultaneous squealer in both suction and pressure surfaces, which have improved the adiabatic efficiency of design and near stall points. The improvement of the surge margin is also the result that can be investigated after the optimization process.

Methodology Using Artificial Neural Network (ANN) as a powerful tool is a common method to use for optimization problems. The most important advantage of this optimization coupling is the reduction of the computational costs in the optimization algorithm cycle. The coupling of ANNs with the genetic algorithm has been widely used in the field of turbo-machinery optimization. Some examples include the research of Benini and Heidarian both for an axial compressor [ 14 , 15 ] and Ekradi et al. for a centrifugal compressor [ 16 ]. Here, the coupling of genetic algorithm and the artificial neural network is utilized to obtain optimal values of squealer-tip geometry parameters, which were defined in previous sections. The results of the L-27 OA of Taguchi (used in the sensitivity analysis step) were used to train the neural network to be used to predict the values of mass flow rate, Total pressure ratio, and adiabatic efficiency for the three operating points of choke, design and near stall. The prediction accuracy of artificial neural networks with CFD results is presented in Fig. 14 , Fig. 15 , and Fig. 16 . The details of the ANN setting are given in Table 4 . In the optimization process of this research, the genetic algorithm is coupled with neural networks to search for optimal points, and the results are verified by CFD in the optimization loop. Therefore, if the error between results obtained from neural networks and CFD were higher than the optimal loop error range, the CFD results are sent back to the initial database for improving the neural network's capabilities. If the error between CFD and neural network results is less than the convergence error, the optimization loop ends, and the CFD results along with genetic algorithm selection coefficients for the optimal point are selected. The DOE process and the sensitivity analysis of design variables, as well as the numerical optimization process, are illustrated in Fig. 17 flowchart. Further details of the genetic algorithm are presented in Table 5 .

result and discussion In the optimization process, a database of 27 arrays was used and then GA coupled with ANNs was solved. In this process, two categories of squealer tips were studied. The first category is suction-side squealer, and the second one is double-sided squealer. The results for the squealer-tip blades compared to original Rotor-67 blade are presented in Fig. 18 . Finally, the two best optimal cases have been selected from this database and their characteristic maps have been extracted. performance map The performance maps for the design speed of the Rotor-67 and two optimized compressors with squealer-tip blade have been calculated and presented in Fig. 19 , Fig. 20 . Additionally, the performance improvement of optimal squealer geometries for three in choke, design and near stall working areas are presented in Table 6 , Table 7 , Table 8 . The increase in choke mass flow rate in double-sided squealer and surge margin improvement using suction-side squealer is obvious from the figures. surge margin Surge margin is one of the important stability parameters of a compressor, showing a safe operating distance between operating point and surge point, which is calculated according to Equation (14) . Table 9 presents these results which show that the surge margin is improved in the optimal squealer blade. optimal rotor tip A sample of squealer tip geometry in the blade-to-blade view is demonstrated in Fig. 21 . The figures demonstrated a detailed view of the optimized squealer geometries for the double-sided and suction-side squealer. Furthermore, the obtained values for optimal geometries are presented in Table 10 . Ellipse is used to form the blade tip leading and trailing edge, in the suction side case, to further refine and adjust the incoming flow. radial profiles The distribution of total pressure ratio and adiabatic efficiency in the radial direction just after the compressor rotor for Rotor-67 base geometry and two obtained optimal geometries are extracted in three different operating conditions and are depicted in Fig. 22 , and Fig. 23 . According to the results, the effects of the squealer are clear in the improvement of the three performance parameters of on-design Total pressure ratio and adiabatic efficiency of blade tip areas (span 0.9 to 1); while it has less decreasing of adiabatic efficiency at near stall region (for squealer-SS). blade loading Change of geometry results in different pressure distribution over the blade tip area, thus to better compare the parameter in optimized squealers and the baseline geometry, pressure coefficient distribution in blade tip section is presented in Fig. 24 , Fig. 25 , Fig. 26 for three operating points. The double-side squealer geometry acts more like the baseline geometry and minor changes are present. But for the suction side squealer, since a considerable amount of thickness is lost the changes in pressure distribution are significant, mainly in near stall operating point. This has finally resulted in better surge margin based on the results. tip leakage The results of the aerodynamic values of the optimized squealer and the Rotor-67 in the blade tip region are presented put into comparison in this section. tip-leakage map The tip leakage mass flow rate-inlet mass flow rate and tip velocity-Total pressure ratio curves have been extracted for the design speed, and demonstrated in Fig. 27 , Fig. 28 . According to the results of two optimal rotors, the leakage mass flow rate in design and near the stall points are lower than the leakage mass flow rate of the Rotor-67. tip-leakage contour The blade tip vortices are presented using the streamlines of the blade tip leakage in five planes perpendicular to the suction and pressure surfaces. Fig. 29 demonstrates these streamlines for the optimal squealer rotors compared to the Rotor-67, in three operating regions. The tip vortex generated at the design and near stall operating points has a greater depth and a smaller width than the vortex in optimal blades which are subsequently created because of the presence of squealer-tip. Therefore, these vortices are the important reason for the reduction of secondary flows and improvement of performance parameters in spanwise direction. The reduction of vortex propagation in the suction side region in blades with squealer tips results in less deviation of flow from the sold surface of the rotor and less dissipation of energy. This has been addressed in velocity curl plots in the next section. Additionally, Fig. 30 demonstrates 3-dimensional surface streamlines in tip region of the near stall operating point. By comparing the entropy contour of the blade tip in Fig. 31 , it also seems that the decrease in relative Mach has caused a decrease in the entropy production in the optimal squealer geometries compared to the Rotor-67. The figures depict that the entropy increase due to presence of squealer is reduced because of the changed mixing loss, affecting the flow structure in suction side. The main region of entropy increase is downstream of the 60 % streamwise location. This positive effect of squealer is more evident in near stall working points, where high Total pressure ratio drives more flow through the tip clearance. The suction side squealer shows a more promising result in reducing the mixing loss. circumferential distribution In Fig. 32 , Fig. 33 , Fig. 34 , circumferential distribution of normalized velocity curl vectors at 0.95 spanwise and 1.5 streamwise locations are plotted. The parameter distribution is demonstrated in design and near stall operating points for baseline and obtained optimum squealer geometries. As it is depicted, the velocity curl is increased in presence of SS and PS-SS squealers, compared to baseline geometry, which is due to creation of additional vortices. This causes a sealing like effect in blade tip area by increasing energy dissipation of the leakage flow and consequently tip leakage flow is reduced. The aforementioned increase in surge margin is another effect caused by this sealing effect. The higher velocity curl is a result of additional vortex effects in the tip area and as mentioned before, by changing the flow structure and mixing loss, the tip leakage is reduced and the suction side flow can follow the solid geometry in a better manner and a more desired flow exit angle at the trailing edge. streamwise distribution To analyze the effects of squealer on the secondary airflow in the tip region of the optimized rotors compared to Rotor-67 more thoroughly, leakage mass flow rate distribution in streamwise direction, through a fixed cross-sectional surface from the LE to is used. These results have been carried out for choke, design, and near stall conditions, as shown in Fig. 35 , Fig. 36 , Fig. 37 , respectively. As expected, the leakage mass flow in both optimized geometries reduced compared to the reference geometry, resulting in reduced losses, improved efficiency, and increased surge margins.

result and discussion In the optimization process, a database of 27 arrays was used and then GA coupled with ANNs was solved. In this process, two categories of squealer tips were studied. The first category is suction-side squealer, and the second one is double-sided squealer. The results for the squealer-tip blades compared to original Rotor-67 blade are presented in Fig. 18 . Finally, the two best optimal cases have been selected from this database and their characteristic maps have been extracted. performance map The performance maps for the design speed of the Rotor-67 and two optimized compressors with squealer-tip blade have been calculated and presented in Fig. 19 , Fig. 20 . Additionally, the performance improvement of optimal squealer geometries for three in choke, design and near stall working areas are presented in Table 6 , Table 7 , Table 8 . The increase in choke mass flow rate in double-sided squealer and surge margin improvement using suction-side squealer is obvious from the figures. surge margin Surge margin is one of the important stability parameters of a compressor, showing a safe operating distance between operating point and surge point, which is calculated according to Equation (14) . Table 9 presents these results which show that the surge margin is improved in the optimal squealer blade. optimal rotor tip A sample of squealer tip geometry in the blade-to-blade view is demonstrated in Fig. 21 . The figures demonstrated a detailed view of the optimized squealer geometries for the double-sided and suction-side squealer. Furthermore, the obtained values for optimal geometries are presented in Table 10 . Ellipse is used to form the blade tip leading and trailing edge, in the suction side case, to further refine and adjust the incoming flow. radial profiles The distribution of total pressure ratio and adiabatic efficiency in the radial direction just after the compressor rotor for Rotor-67 base geometry and two obtained optimal geometries are extracted in three different operating conditions and are depicted in Fig. 22 , and Fig. 23 . According to the results, the effects of the squealer are clear in the improvement of the three performance parameters of on-design Total pressure ratio and adiabatic efficiency of blade tip areas (span 0.9 to 1); while it has less decreasing of adiabatic efficiency at near stall region (for squealer-SS). blade loading Change of geometry results in different pressure distribution over the blade tip area, thus to better compare the parameter in optimized squealers and the baseline geometry, pressure coefficient distribution in blade tip section is presented in Fig. 24 , Fig. 25 , Fig. 26 for three operating points. The double-side squealer geometry acts more like the baseline geometry and minor changes are present. But for the suction side squealer, since a considerable amount of thickness is lost the changes in pressure distribution are significant, mainly in near stall operating point. This has finally resulted in better surge margin based on the results. tip leakage The results of the aerodynamic values of the optimized squealer and the Rotor-67 in the blade tip region are presented put into comparison in this section. tip-leakage map The tip leakage mass flow rate-inlet mass flow rate and tip velocity-Total pressure ratio curves have been extracted for the design speed, and demonstrated in Fig. 27 , Fig. 28 . According to the results of two optimal rotors, the leakage mass flow rate in design and near the stall points are lower than the leakage mass flow rate of the Rotor-67. tip-leakage contour The blade tip vortices are presented using the streamlines of the blade tip leakage in five planes perpendicular to the suction and pressure surfaces. Fig. 29 demonstrates these streamlines for the optimal squealer rotors compared to the Rotor-67, in three operating regions. The tip vortex generated at the design and near stall operating points has a greater depth and a smaller width than the vortex in optimal blades which are subsequently created because of the presence of squealer-tip. Therefore, these vortices are the important reason for the reduction of secondary flows and improvement of performance parameters in spanwise direction. The reduction of vortex propagation in the suction side region in blades with squealer tips results in less deviation of flow from the sold surface of the rotor and less dissipation of energy. This has been addressed in velocity curl plots in the next section. Additionally, Fig. 30 demonstrates 3-dimensional surface streamlines in tip region of the near stall operating point. By comparing the entropy contour of the blade tip in Fig. 31 , it also seems that the decrease in relative Mach has caused a decrease in the entropy production in the optimal squealer geometries compared to the Rotor-67. The figures depict that the entropy increase due to presence of squealer is reduced because of the changed mixing loss, affecting the flow structure in suction side. The main region of entropy increase is downstream of the 60 % streamwise location. This positive effect of squealer is more evident in near stall working points, where high Total pressure ratio drives more flow through the tip clearance. The suction side squealer shows a more promising result in reducing the mixing loss. circumferential distribution In Fig. 32 , Fig. 33 , Fig. 34 , circumferential distribution of normalized velocity curl vectors at 0.95 spanwise and 1.5 streamwise locations are plotted. The parameter distribution is demonstrated in design and near stall operating points for baseline and obtained optimum squealer geometries. As it is depicted, the velocity curl is increased in presence of SS and PS-SS squealers, compared to baseline geometry, which is due to creation of additional vortices. This causes a sealing like effect in blade tip area by increasing energy dissipation of the leakage flow and consequently tip leakage flow is reduced. The aforementioned increase in surge margin is another effect caused by this sealing effect. The higher velocity curl is a result of additional vortex effects in the tip area and as mentioned before, by changing the flow structure and mixing loss, the tip leakage is reduced and the suction side flow can follow the solid geometry in a better manner and a more desired flow exit angle at the trailing edge. streamwise distribution To analyze the effects of squealer on the secondary airflow in the tip region of the optimized rotors compared to Rotor-67 more thoroughly, leakage mass flow rate distribution in streamwise direction, through a fixed cross-sectional surface from the LE to is used. These results have been carried out for choke, design, and near stall conditions, as shown in Fig. 35 , Fig. 36 , Fig. 37 , respectively. As expected, the leakage mass flow in both optimized geometries reduced compared to the reference geometry, resulting in reduced losses, improved efficiency, and increased surge margins.

conclusion The study explores the use of squealer tip to improve the performance of axial compressor blades in various operating conditions in a specified tip clearance similar to baseline geometry. Splines with control points are utilized to modify the geometry of the squealer tip, both on the suction and pressure surfaces. A design of experiments (DoE) approach is used to analyze the impact of these modifications on aerodynamic performance. Neural networks are trained using the data generated in the DoE, and they are integrated with an optimization algorithm to identify optimal performance areas. The research shows that these modifications reduce blade tip leakage flow and weaken tip vortices, leading to improved performance parameters in compressor rotor operation. The main results of the study are summarized below. • For the choke operating region, the optimum double-sided and suction side squealers resulted in an increase in mass flow rate by 0.216 and 0.042%, respectively, but total pressure ratio and adiabatic efficiency were negatively affected. • In the design point, all main performance parameters were considerably improved; 0.575 and 0.405% increase for mass flow rate of double-sided and suction side squealer, for example. In this matter, data for other parameters and working points are presented in Table 6 to Table 8 . • A promising effect of squealer tip is found to be its effect on surge margin improvement, in this research is 4.8 % for double-sided and 6.5 % for suction side squealer. • Entropy increase is reduced in the presence of a squealer tip, mainly after a 60 % streamwise location where a significant entropy increase exists. • Tip leakage flow is significantly reduced when an optimum shape of squealer is employed, mainly in the choke and design point, resulting in an increase overall mass flow rate of the compressor.

This research represents an innovative method for geometry generation of the squealer-tip in axial compressor rotors and its exploit in a numerical optimization process to obtain a better stage performance. For this purpose, the NASA Rotor-67 transonic compressor rotor blade is used as a test case to study the aerodynamic performance using computational fluid dynamics. The validation was performed for the characteristic map at the design speed and the comparison with the experimental results indicates excellent matching and high adaptability of the numerical method. An ingenious method of producing squealer tip for an axial compressor rotary blade is presented in this article, which is capable for locally shaping both suction and pressure surface geometry at a desired spanwise location simultaneously, while keeping the tip clearance at its value of the baseline NASA Rotor-67 geometry. In this method, control points are used to produce the starting spanwise location of the squealer, and modify the depth of the squealer geometry. The L-27 orthogonal array of the Taguchi method as the Design of Experiment (DOE) has been used to investigate the sensitivity of the aerodynamic results in three performance points of the choke, design and near stall regions, in relation to the design variables of the squealer. The generated database in the sensitivity analysis was used to train artificial neural networks to replace the CFD solutions with overwhelming run time. By coupling the genetic algorithm to the aforementioned neural networks and by applying penalties to maintain the minimum performance of the Rotor-67, enhancement of total pressure ratio, adiabatic efficiency, mass flow rate and even the surge margin was achieved. The main effect of the squealer is to modify the shape of blade tip vortices, and by more dissipation of energy in blade tip area and reduced equivalent flow area in this region, finally results in improved overall mass flow rate, total pressure ratio, adiabatic efficiency and surge margin by 0.58 %, 0.36 %, 0.19 % and 4.81 % respectively, at design point. Keywords

Nomenclature Coefficients of squealer depth spline for pressure side Coefficients of squealer depth spline for suction side Coefficients of squealer height The minimum, maximum and middle of Coefficient Artificial neural network Correction factor Coefficient of squealer-tip Pressure coefficient Design of experiments The Ratio of Specific Heats Leading edge Mass Flow Rate [kg/s] Orthogonal array Optimized Pressure Participation percentage Total pressure ratio Sum Surge margin Square of factor Squealer Temperature [K] Trailing edge Temperature ratio Velocity [m/s] The x, y, z-coordinates Y-plus Subscripts Adiabatic Chord Choke Corrected Design Inlet Leakage Near stall Outlet Stagnation property Pressure side Suction side Tip section Greek symbols Difference Adiabatic efficiency Curl three-dimensional simulation In this section, the three-dimensional CFD simulation of the test case is described. NASA Rotor-67 test case A numerical study was conducted on the geometry of NASA's Rotor-67 compressor, which provides a mass flow rate of 33.25 [kg/s] and a total pressure ratio of 1.63 at the design point, with a rotational speed of 16043 [rpm]. The three-dimensional and meridional views of this compressor are presented in Fig. 1 . Stations 1 and 2, upstream and downstream of the rotor, are used to measure the rotor's overall performance. The geometric and performance specifications of this compressor are summarized in Table 1 , extracted from Ref. [ 12 ], which was used to validate the experimental test results. A three-dimensional aerodynamic analysis of the compressor blade was performed using the Reynolds-Averaged Navier-Stokes code (RANS) with structured grids comprising H and O blocks, as shown in Fig. 2 . Side surfaces of the domain were set as periodic faces. In addition, the atmospheric conditions were used at the compressor inlet for the air ideal gas, and the static pressure condition was used at the outlet as presented in Fig. 3 . The rotor domain is set to be rotary while the hub and shroud walls were set with a no-slip condition. The SST model was used as the turbulence model in the analysis. Four structured grids with 480k, 720k, 1360, and 1780k elements are generated for grid study. The comparison of total pressure ratio, mass flow rate and adiabatic efficiency for these four grids at choked point are demonstrated in Fig. 4 . Considering the results of the grid study, the grid no.3 can be chosen as the efficient case to continue the study. Fig. 5 depicts the distribution of blade Yplus in grid No.3 which in case verifies the validity of the turbulence model. The average distribution of the Y-plus value in the middle section of Rotor Blade grid No.3 is approximately 1, which is within the ideal range for the turbulence model used. CFD solver validation To validate the CFD solver, the performance maps from the numerical simulation at the design speed are compared to the experimental data and shown in Fig. 6 [ 12 ]. The minimum total pressure ratio obtained in the numerical method equals to 1.28 at the choke condition, with the maximum mass flow rate of 34.55 [kg/s] and the adiabatic efficiency of 84 %. The numerical simulations also resulted in a maximum Total pressure ratio of 1.67 near the stall region, with a minimum mass flow rate of 33.14 [kg/s] and an adiabatic efficiency of 88 %. The maximum adiabatic efficiency of the compressor is achieved at its design point and is 92.26 % with a total pressure ratio of 1.635 and a mass flow rate of 33.91 [kg/s]. Another validation perspective for the numerical results compared the available experimental data of total pressure ratio and total temperature ratio distribution from the hub to the shroud at the design point with the numerical results, as shown in Fig. 7 . Capturing the complete trend of characteristic curves and radial profiles all proved the valid results of the numerical method. squealer-tip geometry In this research, an innovative method is used to produce the squealer tip geometry for the rotor blade which is applied for both suction and pressure surfaces. The effect of the squealer is investigated at choke, design and near stall conditions. Parameterization In this research, two spline curves are employed to generate squealer-tip geometry in the axial compressor blade, simultaneously in suction and pressure surfaces. Three control points define the depth of the squealer starting from an initial predefined span to the tip-span on the pressure side (a 1 , a 2 , and a 3 ) and suction side (a 4 , a 5 , and a 6 ). The aforementioned starting span is also an optimization parameter (a 7 ), determining the starting location of the squealer in the spanwise direction. Fig. 8 demonstrates a schematic view of the squealer geometry in the rotary blade tip of an axial compressor. A normalized coefficient is used to produce a thinner airfoil in the blade tip region. In this way, first the distance ( ) of each point on the suction and pressure surfaces from the camber line is calculated (Eqn. (1) ), then the related coefficient ( ) is multiplied to this distance; and at last the pressure/suction sides of new airfoil coordinates are calculated by addition or subtraction with camber ( ) coordinates (Eqn. (2) Finally, the three-dimensional geometry is generated by stacking the thinner airfoils on the tip of the blade. Research on the optimal squealer was carried out in two separate simulations, for two-sided (suction-pressure surfaces) squealer and one-sided squealer. Fig. 9 shows the squealer production for two-sided suction-pressure, while Fig. 10 , Fig. 11 show the one-sided squealer production for a suction and pressure surface, respectively. constraints For the design parameters, the constraints are considered to produce the geometries for the squealer tip rotor. These parameters are graphically presented in Fig. 12 . Parameters a 3 and a 6 define the relative location of the first control point of the squealer geometry. For the parameters a 3 and a 6 , the maximum value is set to be 1 which corresponds to the original airfoil without squealer. The parameters a 2 and a 5 are the relative distance of the second control points from the camber line to the first control point. A maximum value of 1 for these parameters means that the first and second control points are coincident. Similarly, parameters a 1 and a 4 define the relative distance of the third control points from the camber line to the second control points. Here, a maximum value of 1 means the coincidence of the second and the third control points. The variable a 7 also defines the spanwise location of the first profile for the squealer geometry. Its minimum and maximum values are set to be 90 % and 100 %, respectively. Table 2 shows the minimum and maximum limits of the squealer-tip coefficients. The coefficients are presented the relative percentage of airfoil thickness at each section. Table 2 summarizes the minimum and maximum values for the defined design parameters. objective functions The objective functions of this research include three main performance parameters of a compressor including corrected mass flow rate, total pressure ratio and adiabatic efficiency according to equations (3) , (4) , (5) . design of experiments Design of experiments (DoE) refers to methods used to investigate and explore the effects of different design variables under various conditions on the results [ 13 ]. So, the design of experiment using Taguchi's approach has been used to study the sensitivity of different compressor performance parameters to variation of defined geometrical parameters mentioned in previous sections. Taguchi DOE approach Considering the number of design variables which are 3 parameters for pressure side, 3 parameters for suction side and 1 parameter for the starting location of squealer-tip, the L-27 OA, meaning 27 three-level factors on 7 design variables has been used to investigate the results. Table 3 demonstrates the L-27 OA [ 13 ]. sensitivity analysis The squealer-tip rotor geometry and grid generation and numerical simulation were performed for all the trials of DOE matrix, and the results of objective functions were extracted for the choke, design and near stall operating regions of design speed. These performance parameters and their variables are utilized to perform the sensitivity analysis. In this way, the results are specified as y 1 to y 27 for which the subscript corresponds to the trial number. For each of the design variables, the average function is calculated using equation (6) in which , and are the mean of the objective functions for minimum, maximum and medium case of variable A, respectively. The sum of all simulations is represented by the variable Sum, while n total is the total number of experiments. The correction factor is determined with C.F. (Eqn. (7) ). The sum of the squares of the factors related to each parameter is denoted by the SOF (Eqn. (8) ). The participation percentage of each parameter is also determined by the PP (which is presented in Eqn. (9) ) [ 13 ]. Having calculated these parameters, the effects of the design variables (three levels factor) on the objective functions have been obtained. Fig. 13 demonstrates the percentage of sensitivities of the objective functions. The results of sensitivity analysis are summarized below. • The control points of the suction surface and the start of the squealer (a 7 ) have the greatest effect on the mass flow rate changes of all three operating points. • In both suction and pressure surfaces, the starting point of the squealer tip primarily affects the on-design compressor total pressure ratio. • The control point of the squealer height (a 7 ) as well as the control points of the suction surface have a great effect on the adiabatic efficiency (design and near stall points) of the compressor. • a 1 and a 2 , mainly affect the two parameters of the leakage mass flow rate and the tip flow velocity. • Parameter a6 appears to significantly affect all performance parameters in the near stall operating point. optimization process The optimization process includes the use of artificial neural networks for accurate prediction of the compressor performance and reduction of the CFD run time, coupling with the optimizer algorithm until reaching the desired objectives, and finally presenting the optimal results obtained, which has been explained in this section. penalties and objective function Using a penalty is a common method to strategize the results towards improvement, and prevent the reduction of the performance values compared to the reference values of Rotor-67. Therefore, the penalties of Equations (10) , (11) , (12) are set in the objective function of the genetic algorithm. Improving the stall efficiency and preventing reduction of the choke efficiency is one of the most important research goals, and therefore, a coefficient has been used in the equation of objective function in Equation (13) . Funding There is no funding for this research. Data availability statement The data that support the findings of this study are available on request from the corresponding author. CRediT authorship contribution statement Mojtaba Heidarian Shahri: Writing - original draft, Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation. Saeid Habibzadeh: Writing - original draft, Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation. Ali Madadi: Writing - review & editing, Supervision, Resources, Project administration, Formal analysis, Data curation, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments Not applicable.

CC BY

no

2024-01-16 23:42:01

Heliyon. 2023 Dec 21; 10(1):e23665

oa_package/d7/bc/PMC10788449.tar.gz

PMC10788466

38071459

INTRODUCTION In the plant immune system, the first line of defence against pathogenic microorganisms, pattern‐triggered immunity (PTI) is mediated by membrane‐localized pattern recognition receptors (PRRs) that recognize microbial‐ or pathogen‐associated molecular patterns (MAMPs or PAMPs). Subsequently, effector‐triggered immunity (ETI) recognizes pathogen effectors by intracellular nucleotide‐binding leucine‐rich repeat receptors (NLRs) to stimulate the immune response (Jones & Dangl, 2006 ). When PTI or ETI is triggered, a cascade of signals will expand and extend from the site of invasion to the downstream of immunity, causing plants to limit pathogen colonization and invasion. Transcription factors (TFs), especially WRKYs, play a critical role in this process. For example, in the immune response induced by flg22, there is a mitogen‐activated protein kinases cascade (MAPK), an indispensable component in the process of plant immune signal transduction. The immune signal is transmitted downward through MEKK1, which affects the downstream TFs such as WRKY22 and WRKY29 to achieve immune signal transduction (Asai et al., 2002 ). MPK3 and MPK6 can directly phosphorylate WRKY33 to promote phytoalexin biosynthesis in Arabidopsis (Mao et al., 2011 ). Phosphorylation of WRKY8 by MAPK functions in the defence response in Nicotiana benthamiana (Ishihama et al., 2011 ). These studies demonstrate that WRKY TFs play an important role in coordinating plant immunity signalling. WRKY TFs are plant‐specific factors that can control the transcription of various genes and participate in the regulation of a variety of plant life activities. They were first identified in sweet potato by Ishiguro and Nakamura ( 1994 ). Subsequently, several WRKY TFs have been reported in more than 20 plant species, including rice, Arabidopsis , and tomato (Huang et al., 2012 ; Wu et al., 2005 ). WRKY TFs are important regulators of the defence response at the transcriptional level. Knockdown of CaWRKY1 in pepper resulted in a reduction of Xanthomonas growth in leaves, demonstrating its important regulatory role in pathogen‐induced immune responses (Oh et al., 2010 ). WRKY11 and WRKY17 negatively regulate plant resistance to Pseudomonas syringae in Arabidopsis (Journot‐Catalino et al., 2006 ). MdWRKY100 can improve leaf resistance to Colletotrichum gloeosporioides in apple (Zhang et al., 2019 ). However, the contribution and regulatory mechanism through which WRKY TFs are involved in protecting apple from V. mali invasion is not yet clear. TFs often require some transcriptional regulators to assist their function, and VQ motif‐containing proteins are one of the key proteins. VQ proteins play an important role in the response of plants to biotic stress (Jing & Lin, 2015 ). The transcription level of AtVQ23 / SIB1 was strongly induced by P. syringae and Botrytis cinerea infection, and gene overexpression improved the disease resistance in Arabidopsis (Lai et al., 2011 ; Xie et al., 2010 ). Overexpression of AtVQ10 enhanced resistance to B. cinerea , whereas the vq10 mutant reduced resistance to the pathogen (Chen et al., 2018 ). As transcriptional regulators, VQ proteins can interact with a variety of TFs, including WRKY, to participate in the response to biotic stress (Chi et al., 2013 ; Jing & Lin, 2015 ). For instance, AtVQ23 and AtVQ16 could interact and activate WRKY33 by enhancing its DNA‐binding activity to improve plant disease resistance (Lai et al., 2011 ). Nevertheless, there are few studies on the joint regulatory roles of VQ proteins and WRKY TFs in resistance to V. mali . Apple Valsa canker, caused by the fungus V. mali , is one of the most severe diseases of apple (Abe et al., 2007 ; Xu et al., 2020 ; Yin et al., 2016 ). In this study, MdVQ12 was upregulated during V. mali infection. Therefore, we thought that it might be involved in the regulation of resistance to apple Valsa canker. However, the regulatory mechanism of MdVQ12 to V. mali resistance remains a mystery. Here, we reported that MdVQ12 confers apple resistance to V. mali by regulating the expression of the histone deacetylase gene MdHDA19 . Histone acetylation plays an important role in plant epigenetic modification and this process is reversible, mainly including histone acetyltransferases (HATs) and histone deacetylases (HDACs) (Ma et al., 2013 ). Histone deacetylases are critical for plant growth, development, and stress response (Ma et al., 2013 ; Zhou et al., 2005 ). This study provides new insights into the molecular mechanism of the resistance to V. mali and an important reference value for the breeding of apple disease resistance.

RESULTS MdVQ12 positively regulates apple resistance to V. mali The analysis of MdVQ12's conserved domain identified a VQ domain (Figure S1a ). Protein feature visualization showed that this protein is located inside the cytomembrane, indicating that it is an intracellular localization protein (Figure S1b ). Subcellular localization analysis revealed that it was localized to the nucleus (Figure S1c ). Furthermore, upregulation of MdVQ12 relative expression was detected during V. mali inoculation (Figure S1d ), suggesting its involvement in the responses to V. mali infection. Next, stable transgenic apple calli expressing MdVQ12 were established to characterize the function of MdVQ12 (Figure S2a ). Calli infected for 4 days were used to determine lesion area, H 2 O 2 , and O 2− levels. Results indicated that MdVQ12 ‐OE‐2/3/6 apple calli exhibited increased resistance to V. mali infection, with 31.4% ± 5.6%, 32.4% ± 6.3%, and 25.1% ± 6.4% reductions in lesion areas compared to the wild type (WT) (Figure S2b,c ). Additionally, MdVQ12‐ overexpressing apple calli exhibited significantly higher levels of reactive oxygen species (ROS) compared with the WT (Figure S2d,e ). We then made an association study by showing the R 2 and p values between levels of MdVQ12 transcripts and lesion area, H 2 O 2 content, and O 2− content (Table S1 ). These results demonstrated that MdVQ12 's capacity to enhance resistance in apple calli against V. mali . Stable transgenic GL‐3 tissue culture seedlings were obtained for further investigating MdVQ12 functionality. Agarose gel electrophoresis experiments demonstrated the presence of DNA bands exclusively in MdVQ12 ‐OE lines (Figure S3a ). Western blot analysis confirmed the detection of MdVQ12‐HA in MdVQ12 ‐overexpression (OE) lines (Figure S3b ). Reverse transcription‐quantitative PCR (RT‐qPCR) analysis revealed higher expression of MdVQ12 in MdVQ12 ‐OE lines compared to the WT (Figure S3c ). Similarly, gene silencing lines were characterized. Fluorescent labelling indicated the presence of green fluorescence solely in MdVQ12 ‐RNAi lines (Figure S4a ). Agarose gel electrophoresis experiments detected DNA bands specifically in MdVQ12 ‐RNAi lines (Figure S4b ). RT‐qPCR analysis showed lower expression of MdVQ12 in MdVQ12 ‐RNAi lines compared with the WT (Figure S4c ). Subsequently, they underwent V. mali infection, with leaves and twigs exposed for 36 and 48 h, respectively. ROS and callose contents and the O 2− production rate of the leaves were measured at 36 h post‐inoculation (hpi). The results showed that MdVQ12 ‐OE‐3/4/6 led to enhanced resistance in apple leaves and twigs against V. mali . Lesion areas and lengths were reduced by approximately 35.1% ± 4.2%, 46.7% ± 5%, and 54.3% ± 4% and 42.5% ± 3.4%, 50.7% ± 4.8%, and 56.6% ± 2.1%, respectively, relative to the WT. Conversely, MdVQ12 ‐RNAi‐3/6/13 apple leaves and twigs exhibited larger and longer lesions than the WT. Lesion areas and lengths were increased by approximately 51.4% ± 9.7%, 54.4% ± 15.3%, and 74% ± 1.6% and 29.9% ± 7.5%, 35.4% ± 4.2%, and 43.6% ± 9.5%, respectively, relative to the WT (Figure 1a ). Moreover, MdVQ12 ‐overexpressing GL‐3 lines exhibited higher ROS and callose contents, as well as a greater O 2− production rate than the WT, while gene silencing lines showed lower values compared to the WT. The H 2 O 2 content, O 2− content, O 2− production rate, and callose content of MdVQ12 ‐OE‐3/4/6 were 1.49 ± 0.29, 2.18 ± 0.13, and 2.5 ± 0.36 and 1.28 ± 0.09, 1.47 ± 0.11, and 1.68 ± 0.12 and 1.28 ± 0.09, 1.47 ± 0.11, and 1.68 ± 0.12 and 1.28 ± 0.04, 1.51 ± 0.13, and 1.87 ± 0.12 times higher than the WT, respectively. In contrast, they were reduced by 55.7% ± 6.9%, 73.3% ± 4.6%, and 84.2% ± 2.8% and 24.7% ± 4.3%, 24.2% ± 8.1%, and 48.9% ± 4.5% and 24.7% ± 4.3%, 24.2% ± 8.1%, and 48.9% ± 4.5% and 30.9% ± 4.6%, 37.8% ± 4.9%, and 57.5% ± 4% in MdVQ12 ‐RNAi‐3/6/13, respectively, relative to the WT (Figure 1b–d ), suggesting that MdVQ12 enhances GL‐3 seedling resistance to V. mali . We then made an association study by showing the R 2 and p values between levels of MdVQ12 transcripts and each trait (i.e., lesion area, lesion length, H 2 O 2 content, O 2− content, O 2− production rate, and callose content) (Table S1 ). The previous results confirm that MdVQ12 positively regulates apple resistance against V. mali . MdVQ12 ‐ induced resistance is MdWRKY23 ‐dependent VQ proteins modulate plant disease resistance by interacting with TFs to regulate their transcriptional activities (Jing & Lin, 2015 ; Li et al., 2014 ). Therefore, to explore the molecular mechanism of MdVQ12 in V. mali resistance, we employed immunoprecipitation‐mass spectrometry (IP‐MS) to identify interacting TFs. Among the candidate proteins, the WRKY TF MdWRKY23 demonstrated interaction with MdVQ12 in yeast two‐hybrid (Y2H) assays (Figure 2a ). This interaction was further confirmed through co‐immunoprecipitation (Co‐IP) and bimolecular fluorescence complementation (BiFC) assays. Co‐IP assay results showed MdVQ12‐HA detection only in the presence of MdWRKY23‐GFP (Figure 2b ). Additionally, the BiFC assay revealed fluorescence when MdVQ12 and MdWRKY23 were co‐expressed, confirming their interaction (Figure 2c ). These results establish that MdVQ12 interacts with MdWRKY23. In the study, MdWRKY23 was divided into seven fragments, and the VQ domain was removed from MdVQ12 to assess the necessity of WRKY and VQ domains for the interaction between MdWRKY23 and MdVQ12 via Y2H assays. Results indicate that the WRKY domain combining the N‐terminal segment can interact with MdVQ12 (Table S2 ). This underscores the essential role of the WRKY domain in facilitating the MdWRKY23‐MdVQ12 interaction. To investigate the relationship between MdVQ12 and MdWRKY23 in V. mali resistance, MdWRKY23 was silenced while overexpressing MdVQ12 in GL‐3 tissue culture seedling leaves. Interestingly, the enhanced resistance to V. mali conferred by MdVQ12 alone was lost after MdWRKY23 silencing (Figure S5 ), indicating that MdVQ12 's ability to enhance apple resistance is contingent upon the presence of MdWRKY23 . MdWRKY23 can bind to the MdHDA19 promoter to activate its expression DNA affinity purification sequencing (DAP‐seq) identified genes bound by MdWRKY23, elucidating its role in regulating resistance against V. mali . MdHDA19 (a histone deacetylase gene) emerged as a downstream target, and was confirmed via electrophoretic mobility shift assay (EMSA) and yeast one‐hybrid (Y1H) assays (Figure 3a,b ). To uncover the transcriptional regulation of MdHDA19 by MdWRKY23, we co‐infiltrated N. benthamiana leaves with constructs pGreenII 62‐SK + proMdHDA19 ‐pGreenII 0800 (combination 1) and MdWRKY23‐pGreenII 62‐SK + proMdHDA19 ‐pGreenII 0800 (combination 2). The luminescence signal and luciferase (LUC) activity were weaker in the leaves of combination 1 than in the leaves of combination 2 (Figure 3c ). Subsequently, apple calli and N. benthamiana leaves were co‐infiltrated with pGreenII 62‐SK + proMdHDA19 ‐pCB308 (combination 3) and MdWRKY23‐pGreenII 62‐SK + proMdHDA19 ‐pCB308 (combination 4). β‐glucuronidase (GUS) staining intensity and GUS activity mirrored luminescence signal and LUC activity (Figure 3d ), suggesting that MdWRKY23 can transcriptionally activate MdHDA19 expression. MdHDA19 positively modulates apple resistance to V. mali Histone acetylation is regulated by histone acetyltransferases and deacetylases, which crucially regulates gene expression. HDA19 has been reported to positively modulate the resistance to the fungal pathogen Alternaria in Arabidopsis by regulating several ethylene (ET) and jasmonic acid (JA) signal transduction‐related genes to participate in the ET and JA signalling pathways (Zhou et al., 2005 ). Therefore, we hypothesized that MdHDA19 similarly contributes to apple Valsa canker resistance. To explore the function of MdHDA19 , we conducted transient expression assays. The transgenic leaves of GL‐3 tissue culture seedlings of MdHDA19 and empty vectors (EVs) were generated (Figure S6a,c ) and infected with V. mali for 32 h. Results confirmed that MdHDA19 ‐OE‐1/5 apple leaves exhibited enhanced resistance to V. mali , with lesion areas decreasing by 42.2% ± 3.9% and 54.4% ± 2.2% compared to EV. Conversely, lesion areas in MdHDA19 ‐RNAi‐2/5 apple leaves were 64.4% ± 14.1% and 55% ± 11.7% larger than EV (Figure S6b,d ). In addition, we made an association study by showing the R 2 and p values between levels of MdHDA19 transcripts and lesion area (Table S1 ). These results demonstrated that MdHDA19 bolsters GL‐3 leaf resistance against V. mali . To explore whether MdHDA19 is involved in ET and JA signalling pathways, we measured the relative expression of ET ( MdERF1 ) and JA ( MdCOI1 , MdMYC2 , MdLOX3 , and MdVSP2 ) signal transduction‐related genes in apple leaves. The results showed that they were all upregulated when MdHDA19 was overexpressed compared with the EVs (Figure S7 ). Because MdHDA19 is a histone deacetylase, we investigated whether it has histone deacetylase activity and whether the activation of this activity is related to the ET and JA pathways. In apple leaves overexpressing MdHDA19 , we quantitatively measured the expression levels of genes related to the ET and JA pathways after treatment with the histone deacetylase inhibitor trichostatin A (TSA). The results demonstrated that after TSA treatment, the expression levels of related genes were significantly decreased in the apple leaves overexpressing MdHDA19 , with some even decreasing to levels close to the control (Figure S8 ). These findings indicate that MdHDA19 possesses histone deacetylase activity and its activation is associated with both ET and JA signalling pathways. Subsequently, stable transgenic apple calli expressing MdHDA19 were established to investigate the function of MdHDA19 (Figure 4a ). The calli were infected with V. mali for 3 days and H 2 O 2 and O 2− levels were measured at 3 days post‐inoculation (dpi). The results indicated that MdHDA19 ‐OE‐1/3/4 apple calli exhibited increased resistance to V. mali infection, with 30.4% ± 7.5%, 51.1% ± 1.5%, and 60.7% ± 4.7% reductions in lesion areas compared to the WT (Figure 4b,c ). In addition, MdHDA19‐ overexpressing apple calli exhibited significantly higher levels of ROS compared to the WT. The H 2 O 2 content and O 2− content of MdHDA19 ‐OE‐1/3/4 were 1.39 ± 0.11, 1.56 ± 0.02, and 1.78 ± 0.14 and 1.71 ± 0.13, 2 ± 0.15, and 2.23 ± 0.2 times higher than the WT, respectively (Figure 4d,e ). We then made an association study by showing the R 2 and p values between levels of MdHDA19 transcripts and lesion area, H 2 O 2 content, and O 2− content (Table S1 ). These results demonstrate that MdHDA19 can enhance the resistance of apple calli to V. mali . Similarly, we measured the expression levels of ET and JA signal transduction‐related genes in apple calli. Consistent with the results of GL‐3 leaves, they were also upregulated in the MdHDA19 ‐overexpressing apple calli compared with the WT (Figure 5 ); therefore, we thought that MdHDA19 was involved in the ET and JA signalling pathways and thus enhanced apple resistance to V. mali . MdVQ12 functions as a positive transcriptional regulator of MdWRKY23 and confers apple resistance to V. mali by activating the ET and JA signalling pathways Because VQ proteins usually act in conjunction with TFs to affect the transcriptional activity of TFs (Jing & Lin, 2015 ; Lei et al., 2017 ), we investigated MdVQ12 's influence on the transcriptional activity of MdWRKY23 by detecting luminescence signals and LUC activity. N. benthamiana leaves were co‐infiltrated with various combinations: combination 1, combination 2, and combination 2 together with MdVQ12‐pGreenII 62‐SK (combination 5). The results showed that both luminescence signal and LUC activity were stronger when combination 5 was co‐expressed than when combination 2 was co‐expressed (Figure 6a,b ), indicating that MdVQ12 functions as a positive transcriptional regulator of MdWRKY23. As MdWRKY23 was identified to transcriptionally activate MdHDA19 , and MdVQ12 acts as a positive transcriptional regulator of MdWRKY23, we assessed the relative expression levels of MdHDA19 in MdVQ12 ‐overexpressing lines. The results indicated a significant upregulation of MdHDA19 (Figure 6c ). We postulated that MdVQ12 may also modulate the ET and JA signalling pathways mediated by MdHDA19 . Accordingly, we quantitatively assessed genes associated with the ET and JA signalling pathways. The results showed a significant increase in their accumulation in MdVQ12 ‐overexpressing lines (Figure 6d ), suggesting that MdVQ12 enhances apple resistance to V. mali by regulating MdHDA19 expression and thereby activating the ET and JA signalling pathways. Taken together, MdVQ12 was able to activate MdHDA19 ‐mediated ET and JA signalling pathways by enhancing the transcriptional activation activity of MdWRKY23 on MdHDA19 , which in turn further enhanced the resistance against V. mali .

DISCUSSION Apple Valsa canker, attributed to V. mali , inflicts significant economic losses. The poor efficiency and effectiveness of traditional control methods have limited apple production. Identifying disease resistance genes remains the most cost‐effective disease control approach. VQ proteins regulate many aspects of plant growth and development, including plant disease resistance, by interacting with TFs, modulating their transcriptional activity (Chi et al., 2013 ; Jing & Lin, 2015 ; Lai et al., 2011 ; Li et al., 2014 ). However, the molecular mechanisms of VQ proteins in V. mali resistance remain unclear. In this study, we found that MdVQ12 confers apple resistance to V. mali by facilitating MdWRKY23's transcriptional activation of MdHDA19 in the ET and JA signalling pathways. Previous studies have shown that the function of VQ proteins is largely affected by the VQ motif (FxxhVQxhTG) (Jing & Lin, 2015 ). There is a conserved VQ motif in MdVQ12; therefore, MdVQ12 should putatively have the typical functions of VQ proteins. VQ proteins regulate plant immunity, for example, AtVQ21 overexpression in Arabidopsis enhanced resistance to P. syringae (Andreasson et al., 2005 ) but reduced resistance to B. cinerea (Fiil & Petersen, 2011 ; Petersen et al., 2010 ). In our study, MdVQ12 increased apple resistance to V. mali , contributing to VQ protein research in plant immunity. VQ proteins function by recruiting other TFs (i.e., MdWRKY23) that activate downstream genes involved in disease resistance (Lai et al., 2011 ; current study). Here, we found that MdVQ12 could interact with MdWRKY23. The WRKY domain in WRKY TFs is required for protein–protein interactions (Eulgem et al., 2000 ). Here, we established that the WRKY domain in MdWRKY23 is essential for the MdWRKY23–MdVQ12 interaction. The cis ‐acting element W‐box ([C/T] TGAC [C/T]) in gene promoters serves as a binding site for WRKY TFs, and mutations within TGAC can impair binding (Rushton et al., 2010 ). Our DAP‐seq results revealed the presence of a W‐box in the promoter of the histone deacetylase gene MdHDA19 , and MdWRKY23 was found to bind to it, thereby activating MdHDA19 expression. Previous studies have demonstrated that HDACs exhibit histone deacetylase activity attributed to their role as histone deacetylases, and this activity is closely associated with ET and JA signalling. For instance, Arabidopsis HDA6 displays histone deacetylase activity, which can globally influence histone acetylation levels. HDA6 mutant and RNAi plants exhibit higher levels of histone acetylation compared to the WT, and the expression of ET and JA signalling‐related genes is downregulated (Wu et al., 2008 ). Similarly, Arabidopsis HDA19 also possesses histone deacetylase activity. Overexpression of HDA19 leads to reduced histone acetylation levels compared to the WT, enhanced resistance to the fungal pathogen Alternaria , and upregulation of ET and JA signalling‐related genes. Conversely, HDA19 RNAi plants show increased histone acetylation levels and downregulated expression of ET and JA signalling‐related genes (Zhou et al., 2005 ). Therefore, we propose that MdHDA19 has histone deacetylase activity and its activation is associated with both ET and JA signalling pathways. In this study, we found that several ET and JA signalling‐related genes were upregulated in MdHDA19 ‐overexpressing apple leaves and calli, leading to increased resistance to the fungal pathogen V. mali . Additionally, these genes exhibited significantly decreased expression levels after TSA treatment. These results indicate that MdHDA19 has histone deacetylase activity and that the activation of this activity is related to the ET and JA signalling pathways, ultimately enhancing apple resistance to the pathogenic fungus V. mali . Moreover, consistent with previous reports that VQ proteins can modulate the transcriptional activity of TFs, we demonstrated that MdVQ12 could promote the transcriptional activation of MdWRKY23 on MdHDA19 . However, there are no reports on the relationship between VQ proteins and HDACs. Therefore, this study offers novel insights into the regulatory mechanism of VQ proteins. In plant defence, ROS burst and callose deposition are fundamental processes crucial for the defensive reaction (Boller & Felix, 2009 ; Schwessinger & Ronald, 2012 ). Callose deposition increases cell wall thickness, thereby slowing pathogen invasion, making it a universal model for quantifying plant defence responses (Luna et al., 2011 ; Nishimura et al., 2003 ). ROS play a central role in defending against pathogen invasion and activating plant immune responses, conferring resistance (Chen et al., 1993 ; Kariola et al., 2005 ; Qi et al., 2017 ; Sharma et al., 2012 ). VQ proteins, functioning as transcriptional regulators, typically co‐regulate plant immune responses along with their interacting TFs, including ROS burst and callose deposition. In this study, we confirmed that MdVQ12 was induced during V. mali infection and significantly enhanced ROS and callose accumulation, advancing our understanding of VQ protein‐mediated disease resistance. The results of our regulatory approach are summarized in a model in Figure 6e . MdVQ12 interacts with MdWRKY23 to form a complex in this model. This interaction modulates the transcriptional capacity of MdWRKY23 towards MdHDA19 , and they are novel components of the regulatory network of apple Valsa canker resistance. Furthermore, MdHDA19 contributes to apple resistance against V. mali by participating in the JA and ET signalling pathways. In conclusion, our study establishes that MdVQ12 acts as an activator within the MdWRKY23‐MdHDA19 module, which mediates apple Valsa canker resistance. This work provides a novel regulatory network for understanding disease modulation by VQ proteins. Our findings offer theoretical guidance and technical support for the cultivation of disease‐resistant germplasm resources.

Abstract Valine‐glutamine (VQ) motif‐containing proteins play a crucial role in plant biotic stress responses. Apple Valsa canker, caused by the ascomycete Valsa mali , stands as one of the most severe diseases affecting apple trees. Nonetheless, the underlying resistance mechanism of VQ proteins against this disease has remained largely unexplored. This study reports MdVQ12, a VQ motif‐containing protein, as a positive regulator of apple Valsa canker resistance. Genetic transformation experiments demonstrated that MdVQ12 overexpression increased resistance to V. mali , while gene silencing lines exhibited significantly reduced resistance. MdVQ12 interacted with the transcription factor MdWRKY23, which bound to the promoter of the histone deacetylase gene MdHDA19 , activating its expression. MdHDA19 enhanced apple resistance to V. mali by participating in the jasmonic acid (JA) and ethylene (ET) signalling pathways. Additionally, MdVQ12 promoted the transcriptional activity of MdWRKY23 towards MdHDA19 . Our findings reveal that MdVQ12 enhances apple resistance to V. mali by regulating MdHDA19 expression and thereby regulating the JA and ET signalling pathways, offering potential candidate gene resources for breeding apple Valsa canker‐resistant germplasm. MdVQ12 activates MdHDA19 to enhance apple resistance against Valsa mali . Han , P. , Zhang , R. , Li , R. , Li , F. , Nie , J. , Xu , M. et al. ( 2024 ) MdVQ12 confers resistance to Valsa mali by regulating MdHDA19 expression in apple . Molecular Plant Pathology , 25 , e13411 . Available from: 10.1111/mpp.13411

EXPERIMENTAL PROCEDURES Plant and microbe materials The apple tissue culture seedlings are of the GL‐3 genotype (Dai et al., 2013 ). The GL‐3 plantlets and apple cv. Orin calli were cultured on Murashige and Skoog (MS) medium at 25°C. N. benthamiana seedlings were grown in a growth chamber and the V. mali WT strain 03‐8 (Yin et al., 2015 ) were grown in incubators at 25°C. RT‐qPCR analysis Quick RNA isolation kits (Huayueyang Biotechnology) and RevertAid First Strand cDNA synthesis kits (Thermo Scientific) were used for total RNA extraction and cDNA synthesis, respectively. The LightCycler 96 System (Roche) and RealStar Green Mixture (GenStar) were used for RT‐qPCR assays. The reaction procedures were as follows: 10 min at 95°C; then 40 cycles of 15 s at 95°C, 30 s at 60°C, and 30 s at 72°C. MdMDH (Perini et al., 2014 ) was used as an internal control for the normalization of gene expression. To analyse the results, the 2 −ΔΔ C t method (Livak & Schmittgen, 2001 ) was performed. The primers that we used were listed in Table S3 . All operations were performed in triplicate. Bioinformatic analysis, molecular cloning, and vector construction The NCBI (National Center for Biotechnology Information) website ( https://www.ncbi.nlm.nih.gov/ ) was used for domain analysis. The Protter website ( http://wlab.ethz.ch/protter/start/ ) was used for the visualization of protein features. The Phyre2 website ( http://www.sbg.bio.ic.ac.uk/phyre2/html/page.cgi?id=index ) was used for the three‐dimensional structural prediction. The specific primers for molecular cloning were designed based on the sequences from the GDR (Genome Database for Rosaceae) website ( https://www.rosaceae.org/ ) and listed in Table S4 . The genes were amplified from the GL‐3 tissue culture seedling cDNA using the Phanta Max super‐fidelity DNA polymerase (Vazyme). The recombinant vector for stable overexpression ( MdVQ12 ‐OE, MdHDA19 ‐OE) was constructed using pK2GW7 combined with the hemagglutunin (HA) tag. The recombinant vectors for stable silencing ( MdVQ12 ‐RNAi) and transient silencing ( MdWRKY23 ‐RNAi‐GFP, MdHDA19 ‐RNAi) were constructed using pK7GWIWG2D (II) containing the green fluorescent protein (GFP) tag. The pK2GW7 and pK7GWIWG2D (II) vectors were provided by Qingmei Guan of Northwest A&F University. The recombinant vectors for subcellular localization ( MdVQ12 ‐GFP) and transient overexpression ( MdVQ12 ‐OE‐GFP, MdHDA19 ‐OE) were constructed using pCAMBIA1302 containing the GFP tag, which was provided by Xiaojie Wang of Northwest A&F University. The recombinant vectors for BiFC (MdVQ12‐YFP C , MdWRKY23‐YFP N ) were constructed using pSPYNE‐35S and pSPYCE‐35S. The recombinant vectors for GUS activity detection (MdWRKY23‐pGreenII 62‐SK, proMdHDA19 ‐pCB308) were constructed using pGreenII 62‐SK and pCB308. The recombinant vectors for luminescence signal and LUC activity detection (MdVQ12‐pGreenII 62‐SK, MdWRKY23‐pGreenII 62‐SK, p roMdHDA19 ‐pGreenII 0800) were constructed using pGreenII 62‐SK and pGreenII 0800. The recombinant vectors for Y2H (MdWRKY23‐AD, MdVQ12‐BD) were constructed using pGADT7 and pGBKT7. The recombinant vectors for Y1H (MdWRKY23‐AD, proMdHDA19 ‐pHIS2) were constructed using pGADT7 and pHIS2. The recombinant vector for EMSA (MdWRKY23‐His) was constructed using pET‐28a. Genetic transformation, subcellular localization, and BiFC The Agrobacterium tumefaciens strains EHA105 and GV3101 (pSoup‐P19) were used for stable and transient expression, respectively. Transient expression assays were performed using the leaves of 4‐week‐old GL‐3 tissue culture seedlings and N. benthamiana seedlings. Experiments were performed according to Zhang et al. ( 2018 ) and Sun et al. ( 2018 ), respectively. Stable expression assays were performed using 15‐day‐old Orin apple calli and the leaves of 4‐week‐old GL‐3 tissue culture seedlings. Experiments were performed according to Xie et al. ( 2012 ) and Wang et al. ( 2017 ), respectively. For the subcellular localization and BiFC, after transient expression in the leaves of N. benthamiana seedlings for 48 h, the fluorescence signal observation was performed using an FV3000 laser scanning confocal microscope (LSCM) (Olympus). Experiments were performed three times. LUC and GUS analysis After transient expression in Orin apple calli and the leaves of N. benthamiana seedlings for 48 h, the luminescence signal observation was performed using d ‐luciferin (Solarbio) and the PlantView100 multispectral dynamic fluorescence microscopic imaging system (Biolight Biotechnology); the LUC activity was measured using Dual Luciferase Reporter Gene Assay Kits (Yeasen Biotechnology); the GUS staining assays were performed using GUS stain Kits (Coolaber); the GUS activity was measured using GUS gene quantitative detection kits (Coolaber). Tests were performed at least three times. Pathogen infection, ROS and callose contents detection, and TSA treatment Ten‐day‐old Orin apple calli, the leaves of 5‐week‐old, and twigs of 4‐month‐old GL‐3 seedlings were infected with V. mali following the protocol of Han et al. ( 2022 ). They were analysed at 3 or 4 dpi, 32 or 36 hpi, and 48 hpi, respectively. The statistics of lesion areas and lengths were performed using the ImageJ software. The H 2 O 2 content, O 2− content and production rate, and callose content were detected using hydrogen peroxide assay kits, superoxide anion assay kits (spectrophotometry), and callose assay kits (fluorescence) (Comin Biotechnology), respectively. TSA (Solarbio) was used to inhibit histone deacetylation activity, and the TSA treatment assay was performed according to Mehdi et al. ( 2016 ). The experiments were performed with three replications. IP‐MS , Co‐IP , and Y2H The leaves of MdVQ12 ‐overexpressing GL‐3 tissue culture seedlings and transiently expressed N. benthamiana seedlings were used for total protein extraction. Pierce anti‐HA magnetic beads (Thermo Scientific) and GFP‐trap A beads (Chromotek) were used to separate fusion proteins for IP‐MS and Co‐IP, respectively. IP‐MS was conducted using the Q Exactive HF‐X ultrahigh‐resolution liquid chromatography‐mass spectrometry (Thermo Scientific). Western blotting was performed for Co‐IP assays following the description of Nie et al. ( 2021 ). Y2H assays were performed using the yeast strain Y2H Gold. The experiments were conducted as described by Han et al. ( 2019 ). All experiments were repeated three times. DAP ‐seq, EMSA , and Y1H Candidate target genes of MdWRKY23 were obtained via DAP‐seq, which was conducted by the Genedenovo Biotechnology Co. Ltd. (Guangzhou, China). The fusion protein MdWRKY23‐His was purified using the Ni‐NTA resin (Thermo Scientific) as described by Nie et al. ( 2021 ). EMSA was performed using chemiluminescent EMSA kits (Beyotime Biotechnology) as described by Wang et al. ( 2018 ). Y1H assays were performed using the yeast strain Y187. The experiments were conducted as described by Yu et al. ( 2020 ). 3‐amino‐1,2,4‐triazole (Coolaber) was used for self‐activation inhibition. The experiment was repeated three times. Statistical analysis All experiments were replicated at least three times. The one‐way analysis of variance (ANOVA, Tukey's test) or t test analysis of GraphPad Prism v. 8.0.2 was used to determine statistical significance. Data are shown as mean ± SD . CONFLICT OF INTEREST STATEMENT The authors declare no conflicts of interest. Supporting information

ACKNOWLEDGEMENTS We thank Dr Qiong Zhang of Northwest A&F University for her technical support. We also thank Zhiyuan Yin and Xiang Meng of Northwest A&F University for their help with the experiment. This work was supported by the National Natural Science Foundation of China (31871917) and the National Natural Science Foundation of China‐Xinjiang Joint Fund (U19032061007919). DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request.

CC BY

no

2024-01-16 23:42:01

Mol Plant Pathol. 2023 Dec 10; 25(1):e13411

oa_package/3f/3e/PMC10788466.tar.gz

PMC10788467

38010059

INTRODUCTION Small cell lung cancer (SCLC) is an aggressive form of lung cancer characterized by high malignancy and an extremely dismal prognosis. 1 Extensive‐stage SCLC (ES‐SCLC) accounts for 70% of all SCLCs, defined as tumors with distant metastasis or exceeding the area that can be treated within a radiation field. Patients have a 5‐year survival of only 3%. 2 The U.S. Food and Drug Administration (FDA) has approved the antiprogrammed cell death‐ligand 1 (PD‐L1) antibody atezolizumab in combination with carboplatin and etoposide as the first‐line treatment for adult patients with ES‐SCLC. 3 Immune checkpoint inhibitors (ICIs) have shifted the therapeutic paradigm of SCLC, yielding longer median progression‐free survival (mPFS) (5.2 m vs. 4.3 m) and median overall survival (mOS) (12.3 m vs. 10.3 m) than placebo plus carboplatin and etoposide. A substantial proportion of patients still show no response to ICIs, which suggests that it is of paramount importance to identify reliable predictors which will enable more precise delivery of immunotherapy. Biomarkers such as intertumoral PD‐L1 expression, tumor mutation burden (TMB), tumor‐infiltrating T lymphocytes (TILs) and neoantigens have been identified to predict the efficacy of ICIs, 4 , 5 , 6 but the clinical predictive values are not entirely consistent. Notably, several studies in preclinical models have highlighted the crucial impact of the gut microbiome (GM) in modifying tumor responses to immunotherapy: greater GM diversity and certain bacterial species are linked to improved ICI outcomes, 7 , 8 , 9 showing that the GM plays a key role in regulating the host innate and acquired immune response. Exposure to antibiotics (ATBs) before or during ICI treatment can affect the integrity of the GM and lead to intestinal dysbiosis, which has a profoundly negative impact on the treatment responses of various malignancies, including metastatic lung cancer, renal cell cancer melanoma and hepatocellular carcinoma. 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 However, most of these studies only included small samples or patients with various cancer types, rather than focusing specifically on SCLC. Thus, the association between the efficacy of ICIs and ATB exposure in ES‐SCLC remains unclear. In this retrospective study, we compared the clinicopathological features and responses in a Chinese cohort of 214 ES‐SCLC patients who received ICIs with or without concomitant ATB treatment and analyzed the prognostic impact of ATB exposure on ICI outcomes.

METHODS Patients We reviewed the electronic medical records of all patients diagnosed with ES‐SCLC who started anti‐PD‐1/PD‐L1‐based therapies from July 2019 to December 2020 at Shandong Cancer Hospital and Institute, China. Figure 1 summarizes the patient selection process. Finally, 214 patients were evaluable for response assessment. All patients received ICIs as monotherapy, in combination with chemotherapy or angiogenesis inhibitors. The ICI information is shown in Table S1 . Covariates for the statistical model were selected based on their prognostic values for ES‐SCLC, mainly including age, gender, Karnofsky performance status (KPS), nutritional risk screening 2002 (NRS2002), numerical rating scale (NRS), CAPRINI, body mass index (BMI), smoking history, drinking history, hypertension, diabetes mellitus, sites of metastases, and previous therapy. The therapeutic regimens, type (if any) of ATB used and the date of death or last follow‐up were recorded. The treatment was continued until disease progression, clinical deterioration, or unacceptable toxicity. This study was approved by the ethics review board of the Shandong Cancer Hospital and Institute. The requirement for informed consent was waived given the retrospective nature of the study. Time window of ATB exposure Previous studies examining the effect of ATB on immunotherapy outcomes used time windows varying from 2 weeks to 3 months, and the effect seems to depend on the time window of exposure, stronger effects being reported when the patients took ATB [−60 days; +60 days] around the first initiation of the ICI. 18 Therefore, we hypothesized that a time window of ATB exposure within 2 months before or after the first infusion of ICIs for patients with ES‐SCLC would be associated with worse PFS and OS. The use of ATB was determined from information about concomitant medications recorded in the case report forms. All ATB classes were considered, including penicillin, cephalosporins, and quinolones (Table S2 ). Statistical analysis Clinicopathological features were descriptively summarized by percentages. PFS was defined as the period from initiation of ICI treatment to the date of disease progression or death from any cause, whichever occurred first; OS was defined as the period from initiation of ICI therapy to the date of death from any cause. PFS and OS curves were drawn using the Kaplan–Meier method and were compared by the log‐rank test. Cox proportional hazards regression models were used to analyze the correlation of baseline clinical characteristics with the efficacy of ICIs. Possible factors associated with PFS and OS were first identified by a screening process via univariate Cox models. Variables with p < 0.05 were then tested in separate multivariate Cox models. Hazard ratios (HRs) estimated from the Cox analysis are reported with their 95% confidence intervals (CIs). All statistical analyses were conducted using SPSS version 27.0, GraphPad Prism version 9.5.1 and R version 4.2.1. All statistical tests were two‐sided, and p < 0.05 was the threshold for statistical significance.

RESULTS Patient characteristics A total of 214 patients were included in this study. We first dichotomized the patients according to ATB exposure: 41 (19.2%) received ATB within 2 months before or after the first initiation of ICI therapy (ATB group), and the remaining 173 patients did not receive ATB (non‐ATB group). The variables were well balanced across the ATB and non‐ATB groups, although there were greater proportions of brain metastasis (46.3% vs. 29.5%, p = 0.039) and thoracic radiotherapy (48.8% vs. 30.1%, p = 0.023) in the ATB group. KPS, NRS2002, NRS, CAPRINI and BMI at baseline between ATB and non‐ATB groups were observed no significantly difference indicating that there was no disparity in the health status at baseline. All patients received anti‐PD‐1/PD‐L1‐based immunotherapies. Of the included patients, 166 received ICIs plus chemotherapy, 17 received ICIs as monotherapy, 22 were treated with ICIs plus angiogenesis inhibitors (apatinib or anlotinib), and nine were treated with ICIs plus chemotherapy and angiogenesis inhibitors. The clinicopathological characteristics of all included patients are shown in Table 1 . ATB treatment characteristics A total of 41 patients (19.2%) received at least one dose of ATB. In six of them (14.62%), more than one ATB was administered. The most frequently prescribed ATB was penicillin (20 cases, 41.7%), followed by quinolones (11 cases, 22.9%), cephalosporins (10 cases, 22.8%), carbapenems (3 cases, 6.3%), glycopeptides (2 cases, 4.2%), aminoglycosides (1 case, 2.1%), and macrolides (1 case, 2.1%) (Table S2 ). ATB was administered intravenously route in 39 cases (95.12%) and orally route in two cases (4.88%). The most common indication for ATB treatment was pneumonitis, which occurred in 31 (75.6%) of the patients in the ATB group (Table S3 ). Correlation between ATB exposure and clinical outcomes We first assessed the impact of ATB exposure on clinical outcomes in the total cohort. In the analysis of all 214 patients, the ATB group showed a shorter mPFS: 4.3 months versus 6.3 months in the non‐ATB group (HR 1.43, 95% CI: 0.97–2.11; log‐rank test, p = 0.043, Figure 2a ). The ATB group also had a shorter mOS (6.9 vs. 13 months; HR 1.47, 95% CI: 0.98–2.20; log‐rank test, p = 0.033, Figure 2b ). We further investigated the impact of ATB exposure on survival according to immunotherapeutic regimen (Figure S1 ). We also conducted subgroup analyses based on various clinicopathological factors. The results were consistent with those of the total cohort analyses, with OS and PFS being superior in the non‐ATB group in most of the analyses (Figure 3a,b ). Multivariate analysis We performed univariate and multivariate Cox regression analyses to explore the potential clinical and pathological parameters that may be associated with PFS or OS (Tables 2 and 3 ). In univariate analysis, we found that patients with concomitant ATB treatment had significantly shorter PFS (HR = 1.43, 95% CI: 1.01–2.02, p = 0.044) and OS (HR = 1.47, 95% CI: 1.03–2.11, p = 0.034) than patients without ATB treatment. Patients with diabetes mellitus (PFS: HR = 1.59, 95% CI: 1.09–2.33, p = 0.016; OS: HR = 1.63, 95% CI: 1.10–2.41, p = 0.016) or metastases (PFS: HR = 1.29, 95% CI: 1.12–1.48, p < 0.001; OS: HR = 1.33, 95% CI: 1.15–1.54, p < 0.001) also had worse PFS and OS. Female patients had better OS (HR = 0.67, 95% CI: 0.47–0.96, p = 0.027). These significant factors, together with the variables with p < 0.05 identified in univariable analysis, were included in multivariate analysis for both PFS and OS. Importantly, concomitant ATB treatment remained an independent prognostic factor for PFS (HR = 1.47, 95% CI: 1.03–2.09, p = 0.035) and OS (HR = 1.46, 95% CI: 1.01–2.11, p = 0.043) after adjusting for other confounding factors. Diabetes mellitus (PFS: HR = 1.72, 95% CI: 1.16–2.54, p = 0.006; OS: HR = 1.66, 95% CI: 1.11–2.49, p = 0.014), metastases (PFS: HR = 1.27, 95% CI: 1.10–1.47, p = 0.001; OS: HR = 1.28, 95% CI: 1.10–1.50, p = 0.002) and previous therapy (PFS: HR = 1.88, 95% CI: 1.37–2.58, p < 0.001; OS: HR = 1.51, 95% CI: 1.09–2.11, p = 0.015) were significantly associated with worse PFS and OS.

DISCUSSION To our knowledge, this is the first study to demonstrate the potential harmful effects of ATB exposure in Chinese ES‐SCLC patients receiving anti‐PD1/PD‐L1‐based immunotherapy. Our results confirm that ATB exposure within 2 months before or after the first infusion of ICIs is significantly associated with worse PFS and OS in ES‐SCLC patients. With the increasing use of ICIs for various malignancies, much effort has been made to identify reliable biomarkers that may predict the efficacy of ICIs, and ATB exposure has recently emerged as one of them. Our findings are consistent with studies reporting adverse effects of ATB in patients receiving ICIs for NSCLC, 10 , 11 , 12 , 14 , 15 melanoma, 13 , 15 renal cell carcinoma, 11 hepatocellular carcinoma, 16 , 17 and other tumor types. The dysbiosis of the GM has been associated with various human health conditions and diseases, such as extraintestinal autoimmune diseases, 19 Alzheimer's disease, 20 Parkinson's disease, 21 and asthma. 22 Accumulating evidence suggests that a loss of diversity or a shift in the composition of the GM can attenuate the therapeutic efficacy of ICIs, indicating that the diversity of the GM may play a prominent role in modulating the tumor response to ICI therapy. 7 , 9 , 23 , 24 , 25 Gopalakrishnan V et al. 7 reported that patients with a favorable diversity of GM have enhanced systemic and antitumor immune responses mediated by increased antigen presentation and improved effector T cell function in the periphery and the tumor microenvironment in melanoma patients in the Western population. Routy et al. 9 found that primary resistance to ICIs can be attributed to abnormal GM composition, and fecal microbiota transplantation (FMT) from cancer patients who responded to ICIs into germ‐free or antibiotic‐treated mice ameliorated the antitumor effects of PD‐1 blockade, whereas FMT from nonresponding patients failed to do so, potentially highlighting the central role of the GM in driving adaptive resistance to ICIs. 26 Using the gold‐standard 16S ribosomal RNA sequence, previous studies have found that the enrichment of certain stool bacterial species, including Ruminococcus, Akkermansia, and Bifidobacteria, is associated with a higher likelihood of response to ICIs. 8 , 17 , 27 ATB exposure has been addressed as a detrimental predictor of ICI efficacy, being associated with the highest disruption of and potential to induce long‐lasting changes to the GM by causing such profound changes as a decrease in bacterial diversity, 28 changes in the abundances of certain bacteria 29 and impairment of the effectiveness of the cytotoxic T cell response against cancer. 30 Owing to the geography, ethnicity and subsistence‐specific variations in human GM composition and diversity, 31 the impact of ATB exposure on ICI efficacy still needs to be confirmed in different patient cohorts. We also investigated the impact of ATB exposure under different immunotherapeutic regimens, and our data demonstrated a negative effect of ATB exposure on PFS (HR 1.37, 95% CI: 0.87–2.15; Gehan‐Breslow Wilcoxon test, p = 0.045, Figure S1A ) and OS (HR 1.54, 95% CI: 0.95–2.48; Gehan‐Breslow Wilcoxon test, p = 0.0216, Figure S1B ) in patients receiving ICIs plus chemotherapy, as expected. However, no significant difference in PFS or OS was observed in patients who received ICI monotherapy, ICI plus angiogenesis inhibitors, or ICI plus chemotherapy and angiogenesis inhibitors (see Figure S1C–H ). Notably, relatively few and heterozygous patients were included in the subgroup analysis. Among the 19, 22, and nine patients in the ICI monotherapy, ICI plus angiogenesis inhibitors, ICI plus chemotherapy and angiogenesis inhibitors cohorts, respectively, only five, four, and two patients were identified in the ATB group. We speculate that the potential imbalance of patient selection and the small sample size might have confounded the survival analysis. Due to the limited data on the prognostic impact of ATB on the combination of ICIs and chemotherapy or angiogenesis inhibitors in lung cancer, larger studies are undoubtedly needed to better understand this phenomenon. Proton pump inhibitors (PPIs), another medication class that can alter the composition of the GM, have also been evaluated for their influence on ICI efficacy. 10 , 32 PPIs are also widely used in patients with cancer to prevent oversecretion of gastric acid and indigestion, which are often induced by chemotherapy. In our cohort, most patients received ICIs plus chemotherapy with concomitant PPIs, so we did not include PPIs in our analyses. The limitations in the present study must be acknowledged. First, this was a retrospective study performed at a single cancer center, making selection bias inevitable. Several discrepancies in baseline characteristics were observed, including a higher rate of brain metastasis and more patients treated with thoracic radiotherapy in the ATB group, which might have confounded our analysis. To compensate for these discrepancies, we evaluated the impact of ATB treatment across individual subgroups and performed multivariable analysis to adjust for multiple prognostic factors. Second, as the patients included in this study were only representative of a single nation, it is difficult to extrapolate the findings to other ethnic populations. In addition, the population was slightly heterogeneous regarding the treatment regimen received, which was attributed to some reasons such as intolerance to chemotherapy, economic hardship, and refusal of treatment by patients. Moreover, we failed to investigate the impact of ATB based on biomarkers, such as PD‐L1 expression, TMB and TILs, because the detection of these biomarkers was not mandatory for ES‐SCLC patients before they received ICIs, which might also skew the clinical responses and survival benefits. In addition, the timing and duration of ATB treatment were not clear. Last, based on growing evidence in the literature and in the clinic, we assumed that antimicrobials may cause an imbalance in the GM and consequently diminish the effectiveness of ICIs. However, this study cannot discuss causality between ATB exposure and impaired clinical outcomes of ES‐SCLC patients treated with ICIs, nor can it elucidate the underlying biological mechanisms involved. It can only show an association between ATB exposure and reduced ICI efficacy. As it is not ethically feasible to conduct interventional, randomized, controlled trials in which ATB would be administered to cancer patients treated with ICIs to demonstrate their deleterious impact when compared to their absence, prospective observational studies and interventional trials of microbiome modifiers are urgently needed to uncover the role of the microbiome and improve patient outcomes by carefully recording ATB dosing and important confounders and collecting samples before and after antimicrobial treatment for biomarker discovery and mechanistic exploration. Such studies will reduce the existing publication bias by allowing analyses on more homogeneous populations, especially in terms of treatments received, which is not possible at this stage given the current state of the field. Until then, ATB prescriptions should be cautiously considered in cancer patients receiving ICIs. In conclusion, ATB exposure is associated with worse survival in ES‐SCLC patients receiving ICI therapy. Given the known overutilization of ATBs in the world today, ATB should be prescribed cautiously in ES‐SCLC patients receiving ICI therapy.

Abstract Background Immune checkpoint inhibitors (ICIs) have dramatically shifted the therapeutic paradigm of extensive‐stage small cell lung cancer (ES‐SCLC). Antibiotic (ATB) exposure before or during ICI therapy can harm the integrity of the gut microbiome and lead to intestinal dysbiosis, which has a profoundly negative impact on the treatment response for various malignancies. Whether this is applicable to ES‐SCLC remains unclear. Methods We retrospectively reviewed the electronic medical records of all patients diagnosed with ES‐SCLC who were treated with ICI‐based immunotherapies from July 2019 to December 2020 at Shandong Cancer Hospital and Institute, China. Outcomes with the use of ATBs before or after the first infusion of ICI, including progression‐free survival (PFS) and overall survival (OS), were investigated using the Kaplan–Meier method. Multivariate analyses were also conducted using a Cox proportional hazards model. Results A total of 214 patients were included, among whom 41 (19.2%) received ATBs within 2 months before or after the first initiation of ICI therapy and were assigned to the ATB group. The ATB group showed a shorter median PFS (4.3 vs. 6.3 months; HR = 1.43, 95% CI: 0.97–2.11; p = 0.043) and a significantly shorter median OS (6.9 vs. 13 months; HR = 1.47, 95% CI: 0.98–2.20; p = 0.033) than the non‐ATB group. In the multivariate analysis, ATB exposure was markedly associated with worse PFS (HR = 1.47, 95% CI: 1.03–2.09, p = 0.035) and OS (HR = 1.46, 95% CI: 1.01–2.11, p = 0.043). Conclusions Our results demonstrate that ATB exposure was significantly associated with worse survival in ES‐SCLC patients who received ICI therapy. This is the first study to demonstrate the potential harmful effects of ATB exposure in Chinese ES‐SCLC patients receiving anti‐PD1/PD‐L1‐based immunotherapy. Antibiotic exposure leads to worse efficacy of ICIs in ES‐SCLC. Zhong J , Xiong D , Liu Y , Yuan S . Association of antibiotic exposure with survival in patients with extensive‐stage small cell lung cancer receiving immune checkpoint inhibitor therapy . Thorac Cancer . 2024 ; 15 ( 2 ): 152 – 162 . 10.1111/1759-7714.15172

AUTHOR CONTRIBUTIONS Jiaqi Zhong: conceptualization, data curation, methodology, software, formal analysis, writing ‐ original draft; Dali Xiong: data curation, writing ‐ original draft; Yu Liu: supervision; Shuanghu Yuan: Writing ‐ review and editing. FUNDING INFORMATION This study was supported in part by the National Natural Science Foundation of China (NSFC82073345), Natural Science Innovation and Development Joint Foundation of Shandong Province (ZR202209010002), Jinan Clinical Medicine Science and Technology Innovation Plan (202019060) and the Taishan Scholars Program to Shuanghu Yuan. CONFLICT OF INTEREST STATEMENT The authors declare no potential conflicts of interest. Supporting information

ACKNOWLEDGMENTS We would like to thank all the reviewers who participated in the review. Finally, we wish to thank American Journal Experts ( china.aje.com ) for their inguistic assistance during the preparation of this manuscript. DATA AVAILABILITY STATEMENT The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

CC BY

no

2024-01-16 23:42:01

Thorac Cancer. 2023 Nov 27; 15(2):152-162

oa_package/c6/95/PMC10788467.tar.gz

PMC10788471

38057283

INTRODUCTION Surgical resection remains the primary treatment for non‐small cell lung cancer (NSCLC), but some patients still experience distant metastasis and recurrence postoperatively. This poor outcome may be attributed to the presence of residual micrometastases or subclinical lesions. 1 , 2 In many patients with NSCLC, local therapies alone are insufficient to prevent recurrence, underscoring the need for perioperative treatments to improve NSCLC outcomes. Neoadjuvant chemotherapy administered before definitive local radiotherapy or surgery aims to shrink primary tumors, eradicate subclinical lesions, facilitate subsequent therapies, and improve patient prognosis. Although traditional neoadjuvant chemotherapy can improve prognosis in patients with NSCLC, the 5‐year absolute survival rate only increases by 5%, suggesting that there is still room for improvement in neoadjuvant therapy in patients with initially resectable NSCLC. 3 , 4 In recent years, immune checkpoint inhibitors (ICIs) targeting programmed cell death receptor 1 (PD‐1) and its ligand, PD‐L1, have demonstrated better safety and efficacy than chemotherapy for advanced driver mutation‐negative NSCLC. 5 , 6 , 7 The application of ICIs in neoadjuvant therapy for initially resectable NSCLC can effectively downstage tumors and reduce the risk of postoperative recurrence and distant metastasis, resulting in a significantly improved prognosis. 8 , 9 , 10 The results from the phase 3 CheckMate‐816 trial showed that compared to surgery alone, preoperative application of 2–4 cycles of nivolumab plus chemotherapy could improve long‐term survival, with the 3‐year disease‐free survival rate significantly increasing from 50% to 63%. 9 The majority of evidence of the advantages of neoadjuvant immune therapy comes from phase I/II clinical trials, which have shown major pathological response (MPR) rates ranging from 19% to 45% for single‐agent immunotherapy and from 33% to 83% for immunotherapy combined with other neoadjuvant therapies. 11 , 12 , 13 However, not all patients benefit from neoadjuvant immunochemotherapy, and the degree of benefit varies among individuals. For patients insensitive to neoadjuvant immunochemotherapy, neoadjuvant therapy not only delays the best treatment timing but also incurs high treatment costs. 10 Therefore, effectively identifying the beneficiaries of neoadjuvant immunochemotherapy in NSCLC and enabling the effective monitoring and prediction of neoadjuvant treatment responses are of critical importance. Tertiary lymphoid structures (TLSs) are organized aggregates of immune cells, including B cells, T cells, and dendritic cells, which arise in nonlymphoid tissues. 14 Accumulating evidence indicates that adaptive immune responses can be initiated or enhanced within TLSs, and that certain antitumor antibodies are closely associated with B cells in TLSs. 15 Ng et al. found that B cells and antibody responses in TLSs can target endogenous retroviral envelope proteins, which can be enhanced by immunotherapy. 16 In hepatocellular carcinoma research, scientists have found that an intra‐tumoral cellular triad of PD‐1 hi CD8 + T cells, CXCL13 + T helper cells, and mature regulatory DCs rich in modulatory molecules promote immune responses induced by PD‐1 inhibitor therapy. 17 The high abundance and maturity of TLSs have been validated as favorable diagnostic factors for immunotherapy in various tumors including hepatocellular carcinoma, 18 melanoma, 19 and sarcoma. 20 TLSs form under chronic inflammatory stimuli. Their structure and function can be modulated by specific inflammatory cues, leading to variations across different tissues and diseases. Unlike lymph nodes, TLSs lack an outer encapsulating structure, which makes the inner immune cells more susceptible to constant inflammatory exposure. 21 Cytokines and metabolic factors produced in the surrounding tumor tissues can directly contact immune cells in TLSs, thereby influencing immune responses. 22 , 23 Therefore, we believe that evaluating TLSs based solely on their abundance and maturity has limitations. Incorporating the inflammatory status of patients may enable a more comprehensive assessment. The systemic immune inflammatory index (SII) is based on a prognostic score of inflammation and immunity, which is calculated as platelet count*neutrophil count/lymphocyte count. Inflammation induces leukocytosis, and the systemic immune‐inflammatory index (SII), neutrophil‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), and platelet‐to‐lymphocyte ratio (PLR) can serve as inflammatory biomarkers and have been validated as diagnostic predictors in patients with lung and liver cancers receiving immunotherapy. 24 , 25 Therefore, we investigated the effects of inflammatory biomarkers (SII, PLR, NLR, and LMR) on TLS abundance and maturity of TLSs. We also compared the predictive values of these inflammatory parameters, TLSs, and the combination of inflammatory parameters with TLSs for immunotherapy efficacy in patients with NSCLC receiving neoadjuvant immunochemotherapy.

METHODS Patients and samples We retrospectively enrolled 106 patients with NSCLC pathologically diagnosed at Shandong Cancer Hospital between January 2020 and August 2022. Inclusion criteria were patients with predominantly resectable stage IB (≥4 cm) to IIIB with no prior antitumor therapy. All patients underwent radical surgery and received at least two cycles of PD‐1 inhibitors combined with taxanes and platinum‐based drugs preoperatively. Patients with active or prior medical history of immune‐related diseases were excluded. The inclusion and exclusion of patients with NSCLC and the tumor information analyses are shown in Figure 1 . Data collection For the enrolled patients with NSCLC, postoperative paraffin blocks, tumor information, postoperative pathology data, and routine blood tests within 1 week before neoadjuvant immunochemotherapy were collected. Key data included sex, age, pathology type, TNM stage, neutrophil count, monocyte count, lymphocyte count, platelet count, TLS abundance, and tissue section maturity. NSCLC staging was based on the AJCC eighth edition Cancer Staging System. Histopathological analysis Two sections were prepared for each paraffin‐embedded tissue block. The sections were subjected to hematoxylin–eosin (HE) staining, and the abundance of TLSs in tumor tissues was scored as 0, 1, or 2: (A) 0 indicates no TLS, (B) 1 indicates <3 TLSs in the tumor, and (C) 2 indicates ≥3 TLSs in the tumor. Patients with a score of 2 were as assigned to the high‐abundance group; otherwise, patients were assigned to the low‐abundance group. According to previous studies, TLSs displaying active germinal centers (GCs) were defined as fully matured TLSs. 26 We assessed the TLSs within the tumor and within the 5‐mm peritumoral area. The TLS scoring was validated by immunohistochemical staining. The TLS assessment was performed independently by two experienced pathologists in a blinded manner. In cases of disagreement between the two pathologists, the higher score was used. Statistical analysis MPR was defined as the presence of ≤10% residual tumor cells in the surgical resection specimen, while the non‐MPR group included patients who did not achieve MPR. Statistical analyses were performed using the R Studio software (R Foundation for Statistical Computing) and SPSS (version 25.0; IBM Corporation). Receiver operating characteristic (ROC) curves were used to determine the optimal cutoff values for blood parameters (SII, PLR, LMR, and NLR). Univariate and multivariate binary logistic regression analyses were used to determine the correlations between inflammatory parameters and TLS abundance and maturity, as well as independent factors influencing MPR. p < 0.05 was considered statistically significant. Based on the identified independent predictors, patients were divided into training and validation cohorts in a 2:1 ratio. In addition, using R statistical software, nomogram models were constructed based on inflammatory biomarkers, TLS abundance and maturity, and their combinations to predict MPR rates. Furthermore, ROC curve analysis and the C‐index were used to compare the performances of the three models.

RESULTS Patient characteristics This study included 106 patients with NSCLC undergoing neoadjuvant immunochemotherapy followed by radical surgery, of whom 94 (88.7%) were male. The median age at diagnosis was 63 years (range 44–102 years). A total of 78 (73.6%) patients had squamous cell carcinoma and 28 (26.4%) had adenocarcinoma. MPR was achieved in 64 patients (60.4%) ( Table 1 ) . Among the enrolled patients, 13 (12.2%), 23 (21.7%), and 61 (57.5%) had TLS abundance scores of 0, 1, and 2, respectively. Mature TLSs were observed in 65 (61.3%) patients. The different maturity states of the TLSs are shown in Figure 2 . Correlation of systemic inflammatory parameters with TLS abundance and maturation The optimal cutoff values for pretreatment SII, NLR, PLR, LMR, and lymphocyte count were determined using ROC curves and the maximum Youden index (Figure 3 ). Optimal cutoff values were used to categorize the inflammatory indices. TLS abundance and maturity were stratified to form two groups to investigate the relationship between inflammatory indices and TLSs in different patients with NSCLC. Univariate analysis revealed that SII (odds ratio [OR] = 0.258, p = 0.001), NLR (OR = 0.309, p = 0.005), and lymphocyte count (OR = 2.722, p = 0.024) correlated with TLS abundance. TNM stage (OR = 0.352, p = 0.032), SII (OR = 0.184, p < 0.05), and NLR (OR = 0.323, p = 0.007) were correlated with TLS maturity. Further multivariate logistic regression analysis found that SII was an independent predictor of both TLS abundance (OR = 0.273, 95% CI: 0.094–0.796, p = 0.017) and TLS maturity (OR = 0.227, 95% CI: 0.077–0.668, p = 0.007), and SII ≤857.7 was a protective factor against high TLS abundance and maturity (Supporting Information ) . In summary, we found that SII was an independent influencing factor for TLS expression and that SII was negatively correlated with TLS expression status in the tumor microenvironment. Correlation between inflammatory parameters, TLSs , and pathological response to neoadjuvant immune combination chemotherapy in patients with NSCLC Comparison of CT and H&E images between responder and nonresponders before and after neoadjuvant therapy is shown in Figure 4a . Based on the pathological response after treatment, patients with NSCLC were divided into MPR and non‐MPR groups. Among the MPR patients, the numbers of cases with TLS abundance scores of 0, 1, and 2 were 2, 11, and 51, respectively, and among the non‐MPR patients, the numbers were 11, 21, and 10, respectively. The number of MPR patients with and without mature TLSs was 56 and eight, respectively; for non‐MPR patients, the numbers were nine and 33, respectively ( Figure 4b,c ) . A comparison of the inflammatory parameters between the MPR and non‐MPR groups is shown in Figure 4d–g . Univariate analysis revealed that the SII (OR = 0.090, p < 0.05), NLR (OR = 0.246, p = 0.001), PLR (OR = 0.208, p < 0.05), TLS abundance ( p < 0.05), and TLS maturity (OR = 25.667, p < 0.05) correlated with patient MPR. Further multivariate logistic regression analysis of the above five factors identified PLR ≤201.8 (OR = 0.187, 95% CI: 0.036–0.965, p = 0.045), TLS abundance ( p = 0.019), and TLS maturity = 1 (OR = 23.9737, 95% CI: 5.063–113.521, p < 0.05) as independent predictors of MPR ( Table 2 ) . Comparison of nomogram diagnostic models Nomogram models were constructed based on the PLR, TLS abundance, maturity, and their combination to predict patient MPR rates ( Figure 5a–c ). Comparison of area under the curve (AUC) values and the C‐index from ROC curves of the three models showed that for MPR prediction, the combined model (training set AUC = 0.939, validation set AUC = 0.900, C‐index = 0.939) was markedly superior to the PLR‐based model (training set AUC = 0.708, validation set AUC = 0.740, C‐index = 0.708) and TLS‐based model (training set AUC = 0.872, validation set AUC = 0.883, C‐index = 0.872) ( Table 3 ) . The calibration curve was close to the ideal curve, and the decision curve analysis showed high clinical benefit and good model performance (Figure 5d ).

DISCUSSION In this study, we investigated the relationship between pretreatment inflammatory biomarkers and postoperative tumor TLS status in 106 patients with NSCLC undergoing neoadjuvant immunochemotherapy. The results showed that the SII was negatively correlated with TLS abundance and maturity, and multivariate analysis confirmed that the SII was an independent risk factor influencing TLS abundance and maturity. Additionally, the PLR, TLS abundance, and maturity were independent predictors of the MPR. Notably, compared with using TLS features or PLR alone, combining both improved the AUC for predicting neoadjuvant treatment sensitivity to 0.939. These data indicate that the status of TLSs within the tumor microenvironment of patients with NSCLC may be modulated by systemic inflammatory processes. Furthermore, our results suggested that the integration of TLS metrics with inflammatory biomarkers may provide a more accurate diagnostic tool for predicting the efficacy of neoadjuvant immunotherapy combined with chemotherapy. Systemic inflammation is an important manifestation of cancer progression. Muhammed et al. found that the NLR and PLR were associated with immunotherapy efficacy and were independent negative diagnostic factors in patients with HCC receiving ICI treatment. 24 In immunotherapy for advanced NSCLC, increased NLR and PLR and poorer nutritional status are predictive of poorer overall survival. 25 As immune cell aggregates, TLSs have been validated as immune predictors of the response to cancer immunotherapy, likely due to the induction of carcinoma‐associated fibroblasts, antigen presentation by dendritic cells, and anti‐tumor activities of CD8+ T and B cells within TLSs. 14 , 17 , 27 , 28 Zhou et al. found that TLS‐associated gene signatures could help stratify responders to immunotherapy in bladder cancer, providing strong evidence for the potential of TLSs to predict immunotherapy efficacy. 29 As immune‐active regions in the tumor microenvironment, the status of TLSs is influenced by both local tumor factors and systemic immune conditions. TLS formation is induced by inflammatory microenvironmental factors and their abundance and structure undergo specific modulations based on inflammatory cues. 21 Therefore, the combined assessment of TLSs and inflammatory cell counts representative of the inflammatory status enables a more comprehensive evaluation of an individual's immune response state. Additionally, reflecting TLS status changes through inflammatory biomarkers in the blood provides a preliminary basis for elucidating specific inflammatory microenvironments that promote TLS expression in NSCLC, while also offering new insights into immunomicroenvironment research. This study is the first to investigate the factors that affect the formation of TLS in the tumor microenvironment from a unique perspective. The research discovered a negative correlation between TLS and the systemic inflammation indicator SII. This finding not only opened up new avenues for TLS research but also established SII as a reference indicator that reflects TLS status. This formed the foundation for investigating the relationship between TLS and the response to immunotherapy. More importantly, the predictive model that integrated TLS and PLR significantly improved the accuracy of assessing chemotherapy sensitivity in patients with NSCLC. This new approach will directly inform individualized treatment regimens and greatly advance the development of precision immuno‐oncology. In conclusion, this study pioneered a new perspective to elucidate the mechanisms of TLS formation and translated this discovery into improved clinical prediction of treatment sensitivity. As a retrospective analysis, this study had inherent selection bias and limited robustness owing to its single‐center design. The limited amount of information on immunocombination chemotherapy in this study could have impacted the outcome of the analysis. Furthermore, there was a variation in tumor size and lymph node metastasis among the patients. The response of ≤10% residual tumor cells may have varied depending on the preimmunization tumor burden. Additionally, only a few inflammatory indices were examined, without comprehensive consideration of other potential influencing factors. Moreover, this study only included patients with resectable NSCLC receiving neoadjuvant immunochemotherapy, and chemotherapy effects cannot be excluded, precluding an accurate assessment of the relationship between PD‐1 inhibitors and TLSs. Future studies should validate the association between more extensive inflammatory biomarkers and TLSs through large‐scale prospective analyses, dynamically investigate the inflammatory factor‐TLS interplay, and experimentally explore the underlying molecular mechanisms. Finally, efforts to improve immunotherapy sensitivity by modulating the inflammatory status and extending research to other cancer types are warranted. In conclusion, this retrospective study of 106 patients with NSCLC who received neoadjuvant immunochemotherapy, identified the SII, a systemic inflammation index, as an independent factor influencing TLS abundance and maturity, with a higher SII negatively associated with TLS expression in the tumor microenvironment. Moreover, compared with using TLSs or PLR individually, combining them more accurately predicted major pathological response rates to neoadjuvant immunochemotherapy.

Abstract Background Neoadjuvant immunochemotherapy can effectively downstage tumors and reduce the risk of postoperative recurrence and distant metastasis in patients with non‐small cell lung cancer (NSCLC). In this study, we investigated the correlation between inflammatory biomarkers and tertiary lymphoid structure (TLS) expression. We also compared the predictive values of these inflammatory parameters, TLSs, and a combination of inflammatory parameters and TLSs for neoadjuvant efficacy in patients with NSCLC. Methods We retrospectively analyzed the clinical information of 106 patients with NSCLC who underwent neoadjuvant immunochemotherapy and radical surgery at Shandong Cancer Hospital between June 2020 and June 2022. Results TLS was evaluated using hematoxylin–eosin staining and immunohistochemically‐stained tissue sections. Logistic analysis was performed to determine the correlation between inflammatory parameters, TLSs, and the factors affecting major pathological response (MPR). Receiver operating characteristic curves and the C‐index were used to evaluate the predictive value of the nomogram models for MPR. The systemic immune‐inflammatory index (SII) was an independent predictor of high TLS abundance and maturity. Platelet‐to‐lymphocyte ratio (PLR) ≤201.8, TLS abundance, and TLS maturity were independent predictors of MPR. The PLR‐TLS combined model performed better in assessing the MPR in patients with NSCLC than models using single indicators. Conclusion Our study demonstrated that the SII is an independent predictor of both TLS abundance and maturity. Both TLSs and PLR can predict MPR rates in patients with NSCLC receiving neoadjuvant immunochemotherapy. However, assessing the MPR in patients with NSCLC using a combination of PLR and TLSs is more accurate than using either indicator alone. This retrospective study of 106 patients with NSCLC receiving neoadjuvant immunochemotherapy identified the SII, a systemic inflammation index, as an independent factor influencing TLS abundance and maturity, with a higher SII negatively associated with TLS expression in the tumor microenvironment. Moreover, compared with using TLSs or PLR individually, combining them more accurately predicted major pathological response rates to neoadjuvant immunochemotherapy. Xu F , Zhu H , Xiong D , Wang K , Dong Y , Li L , et al. Tertiary lymphoid structures combined with biomarkers of inflammation are associated with the efficacy of neoadjuvant immunochemotherapy in resectable non‐small cell lung cancer: A retrospective study . Thorac Cancer . 2024 ; 15 ( 2 ): 172 – 181 . 10.1111/1759-7714.15175

AUTHOR CONTRIBUTIONS Study design: Shuanghu Yuan, Fuhao Xu; Data acquisition and analysis: He Zhu, Dali Xiong, Fuhao Xu; Interpretation of the data: Fuhao Xu, Kang Wang, Yinjun Dong, Li Li; Drafting of the manuscript: Fuhao Xu; Revision of the manuscript: Shuanghu Yuan. All authors contributed to the article and approved the submitted version. FUNDING INFORMATION This study was supported in part by National Natural Science Foundation of China (grant no. NSFC82073345), Natural Science Foundation of Shandong Province (ZR202209010002). CONFLICT OF INTEREST STATEMENT The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Supporting information

ACKNOWLEDGMENTS We thank all the participants who contributed to the article. We would like to thank Editage ( www.editage.cn ) for English language editing. DATA AVAILABILITY STATEMENT The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

CC BY

no

2024-01-16 23:42:02

Thorac Cancer. 2023 Dec 6; 15(2):172-181

oa_package/d0/4d/PMC10788471.tar.gz

PMC10788472

38018652

INTRODUCTION Despite significant improvements in the realm of anticancer strategies, whatever chemotherapy is administered as a monotherapy or in combination with other treatment paradigms encompassing surgery, radiotherapy, immune checkpoint inhibitors (ICIs), antiangiogenesis agents, targeted therapies, and beyond, it remains an important treatment strategy for almost all cancers, especially lung cancer, the most prevalent and fatal malignant tumor in the population. 1 , 2 Platinum‐based doublet chemotherapy occupies an important role in the management of lung cancer; however, there are treatment‐associated side effects which include nausea and vomiting, fatigue, appetite loss, pain, constipation, diarrhea, and many other debilitating symptoms that may deteriorate the quality of life for patients undergoing chemotherapy, and even necessitate dose reduction or discontinuation. 3 , 4 Chemotherapy can also damage the gastrointestinal epithelial cells and result in a disorder of the gut microbiome. 5 , 6 Gut microbiota has been proven to protect the intestinal mucosa, prevent intestinal inflammation, and build the immune ecology of the whole body. 7 , 8 Previous studies showed that certain cytotoxic drugs such as cyclophosphamide, fluorouracil, and etoposide appeared to have antibacterial properties in plasma, and medications such as irinotecan, fluorouracil would affect the diversity of the gut microbiome, 9 , 10 which may result in gastrointestinal mucositis, exacerbating the mucositis caused by chemotherapeutic drugs, thereby leading to severe gastrointestinal complications in patients receiving chemotherapy. 11 , 12 , 13 , 14 Many strategies for controlling chemotherapy‐related adverse events have been applied in clinical practice during the past decades, but the management situation is not optimistic in the real world. 3 , 15 , 16 Emerging evidence favors the strategy of gut microbiota regulation for ameliorating chemotherapy‐related adverse events. 17 In particular, the feasibility of probiotic supplementation to ameliorate chemotherapy‐related adverse effects has been demonstrated in preclinical and clinical studies. 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 Nevertheless, whether administering compound probiotics can relieve chemotherapy‐related adverse events for lung patients undergoing platinum‐based doublet chemotherapy is rarely reported. This study attempted to determine whether oral compound probiotic supplements can reduce chemotherapy‐related adverse effects and improve lung cancer patients quality of life during chemotherapy.

METHODS This prospective, randomized, placebo‐controlled, multicenter clinical study was conducted at three major cancer centers in Sichuan province, China: Thoracic Oncology Ward, West China Hospital, Sichuan University; Cancer Center, No.7 People's Hospital of Chengdu; Cancer Center, People's Hospital of Sichuan Province. The study was approved by the Ethics Committee of the West China Hospital of Sichuan University and conformed to the Declaration of Helsinki. The study was registered in the Chinese Clinical Trial Registry (registration no.: ChiCTR1800019269). All eligible patients provided written informed consent. Patients This study intended to screen and enroll chemotherapy‐naive patients with lung cancer who were scheduled to receive platinum‐based doublet chemotherapy. The quality of life score of lung cancer patients during chemotherapy was around 60 (Figure 1 ). It was expected that it could be improved to 70 by using a compound probiotic preparation, taking the test level α as 0.05, assuming that the number of cases in both groups was equal, the minimum sample size to be included in each group was n1 = n2 = 49, N = 98, considering 10% of patients were excluded, the final number of cases would be 110. Patients who met all of the following criteria were included: (1) pathologically confirmed with lung cancer (including non‐small cell lung cancer and small cell lung cancer); (2) chemotherapy‐naive; (3) aged between 18 and 75 years old; (4) Eastern Cooperative Oncology Group performance status (ECOG PS) 0–2; (5) receiving chemotherapy for the first time with a regimen of cisplatin/carboplatin (AUC ≥5) in combination with one of these following agents: paclitaxel, docetaxel, gemcitabine, vinorebine, pemetrexed, etoposide, and who were supposed to receive two or more cycles of chemotherapy. The main exclusion criteria were as follows: (1) Patients who received recent (within 2 weeks before chemotherapy) antibiotic therapy or proton pump inhibitor therapy, (2) patients who had recently (within 2 weeks before chemotherapy) taken some probiotic preparations, (3) patients with chronic gastrointestinal diseases or gastrointestinal metastatic tumor, (4) patients with severe systemic metabolic diseases or immune system diseases. Based on the computer‐generated program, enrolled patients were randomly assigned (1:1) to either the compound probiotic supplements group (group BP‐1) or the placebo group (group C). A total of 110 random identification numbers were created by the computer before patients enrolled. Each enrolled patient was given an identification number based on the enrolment order and assigned to the corresponding group based on the identification number. The process mentioned above was performed by the Cancer Psychology and Health Management Committee of the Sichuan Cancer Society and was double‐blind for both subjects and researchers. Treatment The enrolled patients were administered the platinum‐based doublet chemotherapy regimen recommended by NCCN/CSCO guidelines. 26 The oral compound probiotic supplements (Hua Wei Yi probiotic solid drink, Yiga Bio‐technology Chengdu Co., LTD, Chengdu, China) contained oligofructose (added at >93.69%), Bifidobacterium lactis Bi‐07, Lactobacillus acidophilus NCFM, Lactobacillus rhamnosus HN001, Bifidobacterium lactis HN019 . It was packaged in an aluminum‐plastic film bag and a maltodextrin‐based placebo with the same appearance and taste. All compound probiotics/placebos in this study were received from Yiga Bio‐technology Chengdu Co., Ltd (via the Cancer Psychology and Health Management Committee of the Sichuan Cancer Society. The corresponding compound probiotic supplement/placebo with an identification number was assigned when a patient was enrolled. The Cancer Psychology and Health Management Committee of the Sichuan Cancer Society kept the assignment information list and was responsible for compound probiotic supplement/placebo distribution. The enrolled patients were given compound probiotic supplements/placebos at the beginning of the first cycle of chemotherapy, one sachet (2 g) dissolved in cold water or indoor temperature twice a day until the start of the third chemotherapy cycle. Follow‐up and data collection All enrolled patients were evaluated for two chemotherapy cycles. The EORTC QLQ C30 questionnaire was completed independently by the enrolled patients prior to the first, second, and third cycles of chemotherapy. The scale consisted of 30 items, including five functional dimensions (physical function, role function, cognitive function, emotional function, and social function), nine symptom dimensions (fatigue, pain, nausea and vomiting, dyspnea, insomnia, appetite loss, constipation, diarrhea, financial difficulties), and one dimension of overall quality of life. 27 For the functional and overall quality of life dimensions, higher scores indicated better functional status and quality of life. In contrast, for the symptom dimensions, higher scores indicated more severe symptoms or problems. The National Cancer Institute Common Toxicity Criteria (version 4.0) was used for the evaluation of adverse events. Statistical analysis The primary endpoint was the difference in the EROTC QLQ C30 questionnaire score between the two groups after two cycles of chemotherapy. For qualitative data, we used the chi‐square test to determine whether there was a difference between groups BP‐1 and C. The Mann–Whitney U or independent‐sample t ‐test were used to compare the differences for quantitative data. The above statistical analysis was performed with SPSS version 27 software. Two‐sided p ‐values < 0.05 were determined to be statistically significant.

RESULTS Patient characteristics From March 2021 to January 2022, 110 patients were enrolled, of whom one patient withdrew their informed consent and 18 patients were excluded due to protocol violation. A total of 91 patients were included in the final statistics. No significant differences were observed between the two groups at baseline (Table 1 ). EORTC QLQ C30 questionnaire analysis No significant difference was observed in the scores of the EORTC QLQ C30 questionnaire at baseline between the two groups (Table 2 ). After one cycle of chemotherapy and compound probiotic supplement/placebo treatment, the scores of the two groups (group BP‐1 vs. group C) showed a statistically significant difference in the following dimensions: overall quality of life (75.45 ± 15.46 vs. 61.55 ± 19.12, p = 0.001), pain (6.76 ± 13.87 vs. 17.75 ± 25.68, p = 0.021), nausea and vomiting (4.05 ± 9.13 vs. 22.46 ± 24.14, p < 0.001), appetite loss (9.91 ± 15.45 vs. 22.46 ± 24.40, p = 0.010), and constipation (6.31 ± 13.24 vs. 23.91 ± 24.00, p < 0.001). The incidence of nausea and vomiting, appetite loss, constipation, and diarrhea in group BP‐1 was 16.67%, 26.19%, 16.67%, and 4.76%, respectively, significantly lower than that of the group C: 63.27%, 53.06%, 57.14%, and 18.37%, respectively ( p < 0.05) (Table 2 , Figure 2a ). After 2 cycles of the study treatment, there was a significant difference in the dimensions, including overall quality of life (76.90 ± 18.31 vs. 58.89 ± 17.17, p < 0.001), role function (93.33 ± 11.58 vs. 85.93 ± 15.06, p = 0.023), nausea and vomiting (0.00 ± 0.00 vs. 27.04 ± 29.15, p < 0.001), appetite loss (6.67 ± 13.53 vs. 22.22 ± 18.80, p < 0.001), constipation (0.95 ± 5.63 vs. 28.15 ± 22.42, p < 0.001) and diarrhea (2.86 ± 9.47 vs. 15.56 ± 16.82, p < 0.001) between the group BP‐1 and group C. The incidence of nausea and vomiting, appetite loss, constipation, and diarrhea in group BP‐1 was significantly lower than in group C (0% vs. 71.43%, 16.67% vs. 57.14%, 2.38% vs. 63.27%, and 7.14% vs. 42.86%, respectively, p < 0.001) (Table 2 , Figure 2b ). Adverse events No grade>3 adverse events were observed. There were no differences in adverse reactions between the two groups, except for the incidence of gastrointestinal reactions. In particular, the incidence of nausea and vomiting, constipation, anorexia, and diarrhea were lower in group BP‐1 than in group C (Table 3 ).

DISCUSSION Our study demonstrated that compound probiotic supplements can improve the quality of life and relieve platinum‐based doublet chemotherapy‐induced gastrointestinal adverse reactions for lung cancer patients undergoing chemotherapy. Previous clinical studies have also indicated that probiotics may ameliorate chemotherapy‐induced adverse effects. Jiang et al. found that a probiotic combination ( Bifidobacterium longum , Lactobacillus lactis , and Enterococcus faecium ) can ameliorate the severity of oral mucositis via gut microbiota modulation for nasopharyngeal carcinoma patients who were undergoing concurrent radiochemotherapy. 28 Probiotic combinations containing Bifidobacterium infants , Lactobacillus acidophilus , Enterococcus faecalis , and Bacillus cereus have also been shown to be effective in attenuating chemotherapy‐related gastrointestinal complications, especially diarrhea for colorectal cancer patients who were undergoing postoperative chemotherapy. 22 As for lung cancer patients receiving platinum‐based doublet chemotherapy, Clostridium butyricum can relieve chemotherapy‐related diarrhea. 25 However, clinical studies exploring the usage of probiotics to mitigate chemotherapy‐related adverse effects have predominantly concentrated on colorectal cancer and head and neck carcinoma, with fewer studies targeting lung cancer patients. In addition, there has been limited exploration regarding whether combination probiotic preparations containing Lactobacillus and Bifidobacterium can improve chemotherapy‐related adverse effects for lung cancer patients. Our study provides preliminary evidence favoring the potential benefits of compound probiotic supplements to ameliorate chemotherapy‐related adverse effects and the possibility of compound probiotic clinical application in managing chemotherapy‐related complications among lung cancer patients. It is our inaugural endeavor to improve the quality of life for lung cancer patients who are undergoing chemotherapy through compound probiotic supplements. In this report, after two cycles of compound probiotic supplement/placebo treatment along with platinum‐based doublet chemotherapy, a significant difference in some questionnaire dimensions was shown between the two groups. Most of all, the overall quality of life score in group BP‐1 was significantly better than that in group C, and so was the score of role function. In other words, patients in group BP‐1 maintained a relatively good quality of life during the chemotherapy course, which was aggravated in group C. Moreover, the prevalence of nausea and vomiting, appetite loss, constipation, and diarrhea in group BP‐1 was significantly lower than in group C. The above results imply that the adverse effects caused by chemotherapy may worsen the quality of life. A randomized controlled trial reported a similar situation: the quality of life analysis of KEYNOTE‐024 showed significantly higher scores in the QLQ‐30 questionnaire for nausea and vomiting, constipation, and diarrhea in the chemotherapy group. 29 The symptom control and quality of life investigation conducted in the LUX‐Lung 3 trial performed the QLQ‐30 questionnaire, revealing that 63% of patients in the chemotherapy group experienced nausea and vomiting, and 24% of patients experienced diarrhea following pemetrexed plus cisplatin treatment. 30 Our study observed that the prevalence of nausea and vomiting in group C was 63.27% and 71.43% before the second and third cycle of chemotherapy, respectively; the incidence of diarrhea was 18.37% and 42.86%, respectively, which were close to the findings from the LUX‐Lung 3 trial. Meanwhile, the incidence and the QLQ‐30 questionnaire scores of diarrhea and vomiting in the BP‐1 group were lower than those reported in the LUX‐Lung 3 trial. These findings indicate that the compound probiotics supplements can relieve gastrointestinal side effects; for example, diarrhea and vomiting, thereby maintaining the patient's quality of life during chemotherapy. How do the probiotics work on improving the quality of life in patients receiving chemotherapy? Chemotherapeutic agents can disturb the composition and diversity of the gut microbiota, correlated with adverse effects such as diarrhea, appetite loss, etc. 5 , 6 , 31 Considering the close connection between the composition of gut microbiota and short‐chain fatty acids (SCFAs) production, 32 it is plausible to hypothesize that chemotherapy‐related gastrointestinal reactions may be attributed to a decline in SCFA levels resulting from an imbalance in gut microbiota post‐chemotherapy. SCFAs have been demonstrated to attenuate chemotherapy‐related toxicities due to their anti‐inflammatory, antioxidant, and protective characteristics. 32 SCFAs can also be against chemotherapy‐induced intestinal injury via immunoregulation, promoting crypt cell proliferation and maintaining epithelial integrity. 32 , 33 In addition, postoperative chemotherapy may lead to a decline in gut phylum Firmicutes levels for colorectal cancer patients, 22 which are known to be an important source of SCFAs. 34 Bifidobacterium and Lactobacillus are SCFA‐producing microbiota; supplementation with compound probiotics can potentially reduce chemotherapy‐related gastrointestinal adverse events for lung cancer patients by restoring SCFA levels and thus improving quality of life. Our aim is to validate this in future studies. It is a pity that the sample size of this study was limited after 19 patients were excluded from the final statistical analysis. Further exploration of the variation of gut microbiota and SCFA levels are needed to elucidate the potential mechanisms of compound probiotic supplements to ameliorate chemotherapy‐related adverse effects. In addition, many patients with early‐stage lung cancer were included in our study, and our future studies will be focused on patients with advanced lung cancer. Our study observed that compound probiotic supplements could effectively alleviate gastrointestinal adverse events. We still need to explore whether compound probiotic supplements can improve other chemotherapy‐related adverse reactions and improve the quality of life of cancer patients in future studies. Probiotic agents have been reported to provide a survival benefit for lung cancer patients treated with ICIs. 35 Our study focused mainly on the management of chemotherapy‐related adverse effects and neglected the observation of treatment efficacy, which will be further explored in a subsequent study. However, this study is the first step in evaluating compound probiotic supplement intervention in improving the quality of life and relieving the symptoms of patients suffering from the adverse effects of chemotherapy. We have found a positive trend from the current study. We also plan further clinical trials to provide more robust evidence to confirm the advantages of compound probiotic supplements to lung cancer patients undergoing chemotherapy. In conclusion, oral compound probiotic supplements can improve the quality of life and relieve chemotherapy‐related gastrointestinal adverse events for lung cancer patients receiving platinum‐based chemotherapy.

Abstract Background Chemotherapy is an important approach for lung cancer patients. The study was designed to evaluate the feasibility of the compound probiotic supplements in improving the quality of life for lung cancer patients undergoing chemotherapy. Methods This randomized, double‐blind, placebo‐controlled trial enrolled chemotherapy‐naive patients with lung cancer who were scheduled to receive platinum‐based doublet chemotherapy. All eligible patients were randomly administered (1:1) compound probiotic supplements (group BP‐1) or placebo (group C) for two chemotherapy cycles. The EORTC QLQ C30 questionnaire scores were evaluated before the first, second, and third cycles of chemotherapy. The primary endpoint was the difference in the EROTC QLQ C30 questionnaire score between the two groups after two cycles of chemotherapy. Results A total of 110 patients were recruited from March 2021 to January 2022. After undergoing two cycles of chemotherapy, group BP‐1 were significantly better in various dimensions of the overall quality of life, role function, nausea and vomiting, appetite loss, constipation, and diarrhea relative to group C (76.90 ± 18.31 vs. 58.89 ± 17.17; 93.33 ± 11.58 vs. 85.93 ± 15.06; 0.00 ± 0.00 vs. 27.04 ± 29.15; 6.67 ± 13.53 vs. 22.22 ± 18.80; 0.95 ± 5.63 vs. 28.15 ± 22.42; 2.86 ± 9.47 vs. 15.56 ± 16.82; p < 0.05, respectively). The incidence of nausea and vomiting, appetite loss, constipation, and diarrhea in group BP‐1 was significantly lower than in group C (0% vs. 71.43%, 16.67% vs. 57.14%, 2.38% vs. 63.27%, and 7.14% vs. 42.86%, respectively, p < 0.001). Conclusions Compound probiotic supplements can improve the quality of life and relieve chemotherapy‐related gastrointestinal side effects for lung cancer patients receiving platinum‐based doublet chemotherapy. (Chinese Clinical Trial Registry: ChiCTR1800019269). Our study demonstrated that oral compound probiotics supplements can improve the quality of life and relieve chemotherapy‐related gastrointestinal adverse events for lung cancer patients receiving platinum‐based chemotherapy. Wei H , Yue Z , Han J , Chen P , Xie K , Sun Y , et al. Oral compound probiotic supplements can improve the quality of life for patients with lung cancer during chemotherapy: A randomized placebo‐controlled study . Thorac Cancer . 2024 ; 15 ( 2 ): 182 – 191 . 10.1111/1759-7714.15177

AUTHOR CONTRIBUTIONS All authors had full access to the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Conceptualization , Yu Sun and Jiang Zhu; Data curation , Jialong Han, Ping Chen, and Ke Xie; Formal analysis , Hao Wei, Zhiying Yue, and Jialong Han; Funding acquisition , Yu Sun and Jiang Zhu; Investigation , Jialong Han, Ping Chen, and Ke Xie; Methodology , Yu Sun and Jiang Zhu; Project administration , Yu Sun and Jiang Zhu; Resources , Jialong Han, Ping Chen, and Ke Xie; Software , Hao Wei and Zhiying Yue; Supervision , Yu Sun and Jiang Zhu; Validation , Yu Sun and Jiang Zhu; Visualization , Hao Wei; Writing – original draft preparation , Hao Wei, Zhiying Yue, and Jialong Han; Writing – Review and editing , Jiang Zhu. CONFLICT OF INTEREST STATEMENT The Authors declare that there is no conflict of interest.

ACKNOWLEDGMENTS We would like to thank all those who participated in this study. The Cancer Psychology and Health Management Committee of the Sichuan Cancer Society supported this trial.

CC BY

no

2024-01-16 23:42:02

Thorac Cancer. 2023 Nov 29; 15(2):182-191

oa_package/96/a0/PMC10788472.tar.gz

PMC10788474

38013668

INTRODUCTION Advanced non‐small cell lung cancer (NSCLC) is an aggressive and difficult to eradicate disease. Recently, outcomes have improved significantly owing to the use of immune checkpoint inhibitors (ICIs), such as antiprogrammed death‐1 (PD‐1) and antiprogrammed death ligand‐1 (PD‐L1) antibodies. 1 Chemoimmunotherapy consisting of a platinum‐based regimen plus anti‐PD‐1/PD‐L1 antibodies is more effective than is chemotherapy alone, even if the tumor cells do not express PD‐L1. 2 , 3 , 4 After first‐line chemoimmunotherapy, cytotoxic agents (e.g., docetaxel) are usually administered to patients with advanced NSCLC without driver mutations according to their condition. For second or more lines, ramucirumab plus docetaxel (RD) is a leading treatment option and is superior to docetaxel alone, as confirmed in a previous phase III study. 5 Using real‐world data, we have shown that RD is a suitable second‐line treatment for patients with advanced NSCLC after combined chemotherapy/PD‐1 blockade therapy. 6 Currently, there are no established parameters for predicting the clinical benefit of RD after first‐line chemoimmunotherapy. Ramucirumab is an antivascular endothelial growth factor (VEGF) receptor 2 (VEGFR2) fully human monoclonal IgG1 antibody that inhibits tumor growth by blocking the interaction of VEGFR2 with its natural ligand. 7 No study reporting the efficacy of RD in previously treated NSCLC has described VEGFR2 expression as a potential prognostic marker. The current standard front‐line treatment for NSCLC patients without driver mutations includes PD‐1 blockade, with most patients receiving RD after PD‐1 blockade. Several recent studies have shown that RD is more effective when administered immediately after regimens with versus without PD‐1 blockade. 8 , 9 , 10 , 11 Moreover, an exploratory analysis in a phase III study of RD in patients with stage IV NSCLC suggests that RD may be effective after disease progression on platinum‐based regimens including taxane, pemetrexed, gemcitabine, or bevacizumab. 12 In contrast, second‐line RD treatment was not beneficial in patients with advanced NSCLC and a KRAS mutation; whether prior chemotherapy which included an ICI affected RD efficacy was not addressed in that study. 13 Several researchers have reported real‐world data on RD in patients with previously treated NSCLC in large‐scale retrospective studies 14 , 15 ; in these studies the front‐line platinum‐based chemotherapy included immunotherapy. Overall, whether prior chemoimmunotherapy affects the efficacy of RD and the mechanism remains unclear. Prior immunotherapy may enhance responsiveness to RD via a mechanism involving synergism between the VEGFR2 signaling pathway and the tumor immune environment. Our REACTIVE study examined the relationship between front‐line chemoimmunotherapy and RD efficacy, 6 and we expect that our approach will explain why RD is an appropriate choice after chemoimmunotherapy. Additionally, further investigations are needed to identify markers that accurately predict RD efficacy after chemoimmunotherapy. To address these issues, we conducted a retrospective study to predict the clinical benefit of RD treatment after front‐line chemoimmunotherapy in patients with advanced NSCLC, using patient population from our REACTIVE study. 6

METHODS Patients and study design The REACTIVE study design has been reported previously. 6 The REACTIVE study was a multicenter retrospective investigation involving 62 Japanese institutions. It included 288 patients (222 men and 66 women; median age, 67 years; age range, 20–82 years) with advanced NSCLC who received platinum‐based chemotherapy plus anti‐PD‐1/PD‐L1 antibodies as first‐line therapy and RD as second‐line treatment between January 2017 and August 2020. Clinical data were extracted from medical records, and the sample in the present study was the same as that of the REACTIVE study. 6 This study was approved by the Institutional Ethics Committee of the International Medical Center at Saitama Medical University. The requirement for written informed consent was waived by the committee because of the retrospective nature of the study. Treatment and assessment All patients received platinum‐based chemotherapy with anti‐PD‐1/PD‐L1 antibodies. The IMpower 150 (1200 mg atezolizumab, 15 mg/kg bevacizumab, area under the concentration‐time curve of 5 mg/mL per min carboplatin, and 1750 mg/m 2 paclitaxel), KEYNOTE 189 (area under the concentration‐time curve of 5 mg/mL per min carboplatin, 500 mg/m 2 pemetrexed, and 200 mg pembrolizumab), and KEYNOTE 407 (area under the concentration‐time curve of 5 mg/mL per min carboplatin, 100 mg/m 2 nab‐paclitaxel, and 200 mg pembrolizumab) regimens were intravenously administered. 2 , 3 , 4 The results of physical examinations, complete blood counts, and biochemical tests were assessed by the chief physician. Toxicity was graded based on the Common Terminology Criteria for Adverse Events version 4.0. Tumor response was evaluated according to the Response Evaluation Criteria in Solid Tumors version 1.1. 16 Statistical analysis The statistical significance level was set at p < 0.05. Fisher's exact test was used to examine the association between two categorical variables. Progression‐free survival (PFS) was defined as the time from RD initiation to disease progression or death. Overall survival (OS) was defined as the time from RD initiation to death from any cause. The Kaplan–Meier method was used to estimate survival as a function of time, and survival differences were analyzed using the log‐rank test. Univariate and multivariate analyses of different variables were performed using logistic regression. In our post hoc analysis, the objective response rate (ORR), disease control rate (DCR), PFS, and OS for RD were evaluated according to the presence or absence of maintenance therapy, duration of ICI treatment, and ORR of front‐line platinum‐based chemotherapy plus anti‐PD‐1/PD‐L1 antibodies. For further analysis, the cutoff value for the duration of ICI treatment was defined as median values. In our exploratory analysis, moreover, receiver operating characteristic (ROC) curve analysis was performed to confirm the optimal cutoff value of the duration of ICI treatment, and the sensitivity and specificity were calculated to determine the optimal cutoff value for differentiating responders from nonresponders by the ROC curve. Responders were defined as those with a PFS of >6 months for DR. Those variables with p < 0.05 in univariable analyses were fit in a multivariable model. The duration of ICI treatment was defined as the period from the starting point of induction therapy by chemoimmunotherapy to the discontinuation of ICI therapy. All statistical analyses were performed using GraphPad Prism (version 8.0; GraphPad Software) and JMP 14.0 (SAS Institute Inc.).

RESULTS Patient demographics and front‐line therapy Patient information including maintenance therapy, duration of ICI treatment, and ORR of front‐line chemoimmunotherapy are shown in Table 1 . As described in our previous report, 6 KEYNOTE 189, 2 KEYNOTE 407, 3 IMpower 150, 4 IMpower 130, 17 IMpower 132, 18 and other regimens were administered to 160 (55.6%), 58 (20.1%), 15 (5.2%), four (1.4%), 11 (3.8%), and 38 (13.2%) patients, respectively. The median number of cycles of induction chemotherapy was four (range, 1–8 cycles). The median number of cycles of maintenance therapy after induction chemotherapy was four (range, 1–29 cycles). The median duration of ICI treatment was 180 days (range, 0–671 days). Therefore, the cutoff value for the duration of ICI treatment were 180 days. The anti‐PD‐1 and anti‐PD‐L1 antibodies used for chemoimmunotherapy were detected in 236 (81.9%) and 52 (18.1%) patients, respectively. Among the 288 patients, 225 (78.1%) received maintenance therapy after induction chemotherapy, and 108 (37.5%) received both maintenance therapy and ICIs for >180 days. On the other hand, all (100%) of 108 patients having ICIs for >180 days received maintenance therapy. Prior radiation therapy was frequently observed in patients receiving maintenance therapy or >180 days of ICI treatment. Pleural effusion and bone metastases were associated with the presence of maintenance therapy. Negative PD‐L1 expression was closely associated with an ICI treatment duration of ≤180 days. Nonadenocarcinoma (AC) significantly correlated with a complete response (CR) or partial response (PR) to front‐line treatment. Efficacy of front‐line therapy Among the 288 patients in our study, CR, PR, stable disease (SD), progressive disease (PD), and not evaluable (NE) were observed in one, 153, 87, 40, and seven patients, respectively. The ORR and DCR of front‐line treatment were 54.8% and 85.7%, respectively. Among the patients receiving RD, CR, PR, SD, PD, and NE were observed in one, 82, 118, 73, and 14 patients, respectively. The ORR and DCR of RD were 28.8% and 69.8%, respectively. Table 2 shows the ORR and DCR of RD according to the presence/absence of maintenance therapy, duration of ICI treatment, and ORR of front‐line chemoimmunotherapy. Maintenance therapy significantly improved the DCR of RD regardless of the histological type, but not the ORR. Continuous administration of an ICI for >180 days significantly improved the DCR. The CR or PR of front‐line therapy significantly increased the ORR of RD, regardless of histology. Univariate and multivariate survival analysis for predictors of RD efficacy The median PFS and OS times for all patients were 4.1 and 11.6 months, respectively. A total of 260 patients experienced disease progression, 146 of whom died. Univariate analysis of all patients identified performance status, histology, maintenance therapy, and ICI treatment duration >180 days as significant predictors of better PFS and OS after RD administration (log‐rank test, Table 3 ). Multivariate analysis confirmed that these factors independently predicted favorable PFS and OS (Table 3 ). The Kaplan–Meier survival curves for PFS and OS according to maintenance therapy, ICI treatment duration, and objective response are shown in Figure 1 . Although the survival analysis according to histology was displayed in Figure A1 (online only), the maintenance and ICI treatment duration >180 days were closely associated with favorable prognosis regardless of histological type. The DCR of front‐line chemoimmunotherapy was also related to the outcome after RD administration in all patients (Figure A2 , online only). The effects of RD on PFS and OS were unaffected by PD‐L1 expression levels (Figure A3 , online only). As shown in Figure A4 (online only), the number of cycles of maintenance therapy (>4 vs. 1–4) significantly altered the effects of RD on PFS in all and non‐AC patients; however, it did not alter the effects of RD on OS regardless of histology.

DISCUSSION Our exploratory analysis identified the transition to maintenance therapy and ICI treatment for >180 days in front‐line chemoimmunotherapy as independent predictors of better outcomes after RD administration in patients with advanced NSCLC. Although all patients receiving ICIs for >180 days also received maintenance therapy, sensitivity to prior immunotherapy appeared to be associated with increased RD efficacy. In agreement, in previous studies, prior ICI treatment was a critical determinant of an improved response to RD. 8 , 9 , 10 , 11 At least, continuous administration of ICI for >180 days as prior treatment could definitely predict the PFS of >6 months for DR. The results of our large‐scale study suggest that RD is an appropriate second‐line choice for patients with advanced NSCLC whose front‐line treatment included maintenance therapy and continuous administration of an ICI. The present study does not explain how maintenance therapy including continuous ICI treatment improved treatment outcome after RD administration. In general, ICIs promote the entry of CD4, CD8, and other tumor‐infiltrating lymphocytes (TILs) into tumors, where they subsequently kill tumor cells. 19 Angiogenetic proteins such as vascular endothelial growth factor (VEGF) and VEGFR create an immunosuppressive tumor microenvironment, with resultant increases in the expression of FOXP3 and the number of myeloid‐derived suppressor cells. 20 , 21 , 22 We hypothesize that extended ICI treatment achieves a tumor microenvironment in which CD4/CD8 TIL levels are high and FOXP3 levels are low, contributing to the downregulation of VEGF signaling. In this situation, tumor growth may be easily suppressed by exposure to VEGFR2 inhibitors such as ramucirumab. In contrast, patients with low sensitivity to ICIs may be resistant to VEGFR2 inhibitors owing to upregulation of VEGF signaling in response to increased FOXP3 expression. Recently, we reported that high VEGFR2 expression in tumor tissue significantly predicted a poor outcome after PD‐1 blockade and closely correlated with the number of FOXP3‐expressing TILs in patients with advanced NSCLC. 22 In the present study, we did not investigate whether the CD4/CD8 TIL and FOXP3 levels in the tumor specimens correlated with VEGFR2 expression, and the biological mechanism underlying the increased efficacy of RD after continuous ICI treatment for >180 days remains unresolved. Further studies are needed to elucidate the relationship between the efficacy of VEGFR2 inhibitors and the status of the tumor microenvironment after ICI administration. In our previous study on 288 patients with advanced NSCLC, RD after first‐line chemoimmunotherapy had an ORR of 28.8%, DCR of 69.8%, median PFS time of 4.1 months, and median OS time of 11.6 months. 6 In the study by Brueckl et al. on 77 NSCLC patients, these values were 32.5%, 62.4%, 6.4 months, and 15.5 months, respectively. 13 In the study by Ishida et al. on 18 NSCLC patients, the ORR of RD was 55.6% and the PFS time was 5.8 months. 23 They found that the patients who responded to prior chemoimmunotherapy for more than 8.8 months exhibited a significantly longer response to RD than those responded for less than 8.8 months. 23 This is similar to the results of our study; however, the duration of response was different (8.8 vs. 6.0 months). However, their study was small sample size with 18 patients, compared to our large sample with 288 patients. At least, the duration responding to prior chemoimmunotherapy may be important for the efficacy of RD as second line setting. In the current analysis, the patients who received maintenance therapy including ICI treatment achieved an ORR of 32.7%, DCR of 78.5%, PFS time of 7.7 months (216 days), and OS time of 14.2 months (397 days). Although it is difficult to compare the results of individual studies because of different sample sizes, we suggest that sensitivity to chemoimmunotherapy may engender a clinical benefit of RD in the second‐line setting. To date, there is no evidence to as to whether prior administration of cytotoxic agents improves the efficacy of RD in various human neoplasms. Thus, we believe that maintenance therapy should include continuous ICI treatment for a sufficient amount of time. Tumor shrinkage due to chemoimmunotherapy has been shown to significantly increase the ORR of RD but not to improve the treatment outcome. It also makes it difficult to distinguish the contribution of cytotoxic agents from that of ICIs. In our study, the response rate of chemoimmunotherapy did not predict the outcome of subsequent RD treatment. Our study had several limitations. First, VEGFR2 expression in tumor cells was not assessed. Thus, whether VEGFR2 expression predicts RD efficacy remains unclear, and further investigation is required. Second, different chief physicians chose the first‐line chemotherapy regimens, and differences in the regimens (albeit small) might have biased our results. Finally, because all patients received RD as the second‐line treatment after chemoimmunotherapy, we could not compare the outcomes of RD with those of ramucirumab or docetaxel alone. Thus, it remains unclear whether prior ICI treatment affects the efficacy of ramucirumab, docetaxel, or both. Prospective studies are needed to address this issue. A previous study reported an improved response rate to docetaxel alone after ICI treatment 24 ; however, the underlying mechanism remains unclear. In conclusion, extended ICI treatment after chemoimmunotherapy and maintenance therapy enhanced the efficacy of second‐line RD treatment in patients with advanced NSCLC. Sensitivity to ICI therapy may improve the outcomes of RD treatment.

Abstract Background The factors that predict the clinical response to ramucirumab plus docetaxel (RD) after first‐line chemoimmunotherapy are unresolved. We explored whether the therapeutic efficacy of prior chemoimmunotherapy could predict the outcome of RD as sequential therapy in patients with advanced non‐small cell lung cancer (NSCLC). Methods Our study comprised 288 patients with advanced NSCLC who received RD as the second‐line treatment after first‐line chemoimmunotherapy at 62 Japanese institutions. Chemoimmunotherapy consisted of a platinum‐based regimen and immune checkpoint inhibitors (ICIs). The association between several variables and the therapeutic outcome of RD was determined via logistic regression analysis. Results Of the 288 patients, 225 (78.1%) received maintenance therapy and 108 (37.5%) received both ICI treatment for >180 days and maintenance therapy. All of 108 patients having ICIs for >180 days received maintenance therapy. Univariate analysis identified performance status, histology (adenocarcinoma), maintenance therapy, and ICI treatment >180 days as significant predictors of better progression‐free survival (PFS) and overall survival (OS) after RD administration. Multivariate analysis confirmed that these factors independently predicted favorable PFS and OS. The therapeutic response and PD‐L1 expression were not closely associated with outcome after RD treatment. In particular, maintenance therapy >4 cycles was more predictive of the better prognosis for RD treatment. Conclusion Extended ICI treatment after chemoimmunotherapy and maintenance therapy enhanced the efficacy of second‐line RD treatment in patients with advanced NSCLC. Extended checkpoint inhibitor (ICI) treatment after chemoimmunotherapy enhances the efficacy of second‐line ramucirumab plus docetaxel (RD) treatment. First‐line ICI treatment for >180 days was independent predictors of better outcomes after RD administration. Continuous administration of prior ICI for >160 days could definitely predict the PFS of >6 months for DR. Yamaguchi O , Mori K , Takata S , Shibata K , Chikamori K , Kimura N , et al. Extended ICI treatment after first‐line chemoimmunotherapy could predict the clinical benefit of ramucirumab plus docetaxel in advanced non‐small lung cancer: Post hoc analysis from NEJ051 ( REACTIVE study) . Thorac Cancer . 2024 ; 15 ( 2 ): 163 – 171 . 10.1111/1759-7714.15173

AUTHOR CONTRIBUTIONS Ou Yamaguchi: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing original draft; Draft review and editing. Keita Mori: Conceptualization; Formal analysis; Methodology; Writing original draft; Writing original draft; Draft review and editing. Saori Takata: Investigation; Draft review and editing. Kazuhiko: Investigation; Draft review and editing. Kenichi Chikamori: Investigation; Draft review and editing. Nozomu Kimura: Investigation; Draft review and editing. Yoshiaki Nagai: Investigation; Draft review and editing. Taku Nakagawa: Investigation; Draft review and editing. Satoshi Igawa: Investigation; Draft review and editing. Taishi Harada: Investigation; Draft review and editing. Hiroshige Yoshioka: Investigation; Draft review and editing. Hisashi Tanaka: Investigation; Draft review and editing. Hitomi Nogawa: Investigation; Draft review and editing. Hiroaki Satoh: Investigation; Draft review and editing. Toshihiro Shiozawa: Investigation; Draft review and editing. Kosuke Tsuji: Investigation; Draft review and editing. Kunihiko Kobayashi: Conceptualization; Methodology; Draft review and editing. Kyoichi Kaira: Conceptualization; Funding acquisition; Methodology; Project administration; Writing original draft; Draft review and editing. FUNDING INFORMATION This study was financially supported by Eli Lilly Japan K.K. CONFLICT OF INTEREST STATEMENT Kyoichi Kaira reports a relationship with AstraZeneca Pharmaceuticals LP that includes speaking and lecture fees. Kunihiko Kobayashi reports a relationship with AstraZeneca that includes speaking and lecture fees. Kunihiko Kobayashi reports a relationship with Takeda Pharmaceutical Co Ltd that includes speaking and lecture fees. peaking and lecture fees. Ou Yamaguchi reports a relationship with Eli Lilly Japan K.K. that includes speaking and lecture fees. Ou Yamaguchi reports a relationship with Ono Pharmaceutical Co Ltd that includes speaking and lecture fees. Ou Yamaguchi reports a relationship with Bristol Myers Squibb Co that includes speaking and lecture fees. Ou Yamaguchi reports a relationship with Chugai Pharmaceutical Co Ltd that includes speaking and lecture fees. Ou Yamaguchi reports a relationship with Merck Sharp & Dohme Corp that includes speaking and lecture fees. Ou Yamaguchi reports a relationship with AstraZeneca that includes speaking and lecture fees. DISCLAIMER The content of this publication does not necessarily reflect the views of policies of the Department of Health and Human Services, nor does mention of trade names, c. Supporting information

ACKNOWLEDGMENTS The authors thank Yuka Matsui (M‐Techno Planning), Tomohiro Marui 14 (M‐Techno Planning), and Hisao Imai (M.D., PhD, Saitama Medial University International 15 Medical Center) for their assistance with the manuscript. The authors also thank Editage 16 ( www.editage.jp ) for English language editing. DATA AVAILABILITY STATEMENT Data are available on reasonable request.

CC BY

no

2024-01-16 23:42:02

Thorac Cancer. 2023 Nov 27; 15(2):163-171

oa_package/96/fe/PMC10788474.tar.gz

PMC10788475

38011005

INTRODUCTION Thymic epithelial tumors (TETs) are rare tumors that occur in the anterior mediastinum, accounting for less than 1% of adult malignancies. 1 , 2 , 3 TETs include thymoma and thymic carcinoma and can be further classified into A, AB, B1, B2, B3, and C (i.e., thymic carcinoma) subtypes based on histological characteristics. 4 , 5 All subtypes are associated with recurrence and metastasis, while the invasiveness of TETs increases with their histological subtype. Known prognostic indicators for TETs include histological type, stage, and the possibility of surgical resection. 6 Surgical resection is the recommended treatment for early‐stage TETs. However, anthracycline or platinum‐based chemotherapy and/or radiation is the main first‐line therapy for advanced unresectable TETs. 7 Unfortunately, advanced TETs are associated with a poor prognosis. In previous studies, patients with thymomas were found to have a median progression‐free survival (mPFS) of 12.10–21.00 months and an objective response rate (ORR) of 15.0%–40.0%. Patients with thymic carcinomas, on the other hand, had a mPFS of 2.90–4.00 months and an ORR of 5.0%–26.0%. 8 , 9 Currently, there is no established second‐line treatment for TETs. Tumor angiogenesis is an important therapeutic target for malignant tumors. Angiogenesis, the formation of new blood vessels, plays a critical role in the development of TETs. Previous studies revealed high expression levels of vascular endothelial growth factor (VEGF)‐A and its receptors VEGFR1 and VEGFR2 in TETs. Furthermore, the density of microvessels and expression level of VEGF have been linked to the invasion, infiltration, and clinical staging of TETs. 10 Several clinical studies have explored the efficacy of targeted therapies in TETs. In a single‐arm phase II clinical study, 41 patients with TETs who had previously failed chemotherapy were administered oral sunitinib; the patients with thymoma ( n = 16) had an ORR of 6.0% and mPFS of 8.50 months, while the patients with thymic carcinoma ( n = 25) had an ORR of 26.0% and mPFS of 7.20 months. 11 Another single‐arm phase II clinical study evaluated the efficacy of lenvatinib in 42 patients with advanced thymic carcinoma, achieving an ORR of 38.0% and mPFS of 9.30 months. 12 Furthermore, a single‐arm phase II screening study was conducted on 19 patients with TETs who had previously failed chemotherapy; the treatment with regorafenib resulted in mPFS of 9.60 months and an OS of 33.80 months. 13 Apatinib, an oral tyrosine kinase inhibitor, was also evaluated in a single‐arm phase II clinical trial including 25 patients who had metastatic or relapsed TETs; an ORR of 40.0% and mPFS of 9.00 months were found in these patients. 14 In a retrospective analysis of 20 patients with advanced TETs who had failed platinum‐containing chemotherapy, daily continuous sunitinib treatment achieved an ORR of 31.6% and an overall mPFS of 7.30 months among 19 patients with evaluable response; for patients with thymoma, the mPFS was 7.30 months and ORR was 41.0%; for patients with thymic carcinoma, the mPFS was 6.80 months and ORR was 41.0%. 15 Another retrospective study was conducted in China, which included 22 patients who received anlotinib monotherapy or anlotinib combined with chemotherapy/immunotherapy; the study reported an ORR of 9.1%, mPFS of 12.00 months, and OS of 24.00 months. 16 These previous findings emphasize the potential effectiveness of targeted therapies on TETs. However, these studies were mostly single‐center, single‐arm studies based on a small number of cases due to the relatively low incidence of TETs. Meanwhile, the efficacy of antiangiogenic inhibitors in the Chinese TET population has not been widely reported. Therefore, we utilized a real‐world database to analyze the efficacy and safety of multitarget antivascular inhibitors in managing advanced TETs. Additionally, we also investigated the clinical factors that have impact on survival projections of the patients.

METHODS Study design and data collection A total of 1242 patients with pathologically documented TETs at Zhejiang Cancer Hospital from October 2016 to October 2022 were screened, among which 52 patients treated with small molecule multitarget antiangiogenic inhibitors were enrolled. The major inclusion criteria were: Eastern Corporation Oncology Group performance status (ECOG PS) of 0–2; stage IVA or IVB defined by the Masaoka‐Koga classification; at least one measurable lesion defined by the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1; with complete clinic data and follow‐up information; treated with small molecule multitarget antiangiogenic inhibitors. The major exclusion criteria were malignant tumors in other sites (Figure 1 ). Ethical approval for conducting this study was obtained from the Institutional Ethics Committee at Zhejiang Cancer Hospital (no. IRB‐2023‐548). As a retrospective study, individual patient consent was not required. Efficacy assessment PFS refers to the time between initiation of therapy and the onset of disease progression, or death from any cause, whichever is sooner. OS refers to the time from the start of therapy to death from any cause. Disease progression is primarily assessed by clinicians on imaging. As defined by the investigators, ORR refers to the proportion of patients with a complete response (CR) or partial response (PR). The disease control rate (DCR) is the percentage of patients with CR, PR, or stable disease (SD). Statistical analysis GraphPad Prism (version 9.0.0) and SPSS (version 24.0) were used for statistical analysis. A chi squared test was performed for features with normally distributed distributions. For PFS and OS survival analyses, Kaplan–Meier methods were applied. In order to obtain adjusted odds ratio (OR) and 95% confidence intervals (95% CI), univariate and multivariate binary logistic regressions were conducted. The significance level was set at p < 0.05.

RESULTS Characteristics of patients A total of 52 patients with TETs who had been treated with small molecule multitarget antiangiogenic inhibitors were enrolled in this retrospective study (Figure 1 ). The baseline characteristics of all the patients are shown in Table 1 . These patients had a median age of 55 (range: 35–82) years. A total of 69.2% of patients ( n = 36) were under 60 years of age, 55.8% ( n = 29) were male, 57.7% ( n = 30) were current or former smokers, 92.3% ( n = 48) had an ECOG PS of 0–1, and 88.5% ( n = 46) had a Masaoka‐Koga staging of IVB. The histology of the patients was 16 (30.8%) thymoma and 36 (69.2%) thymic carcinoma. The most common type of thymoma was type B2 ( n = 7), and the most common type of thymic carcinoma was squamous cell carcinoma ( n = 22). Only one thymoma patient had myasthenia gravis. The most common sites of distant metastases were lung (69.2%, 36/52) and liver (32.7%, 17/52). Moreover, 82.7% ( n = 43) patients had ≥2 metastatic lesions. Furthermore, of the 52 patients, 25 (48.1%) had undergone surgery ( p < 0.001), and 41 (78.8%) had received radiotherapy. An ultrasound‐ and computed tomography‐guided needle biopsy or thoracoscopic examination is commonly performed as a supplementary histopathological examination in patients with TETs who are not undergoing surgery. Seven (13.5%,7/52) patients received antiangiogenic therapy as their first‐line treatment, while the median number of prior treatment lines was two lines (range: 0–5). The majority of patients (80.8%, 42/52) received antiangiogenic inhibitors as monotherapy. Among the patients who received combined therapy, the major (90.0%, 9/10) histology of TETs was thymic carcinoma, seven (70.0%, 7/10) patients received immune checkpoint inhibitors as combined drugs, and three thymic carcinoma patients received chemotherapy combined with antiangiogenesis therapy. Among all the patients treated with small molecule multitarget antiangiogenic drugs, 33 (63.5%) were treated with apatinib, 15 (28.8%) with anlotinib, and four (7.7%) with lenvatinib or sunitinib. No statistically significant differences in age, gender, smoking, ECOG PS, staging, myasthenia gravis, site or number of metastatic lesions, radiotherapy, lines of antiangiogenesis therapy, single or combined regimens, or the type of the antiangiogenesis drugs were found between the two groups. Efficacy and survival analysis Based on reverse Kaplan–Meier analysis, follow‐up ended on August 10, 2022, for a median follow‐up period of 52.3 months. Among the 52 patients with TETs who received small molecule multitarget antiangiogenic drugs, none achieved CR, 21.1% ( n = 11) showed PR, 73.1% ( n = 38) showed SD, and 21.1% ( n = 11) had PD (Table 2 ). The ORR was 21.1%, the DCR was 94.2% (Table 2 ), the mPFS was 8.05 months (Figure 2a ), and the mOS was 25.00 months (Figure 2b ). No CR was achieved in 16 patients with thymoma, 25.0% ( n = 4) achieved PR, 56.3% ( n = 9) showed SD, and 18.7% ( n = 3) had PD, resulting in ORR and DCR of 25.0% and 81.3%, respectively (Table 2 ). The mPFS was 8.40 months (Figure 2c ), and the mOS was 24.30 months (Figure 2d ). No CR or PD was achieved in 36 patients with thymic carcinoma, 19.4% ( n = 7) obtained PR, and 80% ( n = 29) showed SD. In Table 2 , their ORR and DCR correspond to 19.4% and 100.0%, respectively. In addition, the mPFS lasts 10.40 months as shown in Figure 2c , while the mOS reaches 25.10 months as shown in Figure 2d . No statistical differences were observed in mPFS (8.40 vs. 10.40 months, p = 0.703) and mOS (24.30 vs. 25.10 months, p = 0.582) between the two groups (Figure 2c,d ). To further explore whether the effectiveness of single‐drug monotherapy ( n = 42) was distinctive from combined therapy ( n = 10) on these patients, we evaluated their mPFS (8.40 vs. not available, p = 0.102) (Figure 3a ) and mOS (25.00 vs. not available, p = 0.525) (Figure 3b ) but found no statistical differences. Meanwhile, no statistical differences were found in the mPFS (10.40 vs. 7.30 vs. 6.50 months, p = 0.878) (Figure 3c ) and mOS (25.10 vs. 21.30 vs. 29.15 months, p = 0.580) (Figure 3d ) among the patients treated with apatinib ( n = 33), anlotinib ( n = 15), and lenvatinib or sunitinib ( n = 4). Prognostic analysis of patients with TETs Univariate binary logistic regressions indicated that the combined treatment was associated with a superior OS (OR: 0.214, 95% CI: 0.048–0.957, p = 0.044) (Table 3 ). Additionally, multivariate binary logistic regressions further revealed that the combined treatment was an independent prognostic factor for PFS (OR: 0.038, 95% CI: 0.003–0.484, p = 0.012) (Table 3 ) and OS (OR: 0.026, 95% CI: 0.001–0.475, p = 0.014) (Table 3 ). Significant response to apatinib in patients with advanced thymic carcinoma and liver metastasis A 63‐year‐old male was diagnosed with IVB (Masaoka‐Koga staging) thymic carcinoma with liver metastasis. He received two cycles of platinum‐containing chemotherapy as the first‐line treatment from January 17, 2019 to February 11, 2019. After two cycles of treatment at Zhejiang Provincial Cancer Hospital, the patient experienced disease progression in the liver metastasis. Then, he received apatinib monotherapy as the second‐line treatment from March 5, 2019, later confirmed as a partial response by computed tomography scanning. His PFS was 41.80 months, the primary lesion was significantly reduced, and the liver metastases remained stable (Figure 4 ).

DISCUSSION As TET is a relatively rare and indolent tumor, the patients can survive a considerable length of time after disease progression or relapse, making it extremely difficult to conduct large‐scale prospective randomized studies. 19 To the best of our knowledge, this real‐world retrospective study of small molecule multitargeted antiangiogenic inhibitors on TETs in China involved a considerable sample size compared with other recent studies (Table 4 ). Our analysis showed a durable response, indicated by the ORR of 21.1%, the mPFS of 8.05 months (Figure 2a ), and the mOS of 25.00 months (Figure 2b ). No statistical differences in the mPFS or mOS were found between the 16 patients with thymoma and 36 patients with thymic carcinoma (Figure 2c,d ). Similarly, a single‐arm phase II clinical trial in China included 25 patients with advanced TETs who failed platinum‐containing chemotherapy, were given 500 mg orally apatinib per day, and reported an overall population ORR of 40.0%, mPFS of 9.00 months, and mOS of 24.00 months, indicating the antitumor activity of the treatment. 14 Meanwhile, Proto et al. 17 conducted a multicenter Simon 2‐stage phase II trial, and reported that sunitinib as a second‐line treatment achieved an ORR of 21.7% at stage 2 in 32 patients with advanced or recurrent thymic carcinoma. In the current study, the mPFS (Figure 3a ) and mOS (Figure 3b ) of the single‐drug monotherapy group were 8.40 and 25.00 months, respectively, while the mPFS (Figure 3a ) and mOS (Figure 3b ) of the combined therapy group were not available. Multivariate binary logistic regressions revealed that combined treatment was an independent prognostic factor for PFS and OS (Table 3 ), suggesting that the combination treatment regime might be a potentially effective predictor for the prognosis of patients with advanced TETs. Among the combined therapy group, the majority of patients received immune checkpoint inhibitors as the combined therapy drugs. Previous studies have reported the antitumor activity of second‐ or post‐line pembrolizumab. Cho et al. conducted a single‐arm phase II study including 33 patients with TETs with previous chemotherapy failure; the ORRs of the patients with thymoma and thymic carcinoma were 28.6% and 19.2%, respectively, and the mPFS was 6.10 months for both. 20 Another phase II study on pembrolizumab in 40 patients with advanced thymic carcinoma reported an ORR of 22.5%. 21 Additionally, in another study, the incidence of grade 3–5 immune‐related adverse reactions was quite high; 26.4% in TETs, 58.3% in thymoma, and 17.1% in thymic carcinoma, which requires close monitoring. 22 Angiogenesis is necessary for the genesis of TETs, and the architectural changes related to angiogenesis can hamper immune trafficking and immune cell metabolism, thereby reducing antitumor activities. 23 Antiangiogenesis drugs can enhance the efficacy of immunotherapy. 24 Conforti et al. conducted a single‐arm multicenter phase II study to evaluate the efficacy of avelumab plus axitinib combined therapy in 32 patients with advanced TETs, and found an overall ORR of 34%, an mPFS of 7.50 months, and an mOS of 26.6 months. 18 Another phase II study on the effect of combined pembrolizumab and lenvatinib (NCT04710628) 25 on patients with advanced TETs is ongoing. Our study showed that the mPFS and mOS of the patients treated with apatinib were 10.40 and 25.10 months, anlotinib were 7.30 and 21.30 months, and lenvatinib or sunitinib were 6.50 and 29.15 months. Apatinib is a highly selective inhibitor of VEGFR2 and anlotinib is a VEGFR2/3 inhibitor, the treatment of which previously achieved ORRs of 40% and 9.1%, respectively, in patients with advanced TETs. 14 , 16 As promising new drugs for thymic carcinoma, angiogenesis inhibitors such as sunitinib and lenvatinib previously achieved ORRs of 26.0% and 38.0%, respectively. 26 There were certain limitations in this study. First, the sample size of TETs patients was small due to the fact that TETs are relatively rare. Second, our study was single‐center and retrospective. Finally, data of adverse events were not reported due to the lack of complete records. In conclusion, small molecule multitarget antiangiogenic inhibitors possess certain efficacy in treating patients with advanced TETs and may serve as an alternative therapeutic option for second‐ and further‐line treatment for patients with advanced TETs. Furthermore, the effect of combined small molecule antiangiogenic inhibitors treatment and chemotherapy/immunotherapy needs to be further explored in the future.

Abstract Background Thymic epithelial tumors (TETs) are rare malignant tumors with limited treatment options. No established second‐line treatment regimen is available following the preferred first‐line chemotherapy, resulting in unsatisfactory efficacy and poor prognosis for patients with advanced TETs. This study aimed to evaluate the efficacy of small molecule multitarget antiangiogenic inhibitors as well as the prognostic factors for advanced TETs. Methods A retrospective study was conducted using data from a real‐world database. Clinical information and survival follow‐up data were collected from 52 patients with advanced TETs who received small molecule multitarget antiangiogenic inhibitors at Zhejiang Cancer Hospital between August 10, 2016 and August 10, 2022. The short‐term efficacy of the treatments, survival time of the patients, and relevant prognostic factors of advanced TETs were analyzed. Results Out of the 52 patients included in this study, 16 had thymoma and 36 had thymic carcinoma. The 52 patients had an overall response rate of 21.1% and a disease control rate of 94.2%. In addition, the median progression‐free survival (PFS) was 8.05 months, and the overall survival (OS) was 25.00 months. Apatinib was given to 33 patients, anlotinib to 15 patients, and sunitinib or lenvatinib to four patients. Only seven patients received antiangiogenic inhibitors as their first‐line therapy, 27 patients as their second‐line therapy, and 18 patients as third‐line or subsequent therapy. Meanwhile, 42 patients received monotherapy with an antiangiogenesis inhibitor, while 10 patients received combination therapy. Univariate analysis indicated that the combined treatment was associated with a superior OS ( p = 0.044); multivariate analysis indicated that the combined treatment was an independent prognostic factor for PFS ( p = 0.014) and OS ( p = 0.012). Conclusion The findings suggest that small molecule multitarget antiangiogenic inhibitors are efficacious as second or post‐line treatments as a viable alternative treatment option for patients with advanced TETs. The findings suggest that small molecule multitarget antiangiogenic inhibitors are efficacious as second or post‐line treatments as a viable alternative treatment option for patients with advanced TETs. Shen W , Jin Y , Yu Y , Chen N , Fan Y . Small molecule multitarget antiangiogenic inhibitor treatments for advanced thymic epithelial tumors: A retrospective study . Thorac Cancer . 2024 ; 15 ( 2 ): 122 – 130 . 10.1111/1759-7714.15167

AUTHOR CONTRIBUTIONS Y.F. conceived the idea and designed the framework of the manuscript. W.S. conducted data analysis and interpretation, performed literature searches, and wrote the manuscript. Y.J. revised the entire manuscript and ensured its integrity. Y.Y. and N.C. contributed to data acquisition. All authors have read and agreed to the published version of the manuscript. CONFLICT OF INTEREST STATEMENT The authors declare no conflicts of interest.

CC BY

no

2024-01-16 23:42:02

Thorac Cancer. 2023 Nov 27; 15(2):122-130

oa_package/9c/f1/PMC10788475.tar.gz

PMC10788477

38226083

Introduction This article was previously presented as an e-poster at the 15th IHPBA World Congress in New York City in March 2022 and was published online as an abstract in October 2022 in the HPB journal. Periampullary cancer includes neoplasms arising from four different anatomical sites with proximity to the major duodenal papilla: head of pancreas, ampulla of Vater, distal common bile duct (CBD), and periampullary duodenum [ 1 ]. Surgical resection (pancreaticoduodenectomy) is the standard treatment modality for resectable periampullary cancer that offers a chance for a cure. This surgical procedure has evolved over a period of time since it was first described by Codvilla in 1898, but it is still associated with high morbidity (40%), though mortality has decreased to less than 5% [ 2 ]. Although these tumors are in close proximity anatomically, they have different survival outcomes. Non-pancreatic periampullary cancers have a more favorable five-year overall survival (25% to 75%) as compared to pancreatic head cancers (0% to 20%) [ 1 ]. Various clinicopathological factors, like lymphovascular invasion, perineural invasion, resection margin, and lymph node involvement, have been studied to determine the survival outcome after pancreaticoduodenectomy for periampullary cancers [ 3 , 4 ]. These factors can help in determining the prognosis of a patient as well as in treatment planning. So, this study aimed to identify the predictive factors associated with poor survival in periampullary cancers following pancreaticoduodenectomy at Tribhuvan University Teaching Hospital, Kathmandu, Nepal.

Materials and methods We retrospectively analyzed records of patients who underwent pancreaticoduodenectomy (PD) at Tribhuvan University Teaching Hospital, Kathmandu, Nepal, from April 2004 to May 2014. The data was updated until April 2021. The staging of the disease was done according to the 8th edition of the American Joint Committee on Cancer (AJCC). Patients who had periampullary carcinomas (ampullary carcinoma, distal cholangiocarcinoma, pancreatic head carcinoma, and duodenal adenocarcinoma) in histopathological examination were included. Diagnosis and clinical staging of the disease were done by cross-sectional imaging like contrast-enhanced computed tomography (CECT) of the abdomen and pelvis, chest X-rays, and duodenoscopy. Then the patients with resectable disease were subjected to open PD. Data on demographics, primary diagnosis, histopathological diagnosis, pathological staging, and long-term outcome in terms of survival were retrieved from medical records and analyzed. The primary endpoint of the study was overall survival. The overall survival was calculated as the duration from the date of diagnosis until the last follow-up or death. The lymph node ratio (LNR) was defined as the number of lymph nodes with metastases divided by the total number of excised lymph nodes. The microscopic resection margin was considered positive when the tumor involved less than 2mm from the margin. The study protocol was reviewed and approved by the Institutional Review Board at Tribhuvan University Teaching Hospital. Descriptive statistics like median, frequency, and percentage were used for categorical variables. The survival outcome was analyzed by the Kaplan-Meier method. The prognostic variables of overall survival selected were lymphovascular invasion (LVI), perineural invasion (PNI), resection margin, lymph node positivity, and lymph node ratio. Univariate and multivariate analyses of prognostic variables for overall survival were done using Cox regression analysis. Factors that were found to be significant in univariate analysis were included in multivariate analysis. Statistical analysis was performed using IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp.

Results There were 115 patients who underwent PD from April 2004 to May 2014. Among them, 54 patients were excluded from the study for various reasons, as shown in Figure 1 . Thus, the study included 61 patients. The median duration of follow-up was 12 months (3 to 180 months). Demography and clinic-pathological features are shown in Table 1 . The mean age of patients was 56.2 ± 14.2 years, and there was a male preponderance (M:F = 1.4). Most of the patients (88.5%) had jaundice at the time of presentation, and ampullary carcinoma (68.5%) was the most common pathology among the periampullary cancers. Ten percent of the patients had a microscopic resection margin positive (R1). The median survival of all patients was 24 ± 44.3 months (Figure 2 ). The median survival of patients with pancreatic carcinoma, ampullary carcinoma, distal cholangiocarcinoma, and duodenal adenocarcinoma was 8, 24, 24, and 23 months, respectively (Figure 3 ). Non-pancreatic periampullary cancer patients had better median survival as compared to pancreatic cancer patients (24 vs. 8 months, p = 0.03), as shown in Figure 4 . The presence of lymphovascular invasion (LVI), perineural invasion (PNI), nodal involvement, and a higher lymph node ratio (LNR) was associated with poor median survival (Table 2 ). However, perineural invasion was the only factor associated with poor survival in multivariate analysis (Table 3 ).

Discussion Pancreaticoduodenectomy is the standard treatment for periampullary cancers. Postoperative complications and mortality have decreased with the advent of better surgical techniques and perioperative care. However, the long-term survival outcome is still low, and the five-year survival rate reported varied widely [ 4 ]. It ranged from 34.9% to 54% five-year survival [ 5 , 6 ]. El Nakeeb et al. showed that five-year survival was 20.6%, and median survival was 34 months [ 7 ]. They reported the worst prognosis in patients with pancreatic head adenocarcinoma and a better prognosis in patients with ampullary and duodenal adenocarcinoma. In our cohort, the median survival of the patients was 24 months, and pancreatic head cancer had a poor survival outcome as compared to other periampullary cancers. This may be because pancreatic cancer is known to be a biologically more aggressive tumor and has a higher incidence of nodal spread, perineural invasion, and lymphovascular invasion [ 8 ]. Histopathological characters like lymphovascular invasion, lymph node involvement, and perineural invasion have been shown to be predictors of survival. It is postulated that perineural invasion may be responsible for local treatment failure because tumors can grow along the nerve supplying the pancreas and then to the periarterial neural plexus. Similarly, lymphovascular invasion is considered responsible for regional or distant lymph node metastasis as well as solid organ metastasis like liver and lungs [ 9 ]. Chen JW et al. demonstrated that five-year survival was 77% in patients negative for lymphovascular invasion and perineural invasion, while 15% in patients positive for both factors [ 9 ]. In our study, both of these factors were significant predictors of survival in univariate analysis, but multivariate analysis showed perineural invasion as the only significant factor. The LNR was first reported to be related to the prognosis of gastric carcinoma by the Japanese. Then, it was implemented in other gastrointestinal cancers. LNR has been suggested as a predictor of survival in patients with periampullary carcinoma [ 10 , 11 ]. However, LNR was not a significant predictor of survival in our study. The resection margin after pancreaticoduodenectomy included all margins (i.e., anterior, posterior, pancreatic neck, and portal vein margins). There are mixed results regarding the effect of a positive resection margin (R1) on survival outcomes. Some studies showed that positive resection margin (R1) was a significant predictor of poor survival outcome [ 9 , 12 ], while other studies did not [ 13 , 14 ]. Our study is consistent with the later. This may be due to a lack of standard pathological examination and controversy regarding the definition of microscopic margin involvement used by the various studies. The AJCC classification has been shown to have prognostic value in most of the malignancies, including those of pancreatic carcinomas [ 15 , 16 ]. But, in this study, AJCC pathological stage was not a predictor of survival in multivariate analysis. Perineural invasion was shown to be an independently significant prognostic factor for survival in this study as well as in other studies [ 9 , 17 ]. Despite this fact, PNI has not been incorporated into the AJCC staging system. These studies strongly claim the inclusion of this parameter in any postoperative staging system. This study has some limitations. It is a retrospective study conducted in a single center with a small sample size.

Conclusions The presence of perineural invasion is associated with poor survival outcomes in periampullary cancer patients following pancreaticoduodenectomy. Also, pancreatic cancer has poor survival as compared to other periampullary cancers.

Background Periampullary cancers arise from four different anatomical sites and are in close proximity. But they have different survival outcomes. There are various clinicopathological factors associated with survival after pancreaticoduodenectomy done for periampullary cancers. So, we aimed to identify the predictive factors associated with poor survival in periampullary cancers at Tribhuvan University Teaching Hospital, Kathmandu, Nepal. Methods We analyzed the medical records of patients who underwent pancreaticoduodenectomy (PD) at Tribhuvan University Teaching Hospital, Kathmandu, from April 2004 to May 2014. Demography, clinicopathological features, and survival outcomes were analyzed retrospectively. Results This study included 61 patients. The mean age of patients was 56.2 ± 14.2 years, and there was a male preponderance (M:F = 1.4). The median survival of all patients was 24 months. Non-pancreatic periampullary cancer patients had better median survival as compared to pancreatic cancer patients (24 vs. 8 months, p = 0.03). The presence of lymphovascular invasion (LVI), peripheral invasion (PNI), nodal involvement, and a higher lymph node ratio (LNR) were associated with poor median survival. However, perineural invasion was the only factor associated with poor survival in multivariate analysis. Conclusion The presence of perineural invasion is associated with poor survival outcomes in patients with periampullary cancer following pancreaticoduodenectomy. Also, carcinoma of the head of the pancreas has poor survival as compared to other periampullary cancers.

CC BY

no

2024-01-16 23:42:02

Cureus.; 15(12):e50607

oa_package/96/59/PMC10788477.tar.gz

PMC10788479

38041547

INTRODUCTION Lung cancer is the primary cause of cancer‐related deaths worldwide. In general, non‐small cell lung cancer (NSCLC) make up approximately 85% of lung cancers, while small cell lung cancer (SCLC) comprises 15% of lung cancer cases. 1 From a histological point of view, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the two major subtypes of NSCLC. While next‐generation sequencing technology has facilitated the identification of specific somatic mutations in NSCLC, these mutations are only present in approximately 30% of cases and have led to improved survival outcomes through targeted inhibition therapies. 2 Recent studies have highlighted dysbiosis of the lower respiratory tract microbiome affects the progression of lung cancer, and microbiota emerging as crucial modulators in the carcinogenesis process and the immune response regulation against cancer cells. 3 Several studies have demonstrated a significant abundance of Granulicatella , Abiotrophia , and Streptococcus at genus level, along with reduced community diversity in lung cancer patient samples compared to control samples. 4 Our team has also observed that the lower respiratory tracts of lung cancer patients had less diversity in their microbiome. 5 However, the specific profile and functional role of microbiota in tumor colonization among NSCLC patients remain largely unknown. Lung cancer formation is tightly linked to chronic inflammation, which is defined by inflammatory cells infiltration and buildup of proinflammatory factors, including cytokines, which promote angiogenesis, cell proliferation, and tissue remodeling. 6 An elevated risk of microbiota infection exists in lung cancer patients, 7 and repeated exposure to microbiota alters the lung’ immune system. 8 The commensal microbiota, a diverse group of bacteria that colonize the lung following exposure to the external environment, has been found to influence the efficacy of immunotherapeutic treatments for human tumors. 9 Depending on the specific tumor microenvironment (TME), the microbiota may collaboratively modulate tumor‐promoting inflammation and antitumor immunity. Therefore, it is crucial to unravel the signaling pathways involved in the interactions between microbiota and host cells in the TME of NSCLC. Nevertheless, the precise signaling pathways involving microbiota and host cells in the TME of NSCLC are unknown. In conclusion, the dysbiosis of the lower respiratory tract microbiome and its interactions with the host immune system play significant roles in NSCLC progression. Investigating the specific microbiota profiles, functional roles, and signaling pathways involved in the NSCLC TME will contribute to our understanding of tumor development and guide the development of targeted therapeutic approaches in the future. In this study, we addressed this question using a combination of metagenomic sequencing of the microbiota in tumor and normal tissues from 61 NSCLC patients and six patients with other pulmonary diseases as control. As part of our investigation into the relationships between lung microbiota characteristics and clinical traits, as well as the host immune responses associated with microbiota of NSCLC patients, we also detected cytokines in the tumor tissues and their corresponding normal tissues from 24 NSCLC patients. These findings will offer a fresh look at the characteristics of the lung microbiota in NSCLC patients.

METHODS Patients and clinical data collection The enrollment for this study of patients who were diagnosed with NSCLC took place at West China Hospital of Sichuan University in China from 2020 to 2021. All patients included in the study underwent surgical treatment without receiving neoadjuvant therapy before surgery. Tumor samples and matched distal normal lung tissues located 5 cm away from the tumor margin were collected during the surgical procedure. Two pathologists examined each sample in order to determine the pathological diagnosis and tumor cellularity. The eighth edition of the American Joint Committee on Cancer's TNM method was used for cancer staging. Sample collection Clinical sample collection followed the principles stated in the Helsinki declaration and was approved by the Institutional Review Board of West China Hospital of Sichuan University, China. Informed consent was obtained from the patients. Tumor samples and matched distal normal lung tissues (distant from the tumor 5 cm) were collected during surgery. Within 20 min of surgery, we first minced tumor tissues into tiny cubes <0.5 mm 3 , and then divided the tissues into two groups. One was frozen with liquid nitrogen for metagenomic sequencing, and the other was used for cytokine detection. The only equipment and supplies that came into contact with the lung tissues were sterile. In addition, we introduced six negative controls from sample collection, extraction and sequencing. The patients underwent surgical treatment, and neoadjuvant therapy was not administered before the surgical procedure. The Institutional Review Board of West China Hospital of Sichuan University gave its approval to this study (Chengdu, China; project identification code: 2020232). Genomic DNA extraction and metagenomic sequencing Frozen tissue the size of a grain of rice and 500 μl PBS were first placed in a tissue lysis tube, then homogenized and lysed using a bead mill. Sample releasing agent (2007, Genskey) was used to remove hosts, and in accordance with the manufacturer's instructions, bacterial DNA was isolated using a microsample genomic DNA extraction kit (1901, Genskey). Using an NGS library construction kit (2014B, Genskey), the DNA libraries were created by performing DNA enzyme digestion (250–300 bp), end‐repair, A‐tailing, adapter ligation, and PCR amplification. An Agilent 2100 Bioanalyzer (Agilent Technologies) was used in conjunction with qPCR to measure the adapters prior to sequencing to evaluate the quality of the DNA libraries. Following a quality check, Illumina PE150 sequencing was carried out by combining several libraries according to the demands of effective concentration and target data amount. The sequencing tool utilized was the Illumina Novaseq 6000 (Illumina). Cell‐type composition analysis In order to assess whether cell‐type compositions were significantly changed between different diseases, the percentages of each cell‐type in each sample were calculated and visualized as boxplot by R package ggpubr (version 0.4.0). We applied the Wilcoxon rank sum test to compare two independent groups and performed Kruskal–Wallis test to compare three or more independent groups. p ‐values <0.05 were regarded as statistically significant. Microbiota analysis Fastp (version 0.19.5) in particular, 10 used to quality‐filter raw reads from samples, was used to check the data for adaptor contamination, low‐quality reads, and reads with low complexity. Using bowtie2 (version 2.3.4.3), 11 reads that corresponded to the nucleotide sequence database (NT) and the human reference assembly GRCh38 were eliminated. Next, based on the NT (version 20 210 619), the mapped reads were classified with Kraken (version 2.1.2). 12 After the above filtering, we retained the results in the annotated species (bacteria, fungi, and viruses) with a Perl script, normalizing the abundance to a data volume of 20 000 000 for subsequent analysis. Both alpha‐ and beta‐diversity analyses utilized QIIME2 13 and R. Evaluating the differences in alpha‐diversity indices by the Wilcoxon rank‐sum test or Kruskal–Wallis of R package ggpubr ( https://github.com/kassambara/ggpubr ); three dimensionality reduction methods (nonmetric multidimensional scaling [NMDS], principal coordinate analysis [PcoA], and principal component analysis [PCA]) were used in beta‐diversity to observe the sample distribution. Difference analysis is based on relative abundance, using the Wilcoxon test to find out the species with differences between groups ( p < 0.05, |FC| ≥ 10). We prefiltered out species with less than three detections within the group before differential analysis. We excluded the shared 392 species between six negative controls and the lung tissues to avoid being contaminated. Since tumor sizes, TNM stages, and smoking years have a greater impact on the tumor microecology, we also divided these three factors into different groups, and performed the above analysis under each group. Cytokine analysis We used the Spearman rank correlation analysis and Fisher's exact test to evaluate the correlation between the cytokines and the different species under each group ( p < 0.05, |R| ≥ 0.5). In addition, the cytokines under each group were analyzed with Wilcoxon rank‐sum test, and p < 0.05 was used as the filter condition to find the cytokines with differences between groups, and combined with the correlation results to infer the relationship between species and cytokines. Statistical analysis p ‐values <0.05 were regarded as statistically significant for all analyses, which were carried out using R software (version 4.0.3). The Wilcoxon rank‐sum test or the Kruskal–Wallis test was used to evaluate continuous variables. For beta‐diversity, statistical comparisons of weighted/unweighted UniFrac distances were performed by ANOSIM using the vegan package of the R software.

RESULTS The overall profiles of lung microbiome To characterize and visualize human NSCLC microbiota based on lung tissues, we performed metagenomic sequencing on 61 tumor tissues (tumor, n = 61) and their paired normal tissues (normal, n = 61), comprising 43 LUAD and 18 LUSC (Figure 1a , Tables S1 and S2). Beyond that, another six lung tissues of lung diseases were also sequenced. To address operating room or laboratory contaminants, environmental samples from collection and extraction were introduced as negative controls (Figure 1b ), and we found the microbiota load was lower in negative control samples (Table S2 ). Among tissues, the cytokine concentrations of 15 LUAD patients and 9 LUSC patients within the same batch were detected using a 48‐cytokine panel (Figure 1b and Table S3 ). In addition, the Clinical Biochemistry‐Based Indexes (CBBI) of NSCLC patients were also included from West China Hospital, Sichuan University (Table S1 ). To elucidate the microbiota community between tumor, normal tissues and negative controls, we used NMDS dimensionality reduction to compare the microbiota composition, and the results revealed a good confidence interval ellipse (stress <0.2) (Figure 1c ). However, there was no significant difference in microbiota communities between tumor and normal tissues according to the observed species (Figure 1d ). In general, we identified a total of 2034 microbes from 13 genera and four phyla in human lung tissues, and observed a noticeable trend of microbial alpha‐diversity that diminished from normal tissues to tumors. The prevalence of microbiota composition shown a difference between the two groups (Figure 1e ). The relative proportions in the genera Pseudomonas and Prevotella accounted for 0.0369% and 0.0202% of the tumor tissues, respectively, while Pseudomonas represented 0.0265% in normal tissues, and Prevotella accounted for 0.0066% in normal tissues (Table 1 ). In particular, Prevotella, previously reported to be enriched in a proinflammatory condition, 14 , 15 , 16 , 17 , 18 is highly enriched in tumor tissues (Figure 1f ). On the other hand, clinically common pathogens have also been detected in tumor tissues (Table S4 ). For example, Klebsiella pneumoniae abounded in tumors ( p < 0.05). Klebsiella pneumoniae is a bacterium that lives inside human intestines and can lead to pneumonia and infection if it gets into the lungs. 19 We also examined the microbiota composition in LUAD, LUSC, and other lung diseases (Figure S1a, b ). The results indicated that the relative abundance of the dominant microbiota was different in LUSC and LUAD, such as an enrichment of Acinetobacter in LUSC and Gordonia in LUAD. These findings may suggest that the microbiota in tumors is ecologically dysregulated compared to normal tissues. Inflammatory cytokine was significantly increased in tumors of NSCLC patients Lung is a dynamical balance and microbiota can interact with each other directly including mucous membranes, respiration and or indirectly via inflammatory cytokine. In this study, we aimed to assess the potential causal effect of lower airway dysbiosis to pulmonary immunity. We detected cytokine concentration between tumor and normal tissues. The results showed that 10 cytokines associated with proinflammatory including IL‐1β, IL‐4, IFN‐γ, MCP‐1, IL‐8, IL‐17, MIF, MIP‐1α, MIP‐1β, and TNF‐α were upregulated in tumors (Figure 2a ), while the concentration of LIF, SCGF‐β, SDF‐1α, TRAIL, and CTACK were higher in normal tissues (Figure 2b ). To better understand the host–microbe interaction in lung cancer, we evaluated the association between the bacteria and lung tissues, and discovered that Corynebacterium flavescens was more prevalent in tumors (Figure 2c and Supporting Information Table S5 ). On the other hand, Haemophilus influenzae , Staphylococcus aureus , Streptococcus vestibularis , and Acidovorax sp. RAC01 were found be more abundant in normal tissues (Figure 2c ). This accords with the results that IL‐17 could respond to Streptococcus agalactiae and Streptococcus salivarius in NSCLC were remarkably elevated. 20 We speculate that the inflammation caused by microbes may be the indirect promotion of proinflammatory cytokines. Microbiota signatures associated with stage in LUAD In order to determine the microbiome variation between different types of lung tumors, we first estimated microbiome community richness and diversity within the LUAD samples. The alpha‐diversity index, including ACE and Chao1 were analyzed in tumor and normal tissues (Figure 3a–c ). The results showed that the number of OTUs was significantly lower in tumors compared with normal tissues, and the diversity of the microbiota was also higher in normal groups. The dominant genera were abundant in Streptococcus , Pseudomonas , Corynebacterium , Acinetobacter , and Microbacterium in tumor and normal tissues (Figure 3d ). We then evaluated microbiota differences based on the clinical LUAD stages, grouped as I (early stage) and II–III (later stage) stage of TNM classification. The PCoA and ANOSIM test showed that these two groups had a significant difference (Figure 3e , ANOSIM, r = −0.0555, p = 0.763). There was a significant enrichment of common pathogenic microbiota such as Mycobacterium paragordonae , Desulfovibrio vulgaris , and human gammaherpesvirus ‐4 in stages II–III (Figure 3f ). It was noteworthy that Desulfovibrio is commonly found in the human gut and is associated with intestinal diseases. 21 , 22 , 23 , 24 This may suggest “gut‐lung axis” existed between gut and lung. 25 , 26 , 27 , 28 Furthermore, Cutibacterium acnes , Staphylococcus capitis , and Corynebacterium tuberculostearicum , were enriched in stage I and correlated with certain cytokines (Figure 3g ). In our study, its enrichment in stage I may have also played a beneficial role in the immune regulation of LUAD. The results of cytokine association analysis determined that C. tuberculostearicum was significantly and negatively correlated with MIP‐1b, IL‐9, MIG, IL‐2RA, and IP‐10 (Figure 3g ). These findings further suggest that microbially triggered host inflammatory signaling pathways or microecological imbalances may play an important role in tumor development. Smoking inducing microbiota colonized in LUSC To further assess the distribution of microbiota in LUSC, we observed a significant abundance of Staphylococcus and Acinetobacter as the predominant genera in LUSC (Figure 4a ). In contrast to LUAD, the distinction of Acinetobacter was lower abundance in tumor tissues. The NMDS analysis provided visual separation between the two types of tissues (Figure 4b ). Linear discriminant analysis effect size (LEfSe) showed that Candida parapsilosis was significantly enriched in tumor tissues while Pantoea dispersa , Streptococcus cristatus , and Mesorhizobium terrae were enriched in normal tissues (Figure 4c ). The C. parapsilosis , an opportunistic fungal pathogen, was the most prevalent systemic nosocomial infection. Some Candida species, closely associated with increased expression of proinflammatory host immunity, were the most common model to determine the host‐fungus interaction. 29 , 30 , 31 , 32 Several studies have found that fungus can shape host immunity and contribute to carcinogenesis such as esophageal, colorectal, and pancreatic cancer. 33 , 34 , 35 , 36 Furthermore, in cytokine correlation analysis, a positive correlation between IL‐7 and C. parapsilosis was found (Figure 4d ). It is well‐known that IL‐7 plays a critical role in the proliferation of T and B cells. 37 It does appear that IL‐7 could promote tumor cell proliferation in LC by regulating the BCL2 gene family and promoting cFOS and cJUN activity in NSCLC. 38 , 39 We then evaluated the microbiota on the basis of tobacco exposure histories (0–40 vs. >40 pack‐years). In terms of smoking, PCoA was plotted to evaluate the similarity in two groups (Figure 4e ). The different species, Malassezia restricta , Malassezia sympodialis , Cloacibacterium normanense , Corynebacterium xerosis , and Neisseria elongate , were all concentrated in the 0–40 pack‐years group (Figure 4f ). Collectively, our results suggested that it is possible that fungi are also involved in LUSC microbiome imbalances and are associated with immune inflammatory responses.

DISCUSSION In this study, we integrated metagenomic sequencing to characterize the microbiome based on NSCLC tissues and provide a comprehensive method by which nearly all microbiota can be accurately identified, without the need for sequence‐specific amplification. 40 Previous studies on the microbiota in the airways have primarily relied on samples obtained from bronchoalveolar lavage (BAL), bronchoscopic brushing, or sputum, 3 , 41 , 42 , 43 , 44 , 45 , 46 which might be contaminated by oral microbiota in the upper respiratory tract, which affects the analysis and judgment of lung microbes. 47 What is more, lung cancer studies have focused on genus levels. 3 , 14 , 17 , 20 , 48 In our study, we found five core genera; Pseudomonas , Corynebacterium , Acinetobacter , Streptococcus , and Microbacterium , with high relative abundance in lung tissues. However, Prevotella ( Bacteroidetes ), Streptococcus ( Firmicutes ), and Veillonella ( Firmicutes ) genera, which are frequently prevalent in the oral cavity, have repeatedly been discovered in great quantity in BAL studies. 17 Together, these findings suggest that the lung microbiota possesses unique characteristics. Although the diversity and relative richness of microbiota detected in all tumor and normal tissues were not significantly different, the relative proportion of Pseudomonas (0.0369%), Prevotella (0.0202%), and Streptococcus (0.0134%) increased significantly in tumors of NSCLC patients. This observation aligns with previous studies that have reported an enrichment of Streptococcus in tumor tissues, suggested that new insights into the interaction between lung cancer and microbes, come from the changes in lower respiratory microbes. 14 , 17 , 49 Despite the status, 96% bacteria and 4% fungi in TCGA primary tumors suggested that bacteria predominate in the tumor microbiome, and the TME is polymicrobial. 32 , 35 In our study, C. acnes was enriched in stage I. Although C. acnes is primarily well‐known as a skin microorganism, it could also become an opportunistic pathogen in other organs such as intestine, mouth, lungs and stomach. 50 , 51 , 52 , 53 Short chain fatty acids (SCFAs), which are known metabolic byproducts of C. acnes , have been linked to immune system modulation and the emergence of allergic disease, 54 , 55 and could regulate lung immune functions by regulating T cells and dendritic cell (DC) activity. 56 These studies showed C. acnes had a beneficial effect on the host. The host immune cells acquire information directly from the microbiota and the concurrent regional cytokine response. This information exchange modifies inflammatory responses and subsequently alters immune responses. 57 , 58 , 59 In our study, we observed 10 elevated cytokine levels in tumor tissues of NSCLC, with the majority being cytokines involved in proinflammatory and regulatory cytokines like IL‐8, IFN‐γ as well as IL‐17. 60 Among these cytokines, LIF as a pleiotropic cytokine, can substantially facilitate tissue protection during bacterial pneumonia, which is involved in tissue homeostasis. 61 , 62 The proinflammatory cytokines of IL‐1β, IL‐17, MIF, and TNF‐α were significantly increased in tumor represented complex immunity dysregulation and possible molecular mechanisms due to dysbiosis of the microbiome. 63 , 64 , 65 , 66 , 67 , 68 IL2RA can influence the activity of Treg cells to assist in the regulation of immunological tolerance. 69 Targeting and eliminating Treg cells through the use of CD25 antibodies have been recognized as a key mechanism for tumor inhibition and the elimination of immunosuppression. 70 Overall, our results suggest that lower airway dysbiosis in lung cancer is associated with distinct cytokine profiles and microbial compositions. The upregulation of proinflammatory cytokines and the presence of specific bacterial species highlight the intricate interplay between the host immune response, microbiota, and tumor development in the context of lung cancer. These findings contribute to our understanding of the complex mechanisms underlying lung cancer pathogenesis and provide insights for potential therapeutic interventions targeting the host–microbe interaction. Importantly, the immune system plays a crucial role in maintaining the important aspects of host‐microbe symbiosis. 71 In future studies, efforts will be directed towards developing methods for performing multiplex analyses with sorted cells as this will enable the identification of the cellular sources of different cytokines and provide deeper insights into the immune response in the context of lung cancer. However, a limitation of the study was that the sample size in the groups was small, and may have been underpowered to detect important differences among the groups. Future large‐scale animal model studies will be required to investigate the function of the lung microbiome in the emergence of lung cancer, so that the lung microbiome can be successfully used as cancer biomarkers or microbiota treatments in lung cancer patients. In conclusion, we profiled metagenomic sequencing of tumor tissues from NSCLC patients, and researchers discovered lower airway microbiome dysbiosis, which may upset the equilibrium of the immune system and cause lung inflammation. Members of Pseudomonas and Prevotella played an important role in the composition of the tumor microbial community. We also found pathogenic microbiota such as Mycobacterium paragordonae and Human gammaherpesvirus ‐4 in later stage of LUAD, may be associated with inflammation. Candida parapsilosis is also significantly enriched in tumors, suggesting proinflammatory states in heavy smoking LUSC. The observed association between the microbiome and lung cancer biology may indicate an influence of the microbiota on the development and progression of lung cancer.

Abstract Background The lung has a sophisticated microbiome, and respiratory illnesses are greatly influenced by the lung microbiota. Despite the fact that numerous studies have shown that lung cancer patients have a dysbiosis as compared to healthy people, more research is needed to explore the association between the microbiota dysbiosis and immune profile within the tumor microenvironment (TME). Methods In this study, we performed metagenomic sequencing of tumor and normal tissues from 61 non‐small cell lung cancer (NSCLC) patients and six patients with other lung diseases. In order to characterize the impact of the microbes in TME, the cytokine concentrations of 24 lung tumor and normal tissues were detected using a multiple cytokine panel. Results Our results showed that tumors had lower microbiota diversity than the paired normal tissues, and the microbiota of NSCLC was enriched in Proteobacteria , Firmicutes , and Actinobacteria . In addition, proinflammatory cytokines such as IL‐8, MIF, TNF‐ α, and so on, were significantly upregulated in tumor tissues. Conclusion We discovered a subset of bacteria linked to host inflammatory signaling pathways and, more precisely, to particular immune cells. We determined that lower airway microbiome dysbiosis may be linked to the disruption of the equilibrium of the immune system causing lung inflammation. The spread of lung cancer may be linked to specific bacteria. The lung microbiome plays a crucial role in respiratory health, and its dysbiosis has been associated with lung cancer. This study investigated the relationship between microbiota dysbiosis and immune profiles within the tumor microenvironment (TME) in non‐small cell lung cancer (NSCLC) patients. Metagenomic sequencing was performed on tumor and normal tissues from 61 NSCLC patients and six patients with other lung diseases. Cytokine concentrations were measured in 24 lung tumor and normal tissues using a multiple cytokine panel. The results showed lower microbiota diversity in tumors compared to paired normal tissues, with enrichment of Proteobacteria, Firmicutes, and Actinobacteria in NSCLC. Proinflammatory cytokines, including IL‐8, MIF, and TNF‐α, were significantly upregulated in tumor tissues. Specific bacteria were linked to host inflammatory signaling pathways and immune cells. Dysbiosis in the lower airway microbiome may disrupt the equilibrium of the immune system and contribute to lung inflammation and the spread of lung cancer. Li Y , Rao G , Zhu G , Cheng C , Yuan L , Li C , et al. Dysbiosis of lower respiratory tract microbiome are associated with proinflammatory states in non‐small cell lung cancer patients . Thorac Cancer . 2024 ; 15 ( 2 ): 111 – 121 . 10.1111/1759-7714.15166

AUTHOR CONTRIBUTIONS Z. Wang, G. Rao, L. Yuan, and J. Gao performed metagenomic sequencing and processed the data. L. Yuan, J. Gao Y, and C. Cheng performed bioinformatic analyses. J. Tang obtained patient consent and collected the samples. Y. Li assisted in participant selection, consent, clinical information, and procurement of tissues. G. Zhu performed tissue dissociations and cytokine detection. W. Li provided clinical insights. Z. Wang and Y. Li analyzed and interpreted the data. Z. Wang and Y. Li conceived the study and wrote the manuscript. All authors contributed to the article and approved the submitted version. CONFLICT OF INTEREST STATEMENT Authors Guanhua Rao, Lijuan Yuan, and Jianpeng Gao are employed by Genskey Medical Technology Co., Ltd, Beijing, China. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Supporting information

ACKNOWLEDGMENTS We are grateful to all the patients for their voluntary participation in the study. This study was supported by the National Natural Science Foundation of China (92159302 and 32170592), and the Sichuan Science and Technology Program (2023NSFSC0041, 2022NSFSC0785, 2020YFS0572, and 2020YFS0573).

CC BY

no

2024-01-16 23:42:02

Thorac Cancer. 2023 Dec 2; 15(2):111-121

oa_package/18/a5/PMC10788479.tar.gz

PMC10788481

37516011

Introduction Functional neurological disorder (FND) is a condition involving the experience of neurological (seizures, sensory and/or motor) symptoms which are clinically distinguishable from those caused by identifiable neuropathology ( APA, 2013 ; Drane et al., 2021 ). The mechanisms and aetiology underlying FND remain incompletely understood; however, there have been considerable advances in pathophysiological FND research in recent years, with several possible mechanistic processes highlighted across explanatory models, including disrupted attention, emotional processing, and interoception ( Drane et al., 2021 ; Pick et al., 2019 ). Interoception, the sense of awareness of the internal state of the body, is central to the understanding and experience of oneself ( Tsakiris, 2018 ). It is a multidimensional construct including interoceptive accuracy, insight, and sensibility ( Khalsa et al., 2018 ; Box 1 ). Models of FND have suggested that discrepancies between top-down and bottom-up processing in the brain and body play a role in the generation of altered interoception and motor or sensory disturbances in FND ( Brown & Reuber, 2016 ; Edwards et al., 2012 ; Pick et al., 2019 ; Van den Bergh et al., 2017 ). Pick et al. (2019) , for example, suggest that diminished awareness (interoception) of bodily affective responses (i.e., autonomic arousal) may be an important feature in FND, potentially contributing to impaired top-down regulation of these bodily states and thereby allowing them to exert a disproportionate and disruptive influence on awareness and cognitive/motor control. Preliminary neuroimaging data further suggest that the insula, a key brain area involved in interoception, may be structurally and/or functionally divergent and linked with alterations in interoceptive processing in FND samples ( Pick et al., 2019 ; Sojka et al., 2020 ). More specifically, individual differences in interoceptive accuracy and interoceptive trait prediction error in people with functional movement disorders (FMD) have been associated with white matter pathways originating from the insula ( Sojka et al., 2020 ). Reduced insular activation has also been seen during the processing of emotional images and facial expressions in both FMD and functional seizures (FS) ( Espay et al., 2018 ; Szaflarski et al., 2018 ), and is associated with both alexithymia ( Sojka et al., 2019 ) and symptom severity in FND ( Perez, Matin, et al., 2017 ), suggesting that insular alterations may encourage prediction errors and impair one's ability to accurately perceive bodily signals ( Sojka et al., 2020 ). Differences in dimensions of interoception have also previously been linked with a range of clinical characteristics in FND including trauma ( Pick et al., 2020 ), emotional processing differences (alexithymia: Demartini et al., 2019 ), somatoform and psychological dissociation ( Koreki et al., 2020 ; Pick et al., 2020 ), and indices of clinical severity/complexity (physical symptom burden, depression, anxiety: Koreki et al., 2020 ; Pick et al., 2020 ; Ricciardi et al., 2021 ). These findings suggests that interoception may be connected to both aetiological factors and mechanisms in FND, with the possibility that interoceptive differences may be the link between some of these factors ( Koreki et al., 2020 ). Previous studies of cardiac interoceptive accuracy in patients with FND have provided inconsistent findings. Compared to healthy controls, reduced interoceptive accuracy, as measured with the Heartbeat Tracking Task (HTT; Schandry, 1981 ), has been seen in some samples with functional motor symptoms (FMS) ( Demartini et al., 2019 ; Ricciardi et al., 2016 , 2021 ), FS ( Koreki et al., 2020 ), and mixed FND symptoms ( Williams et al., 2021 ), but not in others (FS: Jungilligens et al., 2020 ; mixed symptoms: Pick et al., 2020 ). Although Pick et al. (2020) did not find accuracy to be reduced at baseline, accuracy was impaired after the induction of a dissociative state, aligning with other findings ( Koreki et al., 2020 ). The intact baseline interoceptive accuracy observed by Pick et al. (2020) was coupled with reduced confidence ratings in the FND group, indicating a potential difference in metacognitive interoceptive insight characterised by underestimation of their performance. However, findings in the insight dimension are also variable ( Ricciardi et al., 2021 ). These inconsistencies further extend to the dimension of self-reported trait interoceptive sensibility . Compared to HCs, heightened sensibility was reported by a FS sample ( Koreki et al., 2020 ), although reduced sensibility was reported in a FMD sample ( Ricciardi et al., 2021 ), specifically a reduction in ability to recognize illness signals and predict bodily reactions. In mixed FND samples ( Pick et al., 2020 ), differences between cases and controls also suggest altered sensibility in FND in the form of a greater tendency to distract from unpleasant or uncomfortable bodily sensations as well as reduced subjective trust and safety in the body ( Pick et al., 2020 ). The discrepancies in results could be due to inconsistent measurement of interoceptive dimensions and variable control of known confounds of the HTT ( Murphy et al., 2018 ; Palmer, Ainley, & Tsakiris, 2019 ; Ring & Brener, 1996 ) including body mass index (BMI), knowledge of own heart rate, and time estimation abilities, as well as an overwhelming focus on interoceptive accuracy, with measures of interoceptive insight or sensibility less commonly included. The use of standard HTT instructions alongside pulse oximeters or worn sensors that may facilitate task performance ( Murphy et al., 2019 ) may also account for some discrepancies. Given the possibility that disrupted interoception may play a role in the development or maintenance of FND symptoms, further research is warranted to identify whether interoceptive accuracy is impaired in specific FND subgroups. Furthermore, closer examination of the role of interoceptive insight and sensibility in FND is needed to identify the most notable differences in these dimensions in FND subgroups. Given the variable control of confounding factors in previous studies, it is important to assess whether performance on the HTT in FND samples is reliably affected by common confounds, such as BMI, previous knowledge of heart rate, and time estimation abilities. Aims and hypotheses As part of a larger pilot project using multimodal research methods to examine psychobiological causes and mechanisms in two common subgroups of FND (FMS/FS), the aim of this experiment was to assess interoception in this population across three dimensions. We aimed to pilot the procedures and test the hypotheses that interoceptive accuracy and/or insight would be significantly reduced in the FMS/FS group compared to HCs ( Pick et al., 2019 ), whilst evaluating the potential influence of several possible confounds, including time estimation, possible device-related issues ( Desmedt et al., 2020 ), BMI, general cognitive functioning, and comorbid psychological and physical symptoms. Based on previous findings ( Pick et al., 2020 ), we predicted that the FMS/FS group would report significant alterations in interoceptive sensibility on two or more subscales of the Multidimensional Assessment of Interoceptive Awareness–2 (MAIA-2) compared to HCs. An additional aim was to better understand how interoception is related to a range of relevant clinical characteristics in FMS/FS. If interoceptive differences are, in fact, underlying mechanisms in FND, this would predict significant correlations between FND symptom severity and impact and interoception ( Koreki et al., 2020 ; Ricciardi et al., 2021 ). Given that alexithymia involves difficulties identifying and describing emotions, elevated alexithymia, as seen in FND ( Demartini et al., 2014 ), may be linked to differences in interoception due to an impaired processing of emotional bodily states ( Demartini et al., 2019 ; Pick et al., 2019 ). Similar difficulties have been identified in autistic spectrum disorder, suggesting that elevated autistic traits in FND may also be tied to reductions or alterations in interoception ( Gonzalez-Herrero et al., 2022 ). Associations between elevated psychological distress (depression and anxiety) and altered interoceptive accuracy and sensibility ( Demartini et al., 2019 ; Pick et al., 2020 ) are also present in FND, and these variables may reciprocally influence one another. Previous research has also made apparent the links between dissociation and interoception in FND ( Jungilligens et al., 2020 ; Koreki et al., 2020 ; Pick et al., 2020 ): dissociative experiences are common in FND and negatively correlate with, and can directly impair, interoceptive accuracy ( Pick et al., 2020 ), thus informing the prediction that there would be significant relationships between dissociation and dimensions of interoception. Exploratory correlational analyses examined associations between interoceptive dimensions and these clinically relevant variables.

Methods Participants Seventeen patients with FMS/FS and 17 healthy controls were included. The sample size was deemed appropriate given the goals of the broader pilot project in which this study was conducted. Patients with FMS/FS were recruited online via mailing lists, social media, and advertisements circulated by charitable patient support websites (FND Action, FND Hope UK). Healthy controls were recruited through local community websites (South London Facebook and Gumtree). No participants included in this study overlapped with the samples reported in earlier studies from this group ( Pick et al., 2020 ). The study was approved by the King's College London Health Faculties High-Risk Research Ethics Sub-Committee (ref: HR/DP-21/22–28714) and conforms to the World Medical Association Declaration of Helsinki. Data collection took place between July and October 2022. Participants were between the ages of 18–65 years old, with normal or corrected eyesight and fluency in English. Participants in the FMS/FS group were required to have a primary diagnosis of FND (DSM-5) ( APA, 2013 ), with FMS and/or FS as their primary complaint, confirmed with medical documentation checked by the principal investigator (SP) and in some cases a Consultant Neurologist (BS). The exclusion criteria were: major comorbid cardiovascular or neurological disorder, active severe psychiatric disturbance, or physical symptoms/disability that would confound the findings or impair task performance, taking medications affecting cardiovascular functioning (e.g., beta-blockers) or attention and concentration (i.e., daily/daytime opioids, barbiturates), and pacemakers. Healthy control participants were excluded if they disclosed lifetime functional neurological symptoms or reported the presence of an active major physical or mental health disorder. Procedure After written, informed consent was obtained, a comprehensive screening interview was conducted remotely, to obtain data regarding sociodemographic characteristics and medical history. Participants were asked if they had any prior knowledge of their own heart rate (e.g., from a wearable device) and for their height and weight so BMI could be calculated. A tailored structured clinical interview (SCID-5-RV) ( First, Williams, Karg, & Spitzer, 2015 ) was administered remotely by SP to assess the possible presence of mental health disorders relevant to the eligibility criteria (e.g., active psychosis, severe affective disorder, substance/alcohol dependence). Eligible participants were sent a set of self-report questionnaires to complete online via Qualtrics ( www.qualtrics.com ) within 48 h prior to attending the laboratory session. The laboratory session took place in a quiet testing room at the Institute of Psychiatry, Psychology and Neuroscience. Within this session, participants completed the HTT ( Schandry, 1981 ) and the TET, alongside other experimental and neurocognitive tasks (reported elsewhere). Upon completion, participants were compensated with a £50 shopping voucher. Measures The Heartbeat Tracking Task (HTT) ( Schandry, 1981 ) was included as a measure of interoceptive accuracy and insight, administered with E-Prime experimental software (Psychology Software Tools, Inc.). As recommended to control for device-related confounds ( Murphy et al., 2019 ), electrocardiography (ECG) was used to record heartbeats throughout the task. Participants were seated at a table in front of a computer and asked to attend to and count their own heartbeats during three randomised intervals (25, 35, and 45s). Adapted instructions were used, specifically asking participants to only count the heartbeats they could feel ( Desmedt et al., 2020 ). Participants were also explicitly asked not to count seconds or take their own pulse, or use any device to measure their heartbeats. Thirty second rest periods between each of the heartbeat counting trials were provided. The start and end of each trial were indicated on screen. Immediately after each trial, participants were asked to manually report the number of perceived heartbeats, followed by rating their confidence in their answer (0–10, low-high certainty). Participants did not receive any feedback on task performance and were unaware of the duration of the trials. A practice trial was completed prior to starting the experimental trials. The Time Estimation Task (TET) was used as a control task. In the TET, participants were asked to count seconds during three randomised intervals (23, 37, 42s), separated by rest periods of 10 s. The start and end of each trial was indicated on screen. Immediately after each trial, participants were asked to report manually the number of seconds they had counted and then to rate their confidence (0–10, low-high certainty). Participants did not receive any feedback on task performance. The Multidimensional Assessment of Interoceptive Awareness – second edition (MAIA-2) ( Mehling et al., 2018 ) is a 37-item self-report questionnaire assessing trait-level abilities relating to interoceptive sensibility and recognition of bodily experiences across eight dimensions: Noticing (4 items; α = 0.74), Not-Distracting (6 items; α = 0.89), Not-Worrying (5 items; α = 0.68), Attention Regulation (7 items; α = 0.89), Emotional Awareness (5 items; α = 0.88), Self-Regulation (4 items; α = 0.78), Body Listening (3 items; α = 0.73), Trusting (3 items; α = 0.82). Each question is scored on a Likert-scale from 0 (“never”) to 5 (“always”). A bespoke Functional Neurological Symptoms Questionnaire was designed for this study to assess the presence, frequency, severity, and impact of FND symptoms (Supplementary File 1). Participants are asked to report the presence/absence (Yes/No), frequency (constant/daily/weekly/less than weekly), severity (1 = “Symptom not present” to 7 = “Very severe”), and impact (1 = “No impact at all” to 7 = “Very severe impact”) of FND symptoms within the past week. Analysis All data were analysed using R ( Version 4.1.0, 2021 ). Missing data on the self-report measures were addressed as follows: for participants missing 20% or less of a given scale (or subscale), the missing item/s were imputed with the mean of that individual's scores for the scale (or subscale). If more than 20% of the data for one scale or subscale was missing, the participant was excluded from that analysis. This resulted in 0–15% of participants being excluded from the MAIA-2 subscales. Due to technical issues, two participants were missing the TET (1 FMS/FS, 1 control) and three participants were missing the HTT (1 FMS/FS, 2 controls). Normality was evaluated with Shapiro-Wilk test and QQ-plots for each variable. Categorical variables were analysed with Fisher's exact tests and continuous variables were analysed with independent samples Welch's t-tests, with Hedges' g ( Hedges & Olkin, 1985 ) as the effect size. To calculate interoceptive accuracy, the proportional discrepancy between the actual and perceived number of heartbeats was calculated using the following formula: 1/3 ∑ [(1 − (|actual heartbeats – perceived heartbeats|/actual heartbeats). This resulted in an accuracy error index with values closer to 1 reflecting a lower discrepancy and superior interoceptive accuracy ( Schandry, 1981 ). The same formula was used for the TET: 1/3 ∑ [(1 − (|actual seconds – perceived seconds|/actual seconds). To examine interoceptive insight, we used Pearson's correlations to assess the degree of association between HTT accuracy and confidence ratings. Bonferroni corrections were used in the case of multiple tests conducted on related variables (e.g., subscales of questionnaires, dependent variables in the behavioural tasks). Exploratory Pearson's or Spearman's correlations were computed to assess associations between interoceptive dimensions and clinical characteristics in the FMS/FS group.

Results Participant characteristics The characteristics of the sample are detailed in Table 1 . The groups were comparable in age, gender, BMI, and intellectual functioning. The FMS/FS group reported additional functional symptoms including dizziness, cognitive difficulties, sensory, and speech/swallowing difficulties. The FMS/FS group had a significantly higher resting heart rate, and significantly more participants in the FMS/FS group disclosed previous knowledge of their heart rate, were more likely to be taking medication, and were experiencing a comorbid mental or physical health disorder. Details of medications, physical health diagnoses and mental health diagnoses are reported in Supplementary Table 1 . Interoceptive accuracy and insight The two groups did not differ in accuracy or confidence ratings on the HTT (all negligible effect sizes, see Table 2 ). These results held when the analyses were re-run excluding cases where data was missing for the HTT (FMS/FS: n = 16, HC: n = 14; all p -values >.85; Supplementary Table 2 ). There was a strong positive relationship between HTT accuracy and confidence ratings (interoceptive insight) in the control group but not in the FMS/FS group ( Table 3 ), although the difference between coefficients was a non-significant trend ( z = 1.59, p = .068). Self-reported interoceptive sensibility Compared to controls, the FMS/FS group displayed significantly lower scores on the “Not-Distracting” (e.g., ‘I distract myself from sensations of discomfort’, ‘I try to ignore pain’ – reverse scored) and “Trusting” (e.g., ‘I am at home in my body’, ‘I trust my body sensations’) subscales of the MAIA-2 ( Table 2 ), both withstanding a Bonferroni-adjusted alpha and with large effect sizes. There were no significant between-group differences on the other MAIA-2 subscales. Exploratory analyses Table 3 presents the statistical values for the significant exploratory analyses described below. Non-significant findings are detailed in Supplementary Tables 4 and 6 Examining the influence of possible confounding variables The two groups did not differ in accuracy or confidence ratings on the TET (all negligible effect sizes, Table 2 ). These results held when the analyses were re-run excluding cases where data was missing for the TET (FMS/FS: n = 16, HC: n = 14; all p -values >.83; Supplementary Table 2 ). No association was seen between TET accuracy and confidence in either group ( Supplementary Table 4 ). There was no association in either group between HTT and TET accuracy or HTT and TET confidence ratings ( Supplementary Table 4 ). We ran correlations between key interoceptive outcomes (HTT accuracy and confidence, MAIA-2 Trusting and Not-Distracting) and a range of potential confounds, including: BMI, PHQ-9 (depression), PHQ-15 (physical symptoms), GAD-7 (anxiety), age, gender, intellectual functioning, self-reported previous knowledge of heart rate, baseline heart rate, medication, current physical health diagnoses, and current mental health diagnoses. There were no significant correlations ( Supplementary Table 4 ) except for a strong, significant association between gender and HTT accuracy in HCs, wherein female participants displayed greater HTT accuracy ( Table 3 ). Correlations among interoceptive dimensions There was a strong, significant relationship between HTT confidence ratings and the “Self-Regulation” subscale of the MAIA-2 in the FMS/FS group ( Table 3 ), withstanding a Bonferroni correction (adjusted alpha = .006). No other significant associations were seen between interoceptive accuracy or confidence and MAIA-2 scores in either group ( Supplementary Table 4 ). Correlations between interoception and relevant clinical variables In the FMS/FS group, there were significant correlations between self-reported FND symptom severity and HTT confidence scores, and FND symptom impact and HTT confidence scores ( Table 3 ), both with large effect sizes and withstanding Bonferroni corrections. There were no other significant associations between interoceptive accuracy, confidence, or sensibility (MAIA-2) and any other clinical/background variables in the FMS/FS group (SDQ-20, TAS-20, AQ, MDI [ Supplementary Tables 5 and 6 ]).

Discussion This study aimed to elucidate the possible role of interoceptive processing in FMS/FS, testing the hypotheses that interoceptive accuracy and insight would be reduced, and interoceptive sensibility would be significantly altered in FMS/FS compared to HCs. A further aim was to explore how interoception may be related to a range of relevant aetiological factors and clinical characteristics in FMS/FS. These results present the possibility that there may be a separation between interoceptive accuracy and confidence in FMS/FS, suggesting a potential metacognitive difference characterised by reduced certainty/confidence in one's own interoceptive perceptions. Furthermore, a reduced subjective sense of trust within the body and a tendency towards distracting from uncomfortable bodily sensations seen in FMS/FS may also be linked to a reduced confidence in self-evaluations of bodily experience, possibly reinforcing FND symptoms. There was no evidence of impaired interoceptive accuracy in the FMS/FS group compared to controls, aligning with previous work by Pick et al. (2020) and Jungilligens et al. (2020) . Whilst our sample size limited the statistical power to detect significant between-group differences, the effect sizes indicated that there was no group effect on HTT accuracy. This is contrary to other studies reporting reduced interoceptive accuracy in more specific FND subgroups, including those with FMS ( Demartini et al., 2019 ; Ricciardi et al., 2016 , 2021 ) and FS ( Koreki et al., 2020 ), and does not support the proposal that altered interoception is a core feature in FND. Nevertheless, this study examined only cardiac interoception, at rest. It remains a possibility that FND is associated with impairments of interoception in other bodily domains, or with state-dependent interoceptive differences, such as during dissociative states or acute affective arousal ( Pick et al., 2019 , 2020 ). The differential results across studies could also be due to variations in samples regarding symptom types, the presence of comorbid mental health diagnoses, modest sample sizes, and inconsistent measurement and inclusion of potential confounds of heartbeat tracking tasks. The current study did not reveal generally reduced interoceptive confidence ratings in the FMS/FS group. However, while there was a strong, positive relationship between HTT accuracy and confidence in controls suggestive of adequate interoceptive insight, this association was not seen in those with FMS/FS. This potential disconnect between actual performance and subjective confidence on the HTT in the FMS/FS group suggests that FMS/FS may be associated with less accurate self-evaluations of interoceptive performance (i.e., reduced interoceptive insight). Similarly, this sample displayed discrepancies between objective and subjective neurocognitive functioning, including tests of attention and executive functions, pointing towards possible generalised deficits in metacognition in this sample ( Pick et al., under review , Journal of Clinical and Experimental Neuropsychology). This aligns with other research proposing metacognitive deficits in FND, specifically impaired metacognition in functional cognitive disorders ( Bhome et al., 2022 ; Larner, 2021 ; Teodoro et al., 2023 ). Further research is required to better understand local versus global metacognitive abilities in these disorders, and the ways in which impaired metacognition may contribute to FND symptoms. Though a higher proportion of this FMS/FS group reported previous knowledge of their heart rate, a higher resting heart rate, current medication, and physical and mental health diagnoses, these variables, alongside BMI, showed no significant relationship with any of the interoceptive constructs tested here, suggesting that these potential confounds did not meaningfully affect our results. Gender was also nonsignificant in relation to the interoceptive constructs tested in the FMS/FS group, although there was a significant association between gender and HTT accuracy in controls, wherein female participants displayed greater accuracy. This is consistent with some previous research revealing a female bias towards interoceptive awareness, potentially due to elevated cognitive empathy and emotion recognition ( Grabauskaitė et al., 2017 ). In the present study, the two participant groups did not differ, with negligible effect sizes, in TET accuracy or TET confidence ratings. Unlike some previous studies using the HTT alongside the TET ( Palmer, Ainley, & Tsakiris, 2019 ; Ring & Brener, 1996 ; Ring et al., 2015 ), there was no association in either group between HTT and TET accuracy or confidence, suggesting that performance on the HTT was unlikely to have been influenced by time estimation abilities. Altered self-reported interoceptive sensibility was seen in this FMS/FS sample across two subscales of the MAIA-2, both with large effect sizes. These differences in aspects of interoceptive sensibility paired with intact accuracy and confidence point towards the possibility that there is a separation between trait and state measures of interoception in FMS/FS. Individuals with FMS/FS exhibited lower scores on the “Not-Distracting” subscale, indicating an inclination towards ignoring or distracting from uncomfortable or unpleasant bodily sensations, and the “Trusting” subscale, suggesting that they feel less at home in their body, not trusting their bodily sensations, compared to controls ( Mehling et al., 2018 ), which aligns with some previous results on interoceptive sensibility in FND ( Pick et al., 2020 ; Ricciardi et al., 2021 ). Lower levels of trusting the body may be linked to the reduced interoceptive insight seen in this study, suggesting the possibility of a general reduction in confidence and trust in one's self-evaluations of bodily experiences, which may be present at both local and global levels. However, the finding that individuals with FMS/FS are more likely to distract from uncomfortable or unpleasant bodily sensations is contrary to some models of FND ( Edwards et al., 2012 ; Van den Bergh et al., 2017 ). The tendencies towards distraction and not trusting the body as seen in this sample may be a secondary consequence of living with a chronic physical illness, but equally could be what reinforces symptoms or makes individuals more susceptible to them. These possibilities are not mutually exclusive and longitudinal studies would be needed to elucidate the direction of these relationships. In future research, the inclusion of clinical control groups, such as individuals with other chronic physical health disorders, will help to establish the specificity of these results. Exploratory correlations revealed that the “Self-Regulation” subscale (MAIA-2) was strongly positively correlated with HTT confidence in the FMS/FS group, whereas self-reported FND symptom severity and impact were strongly negatively correlated with HTT confidence. Self-regulation requires bringing awareness to the body, using breathing or focusing in on the body to reduce tension or calm the mind. These results imply that those individuals with FMS/FS who were better able to self-regulate were those with higher levels of subjective interoceptive confidence, while individuals experiencing more severe and impactful FND symptoms were those with lower levels of subjective interoceptive confidence. Given the correlational nature of these findings, it is not possible to make inferences regarding the direction of these relationships; it is possible that reduced interoceptive insight could be a predisposing factor for developing more severe FND symptoms, or it may be a direct result of living with severe FND symptoms. These results have potential implications for treatment, suggesting that interventions targeting aspects of attention and bodily awareness may be particularly beneficial for this population. Therapeutic approaches that encourage a sense of trust and confidence within the body alongside a focus on feelings and interoceptive stimuli, rather than trying to distract from them, could provide benefits in FND. Specific possibilities include body scanning techniques ( Gibson, 2019 ), Somatic Experiencing ( Payne et al., 2015 ), attention training ( Wells et al., 1997 ), and Mindfulness Oriented Meditation ( D'Antoni et al., 2022 ). Strengths and limitations Given the aims of this pilot study, the HTT was selected as a feasible, well-established, and widely used measure of interoceptive accuracy and insight ( Garfinkel et al., 2015 ). However, the reliability and validity of the task has been questioned, with suggestions that task performance can be impacted by prior beliefs about one's heart rate or estimating the amount of time that has passed, rather than an accurate perception of heartbeats ( Desmedt et al., 2020 ; Murphy et al., 2019 ). The use of the HTT with adapted instructions, measurement of self-report BMI and knowledge of heart rate, heart rate measurement via ECG, and inclusion of the TET control task are key strengths of this study that help to minimise the possible influence of estimation abilities other known confounds of the HTT in this study. Nevertheless, future research should aim to include alternative tasks that are not susceptible to these possible confounds. Whilst the results are limited due to the small sample size and modest statistical power, we have presented and considered effect sizes throughout to demonstrate the presence of meaningful differences. The cross-sectional nature of this experiment does not allow conclusions to be drawn regarding the direction of the relationship between FMS/FS and the interoceptive differences observed. The inclusion of an FND sample experiencing primary FMS/FS alongside other functional neurological symptoms, though a strength in terms of generalizability, is a limitation given the possibility that interoceptive deficits may manifest differently depending on symptom types. Future research should aim to examine interoception in the broader FND population alongside specific symptom subtypes. It is possible that the anxiety measure included in this study did not assess somatic symptoms of anxiety and could be the reason for the lack of relationship between interoceptive measures and anxiety. Measures more likely to capture somatic anxiety symptoms should be considered in future. It will be particularly useful in future studies to include clinical comparison groups such as those with relevant mental health disorders (depression, anxiety, PTSD) or other chronic physical health disorders such as neurological diseases. Future research should also aim to include a larger sample as well as objectively measure relevant variables (e.g., BMI). Conclusions Individuals with FMS/FS may not exhibit consistently reduced interoceptive accuracy, but may experience reduced interoceptive insight alongside altered interoceptive sensibility (“Not-Distracting”, Trusting”). These results provide further evidence that there may be a separation between trait and state interoception in FMS/FS. Our future work will explore the possibility that interoceptive differences in FND may vary in specific FND subgroups, measuring these interoceptive domains with additional paradigms, in larger samples, compared to both healthy and clinical controls. Further research should aim to test the potential benefits of interventions aimed at bodily-focused attention or metacognition in FND.

Conclusions Individuals with FMS/FS may not exhibit consistently reduced interoceptive accuracy, but may experience reduced interoceptive insight alongside altered interoceptive sensibility (“Not-Distracting”, Trusting”). These results provide further evidence that there may be a separation between trait and state interoception in FMS/FS. Our future work will explore the possibility that interoceptive differences in FND may vary in specific FND subgroups, measuring these interoceptive domains with additional paradigms, in larger samples, compared to both healthy and clinical controls. Further research should aim to test the potential benefits of interventions aimed at bodily-focused attention or metacognition in FND.

Altered interoception may be a pathophysiological mechanism in functional neurological disorder (FND). However, findings have been inconsistent across interoceptive dimensions in FND including functional motor symptoms (FMS) and seizures (FS). Here, individuals with FMS/FS (n = 17) and healthy controls (HC, n = 17) completed measures of interoceptive accuracy and insight (adapted heartbeat tracking task [HTT] with confidence ratings), a time estimation control task (TET) and the Multidimensional Assessment of Interoceptive Awareness–2 (MAIA-2) to assess interoceptive sensibility. The groups did not differ in interoceptive accuracy ( p = 1.00, g = 0.00) or confidence ( p = .99, g = 0.004), although the FMS/FS group displayed lower scores on the “Not-Distracting” ( p < .001, g = 1.42) and “Trusting” ( p = .005, g = 1.17) MAIA-2 subscales, relative to HCs. The groups did not differ in TET performance ( p = .82, g = 0.08). There was a positive relationship between HTT accuracy and confidence (insight) in HCs ( r = .61, p = .016) but not in FMS/FS ( r = 0.11, p = .69). HTT confidence was positively correlated with MAIA-2 “Self-Regulation” ( r = 0.77, p = .002) and negatively correlated with FND symptom severity ( r = −0.84, p < .001) and impact ( r = −0.86, p < .001) in FMS/FS. Impaired interoceptive accuracy may not be a core feature in FMS/FS, but reduced insight and altered sensibility may be relevant. Reduced certainty in self-evaluations of bodily experiences may contribute to the pathogenesis of FND symptoms. Highlights • Intact interoceptive accuracy in functional motor symptoms/seizures (FMS/FS). • Potentially reduced interoceptive insight in FMS/FS versus healthy controls (HC). • Lower levels of “Trusting” and “Not-Distracting” in FMS/FS compared to HC. • Elevated “Self-regulation” positively related to interoceptive confidence in FMS/FS. • Elevated symptom severity/impact negatively related to interoceptive confidence. Keywords

Source of funding The study was supported by a Medical Research Council Career Development Award to SP [MR/V032771/1]. This paper also represents independent research part-funded by the National Institute for Health and Care Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London . The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. CRediT authorship contribution statement L.S. Merritt Millman: Data curation, Formal analysis, Writing – original draft, Writing – review & editing. Eleanor Short: Data curation. Biba Stanton: Methodology, Supervision, Writing – review & editing. Joel S. Winston: Methodology, Supervision, Writing – review & editing. Timothy R. Nicholson: Methodology, Supervision, Writing – review & editing. Mitul A. Mehta: Methodology, Supervision, Writing – review & editing. Antje A.T.S. Reinders: Methodology, Supervision, Writing – review & editing. Mark J. Edwards: Methodology, Supervision, Writing – review & editing. Laura H. Goldstein: Methodology, Supervision, Writing – review & editing. Anthony S. David: Methodology, Supervision, Writing – review & editing. Matthew Hotopf: Methodology, Supervision, Writing – review & editing, Funding acquisition, Resources. Trudie Chalder: Methodology, Supervision, Resources, Funding acquisition, Writing - review & editing. Susannah Pick: Funding acquisition, Conceptualization, Methodology, Software, Investigation, Data curation, Resources, Validation, Supervision, Writing – review & editing. Declaration of competing interest The authors declare no conflict of interest.

Supplementary data The following is the Supplementary data to this article: Data availability Data will be made available on request. Acknowledgements Thank you to our FND Patient and Carer Advisory Panel, all participants, FND Hope UK and FND Action for supporting the project. Thanks also to Emily Ward and Yiqing Sun for their contributions to data processing.

CC BY

no

2024-01-16 23:42:02

Behav Res Ther. 2023 Sep; 168:104379

oa_package/44/5d/PMC10788481.tar.gz

PMC10788482

38101148

Introduction Over three years since the first COVID-19 vaccine was approved, many countries still have sub-optimal vaccination rates despite holding large amounts of vaccines. Some are even destroying expired vaccine stocks because of low demand [1] . They have sought to increase vaccine uptake using a range of measures. Broadly categorized, some seek to compel or encourage uptake, for example with vaccine mandates or monetary incentives, respectively. Others aim to increase knowledge through public health advice campaigns or overcome barriers by enhancing the accessibility of vaccination facilities [2] . However, there is still little evidence about whether and to what extent these policies are effective, particularly in countries where a large share of the population remains unvaccinated. There is some evidence from randomized control trials on the effectiveness of targeted interventions. Small monetary incentives in Sweden [3] have been found effective as have nudges such as reminders and public health messages in a range of European countries, New Zealand and the US [ 4 , 5 ]. Government-mandates on vaccination certificates have been found to increase uptake by, typically, 5 to 10 percentage points in high-income countries with high vaccination rates [6] . However, these mandates may also generate a political backlash and raise ethical objections from those who see them as restricting personal freedoms [7] . Vaccine lotteries, in which those agreeing to be vaccinated have a chance of winning a reward, have had more modest results in those US states that have implemented them [ 8 , 9 ]. Finally, mobile vaccination units have been also implemented across the US and Europe with the objective of bringing vaccination services closer to the target population [10] , [11] , [12] . Mobile vaccination units have been shown to increase vaccination rates in the UK by 23 % [13] and in Switzerland by more than threefold [14] . The authors suggest that their results may be attributed to several factors. These include easier access to vaccination [13] , reduced administrative barriers [14] , or the enthusiasm generated by a “vaccination event” [14] . However, a major limitation of these prior studies is that they focused on high-income countries, with high vaccination rates and at an early stage of the vaccination process [ 8 , [3] , [4] , [5] , 14 , 9 , 13 ]. It is thus uncertain how effective these programs would be where a majority of the population has persistently sub-optimal levels of vaccine uptake. This scenario is particularly relevant in most low- and middle-income countries (LMICs) where COVID-19 vaccine uptake has remained sub-optimal [15] . Community-based interventions have previously played an important role in outbreak control in LMICs, with recent examples including mpox and Ebola. These interventions may include community surveillance, community education and community vaccination programs, among others [16] . Drawing from these experiences, community-based interventions have emerged as a means to boost COVID-19 vaccination in LMICs. As an example, an initiative employing community champions (including people previously vaccinated and local leaders) significantly increased COVID-19 vaccination rates in low-uptake regions of Tanzania, rising from 10 % to 94 % [17] . However, generalising from such studies is difficult given the importance of context. A community-based intervention may operate differently depending on factors such as geography, healthcare system organisation, political institutions, social norms, etc. The closest study to ours in LMICs is the one conducted by Abdullah et al. [18] in Pakistan. They evaluated the effectiveness of an intervention involving mobile vaccination units and an awareness campaign led by community leaders. This achieved a 17 % improvement in vaccination rates, although confined to only one of three treated areas. In the remaining areas, increased willingness to get vaccinated did not translate into higher uptake. The researchers attributed this to limited access in remote settlements, with increased vaccination units insufficient to overcome this issue. In our study, we examine the effectiveness of a community-based intervention, led by the Ministry of Health and with support from the 10.13039/100004423 World Health Organization at regional, hub and country levels and UNICEF, carried out in North Macedonia in March-April 2022, a country with a sub-optimal uptake of COVID-19 vaccination; only 45 % of the population had been vaccinated by the beginning of the intervention. 1 The intervention involved sending a mobile vaccination and public health advice caravan to different locations. Our study provides evidence on the effectiveness of a community-based intervention in an understudied context, North Macedonia, an upper middle-income country with sub-optimal vaccine uptake. This situation mirrors that of most of its neighbouring countries of the Balkan region [ 19 , 20 ]. Consequently, our findings can provide valuable insights for the development of vaccination policies within this region.

Methods Data We use data on daily vaccines administered per municipality for the 80 municipalities of North Macedonia during the period from 1st March to 17th April. We include any vaccination administered in the municipality, either at the caravan or in any healthcare facility, given our need to capture any lagged effects attributable to the vaccine promotion activities. 2 We then observe each of the treated (i.e. visited by the caravan) municipalities up to an average of three weeks after the COVID-19 caravan visit. 3 WHO Europe and its partners provided data on the number of vaccines administered per municipality per day, and municipality population (based on North Macedonia Population Census 2021). From this, we calculate vaccine rates as the daily number of administered vaccines per 100,000 inhabitants per municipality. We also analyse data on the cost of the intervention from both the vaccine promotion activities and the administration of the vaccine itself. Empirical strategy We exploit the staggered implementation of the COVID-19 vaccine caravan by comparing the evolution of vaccine rates among those municipalities that received a visit of the caravan vs those that did not in a series of difference-in-difference (DiD) models. In total, 22 municipalities received the caravan and 58 did not. The outcome variables of all our models are daily vaccine rates per 100,000 inhabitants measured at the municipality level. All the details (including equations) of the DiD models are explained in Appendix C. First, we utilize a DiD model in an event study-like specification to study the effect of the intervention relative to the time of the caravan visit (See model 1 of Appendix C for a full specification of the model). In this model we test for the presence of pre-treatment parallel trends, a key assumption in the difference-in-difference model as it is necessary to show that there were no differences in trends in treated and control municipalities before the intervention. For this to be true the coefficients prior to the intervention should not be statistically significant from zero. Coefficients after the day of the intervention measure the effect of the caravan each day after the intervention, up to 3 weeks after the intervention. In this model 1 all estimates are estimated with respect to the day prior to the intervention (which serves as the baseline in the model). Second, to study the dynamics of the effect over time further and avoid setting an arbitrary day as a baseline for our estimates, we estimate another DiD model (see model 2 in Appendix C) measuring the effect with respect to the full period before the caravan visit, not only with respect to the day before (as it was in model 1). 4 Finally, we calculate the average treatment effect for the full post-treatment period with a two-way fixed effects (TWFE) model (see model 3 in Appendix C). This model measures the average treatment effect on daily vaccine rates during the three weeks after the intervention. Recent literature has shown how analysing a staggered intervention with a canonical TWFE model may be biased due to the use of early treated units as controls [ 22 , 23 ]. We perform the Goodman-Bacon decomposition to assess which comparisons have the most weight in our estimates and show that only 2.3 % of our comparisons used early treated municipalities as controls (Table A2 in Appendix A). This suggests that the canonical two-way fixed effects is adequate in our context. Still, in the robustness check in Section 3.3 we also carry out the Sant'Anna and Zhao [24] estimator, which uses only not-yet treated municipalities as controls and our results remain unchanged

Results Descriptive statistics Since the intervention was not randomly implemented, there are some differences between treated and control municipalities (Table A3 in Appendix A). Treated municipalities have a larger and younger population and a higher share of the population are foreign-born. In contrast, they have similar levels of education and unemployment. Still, it is important to note that the main assumption under the difference-in-difference design is not that treated and control units must be similar in all characteristics but rather that they should follow a parallel trend in the outcome variable in the absence of the treatment, and therefore the trend in vaccine rates should not be related with the caravan visit. We formally test for this assumption in Section 4.2 . Model 1 finds no significant coefficients before the intervention, which indicates that trends in vaccination rates were similar in treated and control municipalities at that time. Before the intervention, there was already a downward trend in daily vaccination rates for both treated and control municipalities (ture 2-A). However, we see a large jump in vaccination rates on the day of the caravan visit for the treated municipalities. In Fig. 2 -B we show weekly vaccination rates to avoid weekend fluctuations when almost no vaccine was administered and the pattern looks very similar. Main results Fig. 3 a reports the coefficient of the event study-like specification of model 1. Looking at the coefficients prior to the caravan visit we can see that the model complies with the parallel trends assumption as they are close to zero and not significant. Specifically, this shows that there are no statistically significant differences in trends prior to the intervention in treated and control municipalities. Additionally, there is a large jump in the vaccination rate of around 70 per 100,000 inhabitants on the day of the visits, a 318 % increase with respect to the pre-intervention average, suggesting a large and statistically significant immediate impact of the caravan on the day of the visit. While the increase on the day of the visit is intuitive, and indeed if it had not been present it would have raised questions about the data, there seem to be persistent benefits for daily vaccination rates two weeks or more after the caravan visit. Importantly, both the large effect on the day of the visit and, crucially, the persisting effects are also seen in model 2 ( Fig. 3 b), where we compare the effect on vaccination rate with respect to the full pre-intervention period, and not only with respect to the day before the intervention. In Table A4 of Appendix A, we report the results from the TWFE model 3. We estimate an average treatment effect on daily vaccination rates of 7.7 vaccines per 100,000 inhabitants for an average period of 3 weeks after the caravan visit. This corresponds to a 34.8 % increase with respect to pre-intervention vaccine rates. Heterogeneity analysis We further carried out a heterogeneity analysis to examine whether the effect of the intervention was different according to observable municipality characteristics (e.g. population size). Specifically, we stratify the sample of municipalities based on the median value of the following characteristics (based on the North Macedonia Population Census 2021): total population, share of population aged 60 or older, share of foreign-born population, share of population with tertiary education and unemployment rate. We found no significantly different effects of the caravan by any of the characteristics examined (see Figure A2 in Appendix A). This suggests that the effectiveness of the COVID-19 mobile vaccination caravan was independent of the observable characteristics of the municipality. Robustness checks We performed the following robustness checks (Table A5 in Appendix A): i) we perform the doubly robust Callaway and Sant Anna (2020) estimation using only never-treated and not-yet treated municipalities as control municipalities. ii) we include population weights in the regression to give more weight to the results coming from larger municipalities, iii) we grouped data into weekly vaccination rates (per 1000 inhabitants) to avoid any day-specific fluctuations, and iv) we used weekly vaccination rate data jointly with population weights. Results from these robustness checks continue to show a significant increase in vaccination rates of between 24.1 % to 39.9 %, depending on the model. Cost-effectiveness We carried out a basic calculation of the cost per additional vaccination achieved by the intervention. Fig. 4 reports the main results (See Appendix D for detailed calculations). Our main estimate provides a cost-effectiveness estimate of the caravan of US$ 25.4 per additional vaccination, under our main scenario where we include all additional vaccinations estimated to be induced by the caravan up to 3 weeks after the visit, derived from the TWFE model, and only the cost of the vaccine promotion activities. As a benchmark, this is a cost of around half of that in vaccine lotteries in the US (US$ 55–68 per vaccination), which is, to our knowledge, the only comparable cost-effectiveness estimates of population-level interventions to promote COVID-19 vaccination available in previous literature. Systematic reviews that include interventions to encourage influenza vaccination [25] , infant vaccination in low income countries [26] , or child vaccination in the US (Hong et al. 2021) also report higher average cost-effectiveness estimates, as shown in Fig. 4. 5 Even if we included the vaccine administration costs in our estimates, the cost-effectiveness would be around the same as that of the vaccine lotteries (US$ 57.6 per additional vaccine). It should be noted that if we only took into account the effect on vaccinations on the day of the caravan visit would have made the intervention to appear much more expensive (US$ 60.5 per additional vaccine). The intervention would look even more expensive if only vaccines administered within the caravan had been taken into account (US$ 168.8 per additional vaccine). This highlights the importance of implementing rigorous evaluations, by including all extra vaccinations induced by the intervention after the caravan visit (both inside the caravan and in any healthcare centre). Importantly, our cost-effectiveness estimates should be taken as a lower bound since other potential benefits are not taken into account. Among these, we could expect decreases in COVID-19 cases and hospitalizations derived both from the increase in vaccination and the dissemination of other preventive behaviours.

Discussion We describe the effectiveness of the North Macedonia COVID-19 caravan, a community-based intervention that involved sending mobile vaccination units to different locations to increase vaccination rates. Results from our difference-in-difference analysis show that the mobile vaccination caravan had a persisting benefit by increasing vaccination rates by 35 % during the 3 weeks after the caravan visit. This implies a cost of US$ 25.4 per additional vaccination. As with all natural experiment designs, our study has several limitations. First, we tested our analysis for ‘as-if’ randomisation across intervention and control municipalities. Although we found that they were not fully balanced on covariates, they did follow parallel trends, suggesting that areas of imbalance were not major drivers of vaccine trends and validating the main assumption of the difference-in-difference model. Second, we could not disaggregate individual recipients of vaccines to identify those who were fully vaccinated and those who were not as this information was unavailable. That said, we do know that this region has high rates of no- or incomplete-vaccination status. Third, we observed a spike in vaccinations on the day of the caravan, as well as an enduring impact over time. While we cannot fully disentangle the mechanisms underlying this association, a recent systematic review has shown how a wide range of “nudge” interventions can increase vaccine uptake although their impact is highly context-dependent [27] . In this case, increased uptake after the visit could plausibly be explained by i) saliency effect – through promotional activities in the lead-up to the caravan by community leaders and international partners, which may have influenced social norms, and ii) dissemination effect – arising from the diffusion of public health advice from word-of-mouth from family, friends and other peer networks. Our study corroborates evidence from prior studies of mobile units conducted in other settings. One, in the UK, produced results similar in magnitude (23 % increase in vaccination) [13] , and another in Switzerland showed a very large increase of more than threefold in vaccination [14] . In Pakistan, a LMIC, a similar intervention increased vaccination rates by 17 % [18] . Our analysis validates the effectiveness of these measures, including their cost-effectiveness, in a higher middle-income country with a vaccine-hesitant environment. Arguably the most important finding in our study was the persisting effect of the caravan on vaccine uptake. When considering the vaccine uptake solely attributable to the day of the caravan visit, our cost-effectiveness estimates indicated a cost of US$ 60.5 per additional vaccine, increasing up to US$ 168.80 if we only included vaccine administered within the caravan. However, when we included the enduring effect observed in the three weeks following the visit, including vaccines obtained both within the caravan and at other healthcare facility, the cost-effectiveness significantly improved to US$ 25.40 per additional vaccine. This suggests that the promotion activities may have played an important role in the overall effectiveness of the vaccine caravan. Additionally, it underscores the importance of considering lagged effects in community-based interventions, even when the intervention itself has a short duration. Including such temporal effects can have a substantial impact on the overall estimated effectiveness of the intervention.

Conclusions Taken together, our results show that mobile vaccination units can be an effective tool to increase COVID-19 vaccination rates, even in the context of persistent suboptimal vaccine uptake. It demonstrates cost-effectiveness in comparison to alternative approaches, such as lotteries. This may provide useful evidence for policymakers who are struggling to promote vaccination within countries where most of the population is still unvaccinated.

Highlights • We examine the effectiveness of a COVID-19 vaccination caravan in North Macedonia. • The caravan increased vaccinations by 35 % during 3 weeks after the visit. • We estimate a cost-effectiveness of 25.4 US dollars per additional vaccination induced. • Mobile vaccination caravans can be cost-effective interventions to increase COVID-19 vaccination rates. Over three years since the first COVID-19 vaccine was approved, many countries still have suboptimal vaccination rates despite holding great amounts of vaccines. Overall, there is little evidence on which policies are more effective to encourage vaccination, particularly in countries where a large share of the population remains unvaccinated. In this study, we examine the effectiveness of a community-based intervention carried out in March 2022 in North Macedonia, a country with a large and persistent share of the population that remains unvaccinated. The intervention, spearheaded by the Ministry of Health and supported by the World Health Organization and UNICEF, consisted of a mobile caravan offering vaccination and public health advice to different locations across the country on different days. Results from our staggered difference-in-difference model show that the mobile vaccination caravan increased daily vaccination rates by 7.7 vaccines per 100,000 inhabitants during the three weeks after the day of the caravan visit. This corresponds to a 35 % increase with respect to pre-intervention vaccination rates. We estimate a cost-effectiveness of 25.4 US dollars (USD) per additional vaccination induced. These results point to mobile caravan vaccines as an effective and cost-effective strategy to increase COVID-19 vaccination rates, even in a context of persistently suboptimal uptake. Keywords

COVID-19 vaccination in North Macedonia and the caravan North Macedonia is one of the countries with the lowest COVID-19 vaccination rates in Europe. By the beginning of the intervention, in March 2022, around 45 % of the population was fully vaccinated (i.e.: had received two doses of the vaccine). This is similar to the situation in most of the Balkan region ( Fig. 1 ), where countries report vaccination rates between 20 and 30 percentage points lower than the average in Europe (64 % by March 2022). Some scholars have explained this as a consequence of a high level of distrust in national governments, the pervasive presence of the anti-vaccine movement, and widespread misinformation on social media [ 19 , 20 ]. A survey among North Macedonian healthcare professionals pointed to other country-specific factors such as the failure of the institutions to communicate the benefits of vaccination, particularly to those with comorbidities who fear side effects, and communication of vaccine hesitancy from vaccine-hesitant healthcare professionals to patients [21] . The COVID-19 caravan was a community-based intervention carried out in partnership between the World Health Organization, United Nations International Children ́s Emergency Fund (UNICEF), the United States Agency for International Development (USAID), and North Macedonia authorities. It involved sending a mobile vaccination unit to areas with sub-optimal COVID-19 vaccination uptake to increase vaccination rates. Healthcare workers accompanied the mobile vaccination unit (the caravan) disseminating public health advice on COVID-19 protective measures (e.g. giving out brochures and promotional material, one-to-one conversations with patients and local healthcare workers, engaging with local media, etc.). The caravan visited one of 14 locations each day from the 21st of March to the 3rd of April of 2022. From 80 municipalities, 22 were exposed to the 14 caravan visits. Importantly, one of these 14 locations was the main shopping centre of the capital, Skopje, in the municipality of Gazi Baba (Skopje). Skopje has a total of 10 municipalities. This shopping centre is visited by citizens from all the municipalities within Skopje. We then assigned as treated municipalities as of the day of the shopping centre visit the remaining 8 municipalities within Skopje that had not had any caravan visit before. As a result, we have 22 treated municipalities over the 14 days of caravan visits (See Table A1 in Appendix A for a list of these municipalities and Appendix B for more details about the caravan). CRediT authorship contribution statement Manuel Serrano-Alarcón: Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft. Martin Mckee: Conceptualization, Writing – review & editing. Leonardo Palumbo: Conceptualization, Writing – review & editing. Cristiana Salvi: Conceptualization, Writing – review & editing. Anne Johansen: Writing – review & editing. David Stuckler: Conceptualization, Writing – review & editing. Declaration of Competing Interest Authors declare no conflict of interest. The researchers have carried out the analysis independently of the funders of the intervention. WHO Europe only provided the data while it had no role on the design of the study, methodological choices, data analysis nor on the presentation and interpretation of the results.

Supplementary materials Acknowledgements & Funding We are very grateful to Sara Kajevikj, Goran Kochinsksi, Thanas Goga, Ben Duncan and Brett Craig from WHO Europe and the North Macedonia Country Office who provided the data, comments and support during the research project. We thank members of the Competence Centre for Microeconomic Evaluation (CC-ME), 10.13039/501100000900 Joint Research Centre , 10.13039/501100000780 European Commission for providing useful comments. Manuel Serrano-Alarcón conducted the first analysis at DONDENA Research centre, 10.13039/501100006375 Bocconi University . The final draft and the revisions of the article have been conducted when he took service at the 10.13039/501100000780 European Commission , 10.13039/501100000900 Joint Research Centre .

CC BY

no

2024-01-16 23:42:02

Health Policy. 2024 Jan; 139:104966

oa_package/45/c0/PMC10788482.tar.gz

PMC10788493

38226180

Introduction The SARS-CoV-2 virus responsible for the COVID-19 pandemic first appeared in December 2019 in Wuhan, China [ 1 ]. It caught the world's attention in total surprise, unlike any past epidemic/pandemic, e.g., the Great Influenza pandemic during World War I [ 2 ]. Beginning in 2020, news of the outbreak of COVID-19 disease started to flash around the world, including Bangladesh. On January 30, 2020, WHO declared COVID-19 as a Global Public Health Emergency [ 3 ] and a pandemic on March 11, 2020. After the initial inertia, scientists worldwide joined hands to investigate various dimensions of the disease to mount an evidence-based pandemic response to contain morbidity and mortality. An explosive state of publications occurred to fulfil the urge to share covid data early for critical and strategic decision-making for prevention and treatment [ 4 , 5 ]. Science termed this one of “the biggest explosions of scientific literature ever” [ 6 ]. Interestingly, Bangladesh also joined this race to generate and disseminate new knowledge on COVID-19 although the culture of research and publication still has much to offer [ 7 , 8 ]. The beliefs, attitudes, and conventions within the academic community have previously demonstrated a lack of attention to research and a lack of proper financing, which needs to further evolve for translating evidence into policies [ 8 ] The first three COVID-19 cases in Bangladesh were confirmed on March 8, 2020 [ 9 ]. Thus, Bangladesh got a valuable lead time of around five weeks (seven weeks if we count the last two weeks of January) to prepare the people and the health systems to respond to the outbreak, including the impending surge of patients in healthcare facilities. However, neither the health ministry nor the government was found to rise to the occasion and provide the necessary stewardship for a coordinated and comprehensive response. The political establishment followed a ‘go alone’ and ‘reactive’ approach relying on the bureaucracy and was mostly indifferent to the advice of public health scientists and practitioners. There were also severe flaws in the ‘transparency and accountability of the government's various pandemic-related responses, such as emergency procurement and purchases, and corruption was all-embracing [ [10] , [11] , [12] ]. Since the pandemic's beginning, Bangladeshi researchers and academics at home and abroad have begun to conduct and publish rapid studies on issues of immediate importance to feed the policymakers for appropriate COVID-19 response [ 13 ]. However, these publications, using data originating from Bangladesh by authors working in Bangladeshi institutions are dispersed widely in various data sources, and it is not easy for researchers and stakeholders to trace and find these for various academic and real-time use in policy and practice. This situation motivated Bangladesh Health Watch, a civil society watchdog on health issues, to archive these publications on COVID-19 in Bangladesh into an online research repository to facilitate this process, and covered a wide variety of themes and topics of importance [ 14 ]. This study reviewed and analysed selected papers on governance issues related to the COVID-19 pandemic in Bangladesh and attempted to consolidate emerging lessons for effective and evidence-based epidemics/pandemic response in future.

Methods Settings Bangladesh Health Watch (( https://bangladeshhealthwatch.org ) is a civil society initiative for advocacy and monitoring to improve Bangladesh's health system by critically reviewing policies and programmes and facilitating appropriate actions for change. BHW has taken the initiative to archive all peer-reviewed publications on COVID-19 by Bangladeshi authors from home and abroad in a “research repository” that used data originating from Bangladesh ( https://r.bangladeshhealthwatch.org ). The idea was to make it easy for policymakers and practitioners, academics and researchers, and stakeholders within and outside Bangladesh to search and retrieve COVID-19-related documents for necessary use. A scoping review approach retrieved relevant documents on COVID-19 governance (see Table 1 ) following a protocol which defined key search terms, search engines to use, the range of documents to search, and the search period (see Table 2 ). The search terms were used in different combinations. The Boolean operators' AND’ & ‘OR’ were used to connect these search terms in order to find the most suitable articles. Selection process After identifying all articles on COVID-19 in Bangladesh fulfilling the above conditions, duplicates were removed, and the titles and abstracts were screened for relevancy. A second stage screening was done to remove non-peer-reviewed articles, articles that were not full text, and articles that were beyond the timeframe. One reviewer (NSS) searched and screened the selected databases for extracting relevant articles. A second reviewer (MK) check was done for the quality assessment of included articles. After discussion, the two reviewers resolved any confusion or disagreement at the screening and data extraction stage. Any further confusion was addressed with support from the lead author. Articles meeting all the inclusion criteria were finally selected for analysis (n = 11) (see Fig. 1 ). Data extraction and analysis Data were extracted using a pre-designed template that included columns for the name of authors, theme/sub-themes, codes used, study population and key findings. From the wide range of data gather from the “research repository”, we identified and used the data related to ‘governance’ for this study. We dida descriptive analysis of the selected articles. We developed a brief narrative synthesis, specifically to inform an invited expert who critically reflected on the review findings, discussed these in the context of other Asian LMICs and identified key take-home messages. As we worked with secondary data, no ethical approval was obtained for this step. Finally, recommendations were made for future research in specific areas to develop the relevant topic further. Expert deliberations The review findings on the governance of Bangladesh's COVID-19 response were shared with some invited experts with varying backgrounds in public health, governance, and pandemic response in a deliberative discussion. They critically reflected on the findings and discussed at length the its importnance and significance in the context of Bangladesh. All the experts pointed out the governance shortcomings in taking quarantine measures, implementing screening for COVID-19, mitigating corruption and logistics of procurement. The findings from the reviewed articles are presented in Table 3 .

Results A total of 11 articles on COVID-19 ‘governance’ were selected for review ( Table 3 ). Of these, two were cross-sectional surveys; two were qualitative studies; two were reviews; two were perspective pieces, and one each of case study, report and a mixed-method study. The review findings are described below under the following thematic headings. Quarantine measures: from enforcement to relaxation From the very beginning, governance problem was prominent in managing the lockdown to limit the spread of the virus, characterised by ‘confusion, incoherence, and reversal’ [ 20 ]. In the early weeks, the health system displayed poor preparedness in tackling the returnees from Italy (and other countries) by institutional ‘quarantine’ in the airports or, later, in the homes [ [20] , [21] , [22] ]. The expatriates at the airports revolted against the poor arrangement of quarantine facilities, and the authorities had to succumb and release them. Similarly, unsupervised home quarantine was ignored by people and was largely ineffective. The first lockdown of 66 days (from 26 March to May 30, 2020, starting with a ten-day ‘national holiday’ and extended seven times) started with a robust enforcement regime. People initially supported the stringent measures as they panicked from the unknown virus and the consequent disease. Over time, when the economic condition of the poor worsened and the government failed to provide subsistence relief to the poor and marginalised, coercive lockdown gave way to exceptions [ 20 ]. Excuses such as permitting the “boro rice harvest,” “mosques to host congregations with social distancing rules,” “restaurants to sell iftar foods,” “garments factories and shops to reopen” etc. were put forward to loosen the ‘lockdown’ restrictions. Researchers came forward with advice to strategically tackle both lives and livelihood simultaneously and reinforce ‘safety net’ entitlements to overcome the situation [ 23 ]. Testing for COVID-19: limited to a single institution initially The primary tool to fight COVID-19, i.e. facilities for testing the presence of SARS-CoV-2, was restricted to a single government institution until the end of March 2020, leaving many districts and sub-districts without any such facility in the early weeks [ 21 , 24 ]. Many facilities with test kits could not implement a standardised test protocol due to the absence of biosafety level 2 labs or a shortage of trained personnel. The number of test labs and tests performed was meagre compared to the size of the population in the country (13 tests per million) [ 25 ] and not proportionally distributed geographically. This shortage of tests resulted in fewer reported cases and left the decision-makers without an efficient epidemiological tool to pursue an evidence-based Governance of COVID-19 [ 25 ]. The number of test labs slowly expanded over time, however. All-pervading corruption: dent in trust in health systems What shocked the nation was the continuation of the all-pervading health sector corruption even during the ongoing pandemic [ 10 ]. Prominent among these and frequently reported in media, were corruption related to the procurement of personal protective equipment, masks and other supplies; fake COVID-19 testing and report (e.g., Regent Hospital and JKG Health Care scams); five hundred physicians' food and living costs for one month; and the relief regime for the poor and the disadvantaged. These caused many unnecessary deaths, including doctors and nurses, and raised the cost of care for COVID-19 patients [ 26 ]. The level of corruption during the pandemic made a dent in people's trust in the health system, especially its management [ 12 ], which also spilt over to the healthcare providers (especially doctors and nurses) [ 27 ]. This hampered government's ability to act ‘decisively’ and ‘transparently,’ e.g., in enforcing ‘lockdown’ measures when needed. This lack of “state capacity to make and enforce policy,” e.g., related to lockdowns, was argued by some authors from a political economy perspective as a reflection of the need to demonstrate outcome performance in the face of questionable political legitimacy of the government [ 20 ]. Improving governance: suggested measures The stakeholders made various suggestions, including facilitation of local governance, data-driven governance and emphasising the moral aspects of governance to counter the problems observed with COVID-19 governance. By activating and mobilising the local government bodies, the community was found to effectively engage in COVID-19 mitigation measures, including the delivery of essential healthcare services [ 28 ]. For the latter, ICT tools and local governance digitisation increased accountability and transparency by connecting more people to the decision-making process. A four-tier bio-ethical ‘Pandemic Outbreak Disaster Management Model (PODM)' was proposed incorporating issues concerning ‘life, living beings, interests of victims, food safety, necessary medical equipment, and medicine,’ over and above that described in the government's National Preparedness and Response Plan for COVID-19 [ 29 ]. The proposed tiers consisted of i) critical assessment of the current scenario to develop a response; ii) understanding the global experiences of pandemic impacts and using it for the action plan; iii) helping people recognise how they should interact with the consequences of a pandemic situation; iv) strengthened techniques and capacity to bring life back to ‘normal’ post-pandemic.

Discussion This study presents critical reflections on Bangladesh Government's COVID-19 governance response through a review of selected papers on the topic (n = 11), followed by expert deliberations on the review findings. Findings reveal a lack of governance capability to mount a quick, effective and efficient response, such as lockdown and testing, that is inclusive and comprehensive [ 22 ]. The findings are discussed below with implications for future epidemic/pandemic preparation in the context of LMICs like Bnagladesh. The governance challenges against COVID-19 in Bangladesh came out starkly in the articles reviewed [ [20] , [21] , [22] ]. Experiences from a few Asian countries (Brunei, Cambodia, Sri Lanka, Taiwan, Thailand and Vietnam) ‘beating’ COVID-19 reiterated the importance of an effective and efficient governance mechanism that Bangladesh lacked [ 22 ]. For effective and inclusive governance of a health emergency of the magnitude of COVID-19 pandemic, a ‘whole of government’ and a ‘whole of society’ approach is essential which was lacking in Bangladesh, at least in the early months [ [30] , [31] , [32] ]. The pandemic was an eye-opener to the fundamental shortfalls of the Bangladesh health systems such as shortage of health workforce of all categories and at all levels, essential diagnostics, personal safety gear for the frontline healthworkers, and medical oxygen supply and intensive care units (ICUs). This is not surprising, and consistent with what was observed in the latest Bangladesh Health Facility Survey (2017). The survey found only 28% of the static health facilities having all the six basic equipment (stethoscope, thermometer, blood pressure machine, adult weight scale, child or infant scale, and light source) which are essential for providing services of a minimal quality [ 33 ]. In the early months, lockdown and other non-pharmaceutical measures were the only available tools to contain the spread of the infection. The lockdown measures give health systems breathing space to prepare for the surge in COVID-19 suspects and patients. However, due to resource constraints (e.g., shortage of skilled health care workers, leakage of financial resources due to health sector corruption, lack of lab and other technical capacity), many low and middle-income countries (LMICs) could not prepare the health systems in time for lockdown, and Bangladesh was no exception [ 20 , 34 , 35 ]. Lockdown measures in LMICs should be contextualised for local conditions, beneficial for the concerned population, and prevent the need for re-imposing lockdown [ 36 ]. In these countries, a localised lockdown of the hotspots, combined with disease surveillance and other non-pharmaceutical measures should be implemented [ 35 ]. For this to happen, science needs to be prioritised over politics, actively engage the communities in COVID-19 containment activities, and recruit and train more health care workers to work at the front lines. Corruption in the health sector of Bangladesh is phenomenal [ 37 ]. The COVID-19 pandemic not only unmasked the weaknesses of the health system in this regard, but also “created new opportunities for corruption” [ 10 , 38 ]. This trend of continued corruption in the times of pandemic has been observed globally as well [ [39] , [40] , [41] ]. Various strategies are suggested to reiterate that anticorruption must remain a priority even during pandemic like COVID-19 [ 41 ]. These include, but not limited to, recruitment of appropriately skilled staff, positioning public health experts in command (“put science before politics”) [ 42 ], and a gender perspective to ensure that anticorruption measures “do not further marginalise or disadvantage women and other vulnerable and marginalised groups” [ 41 ]. Globally, “populist” governments did a lousy job of responding to COVID-19 due to inappropriate policy responses, downplaying the gravity of the pandemic and putting politics over science [ 43 ], as was also observed in case of Bangladesh. Anti-intellectualism (generalised distrust of experts and intellectuals) among the masses at large also contributes to this kind of “populist” governance because people usually comply with antipandemic measures when the information comes from a source they trust [ 44 ]. The importance of ‘good governance’ for a successful COVID-19 response cannot be overemphasised. Globally, argument is made to turn the COVID-19 health crisis into an opportunity to prepare for the next epidemic/pandemic [ 36 , 45 , 46 ]. In Bangladesh, the leadership must prepare for such crisis and follow ethical principles to overcome various forms of incompetencies in the system. These include mismanagement of resources allocated (e.g., for COVID-19), failure to harmonise coordination among government's different agencies (e.g., relevant to COVID-19 response), and resilience to deliver services (e.g., for COVID- 19 cases) without compromising essential services, e.g., as has been observed in India [ 47 ]. Strengths and weaknesses The findings from the reviewed papers were further shared and discussed with experts in the field which strengthened the validity of the information. We restricted the search of the papers available within the repository and might have missed papers on the topic, especially related to the later part of the pandemic, whose includion would have affected the analysis.

Conclusions Bangladesh's COVID-19 response in the early months was characterised by slow, delayed and ambiguous measures which reflected poorly on its governance [ 48 ]. Governance gaps in areas such as instituting screening and lockdown measures, prioritising safety and security of the frontline workers to preserve the workforce, COVID-19 testing, quarantine (suspects) and isolation (cases), and logistics and procurement was phenomenal. However, over time, the GoB laid down required actions and services for mitigation of the pandemic impact on the country, though the stewardship functions were not seamless. Diagnostic and case management services gained strength after some initial faltering. Continued shortage of all kinds of healthworkers, poor capacity of the health facilities to cater to the COVID-19 suspects and cases, particularly outside the major metropolises, and constraints in resources and logistics were some of the critical factors limiting government's COVID-19 responses. The scarcity of governance related articles indicate the need for more focused research in this area, so that substantial contributions can be made through indentifying gaps in policies and regulations.

Background On January 30, 2020, WHO declared COVID-19 as a Global Public Health Emergency. The first three COVID-19 cases in Bangladesh were confirmed on March 8, 2020. Thus, Bangladesh got substantial time to prepare the people and the health systems to respond to the outbreak However, neither the health ministry nor the government was found to rise to the occasion and provide the necessary stewardship for a coordinated and comprehensive response. Objective The importance of governance to mount an evidence-based pandemic response cannot be overemphasised. This study presents critical reflections on the Bangladesh government's COVID-19 response through a review of selected papers, with expert deliberations on the review findings to consolidate emerging lessons for future pandemic preparedness. Study design A scoping review approach was taken for this study. Methods Documents focusing on COVID-19 governance were selected from a repository of peer-reviewed articles published by researchers using data from Bangladesh (n = 11). Results Findings reveal Bangladesh's COVID-19 response to be delayed, slow, and ambiguous, reflecting poorly on its governance. Lack of governance capability in screening for COVID-19, instituting quarantine and lockdown measures in the early weeks, safety and security of frontline healthcare providers, timely and equitable COVID-19 testing, and logistics and procurement were phenomenal. The pandemic unmasked the weaknesses of the health system in this regard and “created new opportunities for corruption.” The failure to harmonise coordination among the government's different agencies for the COVID-19 response, along with poor risk communication, which was not culture-sensitive and context-specific. Over time, the government initiated necessary actions to mitigate the pandemic's impact on the lives and livelihoods of the people. Diagnostic and case management services gained strength after some initial faltering; however, the stewardship functions were not seamless. Conclusions Shortage of healthcare workers, incapability of health facilities to cater to COVID-19 suspects and cases, absence of health system resilience, and corruption in procurement and purchases were limited the government's COVID-19 response. These need urgent attention from policymakers to better prepare for the next epidemic/pandemic. Keywords

Ethics approval and consent to participate Not applicable. Patient consent for publication Not applicable. Availability of data and materials All data generated and analysed during this study are included in this published aeticle. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Declaration of competing interest The author(s) declare that there is no potential conflict of interest.

Supplementary data The following is the Supplementary data to this article: Acknowledgements The researchers appreciate the support they received from Bangladesh Health Watch Secretariat while conducting the research.

CC BY

no

2024-01-16 23:42:02

Public Health Pract (Oxf). 2023 Dec 16; 7:100457

oa_package/6a/2b/PMC10788493.tar.gz

PMC10788500

38226206

Introduction Hunger breeds discontentment, safety is the supremacy for food, according to an old Chinese saying. Food safety is related to people's health and the future of the Chinese nation (Xi, 2014). The report of the 20th National Congress of the Communist Party of China emphasizes the necessity to strengthen food safety supervision. The first document of the Central Government in 2023 further elaborated on the need to strengthen the supervision of food safety and agricultural product quality safety, and improve the traceability management system. However, from melamine to gutter oil to clenbuterol, public discussions of problems in connections with food safety have continued, seriously affecting people's physical and mental health, even causing a decline in social credibility [ 1 , 2 ]. The Research Group of the Chinese People's Livelihood Survey of the Development Research Center of the State Council (2018) notes that food safety is China's foremost socio-environmental concern. Strengthening food safety governance continues to be called for by urban and rural residents, which indicates that food safety is of substantial practical significance to the people and the entire society. In recent years, China has made remarkable achievements in economic construction, with a continuous increase in per capita income. But meanwhile, China has fallen into the dilemma of “stagnation of happiness”. Easterlin's study on China showed that income growth and residents' happiness were not synchronized in transition countries. Between 1990 and 2009, China's economic growth rate was about 8 %, while the happiness status of Chinese residents during the same period showed an inverted U-shaped pattern. The happiness level of rural residents in 2009 was even lower than that in 1990 [ 3 ]. The results of the World Values Survey also indicated that the happiness level of Chinese didn't increase synchronously with economic growth [ 4 ]. China has also been adjusting its economic policies, focusing on ensuring and improving people's livelihoods. To this end, the academic community has been investigating how to crack the “happiness code” to enhance people's happiness. From economic factors to social factors, from micro factors to macro factors, scholars have performed numerous in-depth studies on happiness. However, food safety, a major concern of daily living, has received little attention from scholars. Furthermore, it is worth noting that although China's per capita GDP has reached 12,000 US dollars, the wealth gap is still significant, with a Gini coefficient of 0.474 in 2022, with the urban-rural gap being the most significant. 2 Many rural residents have difficulty ensuring food safety, and a safe food supply is crucial for them. Therefore, the following three research questions were considered. What role does food safety play in the process of achieving a happy life for the general public? How deeply does food safety affect farmers' happiness, and what are the characteristics of the influence? To answer these questions, this paper focuses on the impact of food safety perception on farmers' happiness. This paper not only provides a more substantial basis for decision-making to promote food safety governance measures but also has strong practical significance for building a harmonious society and enhancing people's sense of progress, security and happiness.

Methods Design This paper utilizes the Ordered Probit model to investigate the impact of food safety perception on farmers’ happiness, using the data collected from the China Social Survey (CSS). To address sample selection bias, the paper employ propensity score matching (PSM) method, the recursive bivariate ordered probit (RBOP) model and the conditional mixed process (CMP) method. Next, this paper will introduce the Population and Sample, Procedure in details. Population and sample This study uses open-access data provided by the China Social Survey (CSS), 3 hosted by the Institute of Sociology of the Chinese Academy of Social Sciences. 4 The survey was conducted nationwide based on PPS (Probability Proportionate to Size) sampling, covering various aspects such as labor and employment, family and social life, and social attitudes, which was launched in 2006 and the latest released data is for 2021. Only three years of data, 2013, 2017, and 2021, involve food safety perception. Therefore, this article utilisizes the data from these three years. It is worth noting that CSS2017 did not directly set happiness variable, but instead set a highly correlated “life satisfaction” variable. Although CSS2021 sets variables for happiness and life satisfaction, the forms of the two variables are different from CSS2013, and the two variables are distributed in the A and B volumes of CSS2021, which limited the sample size. By contrast, the CSS2013 data is the most suitable for analyzing the relationship between food safety and farmers’ happiness, so this paper uses it as the main data for empirical analysis. CSS2017 and CSS2021 are mainly used for robustness check of empirical models. The CSS2013 data includes 596 villages from 149 counties in 30 provinces nationwide, with 10,206 valid questionnaires collected. The CSS2017 data includes 576 villages from 151 counties, with 10,091 valid questionnaires collected. The CSS2021 data includes 592 villages from 152 counties, with 10,136 valid questionnaires collected. The paper selected samples living in rural areas. In CSS2013, 6271 valid samples were obtained. Similarly, In CSS2017, 6727 valid samples were obtained. In CSS2021, 2946 valid samples were obtained. Procesure Modeling the food safety perception effect on farmers’ happiness Happiness is a discrete ranking data. The paper use the orderd probit (Oprobit) model as the benchmark model. The paper assume happiness variable to be a function of a food safety perception variable ( ) and a vector of explanatory variables ( ): where is an unobserved latent variable representing farmers' happiness, represented by an observed categorical variable . This latter is determined by the unknown cutoffs , , ..., , which satisfy the condition that < . indicates food safety perception, and is a vector of explanatory variables. and are parameters to be estimated. is a random error term. Propensity score matching method Given that farmers' food safety perception is likely to be a self-selection process determined by individual characteristics (e.g., farmers’ age, education level, employment status and income level). Thus, this paper use PSM method to construct the counterfactual framework to correct the sample selection bias. Propensity score is proposed by Ref. [ 36 ]; which is defined as the conditional probability that an individual is affected by some explanatory variables after controlling the observed variables. It should be noted that PSM method requires treatment variable is binary. Therefore, the paper redefine the variable of food safety perception, and define “very unsafe and unsafe” as “unsafe”, and assigns it to 0. Similarly, it defines “safe and very safe” as “safe” and assigns it to 1. Within the sample range, there are 3790 farmers who think food safe, accounting for 54 %, and 3229 farmers who think food unsafe, accounting for 46 %. As shown in equation (2) , is the propensity score, is a vector of observed variables. The dummy variable , known as the treatment variable, indicates whether the farmer reports food safe or not. is the cumulative distribution function of the logical distribution, is the parameter to be evaluated, which is used to obtain the propensity score . As shown in equation (3) , the paper compare the average difference in farmers' happiness between the treatment group and the matched control group based on the matched samples, and obtain the causal effect between food safety perception and farmers’ happiness, that is, the average treatment effect on treated (ATT). It is also worth noting that the PSM method has limitations [ 37 ]. If the first stage model is set up incorrectly or if the observable variables are chosen improperly or too few, estimation bias can easily result. For this reason [ 37 ], notes that caution is required when estimating the use of the propensity matching method. Based on PSM method and referring to Ref. [ 38 ]; this paper uses inverse probability weighting to modify the model. Inverse probability weighting (IPW) is similar to the basic principle of PSM method. However, IPW does not directly use propensity scores to estimate but, rather, assigns higher weight to individuals with lower propensity scores and lower weight to individuals with higher propensity scores. This approach contributes to the closer distribution of the covariates of the treatment group and the control group and more robust ATT results. In addition, scholars have optimized IPW, typically represented by inverse probability weighting-regression adjustment (IPWRA) [ 39 ]. The largest advantage of this method is that the estimation results have double robustness; that is, as long as one of the first-stage equations and the result equations are correct, the ATT estimation results are consistent [ 38 , 39 ]. The ATT of the IPW method and IPWRA method can be shown in equations (4) , (5) . Recursive bivariate ordered probit (RBOP) model The PSM, IPW and IPWRA methods can correct the sample selection bias caused by observed variables, but it does not account for unobserved factors when serving to address the issue of selection bias. The RBOP model proposed by Ref. [ 40 ]; in contrast, can sufficiently address selection bias by taking into account both the observed and unobserved factors and then estimating the impact of food safety perception on farmers’ happiness. We also adopt a conditional mixed process (CMP) approach for its robustness checks. 5 The RBOP model jointly estimates Equation (1) , which models the food safety perception and farmers’ happiness, and Equation (6) , a latent model whose observable components enable indirect expression of the utility difference. where is a latent variable to measure food safety perception which cannot be directly observed, but has a certain quantitative relationship with . This latter is determined by the unknown cutoffs , , , which satisfy the condition that < . indicates food safety perception, and is a vector of explanatory variables, and are parameters to be estimated, and is a random error term. As shown in equation (7) , The RBOP model estimates Equations (1) , (6) simultaneously using a full information maximum likelihood (FIML) estimator [ 40 ] and under the assumption that the random errors ( ) follow a bivariate normal distribution across individuals with a zero mean and unit variance. When is significantly different from 0, it indicates that the model has an endogenous problem, that is, the estimation result of RBOP model is better than that of Oprobit model. On the contrary, if is not significantly different from 0, then the estimation results can be obtained by reference to the Oprobit model. Although the RBOP model can be identified on the non-linearity of the system, for a better identification, the food safety perception equation should include a variable that is absent from the farmers' happiness equation, one that serves as an instrumental variable (IV) affecting food safety perception but having no direct impact on farmers’ happiness. This paper employ the frequency of farmers reading newspapers as an IV. Considering that RBOP model can not directly test the validity and effectiveness of IV, the paper use the two-stage least square estimation method (2SLS) to test it. Data analytic The dependent variable is farmers’ happiness, which was addressed in the survey questionnaire in the following manner. Survey participants were asked to respond to the statement “Overall, I am a happy person” by choosing from the following response options: very unhappy, unhappy, not very happy, relatively happy, happy, very happy and hard to say. This paper delete the response “hard to say” and assign the other six items scores of 1, 2, 3, 4, 5 and 6, respectively. As shown in Table 1 , in the CSS2013 data, the number of farmers who responded with “relatively happy” is the largest, which is 2666 accounting for 37.26 %. The number of farmers who responded with “happy” ranked the second, which is 2126 accounting for 29.71 %. In contrast, the number of farmers who responded “very unhappy” was the least (144), with the lowest proportion (2.46 %). The independent variable is food safety perception. Respondents were asked, “How do you feel about the safety of food in the current society?” and were requested to respond by choosing from very unsafe, unsafe, safe, very safe and hard to say. This paper delete the response “hard to say” and assign the remaining four items scores of 1, 2, 3 and 4, respectively. The higher that the value is, the safer the respondents believe food is, that is, the higher the level of food safety perception. Fig. 1 demonstrates farmers' food safety perception in data from different years of 2013, 2017 and 2021. It shows that in the CSS2013 data, the mean value of food safety is 2.547, while in the CSS2017 and CSS2021 data, the mean values are 2.505 and 2.974, respectively. This means that over time, farmers’ food safety perception has improved. As shown in Fig. 2 , in the CSS2013 data, there is a positive correlation between farmers’ food safety perception and their happiness. Specifically, the average happiness level of the farmers who replied “unsafe” was only 3.854 compared with 4.211 (i.e., 9.26 % higher) for the farmers who replied “very unsafe”. Of course, the logical relationship between food safety perception and happiness requires rigorous empirical analysis. Based on the CSS2013, this paper also controls for a number of variables that may affect farmers’ happiness ( Table 2 ), including age, age squared, education, gender, marital status, political status, employment status, income, Internet use, economic status, and social trust. In addition, given regional heterogeneity, this paper also controls for regional dummy variables.

Results and discussion Benchmark regression In Table 3 , columns (1)–(3) list the OLS model estimates, whereas columns (4)–(6) list the Oprobit model estimates. Overall, the model runs well, with the F value and the Wald test values both passing the significance test at the statistical level of 1 %. Additionally, there is no significant change in the direction and significance level of the independent variable between the columns, indicating that the model estimates are robust. Through comparison, the paper can observe that whether according to the OLS model (which regards happiness as a continuous variable) or the Oprobit model (which considers the intrinsic ranking of happiness) the estimation results reveal that food safety perception is significantly positively correlated with farmers’ happiness, even after adding control and regional dummy variables. In column (6), the probability of farmers responding “very happy” increases by 1.2 %, and the average level of farmers responding “very happy” (7.46 %) increases by 16.09 % for each unit of improvement in food safety perception. These outcomes reveal that the significance of food safety perception to farmers' happiness is not only reflected on the statistical level but also in the real economy. To enhance farmers’ happiness and break free from the “stagnation of happiness” state, the policy makers should consider taking food safety as the starting point and promoting food safety regulatory policies. In terms of the control variables, most of the variables also significantly affect farmers' happiness, and the estimation results are basically consistent with the literature. Next, this paper briefly analyzes the estimation results based on column (6). The influence of age on the happiness of farmers displays a typical U-shaped distribution. The lowest point of U-shaped distribution, the “turning point of happiness”, is approximately 38 years of age. A possible explanation of this finding is that in youth, people have less stress, lighter burdens, and a stronger sense of happiness. As they grow older, pressure at home and work increases, and happiness decreases to the lowest point. Subsequently, happiness increases with age. The farmer's mental state gradually becomes peaceful, and the sense of happiness improves. Education level, income level, economic status and social trust are significantly positively related to farmers' happiness. In addition, whether a farmer is married, a party member, employed or an Internet user has a significant positive impact on the farmer's happiness. However, considering that certain control variables may face potential endogeneity problems, one must be careful regarding the above estimates. Correction of selection bias Using the PSM method, a balance test is required to ensure that after matching there is no significant systematic difference between the treatment group and control group of samples except for differences among food safety perception variables [ 41 ]. noted that there should be no systematic differences in the distribution of explanatory variables between the treatment group and the control group after matching. Therefore, pseudo R 2 should decrease significantly, and the LR test of the explanatory variables should be rejected. In addition [ 42 ], observed that after matching, the standardization bias of explanatory variables decreases dramatically. Generally, the normalization coefficient of the explanatory variables after matching should be less than 20 %, and a coefficient higher than 20 % means that the matching process has failed. As shown in Table A1 , after the matching was completed, a balance test was performed. Prior to the matching, pseudo R 2 was 0.056, and the LR test outcome was 499.02, which is significant at a statistical level of 1 %. The average and median of the standardized errors were 22.1 % and 15.4 %, respectively. After the application of different matching methods, pseudo R 2 decreases to 0.002 and below. The results of LR test are not statistically significant, and the average and median of the standardization errors are not higher than 2.3 %. These results indicate that the PSM significantly weakens the systematic differences in explanatory variables and that the matching process is successful. To ensure matching quality, the paper also establish the probability distribution of the propensity scores of treatment group and control group before and after matching. As shown in Fig. 3 , the difference in the probability distribution of the two groups of samples prior to matching is extremely significant, and the overlap interval of the two groups of samples is narrow. After matching, the difference between the two groups of samples is significantly smaller, with a considerable range of overlap interval. In this way, the proportion of effective samples lost is very low, and the matching quality is satisfactory. This result further confirms that the PSM method can correct the sample selection bias and more accurately assess the causal effect between food safety perception and farmers’ happiness. Finally, this paper measures the ATT of two sets of samples after matching ( Table 4 ), although different matching methods produce different quantitative results. Qualitatively, the results of the different matching methods are consistent. That is, after observing systematic differences between samples, food safety perception and farmers’ happiness are significantly positively related. It is worth noting that in the process of radius matching, the matching accuracy constantly improves and reduces the caliper range. Although there is a certain “loss” of samples, the ATT estimation results remain robust. In addition, as shown in Table A2 , this paper uses IPW method and IPWRA method to calculate ATT. The results reveal that ATT as obtained by IPW method and IPWRA method differs from that obtained by PSM method in numerical level but is highly consistent in significance and direction. This outcome also confirms the robustness of the empirical results. Endogeneity discussion Based on the preceding discussion of the potential endogeneity problems of the model, this paper uses the RBOP model and the CMP method to analyze and reduce the potential impact of endogeneity problems. As shown in Table 5 , generally, the estimation results obtained by the two methods are very close, which reveals the consistency and robustness of the estimation results. More specifically, in the first stage, the frequency of farmers reading newspapers is significantly positively correlated with food safety perception, indicating that the instrumental variable satisfies the correlation condition. Further, ρ με is significant at the statistical level of 1 %, indicating that the model has endogeneity problems and that the RBOP model is superior to the ordinary model. Based on the results of the second stage, food safety perception is significantly positively related to farmers’ happiness. This outcome is consistent with the preceding estimation results, indicating that these results are robust and reliable. Robustness checks Add control variables Both the independent variable and the dependent variables are subjective variables. Hu (2019) notes that the largest challenge in explaining one subjective variable with another is that these subjective variables may have a common basis for potential psychological traits, which may result in falsely related problems. He further emphasizes that if psychological traits are independent, that is, two subjective variables are generated by different psychological traits, they will not be constrained by the same psychological trait and cause confusion and bias. Although food safety perception and happiness are both subjective evaluations of respondents, there are significant differences in their psychological basis. The perception of food safety often “tells the truth” with stronger relevance, mostly regarding the respondents’ actual feelings on food safety issues or their attention to policy information and personal observation. In contrast, happiness is a quite comprehensive inner feeling. Additionally, the psychological state of the respondents is likely to affect food safety perception and happiness. Therefore, this paper attempts to add psychological state variables in the robustness test. In the CSS2013 questionnaire, respondents are asked, “Overall, how often do you feel worried (scared)?” They answered by choosing from the options never, rare, sometimes, often, always, which are assigned scores of 1, 2, 3, 4 and 5, respectively, as proxy variables of the mental state. This paper further add the fairness perception variable to the test. Respondents were asked, “What do you think of the overall social equity situation?” The response options were very unfair, not fair, fair, very fair, which are assigned scores of 1, 2, 3 and 4, respectively. As shown in Table A3 , mental state and fairness perception have a significant impact on happiness. When the variables of mental state and fairness perception are added, the regression coefficient of food safety perception variable decreases but still has a significant positive impact on happiness. Omitted variable test In addition to the previously mentioned addition of mental state and fairness perception variables for robustness testing, this paper also refers to the method proposed by Ref. [ 43 ] to test the unobservable variables in the regression [ 43 ]. demonstrated that when there are unobservable omitted variables in the model the estimate = can be used to obtain a consistent estimate of the true coefficients. refers to the maximum goodness of fit of the regression equation when the unobservable omitted variables can be observed, and refers to the selection balance between observable and unobservable variables. Specifically, there are two methods for testing as follows. In method (1), the paper assume that is a certain value (generally, is 1.3 times the goodness of fit of the current regression). On this basis, the paper calculate the value of that makes . If is greater than 1, the estimation result passes the test. Method (2) is similar to method (1). When the paper assume that is a certain value, if = falls within the 95 % confidence interval of the estimated parameters, the estimated results pass the test. As shown in Table A4 , the results of this paper are robust and reliable according to the test of omitted variables. Regression analysis based on CSS2017 and CSS2021 In addition to the CSS2013 data, the CSS2017 and CSS2021 data released by the Institute of Sociology of Chinese Academy of Social Sciences also involves variables related to food safety and happiness. Therefore, the paper use the CSS2017 and the CSS2021 data to test the robustness of the regression results. It is worth noting that, slightly different from the CSS2013, the CSS2017 data does not directly relate to respondents' happiness, but examines respondents’ life satisfaction. Specifically, the questionnaire asks respondents: Overall, how satisfied are you with your life. Respondents choose an integer from 1 to 10, with 1 being very dissatisfied and 10 being very satisfied. Using the life satisfaction index to measure happiness is also a method commonly used in existing literature [ 44 ]. Although the CSS2021 sets variables for happiness and life satisfaction, these two variables are set differently from CSS2013, and due to variable limitations (happiness and life satisfaction are random a and b volumes, with sample size halved), CSS2013 is still used as the benchmark regression analysis. As shown in Table A5 , the estimation results of OLS regression and Oprobit model based on the CSS2017 and CSS2021 show that farmers’ food safety perception exerts a positive and significant impact on their happiness or life satifacation. Even after adding other explanatory variables and regional dummy variables, the finding of a positive relationship between food safety perception and happiness or life satifacation confirms the results presented in the above part of Table 3 . In addition, as shown in Table A2 , this paper uses IPW method and IPWRA method to calculate ATT ( Table A3 in the Appendix). The results reveal that the ATT obtained by IPW method and IPWRA method differs from that obtained by PSM method in numerical level but is highly consistent in significance and direction. This finding further confirms the robustness of the empirical results. Further analysis Although the paper have concluded that food safety perception has a significant positive effect on farmers’ happiness, the paper has only obtained the average effect of the entire sample, without considering the heterogeneity between groups. Therefore, this section of the paper focuses on educational and intergenerational differences between subgroups to develop a more detailed discussion. In terms of educational differences, this paper divides farmers into two groups according to education level: those who have received junior high school education or below (lower education level group) and those who have received senior high school education or above (higher education level group). Within the sample range, there are 1082 farmers with higher education (15.25 %) and 6012 farmers with lower education (84.75 %). As shown in Table 6 generally, the impact of food safety perception on the happiness of farmers with different education levels is significant at the statistical level of 1 %. Specifically, the impact of food safety perception on the happiness of farmers with a higher education level is more obvious, which indicates that food safety is more important for farmers with such education levels. A possible explanation for this result is that highly educated farmers know more about food safety issues, and because they have a better understanding of these issues, they pay more attention to them. Therefore, food safety perception plays a more important role with respect to their happiness. In terms of intergenerational differences, this paper divides the sample into three groups according to age: young, middle-aged and elderly. Here, young people are farmers under 40 years old, middle-aged farmers are 40–60 years old, and elderly farmers are over 60 years old. Within the sample range, there are 2504 young farmers (34.43 %), 3488 middle-aged farmers (47.96 %), and 1281 elderly farmers (17.61 %). As shown in Table 6 , food safety has a significant positive impact on the happiness of farmers of different ages. From the regression coefficient perspective, food safety has the most significant impact on the happiness of elderly farmers, whereas the impact on the well-being of young and middle-aged farmers is approximately the same. One reason why elderly farmers are more sensitive to food safety may be that with increasing age the health of the elderly is not as good as that of young and middle-aged individuals. Life experience enables the elderly to better understand the truth that illness “comes from the mouth”. Therefore, the elderly are significantly more sensitive to food safety issues than young and middle-aged individuals. In conclusion, there is educational and intergenerational heterogeneity in the impact of farmers’ food safety perception on happiness. Therefore, in the process of filling the gaps in rural food safety, it is necessary to mobilize highly educated farmers to become food safety regulators and strengthen the promotion of food safety among the elderly in rural areas.

Results and discussion Benchmark regression In Table 3 , columns (1)–(3) list the OLS model estimates, whereas columns (4)–(6) list the Oprobit model estimates. Overall, the model runs well, with the F value and the Wald test values both passing the significance test at the statistical level of 1 %. Additionally, there is no significant change in the direction and significance level of the independent variable between the columns, indicating that the model estimates are robust. Through comparison, the paper can observe that whether according to the OLS model (which regards happiness as a continuous variable) or the Oprobit model (which considers the intrinsic ranking of happiness) the estimation results reveal that food safety perception is significantly positively correlated with farmers’ happiness, even after adding control and regional dummy variables. In column (6), the probability of farmers responding “very happy” increases by 1.2 %, and the average level of farmers responding “very happy” (7.46 %) increases by 16.09 % for each unit of improvement in food safety perception. These outcomes reveal that the significance of food safety perception to farmers' happiness is not only reflected on the statistical level but also in the real economy. To enhance farmers’ happiness and break free from the “stagnation of happiness” state, the policy makers should consider taking food safety as the starting point and promoting food safety regulatory policies. In terms of the control variables, most of the variables also significantly affect farmers' happiness, and the estimation results are basically consistent with the literature. Next, this paper briefly analyzes the estimation results based on column (6). The influence of age on the happiness of farmers displays a typical U-shaped distribution. The lowest point of U-shaped distribution, the “turning point of happiness”, is approximately 38 years of age. A possible explanation of this finding is that in youth, people have less stress, lighter burdens, and a stronger sense of happiness. As they grow older, pressure at home and work increases, and happiness decreases to the lowest point. Subsequently, happiness increases with age. The farmer's mental state gradually becomes peaceful, and the sense of happiness improves. Education level, income level, economic status and social trust are significantly positively related to farmers' happiness. In addition, whether a farmer is married, a party member, employed or an Internet user has a significant positive impact on the farmer's happiness. However, considering that certain control variables may face potential endogeneity problems, one must be careful regarding the above estimates. Correction of selection bias Using the PSM method, a balance test is required to ensure that after matching there is no significant systematic difference between the treatment group and control group of samples except for differences among food safety perception variables [ 41 ]. noted that there should be no systematic differences in the distribution of explanatory variables between the treatment group and the control group after matching. Therefore, pseudo R 2 should decrease significantly, and the LR test of the explanatory variables should be rejected. In addition [ 42 ], observed that after matching, the standardization bias of explanatory variables decreases dramatically. Generally, the normalization coefficient of the explanatory variables after matching should be less than 20 %, and a coefficient higher than 20 % means that the matching process has failed. As shown in Table A1 , after the matching was completed, a balance test was performed. Prior to the matching, pseudo R 2 was 0.056, and the LR test outcome was 499.02, which is significant at a statistical level of 1 %. The average and median of the standardized errors were 22.1 % and 15.4 %, respectively. After the application of different matching methods, pseudo R 2 decreases to 0.002 and below. The results of LR test are not statistically significant, and the average and median of the standardization errors are not higher than 2.3 %. These results indicate that the PSM significantly weakens the systematic differences in explanatory variables and that the matching process is successful. To ensure matching quality, the paper also establish the probability distribution of the propensity scores of treatment group and control group before and after matching. As shown in Fig. 3 , the difference in the probability distribution of the two groups of samples prior to matching is extremely significant, and the overlap interval of the two groups of samples is narrow. After matching, the difference between the two groups of samples is significantly smaller, with a considerable range of overlap interval. In this way, the proportion of effective samples lost is very low, and the matching quality is satisfactory. This result further confirms that the PSM method can correct the sample selection bias and more accurately assess the causal effect between food safety perception and farmers’ happiness. Finally, this paper measures the ATT of two sets of samples after matching ( Table 4 ), although different matching methods produce different quantitative results. Qualitatively, the results of the different matching methods are consistent. That is, after observing systematic differences between samples, food safety perception and farmers’ happiness are significantly positively related. It is worth noting that in the process of radius matching, the matching accuracy constantly improves and reduces the caliper range. Although there is a certain “loss” of samples, the ATT estimation results remain robust. In addition, as shown in Table A2 , this paper uses IPW method and IPWRA method to calculate ATT. The results reveal that ATT as obtained by IPW method and IPWRA method differs from that obtained by PSM method in numerical level but is highly consistent in significance and direction. This outcome also confirms the robustness of the empirical results. Endogeneity discussion Based on the preceding discussion of the potential endogeneity problems of the model, this paper uses the RBOP model and the CMP method to analyze and reduce the potential impact of endogeneity problems. As shown in Table 5 , generally, the estimation results obtained by the two methods are very close, which reveals the consistency and robustness of the estimation results. More specifically, in the first stage, the frequency of farmers reading newspapers is significantly positively correlated with food safety perception, indicating that the instrumental variable satisfies the correlation condition. Further, ρ με is significant at the statistical level of 1 %, indicating that the model has endogeneity problems and that the RBOP model is superior to the ordinary model. Based on the results of the second stage, food safety perception is significantly positively related to farmers’ happiness. This outcome is consistent with the preceding estimation results, indicating that these results are robust and reliable. Robustness checks Add control variables Both the independent variable and the dependent variables are subjective variables. Hu (2019) notes that the largest challenge in explaining one subjective variable with another is that these subjective variables may have a common basis for potential psychological traits, which may result in falsely related problems. He further emphasizes that if psychological traits are independent, that is, two subjective variables are generated by different psychological traits, they will not be constrained by the same psychological trait and cause confusion and bias. Although food safety perception and happiness are both subjective evaluations of respondents, there are significant differences in their psychological basis. The perception of food safety often “tells the truth” with stronger relevance, mostly regarding the respondents’ actual feelings on food safety issues or their attention to policy information and personal observation. In contrast, happiness is a quite comprehensive inner feeling. Additionally, the psychological state of the respondents is likely to affect food safety perception and happiness. Therefore, this paper attempts to add psychological state variables in the robustness test. In the CSS2013 questionnaire, respondents are asked, “Overall, how often do you feel worried (scared)?” They answered by choosing from the options never, rare, sometimes, often, always, which are assigned scores of 1, 2, 3, 4 and 5, respectively, as proxy variables of the mental state. This paper further add the fairness perception variable to the test. Respondents were asked, “What do you think of the overall social equity situation?” The response options were very unfair, not fair, fair, very fair, which are assigned scores of 1, 2, 3 and 4, respectively. As shown in Table A3 , mental state and fairness perception have a significant impact on happiness. When the variables of mental state and fairness perception are added, the regression coefficient of food safety perception variable decreases but still has a significant positive impact on happiness. Omitted variable test In addition to the previously mentioned addition of mental state and fairness perception variables for robustness testing, this paper also refers to the method proposed by Ref. [ 43 ] to test the unobservable variables in the regression [ 43 ]. demonstrated that when there are unobservable omitted variables in the model the estimate = can be used to obtain a consistent estimate of the true coefficients. refers to the maximum goodness of fit of the regression equation when the unobservable omitted variables can be observed, and refers to the selection balance between observable and unobservable variables. Specifically, there are two methods for testing as follows. In method (1), the paper assume that is a certain value (generally, is 1.3 times the goodness of fit of the current regression). On this basis, the paper calculate the value of that makes . If is greater than 1, the estimation result passes the test. Method (2) is similar to method (1). When the paper assume that is a certain value, if = falls within the 95 % confidence interval of the estimated parameters, the estimated results pass the test. As shown in Table A4 , the results of this paper are robust and reliable according to the test of omitted variables. Regression analysis based on CSS2017 and CSS2021 In addition to the CSS2013 data, the CSS2017 and CSS2021 data released by the Institute of Sociology of Chinese Academy of Social Sciences also involves variables related to food safety and happiness. Therefore, the paper use the CSS2017 and the CSS2021 data to test the robustness of the regression results. It is worth noting that, slightly different from the CSS2013, the CSS2017 data does not directly relate to respondents' happiness, but examines respondents’ life satisfaction. Specifically, the questionnaire asks respondents: Overall, how satisfied are you with your life. Respondents choose an integer from 1 to 10, with 1 being very dissatisfied and 10 being very satisfied. Using the life satisfaction index to measure happiness is also a method commonly used in existing literature [ 44 ]. Although the CSS2021 sets variables for happiness and life satisfaction, these two variables are set differently from CSS2013, and due to variable limitations (happiness and life satisfaction are random a and b volumes, with sample size halved), CSS2013 is still used as the benchmark regression analysis. As shown in Table A5 , the estimation results of OLS regression and Oprobit model based on the CSS2017 and CSS2021 show that farmers’ food safety perception exerts a positive and significant impact on their happiness or life satifacation. Even after adding other explanatory variables and regional dummy variables, the finding of a positive relationship between food safety perception and happiness or life satifacation confirms the results presented in the above part of Table 3 . In addition, as shown in Table A2 , this paper uses IPW method and IPWRA method to calculate ATT ( Table A3 in the Appendix). The results reveal that the ATT obtained by IPW method and IPWRA method differs from that obtained by PSM method in numerical level but is highly consistent in significance and direction. This finding further confirms the robustness of the empirical results. Further analysis Although the paper have concluded that food safety perception has a significant positive effect on farmers’ happiness, the paper has only obtained the average effect of the entire sample, without considering the heterogeneity between groups. Therefore, this section of the paper focuses on educational and intergenerational differences between subgroups to develop a more detailed discussion. In terms of educational differences, this paper divides farmers into two groups according to education level: those who have received junior high school education or below (lower education level group) and those who have received senior high school education or above (higher education level group). Within the sample range, there are 1082 farmers with higher education (15.25 %) and 6012 farmers with lower education (84.75 %). As shown in Table 6 generally, the impact of food safety perception on the happiness of farmers with different education levels is significant at the statistical level of 1 %. Specifically, the impact of food safety perception on the happiness of farmers with a higher education level is more obvious, which indicates that food safety is more important for farmers with such education levels. A possible explanation for this result is that highly educated farmers know more about food safety issues, and because they have a better understanding of these issues, they pay more attention to them. Therefore, food safety perception plays a more important role with respect to their happiness. In terms of intergenerational differences, this paper divides the sample into three groups according to age: young, middle-aged and elderly. Here, young people are farmers under 40 years old, middle-aged farmers are 40–60 years old, and elderly farmers are over 60 years old. Within the sample range, there are 2504 young farmers (34.43 %), 3488 middle-aged farmers (47.96 %), and 1281 elderly farmers (17.61 %). As shown in Table 6 , food safety has a significant positive impact on the happiness of farmers of different ages. From the regression coefficient perspective, food safety has the most significant impact on the happiness of elderly farmers, whereas the impact on the well-being of young and middle-aged farmers is approximately the same. One reason why elderly farmers are more sensitive to food safety may be that with increasing age the health of the elderly is not as good as that of young and middle-aged individuals. Life experience enables the elderly to better understand the truth that illness “comes from the mouth”. Therefore, the elderly are significantly more sensitive to food safety issues than young and middle-aged individuals. In conclusion, there is educational and intergenerational heterogeneity in the impact of farmers’ food safety perception on happiness. Therefore, in the process of filling the gaps in rural food safety, it is necessary to mobilize highly educated farmers to become food safety regulators and strengthen the promotion of food safety among the elderly in rural areas.

Conclusions and insights This paper systematically examines the impact of food safety perception on farmers' happiness, using the data collected from the China Social Survey in 2013. The empirical results show that farmers' perception of food safety is significantly positively related to their level of happiness, and this effect continues after adding control variables and considering regional heterogeneity. Besides, considering that farmers' perception of food safety is the result of self-selection, the paper use PSM, IPW, and IPWRA methods to correct sample selection bias. This paper control for potential endogeneity problems using the RBOP model and the CMP method. Given the problems of omitted variables, mental state variables and fairness perception variables are added to the model, and the [ 43 ] method is used to test the impact of the omitted variables on the empirical results. The final conclusion remains stable. Furthermore, the results of the expansibility analysis further indicate that educational and intergenerational differences affect the impact of food safety perception on farmers’ happiness. Food safety perception is even more important in the more highly educated, middle-aged and older farmers. The core contribution of the study lies in its use of authoritative empirical evidence to confirm the positive effect of food safety perception on farmers' happiness and to suggest an important means for farmers to find their “road to happiness”. At present and for a period in the future, continuing to strengthen food safety and sparing no effort to advance food safety strategies should be an important policy focus for achieving farmers’ happiness. Specifically, the paper must compensate for food safety shortcomings in the countryside, strengthen the establishment of professional food safety teams at the grass-roots level, and gradually improve food safety supervision in countryside. At the same time, it is of substantial significance to disseminate food safety publicity, improve the perception of food safety risks of farmers (particularly the middle-aged and elderly groups), advocate the idea that everyone is responsible for food safety supervision, and mobilize farmers (particularly those with higher education levels) to become food-safety “supervisors”. In the long run, the policy makers should establish a food-safety supervision system based on strict laws, strict supervision, severe punishment and a serious accountability mechanism to truly realize the “safety on the tip of the tongue” of farmers and guarantee the “road to happiness” for farmers. Finally, it should be pointed out that there are still some shortcomings in this paper. Firstly, farmers' understanding of happiness varies from person to person, and their perception of food safety also differs. However, due to the fact that CSS databases are not tracking data, the paper cannot capture the dynamic changes in farmers' food safety perception and happiness, making it difficult to more accurately identify the causal effects between the two variables. Secondly, China is promoting food safety regulations, and different regulatory models and intensities may lead to the changes in farmers' food safety perception. However, due to data limitations, the paper cannot examine the impact of regulations on farmers' perception of food safety. Thus, the future research should conduct tracking research on farmers, and attempt to develop a questionnaire to examine the impact of different regulatory models and intensities on farmers’ food safety perception and happiness.

Zhongkun Zhu and Chenxin Leng are co-first authors of this paper. Although the determinants of individuals' happiness have been widely examined in the literature, little is known regarding whether and how food safety perception affects farmers' happiness. To fill this research gap, this paper examines the impact of food safety perception on happiness among Chinese farmers, utilizing open-access data collected through the Chinese Social Survey project in 2013, 2017 and 2021. This study focuses on Chinese farmers as the research subject, attempting to analyze the “happiness code” from the perspective of food safety, which supplements the literature on happiness and provides reference for protecting the rights of low-income groups and promoting food safety strategies in developing countries. To address sample selection bias, this paper employs the recursive bivariate ordered probit (RBOP) model and conditional mixed process (CMP) method. The results reveal that the perception of food safety exerts a positive and statistically significant impact on farmers' happiness in China. In addition, food safety perception is more important among middle-aged and elderly farmers and among those with higher education. Thus, the policy makers should continue to make up for the shortcomings of rural food safety work and extend regulatory measures to rural areas. They also need to take efforts to strengthen food safety promotion, enhance farmers' safety awareness, and safeguard farmers’ “safety on the tongue”. Keywords

Literature review Theory as the ground of this study Happiness is the ultimate goal of human beings, which is an overall evaluation of personal quality of life and subjective feedback on their inner state [ 5 , 6 ]. Happiness is also a permanent topic among scholars. More than 2000 years ago, Aristotle proposed that happiness was the ultimate end or object of human life and the epitome of all good [ 7 ]. Early economics, especially classical economists, believed that economic growth and wealth increase were the only factors that increased people's happiness. They established the foundation for studying economic activities on people's subjective psychological feelings, and regarded enhancing people's well-being and happiness as the ultimate goal of economic activities. Adam Smith, believed that economics should aim for the happiness of human beings as its ultimate goal. Utilitarian master [ 8 ] proposed on the basis of cardinal utility theory that the focus of economics was on how to maximize people's happiness. Since the 1920s [ 9 ], has established welfare economics, and welfare economists have replaced “happiness” with “welfare” to study economic activities. However, after the 1930s, as ordinal utility theory gradually replaced cardinal utility theory, the concept of “happiness” gradually faded away in economics, and utility gradually lost its connotation of happiness. In the 1950s, psychologists began to focus on the study of happiness. More recently, positive psychology, a branch of psychology that aims to improve individual happiness, has emerged [ 10 , 11 ]. [ 12 ] pioneered the concepts of decision utility and experiential utility, drawing on positive psychology. They pointed out that in current economic decision-making theory, utility refers to decision-making utility, while actual feelings such as happiness and pain are experiential utility. From this the development of positive psychology reintroduces the exploration of the essence and sources of happiness into the framework of scientific analysis. In 1974 [ 13 ], directly focused on happiness in economic research and creatively proposed the Easterlin Paradox. He observed that within a country, people with higher incomes find it easier to obtain happiness, but at the national level, the average happiness of a country does not improve with the growth of per-capita GDP, thus creating a clear paradox. This paradox has created a precedent for the systematic study of happiness and a new direction in economics: happiness economics. Since the emergence of the Easterlin Paradox, scholars have tried to crack the happiness code from different perspectives [ 14 ]. From absolute income to relative income to income inequality, income has been an important focus of scholarly attention [ 5 , [15] , [16] , [17] ]. In addition, there have been a variety of studies on the relationship between happiness and socio-demographic factors, such as age, gender, education, marital status, health status, housing status and religious beliefs [ 6 , [18] , [19] , [20] ]. Macroeconomic factors of substantial significance to happiness include unemployment, inflation and environmental pollution [ [21] , [22] , [23] ]. In recent years, institutional factors, such as democratic development and government quality, have been linked to happiness [ 24 , 25 ]. In addition, the economic impact of happiness has received more and more attention [ 26 , 27 ]. A number of studies discusses the relationship between food and happiness [ [28] , [29] , [30] ], but few papers focus on the impact of food safety on individuals’ happiness. Food safety Food safety affects the entire nation and has long been a concern of all sectors of society. As time has passed, the concept of food safety has been enhanced, and the perception of food safety worldwide has been evolving. Overall, the focus of food safety perception has undergone a transition from food quantity safety to food quality safety. In 1974, the Food and Agriculture Organization (FAO) first defined food safety as the amount of food required to maintain people's basic needs. In 1996, the World Health Organization (WHO) regarded food safety as a guarantee of consumer health when food was produced and consumed according to original purpose. In 2003, FAO/WHO further noted that food safety referred to all hazards that may make food harmful to health. In addition, foreign scholars have put forward their own definitions of food safety. According to Ref. [ 31 ]; food safety refers to the opposite of food risk in a narrow sense, that is, the possibility of eating a food without contracting a disease. In a broad sense, food safety also includes the nutritional quality of food, and more extensive attention paid to unusual food characteristics [ 32 ]. stress that food safety means that the health of consumers may be harmed by food as a result of chemical residues, antibiotics or food additives in food. Over time, food safety issues have also become a focus for domestic scholars [ 33 ]. propose that since China's reform and opening up, the trajectory of change in China's food safety concerns can be described as “Food quantity safety→Food quantity and hygiene→Food quality safety→Food quality and nutrition safety”. With the continuous increase in the consumption level of urban and rural residents, the desire of urban and rural consumers has shifted from the pursuit of food quantity to the pursuit of food quality, safety and health. As the understanding of food safety has increased, relevant research in the field of food safety has been constantly emerging. Scholars have offered many insights on the meaning, causes and supervision of food safety issues. In terms of food safety supervision, scholars have engaged in numerous discussions (Martinez et al., 2007; [ 2 , 34 ]. The root cause of food safety problems is market failure caused by information asymmetry. Information asymmetry tempts enterprises to imitate low-quality competitors, which can trigger an industrial food safety crisis (Rouviere & Soubeyran, 2008). The “short-sighted cognitive bias” of enterprises amplifies the “false impulse” to produce fraudulent and inferior products [ 2 ]. From the perspective of government regulation [ 34 ], emphasize that the policy burden results in the weakening of regulation, which can lead to an absence of government regulation. Most previous studies believe that China's food safety governance should adopt the basic strategy of “combination and coordination of compatible short-term containment measures and long-term strategies” to overcome a food safety crisis [ 2 ]. Short-term measures focus on the establishment of a company blacklist system, with regulations regarding repeated offenses, including heavy penalties and supervision mechanisms for offending companies. Long-term measures stress the improvement of relevant laws and information-disclosure mechanisms, the enhancement of the food regulatory system and government-internal governance, and the establishment of third-party governance structures, such as media and industry associations (Zhou & Wang, 2013). Zhou & Wang (2013) further propose that in addition to the construction of a supervision system, the food safety basic education system should be improved and a food safety integrity system established. Despite the wealth of research in the field of food safety, studies on the relationship between food safety perception and happiness remain scarce, and even quantitative assessments of the effects of food safety on individual or family welfare are rare [ 35 ]. analyze the potential relationship between food safety and farmers' production technical behavior choices based on 331 household questionnaire data from Guangdong Province. From the perspective of producer welfare, Wen & Han (2018) examine the “yield premium” effect of enterprise participation in food safety regulation. In terms of the relationship between food safety and happiness, Li & Wang (2015) use food safety as a control variable to investigate the influencing factors of happiness, which is not targeted. Tang (2017) uses 2016 survey data of urban residents in Jiangsu and Shandong provinces of China to investigate the impact of food safety perception on happiness. Tang's study represents a useful examination of the relationship between food safety and happiness. In contrast with this paper, Tang's study mainly focuses on urban residents of Jiangsu Province and Shandong Province, while failing to address the endogeneity problem in detail. Thus, the robustness of Tang's conclusions must be reconsidered. In summary, there has been a lack of attention and insufficient explanation regarding the important questions of how food safety affects people's happiness, particularly with respect to whether and to what extent food safety affects farmers' happiness. Therefore, the study attempts to analyze the “happiness password” from the perspective of food safety, which is an important supplement to literature on happiness. Hypothesis As mentioned earlier, happiness is the ultimate goal of people's lives, and it can be said that happiness comes from a sense of inner satisfaction and security. And safe food supply is the most basic human demand, and in China, there are still some farmers whose food safety has not been fully met. It is not difficult to infer that food safety will bring joy, satisfaction, and security to farmers, thereby enabling them to achieve happiness. Therefore, the paper proposes a research hypothesis: Hypothesis: Food safety perception can help improve farmers’ happiness. Data availability statement The data that support the findings of this study are available from the corresponding author, Chenxin Leng ( lengchenxin@163.com ), upon reasonable request. CRediT authorship contribution statement Zhong-kun Zhu: Writing - review & editing, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation. Chen-xin Leng: Writing - review & editing, Writing - original draft, Visualization, Validation, Supervision, Software, Resources, Formal analysis, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CC BY

no

2024-01-16 23:42:02

Heliyon. 2023 Dec 19; 10(1):e23868

oa_package/18/e8/PMC10788500.tar.gz

PMC10788501

38226243

Introduction Cyclosporine A (CsA) is the immunosuppressor most frequently used in transplant surgery and in the treatment of autoimmune diseases because of its specific inhibiting effect on the signal transduction pathways of cell T receptor. CsA-induced kidney and liver damage is the main clinical problem associated with CsA therapy in which oxidative stress (OS) is the conceivable accountable mechanism. Therefore, the use of antioxidants is a useful tool to reduce CsA adverse effects [ 1 , 2 ]. Vitamins can protect our body against a lot of diseases, like beriberi, night blindness and scurvy. Most countries allow food additives with vitamins extracted from plants as an optimal intake of vitamins [ 3 ]. Micronutrient supplementation guidelines were disseminated by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO) to provide the best approach for plant additives [ 4 ]. To fully exploit the vitamins in humans, phytosome technique was used. Phytosome is one of the novel lipid-based vesicular delivery systems used in the formulation of botanical-based nutraceuticals [ 5 ] and medicines [ 6 , 7 ]. Phytosome can improve bioavailability and absorption in the gastrointestinal tract for bioactive compounds extracted from herbs, such as vitamins and minerals [ 8 ]. Phytosomes also enhance antimicrobial and antioxidant activities of nutraceutical compounds and protect bioactive compounds during food processing, heat treatment (sterilization & pasteurization) and storage [ 9 ]. The interaction between phosphatidylcholine molecules and micronutrients via hydrogen bonds increases the stability of phytosomes and forms a water and lipid soluble complex [ 10 ]. However, the phytosome technique is underresearched as a novel food delivery system. During food manufacturing and storage there are main disadvantages such as insolubility in aqueous phase, strong odor, biodegradation, alkaline conditions, and sensitivity to heat. These were reasons for using a novel method like phytosome encapsulation [ 11 ]. The innate and adaptive immune systems are the two main immune system components. The effectiveness of a person's immune system is significantly influenced by the nutritional status of these systems. The body's capacity to maintain innate immune responses may be compromised by under-nutrition because of insufficient consumption of micronutrients [ 12 ]. Nutritional approaches to support immune system function are frequently overlooked in public health talks on immunity and illnesses, although nutrition is key in immune function. Numerous vitamins, such as vitamins A, B6, B12, C, D, and E, as well as trace minerals, such as zinc, iron, selenium, magnesium, and copper, promote the innate and adaptive immune systems. Immune function is negatively impacted by micronutrient deficiencies or inadequate status, which might lower resistance to infections [ 13 ]. Micronutrients' molecular functions in immune system have lately received extensive description. Most micronutrients play pleiotropic actions in promoting immunological health. Regarding innate immunity, the vitamins and minerals enhance the proliferation, differentiation, and motility/chemotaxis of innate cells, as well as the phagocytic and killing (e.g., oxidative burst) activities of neutrophils and macrophages, the induction of inflammation and its recovery (e.g., cytokine production and antioxidant activity). Additionally, they promote adaptive immunity through the development of memory cells, cytokine synthesis, antibody formation, lymphocyte differentiation, proliferation, and homing [ 14 ]. In addition to being utilized in modern medicine in East Asia, star anise ( Illicium verum Hook f) is regarded as a key species in Traditional Chinese Medicine. The presence of beneficial secondary metabolites like sesquiterpenoids, monoterpenoids, phenylpropanoids, sesquilignans, shikimic acid, seco-prezizaane-type, sesquiterpenoids, and flavonoids determines the biological activity of star anise. Recent pharmacological research on star anise essential oil has validated its antioxidant, antibacterial, and antifungal properties [ 15 , 16 ]. Ice cream is a delicious and popular frozen dairy product appreciated by a very broad spectrum of consumers, made from milk and/or milk products combined with other ingredients such as sweeteners, emulsifiers, stabilizers and flavouring agents [ 17 ]. Frozen functional dairy products are very important vehicles of bioactive ingredients for enhancing nutritional health benefits [ 18 ] . There are different types of ice cream with new functional ingredients that are available on the markets worldwide. In addition, numerous ice cream formulations with functional properties have been developed, for example, ice cream with natural antioxidants [ 19 ] , with dietary fibers and probiotics [ 20 ] , with polyunsaturated fatty acids [ 21 ] , and with vitamins and minerals [ 22 ] . This study aims to investigate the effect of flavoured nanophytosomes loaded with vitamins on the immunosuppressive CsA-induced liver and kidney injury in rats and to develop ice cream as a functional food fortified with vitamins-loaded flavoured nanophytosomes (to protect the bioactive vitamines during food processing) as an antioxidant and an anti-inflammatory agent against CsA-induced liver and kidney injury, and to flavour the final product with star anise oil to overcome the major problems of off-flavour and unacceptable taste.

Materials and methods Materials Star anise ( Illicium verum ) was procured from a specialized aromatic plant market in Cairo – Egypt. Vitamins (A, E, D, B complex, Folic acid and C) and element (Zn) were procured from local pharmacy in Cairo – Egypt. Soy lecithin granules were obtained from Solgar, Inc. (Leonia, NJ 07605, USA). All chemicals and solvents for HPLC and GC mass were from Sigma-Aldrich (Sternheim, Germany). Isolation of star anise essential oil Hydro-distillation method was used to isolate the star anise essential oil in the Clevenger's apparatus for 3 h [ 23 ] . Determination of total phenolic content and antioxidant activity Total phenolic content and reducing power assessment DPPH radical scavenging activity were determined according to Zhang et al., [ 24 ] and Bose and Kim [ 25 ] , respectively. Gas chromatography-mass spectrometry (GC – MS) analysis The volatile compounds were determined using gas chromatography coupled with mass spectrometry. The instrument used was a Hewlett–Packard model 5890 GC coupled with a Hewlett–Packard-MS (5970) MS. The analysis was performed using a DB-5 column with dimensions of 60 m × 0.32 mm i.d. × 0.25 μm film thickness. The temperature program for the oven started at 50 °C for 5 min and then increased from 45 to 250 °C at a rate of 5 °C/min. The flow rate of helium gas was 1.1 ml/min. The sample size used was 2 μl with a split ratio of 1:10, and the injector temperature was set at 220 °C. Mass spectra were obtained in the electron impact mode (EI) at 70 eV, and the scan m / z range was from 39 to 400 amu. The identification of isolated peaks was achieved through matching with data from the mass spectra library (National Institute of Standard and Technology, NIST), comparison with published data, and utilizing authentic compounds [ 26 ]. Preparation of flavoured vitamins-loaded nanophytosomes Nanophytosomes technique (thin layer hydration) was used to encapsulate vitamins (A, E, D, B complex, Folic acid and C), element (Zn) and their mixture according to Nazari et al. [ 11 ], with some modification. The ratio of soy lecithin and vitamins was 1:1. 60 mg. Vitamins and same amount of soy lecithin were dissolved in absolute ethanol and added to a round flask of 100 ml, then evaporated at 60 °C/60 min by a vacuum rotary evaporator (Heidolph, Laborota 4002 control, Germany) to remove all ethanol and form a thin dry film at the round bottom of the flask. Then, 10 ml of distilled water (60 °C) was added in a round flask to hydrate the thin dry film, then star anise oil (3 %) was added and homogenized using probe sonication (Hielscher – 130 W, 20 kHz, Germany) (15 min cycles with 30 s rest between cycles). The size of phytosomes was decreasing. Characterization of vitamins-loaded flavoured nanophytosomes Particle size and zeta potential The particle size and zeta potential of VFnPs were measured using the Malvern Zetasizer Nano Z, (Worcestershire, UK) Transmission electron Microscopy (TEM) The morphology of nanophytosomes was studied and visualized using transmission electron microscopy (TEM) (JEM-2100 Electron Microscope Instruments, China) after dry sample coating with gold (DST3, Nanostructured Coating Co., Tehran, Iran). Loading parameters Encapsulation efficacy (EE) of VFnPs was calculated using the centrifugation method [ 27 ]. An amount of nanophytosomes was centrifuged (3 k-30, Sigma, Germany) at 15000 rpm/15 min/4 °C. The free vitamins were determined by HPLC and the following equations were used to calculate EE: HPLC conditions The column Agilent C18 (100 mm i.d., 3.5 μm × 4.6 mm) was used to determine free vitamin. The methanol: acetonitrile (65:35) was used as a mobile phase and the flow rate was 1 ml/min 20 μl of the sample solutions was injected. The DAD was adjusted to 295 nm. The column temperature was 40 °C. Biological study Animals We obtained adult male Wistar rats from the Animal Care Unit of the National Research Centre in Egypt that were 120 days old and weighed between 150 and 200 g. Animals were kept in plastic transparent cages in the animal house with lights on between 7:00 a.m. and 7:00 p.m., a room temperature of 22± 2 °C, and a humidity level of 50 ± 10 %. Food and water were freely available to the rats. Animals' diet AIN-93 balanced diet: 58.5 % maize starch, 5 % fibre, 3.5 %, 10 % corn oil, 10 % sucrose, 12 % casein-supplemented protein was mixed and contained 1 % AIN-93 vitamins and AIN-93 salt according to Reeves et al. [ 28 ] . Evaluation of the flavoured vitamins-loaded nanophytosomes for improving immunity and protecting the liver against cyclosporine-A The animals were kept under observation for about 7 days before starting the experiment for acclimatization. Then, the animals were classified into 3 groups (N = 6/group) according to the treatment schedule. The control normal group received orally 1 ml saline (vehicle), immunosuppressive group received cyclosporine-A (CsA) dissolved in saline orally in a dose of 15 mg/kg body weight daily for 8 weeks [ 29 ] . The third group received CsA simultaneously with the VFnPs (3 mg of the vitamins’ nanophytosomes) daily for 8 weeks. The Ethical Committee for Medical Research of the National Research Centre in Egypt approved the experimental protocol (Code No. 19182.) At the end of the trial period (8 weeks), Diethyl ether was used to anaesthetize the animals. After that, blood was drawn from the retro-orbital venous plexus and placed into EDTA-free tubes to separate the sera, which were then chilled to −80 °C for further analysis. The animals were then killed via cervical dislocation, and the liver was removed right away. Biochemical analyses According to Raeeszadeh et al. [ 30 ], the ferric reducing antioxidant power (FRAP) method, was used to determine plasma total antioxidant capacity (TAC). This method measured the plasma's capacity to lower ferric ions. The FeIII-TPTZ combination has the maximum optical absorption at 593 nm at an acidic pH when it is reduced to FeII and produces a blue color. Colorometry and using UVPC spectrophotometer (Jasco V-730, serial No. A 112361798, Japan), serum total protein, the activities of aspartate transaminase (AST), and alanine transaminase (ALT), creatinine, urea, and albumin, respectively were determined according to the methods described by Rheinhold & Seligron [ 31 ] , Reitman & Frankel [ 32 ] Larsen [ 33 ] , Fawcett and Scott [ 34 ] , and Doumas et al. [ 35 ] . Liver homogenates (10 % w/v) in a cold homogenization buffer (100 mM potassium phosphate buffer, pH 7.4) were prepared and centrifuged, then the supernatants were analyzed for tumor necrosis factor-alpha (TNF-α), malondialdehyde (MDA), glutathione S. transferase (GST), catalase (CAT), and superoxide dismutase (SOD) activity. Liver TNF-α was determined using an Eliza kit (Cat N.: E-EL-R2856) (Elabscience Biotechnology Co., Ltd, Wuhan, China). MDA was determined using thiobarbituric acid (TBA) method. Briefly, 1 ml trichloroacetic acid (25 mmol/L) were added to 200 μl of the supernatants, mixed for 1 min before being submerging in a bath of boiling water. Then, a measurement of the pink solution's absorbance at 532 nm was carried out. After preparing various MDA concentrations in N-butanol (0.2 μM–2 μM), a standard curve was prepared [ 36 ] . The measurment of GST activity was based on the conjugation of 1-chloro-2,4-dinitrobenzene (CDNB) with reduced glutathione. At 340 nm, absorbance increases in parallel with conjugation [ 37 ] . According to Beers and Sizer [ 38 ], the spectrophotometric measurement of H 2 O 2 degradation, which was directly correlated with the decrease in its absorbance at 230 nm per time unit, used as the basis for an estimation of CAT activity. The role of SOD in converting the damaging radical O2-superoxide to molecular oxygen and hydrogen peroxide during oxidative processes was used as the basis to assess its activity [ 39 ]. Serum cluster of differentiation 4 (CD4), cluster of differentiation 8 (CD8), interferon-gamma (INF-γ), interleukin 6 (IL-6), interleukin 1-beta (IL-1β) and toll-like receptor 4 (TLR 4) were determined using rats CD4 (Cat. N.: E-EL-R2459), CD8 (Cat N.: E-EL-R0219), INF-γ (Cat N.: E-EL-R0009), IL-6 (Cat N.: E-EL-R0015), IL-1β (Cat N.: E-EL-R0012) and TLR 4 (Cat N.: E-EL-R0990) enzyme-linked immunosorbent assay kits (Elabscience Biotechnology Co., Ltd, Wuhan, China). Ice cream formulation The ice cream mixes (2 Kg each as shown in Table 1 ) were formulated to contain 12 % fat, 14 % SNF, stabilizers 0.5 % and 16 % sugar. The ingredients of all treatments were homogenized well and heated at 90 ± 1 °C/5 min [ 40 ]. The mixtures were cooled to 5 °C. Then, the mixtures were divided into three parts: the first one as a control (C). The second one (T1) was formed by adding 0.166g of VFnPs. The third one (T2) was formed by adding 0.330g of VFnPs (This concentration according to daily intake from vitamins). The ice cream mixes were prepared according to Mabrouk et al [ 18 ] . Physiochemical analysis of ice cream Specific gravity and weight per gallon Specific gravity and weight per gallon of mixes and the ice cream were calculated according to Sadek et al. [ 41 ] and Arbukle et al [ 40 ] , respectively . pH values, titratable acidity and ash contents% The pH values, titratable acidity and ash contents of ice cream samples were measured according to Mabrouk et al. [ 18 ] , AOAC [ 42 ] , respectively. Overrun and melting rate The overrun and melting dawn of ice cream was determined according to Akın et al. , [ 43 ]. Sensory evaluation of ice cream Ice cream samples were sensory evaluated after 24 h hardening at 20 °C by ten well-trained panellists. The samples were scores for flavour (45), body &texture (35), colour (10) and melting quality (10) as suggested by Arbukle et al (986). Statistical analysis For statistical analysis SPSS (20) was used., Using ANOVA one-way the data were statistically evaluated, and the mean standard error was reported, then the Duncan test followed. The statistical significance of the difference utilizing probability is P ≤ 0.05.

Results and discussion The total phenolic content and antioxidant activity of star anise oil Results shown that the amount of total phenolic content was 265.01 ± 1.50 μg GAE gallic acid equivalent/ml. Anise oil showed good reducing power (0.188 ± 0.01 mg Vit C equivalent/ml). The reducing power of essential oil might be due to their hydrogen donating ability. The components present in the oil could act as good reductant. The total phenolic content of star anise oil showed positive correlation with its reducing capacity [ 44 ]. Star anise oil has strong scavenging activity towards DPPH radical (89.72 % ± 2.03). Our results agreed with Singh et., al. [ 45 ] , who reported that the method is based on the reduction of DPPH radicals and formation of non-radical form (DPPH-H), and that star anise oil is able to perform this reaction and is considered as radical scavenger and hence antioxidant. Star anise oil showed the strongest scavenging power that was even higher than BHA and BHT [ 45 , 46 ] . Figure (1) Illustrates the GC-MS chromatogram of Egyptian star anise extracted by hydro-distillation and the nine identified compounds listed in Table (2) represent about 97.6 % of the total detected compounds. The major compounds were anethole (63.47 %), oleic acid (13.72 %) and linoleic acid (11.99 %). The main compounds in our results matched with results of the Indian and Italian star anise oil [ 47 , 48 ] . Characterization of nanophytosomes Particle size and zeta potential In this study, the particle size (nm), PdI, zeta -potential (mV) and encapsulation efficiency (EE) of VFnPs are shown in Table 3 . According to these results, a variation was found between particle size for vitamins (A, D, E, C, F, B), Zn and Mixture loaded nanophytosomes were 213.6, 81.36, 228.5, 214.8, 107.3, 168.4167.4, and 149.4, respectively. These results clearly indicate that the vitamins maximized the size of the VFnPs. Gibis et al., [ 49 ] stated that the size of the phytosomes was dependent on the quality of the materials loaded in the phytosomes, which explains the present finding. Phytosomes agglomerated into nano-size micelles (approximately 100–300 nm) [ 50 ]. The particle distribution index (PDI) defines the particle distribution curve. The obtained results indicated almost the same PDI for different percentagesof the loaded vitamins except for the largest one (vitamin B), which showed narrower size distribution of the formed phytosomes. The zeta-potential values of the VFnPs ranged from - 11.2 to - 34.3 mV. This might be because vitamins (positive charge) interacted with the phosphate group in phosphatidylcholine (the negatively charged) giving the VFnPs (negative charge). In general, zeta-potential values of above −30mV or under +30 mV were observed to protect particles and minimize electrostatic and congregating force between nano-phytosomes, which might create large collection of nanophytosome nanovesicules [ 51 ]. Encapsulation efficiency (EE) Encapsulation efficiency (EE) was determined via calculation of free vitamins content in VFnPs. A smaller amount of free vitamins content means high encapsulation efficiency. There was no significant (p < 0.05) difference between EE of VFnPs. To assess the effectiveness of nanocarriers in delivering active substances, EE is a critical factor in nano-based delivery systems [ 52 ]. The achieved results of VFnPs, that were prepared via three different formulations and showed the exceptional capacity of nano-phytosomes as carriers, are shown in Table 3 . Nazari et al., [ 11 ] investigated the garlic essential oil (GEO) loaded in nano-phytosomes as a new phytochemicals delivery vehicles using three varied techniques, and found that GEO nano-phytosomes using homogenization-probe sonication (the same technique used in this study) is promising with a size of 115 nm and EE of 86.00 % (which is similar to the values found for the vitamins loaded nano-phytosomes presented in this study). Transmission electron microscopy (TEM) Transmission electron microscopy (TEM) was used to study the morphology of the VFnPs, which revealed spherical vesicles in all pictures ( Fig. 2 ). Moreover, the particles size distribution was existence of certain aggregates, indicating was homogemized, which is consistent with the PDI values reported ( Table 3 ). The size for particle via image is agree with particle size which measured using Malvern Zetasizer that have reported a size distribution between 100 and 300 nm for phytosomes used in the encapsulatation [ 53 , 54 ]. Role of the vitamins-loaded flavoured nanophytosomes in improving immunity, antioxdant and protecting the liver and kidney against cyclosporine-A According to Table 4 , the control positive group reported considerably (P > 0.05) higher values for AST, ALT, creatinine, and urea than the normal control group. Compared to the normal control group, the results for total protein and albumin dramatically (P > 0.05) fell in the control positive group. Rats given the VFnPs had lower (P > 0.05) levels of AST, ALT, creatinine, and urea than the control positive group. Rats given the VFnPs had greater (P > 0.05) total protein and albumin values than the control group of positive animals. Table 5 shown that the total antioxidant, liver GST, liver SOD, and liver catalase values were considerably (P > 0.05) lower in the control positive group than in the normal control group. As opposed to the normal control group, the control positive group's liver MDA and TNF- levels considerably (P > 0.05) rose. The liver GST, SOD, and catalase values in VFnPs-treated rats were higher (P > 0.05) than those in the control positive group. Rats given the vitamin-loaded nanophytosomes had considerably (P > 0.05) lower liver MDA and TNF levels than the control-positive group. According to Table 6 , the control positive group recorded considerably (P > 0.05) higher CD8, INF-γ, IL-6, IL-1β, and TLR4 values than the normal control group. As opposed to the normal control group, the CD4 value in the control positive group considerably (P > 0.05) reduced. Rats given the VFnPs had lower levels of CD4, INF- γ, IL-6, IL-1 β, and TLR4 than the positive control group. Rats given the VFnPs had considerably (P > 0.05) greater CD8 values than the control-positive group. The liver plays a key role in the metabolism of drugs, foods, and many compounds, so changing its function endangers a person's health. Liver damage could eventually lead to the increased serum activities of some liver enzymes Although ALP, GGT, and LDH are found in many tissues, some previous studies have shown that the most common reason for these enzymes' increase is a defect in liver function [ 55 ]. The findings of the current investigation showed that cyclosporine-A caused harm to the liver and kidneys of rats, as evidenced by an increase in ALT, AST, creatinine, and urea and a decrease in total protein and albumin levels in the serum. Reduced total antioxidant levels, elevated levels of lipid peroxidation product (MDA), and decreased SOD, catalase, and GST activity were indicators of cyclosporine-A-induced oxidative stress. The immunosuppressive and inflammatory effects of cyclosporine-A were also demonstrated by changes in the levels of CD4, CD8, INF-γ, IL-6, IL-1β, TLR4, and hepatic TNF-α. When cyclosporine-A causes liver damage, oxidative stress is a major factor. Several cells are stimulated to undergo oxidative stress, apoptosis, and autophagy as a result of cyclosporine-A therapy, which produces ROS, an important factor [ 56 ]. Cyclosporine-A stimulates intra-mitochondrial Ca 2+ , inhibits mitochondrial glucose metabolism and ATP synthesis, and increases ROS, which causes lipid peroxidation and elevates its byproducts such MDA [ 57 ]. The important antioxidant GSH, which helps keep mitochondria and cell membranes healthy by converting lipid peroxides into harmless byproducts, is similarly decreased by cyclosporine-A administration. Additionally, the antioxidant enzyme activity of GST, SOD, reduced glutathione, glutathione peroxidase, and glutathione reductase are decreased by cyclosporine-A [ 58 ]. To regulate the effects of cyclosporine-A, ROS elimination is therefore regarded as a crucial target. The current study's findings suggested that the prepared vitamins-loaded nanophytosomes prevented liver and kidney damage, as seen by rising levels of total protein and albumin and declining levels of ALT, AST, creatinine, and urea. Additionally, the vitamins-loaded nanophytosomes reduced hepatic levels of lipid peroxidation product (MDA), boosted SOD, catalase, and GST activities, and decreased hepatic levels of MDA as a result of oxidative stress. Increased serum CD4 levels, decreased serum CD8 levels, INF-γ, IL-6, IL-1β, TLR4, and hepatic TNF-α all indicated immunosuppression and inflammation, which were both inhibited by the prepared vitamins-loaded nanophytosomes. The benefit of prepared vitamins-loaded nanophytosomes in cyclosporine-related effects prevention may be attributed to the increased consumption of vitamins (A, B complex, C, D, E and folic acid) and zinc which were encapsulated into nanophytosomes. Vitamin A, commonly known as retinoic acid, is a member of the retinyl-ester family and regulates several genes involved in both innate and adaptive immune responses. Adaptive and innate immunity are supported by vitamin A role as T-cell effectors [ 59 ]. Retinoid directly stimulates the expression of Interferon stimulated genes (ISGs), including retinoic acid-inducible gene I (RIG-I) and IFN regulatory factor 1 (IRF-1) [ 60 ]. Vitamin B may control the production of chemokines and cytokines and control how immune cells communicate in pathogenic pathways. Additionally, since probiotics like bifidobacteria and lactobacilli have been shown to influence immune responses and guard against infections, vitamin B may be beneficial for immunity since it regulates colonic immune function and helps the intestinal barrier function [ 14 ]. Vitamin C and vitamin D are immunomodulating substances that have been used for decades to treat a variety of diseases. Vitamins D and C inhibit the release of proinflammatory cytokines in some immune system components and promote the growth of other immune cells, allowing the host to combat infection effectively while not depleting its immunological and energy reserves [ 61 ]. Vitamin C is an antioxidant that has a significant impact on both innate and adaptive immunological responses, as well as microbial metabolism [ 12 ]. Vitamin C treatment protects rat liver function against cyclosporine-A-induced damage by lowering ALT, AST, LDH, and ALP levels while increasing total protein and albumin levels [ 62 ]. As a strong antioxidant, vitamin E is critical in regulating and sustaining immune system activity [ 63 ]. Vitamin E is a free radical scavenger that decreases oxidative stress and protects cells against extremely energetic and damaging free radicals with unshared electrons [ 64 ]. When unshared electrons react quickly with oxygen, they generate reactive oxygen species (ROS). Vitamin E is key in immunity in addition to its antioxidant and anti-inflammatory activities [ 65 ]. Folate is a B vitamin that is required for DNA and protein synthesis, as well as the adaptive immune response [ 66 ]. The deleterious effects of folate deficiency on immune function are most likely mediated by anomalies in DNA and RNA synthesis or methyl metabolism, both of which are heavily influenced by folate availability [ 12 ] . Zinc is an important metal that plays a role in a range of biological processes as a cofactor, signalling molecule, and structural element. It possesses antiviral and antioxidant properties and modulates inflammatory activity [ 67 ]. Zn deficiency promotes oxidative stress, pro-inflammatory TNF-α, and vascular cell adhesion molecule (VCAM)-1 expression in rats, according to studies [ 68 ]. The star anise essential oil was employed to hide the unpleasant taste of vitamins and minerals in the current study. Aside from its pleasant aroma, star anise essential oil is a rich source of the shikimic acid molecule, which is utilized by pharmaceutical companies to create Tamiflu, an anti-influenza drug. Trans -anethole, the major fragrance component of star anise oil (as observed from our results Table 3 and Fig. 1 ), was also found to have anti-inflammatory properties, lowering TARC, MDC, and the cytokines IL-6 and IL-1β [ 69 ]. As noticed from the results presented in Table 2 , star anise oil has antioxidant effects, which are thought to be linked to the presence of trans -anethole, namely its double bonds in the molecules [ 70 ]. As a result, star anise oil in the VFnPs may play an important role in preventing cyclosporine-A side effects. Physiochemical properties in ice cream mixes - The specific gravity, weight per gallon , of ice cream mixes are illustrated in Table 7 . The mean values of specific gravity were 1.052, 1.078 and 1.095 g/cm 3 for the control, T1, and T2, respectively. From the obtained results, it could be observed that the specific gravity increased with the increasу in the percentage of encapsulated star anise into milk powder. On the other hand, the weight per gallon (Kg) of ice cream mixes were closely related to the specific gravity and were recorded 3.996, 4.233 and 4.254 for the control, T1, and T2, respectively [ 71 ]. Acidity pH values : the acidity of ice cream mixes was 0.73, 0.36, and 0.38, and the pH values take an opposite trend of the acidity. These data indicated that the acidity of mixes was nearly the same and was affected by high total solids in all treatments [ 72 ]. Ash contents % : the ash percentage of ice cream mixes were 0.79, 0. 82 and 0.85 % for the control, T1, and T2, respectively. The obtained results indicated that the ash contents slightly increased with increasing the percentage of milk powder with encapsulated star anise. Physiochemical properties in the resultant ice cream The specific gravity, weight per gallon , of the resultant ice cream are shown in Table 8 . The mean values of specific gravity were 0.891, 0.844 and 0.823 g/cm 3 for the control, T1, and T2, respectively. The weight per gallon (Kg) of the resultant ice cream were closely related to the specific gravity and were recorded as 3.45, 3.27 and 3.18 for the control, T1, and T2, respectively [ 73 ]. Overrun% : the overrun was 48.58, 50.90 and 54.67 % for the control, T1, and T2, respectively. The results showed that the increase in the overrun was due to the increase of milk powder and total solids in the mixes, therefore T2 had the highest overrun percentage [ 74 ]. Melting rate % : the melting rate of the resultant ice cream was 94, 89 and 82 % for the control, T1, and T2, respectively. It could be seen that the high melting rate was recorded in control ice cream, but with increasing the milk powder into T1 and T2 leads to high melting resistance compared with control one. The milk powder increased the total solids in mixes and enhancing the consistency and meting rate ability [ 74 , 75 ]. Sensory evaluation of functional ice cream The mean of sensory evaluation scores for ice cream is illustrated in Table 8 . The results showed that the control had the highest scores, followed by the treatment 2, which had 0.66 % of encapsulated star anise oil. Finally, functional ice cream fortified with encapsulated star anise oil and encapsulated vitamins had higher quality and acceptability, which could be due to the combination of the ingredients of mixes and star anise oil. Increasing the ratio of encapsulated star anise and vitamins has slight effect on the sensory evaluation of the ice cream. The improved body and texture of ice cream may be attributed to the increase of total solids in the mixes. The findings are consistent with those reported by Abdel-Haleem and Awad [ 71 ] . This study's main limitation was that it was unable to perform the experiment on volunteers. The pre-study on animals was necessary to gather sufficient information regarding the likely biological effects and reasonable safety of these newly formulated flavoured nanophytosomes and ice cream, even though mineral and vitamin mixtures are classified as dietary supplements. Thus, more research examining the impact of these flavoured nanophytosomes and ice cream fortified with it is needed.

Results and discussion The total phenolic content and antioxidant activity of star anise oil Results shown that the amount of total phenolic content was 265.01 ± 1.50 μg GAE gallic acid equivalent/ml. Anise oil showed good reducing power (0.188 ± 0.01 mg Vit C equivalent/ml). The reducing power of essential oil might be due to their hydrogen donating ability. The components present in the oil could act as good reductant. The total phenolic content of star anise oil showed positive correlation with its reducing capacity [ 44 ]. Star anise oil has strong scavenging activity towards DPPH radical (89.72 % ± 2.03). Our results agreed with Singh et., al. [ 45 ] , who reported that the method is based on the reduction of DPPH radicals and formation of non-radical form (DPPH-H), and that star anise oil is able to perform this reaction and is considered as radical scavenger and hence antioxidant. Star anise oil showed the strongest scavenging power that was even higher than BHA and BHT [ 45 , 46 ] . Figure (1) Illustrates the GC-MS chromatogram of Egyptian star anise extracted by hydro-distillation and the nine identified compounds listed in Table (2) represent about 97.6 % of the total detected compounds. The major compounds were anethole (63.47 %), oleic acid (13.72 %) and linoleic acid (11.99 %). The main compounds in our results matched with results of the Indian and Italian star anise oil [ 47 , 48 ] . Characterization of nanophytosomes Particle size and zeta potential In this study, the particle size (nm), PdI, zeta -potential (mV) and encapsulation efficiency (EE) of VFnPs are shown in Table 3 . According to these results, a variation was found between particle size for vitamins (A, D, E, C, F, B), Zn and Mixture loaded nanophytosomes were 213.6, 81.36, 228.5, 214.8, 107.3, 168.4167.4, and 149.4, respectively. These results clearly indicate that the vitamins maximized the size of the VFnPs. Gibis et al., [ 49 ] stated that the size of the phytosomes was dependent on the quality of the materials loaded in the phytosomes, which explains the present finding. Phytosomes agglomerated into nano-size micelles (approximately 100–300 nm) [ 50 ]. The particle distribution index (PDI) defines the particle distribution curve. The obtained results indicated almost the same PDI for different percentagesof the loaded vitamins except for the largest one (vitamin B), which showed narrower size distribution of the formed phytosomes. The zeta-potential values of the VFnPs ranged from - 11.2 to - 34.3 mV. This might be because vitamins (positive charge) interacted with the phosphate group in phosphatidylcholine (the negatively charged) giving the VFnPs (negative charge). In general, zeta-potential values of above −30mV or under +30 mV were observed to protect particles and minimize electrostatic and congregating force between nano-phytosomes, which might create large collection of nanophytosome nanovesicules [ 51 ]. Encapsulation efficiency (EE) Encapsulation efficiency (EE) was determined via calculation of free vitamins content in VFnPs. A smaller amount of free vitamins content means high encapsulation efficiency. There was no significant (p < 0.05) difference between EE of VFnPs. To assess the effectiveness of nanocarriers in delivering active substances, EE is a critical factor in nano-based delivery systems [ 52 ]. The achieved results of VFnPs, that were prepared via three different formulations and showed the exceptional capacity of nano-phytosomes as carriers, are shown in Table 3 . Nazari et al., [ 11 ] investigated the garlic essential oil (GEO) loaded in nano-phytosomes as a new phytochemicals delivery vehicles using three varied techniques, and found that GEO nano-phytosomes using homogenization-probe sonication (the same technique used in this study) is promising with a size of 115 nm and EE of 86.00 % (which is similar to the values found for the vitamins loaded nano-phytosomes presented in this study). Transmission electron microscopy (TEM) Transmission electron microscopy (TEM) was used to study the morphology of the VFnPs, which revealed spherical vesicles in all pictures ( Fig. 2 ). Moreover, the particles size distribution was existence of certain aggregates, indicating was homogemized, which is consistent with the PDI values reported ( Table 3 ). The size for particle via image is agree with particle size which measured using Malvern Zetasizer that have reported a size distribution between 100 and 300 nm for phytosomes used in the encapsulatation [ 53 , 54 ]. Role of the vitamins-loaded flavoured nanophytosomes in improving immunity, antioxdant and protecting the liver and kidney against cyclosporine-A According to Table 4 , the control positive group reported considerably (P > 0.05) higher values for AST, ALT, creatinine, and urea than the normal control group. Compared to the normal control group, the results for total protein and albumin dramatically (P > 0.05) fell in the control positive group. Rats given the VFnPs had lower (P > 0.05) levels of AST, ALT, creatinine, and urea than the control positive group. Rats given the VFnPs had greater (P > 0.05) total protein and albumin values than the control group of positive animals. Table 5 shown that the total antioxidant, liver GST, liver SOD, and liver catalase values were considerably (P > 0.05) lower in the control positive group than in the normal control group. As opposed to the normal control group, the control positive group's liver MDA and TNF- levels considerably (P > 0.05) rose. The liver GST, SOD, and catalase values in VFnPs-treated rats were higher (P > 0.05) than those in the control positive group. Rats given the vitamin-loaded nanophytosomes had considerably (P > 0.05) lower liver MDA and TNF levels than the control-positive group. According to Table 6 , the control positive group recorded considerably (P > 0.05) higher CD8, INF-γ, IL-6, IL-1β, and TLR4 values than the normal control group. As opposed to the normal control group, the CD4 value in the control positive group considerably (P > 0.05) reduced. Rats given the VFnPs had lower levels of CD4, INF- γ, IL-6, IL-1 β, and TLR4 than the positive control group. Rats given the VFnPs had considerably (P > 0.05) greater CD8 values than the control-positive group. The liver plays a key role in the metabolism of drugs, foods, and many compounds, so changing its function endangers a person's health. Liver damage could eventually lead to the increased serum activities of some liver enzymes Although ALP, GGT, and LDH are found in many tissues, some previous studies have shown that the most common reason for these enzymes' increase is a defect in liver function [ 55 ]. The findings of the current investigation showed that cyclosporine-A caused harm to the liver and kidneys of rats, as evidenced by an increase in ALT, AST, creatinine, and urea and a decrease in total protein and albumin levels in the serum. Reduced total antioxidant levels, elevated levels of lipid peroxidation product (MDA), and decreased SOD, catalase, and GST activity were indicators of cyclosporine-A-induced oxidative stress. The immunosuppressive and inflammatory effects of cyclosporine-A were also demonstrated by changes in the levels of CD4, CD8, INF-γ, IL-6, IL-1β, TLR4, and hepatic TNF-α. When cyclosporine-A causes liver damage, oxidative stress is a major factor. Several cells are stimulated to undergo oxidative stress, apoptosis, and autophagy as a result of cyclosporine-A therapy, which produces ROS, an important factor [ 56 ]. Cyclosporine-A stimulates intra-mitochondrial Ca 2+ , inhibits mitochondrial glucose metabolism and ATP synthesis, and increases ROS, which causes lipid peroxidation and elevates its byproducts such MDA [ 57 ]. The important antioxidant GSH, which helps keep mitochondria and cell membranes healthy by converting lipid peroxides into harmless byproducts, is similarly decreased by cyclosporine-A administration. Additionally, the antioxidant enzyme activity of GST, SOD, reduced glutathione, glutathione peroxidase, and glutathione reductase are decreased by cyclosporine-A [ 58 ]. To regulate the effects of cyclosporine-A, ROS elimination is therefore regarded as a crucial target. The current study's findings suggested that the prepared vitamins-loaded nanophytosomes prevented liver and kidney damage, as seen by rising levels of total protein and albumin and declining levels of ALT, AST, creatinine, and urea. Additionally, the vitamins-loaded nanophytosomes reduced hepatic levels of lipid peroxidation product (MDA), boosted SOD, catalase, and GST activities, and decreased hepatic levels of MDA as a result of oxidative stress. Increased serum CD4 levels, decreased serum CD8 levels, INF-γ, IL-6, IL-1β, TLR4, and hepatic TNF-α all indicated immunosuppression and inflammation, which were both inhibited by the prepared vitamins-loaded nanophytosomes. The benefit of prepared vitamins-loaded nanophytosomes in cyclosporine-related effects prevention may be attributed to the increased consumption of vitamins (A, B complex, C, D, E and folic acid) and zinc which were encapsulated into nanophytosomes. Vitamin A, commonly known as retinoic acid, is a member of the retinyl-ester family and regulates several genes involved in both innate and adaptive immune responses. Adaptive and innate immunity are supported by vitamin A role as T-cell effectors [ 59 ]. Retinoid directly stimulates the expression of Interferon stimulated genes (ISGs), including retinoic acid-inducible gene I (RIG-I) and IFN regulatory factor 1 (IRF-1) [ 60 ]. Vitamin B may control the production of chemokines and cytokines and control how immune cells communicate in pathogenic pathways. Additionally, since probiotics like bifidobacteria and lactobacilli have been shown to influence immune responses and guard against infections, vitamin B may be beneficial for immunity since it regulates colonic immune function and helps the intestinal barrier function [ 14 ]. Vitamin C and vitamin D are immunomodulating substances that have been used for decades to treat a variety of diseases. Vitamins D and C inhibit the release of proinflammatory cytokines in some immune system components and promote the growth of other immune cells, allowing the host to combat infection effectively while not depleting its immunological and energy reserves [ 61 ]. Vitamin C is an antioxidant that has a significant impact on both innate and adaptive immunological responses, as well as microbial metabolism [ 12 ]. Vitamin C treatment protects rat liver function against cyclosporine-A-induced damage by lowering ALT, AST, LDH, and ALP levels while increasing total protein and albumin levels [ 62 ]. As a strong antioxidant, vitamin E is critical in regulating and sustaining immune system activity [ 63 ]. Vitamin E is a free radical scavenger that decreases oxidative stress and protects cells against extremely energetic and damaging free radicals with unshared electrons [ 64 ]. When unshared electrons react quickly with oxygen, they generate reactive oxygen species (ROS). Vitamin E is key in immunity in addition to its antioxidant and anti-inflammatory activities [ 65 ]. Folate is a B vitamin that is required for DNA and protein synthesis, as well as the adaptive immune response [ 66 ]. The deleterious effects of folate deficiency on immune function are most likely mediated by anomalies in DNA and RNA synthesis or methyl metabolism, both of which are heavily influenced by folate availability [ 12 ] . Zinc is an important metal that plays a role in a range of biological processes as a cofactor, signalling molecule, and structural element. It possesses antiviral and antioxidant properties and modulates inflammatory activity [ 67 ]. Zn deficiency promotes oxidative stress, pro-inflammatory TNF-α, and vascular cell adhesion molecule (VCAM)-1 expression in rats, according to studies [ 68 ]. The star anise essential oil was employed to hide the unpleasant taste of vitamins and minerals in the current study. Aside from its pleasant aroma, star anise essential oil is a rich source of the shikimic acid molecule, which is utilized by pharmaceutical companies to create Tamiflu, an anti-influenza drug. Trans -anethole, the major fragrance component of star anise oil (as observed from our results Table 3 and Fig. 1 ), was also found to have anti-inflammatory properties, lowering TARC, MDC, and the cytokines IL-6 and IL-1β [ 69 ]. As noticed from the results presented in Table 2 , star anise oil has antioxidant effects, which are thought to be linked to the presence of trans -anethole, namely its double bonds in the molecules [ 70 ]. As a result, star anise oil in the VFnPs may play an important role in preventing cyclosporine-A side effects. Physiochemical properties in ice cream mixes - The specific gravity, weight per gallon , of ice cream mixes are illustrated in Table 7 . The mean values of specific gravity were 1.052, 1.078 and 1.095 g/cm 3 for the control, T1, and T2, respectively. From the obtained results, it could be observed that the specific gravity increased with the increasу in the percentage of encapsulated star anise into milk powder. On the other hand, the weight per gallon (Kg) of ice cream mixes were closely related to the specific gravity and were recorded 3.996, 4.233 and 4.254 for the control, T1, and T2, respectively [ 71 ]. Acidity pH values : the acidity of ice cream mixes was 0.73, 0.36, and 0.38, and the pH values take an opposite trend of the acidity. These data indicated that the acidity of mixes was nearly the same and was affected by high total solids in all treatments [ 72 ]. Ash contents % : the ash percentage of ice cream mixes were 0.79, 0. 82 and 0.85 % for the control, T1, and T2, respectively. The obtained results indicated that the ash contents slightly increased with increasing the percentage of milk powder with encapsulated star anise. Physiochemical properties in the resultant ice cream The specific gravity, weight per gallon , of the resultant ice cream are shown in Table 8 . The mean values of specific gravity were 0.891, 0.844 and 0.823 g/cm 3 for the control, T1, and T2, respectively. The weight per gallon (Kg) of the resultant ice cream were closely related to the specific gravity and were recorded as 3.45, 3.27 and 3.18 for the control, T1, and T2, respectively [ 73 ]. Overrun% : the overrun was 48.58, 50.90 and 54.67 % for the control, T1, and T2, respectively. The results showed that the increase in the overrun was due to the increase of milk powder and total solids in the mixes, therefore T2 had the highest overrun percentage [ 74 ]. Melting rate % : the melting rate of the resultant ice cream was 94, 89 and 82 % for the control, T1, and T2, respectively. It could be seen that the high melting rate was recorded in control ice cream, but with increasing the milk powder into T1 and T2 leads to high melting resistance compared with control one. The milk powder increased the total solids in mixes and enhancing the consistency and meting rate ability [ 74 , 75 ]. Sensory evaluation of functional ice cream The mean of sensory evaluation scores for ice cream is illustrated in Table 8 . The results showed that the control had the highest scores, followed by the treatment 2, which had 0.66 % of encapsulated star anise oil. Finally, functional ice cream fortified with encapsulated star anise oil and encapsulated vitamins had higher quality and acceptability, which could be due to the combination of the ingredients of mixes and star anise oil. Increasing the ratio of encapsulated star anise and vitamins has slight effect on the sensory evaluation of the ice cream. The improved body and texture of ice cream may be attributed to the increase of total solids in the mixes. The findings are consistent with those reported by Abdel-Haleem and Awad [ 71 ] . This study's main limitation was that it was unable to perform the experiment on volunteers. The pre-study on animals was necessary to gather sufficient information regarding the likely biological effects and reasonable safety of these newly formulated flavoured nanophytosomes and ice cream, even though mineral and vitamin mixtures are classified as dietary supplements. Thus, more research examining the impact of these flavoured nanophytosomes and ice cream fortified with it is needed.

Conclusion The results revealed no statistically significant differences between samples containing vitamins-loaded flavoured nanophytosomes and control ones. It can be concluded that vitamins-loaded flavoured nanophytosomes may be offered as an efficient natural food preservative. Flavoured nanophytosomes containing vitamins were developed for ice-cream to overcome the major problems with flavoured vitamins and improve the immune system of the human body. Along with its function as an immune-enhancing agent, vitamins-loaded flavoured nanophytosomes may have a potential as a hepatoprotective due to its antioxidant and anti-inflammatory actions. After full characterization, vitamins-loaded flavoured nanophytosomes were used in ice cream.

This study investigated the effect of flavoured nanophytosomes loaded with vitamins A, E, D, B complex, folic acid, and C, as well as zinc on the immunosuppressive cyclosporin A (CsA)-induced liver and kidney injury in male rats. The vitamins flavoured nanophytosomes (VFnPs) were characterized in terms of particle size, zeta potential, encapsulation efficiency. Ice cream was flavoured with star anise volatile oil to mask the VFnPs' flavour and unacceptable taste. The study found that treatment with CsA alone resulted in increased (P > 0.05) levels of creatinine, urea, and MDA, as well as the activities of AST and ALT, while the levels of SOD, CAT, GST, proteins, CD4, INF-γ, IL-6, IL-1β, and TLR4 decreased (P > 0.05). However, the group that received CsA simultaneously with VFnPs showed a significant (P > 0.05) decrease in the levels of creatinine, urea, and MDA, as well as the activities of AST and ALT, and increased (P > 0.05) levels of SOD, CAT, GST, proteins, CD4, INF-γ, IL-6, IL-1β, and TLR4. The increase in the ratio of VFnPs had little effect on the physiochemical and sensory evaluation of the ice cream. Finally, the study suggests that VFnPs could potentially protect against CsA-induced liver and kidney injury and serve as a promising natural therapy for treating such conditions. Keywords

Data availability statement The data that support the findings of this study are available within the article. CRediT authorship contribution statement Manal M. Ramadan: , Supervision, Project administration, Investigation, Conceptualization. Rasha S. Mohamed: , Visualization, Validation, Methodology, Investigation, Formal analysis. Amal G. Hussien: , Writing – original draft, Validation, Methodology, Conceptualization. Ola A.M. Mohawed: , Writing – original draft, Methodology. Ahmed M. Mabrouk: Writing – original draft, Methodology. Abeer E. Mahmoud: , Writing – original draft, Methodology. Kadry Z. Ghanem: , Validation, Formal analysis. Tamer M. El-Messery: Writing – review & editing, Visualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement Authors would like to thank the 10.13039/100007787 National Research Centre , Egypt for ongoing co-operation to support research and that provided facilities necessary to achieve the desired goals of research. This study founded in partial fulfilment of the requirement of internal project submitted for Chemistry of flavours and aromas Department in title "Production of functional flavouring micro-capsules (powders) for healthy food products, No. 13050213′′, National Research Centre, Egypt.

CC BY

no

2024-01-16 23:43:42

Heliyon. 2023 Dec 19; 10(1):e23894

oa_package/b0/ed/PMC10788501.tar.gz

PMC10788502

38226241

Introduction Spirocyclic compounds are an attractive target in drug discovery due to their enriched bio-profile [ [1] , [2] , [3] ]. These molecules are widely distributed in natural and non-natural products and show impressive biological properties [ [4] , [5] , [6] ]. Other applications of spirocyclic molecules include asymmetric synthesis and organic optoelectronics [ 1 , 7 ]. In the case of spiropyrazoline, two rings are connected at the C-5 position [ 8 , 9 ] with a unique spirocyclic junction that is conformationally rigid [ 1 , 10 ]. Due to widespread applications of these spiro skeletons, effective methods have been developed including catalyst-assisted synthesis [ 11 ], catalyst-free synthesis [ 12 ], cycloaddition reaction using diaziridines and nitrile imines or diazoalkanes, as appropriate dipoles where multistep reaction sequence is adopted and at times suffers poor yield and regioselectivity [ 7 , 13 ]. Even with these inspiring advances, it is still important to further investigate better synthetic approaches for spiropyrazolines under the umbrella of green chemistry. Because of environment concerns, non-toxic, biodegradable and recyclable solvents like deep eutectic solvents (DES) are emergent solvents for synthesis [ [14] , [15] , [16] , [17] ]. Additionally, these solvents are less volatile, biocompatible, cost-effective, water insensitive and easy to prepare with no purification issues and storage [ [18] , [19] , [20] , [21] ]. Inspired by these features, the present research aims to endeavor the synthesis of new spiropyrazolines in DES as no attempt has been made before to the best of our knowledge. Moreover, a comparison is also made between the convection heating and microwave heating methods. Synthetic chemists execute post-reaction amendments that allow molecular complexity in core scaffolds for various improved applications. This leads to the region and stereo-specific frameworks with functional diversity. Thus, to accomplish this effectively, a multicomponent reactions (MCR) approach is employed for the synthesis of spiropyrazolines. Therefore, tethering the 1,2-pyrazoline and indolinones motifs simultaneously into one molecule as spiropyrazoline-indolinones ( Fig. 1 ) seems to be a potential strategy for drug discovery. Organic synthesis is useful for drug design when it is combined with computational chemistry to study various electronic parameters of compounds, hence, provides very valuable information [ 22 ]. Apart from the geometries of compounds, the picture of molecular size and its electronic structure can be studied with the help of density functional theory (DFT) calculations. They provide detailed information about the frontier molecular orbitals (FMOs) of all the compounds. This study was performed using the PBE0/def2-TZVP basis set to achieve an understanding of their structural properties. Similarly, using Frontier Molecular Orbital (FMO) analysis, the kinetic stability of all compounds (4a-4t) was calculated at the same level of theory. Molecular electrostatic potential (MEP) mapping over the entire stabilized geometries of the molecules was used to determine reactive sites. Furthermore, the PBE0/def2-TZVP level of theory was used to simulate the first hyperpolarizability analysis, which provided insights into nonlinear optical response.

Materials and methods All chemicals were purchased from Merck, Sigma Aldrich, Riedel-de Haën and used without purification. Reactions were monitored through pre-coated TLC plates of silica gel (Merck 60 F254, 0.2 mm thick) and spots were examined under UV light (CAMAG Scientific Inc) at 254/365 nm. Column chromatography was used to purify compounds over Merck silica gel 60 (0.063–0.200 mm, 70–230 mesh). MW-assisted synthesis was conducted in CEM Discover microwave reactor, model 908010, volts 180/264 VAC, max. power 300W (Synergy software). Melting points were recorded on digital Stuart apparatus, SMP 10 model and considered uncorrected. FTIR spectra were mentioned in wave numbers (cm −1 ) using Alpha ATR-IR spectrometer, Bruker. 1 HNMR spectra were determined at AVII400, AV400RG (400 MHz) and 13 CNMR spectra were recorded at 100.56 MHz on a Bruker spectrophotometer. Chemical shift ( δ ) values are noted in ppm and coupling constants are indicated as J values in Hz. Characterization of the signal fragmentations: s = singlet, d = doublet, dd = doublet of doublet, t = triplet, q = quartet, m = multiplet. Elemental analyses were performed on the Perkin Elmer 2400 CHNS elemental analyzer. Preparation of deep eutectic solvents (DES) Three different DES was prepared according to the literature method with little modifications [ [23] , [24] , [25] ]. DES-1 Choline chloride (100 mmol, 13.96 g, 1 eq.) along with urea (200 mmol, 12 g, 2 eq.) were slowly heated at 80 °C for 10 h to obtain a colorless homogenized solution. This solution was cooled at room temperature and used for synthesis without any further purification. pH: 7, Freezing point: 12 °C, FTIR cm −1 : 783 (N–H), 864 (C–N), 1475 (CH 2 ), 1609 (N–H), 1662 (C=O), 3189 (O–H and N–H), 3321 (NH 2 ). DES-2 Choline chloride (100 mmol, 13.96 g, 1 eq.) along with fructose (100 mmol, 18 g, 1 eq.) was gently heated at 50 °C to get a light-yellow adhesive solution after 7 h. This solution was cooled at room temperature for synthetic purposes without purification. pH: 7, Freezing point: 5 °C, FTIR cm −1 : 570 and 3200 (OH), 862 and 1042 (C–C–O), 1120 (C–O), 1205 (C–O–H), 1470 (CH 2 ), 1655 (C=O), 2870 and 2900 (C–H), 3012 (N–H). DES-3 Choline chloride (100 mmol, 13.96 g, 1 eq.) was slowly heated with glycerol (200 mmol, 18.4 g, 14.6 mL, 2 eq.) at 110 °C for 8 h. The resultant colorless solution was cooled at room temperature for synthetic purposes without further purifying. pH: 7, Freezing point: −40 °C, FTIR cm −1 : 565 and 3300 (OH), 862 and 1036 (C–C–O), 1110 (C–O), 1205 (C–O–H), 1485 (CH 2 ), 2876 and 2932 (C–H), 3035 (N–H). Procedure DES mediated synthesis of spiropyrazoline-indolinones To a stirred mixture of 5-chloro/bromo isatin ( 1a–1b , 5 mmol, 1 eq.), aromatic acetyl ketones ( 2a–2b , 5 mmol, 1 eq.) and diethyl amine (6.5 mmol, 671 μL, 474 mg, 1.3 eq.) at room temperature, then after TLC monitoring, hydrazine derivative ( 3a–3e , 5 mmol, 1 eq.) was added with DES-1 (8 mL) and heated at 65 °C till the completion of reaction. The flask's contents were poured over crushed ice to induce precipitation, which was then neutralized with 10% glacial acetic acid. To obtain purely targeted spiropyrazolines, the crude product was subjected to column chromatography using an eluting system with ethyl acetate and n-hexane as a gradient. Microwave-assisted synthesis of spiropyrazoline-indolinones An equimolar mixture of 5-chloro/bromo isatin ( 1a/1b , 3 mmol), acetyl ketones ( 2a / 2b , 3 mmol) and different hydrazine derivatives ( 3a–3e , 3 mmol) were introduced in a Teflon reaction vessel equipped with diethyl amine (3.9 mmol, 403 μL, 285 mg, 1.3 eq.) in solvent ethanol (5 mL). This mixture was irradiated for 8–17 min at 240 W. Infrared (IR) temperature was maintained at 70 °C having the pressure of 20 bar inside the reaction vessel throughout the synthesis. Reaction progress was monitored by TLC at an interval of 30 s using ethyl acetate: n -hexane (4:6 v/v) as eluent. The work-up procedure was similar as mentioned in the conventional setup previously.

Results and discussion Chemistry of spiropyrazoline-indolinones New spiropyrazoline-indolinones (4a–4t) were synthesized using DES as a catalyst in addition to its role as reaction media. The multicomponent reaction proceeded with 5-Cl or 5-Br isatin ( 1a/1b ), acetophenone or 2-acetyl thiophene ( 2a / 2b ) and different hydrazine analogs ( 3a–3e ) in the presence of diethyl amine (DEA). In general, the multicomponent reaction proceeded leading to the cyclization step. According to available protocols [ 26 , 27 ], initially two steps of synthetic protocols were followed which were low yielded due to purification issues. These unsatisfactory outcomes were our motivation to explore one-pot, two-steps strategy for spiropyrazolines synthesis which sounds promising. In the first step, exocyclic α,β -unsaturated ketone ( I ) was produced by the reaction of 1a/1b with acetyl ketone 2a/2b . In the second step, enone ( I ) and selected hydrazine derivatives ( 3a–3e ) were reacted to furnish a desired product which underwent column purification as mentioned in Scheme 1 . The plausible reaction mechanism showed Aldol condensation in the first place then Michael addition reaction to yield the final product [ 9 , 22 , 28 ]. In the Aldol reaction, DEA acts as a base to abstract acidic proton from acetophenone to yield a reactive anionic intermediate which quickly reacts with the carbonyl group of isatin to furnish a stable α,β -unsaturated ketone ( I ). The exocyclic C=C of enone is attacked by nitrogen of hydrazine analogous to Micheal addition to start a reaction series that furnishes pyrazoline ring finally. DES played an important role in catalyzing via hydrogen bonding with carbonyl oxygen ( I ), thus making it more electrophilic and providing the ease of nitrogen attack to form a spiro junction ( Fig. 2 ). The reaction conditions favored the aldol mechanism as it occurs at room temperature while another possibility is to achieve formation via Schiff ‘s base route, however, it requires elevated temperature. Optimization of reaction conditions Initially, the reaction between isatin, acetophenone and thiosemicarbazide was chosen for optimization studies. For this, the equimolar ratio of reactants was treated in the presence of 1 mmol of different suitable bases in ethanol and diethyl amine (DEA) formed the most appreciable amount of product ( Table 1 , entry 4). Initially isatin reacted with acetophenone to give a yellow mixture that further became orange-yellow product after stirring the reaction media for 7 min which indicated the existence of exocyclic α , β -unsaturated enone ( I ). Reaction progress was monitored via TLC technique and FTIR spectroscopy. Without any purification step, thiosemicarbazide ( 3d ) was added in the same vessel which was refluxed in the presence of ethanol. The yield was improved by increasing the DEA concentration gradually from 1 to 1.3 mmol ( Table 1 , entry 7). Any further increase in DEA amount retarded the reaction due to the formation of imine as a side product. To avoid volatile organic solvents as much as possible and reduce reaction time, the above-mentioned reaction was also carried out in benign media such as neutral deep eutectic solvent (DES-1 to DES-3) and the results were compared with ethanol. It was observed that DES-1 produced an excellent yield (86 %) while DES-2 and DES-3 furnished lower yields and took comparatively longer time in product formation ( Table 1 , entry 12, 13, 14). It was envisioned to study the spiropyrazoline-indolinones synthesis at different temperatures, i.e., 25, 45, 65 and 70 °C using DES-1 which concluded 65 °C as the optimum reaction temperature as further increase in temperature decrease the yield ( Table 1 , entry 17). This could be explained by a lowering in H-bonding between the carbonyl oxygen of ketone and DES at elevated temperature. Microwave mediated synthesis of spiropyrazoline-indolinones ( 4a–4t ) Optimization studies were conducted to find the most suitable reaction conditions which were experimented to produce a variety of products in DES-1 using 5-Cl/Br isatin ( 1a / 1b ) with two different acetyl ketones ( 2a and 2b ) and different hydrazine derivatives ( 3a–3e ) ( Scheme 1 ). Targeted derivatives were produced after simple workup in 24 min to 3 h in a conventional setup (entries 7 and 9, Table 1 ). Hydrazine 3a was employed to produce 4a, it was formed in a longer time (2.5 h) with a low yield (42 %) while hydrazine 3b gave a moderate yield (63 %) of 4b in 1.5 h. Thiosemicarbazide ( 3d ) furnished 4d with a high yield (86 %) in 24 min which is due to the good nucleophilicity of hydrazine moiety while others are less reactive due to electron withdrawing functionalities ( Table 3 ). The overall outcomes showing the reactivity of hydrazine analogs in the case of 1a with 2a are mentioned in descending order as 3d > 3e > 3b > 3c > 3a . After examining the behavior of acetophenone ( 2a ), the next 2-acetyl thiophene ( 2b ) was reacted which showed the same reactivity order as observed in the case of ketone 2a . This observation indicated that the electron withdrawing ability of chloro as well as nitro substituent on aromatic ring was responsible for decreasing the hydrazine reactivity. Overall 2a produced better results than 2b indicating the superiority of the phenyl ring of ketone over the thienyl ring. In the case of 1b as substrate, hydrazine reactivity order was almost similar as mentioned above with slight variation. Hydrazine 3d and 3e reacted faster than 3c when acetophenone was used. Only a few reports highlight the clean and fast synthesis of spiropyrazoline in microwave [ 29 ]. So, inspired by this fact, an experimental study for new spiropyrazolines ( 4a–4t ) has also been carried out at 70 o C in the synthetic microwave. To explore the optimum reaction conditions in a synthetic microwave reactor, a model reaction was performed using the equimolar ratio of the same reactants as used in classical settings. The reaction contents were irradiated at different power levels ranging from 100 to 280 W and product formation was observed by TLC. Results depicted that the reaction rate at 100 W was very slow which produced a 19% yield in 25 min whereas it was improved by increasing the power level gradually. At 240 W, the highest yield (82%) was obtained in 8 min ( Table 2 , entry 4), however, a further increase in power level furnished gummy product indicated impurities and side products. Once the best radiation level was achieved, the optimum catalyst amount was explored by using two concentrations of DEA in the reaction. At first, the equimolar ratio of reactants along with the catalyst was experimented, while 1.3 eq. of DEA was used in the second attempt ( Table 2 ). Both the concentrations were applied by performing several reactions at different times. In the case of 1:1:1, 8 min was the optimum time for the required product ( Table 2 , entry 4). It was observed that an increase in reaction time decreased the yield. This could be rationalized by the high heating effect of the reaction chamber. In the case of ratio 1:1:1.3, it was investigated that comparable yields were recorded at 8 and 15 min whereas after 18 min irradiations maximum yield (52 %) was achieved. These observations concluded that the mole ratio 1:1:1 was better than 1:1:1.3 in terms of reaction time product yield. Versatility and the scope of the adopted procedure were studied by synthesizing a series of spiropyrazolines ( 4a–4t ) from diketones. The mild reaction conditions enabled the incorporation of synthetically useful functionalities in the substrate. Its internal heating is more homogeneous than classical heating. The effect of substituted hydrazines ( 3a–e ) was explored by comparing the yield of the desired products and reaction time. The spiropyrazoline 4a and 4b were furnished using 3a and 3b, respectively, in 9 min with moderate yield (58 %) to good yield (75%), revealing the role of chloro group at phenyl moiety. The product 4c was synthesized in 10 min with moderate yield due to the presence of electron-withdrawing effect of two nitro groups on the phenyl ring of hydrazine ( 3c) . The best results were obtained in 8 min for the formation of 4d with 82% yield. The yield of 4e was also close to that of 4d and this observation is rationalized by the appreciable nucleophilic character of hydrazine 3d and 3e . From the results, it was inferred that the reactivity of hydrazine 3b was better than its analogs 3a a nd 3c when reacted with acetophenone. In the case of 2-acetyl thiophene, 3d is the most reactive as compared to other analogs. However, 4l was produced in 76 % in 12 min when reacted with 3b ( Table 3 , entry 12). To study the effect of two diketones; 1a and 1b , the yield of 4a - 4j was compared with 4k - 4t and 5-bromo isatin was found more reactive. The effect of ketones 2a and 2b was also understandable by comparing yield which showed better results with 2-acetyl thiophene ( 4f - 4j ). Conventional and microwave approach of synthesis was analyzed for Scheme 1 which concluded that the classical method was lengthier in reaction time (0.5–3 h) in the presence of ethanol with moderate yield (41–86 %). While microwave-assisted synthesis (time 8–17 min, with moderate yield (41–86 %) is preferred; Microwave method > Conventional method. However, ethanol has been used as a reaction medium to facilitate microwave heating while conventional setup has used biodegradable deep eutectic solvent. It is easily prepared from non-toxic and low-cost chemicals. Their compositional flexibility makes it popular for the preparation of a variety of spiropyrazolines. From an environmental point of view, the classical synthesis described here is preferred over non-classical reaction setup ( Table 3 ). If the microwave is not available, spiropyrazolines can be successfully prepared in DES, avoiding volatile organic solvents. Physical properties and spectroscopic data of newly synthesized spiropyrazoline-indolinones ( 4a–4t ) are mentioned in supporting information. All prepared DESs were confirmed by FTIR [ 30 ]. The freezing point of DES-1 [ 31 ], DES-2 [ [32] , [33] , [34] ] and DES-3 [ 35 , 36 ] was found to be 12. 5 and −40 °C respectively. Structure confirmation of newly synthesized compounds was achieved with elemental analysis, 1 HNMR and 13 CNMR and FTIR spectroscopy. The spectral data is well agreed with the literature values [ 37 ]. Based on the most supportive 13 C NMR data, the spiro junction in spiropyrazoline was confidently assigned as a quaternary carbon at 70.21 ppm. The formation of diazole rings was confirmed by an absorption band in the FTIR spectrum at 1250 cm −1 for the C–N stretch and 3232 cm −1 for the N–H stretch. The 1 H NMR spectrum confirmed this, with two singlets at 6.91 and 6.24 ppm assigned to H-4' and the hydrogen attached to the diazole nitrogen, respectively. Furthermore, in the 1 H NMR spectrum, a set of doublets at 6.94 ppm and a double doublet at 7.38 ppm confirmed the involvement of the ketone skeleton provided by 1a . The phenyl protons resonating at 7.52–7.64 ppm indicated that acetophenone had successfully contributed to ring formation, which was supported by the quaternary carbon resonating at 127.05 ppm (C-5 of 4a ). The FTIR spectrum provided additional confirmation, with absorption at 1608 cm −1 indicating the presence of a C=C stretch for the diazole ring. Aromatic protons attached to nitrogen were responsible for the multiplet observed in the 1 H NMR spectrum at 7.71–7.89 ppm. In addition, the C=O group at C-2 was assigned a downfield signal in the 13 C NMR spectrum at 162.84 ppm. The 1 HNMR spectra of 4b to 4t , revealed a singlet at 6.62–6.91 ppm designated to H-4. On the other hand, its 13 CNMR was found to be supportive by displaying a quaternary carbon singlet in the range of 69.21–70.83 ppm as proof of spiro 1,2 diazole ring formation. In 4e , an additional signal observed at 29.24 ppm indicated the (C-3′′′) of thiosemicarbazide in 13 CNMR. Compound 4f displayed a multiplet at 7.71–7.84 ppm, designated to thiophene moiety in the 1 HNMR spectrum. The 1 HNMR spectrum of 4g , a multiplet (4H) resonated in the aromatic region 7.42–7.59 ppm was attributed to phenyl protons as a substituent of hydrazine. The 1 HNMR spectrum of 4h , showed a double doublet at 8.30 ppm and two doublets at 7.69 and 7.94 ppm with the ABX splitting pattern showing the presence of 2,4-dinitro phenyl moiety. The 13 CNMR spectrum of 4i revealed a high field signal at 177.36 ppm designated to thioamide moiety while a signal at 106.63 ppm was attributed to methine carbon as C-4′. Some of the significant signals in 13 CNMR of 4j exhibited at 166.46 ppm were credited to C-2 of 5-chloroisatin, 106.43 ppm to C-4′, 27.46 and 177.32 ppm were designated to methyl and quaternary carbon of thiosemicarbazide. The compounds from 4k to 4t are bromine analogs of spiropyrazoline and are in close agreement with chlorine analogs 4a to 4j . Nonetheless, condensations as well as cycloaddition reactions have a high potential to furnish very interesting spirocyclic frameworks. In the light of high demand of spiropyrazolines, it is speculated that the development of this new synthetic protocol will also present future insight into this area. Computational studies Theoretical studies serve as a complement to verify and support experimental data. DFT serves as a powerful tool to predict various properties including chemical reactivity, stability and electronic structure. Gaussian 09 revision D.01 [ 38 ] has been used for all the calculations done in the present study. All the calculations have been performed using density functional theory (DFT) using the density functional PBE0 [ 39 , 40 ] with a triple ζ basis set def2-TZVP [ 41 ]. The non-bonding effects in the molecules were added using Grimme’s empirical dispersion correction [ [42] , [43] , [44] ] as implemented in Gaussian 09. The said method has been benchmarked earlier by us on a variety of similar studies and others as well and it proved to produce good results [ [45] , [46] , [47] , [48] , [49] , [50] , [51] ]. Solvent effects were added through the Polarizable Continuum Model (PCM) [ [52] , [53] , [54] , [55] , [56] , [57] , [58] ] added through Truhlar’s SMD parameter [ 59 ]. Frequency calculations on optimized geometries have been performed to confirm the structures as true minima by the absence of imaginary frequencies. GaussView and CYLview [ 60 ] software tools have been used to visualize the calculation results and produce figures for the manuscript. The optimized structures are depicted in Fig. 3 (a–t), i.e., chlorospiropyra acetophenones ( Fig. 3 4a–4e ), chlorospiropyra thiophenes ( Fig. 3 4f–4j ), bromospiropyra acetophenones ( Fig. 3 4k–4o ), and bromospiropyra thiophenes ( Fig. 3 4p–4t ) were 3D modelled and optimized using Gaussian 09 rev. D01 software. The optimized structures were then analyzed for vibrational frequencies to confirm the absence of imaginary frequencies, establishing them as true potential energy surface (PES) minima. DFT calculations were used to determine the Frontier Molecular Orbital (FMO) Analysis, hyperpolarizability, molecular reactivity, and physical properties of compounds are computed and are depicted in Fig. 4 ( a–j ), i.e., ( 4a–4e ) the frontier orbitals of the chlorospiropyra acetophenones and ( 4f–4j ) chlorospiropyra thiophenes. The frontier orbitals were calculated at PBE0-D3BJ/def2-TZVP/SMD DMSO level of theory and are presented in Fig. 5 ( a–t ), i.e., bromospiropyra acetophenones ( 4k–4o ), and bromospiropyra thiophenes ( 4p–4t ) [ 61 ] . Table 4 enlists the HOMO-LUMO gap (ΔE) and hyperpolarizability ( β ) values of all the compounds ( 4a–4t ). The ΔE values of these molecules are in a relatively narrow range from 3.63 to 4.79 eV which means that their reactivity is almost similar. The lowest ΔE value of compound 4h (3.63 eV) suggests it to be the most reactive among the series. That can be attributed to the inductive electron withdrawing –Cl group on one phenyl ring and –NO 2 group on the other phenyl ring in the molecule. Similarly, 4d has the highest ΔE value (4.79 eV) which establishes it to be the most stable in the series. The next most stable compounds are 4k and 4l which have deactivating Br group on the aromatic ring. All the HOMO and LUMO energies are given in eV. The distribution of iso-density seems very similar in these compounds. In chlorospiropyra acetophenones ( 4a–4e ), chlorospiropyra thiophenes ( 4f–4j ), bromospiropyra acetophenones ( 4k–4o ), and bromospiropyra thiophenes ( 4p–4t ), the iso-density is mainly spread over the whole molecule except the chloro- and bromo-substituted rings in all the compounds under study for HOMO. Interestingly, LUMO iso-density is also located on the rest of the molecule except the chloro and bromo-substituted aromatic rings. Only in the case of compound 4o , it is located on the bromophenyl ring as well to some extent. The hyperpolarizability ( β ) values of the compounds under study do not show them as potent non-linear optical (NLO) materials but four of them ( 4c , 4h , 4m , and 4r ) show quite good NLO response. The highest β value is shown by compound 4m and the second highest is shown by 4c , 4h and 4r . That can be explained by the presence of the –NO 2 group as a deactivator and the bromide as a weak activator on the other side in compound 4m . These groups govern the electron’s push and pull mechanism in these molecules. Molecular electrostatic potential MEP maps (molecular electrostatic potential) are useful 3D plots for visualizing the charge distribution, size, and shape of compounds under investigation. These maps depict a proton's energy about its current position. The density of electrons is represented in different colors on these maps, providing information about a molecule relative polarity. The molecular electrostatic potentials of the molecules are presented in Fig. 6 ( 4a–4t ) calculated at PBE0-D3BJ/def2-TZVP/SMD DMSO level of theory. In Fig. 6 ( 4a–4t ), the electron-rich nucleophilic positions of the molecule in red, while sites with lower electron density are depicted in blue can be seen. So, it can be understood in terms of nucleophilic or electrophilic sites, Fig. 6 ( 4a–4t ) can be visualized individually for their electrophilic and nucleophilic sites. In compounds 4h , 4m , and 4r the electron density is distributed equally throughout the molecule while in other compounds the red color depicts the unequal charge distribution on the molecule. Conceptual DFT reactivity descriptors The chemical reactivity descriptors of a molecule include electron affinity ( A ), ionization potential ( I ), chemical hardness ( ƞ ), electronic chemical potential ( μ ), and Nucleophilicity Index ( N ) which were determined by FMO calculations. The values of all the important reactivity descriptors of the compounds under study are given in Table 5 . The Koopman’s theorem was used to calculate I and A which stated that the negative of E HOMO and E LUMO correspond to the ionization potential ( I ) and electron affinity ( A ) of the compound [ 62 , 63 ]. The other descriptors i.e., η (chemical hardness), μ (electronic chemical potential), ω (electrophilicity index), and N (Nucleophilicity Index) are then subsequently calculated as shown in Eqs. (1)–(4) . Table 5 shows the values of all the crucial reactivity descriptors for the compounds under investigation. Chemical hardness, a measure of a substance's resistance to deformation, is prominently featured. As the chemical hardness value increases, reactivity tends to decrease, indicating greater stability for the substance. So, it can be suggested that the HOMO-LUMO gap is supported by the ƞ values as compound 4h has one of the lowest ƞ values and 4d has the highest ƞ value. Chemical potential is the ability of a system to accept or donate the electrons, lower the chemical potential, lower the electron-acceptance and vice versa. In the light of chemical potential, 4h shows highest μ value, supporting its electron-donating nature. Ionization potential and electron affinity values also supports the higher reactivity of 4h as observed through chemical potential and electrophilicity index. The nucleophilicity index ( N ) is the measure of the ease of donation of an electron pair by a molecule or an atom to an electrophile and calculated, based on the scale proposed by Domingo [ 64 ]. Thus, higher the value of ( N ), higher is the reactivity towards electrophiles. According to Table 5 , 4j shows higher reactivity towards electrophiles and 4m indicates lower reactivity towards the electrophiles.

Results and discussion Chemistry of spiropyrazoline-indolinones New spiropyrazoline-indolinones (4a–4t) were synthesized using DES as a catalyst in addition to its role as reaction media. The multicomponent reaction proceeded with 5-Cl or 5-Br isatin ( 1a/1b ), acetophenone or 2-acetyl thiophene ( 2a / 2b ) and different hydrazine analogs ( 3a–3e ) in the presence of diethyl amine (DEA). In general, the multicomponent reaction proceeded leading to the cyclization step. According to available protocols [ 26 , 27 ], initially two steps of synthetic protocols were followed which were low yielded due to purification issues. These unsatisfactory outcomes were our motivation to explore one-pot, two-steps strategy for spiropyrazolines synthesis which sounds promising. In the first step, exocyclic α,β -unsaturated ketone ( I ) was produced by the reaction of 1a/1b with acetyl ketone 2a/2b . In the second step, enone ( I ) and selected hydrazine derivatives ( 3a–3e ) were reacted to furnish a desired product which underwent column purification as mentioned in Scheme 1 . The plausible reaction mechanism showed Aldol condensation in the first place then Michael addition reaction to yield the final product [ 9 , 22 , 28 ]. In the Aldol reaction, DEA acts as a base to abstract acidic proton from acetophenone to yield a reactive anionic intermediate which quickly reacts with the carbonyl group of isatin to furnish a stable α,β -unsaturated ketone ( I ). The exocyclic C=C of enone is attacked by nitrogen of hydrazine analogous to Micheal addition to start a reaction series that furnishes pyrazoline ring finally. DES played an important role in catalyzing via hydrogen bonding with carbonyl oxygen ( I ), thus making it more electrophilic and providing the ease of nitrogen attack to form a spiro junction ( Fig. 2 ). The reaction conditions favored the aldol mechanism as it occurs at room temperature while another possibility is to achieve formation via Schiff ‘s base route, however, it requires elevated temperature. Optimization of reaction conditions Initially, the reaction between isatin, acetophenone and thiosemicarbazide was chosen for optimization studies. For this, the equimolar ratio of reactants was treated in the presence of 1 mmol of different suitable bases in ethanol and diethyl amine (DEA) formed the most appreciable amount of product ( Table 1 , entry 4). Initially isatin reacted with acetophenone to give a yellow mixture that further became orange-yellow product after stirring the reaction media for 7 min which indicated the existence of exocyclic α , β -unsaturated enone ( I ). Reaction progress was monitored via TLC technique and FTIR spectroscopy. Without any purification step, thiosemicarbazide ( 3d ) was added in the same vessel which was refluxed in the presence of ethanol. The yield was improved by increasing the DEA concentration gradually from 1 to 1.3 mmol ( Table 1 , entry 7). Any further increase in DEA amount retarded the reaction due to the formation of imine as a side product. To avoid volatile organic solvents as much as possible and reduce reaction time, the above-mentioned reaction was also carried out in benign media such as neutral deep eutectic solvent (DES-1 to DES-3) and the results were compared with ethanol. It was observed that DES-1 produced an excellent yield (86 %) while DES-2 and DES-3 furnished lower yields and took comparatively longer time in product formation ( Table 1 , entry 12, 13, 14). It was envisioned to study the spiropyrazoline-indolinones synthesis at different temperatures, i.e., 25, 45, 65 and 70 °C using DES-1 which concluded 65 °C as the optimum reaction temperature as further increase in temperature decrease the yield ( Table 1 , entry 17). This could be explained by a lowering in H-bonding between the carbonyl oxygen of ketone and DES at elevated temperature. Microwave mediated synthesis of spiropyrazoline-indolinones ( 4a–4t ) Optimization studies were conducted to find the most suitable reaction conditions which were experimented to produce a variety of products in DES-1 using 5-Cl/Br isatin ( 1a / 1b ) with two different acetyl ketones ( 2a and 2b ) and different hydrazine derivatives ( 3a–3e ) ( Scheme 1 ). Targeted derivatives were produced after simple workup in 24 min to 3 h in a conventional setup (entries 7 and 9, Table 1 ). Hydrazine 3a was employed to produce 4a, it was formed in a longer time (2.5 h) with a low yield (42 %) while hydrazine 3b gave a moderate yield (63 %) of 4b in 1.5 h. Thiosemicarbazide ( 3d ) furnished 4d with a high yield (86 %) in 24 min which is due to the good nucleophilicity of hydrazine moiety while others are less reactive due to electron withdrawing functionalities ( Table 3 ). The overall outcomes showing the reactivity of hydrazine analogs in the case of 1a with 2a are mentioned in descending order as 3d > 3e > 3b > 3c > 3a . After examining the behavior of acetophenone ( 2a ), the next 2-acetyl thiophene ( 2b ) was reacted which showed the same reactivity order as observed in the case of ketone 2a . This observation indicated that the electron withdrawing ability of chloro as well as nitro substituent on aromatic ring was responsible for decreasing the hydrazine reactivity. Overall 2a produced better results than 2b indicating the superiority of the phenyl ring of ketone over the thienyl ring. In the case of 1b as substrate, hydrazine reactivity order was almost similar as mentioned above with slight variation. Hydrazine 3d and 3e reacted faster than 3c when acetophenone was used. Only a few reports highlight the clean and fast synthesis of spiropyrazoline in microwave [ 29 ]. So, inspired by this fact, an experimental study for new spiropyrazolines ( 4a–4t ) has also been carried out at 70 o C in the synthetic microwave. To explore the optimum reaction conditions in a synthetic microwave reactor, a model reaction was performed using the equimolar ratio of the same reactants as used in classical settings. The reaction contents were irradiated at different power levels ranging from 100 to 280 W and product formation was observed by TLC. Results depicted that the reaction rate at 100 W was very slow which produced a 19% yield in 25 min whereas it was improved by increasing the power level gradually. At 240 W, the highest yield (82%) was obtained in 8 min ( Table 2 , entry 4), however, a further increase in power level furnished gummy product indicated impurities and side products. Once the best radiation level was achieved, the optimum catalyst amount was explored by using two concentrations of DEA in the reaction. At first, the equimolar ratio of reactants along with the catalyst was experimented, while 1.3 eq. of DEA was used in the second attempt ( Table 2 ). Both the concentrations were applied by performing several reactions at different times. In the case of 1:1:1, 8 min was the optimum time for the required product ( Table 2 , entry 4). It was observed that an increase in reaction time decreased the yield. This could be rationalized by the high heating effect of the reaction chamber. In the case of ratio 1:1:1.3, it was investigated that comparable yields were recorded at 8 and 15 min whereas after 18 min irradiations maximum yield (52 %) was achieved. These observations concluded that the mole ratio 1:1:1 was better than 1:1:1.3 in terms of reaction time product yield. Versatility and the scope of the adopted procedure were studied by synthesizing a series of spiropyrazolines ( 4a–4t ) from diketones. The mild reaction conditions enabled the incorporation of synthetically useful functionalities in the substrate. Its internal heating is more homogeneous than classical heating. The effect of substituted hydrazines ( 3a–e ) was explored by comparing the yield of the desired products and reaction time. The spiropyrazoline 4a and 4b were furnished using 3a and 3b, respectively, in 9 min with moderate yield (58 %) to good yield (75%), revealing the role of chloro group at phenyl moiety. The product 4c was synthesized in 10 min with moderate yield due to the presence of electron-withdrawing effect of two nitro groups on the phenyl ring of hydrazine ( 3c) . The best results were obtained in 8 min for the formation of 4d with 82% yield. The yield of 4e was also close to that of 4d and this observation is rationalized by the appreciable nucleophilic character of hydrazine 3d and 3e . From the results, it was inferred that the reactivity of hydrazine 3b was better than its analogs 3a a nd 3c when reacted with acetophenone. In the case of 2-acetyl thiophene, 3d is the most reactive as compared to other analogs. However, 4l was produced in 76 % in 12 min when reacted with 3b ( Table 3 , entry 12). To study the effect of two diketones; 1a and 1b , the yield of 4a - 4j was compared with 4k - 4t and 5-bromo isatin was found more reactive. The effect of ketones 2a and 2b was also understandable by comparing yield which showed better results with 2-acetyl thiophene ( 4f - 4j ). Conventional and microwave approach of synthesis was analyzed for Scheme 1 which concluded that the classical method was lengthier in reaction time (0.5–3 h) in the presence of ethanol with moderate yield (41–86 %). While microwave-assisted synthesis (time 8–17 min, with moderate yield (41–86 %) is preferred; Microwave method > Conventional method. However, ethanol has been used as a reaction medium to facilitate microwave heating while conventional setup has used biodegradable deep eutectic solvent. It is easily prepared from non-toxic and low-cost chemicals. Their compositional flexibility makes it popular for the preparation of a variety of spiropyrazolines. From an environmental point of view, the classical synthesis described here is preferred over non-classical reaction setup ( Table 3 ). If the microwave is not available, spiropyrazolines can be successfully prepared in DES, avoiding volatile organic solvents. Physical properties and spectroscopic data of newly synthesized spiropyrazoline-indolinones ( 4a–4t ) are mentioned in supporting information. All prepared DESs were confirmed by FTIR [ 30 ]. The freezing point of DES-1 [ 31 ], DES-2 [ [32] , [33] , [34] ] and DES-3 [ 35 , 36 ] was found to be 12. 5 and −40 °C respectively. Structure confirmation of newly synthesized compounds was achieved with elemental analysis, 1 HNMR and 13 CNMR and FTIR spectroscopy. The spectral data is well agreed with the literature values [ 37 ]. Based on the most supportive 13 C NMR data, the spiro junction in spiropyrazoline was confidently assigned as a quaternary carbon at 70.21 ppm. The formation of diazole rings was confirmed by an absorption band in the FTIR spectrum at 1250 cm −1 for the C–N stretch and 3232 cm −1 for the N–H stretch. The 1 H NMR spectrum confirmed this, with two singlets at 6.91 and 6.24 ppm assigned to H-4' and the hydrogen attached to the diazole nitrogen, respectively. Furthermore, in the 1 H NMR spectrum, a set of doublets at 6.94 ppm and a double doublet at 7.38 ppm confirmed the involvement of the ketone skeleton provided by 1a . The phenyl protons resonating at 7.52–7.64 ppm indicated that acetophenone had successfully contributed to ring formation, which was supported by the quaternary carbon resonating at 127.05 ppm (C-5 of 4a ). The FTIR spectrum provided additional confirmation, with absorption at 1608 cm −1 indicating the presence of a C=C stretch for the diazole ring. Aromatic protons attached to nitrogen were responsible for the multiplet observed in the 1 H NMR spectrum at 7.71–7.89 ppm. In addition, the C=O group at C-2 was assigned a downfield signal in the 13 C NMR spectrum at 162.84 ppm. The 1 HNMR spectra of 4b to 4t , revealed a singlet at 6.62–6.91 ppm designated to H-4. On the other hand, its 13 CNMR was found to be supportive by displaying a quaternary carbon singlet in the range of 69.21–70.83 ppm as proof of spiro 1,2 diazole ring formation. In 4e , an additional signal observed at 29.24 ppm indicated the (C-3′′′) of thiosemicarbazide in 13 CNMR. Compound 4f displayed a multiplet at 7.71–7.84 ppm, designated to thiophene moiety in the 1 HNMR spectrum. The 1 HNMR spectrum of 4g , a multiplet (4H) resonated in the aromatic region 7.42–7.59 ppm was attributed to phenyl protons as a substituent of hydrazine. The 1 HNMR spectrum of 4h , showed a double doublet at 8.30 ppm and two doublets at 7.69 and 7.94 ppm with the ABX splitting pattern showing the presence of 2,4-dinitro phenyl moiety. The 13 CNMR spectrum of 4i revealed a high field signal at 177.36 ppm designated to thioamide moiety while a signal at 106.63 ppm was attributed to methine carbon as C-4′. Some of the significant signals in 13 CNMR of 4j exhibited at 166.46 ppm were credited to C-2 of 5-chloroisatin, 106.43 ppm to C-4′, 27.46 and 177.32 ppm were designated to methyl and quaternary carbon of thiosemicarbazide. The compounds from 4k to 4t are bromine analogs of spiropyrazoline and are in close agreement with chlorine analogs 4a to 4j . Nonetheless, condensations as well as cycloaddition reactions have a high potential to furnish very interesting spirocyclic frameworks. In the light of high demand of spiropyrazolines, it is speculated that the development of this new synthetic protocol will also present future insight into this area. Computational studies Theoretical studies serve as a complement to verify and support experimental data. DFT serves as a powerful tool to predict various properties including chemical reactivity, stability and electronic structure. Gaussian 09 revision D.01 [ 38 ] has been used for all the calculations done in the present study. All the calculations have been performed using density functional theory (DFT) using the density functional PBE0 [ 39 , 40 ] with a triple ζ basis set def2-TZVP [ 41 ]. The non-bonding effects in the molecules were added using Grimme’s empirical dispersion correction [ [42] , [43] , [44] ] as implemented in Gaussian 09. The said method has been benchmarked earlier by us on a variety of similar studies and others as well and it proved to produce good results [ [45] , [46] , [47] , [48] , [49] , [50] , [51] ]. Solvent effects were added through the Polarizable Continuum Model (PCM) [ [52] , [53] , [54] , [55] , [56] , [57] , [58] ] added through Truhlar’s SMD parameter [ 59 ]. Frequency calculations on optimized geometries have been performed to confirm the structures as true minima by the absence of imaginary frequencies. GaussView and CYLview [ 60 ] software tools have been used to visualize the calculation results and produce figures for the manuscript. The optimized structures are depicted in Fig. 3 (a–t), i.e., chlorospiropyra acetophenones ( Fig. 3 4a–4e ), chlorospiropyra thiophenes ( Fig. 3 4f–4j ), bromospiropyra acetophenones ( Fig. 3 4k–4o ), and bromospiropyra thiophenes ( Fig. 3 4p–4t ) were 3D modelled and optimized using Gaussian 09 rev. D01 software. The optimized structures were then analyzed for vibrational frequencies to confirm the absence of imaginary frequencies, establishing them as true potential energy surface (PES) minima. DFT calculations were used to determine the Frontier Molecular Orbital (FMO) Analysis, hyperpolarizability, molecular reactivity, and physical properties of compounds are computed and are depicted in Fig. 4 ( a–j ), i.e., ( 4a–4e ) the frontier orbitals of the chlorospiropyra acetophenones and ( 4f–4j ) chlorospiropyra thiophenes. The frontier orbitals were calculated at PBE0-D3BJ/def2-TZVP/SMD DMSO level of theory and are presented in Fig. 5 ( a–t ), i.e., bromospiropyra acetophenones ( 4k–4o ), and bromospiropyra thiophenes ( 4p–4t ) [ 61 ] . Table 4 enlists the HOMO-LUMO gap (ΔE) and hyperpolarizability ( β ) values of all the compounds ( 4a–4t ). The ΔE values of these molecules are in a relatively narrow range from 3.63 to 4.79 eV which means that their reactivity is almost similar. The lowest ΔE value of compound 4h (3.63 eV) suggests it to be the most reactive among the series. That can be attributed to the inductive electron withdrawing –Cl group on one phenyl ring and –NO 2 group on the other phenyl ring in the molecule. Similarly, 4d has the highest ΔE value (4.79 eV) which establishes it to be the most stable in the series. The next most stable compounds are 4k and 4l which have deactivating Br group on the aromatic ring. All the HOMO and LUMO energies are given in eV. The distribution of iso-density seems very similar in these compounds. In chlorospiropyra acetophenones ( 4a–4e ), chlorospiropyra thiophenes ( 4f–4j ), bromospiropyra acetophenones ( 4k–4o ), and bromospiropyra thiophenes ( 4p–4t ), the iso-density is mainly spread over the whole molecule except the chloro- and bromo-substituted rings in all the compounds under study for HOMO. Interestingly, LUMO iso-density is also located on the rest of the molecule except the chloro and bromo-substituted aromatic rings. Only in the case of compound 4o , it is located on the bromophenyl ring as well to some extent. The hyperpolarizability ( β ) values of the compounds under study do not show them as potent non-linear optical (NLO) materials but four of them ( 4c , 4h , 4m , and 4r ) show quite good NLO response. The highest β value is shown by compound 4m and the second highest is shown by 4c , 4h and 4r . That can be explained by the presence of the –NO 2 group as a deactivator and the bromide as a weak activator on the other side in compound 4m . These groups govern the electron’s push and pull mechanism in these molecules. Molecular electrostatic potential MEP maps (molecular electrostatic potential) are useful 3D plots for visualizing the charge distribution, size, and shape of compounds under investigation. These maps depict a proton's energy about its current position. The density of electrons is represented in different colors on these maps, providing information about a molecule relative polarity. The molecular electrostatic potentials of the molecules are presented in Fig. 6 ( 4a–4t ) calculated at PBE0-D3BJ/def2-TZVP/SMD DMSO level of theory. In Fig. 6 ( 4a–4t ), the electron-rich nucleophilic positions of the molecule in red, while sites with lower electron density are depicted in blue can be seen. So, it can be understood in terms of nucleophilic or electrophilic sites, Fig. 6 ( 4a–4t ) can be visualized individually for their electrophilic and nucleophilic sites. In compounds 4h , 4m , and 4r the electron density is distributed equally throughout the molecule while in other compounds the red color depicts the unequal charge distribution on the molecule. Conceptual DFT reactivity descriptors The chemical reactivity descriptors of a molecule include electron affinity ( A ), ionization potential ( I ), chemical hardness ( ƞ ), electronic chemical potential ( μ ), and Nucleophilicity Index ( N ) which were determined by FMO calculations. The values of all the important reactivity descriptors of the compounds under study are given in Table 5 . The Koopman’s theorem was used to calculate I and A which stated that the negative of E HOMO and E LUMO correspond to the ionization potential ( I ) and electron affinity ( A ) of the compound [ 62 , 63 ]. The other descriptors i.e., η (chemical hardness), μ (electronic chemical potential), ω (electrophilicity index), and N (Nucleophilicity Index) are then subsequently calculated as shown in Eqs. (1)–(4) . Table 5 shows the values of all the crucial reactivity descriptors for the compounds under investigation. Chemical hardness, a measure of a substance's resistance to deformation, is prominently featured. As the chemical hardness value increases, reactivity tends to decrease, indicating greater stability for the substance. So, it can be suggested that the HOMO-LUMO gap is supported by the ƞ values as compound 4h has one of the lowest ƞ values and 4d has the highest ƞ value. Chemical potential is the ability of a system to accept or donate the electrons, lower the chemical potential, lower the electron-acceptance and vice versa. In the light of chemical potential, 4h shows highest μ value, supporting its electron-donating nature. Ionization potential and electron affinity values also supports the higher reactivity of 4h as observed through chemical potential and electrophilicity index. The nucleophilicity index ( N ) is the measure of the ease of donation of an electron pair by a molecule or an atom to an electrophile and calculated, based on the scale proposed by Domingo [ 64 ]. Thus, higher the value of ( N ), higher is the reactivity towards electrophiles. According to Table 5 , 4j shows higher reactivity towards electrophiles and 4m indicates lower reactivity towards the electrophiles.

Conclusion In summary, highly functionalized new spiropyrazoline-indolinones have been developed through a facile, one-pot two-step, multicomponent green methodology. This protocol features catalyst-free conditions, green solvents, mild reaction conditions, easy work-up with high yield, and short reaction time. The tricyclic spiro framework, as the final product, could serve as important scaffolds for drug discovery and be advantageous for both medicinal and synthetic chemists. The structural and electronic properties can be understood through density functional theory calculations performed on the synthesized chlorospiropyra acetophenones (4a-4e) and thiophenes (4f-4j), as well as bromospiropyra acetophenones (4k-4o) and thiophenes (4p-4t). Furthermore, an examination of frontier orbitals and other reactivity descriptors, such as ionization potential, electron affinity, chemical hardness, electronic chemical potential, and electrophilicity index, revealed that compound 4h is the most reactive in the series, while compound 4d is the most stable.

Novel spiropyrazoline-indolinones ( 4a–t ) have been synthesized successfully in neutral deep eutectic solvents by reacting 5-Cl/Br-isatin ( 1a–b ) with aromatic ketones ( 2a–b ) and a variety of substituted hydrazines ( 3a–e ) in good to excellent yields. This eco-friendly straightforward synthetic protocol discloses good functional group compatibility. The conventional synthetic approach was compared with the greener route of microwave-assisted synthesis of spiropyrazolines using ethanol. This approach utilized mild reaction conditions which furnished high yields in short reaction time employing one pot two-step multicomponent. All new compounds were structurally confirmed by detailed spectroscopic analysis and density functional theory calculations. This method provides efficient access to spiropyrazole derivatives using biodegradable and green solvent. Keywords

Research funding This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R158), 10.13039/501100004242 Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia . The authors extend their appreciation to the Deanship of Scientific Research at 10.13039/501100007446 King Khalid University for funding this work through large group Research Project under grant number RGP.2/575/44. Data availability statement Data included in article/supp. material/referenced in article. CRediT authorship contribution statement Zubi Sadiq: Writing – original draft, Investigation. Ambreen Ghani: Formal analysis, Data curation. Muhammad A. Hashmi: Software, Methodology, Data curation. A. Dahshan: Software, Formal analysis, Funding acquisition. Shahnaz: Project administration, Methodology. Samiah H. Al-Mijalli: Resources, Funding acquisition. Munawar Iqbal: Writing – review & editing, Validation. Erum A. Hussain: Methodology, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary data The following is the Supplementary data to this article: Acknowledgements The authors extend their appreciation to the Deanship of Scientific Research at 10.13039/501100007446 King Khalid University for funding this work through large group Research Project under grant number RGP.2/575/44. The authors express their gratitude to Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R158), 10.13039/501100004242 Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia . The authors acknowledge the Higher Education Commission of Pakistan and Lahore University of Management Sciences for technical assistance. Additional computer time was provided by the Victoria University of Wellington High Performance Computer Facilities Raapoi and Heisenberg .

CC BY

no

2024-01-16 23:43:42

Heliyon. 2023 Dec 20; 10(1):e23814

oa_package/98/45/PMC10788502.tar.gz

PMC10788504

38226174

Introduction Brain-computer interfaces (BCIs) constitute a promising tool for establishing direct communication and control from the brain over external effectors for clinical applications. 1 , 2 However, the ideal features to design a BCI are unknown, since the underlying microscopic brain processes and their reflection on brain signals, are poorly understood. 3 As a result, mastering noninvasive BCI systems remains a learned skill that yields suboptimal performance in ∼30% of users, referred to as the “BCI inefficiency” phenomenon. 4 Measuring the dynamic features that are relevant to the execution of a task and, as a consequence, may improve BCI performance remains an open challenge. 3 Indeed, the current features that are used in the context of BCI rely on local measurements 5 (mostly frequency band power features and time-point features, depending on the BCI paradigm) disregarding the interconnected nature of brain dynamics. Electromagnetic imaging data are dominated by ‘bursty’ dynamics, with fast, fat-tailed distributed, aperiodic perturbations, called “neuronal avalanches”, traveling across the whole brain, 6 , 7 , 8 , 9 that have been recorded using electro/magnetoencephalography. 10 , 11 Neuronal avalanches spread preferentially across the white-matter bundles, 12 they are modified by neurodegenerative diseases, 13 and they evolve over a manifold during resting-state, generating rich functional connectivity dynamics. 14 Such rich dynamics are a major contributor to time-averaged functional connectivity. 6 , 15 Hence, the spreading of neuronal avalanches might be a correlate of the functional interactions among brain areas and, as such, we hypothesize that they could spread differently according to the task at hand, thereby providing a powerful and original marker to differentiate among behaviors. To test our hypothesis, we compared source-reconstructed magnetoencephalography (MEG) signals in resting state (RS) and while performing a hand motor imagery (MI) task within a BCI protocol, in order to track the dynamical features related to motor imagery as compared to rest. We obtained the probabilities of each pair of regions being recruited sequentially in an avalanche, 12 compared these probabilities across MI and RS conditions edge- and subject-wise, and related the differences between the two conditions to the performance in the BCI task, as measured using the BCI classification accuracy. Furthermore, we used these features to decode the tasks from source-reconstructed data.

STAR★Methods Key resources table Resource availability Lead contact Marie-Constance Corsi ( marieconstance.corsi@icm-institute.org ). Materials availability Given the personal nature of the data, it is not possible to make it public now. However, the data is available upon request to the corresponding authors for the purpose of replication. Data and code availability (1) The conception of the protocol was done before changes in the French legislation regarding the data sharing process. Therefore, there is a substantial number of requirements to be met before being allowed to share the data. At this point, it is not possible to make the data public now. However, the data is available upon request to the corresponding authors for the purpose of replication. (2) The code is publicly available at https://github.com/mccorsi/NeuronalAvalanches4BCI.git . (3) Any additional information required to reanalyze the data reported in this work paper is available from the lead contact upon request. Experimental model and study participant details The research was conducted in accordance with the Declaration of Helsinki. A written informed consent was obtained from subjects after explanation of the study, which was approved by the ethical committee CPP-IDF-VI of Paris. All participants received financial compensation at the end of their participation. Twenty healthy subjects (27.5 ± 4.0 years old, 12 men), with no medical or psychological disorder, were recruited. They participated in a BCI experiment where MEG and EEG were simultaneously recorded. A description of the participants characteristics is provided in the Table S1 . In the French legislation is not allowed to register the ancestry, race, or ethnicity of the participants unless the main aim of the protocol is the assessment of the effect of such information on the observations. Therefore, the authors cannot provide such participant information. Method details BCI experiment We used the dataset from Corsi et al. 29 The BCI task consisted of a standard two-target box task, 43 where the subjects were instructed to modulate their alpha and/or beta band brain activity to control the vertical position of a moving cursor to hit a gray vertical bar, referred as the target, displayed on the right part of the screen. To hit the “up-target” the subjects had to perform a sustained hand motor imagery (MI) of the right-hand grasping and to hit the “down-target”, the subjects were instructed to remain at rest. Each run was composed of 32 trials each with either up and down targets, respectively associated with MI and Rest instructions, equally and randomly distributed across trials. The online BCI experiment was composed of two phases (see Figure S10 ). i) the training phase, divided in five consecutive runs without providing any feedback, meaning that the gray target was the only element displayed on the screen. Each trial consisted of 1s of inter-stimulus interval (ISI) followed by 5s of target presentation. At the end of the training phase, offline analysis consisted of extracting R-square maps from the power spectra computed from the collected data to plot contrast maps between conditions to elicit the most relevant information, namely the (channel; frequency bins) couples of interest that best discriminate the subjects’ intent, to train the classifier. ii) the testing phase was made of six runs where the feedback, consisting of a moving cursor, was provided. Each trial consisted of 1s of ISI, followed by 5s of target presentation. The feedback was provided from t = 3s to t = 6s. It consists of a cursor that starts from the left to the right part of the screen with a fixed velocity. Experimenters instructed the subjects to start to either remain at rest or to perform a sustained MI task as soon as they saw the target, i.e., at t = 1s. The online features were obtained from the estimation of the power spectra via an autoregressive model that relied on the maximum entropy method 44 every 28 ms on a time window of 0.5s. These features were classified using the Linear Discriminant Analysis (LDA) method. The feedback provided to the subject, namely the vertical position of the moving cursor, relied on the linear combination of the computed features via the moving average method. 45 The BCI performance used in this study refers to the proportion of trials in which the subjects could control the vertical position of the moving cursor to hit the target. In this work, the analysis relied on the data obtained from the testing phase. M/EEG data acquisition and preprocessing EEG signals were recorded with a 74 EEG-channel system, with Ag/AgCl passive sensors (Easycap, Germany) placed according to the standard 10-10 montage, with the references placed at the mastoids, and the ground electrode located at the left scapula. MEG signals were recorded via a system composed of 102 magnetometers and 204 gradiometers (MEGIN Neuromag TRIUX MEG system). M/EEG signals were simultaneously recorded in a magnetic shielding room with a bandwidth of 0.01–300 Hz and a sampling frequency of 1 kHz. Head positions were digitized via the Polhemus Fastrak digitizer (Polhemus, Colchester, VT). Three points were used as landmarks to provide co-registration with the individual anatomical MRI: nasion, left and right pre-auricular points. Individual T1 sequences (256 sagittal slices, TR = 2.40 ms, TE = 2.22 ms, 0.80 mm isotropic voxels, 300x320 matrix; flip angle = 9°) were acquired with a 3T Siemens Magnetom PRISMA after the BCI experiments. Subjects were instructed to remain at rest for 15 min. Images were preprocessed with the FreeSurfer toolbox 46 and imported to the Brainstorm toolbox 47 where the digitized locations of the landmarks, and of the EEG electrodes were aligned with the MRI. To remove the environmental noise in MEG signals, we applied the temporal extension of the Signal Space Separation (tSSS) with MaxFilter. 48 To remove ocular and cardiac artifacts, we performed an Independent Components Analysis (ICA) via the Infomax approach with the Fieldtrip toolbox. 49 , 50 Only the components that contained physiological artifacts were removed through a visual inspection of the signals. Once the data was preprocessed, we cut the recordings into epochs of 7 s. Source reconstruction was performed by the computation of individual head models with the Boundary Element Method (BEM) 51 , 52 where the surfaces were obtained from three layers related to the individual MRI (scalp, inner skull, outer skull) that contained 1922 vertices each. Sources were estimated via the weighted Minimum Norm Estimate (wMNE). 53 , 54 In this work, we used the Desikan parcellation scheme. 55 The list of the regions of interest is available in the Table S2 . For a complete description of the preprocessing steps, please refer to Corsi et al. 29 Data pipeline Each source-reconstructed signal was z-scored (over time), thresholded, and set to 1 when above threshold, and to zero otherwise (threshold: z = |3| 10 ). Note that each region was z-scored independently (over time). Then, an avalanche was defined as starting when at least one region is above threshold, and as finishing when no region is active. For each avalanche, we estimated a transition matrix, structured with regions in rows and columns, and the ij-th edge is defined as the probability that regions j would be active at time t+1, given region i was active at time t. 13 , 56 To consider the intra-regional dynamics, the main diagonal of the transition matrix contains the probability that if a region is recruited by an avalanche, it will keep being active at the successive time step. For each subject, we obtained an average transition matrix (i.e., averaging edge-wise over all avalanches) for the baseline condition, and an average transition matrix for the hand motor imagery task. To ensure appropriate sampling, 57 we have binned the data with bins ranging from 1 to 3 (stopping at three to avoid aliasing). To select the optimal binning, we looked at the branching ratio, since a branching ratio 1 typically indicates a process operating near a critical regime. The branching ratio is calculated as the geometrically averaged (over all the time bins) ratio of the number of events (activations) between the subsequent time bin (descendants) and that in the current time bin (ancestors) - Equation 1 , as: and then geometrically averaging it over all the avalanches - Equation 2 . 22 where σ i is the branching parameter of the i-th avalanche in the dataset, N bin is the total amount of bins in the i-th avalanche, n events (j) is the total number of events active in the j-th bin, and N aval is the total number of avalanches in each participant’s recording. In branching processes, a branching ratio of σ = 1 indicates critical processes with activity that is highly variable and nearly sustained, σ < 1 indicates subcritical processes in which the activity quickly dies out, and σ > 1 indicates supercritical processes in which the activity increases as runaway excitation. The bin length equal to one sample yielded a σ = 1, hinting at the avalanches as occurring in the context of a dynamical regime near operating near criticality, was chosen for subsequent analyses. Importantly, the other binnings also yielded branching ratios extremely close to 1 (0.995, and 0.978 for binnings 2 and 3, respectively), and the results of the analyses remain unchanged, showing resilience to the details of the pipeline. However, one should notice that this particular dataset entails rather short epochs and, as such, it is not best suited for the evaluation of a long tail. This is all the more true considering that a stimulus was being delivered and, as such, the dynamics was not evolving unperturbed. In order to compare how the trials are encoded in the data, we provide a comparison with standard feature extraction techniques, we computed the power spectra, via the Welch method with a window length of 1 s and a window overlap ratio of 50%, the event-related desynchronization/synchronization (ERD/S) effects via Morlet wavelets with a central frequency of 1 Hz and a time resolution of 3s between 3 and 40 Hz, 58 , 59 and the phase-locking value, as in Lachaux et al. 60 The PLV was chosen for its straight-forward interpretation, and for its theoretical assumptions (i.e., stationarity of the signal), which is different from the one of the ATMs. Even though working in the source space may mitigate the volume conduction effects, 61 it is important to mention that the PLV method is influenced by zero-lag interactions, which might be either true interactions or spurious correlations induced by the field-spread. For these analyses, the classification of the trials as MI or RS was based on the outcome of the experiment. To explore the robustness of our results to different classification algorithms, we also classified the trials as MI/RS based on either Linear Discriminant Analysis or a Support Vector Machine. The results showed that our conclusions are robust to the classification algorithm (see Figure S6 ). Classification analysis To assess the extent to which the ATMs might be considered as an alternative feature for BCIs, we compared the classification performance resulting from a feature extraction approach based respectively on the ATMs and on spatial filters, namely Common Spatial Patterns (CSP). 18 , 19 In addition, as a preliminary study, we also tested the classification performance associated with other features such as the power-spectra (of the source-reconstructed time-series) and the phase-locking values. All the considered features were classified with two different techniques, namely linear discriminant analysis (LDA) and support vector machines (SVM). We obtained the best classification performance using CSP followed by the Support Vector Machine (SVM) classifier. Therefore, we selected this framework as the benchmark against which ATMs were compared. For each subject, we divided the dataset to include 80% of the trials in the train split and 20% of the trials in the test split. The classification scores for all pipelines were evaluated with an accuracy measurement using a random permutation cross-validator. 50 re-shuffling and splitting iterations were performed. The SVM was trained using either the CSPs or the ATMs. For each subject, the CSP method decomposes the source-reconstructed signals using spatial filters, and then selects the n modes that capture most inter-class variance. Here, we selected eight spatial modes (since they yielded the best classification accuracy) and returned the average power of each. As for the ATMs, for each subject we found the optimal Z score threshold for identifiability. Then, we fed an SVM classifier with either feature (CSP-filtered data or ATM). Finally, we compared the classification performance (i.e., the proportion of correctly labeled trials) for CSP+SVM and ATM+SVM, over 50 random splits of the data. For each subject, we ran t-tests (and confirmed them with Wilcoxon) under the null hypothesis that CSP+SVM and ATM+SVM would not yield a statistically different performance in trial classification. We repeated this comparison for all the subjects and corrected the statistical comparisons for multiple comparisons across subjects using the False Discovery Rate (FDR). To calculate the inter-subject variability, we used the standard deviation of the classification performance across splits and subjects. As per the intra-subject variability, we calculated the standard deviation of the classification accuracy across the 50 splits for each subject. To estimate the computational time required to extract and to classify the features, we used a built-in function in python. Quantification and statistical analysis For each subject, we computed the difference in the probability of a perturbation running across a given edge during resting-state and during the MI task. To statistically validate this, for each individual, we randomly shuffled the labels of the individual avalanches (i.e., each trial-specific transition matrix was randomly allocated to either resting-state and hand motor imagery). We performed this procedure 10000 times, obtaining, for each edge, the distribution of the differences given the null-hypothesis that the transition matrices would not capture any difference between the two conditions. Note that this approach does not require normality of the original distributions. We used the null distribution to obtain a statistical significance for each edge. The retrieved significances were Benjamini-Hochberg-corrected for multiple comparisons across edges. 16 Following this procedure, we obtained for each patient, a matrix with the edges that significantly differed from the two conditions. We then looked at the concordance of such matrices across subjects, as to only focus on the edges that are reliably related to the task at hand. We have only selected those edges that were significant in a higher-than-chance number of subjects. Finally, we selected only those nodes that had more significantly different edges incident upon them, as compared to chance level. This way, we selected the areas whose involvement in large-scale dynamics is qualitatively different, in multiple subjects, between the two conditions (i.e., RS vs. MI task), and refer to these as the “task-specific” areas. Then, we moved on to check what edges differed related to the BCI performance. To this end, we related, for each edge, the individual differences in the transition probabilities in the two experimental conditions to the individual BCI performances. We then grouped the edges according to functional areas, namely: executive areas, pre/motor areas, parietal areas, temporal areas, and occipital areas. To statistically validate this approach, for 10000 we have randomly allocated the edges to these groups and computed the average correlation coefficient at each iteration for each group of edges. We used these averages to build a null-distribution for each functional area, and used to have a statistical significance. Finally, these significances were corrected across functional regions using the BH correction for multiple comparison. We have repeated the correlation analysis without grouping the regions into functional areas but carrying out the correlation analysis for each region separately. In this case, no single region survived the BH correction (not shown). Finally, we replicated our results using the Destrieux parcellation scheme 62 (the associated list of the regions of interest is available in the Table S2 ) and using the electroencephalogram. Furthermore, we repeated the analysis changing the threshold to define active regions.

Results We used the spatiotemporal spreading of large aperiodic bursts of activations as a proxy for communications between pairs of regions. Within this framework, large-scale, higher-order perturbations are considered to mediate the interactions between brain regions. We tested for differences between the two experimental conditions (i.e., resting-state, RS, and hand motor imagery, MI) in the probabilities of any such perturbation to propagate across two brain regions. To this end, we built an avalanche transition matrix (ATM) for each subject, containing regions in rows and columns, and the probability that region j would activate at time (t+1), given that region i was active at time t, as the ij th entry. Here, we consider the brain as a network, where the nodes represent brain regions, and the edge linking two of them is defined as the probability of the two regions being subsequently recruited by an avalanche. The differences in the probability of being sequentially recruited by an avalanche was used to track (subject- and edge-wise) the spatial propagation of the perturbations across the two experimental conditions. To validate the observed differences, for each subject and each edge, we built a null-model ( Figure 1 A) randomizing the labels of each trial (i.e., RS or MI) 10,000 times so as to obtain a null distribution of the differences expected by chance. These distributions were used to spot, individually, the edges that differed between the two conditions above chance level. The significances were corrected for multiple comparisons across edges using the Benjamini-Hochberg (BH) correction. 16 Following this step, we focused on the edges that were consistently significant across subjects (defined here as “reliable” edges). To achieve this, we randomized 10000 times, in each subject, the statistically significant edges ( Figure 1 B). This way, we identified the edges that differed significantly between the experimental conditions in a higher number of subjects than expected at chance level (p < 0.05, BH corrected across edges). Our results show that there is a set of edges, consistent across most subjects, across which large-scale perturbations propagate differently according to the experimental condition ( Figure 2 A). We then checked if the significantly different edges would cluster over specific brain regions. To this end, we computed the expected number of significant edges incident on any region, given a random distribution (with a comparable density), and selected those regions with an above-chance number of significant edges clustered upon them ( Figure 1 B). Statistics were again corrected using BH, this time separately for each region, to avoid inflating the probability of finding significant results by chance. As evident in Figure 2 , panel C, to the left, these “reliably different” edges cluster on premotor regions bilaterally and, particularly, on the caudal middle frontal gyri bilaterally (p < 0.0001, BH corrected). We replicated the analysis demonstrating the robustness to the choice of arbitrary parameters (see Figure S1 ), and to the methodology and parcellation used (see Figure S2 ). We repeated the analyses with 200000 permutations which confirmed the stability of our results (not shown). We have also performed the same pipeline as described above, this time using the power spectra, the ERD/S, and the phase locking-value, all of them in the theta, alpha and beta bands, as features to distinguish the hand motor imagery from the resting-state (see Figure S3 ). So far, we have classified the trials according to the stimulus presented to the subject. However, if the differences we found were genuinely related to the task execution, one might expect that they would be greater when the trials were successful (i.e., when the subject could control the BCI device), as compared to when the trials were unsuccessful. To test this hypothesis, in each subject, we compared the differences between MI and RS in the successful trials, to the differences between MI and RS in the unsuccessful trials, expecting to see greater differences at the individual level (in the same set of edges) in the former case as compared to the latter. To statistically test this hypothesis, we used a permutation approach, randomizing successful and unsuccessful trials within each subject. Here, we proceeded under the null hypothesis that if the differences in transition probabilities were truly related to the kind of task at end (i.e., MI or resting state) they should be greater when the task is performed correctly, as compared to when the task has been done wrongly. Hence, we have compared the differences between successful MI and successful resting state, to the differences between unsuccessful MI and unsuccessful resting state. Then, we have built the corresponding null-model under the null-hypothesis that the correct execution of the task would not entail greater differences in the transition probabilities. Hence, we have allocated the trials randomly to the successful (hit) and unsuccessful (miss) trials, and we computed the distribution of the differences expected by chance. Finally, we compared the observed differences between hits (i.e., successful rest vs. successful MI) versus the differences between the misses, demonstrating that when tasks are successfully executed the corresponding differences in the edges are greater than what would be expected by chance. As shown in Figure 2 , panels C, to the right, we could confirm that the transition probabilities across the previously identified reliable edges differed more, in each subject, between conditions, in successful trials as compared to unsuccessful trials, supporting the hypothesis that the relationship between transition probabilities and task performance is valid and measurable at the individual level. MI-based BCI experiments rely on the use of features extracted from power spectra measured in location and frequency bins sensitive to oscillatory changes. More specifically, the system takes advantage of the desynchronization effect associated with a decrease of the power spectra as compared to the rest condition observed within the mu and/or beta band and over the contralateral sensorimotor area when one performs a motor imagery task of the right hand. 17 To improve the classification performance based on power spectra, spatial filters relying on the common spatial patterns (CSPs) approach 18 , 19 have been adopted and widely used in the BCI domain. 5 To take advantage of the interconnected nature of brain functioning, recent work consisted in using functional connectivity estimators, mostly relying on phase-locking value (PLV), 20 as alternative features for classification. 20 , 21 To explore the performance of neuronal avalanches in the decoding of the task (i.e., resting-state versus hand motor imagery), we compared the ATMs to the CSP approach. In a preliminary analysis, we also explored the performance of the power-spectra and of the PLVs which both performed, as expected, worse than the CSP (not shown). The CSP and ATM outputs were classified with a Support Vector Machine (SVM), and the results were compared. As it can be seen in Figures 3 A and 3D, the classification performance seemed comparable for both methods with MEG (averaged performance of 0.76 for both CSP+SVM and for ATM+SVM) and greater for ATM+SVM than CSP+SVM with EEG (averaged performance of 0.75 and of 0.80 respectively for CSP+SVM and for ATM+SVM). Furthermore, in both MEG and EEG we observed greater inter-subject variability in the case of CSP+SVM (standard deviation = 0.13 and 0.15, for MEG and EEG, respectively) than with ATM+SVM (standard deviation = 0.11 and 0.10 for MEG and EEG, respectively). Then, we moved on to a subject-specific analysis, to explore the applicability of the ATM method in the context of a BCI training. We aimed to compare the ability of correctly classifying a trial as MI and RS within each subject. Hence, for each subject, we ran t-tests (and confirmed them with Wilcoxon tests) to compare the 50 success rates obtained with CSP+SVM to the 50 success rates obtained using ATM+SVM. This was done under the null hypothesis that CSP+SVM and ATM+SVM would not yield any statistically different performance in trial classification. We repeated this comparison for every subject, and corrected the statistical comparisons for multiple comparisons across subjects using the False Discovery Rate (FDR). We also repeated the analysis for 75 random splits, and the results did not change, showing that our results reached convergence at 50 splits. This analysis showed that for the MEG dataset, ATM+SVM yielded significantly higher classification accuracy than CSP+SVM did for 6 subjects, while the opposite was true for 7 subjects. For the remaining 7 subjects, there was not any statistically significant difference between the decoding performances of CSP+SVM and ATM+SVM ( Figure 3 , panel B). For the EEG data, ATM+SVM yielded better classification accuracy than CSP+SVM for 12 subjects. In four subjects, CSPs yielded better accuracy than ATMs ( Figure 3 , panel E). In 5 subjects, there was not any statistically significant difference between the two approaches. Moreover, we examined the variability of the estimates across the splits. Steady estimates are important to train online algorithms and high variability might be partly responsible for ineffective training. We observed marginally higher intra-subject variability in CSP+SVM (median value of 0.07 in both modalities) as compared to ATM+SVM (median value of 0.06 in both modalities). In particular, the standard deviation across the split is smaller for the ATMs for most subjects. In Figure 3 , panels C and F for MEG and EEG respectively, we compare the variance (across random splits) of the estimates obtained with the two pipelines (again, ATM on the x axis, CSP on the y axis). We have also checked what is the contribution of very small avalanches (given that most avalanches are power-law distributed, and small avalanches are the most frequent). As reported in Figure S7 for the case of the threshold |z | > 3, one can observe that extremely small avalanches do not contribute significantly to the performance of the classification, as convergence is reached when including avalanches of size three. We have also investigated the influence of the frequency band (as opposed to broad-band) to the classification performance. As reported in the Figure S8 , the broad-band case shows the best performance. Finally, we explore the relationship between the magnitude of the differences in the transition probabilities between the two experimental conditions (in each subject, for every edge) to the individual BCI performance (defined as the proportion of trials in which the subject controlled the BCI device) in the MI task, as measured using the BCI score. Figure 4 , panel A shows the edges whose differences between conditions correlate the most with the BCI scores (the color code shows the intensities of the correlations, for visualization purposes only edges with correlations with p values <0.05 are shown). Firstly, for nearly every edge we observed a positive correlation. To help interpretation, we clustered all the edges according to functional regions (i.e., executive regions, pre/motor areas, parietal areas, temporal areas, occipital areas, ( Figure 1 C). That is, we computed the average Spearman’s correlation over all the edges connecting any two functional regions (also including self-connections, i.e., edges which are comprised within a functional region). To check if the differences in edges transitions which correlated to task performance clustered over certain functional areas above chance-level, we again built a null-model. To this end, for 10000 times, we randomly allocated edges correlation coefficients to functional areas and, each time, we computed the average. We compared the observed average correlation coefficient to the null distribution to obtain a significance value per functional area. Significance values were then corrected for multiple comparisons across all their combinations (i.e., 5 × 5, 25 p values). Our results suggest that edges that significantly relate to BCI task performance hinge pre/motor areas and parietal areas (p < 0.0001, See Figure 4 , panel B). Since we retrieved nearly exclusively positive correlations, our results capture that perturbations spread more often between premotor/motor areas and parietal areas when the subject is engaged in the motor-imagery task, as compared to the resting-state condition. We replicated these results using different parcellation schemes (see Figure S9 ).

Discussion In this work, we set out to test if neuronal avalanches can track subject-specific changes induced by the execution of a task (i.e., hand motor imagery) in the large-scale brain dynamics. The working hypothesis was that meaningful communication among regions on the large-scale is intermittent, and it is best understood and measured in terms of aperiodic perturbations. Neuronal avalanches are inherently aperiodic processes with scale-free fluctuations, whose statistical parameters meet theoretical predictions from mean-field theory. 22 , 23 , 24 In our data, we confirmed that the measured branching ratio is compatible with that of a system operating at criticality or near-criticality. 25 We went on from there to test the basic idea that brain regions interact differently while performing different tasks. We reasoned that, if avalanches convey interactions occurring between regions, their spreading should also be modified according to the task at hand. Such context-dependent modifications should then be encoded in the avalanche transition matrices and, in turn, might be decoded in order to tailor BCIs. More specifically, such information could be considered either as potential predictors of BCI performance, to conceive tailored training programs, or as alternative features, to improve the classification performance. With respect to the encoding framework, we identified, in an unsupervised manner, a number of functional links (i.e., edges) that are reliably more likely to be dynamically recruited during a hand motor imagery task as compared to resting state. The edges cluster over regions typically involved in motor planning and attention, as expected from a motor imagery task. In particular, our results demonstrated that the activities spreading across these edges differed mostly when contrasting trials that had been successful, as compared to the trials during which the subject could not control the interface. This finding demonstrates a behavioral readout for the observed changes in the transition probabilities. This is in line with previous evidences demonstrating that premotor areas are involved in the planning of motor actions, in the imagining of actions, in allocating executive attention, 26 as well as in the selection between competing visual targets, 27 while parietal areas are notably involved, among other things, with the processing of sensitive input. In line with previous findings, 28 a premotor-parietal network was found to be specifically implicated with spatial imagery tasks. These results suggest that indeed the localization of the different edges carries a behavioral meaning. The ATMs directly track the spreading of activations as they happen (as opposed to quantifying dependencies over time intervals). Using such straight-forward approach, 12 we reliably retrieve functional information related to the execution of a task at the subject-level, which was not possible using classical functional metrics. 29 Our approach is based on theoretical underpinnings derived from statistical mechanics, which posits that higher-order, long-range correlations would appear in a near-critical dynamical regime. 22 , 25 In fact, it is important to notice that, by z-scoring each region and using a high-threshold we selected only very strong coherent activity, which is unlikely to be generated by a linear process and that, instead, refers to a higher-order phenomenon. In doing so, we discarded most of the available signals. In practice, we have discarded roughly 90% of the data, applying a “spatio-temporal” filter, and only selecting those points in time and space where large-scale aperiodic perturbations were found. To provide a comparison with more standards techniques, we have used the same pipeline based on techniques that assume stationarity (and take the whole data into account), namely the power-spectra and the event-related desynchronization/synchronization (ERD/S) effects (both containing local information) and the phase-locking value (estimating bivariate synchronization between brain regions). Importantly, all these techniques failed to reproduce any pattern of differences between the two conditions that was replicable at the individual level (see Figure S3 ). However, in the same dataset, a previous work showed that the power spectra shows differences at the group level 29 and the grand average of the ERD/S over the cohort showed a clear desynchronization within the beta band in the contralateral sensorimotor area in the MI condition (see Figures S4 and S5 ) in line with previous studies. 30 , 31 , 32 , 33 The fact that we could find robust individual differences while discarding most data and that we failed to do so when taking the whole data into account suggests that focusing on higher-order perturbations might be useful to capture functionally relevant processes and, in turn, to apply them to the design of BCIs. We replicated our results using different thresholds and binnings showing that they are resilient to these choices. Also, they can be replicated using different parcellation schemes and using EEG signals, which is more widely available than MEG for BCI applications, thereby making our methodology suitable in a wide variety of settings. All in all, extensive replications make it unlikely that our results could be due to arbitrary choices or limited to a specific methodology. Within the decoding framework, we compared the offline classification performance resulting from the use of the ATM to the gold-standard approach, which relies on spatial filters (i.e., the Common Spatial Patterns). Our results suggest that the integration of periodic and aperiodic features would be a straightforward way to improve task classification. Indeed, the information captured by the two types of feature extraction (namely CSPs and ATMs) and the two modalities (MEG and EEG) are complementary. The ATMs maintain a fairly straightforward interpretability as opposed to CSPs, which operate on large-scale components of the signal that are not as readily interpretable. In particular, the ATMs focus on the strong coherent interactions that intermittently occur on the large-scale. The good performance of the ATMs on the EEG data is relevant to translate our methodology to real-world scenarios. In this configuration, the classification of ATMs leads to a significant improvement of the decoding performance with respect to the benchmark in the majority of subjects. Importantly, in both modalities, we observed a reduced intra and inter-subject variability with our approach as compared to CSP+SVM. This might help, in real-life experiments, to reduce the BCI inefficiency phenomenon. To evaluate the feasibility in online applications, we estimated that for an epoch of 5s the time necessary to extract the features, and to perform the classification, was approximately 25 ms for ATM+SVM and 27 ms for CSP+SVM. This value is actually compatible with current on-line settings which use similar time windows and update the feedback every 28 ms. Further investigations are needed to explore the performance in the context of online classification with shorter time windows. Nevertheless, it is worthwhile mentioning that this is a first proof-of-concept study of the use of neuronal avalanches as complementary/alternative features for the design of BCI. Identifying neural markers associated with BCI performance is crucial to design optimized and tailored BCI systems. 34 In turn, the most informative markers provide insight into the processes that underpin the execution of a given task. Neurophysiological predictors of BCI scores are most commonly associated with power spectra. Indeed, sensorimotor μ- and α-rhythms or, more recently, time-averaged brain interactions in these frequency bands have been considered as potential markers. 33 These findings were mainly empirical and, in this oscillatory perspective, features such as power spectra and/or (static) synchronization measures have been widely explored to inform the interfaces. 21 , 33 Furthermore, regional connectivity strength 29 and the M/EEG multiplex core periphery 35 of specific associative and somatosensory areas held predictive power over BCI performance in the same session. However, between 15% and 30% of the subjects do not learn to control the effector despite extensive training. This might mean that the typical features only partly capture the processes that lead to the execution of the task. Hence, different markers might be exploited. Our study contributes, on a practical level, by achieving a differentiation between tasks at the individual level. From a more theoretical perspective, our results suggest that the spreading of local synchronization on the large-scale might be intermittent and aperiodic, and that such spreading carries behavioral relevance. The fact that neuronal avalanches are relevant to the execution of a task might also have implications on the underlying microscopic dynamics. As such, this would allow the deployment of complex and solid mathematical tools derived from statistical mechanics to test the presence of specific microscopic physiological processes. When relating the differences between MI and RS in the probability of an avalanche consecutively recruiting two regions to the magnitude of BCI performance we find mostly positive correlations, indicating that the more avalanches spread between premotor/motor and parietal regions during the task, the better the control of the BCI. This might suggest that the interactions between pre/motor regions and parietal ones underpin the execution of the task. These findings are in line with previous studies relying on MI-based BCI paradigms. In particular, Buch et al. 36 showed that the structural integrity of the frontoparietal networks predict the ability of stroke patients to control a brain computer interface in a motor imagery task. Using fMRI, Halder et al. showed that the premotor areas participate in executing voluntary modulation of brain rhythms through an MI-based BCI. 37 Importantly, when interpreting the results in cognitive terms, one should consider that a (BCI) task likely recruits multiple cognitive processes, beyond those exploited by the BCI classification itself. As such, a psychophysiological interpretation of the areas involved in the BCI classification is not straightforward. For example, the right frontoparietal network dynamics also reflects the allocation of attentional resources, which are typically engaged in cognitive/motor tasks. It is also known that frontomedial activities are one of the main correlates of sustained attention. 38 Thus, although the clustering of the edges that we found in the frontoparietal network is consistent with the prominent involvement of this network in motor imagery tasks, it cannot be mapped uniquely onto one cognitive process. A different perspective is provided by the analysis of cognitive profiles, since it was shown that spatial abilities influence BCI performance, 39 and in particular mental rotation. 40 As such, training strategies might be tailored over a subject-specific assessment of such abilities. Intriguingly, mental rotation abilities were related in turn to increased activity of the premotor cortex, the superior-parietal and the intra-parietal cortices. 41 , 42 Furthermore, activations in the right middle frontal gyrus correlated with BCI performance, which might be interpreted in the light of the role that this region plays in the processing of an observed movement. 37 In conclusion, in a real-world scenario, multiple mechanisms might be in place. As such, our approach is not expected to be the only useful framework. However, it might capture part of the processes that were typically overlooked in a more oscillatory perspective. Our work paves the way to use aperiodic activities to improve classification performance and tailor BCI training programs. Limitations of the study This first proof-of-concept study aimed at assessing to which extent neuronal avalanches could be relevant to identify potential markers of BCI performance and alternative features to detect the subjects’ intent. However, to explore scalability and deployability, studies will need to involve different types of motor imagery tasks (e.g., feet motor imagery, tongue motor imagery etc.), the assess the sensibility of ATMs toward the discrimination of tasks that involve areas close to each other. Furthermore, we have only assessed the performance of the ATMs in controlling one degree of freedom. However, the performance of ATMs in controlling more degrees of freedom will have to be assessed to study the use of ATMs in richer frameworks (i.e., instead of considering only the vertical position of the moving cursor, the horizontal position might also be considered).

These authors contributed equally These authors contributed equally Lead contact Summary Large-scale interactions among multiple brain regions manifest as bursts of activations called neuronal avalanches, which reconfigure according to the task at hand and, hence, might constitute natural candidates to design brain-computer interfaces (BCIs). To test this hypothesis, we used source-reconstructed magneto/electroencephalography during resting state and a motor imagery task performed within a BCI protocol. To track the probability that an avalanche would spread across any two regions, we built an avalanche transition matrix (ATM) and demonstrated that the edges whose transition probabilities significantly differed between conditions hinged selectively on premotor regions in all subjects. Furthermore, we showed that the topology of the ATMs allows task-decoding above the current gold standard. Hence, our results suggest that neuronal avalanches might capture interpretable differences between tasks that can be used to inform brain-computer interfaces. Graphical abstract Highlights • The spatial spreading of neuronal avalanches on the large scale is task-dependent • Large-scale avalanches spread more through premotor areas during motor imagery • Task-related differences are consistent over subjects and related to task execution • Neuronal avalanches properties allow task-decoding above the current gold standard Neuroscience; Computer science Subject areas Published: December 14, 2023

Supplemental information Acknowledgments The authors acknowledge support from 10.13039/501100000781 European Research Council ( 10.13039/100017325 ERC ) under the European Union’s 10.13039/501100007601 Horizon 2020 research and innovation program (grant agreement No. 864729); the program “Investissements d’avenir” ANR-10-IAIHU-06; European Union’s 10.13039/501100007601 Horizon 2020 research and innovation program under grant agreement No. 945539 (SGA3) Human Brain Project, VirtualBrainCloud No.826421. Author contributions Conceptualization: M.C.C. and P.S. Methodology: M.C.C. and P.S. Investigation: M.C.C. and P.S. Visualization: M.C.C. and P.S. Supervision: F.D.V.F. and V.J. Data collection and curation: M.C.C., D.S., and L.H. Data processing: M.C.C., P.S., and A.E.K. Writing—original draft: M.C.C. and P.S. Writing—review and editing: M.C.C., P.S., D.S., N.G., L.G., S.C., L.H., A.E.K., S.D., D.S.B., V.J., and F.D.V.F. Declaration of interests The authors declare no competing interests.

CC BY

no

2024-01-16 23:43:43

iScience. 2023 Dec 14; 27(1):108734

oa_package/4d/a9/PMC10788504.tar.gz

PMC10788512

38226284

Introduction Over the last hundred years, globalization has created a geographically concentrated production system in which certain areas of the planet now operate as engines of the entire world's gross domestic production (GDP). This agglomeration of production activity has led to new trends in economic geography in which global GDP is obtained by a relatively small number of regions that hold the world's economic performance in their hands. According to OECD statistics, in 1996 China's contribution to global GDP (adjusted by purchasing power parity) was 6.8 %, while that of the United States of America was 26.9 % and that of the OECD countries of the European Union (EU) was 28.5 %. 1 By 2022, China's contribution was 22.3 %, while that of the United States was 21.4 % and that of the OECD countries of the EU was 18.9 % [ 1 ]. This means that these three regions jointly contributed 62.2 % to global GPD in 1996 and 62.6 % in 2022. Although the contribution from this economic area changed little between 1996 and 2022, there was a modification within the group as China's relative importance increased with respect to that of both the United States and the European Union. From a global perspective, the distribution of world production is a central issue in the debate on the gap between rich and poor countries. 2 Broadly speaking, there are two perspectives for understanding this gap, namely the classical dichotomy between economic convergence (i.e., a decreasing gap over time) and economic divergence (i.e., an increasing gap over time). 3 Moreover, the policy relevance of product allocation worldwide is explained by its connection to global distributive aspects such as the distribution of income and welfare between countries. 4 From a national perspective, a country's large contribution to global GDP is linked to a large contribution by that country to world trade, a certain degree of market power for its national products in the global markets, and the possibility of exerting influence on world prices. 5 Moreover, a country's role in international forums and multinational organizations is largely determined by its economic significance. 6 An easy way to identify that significance is to analyze the country's contribution to global production. Changes in the (individual) relative contribution to global GDP also enable local policymakers to judge whether the external context is providing economic advantages domestically. In other words, since the distribution of global production provides an overall picture of the wealth of individual economies, it also provides the option to judge each country's degree of success on the global scene. The literature has examined the distance between income in rich and poor countries both theoretically and empirically. Within this line of research, one issue focuses on trends in global GDP, which are evaluated using various modeling techniques such as statistical analyses of the economic organization worldwide and projections for the future directions in world production. 7 Another issue focuses on the consequences of the new production geography on international income distribution, with special emphasis on temporal variations in inequality between countries. 8 Another line of research makes dynamic projections to determine the relative contributions of different countries and regions to future global production. 9 In the last few decades, the development of world production statistics, and especially those related to input-output intersectoral and intercountry transactions, has enabled the construction of multiregional (multi-country) models to explain the determining factors of world production. By transforming this model, we can also determine the relative contribution of countries to global production. This transformation enables us to identify the mechanisms underlying the individual role (i.e., the individual position of countries) within the global production mosaic. This paper discusses these issues and adapts a worldwide version of a multi-country input-output model to define the production of individual economies in relative terms. By assuming changes in the model's exogenous components, we can quantify how far each country's relative GDP is modified by changes in economic scenarios. Interregional input-output literature contains a huge number of contributions focused on the interconnections between regions. In particular, the interregional model has the option of quantifying production impacts emerging in one part (country/region) of the model but originating in another (country/region). 10 Like many other authors [ [23] , [24] , [25] ], proposed the pioneering input-output interregional contributions. Since these initial models, numerous studies have been published, thereby demonstrating the great explanatory potential of this research field. 11 The aim of this paper is to examine the underlying mechanisms that determine the role played by countries within the global production system. This will help to further our knowledge of the factors behind the economic importance of countries and their contribution to world GDP. Since the geographical configuration of economic activity and income distribution worldwide helps to shed light on the rich-country/poor-country debate and to better understand the gap between rich and poor countries and regions, the underlying factors affecting the position of individual economies are of crucial interest. This paper develops these aspects by using a (relatively simple) input-output approach which has an undeniable explanatory potential and clarifies some of the complex and intricate determinants of world production. Although the multiregional input-output model has been used largely to describe production channels across regions and countries, to the best of my knowledge no paper has studied production issues in relative terms, while the relative income modelizations developed so far are circumscribed in the context of the social accounting matrix (SAM) models, which are an extension of the input-output (limited-to-production) model. Specifically, the SAM framework contains larger income channels since it includes institutional sectors (i.e., consumers and value added) in the determination of endogenous income. Among SAM analyses for studying relative incomes [ 30 ], presented a relative measure to investigate the distribution of the multiplier effects among the components of a model constructed for the Netherlands [ 31 ]; proposed a general and systematic analytical framework to define the SAM income distribution process and provided an application for the United States [ 32 ]; used the context of [31] to analyze redistributional impacts among various types of UK households and emphasized the role of the agricultural sector through the impact of agricultural policies [ 33 ]; identified several components of SAM income redistribution channels and presented an empirical application to the region of Catalonia (Spain) [ 34 ]; analyzed the distributive impacts of alternative agricultural policies using a SAM for Italy [ 35 ]; applied the relative income model to a SAM for the region of Extremadura (Spain); and for the Chinese province of Jiangsu [ 36 ], studied the distribution mechanism between tourism and non-tourism industries. In this paper, the input-output model is transformed to provide a relative measurement of the contributions from individual countries or regions to global GDP. The (world-focused) method also evaluates how far the countries’ contributions to world production (or relative GDP) are affected by changes in the (exogenous) final demand of sectors. Since this approach includes a rich set of information, the outcomes rely not only on a worldwide perspective of production processes but also on specific implications for: i) each single country or region, and ii) each sector of production reflected in the model. The empirical application considers the three major contributors to world production (China, the United States, and the European Union) as well as the Rest of the World (ROW). By looking at the positions of the main economic blocks at the world level and their changes after global economic expansions, we are able to put forward a superficial analysis of world production statistics. Moreover, the novel input-output model used enables us to further examine the intersectoral and intercountry linkages behind the disparity in the economic importance of countries. All these issues enable us to go beyond a mere quantitative interpretation of statistics, by showing several determining factors of the economic importance of countries and the transmission channels of this influence across countries. The rest of this paper is organized as follows. Section 2 describes the multiregional setting, derives measurements of the contributions of countries to production, and evaluates how changes in final demand affect the relative importance of countries. Section 3 describes the database used, while Section 4 shows the empirical results and discusses the main findings. Finally, Section 5 draws conclusions.

Discussion of the results Previous literature reported a persistent and growing gap between rich and poor countries across the world during the second half of the twentieth century. In addition, in developing countries the gap in personal income distribution, specifically between the rich and the poor, also increased. In short, previous research established the generally accepted wisdom that both internal and international income gaps were widening. This line of knowledge used empirical analyses that employed econometric and statistical approaches to determine a persistent difference between the rich and the poor [ 3 ]. This assertion represented a rebuttal to the economic convergence hypothesis [ 4 ], which suggests that the phenomenon of rich and poor disparity is transitory and can be reduced. This literature also described a downturn trajectory in the differences in global income distribution since the turn of the century that was largely explained by the rapid growth in certain Asian countries (i.e., India and China), though the within-country gap continued to increase [ 5 ]. The results reported in the present study contribute to this evidence by clearly suggesting that a universal economic expansion is linked to a boost in the asymmetries of production across the world and that a global economic crisis would reduce the differences in the production worldwide. In other words, these findings suggest that economic growth is linked to a concentration of world production in countries with the highest initial GDP (particularly China and, to a lesser extent, countries of the European Union). These outcomes reinforce the argument that, in marked contrast to the convergence theory, the distance between the GDP in rich and poor countries is increasing. To gain knowledge of the processes that determine global production and their implications for individual countries and regions, it is crucial to disentangle the underlying mechanisms governing the current geography of world production. The role individually played by countries within the global economic system has significant consequences for national production, domestic welfare and the capacity to exert economic influence in world markets. The ability to uncover the mechanisms that affect relative individual positions within the complexity of world production is therefore crucial to defining redistribution measures worldwide. It is also useful to anticipate and counterbalance the automatic reallocation mechanisms that can harm internal economic activity and domestic income. Moreover, all these findings have important policy implications globally since they support the idea of a diverging economic trend across the world and reaffirm the postulate that policy responses to economic divergence should play a role in slowing the gap between rich and poor economies. The outcomes in this paper should therefore guide key aspects of international economics such as trade and monetary agreements or environmental protocols. Since this paper proposes a novel input-output modelization of world production for analyzing distribution mechanisms, it can be considered complementary to previous knowledge, which was mainly based on statistical and econometric methods. However, it is important to bear in mind that since the input-output production structure does not allow substitution possibilities, the results appear in an upper range of possible impacts. It is also worth noting that the model used identifies winners and losers in net terms since the relative income determination necessarily implies a zero-sum game in which total relative increases in the individual contribution to world GDP are equal to total relative decreases. Despite these weaknesses, this framework has undeniable advantages, namely its faithful connection with the economic complexity involved and its ability to provide detailed information. All these aspects make the input-output model a powerful tool for analyzing global production issues.

Discussion of the results Previous literature reported a persistent and growing gap between rich and poor countries across the world during the second half of the twentieth century. In addition, in developing countries the gap in personal income distribution, specifically between the rich and the poor, also increased. In short, previous research established the generally accepted wisdom that both internal and international income gaps were widening. This line of knowledge used empirical analyses that employed econometric and statistical approaches to determine a persistent difference between the rich and the poor [ 3 ]. This assertion represented a rebuttal to the economic convergence hypothesis [ 4 ], which suggests that the phenomenon of rich and poor disparity is transitory and can be reduced. This literature also described a downturn trajectory in the differences in global income distribution since the turn of the century that was largely explained by the rapid growth in certain Asian countries (i.e., India and China), though the within-country gap continued to increase [ 5 ]. The results reported in the present study contribute to this evidence by clearly suggesting that a universal economic expansion is linked to a boost in the asymmetries of production across the world and that a global economic crisis would reduce the differences in the production worldwide. In other words, these findings suggest that economic growth is linked to a concentration of world production in countries with the highest initial GDP (particularly China and, to a lesser extent, countries of the European Union). These outcomes reinforce the argument that, in marked contrast to the convergence theory, the distance between the GDP in rich and poor countries is increasing. To gain knowledge of the processes that determine global production and their implications for individual countries and regions, it is crucial to disentangle the underlying mechanisms governing the current geography of world production. The role individually played by countries within the global economic system has significant consequences for national production, domestic welfare and the capacity to exert economic influence in world markets. The ability to uncover the mechanisms that affect relative individual positions within the complexity of world production is therefore crucial to defining redistribution measures worldwide. It is also useful to anticipate and counterbalance the automatic reallocation mechanisms that can harm internal economic activity and domestic income. Moreover, all these findings have important policy implications globally since they support the idea of a diverging economic trend across the world and reaffirm the postulate that policy responses to economic divergence should play a role in slowing the gap between rich and poor economies. The outcomes in this paper should therefore guide key aspects of international economics such as trade and monetary agreements or environmental protocols. Since this paper proposes a novel input-output modelization of world production for analyzing distribution mechanisms, it can be considered complementary to previous knowledge, which was mainly based on statistical and econometric methods. However, it is important to bear in mind that since the input-output production structure does not allow substitution possibilities, the results appear in an upper range of possible impacts. It is also worth noting that the model used identifies winners and losers in net terms since the relative income determination necessarily implies a zero-sum game in which total relative increases in the individual contribution to world GDP are equal to total relative decreases. Despite these weaknesses, this framework has undeniable advantages, namely its faithful connection with the economic complexity involved and its ability to provide detailed information. All these aspects make the input-output model a powerful tool for analyzing global production issues.

Conclusions Economic globalization has concentrated production in a limited number of countries and regions around the world. Indeed, adapting production processes to a globally organized setting has led to substantial changes in economic geography so that nowadays just a few regions are driving the world's entire GDP. This paper provides a novel framework for calculating the contributions of countries to global production. By defining a simple and treatable general equilibrium structure for world GDP, we can evaluate the extent to which the relative contributions of countries/regions to global production are affected by changes in the model's (exogenous) final demand. The method proposed contributes to the debate on the gap between rich and poor countries as it shows whether this gap decreases (i.e., the economies converge) or increases (i.e., the economies diverge) when an increase in demand is produced. In turn, this sheds light on the ability of the automatic mechanisms operating in world production to modify inequalities across countries. Several interesting aspects from this paper deserve to be highlighted. First, a limited number of service sectors monopolize the largest contribution to global GDP. This sectoral concentration of product into a few activities warrants special attention from the field of international economics given its potential implications for income generation and income distribution around the world. Second, the outcomes presented in this paper provide new insights into the impacts that shocks in demand cause in the relative contributions of countries to global production. In particular, China's relative GDP increases after an increase in world demand at the expense of the ROW's relative GDP. This suggests that economic growth per se does not reduce the gap between rich and poor countries since the most important producers (i.e., those with the highest contribution to world GDP) are receiving the greatest impacts on their relative production. Moreover, it should be pointed out that all the bilateral country-to-country effects are negative and that only demand shocks occurring and materialized domestically have a positive impact on relative GDP. Third, this model can be easily applied at the empirical level by using available global inter-country input-output statistics. In addition, since this method provides a novel tool for evaluating the contributions of individual countries to global GDP, it may be useful for improving decision-making in areas such as the geopolitics of production, economic cycle theory and world economic planning. Finally, although the framework proposed provides new information about GDP determination worldwide, the potentialities of the analysis go beyond the application shown in this article. Many extensions to this approach can be used to analyze other interesting issues by defining variables other than world GDP, such as world employment and global emissions. Since the information required can be obtained from available global databases, such extensions can be applied easily.

Economic globalization has led to production increasingly becoming concentrated in certain regions and countries of the world. This article develops an accounting framework to provide the trends for the contribution of countries to global gross domestic production (GDP). In particular, the method transforms the multiregional input-output model to quantify the relative importance of individual economies to world GDP. The proposal uses a world input-output database that distinguishes between three main economic areas: China, the United States of America and the European Union. The results suggest that identical changes in sectoral demand asymmetrically modify the relative contributions from individual economies, with China showing the highest positive (negative) impact after an increase (decrease) in world demand. These findings suggest that a generalized economic expansion (contraction) is linked to a boost (decline) in the asymmetries of production across the world. Keywords

Modeling framework Global GDP in the two-country case The starting point for analyzing the contribution of countries to world production is the multiregional input-output framework, which explicitly captures the economic connections between countries throughout the sectoral inputs and outputs circulating worldwide. Compared with other partial-equilibrium methods, the (deterministic) input-output framework allows the production system to be comprehensively described by using a general-equilibrium view of the interregional and intersectoral transactions. Moreover, the approach used enables the production value chains to be completely covered by the analysis, resulting in a genuinely global model. For the sake of simplicity, let us assume a world with two countries or regions ( and ). Goods produced there can be used either as intermediate inputs or final products. In both areas, the intermediate and final goods are either consumed within the area's borders or exported to the other. The input-output model characterizing this two-country system can be represented as follows: where is a block matrix of the input-output structural coefficients, which are calculated by dividing the intermediate goods from sector by the gross output of sector . Note that this matrix includes all possible intercountry transactions: and include the sectoral transactions within each region or country, while and represent the sectoral transactions between regions or countries (from to and from to , respectively). In Equation (1) , is the vector of gross output, is the matrix of intercountry final demand transactions, and is a unitary column vector that adds up the elements in the rows of matrix . Equation (1) can alternatively be written as: From this general production setting, gross domestic product is obtained by transforming expression (2) as follows: where is the column vector of the sectoral value added in ( ) and ( ), respectively, and is the diagonal matrix of the sectoral value added ratios in relation to gross output in and , respectively. Compactly, Equation (3) can be written as: where is the matrix of input-output multipliers or Leontief inverse matrix in the multiregional approach. The global framework described above directly determines the individual (national or regional) output (Equation (2) ) and individual value added (Equation (3) ). Total (global) values can easily be calculated by simply adding the individual values. For the two-country case, global output would be or, alternatively, with being a unitary row vector. Similarly, global GDP would be or, alternatively, . Another advantage of using the multi-country approach is that both the origin and destination of economic impacts can be identified and numerically quantified because all the interregional flows of goods are explicit in the determination of the economic relationships. Relative GDP in the two-country case The multiregional framework can be adapted to define each country's contribution to global GDP. 12 By transforming expression (4) to define relative values, the contribution to GDP is equal to: where adds up the elements in vector so that is the value of total GDP. 13 In Equation (4) , is the product contribution vector , which contains two blocks, i.e., ( ) and ( ), which show sectoral contribution to global production in and , respectively. From this vector, the addition of sectors in each region ( and , respectively) provides a total measurement of the region's contribution to global production: and . This leads to the following structure for : where the sum of the elements is necessarily equal to 1 (or, alternatively, 100 % of world GDP): i.e., . Equation (4) determines the relative importance of sectors and countries in function of the parameters of the input-output model, namely the elements in matrices , , and . Partial derivative of Equation (4) with respect to final demand matrix provides a quantification of how much the relative contribution to GDP changes when final demand is modified. Let us assume a change in , which modifies as follows: Equation (5) evaluates the changes in the contribution to GDP ( ) due to changes in the final demand matrix ( ). In this expression, is the demand-to-product reallocation matrix , which contains the changes in the relative positions (in global GDP) of the sectors of each country. This reallocation matrix provides insights into the underlying mechanisms operating in global production, since its elements ( ) quantify by how much the relative position of sector in country or is modified when there is a unitary inflow in the final demand of sector in country or . For the two-region system described earlier, the structure of matrix is: where each element is a block containing the changes in the relative production of sectors due to exogenous inflows in the final demand of all other sectors. This is a complete portrait of all the possible effects, since matrix is made up of all the possible vis-à-vis connections reflected in the model. Note also that the individual elements in this matrix can either be positive, which shows an increase in a particular sector's contribution to total GDP, or negative, which shows a decrease in its contribution to total GDP. At the aggregate level, it can be checked that the sum of the columns is null: This shows that the positive and negative values of the demand-to-product reallocation matrix balance out, so the changes in relative GDP, or the product reallocation process, can be understood as a zero-sum game. Database The empirical application is based on the latest version of the World Input-Output Database (WIOD), which contains data for the year 2014. 14 The WIOD is a multiregional input-output table that originally comprised 56 sectors of production for 43 countries plus a residual Rest of the World (ROW). This database has been aggregated to individually show the three most important producers globally, i.e., China, the United States, and the European Union (EU), 15 plus a residual Rest of the World to complete the world system. The aggregation of countries was done by including (i.e., adding) the intersectoral elements ( , ) of a country to the corresponding Rest of the World account or to the European Union region. 16 The 56 original sectors were divided into 25 activities: one agricultural sector, four energy activities, eight industries and twelve services. This aggregation was done by completely allocating all the original sectors of the WIOD to any of the new aggregated sectors so that no partial allocations to the compacted sectors were possible. The resulting database provided all the data (i.e., intercountry input-output transactions, sectoral value added and final demand) needed for the empirical analysis. Applying this database to the model described in Section 2 involves regional blocks, each of which has a number of sectors equal to . This leads to an interregional structure made up of accounts, so that matrix has a dimension of , vector of sectoral output has a dimension of , and matrix of intercountry final demand has a dimension of . The number of columns in the final demand matrix is equal to since each of the 4 regions contains demand elements (private consumption, public consumption and gross fixed capital formation). Table 1 shows various statistics directly obtained from the WIOD. In 2014 world GDP was 73, 806, 918 million US dollars, which was roughly 46 % of the world's total output (160,997,197 million US dollars). Also in Table 1 , private consumption was the largest component of final demand, i.e., 41,998,603 million US dollars, which represented 56 % of the total amount (75,447,435 million US dollars). 17 This was followed at great distance by investment (19,942,312 million US dollars), which represented 26 % of total demand. Public consumption (13,506,520 million), which accounted for the remaining 18 %, represented the lowest value. By country, the United States led value added (17,348,070 million US dollars), private consumption (11,908,807 million), and demand (17,897,697 million). China had the largest value for output (31,745,102 million) and investment (4,772,425 million), while the EU had the largest value for public consumption (3,487,357 million). The figures in Table 1 illustrate the differences in the economic structures of these three areas. With regard to production, China had the highest output but the lowest value added. With regard to final demand, in the United States (where it represented roughly 28 % of the global value) private consumption was well above that of the other countries. Public consumption in the EU was clearly the highest, representing roughly 26 % of the world's total. Finally, China led the world in investment, where it was 65 % higher than in the EU and 39 % higher than in the United States. Empirical application Relative contribution to global GDP Table 2 contains sectoral GDP (directly obtained from the WIOD) and the relative contributions of sectors and regions to the global amount (i.e., the elements calculated following the product contribution vector in Equation (4) ). At the regional level (final row in Table 2 ), the United States (23.50 %) led contributions to global GDP. The US was followed by the European Union (18.86 %), while China had the lowest contribution (13.93 %) of the three regions. Joint contribution represented roughly 56 % of total production, which clearly confirms the agglomeration of world production in just a few geographical areas. Note that adding the contributions made by these three countries and ROW (43.69 %) provides total world GDP (100 % or 1.00 according to the model). By sector, the right-hand column shows that the world's largest production was for Other Service Activities (Sector 25). This represents 20.1 % of total GDP, of which the US contributed 6.0 % and the EU 4.7 %. Also note Trade and Commerce (Sector 14), which accounted for 11.9 %. Jointly, these two activities represented roughly a third (32 %) of world production, which means that global GDP is largely dependent on these two service activities. Public Administration (Sector 24), Financial Services (Sector 21), Construction (Sector 13) and Human Health (Sector 23) also had notable contributions (7.7 %, 5.9 %, 5.6 %, and 5.0 %, respectively). The first result to highlight from Table 2 is that not only is world GDP geographically concentrated but it is also asymmetrically distributed at the sectoral level. Another result is that China is at the forefront of world industrial production, with the highest contribution made by industries (Sectors 5 to 12). On the other hand, the United States leads the world's services production (Sectors 14 to 25), except in Sector 22 (Education), which is led by the European Union. Changes in contribution to global GDP This section illustrates the changes in relative GDP by focusing on the effects that modifying the model's (exogenous) final demand has on contributions to global GDP by sectors and countries. Table 3 summarizes the results of an exogenous change in final demand. This change can come, for instance, from a rise in private income that increases private consumption, an increase in public expenditure, or an increase in investment by sectors. Since this simulation evaluates the impact on relative contribution to GDP that was originated in final demand, it can be interpreted as an evaluation of how cyclical fluctuations of demand affect the importance of sectors and countries within world production. Understanding the relationship between demand shocks and relative GDP will improve our knowledge of the consequences of the economic cycle at both the world level and the regional (i.e., country) level. The figures in Table 3 correspond to the regionally aggregated elements of matrix . This calculation transforms the reallocation process (matrix in order to keep the amount of GDP constant at the initial level. In other words, since the changes in the relative contribution ( ) are pre-multiplied by total GDP ( ), the resulting matrix can be interpreted as the reallocated GDP for all the bilateral elements captured by the model. Since the columns in this matrix also add up to zero, the reflected process can be seen as a compensating mechanism of winners and losers in net terms. 18 The values in Table 3 should be interpreted as follows. When China receives an exogenous and unitary demand inflow, its relative GDP increases by 18.62 million US dollars, whereas the impact on the other regions is negative. In particular, the impact on the United States is a decrease of 5.60 million dollars, and the impact on the European Union and the Rest of the World is, respectively, a decrease of 4.36 and 8.65 million dollars. The columns in Table 3 contain the redistributed GDP when an exogenous shock in demand is received by the country in the column. Interestingly, all values in this table are negative except the symmetrical elements. This indicates that the bilateral relations between regions are detrimental in terms of the impacts they receive on the relative product, and only inflows received domestically and materialized in domestic input-output transactions can improve the contribution to global GDP. The rows in Table 3 show the changes in the relative GDP of the region in the row when they all simultaneously receive a unitary inflow in final demand. Interestingly, we can see from the right-hand column that the highest (positive) change is for China (9.58 million dollars), which means that increases (decreases) in the final demand of all countries would increase (decrease) Chinese contribution to global GDP. This is achieved at the cost of decreasing the contribution from the Rest of the World, which shows a large negative value (−13.98 million dollars). The EU, and to a lesser extent the US, have positive values in the right-hand column (3.70 and 0.70 million, respectively). In summary, Table 3 indicates that an economic expansion (crisis) that increases (reduces) world demand, would increase (reduce) the importance of China at the global level and reduce (increase) the contribution from the Rest of the World. Importantly, while the European Union and the United States evolve in the same direction as China, the magnitude of the redistribution in these two areas is much lower than the impact received by China. Table 4 shows the sectoral decomposition of the right-hand column in Table 3 . The figures in this table quantify how many dollars of GDP are reassigned among sectors of production when total GDP is held constant at the initial level and final demand in all regions increases by one monetary unit. For instance, when there is a generalized and unitary inflow in world demand, Agriculture (Sector 1) increases its relative GDP by 0.75 million dollars in China, by 0.56 million dollars in the United States, and by 0.42 million dollars in the European Union. On the other hand, the agricultural sector in the Rest of the World decreases its relative GDP by 0.87 million dollars. This results in a global impact received by agriculture that amounts to 0.85 million dollars of relative GDP after a generalized increase in world demand. The rest of the figures in Table 4 should be read in a similar way. For China, all sectoral values are positive except Construction (Sector 13), which reduces its relative GDP by 0.61 million dollars after a unitary increase in demand. The signs of GDP reallocation for sectors in the United States and the European Union follow a similar pattern, though the European values are generally higher than those of the United States. In particular, these two regions show reductions in the relative GDP for Construction (Sector 13), Trade and Commerce (Sector 14), as well as various service activities. Table 4 also shows that Agriculture (Sector 1), various industrial activities, Construction (Sector 13), and most services in the Rest of the World suffer reductions in their relative contribution to world GDP. Finally, the right-hand column in Table 4 shows the changes in the relative GDP of sectors at the world level. This is an interesting outcome for international economics, since these values illustrate which sectors gain importance and which ones lose importance within global production. Among the positive impacts, Electricity and Gas (Sector 3), Water (Sector 4), Chemicals (Sector 7), Metal Products (Sector 8), and Transport Services (Sectors 15, 16, 17, and 18) show a considerable increase. On the other hand, there are clear reductions in relative GDP for Construction (Sector 13), Trade and Commerce (Sector 14), Public Administration (Sector 24) and Other Services (Sector 25). Data Availability statement Data used in this article are available at www.wiod.org . Ethics statement Informed consent was not required for this study because no personal or individual data were used. CRediT authorship contribution statement Maria Llop: Writing – review & editing, Writing – original draft, Validation, Methodology, Formal analysis, Data curation, Conceptualization. Declaration of competing interest The author declares no relevant or material financial interests that relate to the research described in this paper. The author also declares no conflict of interest.

Acknowledgements Useful and constructive comments by three anonymous referees and by the editor of the journal have substantially improved an earlier version of this article. Funding by the 10.13039/501100007512 Universitat Rovira i Virgili (PFR2022) is also acknowledged.

CC BY

no

2024-01-16 23:43:44

Heliyon. 2023 Dec 19; 10(1):e23909

oa_package/e9/bc/PMC10788512.tar.gz

PMC10788513

38226288

Introduction In recent decades, renal cell carcinoma (RCC) has emerged as a global health concern due to its increasing incidence and resulting status as the primary cause of death among urological malignancies [ 1 ]. Clear cell renal cell carcinoma (ccRCC), representing the most common RCC subtype, is particularly challenging to manage [ 2 ]. Surgical intervention remains the most efficacious treatment for ccRCC, yet postsurgical relapse and metastatic progression are common and considerably augment the likelihood of cancer mortality [ 3 , 4 ]. Amid continuing advancements in cancer diagnosis and therapy, the long-term survival rate for metastatic ccRCC patients rests at approximately 20 %, highlighting the critical need for more effective treatments [ 5 ]. Given the resistance of ccRCC to conventional radiation and chemotherapy, targeted therapeutics and immunotherapeutic interventions have progressively taken center stage in ccRCC patient management strategies [ 6 ]. In particular, immune checkpoint blockade (ICB) therapies have reshaped the landscape of cancer treatment [ 7 ]. Checkpoint blocking in conjunction with other anticancer medications is now the first-line treatment for advanced ccRCC. Immune suppression is abolished by ICB in a subset of patients with ccRCC, resulting in astounding clinical improvements [ 8 ]. However, it remains that a significant number of patients do not qualify for ICB treatment or do not show the desired response, underscoring the persistent need for reliable biomarkers to guide treatment selection. Cancer metastasis embodies a complex process involving the dispersal of cancer cells from the initial tumor site to distant organs. This process hinges on the intricate, bidirectional interactions between cancer cells and their environment [ 9 ]. During metastasis, cancer cells are known to infiltrate the extracellular matrix (ECM) using the mechanism facilitated by invadopodia. This process is considerably influenced by Soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) which are essentially involved in intracellular vesicle trafficking [ 10 ]. There is substantial evidence from previous research indicating that specific SNAREs, especially those participating in the transport of invadopodium-associated proteins, have key roles in enabling the invasive and migratory characteristics observed in malignant cancer cells [ [11] , [12] , [13] ]. Syntaxin 4 (STX4), one member of the SNARE protein family, is implicated in shepherding MT1-MMP to the plasma membrane [ 14 ]. Recent studies have indicated that STX4 increases breast tumor and ovarian cancer invasion by mediating invadopodium development [ [15] , [16] , [17] ]. The prognostic utility of STX4 in ccRCC has likewise been alluded to in previous studies [ 18 ]. Despite these advances, a significant knowledge gap exists regarding the direct impact of STX4 on ccRCC cell proliferation and invasion and its potential influence on the tumor microenvironment. In the current study, we explored the expression pattern and clinical significance of STX4 in depth. A series of molecular experiments were conducted to evaluate the influence of STX4 on the biological features of ccRCC cells. To identify differences and potential mechanisms between groups with high and low STX4 expression, functional analysis was performed. Furthermore, the correlation between the degree of immune cell infiltration and STX4 expression was assessed through the use of multiple algorithms. To evaluate its potential as a clinical tool to guide treatment selection, we investigated the relationships between patient responses to immunotherapy and targeted therapies and STX4 expression. This comprehensive examination could offer valuable insights into the functions of STX4 and its therapeutic implications in ccRCC management.

Materials and methods Data collection and prognosis analysis We sourced expression profiles and clinical data of KIRC, KIRP, and KICH from The Cancer Genome Atlas (TCGA) database. Additionally, we obtained expression data of an immunotherapy cohort undergoing anti-PD-1 therapy (nivolumab) in RCC from the Gene Expression Omnibus (GEO) database (GSE67501) [ 19 ]. We also used the NIHMS1611472 dataset from the supplemental material of a previous study, which included 1006 ccRCC patients treated with either nivolumab or everolimus [ 20 ]. To ascertain the prognostic value of STX4, we conducted a Cox regression analysis to evaluate the relationship between STX4 expression and various survival outcomes, specifically overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS), in ccRCC patients. Furthermore, we examined the correlation between STX4 expression and various clinicopathological characteristics within the TCGA-KIRC cohort. Functional enrichment and immune cell infiltration analyses Utilizing LinkedOmics, we conducted co-expression analysis for the TCGA-KIRC cohort [ 21 ]. The results are depicted in a heatmap that reveals genes exhibiting high positive or high negative correlation with STX4. To further elucidate the functional significance of these co-expressed genes, we applied the "LinkInterpreter" module within LinkedOmics. This tool facilitated Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, which shed light on the biological processes, cellular components, molecular functions, and signaling pathways in which these co-expressed genes are implicated. In this study, patients were divided into two groups, STX4 high and STX4 low , using the median value of STX4 expression as the cutoff. Infiltration estimate data computed by CIBERSORT, TIMER, xCell, quanTIseq, MCP-counter, and EPIC algorithms were downloaded from TIMER 2.0 [ 22 ]. The differing levels of immune cell infiltration in both the STX4 high and STX4 low groups were visualized using a heatmap. Applying the ssGSEA method, we compared the infiltration levels of 28 immune cells between the STX4 high and STX4 low groups [ 23 ]. The immune score and stromal score of each patient were calculated by the “ESTIMATE” package [ 24 ]. A comparison of the human leukocyte antigen (HLA) gene family was made between the STX4 high and STX4 low groups. To guide treatment decisions in clinical practice, we focused our analysis on several immune cells that have been identified to have significant associations with immunotherapy efficacy. We obtained the expression data of three cell types (CAFs, MDSCs, and M2-TAMs), which are believed to inhibit T-cell infiltration in tumors, of TCGA patients from the TIDE database [ 25 ]. The comparison of these cells was performed between the STX4 high and STX4 low groups. Immunotherapy and targeted therapy response prediction To predict potential immunotherapy responses among patients with varying STX4 expression levels, we initially assessed the differential expression of immune checkpoint genes between the STX4 high and STX4 low groups. Additionally, we retrieved the Immunophenoscore (IPS) for ccRCC patients from The Cancer Immunome Database (TCIA). The IPS for each patient was objectively determined by considering four categories of genes that determine immunogenicity: effector cells, immunosuppressor cells, MHC molecules, and immune modulators [ 26 ]. Higher IPS scores typically denote elevated immunogenicity. Chemokines and chemokine receptors play vital roles in the orchestration of host immune responses to cancer [ 27 ]. Given the integral roles that chemokines and chemokine receptors play in coordinating host immune responses to cancer, we also evaluated the correlation between STX4 expression and the expression of CXCL9 and CXCL10, which have been previously reported to favor the emergence of a "hot" tumor microenvironment [ 28 ]. The tumor mutation burden (TMB), which has been identified as a predictive biomarker for determining patients' likelihood of positive response to ICB, was also explored across patients with varying STX4 levels [ 29 ]. Finally, we utilized two immunotherapy cohorts (GSE67501 and NIHMS1611472) to validate the identified correlation between STX4 expression and response to immunotherapy. We also compared the susceptibility to sorafenib, sunitinib, pazopanib, and axitinib across the STX4 high and STX4 low groups. The half maximal inhibitory concentrations (IC50) of these drugs were compared by applying the “pRRophetic” package [ 30 ]. Moreover, RNA-seq and DTP NCI-60 data from the CellMiner database were downloaded, and drugs with FDA approval or those undergoing clinical trials were selected for further analysis. The correlation between STX4 expression and drug sensitivity was estimated. Renal cell carcinoma cell lines and tissue specimens Two ccRCC cell lines (786O and OSRC-2) were procured from the CAS Cell Bank (Shanghai, China). These cells were cultured in RPMI 1640 medium, supplemented with 10 % FBS (Boster Biological Technology, Wuhan, China). Standard cell culture conditions were maintained at a temperature of 37 °C in an incubator with a CO2 concentration of 5 %. Tissue samples, both tumorous and matched normal, were obtained from patients with ccRCC who had undergone either partial or radical nephrectomy procedures at Tongji Hospital. The Institutional Research Ethics Committee of Tongji Hospital provided the requisite ethical approval for this study (TJ-IRB-20230331). SiRNA transfection siRNA and corresponding negative control were synthesized by RiboBio Company (Guangzhou, China). For the process of transfection, Lipofectamine 3000 (Thermo Fisher Scientific) was employed, wherein OSRC-2 and 786-O cells were transfected with STX4 or control siRNA at a concentration of 80 nmol/L. Post transfection, we determined the efficacy of the knockdown by employing qRT-PCR and Western Blot analysis. These analytical methods were executed as described in our previous studies [ 31 ]. CCK-8 and EdU assays Cells were plated at a density of 2000 cells/well in 96-well plates, and cell viability and cytotoxicity were measured according to the protocol (Yeasen Biotechnology, Shanghai, China). When performing the drug sensitivity analysis, the cells were incubated with 100 μL of fresh medium containing vehicle (DMSO) or drugs for 48 h and were assayed for cell viability measurement. The following drugs were used at the indicated concentrations: axitinib (1 μM, Selleck, S1005), sunitinib (5 μM, Selleck, S7781), pazopanib (5 μM, Selleck, S3012) and everolimus (25 nM, Selleck, S1120). For the EdU assays, post transfection for 48 h, cells were seeded in 12-well plates at a density of 8 × 10 4 cells per well. The cells were then incubated with a medium containing 50 μM EdU for a period of 2 h. Subsequently, the cells were fixed with 4 % paraformaldehyde at room temperature for a duration of 20 min. This was followed by staining the cells with Hoechst reagent and Apollo staining solution. The percentage of EdU-positive cells was calculated under a microscope in five randomly selected fields. Wound-healing and transwell assays Transfected 786O or OSRC-2 cells were seeded into 6-well plates at a cellular density of 2 × 10 5 cells per well. Upon reaching 90 % confluence of the cell monolayers, a scratch was made parallely using a 1 ml pipette tip to simulate a wound. The healing rate of this wound was subsequently assessed after the 24 h using ImageJ software. For the transwell assay, 3 × 10 4 cells were cultured in serum-free medium in the upper chamber, while 500 μl of 10 % FBS-containing medium was added to the bottom chamber. After 24 h, the pierced cells were fixed in 4 % paraformaldehyde and stained with 0.1 % crystal violet. Under a microscope, cells were counted in five randomly selected fields. Flow cytometry analysis of the cell cycle and apoptosis To ascertain the rate of apoptosis, harvested cells were twice rinsed with PBS. These were then subjected to co-staining with PI and Annexin V- FITC (Yeasen Biotechnology, China), followed by an incubation period of 10–15 min before flow cytometry detection. To study the effect of everolimus between the STX4 high and STX4 low groups, transfected 786O and OSRC2 cells were incubated with vehicle (DMSO) or everolimus (25 nM, Selleck, S1120) for 48 h, and the proportion of apoptotic cells was detected. For the analysis of cell cycle distribution, collected cells were treated with RNase and PI (Yeasen Biotechnology, China) for 30 min at 4 °C after overnight fixation in 70 % ethanol. A CytoFlex cytometer was used to obtain flow cytometry data, which were then analyzed using FlowJo V10 software. Immunohistochemical (IHC) staining Immunohistochemical staining was carried out on paraffin-embedded sections derived from clinical specimens of our hospital. We utilized rabbit anti-STX4 primary antibody (A5996; ABclonal) and goat anti-rabbit secondary antibodies (GB23303; Servicebio) for this purpose. A DAB kit was employed to visualize the antibody interactions subsequent to incubation with the secondary antibodies. Pan-cancer analysis of STX4 To elucidate the expression differences across 33 cancer types, we utilized the TIMER database. The RNA-seq data for these cancer types was downloaded from the TCGA database, which allowed us to evaluate the correlation between STX4 expression and immune checkpoint genes. Additionally, univariate Cox regression analysis was performed to explore the relationship between STX4 expression and OS and PFS in these 33 cancer types. Finally, we conducted correlation analysis between TMB, MSI, and STX4 expression across 33 cancer types. Statistical analysis Data analyses were performed using R (version 4.0.4) and GraphPad Prism (version 7). The Spearman correlation method was employed to compute correlations. Two groups were compared using Student's t-test or Wilcoxon test. For comparison across multiple groups, we utilized the Kruskal-Wallis test and One-Way Analysis of Variance (ANOVA). A P-value less than 0.05 was considered indicative of statistical significance.

Results STX4 is positively correlated with poor prognosis in ccRCC From the TCGA database, we observed a significant increase in STX4 expression in ccRCC ( Fig. 1 A). Patients demonstrating high STX4 expression had notably reduced OS, PFS, and DSS compared to those with low STX4 expression ( Fig. 1 B). We further investigated the role of STX4 in other subtypes of RCC. Interestingly, we found that STX4 expression was notably upregulated in KIRP but downregulated in KIRP ( Figs. S1A and B ). Deviating from its impact in KIRC, STX4 did not present a significant association with the prognosis of KIRP and KICH ( Figs. S1C and D ). Additionally, we reinforced the upregulation of STX4 in ccRCC by cross-validating our findings with the HPA database and IHC staining, which yielded concordant results ( Fig. 1 C and D). As anticipated, patients within the STX4 high subgroup exhibited a higher proclivity toward clinical advancement ( Fig. 1 E). Intriguingly, with progressing pathological stages, the role of STX4 appeared to escalate in the survival trajectory of patients ( Fig. 1 F). Cumulatively, these findings suggest that STX4 may function as a tumor enhancer in ccRCC. Functional enrichment analyses of STX4 To gain a deeper understanding of the biological functions of STX4, we conducted a co-expression analysis in the TCGA-KIRC cohort using LinkedOmics. A volcano plot depicted genes that are correlated with STX4 ( Fig. 2 A), and the top 50 positively and negatively correlated genes were visualized by a heatmap ( Fig. 2 B). Functional enrichment analysis revealed a strong correlation between STX4 and immune activation, immune cell proliferation, and the overall immune response ( Fig. 2 C). Interestingly, we also found that STX4 is associated with several pathways that play significant roles in ccRCC progression, including the VEGF signaling pathway, mTOR signaling pathway, NF−κB signaling pathway, MAPK signaling pathway, and HIF−1 signaling pathway ( Fig. 2 C). Knockdown of STX4 suppresses ccRCC proliferation, invasion, and metastasis We further explored the potential pro-oncogenic effect of STX4 in 786O and OSRC-2 cells. After transfecting cells with siRNA to downregulate STX4, we confirmed the decrease in STX4 levels through qRT-PCR ( Fig. S2 ) and Western blotting ( Fig. 3 A). Cell proliferation was evidently suppressed in cells with STX4 knockdown, as indicated by the CCK-8 and EdU assays ( Fig. 3 B and C). Simultaneously, cell apoptosis was increased due to STX4 knockdown ( Fig. 3 D). Additionally, the reduction in STX4 levels also notably triggered cell cycle arrest at the G0/G1 phase ( Fig. 3 E). Furthermore, the wound healing and Transwell assays suggested a sharp decrease in cell migration ability with STX4 downregulation ( Fig. 4 A and B). Interestingly, upon conducting Western blot analysis, we observed a decrease in the expression of AKT, HIF2α, and VEGFA following STX4 knockdown. This alteration might provide an explanation for the suppression of ccRCC proliferation and metastasis ( Fig. 4 C, S3 ). STX4 promotes the infiltration of CD8 + T cells and reduces the proportions of CAFs and M2-TAMs To characterize the immune status, we carried out a comparison of immune cell infiltration levels between the STX4 high and STX4 low groups within the TCGA-PRAD cohort. Most algorithms revealed that patients with high STX4 expression had increased immune cell infiltration levels, especially for T cells ( Fig. 5 A, S4 ). Notably, the infiltration levels of CD8 + T cells, CD4 + T cells, neutrophils, and dendritic cells were associated with altered STX4 gene copy numbers ( Fig. S5 ). We calculated the ImmuneScore and StromalScore, and those in the STX4 high group reflected lower stromal activity and increased immune activity ( Fig. 5 B). Furthermore, we noticed that the expression levels of most HLA-related genes, which play a pivotal role in antigen presentation during immune recognition processes, were also elevated in the STX4 high groups ( Fig. 5 C). To help accurately predict the effectiveness of immunotherapy, we compared the infiltration levels of CAFs, MDSCs, and M2-TAMs. Patients with high expression of STX4 had considerably fewer CAFs and M2-TAMs ( Fig. 5 D). We further validated the association between STX4 expression and CD8 + T cells, CAFs, and M2-TAMs through TIMER 2.0. STX4 expression was positively associated with CD8 + T-cell infiltration and negatively associated with M2-TAM infiltration in a majority of cancers ( Fig. 6 A). The respective correlation coefficients are shown in Fig. 6 B and C. Notably, while STX4 expression exhibited a positive correlation with CAFs in other types of tumors, it displayed a negative correlation with CAF infiltration in ccRCC ( Fig. 6 D). STX4 as a potential biomarker to predict therapeutic benefits To assess the relationship between immunotherapy response and STX4 expression, we evaluated the correlation between STX4 and immune checkpoint gene expression. Crucially, the expression of most immune checkpoint genes, including CTLA4 and PD-1, was found to be higher in the STX4 high group than in the STX4 low group ( Fig. 7 A). The correlation analysis suggested a positive association between STX4 expression and immune checkpoint gene expression ( Fig. 7 B). Using IPS analysis to assess the immunogenicity of the two prognostic groups, we found that patients with high STX4 expression scored higher on IPS, IPS-CTLA4, IPS-PD1, and IPS-PD1-CTLA4, indicating a potentially increased response to immunotherapy for these patients ( Fig. 7 C). In addition, analysis using the TISIDB database to determine correlations with various chemokines ( Fig. S6 ) showed that STX4 also had a positive correlation with CXCL9 and CXCL10 ( Fig. 7 D), which contribute to a "hot" tumor microenvironment and can increase immunotherapy effectiveness. TMB is emerging as a promising biomarker for predicting patients' ICB responses [ 32 ]. We discovered that patients in the STX4 high group had a higher TMB than those with low expression of STX4 ( Fig. 7 E) and that STX4 expression was positively related to TMB ( Fig. S7 ). In summary, all our results indicate that patients expressing high levels of STX4 may benefit more from immunotherapy. These findings were further confirmed when evaluated in two independent cohorts undergoing immunotherapy (GSE67501 and NIHMS1611472), where a higher response rate to immunotherapy was observed in STX4 high patients ( Fig. 7 F). Given that tyrosine kinase inhibitors remain the first-line therapeutic choice for advanced ccRCC, we compared the sensitivity of sorafenib, sunitinib, pazopanib, and axitinib across the STX4 high and STX4 low groups. The patients in the STX4 high group were more likely to respond to axitinib, while the patients with low expression of STX4 responded better to sunitinib and pazopanib ( Fig. 8 A). For sorafenib, the difference between the two groups was not statistically significant ( Fig. S8 ). By analyzing the CellMiner database, we identified 37 drugs with sensitivities significantly related to STX4 expression ( Table S1 ). Interestingly, everolimus, an mTOR pathway inhibitor approved for the treatment of refractory RCC [ 33 , 34 ], showed a positive correlation with STX4 expression ( Fig. 8 B). Patients expressing high STX4 levels also had higher sensitivity to everolimus. To further validate these findings, we compared cell viability between cell groups treated with si-STX4 and si-NC following treatment with these drugs. Surprisingly, consistent with the results of the bioinformatics analysis, both the therapeutic effects of axitinib and everolimus were diminished following STX4 knockdown ( Fig. 9 A). Furthermore, everolimus-induced apoptotic cells were significantly less prevalent in the si-STX4 group than in the si-NC group ( Fig. 9 B). Nevertheless, it seemed that there was no close relationship between STX4 expression and the drug sensitivity of sunitinib and pazopanib in ccRCC ( Fig. 9 A). Pan-cancer analysis The TIMER database provided us with a visualization of the differential expression of STX4 in a range of cancers. Differential expression of STX4 was observed in BLCA, BRCA, CHOL, ESCA, HNSC, KICH, KIRC, KIRP, LIHC, LUAD, STAD, and THCA ( Fig. 10 A). Moreover, STX4 was found to be strongly associated with immune checkpoint genes across most tumors ( Fig. 10 B), and it correlated with TMB and MSI in several cancers ( Fig. 10 C and D). From survival analysis, we also identified that STX4 expression was linked to OS or PFS in numerous types of tumors ( Fig. S9 ).

Discussion Currently, continuous progress in understanding renal cell tumor biology has resulted in the development of molecular therapies aimed at the VEGF and mTOR pathways [ 35 , 36 ]. Concurrently, the emergence of immune checkpoint inhibitors has added another therapeutic option for patients with advanced ccRCC [ [37] , [38] , [39] ]. Notably, immunotherapies such as nivolumab have already been incorporated into treatment regimens for metastatic ccRCC [ 40 ]. However, a key challenge remains in dealing with the high heterogeneity of tumors, as they vary greatly in their cell biological characteristics and genetic makeup. Consequently, patients suffering from metastatic or advanced RCC often have a poor prognosis, given the lack of effective therapies that can provide long-lasting responses [ 41 , 42 ]. Therefore, it is crucial to focus on identifying and validating reliable biomarkers. These could improve the selection process for first-line treatments and make them more effective by tailoring them more specifically to the individual patient's genetic and biological context. The process of cancer cell metastasis relies on the delivery of ECM and integrins to the cell surface, driven by various SNARE proteins [ 43 ]. These proteins play a critical role in vesicle transport at both the cell surface and within intracellular compartments [ 43 ]. STX4 is involved in the formation of cell invadopodium and tumor cell infiltration [ 16 ]. A previous study by He et al. suggested the prognostic value of STX4 in kidney renal clear cell carcinoma (KIRC) [ 18 ]. Nevertheless, whether STX4 impacts the proliferative and invasive abilities and tumor microenvironment of ccRCC remains to be investigated. In this study, we demonstrated the aberrant upregulation of STX4 expression in ccRCC and discovered its close correlation with the prognosis of ccRCC patients. Interestingly, we observed that STX4 was abnormally overexpressed during tumor progression. Patients in the STX4 high group had a higher proportion of advanced clinicopathological characteristics. These findings suggest that STX4 plays a crucial role in the prognosis of patients with advanced and metastatic ccRCC. To decipher the underlying molecular mechanisms, we performed functional enrichment analysis in the STX4 high and STX4 low groups. This revealed that dysregulation of STX4 was connected with several known cancer-promoting pathways, including VEGF, NF−kappa B, and HIF−1 signaling pathways. Additionally, in 786O and OSRC-2 cells, we conducted molecular experiments to gauge the potential tumor-promoting function of STX4. The results illustrated that STX4 knockdown decreased the proliferation and migratory abilities of ccRCC cell lines and increased apoptosis. Western blot results further suggested that STX4 might impact the levels of AKT, HIF2α, and VEGFA, thereby affecting ccRCC development. The results of pathway enrichment analysis suggested a link between STX4 and immune responses. This implies potentially significant immunological differences between ccRCC patients with high and low STX4 expression. We observed higher levels of immune cell infiltration, particularly of T cells, in patients showing increased STX4 expression. Several algorithms have confirmed the positive correlation between STX4 expression and infiltration levels of CD8 + T cells, which are vital for host defense against tumors [ 44 ]. In contrast, we observed a significant reduction in the cell populations of CAFs and M2-TAMs, cells known for their immune-suppressive properties in the tumor microenvironment. Moreover, the expression levels of immune checkpoint genes and the majority of HLA-related genes were considerably elevated in the STX4 high group. Higher IPS scores are related to increased immunogenicity [ 45 ], and we indeed discovered higher IPS, IPS-CTLA4, IPS-PD1, and IPS-PD1-CTLA4 scores in patients with high STX4 expression. CXCL9 and CXCL10 expression have been reported to contribute to the generation of a "hot" tumor microenvironment [ 28 ]. By using the TISIDB database, we identified a positive correlation between STX4 expression and CXCL9 and CXCL10 expression. Recent studies have reported that tumor mutation burden (TMB) correlates with immunotherapy response because it reflects the total neoantigen load [ 46 , 47 ]. Here, we found a strong positive association between STX4 expression and TMB. Patients with high STX4 expression had a higher TMB, indicating a potentially superior response to treatment. These results all suggest that patients with high STX4 expression may benefit from immunotherapy. To validate these findings, we utilized two cohorts of ccRCC patients treated with immunotherapy. Consistent with our previous findings, patients in the STX4 high group had a higher immunotherapy response rate. The European Association of Urology recommends the usage of combination therapies such as nivolumab and ipilimumab or pembrolizumab and axitinib as initial lines of treatment for intermediate and high-risk patients [ 48 ]. Another clinical trial reported that the PFS was noticeably extended with the administration of avelumab in combination with axitinib, as compared to sunitinib in patients suffering from advanced RCC [ 49 ]. Moreover, targeted therapies for metastatic RCC have been observed to exhibit immunomodulatory effects, including the enhancement of tumor cell antigenicity and incitement of T-cell infiltration [ 50 ]. Consequently, the combination of targeted therapies and personalized immunotherapy might be a more suitable therapeutic approach for individuals diagnosed with advanced ccRCC. Thus, we undertook a comparative analysis of the IC50 values of first-line therapeutic agents available in the GDSC database between the groups presenting high and low levels of STX4 expression. Our findings suggest that patients in the STX4 high group were more likely to be responsive to axitinib. Everolimus has been approved by the FDA for the treatment of RCC refractory to inhibitors of VEGF receptor signaling [ 34 ]. Through analysis results from the CellMiner database, we observed that patients with high expression of STX4 are more sensitive to everolimus, which was preliminarily proven by CCK8 and flow cytometry results. Based on these observations, we posit that STX4 could serve as a biomarker potentially aiding in the selection of treatment regimens in clinical practice. Patients with high STX4 expression appear to show a better response to immunotherapy and increased sensitivity to axitinib and everolimus. Although we validated the pro-oncogenic effect of STX4 on ccRCC cell lines and identified STX4 as a potential biomarker to aid treatment decisions in ccRCC, several limitations to this study need to be acknowledged. First, animal experiments are vital to further validate the biological functions of STX4 in ccRCC. Additionally, although we validated the correlation between STX4 and immune checkpoint genes, TMB, and MSI by pan-cancer analysis, the specific mechanism still needs further investigation.

Conclusions In conclusion, we validated the disparity in the expression of STX4 and its prognostic value in ccRCC. In vitro tests were conducted to examine the cancer-promoting role of STX4 in ccRCC. Additionally, we evaluated the correlations between patient response to immunotherapy, targeted therapies, and STX4 expression. Our results suggest that ccRCC patients with high STX4 expression could potentially benefit from axitinib, everolimus, and immunotherapy. This finding adds to our understanding of STX4 as a promising biomarker for predicting treatment responses and aiding therapeutic decisions in ccRCC.

These authors contributed to this work equally and shared first authorship. Clear cell renal cell carcinoma (ccRCC) represents a frequent subtype of kidney cancer, with the prognosis remaining poor for individuals with metastatic disease. Given its resistance to both radiation and chemotherapy, targeted therapies and immunotherapies have emerged as critical for effective ccRCC treatment. Within this context, the SNARE protein STX4, which is associated with malignant cancer cell migration, provides a promising focus. The underlying mechanism, however, requires further illumination. Furthermore, the influence of STX4 on the ccRCC tumor microenvironment remains to be determined. In our research, we utilized multiple databases and immunohistochemical staining to confirm differential STX4 expression and its prognostic implications. We evaluated the potential tumor-promoting function of STX4 in ccRCC cell lines through molecular studies. Additionally, we conducted functional enrichment analysis to delve deeper into the underlying mechanisms and performed immune infiltration and drug sensitivity analyses to assess the potential of STX4 as a prognostic biomarker and therapeutic target. Our study reveals that STX4 contributes to cancer progression by enhancing AKT expression and stimulating the activation of VEGF signaling pathways. Additionally, STX4 further fosters CD8 + T-cell infiltration and diminishes the percentage of CAFs and M2-TAMs. Our findings suggest that patients presenting higher STX4 levels may exhibit enhanced responsiveness to immunotherapy and higher sensitivity to the medications axitinib and everolimus. Finally, we propose STX4 expression assessment as a novel approach to predict patient response to respective immunotherapies and targeted treatments, hence potentially improving patient outcomes. Keywords

Data availability statement Data will be made available on request, and all the data can be obtained by contacting the corresponding author. CRediT authorship contribution statement Kai Zeng: Writing – review & editing, Investigation. Qinyu Li: Writing – review & editing, Investigation. Xi Wang: Writing – review & editing, Writing – original draft. Chaofan Liu: Writing – review & editing, Software. Bingliang Chen: Writing – review & editing, Resources. Guoda Song: Writing – review & editing, Software. Beining Li: Writing – review & editing, Resources. Bo Liu: Writing – review & editing, Resources. Xintao Gao: Project administration, Conceptualization. Linli Zhang: Project administration, Conceptualization. Jianping Miao: Writing – review & editing, Project administration, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary data The following is/are the supplementary data to this article. Acknowledgements The funding for this research was provided by several grants. This included grants from the 10.13039/501100001809 National Natural Science Foundation of China (grant numbers 81902619 and 82360606), the Wuhan Shuguang Project (grant number 2022020801020447), as well as funding from the 10.13039/501100004317 Shihezi University Project (grant number ZZZC2022088).

CC BY

no

2024-01-16 23:43:44

Heliyon. 2023 Dec 21; 10(1):e23918

oa_package/18/7b/PMC10788513.tar.gz

PMC10788514

38226246

Introduction Soil erosion is generally viewed to be the result of a confluence of natural factors and human activities [ 1 ]. With global warming, extreme rainfall and severe weather are becoming more and more frequent. Extreme rainfall events lead to soil nutrient depletion and destruction and loss of land productivity [ 2 ], which strongly controls the amount of soil erosion every year and for many years [ 3 ]. At the same time, increasing human activities such as population increase, accelerated urbanization and land use changes, have accelerated soil degradation and caused a decline in regional soil quality [ 4 ]. Soil erosion has gravely threatened the social and economic security of various countries in the world [ 5 ], its governance has received extensive attention from scholars around the world [ 6 ]. Soil erosion not only leads to soil degradation, resulting in a decline in land productivity, but also leads to massive soil erosion, it can easily lead to ecological problems such as river siltation and increased floods, thus threatening the development of human society [ 7 ]. Based on this, quantitative analysis of soil erosion is essential for controlling soil erosion, implementing the overall requirements of ecological civilization construction, and achieving sustainable social and economic development. For the research of soil erosion, scholars engaged in this work have passed a lot of experiments, combined with statistics and analysis, among which the USLE (Universal Soil Loss Equation) [ 8 ] and WEPP [ 9 ] models of the United States have been recognized by many scholars. As early as 1882, the German soil scientist Ewald Wollny established the runoff plot method and began the quantitative research of soil erosion [ 10 ]. After years of development, Wischmeier and Smith [ 11 ] formulated the USLE through artificial simulated rainfall test and observation data analysis of multiple runoff plots. Later, after a lot of practice by experts and scholars, in 1986, the USDA developed a water erosion prediction model (WEPP) [ 12 ] that comprehensively considered the hydrological conditions of the land. In 1997, a modified equation (Revised Universal Soil Loss Equation, RUSLE) was obtained which can carry out soil erosion prediction of single rainfall. And in 2002, Liu et al. [ 13 ] analyzed the runoff plot data, established the CSLE (China’s Soil Loss Equation). Scholars’ early studies on soil erosion models are mainly the introduction and improvement of models such as WEPP, USLE, and others. Later research is based on the USLE model. Through a series of exploration and practice of soil erosion impact factors [ 14 ], the research which are based on the USLE/RUSLE model has many practical applications in regions and basins. At present, scholars’ research on soil erosion mainly covers several aspects such as scale, method, content etc. In terms of scale, there are mainly natural regional scales such as watershed [ 15 , 16 ], plateaus [ [17] , [18] , [19] ], basins [ 20 ], and administrative unit scales such as countries [ 21 ], provinces [ 22 ], cities [ 23 ], soil erosion zoning. Based on these research scales, scholars have made more estimates of soil erosion in Chinese watersheds, but relatively few studies on soil erosion at the scale of the lower reach of the Yellow River (LYR), and most of them take administrative units [ 24 ] or typical geomorphological areas [ 25 ] as research objects. There are few reports on soil erosion estimation in LYR by USLE/RUSLE. From the perspective of methods, there are mainly USLE/RUSLE model estimation [ 26 ], InVEST (Integrated Valuation of Ecosystem Servicesand Tradeoffs) model analysis [ 27 ], WaTEM/SEDEM (Water and Tillage Erosion Model/Sediment D Elivery Model) model evaluation [ 16 ]. On the whole, the basic trend and method of quantitative evaluation of soil erosion are supported by GIS and RS, using soil erosion models such as USLE/RUSLE, WEPP, CSLE, and others, to create a soil erosion impact factor library to complete the quantitative evaluation of soil erosion. Among them, WEPP model belongs to physical process model, and its applicability in AALYR is still unknown. The RUSLE method comprehensively considers the effects of rainfall, soil, terrain, vegetation and engineering measures. Compared with the USLE model, it is suitable for more complex terrain and has strong applicability and is widely used in quantitative soil erosion studies around the world [ 25 , 28 ]. From the perspective of research content, it is mainly related to climate change [ 29 ], land use [ 16 ], mining area development [ 30 ] and other factors. There are also studies on a single comprehensive understanding and analysis of soil erosion, and to investigate the impact mechanisms behind it [ 31 ]. As the birthplace of China’s agricultural civilization, the Yellow River Basin (YRB) has a long history of agricultural development. It has been in high-intensity development for a long time, resulting in contradictions such as fragile ecological environment, water shortage and prominent water environment problems in YRB [ 32 ]. As one of the China’ main grain producing areas and core areas, AALYR belongs to the traditional agricultural area. It is one of the typical regions in China with rapid economic development and greater impact from human activities [ 33 , 34 ]. While facing the transformation to a modern society, it also bears the pressure of dense population and the resource and environmental load problems brought by agricultural development [ 35 ]. On the basis of these, the development of urbanization and cultivated land rotation have brought many environmental problems to AALYR. With the increasing demand for limited soil resources and the gradual reduction of per capita cultivated land, soil erosion and destruction has become an important issue affecting the ecological protection and sustainable economic and social development in AALYR. The quantitative research of soil erosion in AALYR has become an urgent problem to be solved. Therefore, based on the data of remote sensing image, land use, soil properties and so on, combined with RUSLE model and GIS technology, this paper maps and analyzes the soil erosion assessment in AALYR, so as to have a comprehensive and holistic understanding of its soil erosion situation. It can be used as the basis for developing AALYR soil protection measures, and also contributes to the ecological environment management, high quality and sustainable development of the world’s great river basins ( Fig. 1 ).

Materials and methods Study area Considering the ancient Yellow River flood distribution, and reference to relevant literature [ 36 , 37 ], 20 prefecture-level cities of Henan and Shandong provinces were selected as AALYR. Among them, Laiwu was assigned to Jinan in 2019. In this paper, it is attributed to Jinan for analysis. The overview of study area is shown in Fig. 2 . The topography of AALYR is dominated by plains, hills and fan delta. The terrain is undulating and gentle, the sediment is constantly silting up, and the downstream river channel is rising year by year, thus forming the world’s famous “suspended river”. Under the national soil and water conservation zoning, AALYR is located in the China’ Northern Rocky Mountain area [ 38 ]. The soil is mainly fluvo-aquic soil, frequent cultivate leads to weak corrosion resistance and high risk of soil erosion. Data sources The relevant data required are as follows ( Table 1 ). Methods RUSLE model RUSLE is an effective tool for quantitative estimation of soil erosion [ 40 ] is widely used. In this paper, according to the RUSLE model method, the results of spatial distribution of R , K , LS , C , and P factor are obtained. Then, the factors are multiplied in ArcGIS 10.3 to obtain the estimation results. Calculation formula is as follows (1) : where: R is rainfall erosivity factor, K is soil erodibility factor; LS is slope length factor; C is vegetation cover management factor; P is the factor of soil and water conservation measures; A is the amount of soil erosion t/(hm 2 ·a), the unit is converted to t/(km 2 ·a) after multiplying 100. Factor R Rainfall is the direct external driving force of soil erosion. R reflects the influence of rainfall on soil erosion. Considering the size of AALYR, the availability of data and the simplicity of processing, this paper chooses Wischmeier [ 41 ] formula to obtain R . The formula is as follows (2) : where: R is the rainfall erosivity factor; p j is monthly rainfall; p is the annual rainfall. Factor K K is determined by the physical properties of the soil, but it is usually difficult to obtain parameters such as soil structure and soil infiltration ratio [ 42 ]. In view of the easy availability of data, the EPIC (Erosion-Productivity Impact Calculator) model constructed by Williams [ 43 ] is selected to calculate the K factor, which responded well to soil erodibility. The formulas are as follows (3) and (4) : where: SAN is the percentage of sand (%); SIL (0.002∼0.05 mm) is the percentage of silt (%); CAL is the content of clay (%) [ 44 ] (See supplementary file for details); OC is the organic carbon content (%). Factor LS LS is obtained based on the LS factor calculation tool [ 45 , 46 ] established by Fu et al. [ 47 ] for evaluating soil erosion in China. The formulas are as follows (5) , (6) , and (7) : where: L i is slope length factor of i th grid; , is slope length of the grid outlet and inlet respectively; m is slope length index. Factor C The higher the C , the worse the vegetation cover [ 48 ]. According to the Rocky Mountain area of Northern China where the study area is located and referring to scholars [ 49 , 50 ] used the estimation method model in the calculation of China’ soil erosion to calculate C factor. The formulas are as follows (8) and (9) : where: F represents fractional vegetation cover. Factor P The higher the P , the greater the possibility of soil loss (its value is between 0 and 1) [ 51 ]. The study area is in the rocky mountain, so the P factor are assigned by relevant literatures of the same type of research area [ 52 , 53 ], as shown in Table 2 . Kernel density analysis Kernel Density Analysis will produce a density surface to reflect the aggregation of the elements [ 54 ]. Generally speaking, kernel density analysis refers to the probability of geographical events occurring in different spatial locations. The probability of point-intensive regional events is high, and its density is large; on the contrary, the events in the region of sparse points have a low probability of occurrence and a small density. Through kernel density analysis, we can intuitively see the probability of soil erosion, reflecting its aggregation characteristics. Calculation formula is as follows (10) : where: f(x) is kernel density value, k is kernel function, x g represents the independent distribution of g sample points, and g is the number of points in the sample range. Multi-scale analysis In this paper, through the administrative vector data of the city, county and town, the soil erosion situation in 2000, 2005, 2010, 2015 and 2020 is counted to analyze the soil erosion characteristics at different scales. The average value of all pixels in the grid belonging to the same area as the output pixel is calculated, so as to measure the average soil erosion amount of each administrative region at different scales. According to the principle of zoning statistics, in the larger administrative divisions, the same amount of soil erosion, due to the larger coverage area, the average treatment compared with the smaller administrative grading changes are not obvious. Therefore, the smaller the scale is, the more prominent the serious erosion area is. In this way, according to the erosion in the administrative district, relevant policy measures for the avoid and contain of soil erosion can be effectively formulated and implemented by administrative means, which is more conducive to the management of regional soil erosion. The brief method is illustrated in Fig. 3 . Geodetector Geodetector is a statistical analysis method based on spatial differentiation theory [ 55 ]. It can reflect the similarity of the same region and the difference of different regions, so as to obtain the spatially distinctive features of geographical phenomena and the driving factors behind them [ 56 ]. The Geodetector includes four modules: factor detection, interactive detection etc. The two main detections used are as follows. (1) The factor detection reflects the ability of a single factor to explain a geographic phenomenon. Formula is: where: l represents the number of layers of the independent variable X; N e and N are the number of samples in the layer and region; 2 and are the overall variance of the sample. When 2 ≠0, the model is established. q ∈ [0,1], it reflects the explanatory power of X for the spatially differentiated characteristics of soil erosion. (2) The interactive detection reflects the common explanatory power of the interaction between factors. Based on the analysis results, the important influencing factors of soil erosion can be understood.

Results Spatiotemporal characteristics of soil erosion in AALYR Spatial pattern of soil erosion factors RUSLE for assessing soil erosion is composed of R , K , LS , C , and P factors. R is mainly caused by heavy rainfall, reflecting the influence of rainfall. Factor K reflects soil erodibility and soil erosion resistance. LS reflects the influence of topographic features. Factor C describes the effect of vegetation coverage on soil erosion. P mainly reflects the influence of agricultural tillage measures, engineering measures and plant measures. They can be obtained according to the calculation method in the RUSLE model. R factor is an important influencing factor in this paper. R is obtained from Formula (2) ( Fig. 4 ). From Fig. 4 , the high value of R factor is mostly distributed in or near the provincial capitals of Zhengzhou and Jinan in the five years. This may be due to the large population and intensive industry in large cities, which triggers the urban rain island effect and leads to an increase in precipitation. In addition, the high degree of hardening of the ground will affect the infiltration process of rainwater, which will lead to the increase of surface runoff in these areas and cause soil erosion. The R factor was generally lower in 2015, due to the impact of drought, and the precipitation was lower than other years [ 57 ]. In general, due to the effect of various factors, the spatial difference of R factor in different years is obvious, and it also has different influence on soil erosion in that year. According to the RUSLE model, the factor K and LS are obtained ( Fig. 5 ). From Fig. 5 , the K factor shows a high value in most areas, and the K factor in a few and very few areas show medium and low values, mainly distributed in the eastern. This is largely related to the large-scale distribution of fluvo-aquic soil in AALYR, its physical and chemical properties determine the risk of soil erodibility. LS is mainly related to the terrain, the value of high altitude and large slope is larger, so it is higher in the mountains of central-south Shandong province, Taihang Mountains and Songshan Mountains in the study area, and the value in other areas is lower. Among them, the mountains of central-south Shandong province, Taihang Mountains and Songshan Mountains are in the eastern, western and southwestern. Factor C is calculated by the RUSLE model is shown in Fig. 6 . In areas with dense vegetation, the water retention effect of plant canopy making soil erosion lighter. On the whole, the high value of C factor is mainly in the north and scattered in the middle, corresponding to the waters and some bare areas in the study area. In addition, the implementation of returning farmland to forest policies around 2000 has greatly increased the vegetation coverage. Fig. 6 shows that factor C is changing in a good direction from 2000 to 2020, which is conducive to preventing soil erosion. Factor P is an important factor affecting soil erosion. Factor P results are obtained according to Table 2 ( Fig. 7 ). According to the distribution of P ( Fig. 7 ) and its calculation method, the P of unused land and built-up land is 1, so they are the high-value concentration areas of the P . Correspondingly, the low values are mainly distributed in the waters. P value is closely related to changes in the land use. Spatial distribution characteristics of soil erosion grade According to the results of each factor obtained in Section 3.1 , after being converted into a unified resolution (30 m), the soil erosion from 2000 to 2020 is obtained in ArcGIS 10.3 through map algebra tool. To more clearly analyze the changes of erosion from 2000 to 2020, we classify erosion grades according to the classification standard [ 58 ] ( Table 3 ). According to the erosion grade map ( Fig. 8 ), the distribution pattern of erosion grade is generally consistent. Very slight grade area is the largest, followed by slight and moderate grade, which occupy most area. Severe, very severe and extremely severe grade is less distributed, mainly in Jinan, Zibo, Tai 'an, Anyang, Hebi, and Zhengzhou. To intuitively explore the distribution of serious erosion area, using ArcGIS 10.3 kernel density analysis tool, the amount of soil erosion at each point was used as the basic data for analysis, and the kernel density map is obtained ( Fig. 9 ). From Fig. 9 , we can find that the areas with high erosion grade are obviously distributed in the western, southwestern, and eastern, and some years are also more serious in the south. The soil erosion in 2015 was the weakest compared with other years, which was largely due to the low rainfall erosivity in 2015 and didn’t have much impact on soil erosion, while the rainfall erosivity in other years was relatively high. Generally, the density center of the serious erosion region is gradually weakening, reflecting the gradual improvement of the soil and water environment. To reveal the characteristics of erosion grade changes, a statistical table of soil erosion grade change area is made ( Table 4 ). From Table 4 , the soil erosion grade in the 110.64 × 10 3 km 2 area of the study area don’t change, and the area accounted for 74.94%. The erosion grade of 16.37% of the area decreased, and the proportion of one grade decreased was the largest in the area of 24.17 × 10 3 km 2 , which was 10.12%. There are 1.12 % of the five grades of decline, while only 0.07 % of the five grades of increase. The erosion of these areas with large grade decline was more serious in 2000 and improved by 2020. The area with increased erosion grade accounted for 8.69%, which was less than the area with decreased erosion grade. The area of 6.39 % increased by one grade, and the increase of most erosion grades was relatively small. Spatiotemporal evolution characteristics of soil erosion grade According to the erosion during study period, obtains the transformation map of soil erosion grade ( Fig. 10 ). The width between the chord lengths at both ends in Fig. 10 represents the proportion of the transfer area, and the arrow represents the direction of the transfer. From Fig. 10 , the very slight and slight erosion in each period occupied most of the area, all of which were above 85%, and up to 95.20% in 2015. According to the transformation between different erosion grades shown in Fig. 10 , we can see that during the study period, in the 2000–2005 stage, the area of slight to very slight was the largest, accounting for 7.58%, followed by the 2010–2015 stage, very slight to slight with an area ratio of 7.40 %. In addition, compared with the transformation of erosion grade in different time periods in Fig. 10 , it can be found that some variations in the shift of soil erosion grades at each stage. In addition to the erosion grade unchanged, the transition of erosion grade from very slight to slight, and from slight to very slight occupies a relatively large area. On the whole, the area proportion of very slight in the study area increased from 71.04 % to 79.58%, with an increase of 8.54%. The area proportion of other erosion intensity grades decreased, with a decrease of 0.5%–5%. The largest decrease was slight erosion, which decreased by 4.83%. According to the soil erosion, the statistical table of erosion grade area from 2000 to 2020 is obtained ( Table 5 ). It can be seen from Table 5 that the extremely severe area reached the maximum in 2000 and the minimum in 2015. The very slight erosion area reached the maximum in 2015, which was 125.78 × 10 3 km 2 , and the minimum in 2000, reflecting that the erosion situation is the best in 2015. In addition, the area of very slight and slight erosion increased from 128.91 × 10 3 km 2 in 2000 to 133.93 × 10 3 km 2 in 2020. On the basis of the increase of low erosion grades area, the area of the more severely eroded area shows a decrease. Severe, very severe and extremely severe erosion grade decreased to 7.79 × 10 3 km 2 by 2020. Soil erosion characteristics at different scales In order to further understand the soil erosion situation in AALYR from an administrative perspective, the soil erosion characteristics of AALYR are analyzed from multiple scales of city, county and town. Table 6 shows the area of erosion grades at different scales of AALYR. Fig. 11 shows the soil erosion grade at different scales during the study period. From Table 6 , the erosion grade is mostly distributed in very slight, slight and moderate grade on the city scale. The largest area is the very slight erosion in 2015, the smallest area is the severe erosion in 2010, which is 10.231 × 10 3 km 2 . At the county scale, the distribution of erosion grade increased to extremely severe erosion grade. At the town scale, each erosion grade is distributed, but mostly concentrated in the lower erosion grade. The largest area is 112.505 × 10 3 km 2 , which is the very slight erosion in 2015, and the smallest area is the extremely severe erosion in 2015. It can be seen from Fig. 11 that at the city scale, the high erosion grade regions are mainly concentrated in mountainous areas. On the county scale, the dispersion trend of areas with higher erosion intensity grades is gradually significant. Compared with the city scale, some areas with high erosion intensity grades are significantly increased, including some municipal districts in Zibo, some municipal districts in Jinan, and a few municipal districts in Hebi. From the perspective of the distribution on the town scale, the patches with higher grades are mostly focused in the surrounding areas of Jinan, Anyang, Zhengzhou and Zhoukou, showing a more dispersed and specific distribution. At the micro scale, the serious soil erosion areas are more clearly exposed to the administrative jurisdiction, which is convenient for the management of administrative divisions. In general, with the reduction of the scale, the higher-grade soil erosion area is gradually increasing, and the distribution is more and more detailed, which is beneficial to put forward and formulate soil conservation measures on a small scale based on regions of serious erosion, and effectively prevent and control erosion in AALYR from a micro perspective. Analysis of influencing factors based on geodetector Soil erosion process is complex. To explore the differentiation of soil erosion, we select six factors of land use type, elevation, slope, NDVI, annual precipitation and population for analysis with 2020 as the base year. The single factor and interactive detection results of AALYR by Geodetector are shown in Table 7 , Table 8 . The q reflects the influence of factors ( Table 7 ). From Table 7 , The factors are ranked of influence as follows: elevation > land use type > annual precipitation > slope > NDVI > population, all of which passed the significance test (P < 0.05). Among them, elevation (11.92%) and land use type (5.63%) have strong explanatory power. The interactive detection reflects the influence of the interaction between the factors on soil erosion ( Table 8 ). Table 8 reflects that soil erosion is a complex process and indicating that the interaction between factors in this paper has different degrees of enhancement in the explanatory power of soil erosion compared with single factor. Among them, the interaction between elevation and slope has the largest explanatory power, which is 24.19%, followed by the interaction between elevation and NDVI, which is 23.50%, and the interaction between elevation and annual precipitation is 23.29%, indicating that elevation and slop during this period are important factors leading to soil erosion. The above detection results indicate that except topographic, the main factor affecting soil erosion is land use. Soil erosion of different land use type is calculated by ArcGIS 10.3, as shown in Fig. 12 . Fig. 12 shows that there is variation in soil erosion per unit area for different types of land during study period. On the whole, the largest of soil erosion by land use type is forestland. In terms of time, the soil erosion of forestland and grassland water area show a trend of “increase-decrease-increase”, the cultivated land and water show a trend of decreasing fluctuation. Of these, soil erosion was relatively lightest in 2015.

Discussion The soil erosion in AALYR from 2000 to 2020 is estimated by RUSLE, and the results show that the erosion grade is mainly very slight, and the severe and above erosion grades are mainly distributed in Zibo, Jinan, Anyang, Zhengzhou and Tai 'an. The common feature of these cities with serious erosion is that the elevation is relatively high. According to the RUSLE model, K and LS don’t change much, C depends on the surface vegetation coverage and land use type has a great relationship, P value is obtained directly according to the land use type assignment. So, the soil erosion is mainly affected by rainfall and land use. R of the whole study area in 2000–2020 shows a trend of “decline-rise-decline-rise”. Among them, it is particularly obvious that the rainfall erosivity is very small in 2015 due to the influence of drought, and the maximum value don’t reach one third of the maximum value in 2005, and the annual average erosion amount in this year is also the smallest due to the rainfall erosivity, which shows the impact of rainfall. Soil erosion is influenced to some extent by the rainfall erosion factor, but it is not entirely dependent on the change of rainfall but is also affected by other factors. Additionally, when we research the spatiotemporal evolution characteristics of erosion grades and find that the percent of slight and below area is mostly about 85%. While the area percentage of the same grade in Henan Province researched by Liu et al. [ 59 ] is 88.39%, and in the study of mountainous areas of south-central Shandong by Li et al. [ 60 ], the proportion of the same grade of area is also about 85%, which reflected the reliability of the conclusions of this study. Then we find that the smaller the scale, the more detailed the serious soil erosion area, which is beneficial to formulate soil and water conservation planning for severe areas with administrative divisions as management units. Thereafter, the results of influencing factors analyzing show that elevation is the main impact factor of soil erosion, followed by land use type. Fig. 8 also shows that the area with high elevation has serious erosion. Among the different types of land, forestland and grassland have a high degree of erosion, which is affected by vegetation coverage and land use intensity of various types of land. In the studies about YRB [ 61 , 62 ], soil erosion in YRB is declining, in which topography is the important influencing factors, and our conclusion is the same as that. Different from their research, we only analyzed the influencing factors in 2020 and lacked the comparative analysis of the changes of the main influencing factors in each period. After that, we can go deep into this aspect of the research. The effect of land use is actually the influence of human activity-induced changes in land use types on soil erosion. Previous studies [ 63 , 64 ] pointed out that human activities have a greater impact than climate change. We should strengthen the management of soil erosion. In fact, since 1999, return to forestry measures have played an essential role in controlling soil erosion as evidenced by the increase in vegetation cover [ 65 , 66 ], whose role in soil erosion control is very important. AALYR is the key development area of YRB. Previous studies about erosion in AALYR are relatively lacking. And this research is important for the ecological civilization construction and sustainable development of AALYR. The selection of the calculation data of each factor in this paper is consistent with Yang et al. [ 67 ] ( R factor), Qian et al. [ 19 ] ( K factor), Guo et al. [ 68 ] ( P factor), Yin et al. [ 61 ] ( LS factor), Qian et al. [ 69 ] ( C factor), which reflects the scientific nature of the estimation in this paper. The social activities in AALYR are complex and diverse, the land use change is a long-term and slow process. Because of the limitation of data sources, the data of AALYR in 2000, 2005, 2010, 2015 and 2020 are selected. The accuracy of the model calculation is affected by the accuracy of the input data. When calculating the RUSLE model, due to the difficulty of obtaining high-precision data, a simple algorithm is selected to determine the calculation method of the R factor, which would cause the deviation of the results to a certain extent. To summarize, in future studies, data accuracy should be improved as much as possible, and the calculation of each factor should be optimized to promote the precision of the results. In addition, RUSLE has a simple structure, fewer parameters, and more accurate predictions of average soil erosion compared with other soil erosion models [ 70 ]. However, there are some models and methods for quantitative estimation of soil erosion, such as WEPP model, InVEST model, WaTEM/SEDEM model, CSLE model and so on. Among them, CLSE is a soil erosion estimation method derived by Chinese scholars on the basis of soil loss equation, which considers the China’s characteristics of soil erosion. In the future, we can update the data source, refine the research period, try a variety of methods according to the research focus, and carry out deeper research and analysis from more relevant influencing factors.

Conclusions With the increasing impact of global warming and human disturbance, soil erosion has become a serious and lasting environmental challenge affecting ecological construction and social economic development [ 71 ]. The high-quality development of AALYR has very important strategic significance for the development of China. Conclusions in the text can serve as foundations for developing reasonable soil and water conservation measures in AALYR. What’s more, it has important practical significance for local agriculture, industry, economic production, and environmental protection. The analysis revealed that although soil erosion in AALYR varies from 2000 to 2020, it shows a general pattern of “northeast high, middle low, southwest high”. Annual average soil erosion shows the most obvious downward trend from 2010 to 2015. Overall, the erosion grade is changing to very slight and slight grade, and the soil erosion status is also significantly improved. When analyzing the erosion characteristics at the city, county, and town scales, it is concluded that with the reduction of the scale, the area of serious erosion area gradually increases and the distribution gradually disperses, but the location characteristics of serious erosion area will be more detailed. In the final influencing factors analysis, soil erosion is mainly affected by elevation and land use. Soil erosion in high altitude areas is more serious than that in low altitude areas. Forestland is the land type with the highest soil erosion, followed by grassland. Generally, AALYR belongs to the cultivation area, human activities are frequent, and the built-up land is gradually expanding, which will greatly increase the soil erosion, so the ecological protection of soil should be paid attention to. Based on this, we should vigorously promote the advantages of protecting the soil environment. Depending on the erosion condition in AALYR, scientific planning and rational use of land; returning large slope cultivated land to forestland, changing unreasonable cultivation system; increasing organic fertilizer, rational rotation, and improving soil erosion resistance. Create water conservation forests near the reservoir area and the lake area to prevent silt accumulation; through small water conservancy projects to protect and rationally use water and soil resources to prevent soil erosion and restore the ecological environment.

With the accelerated development of urbanization, the exploration and usage of land resources is becoming more and more frequent, which leads to the decline of soil quality, resulting in a series of soil ecological issues, such as soil nutrient loss, soil quality degradation and destruction. At present, the contradiction between soil erosion and sustainable development of human society has become one of the hot issues studied by scholars. The Yellow River Basin is an important experimental area for high-quality development in China, constructing the Yellow River Ecological Economic Belt play an important role in China’s regional coordinated development. Although most of the affected area of the Lower Yellow River (AALYR) is in the plain, they have a large population density and are in the historical farming area. In latest years, because of the development and transformation of modern society, their ecological environment has become more fragile and soil erosion problems has become increasingly serious. Studying and analyzing soil erosion is of vital meaning for ecological protection and can provide scientific support for soil conservation work. Depending on the data of precipitation, soil properties, land use, population, etc., this paper studies and analyzes the soil erosion in AALYR from 2000 to 2020 through the RUSLE. We found that during the 20 years the proportion of very slight and slight grade area increased, and the distribution of moderate and above erosion grade was less, mainly in Zibo, Jinan, Anyang, Zhengzhou, and Tai 'an. Nearly three quarters of the regional soil erosion grade didn’t change, apart from the increase of slight grade area, the other erosion grades area showed a downward trend. We take the city, county and town zoning analysis find that as the scale decreases, the area of serious erosion grades increases, and the distribution is gradually detailed. Land use is the main influencing factor of erosion except DEM. Forestland and grassland are larger of the soil erosion in various types of land use. Through these conclusions in this paper, it is promising to provide theoretical references for the ecological environment governance and high-quality and sustainable development of great river basins of the world and similar regions. Keywords

Data availability statement Data will be made available on request. CRediT authorship contribution statement Ying Zhang: Writing – original draft, Methodology. Pengyan Zhang: Writing – review & editing, Project administration, Funding acquisition. Zhenyue Liu: Software. Guangrui Xing: Software. Zhuo Chen: Writing – review & editing. Yinghui Chang: Investigation. Qianxu Wang: Investigation. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary data The following is the Supplementary data to this article: Acknowledgements This research was funded by the 10.13039/501100001809 National Natural Science Foundation of China , grant number 41601175, 41801362, 2022 Program for Youth Talent of Zhongyuan , 2023 Funding for the Construction of Key Laboratory of Soil Ecology and Environment (2023HNTRWRFZ-HNDX001). We also thank the Geographical Science Data Center of The Greater Bay Area for providing the relevant data in this study.

CC BY

no

2024-01-16 23:43:44

Heliyon. 2023 Dec 20; 10(1):e23819

oa_package/14/b9/PMC10788514.tar.gz

PMC10788515

38226237

Introduction Water is essential to life and water pollution and the introduction of toxic substances to water bodies such as lakes, rivers, oceans, and so on, getting dissolved in them, lying suspended in the water, or depositing on the bed [ 1 ], represents one of the most serious ecological threats. The main aim of this study is to analyze the research dedicated to the system dynamics modelling of water ecosystems' pollution generated by tourism. The water ecosystems' pollution in tourism should be researched in a transdisciplinary way with a special focus on the interrelationship with the social responsibility concept and sustainability management (e.g. Ref. [ 2 ], sustainability indicators (e.g. carbon footprint – [ 3 ], case studies (e.g. Ref. [ 4 ], predictive models [ 5 ] and ecosystem services (biodiversity economy; [ 6 , 7 ]. As a starting point for the desirable transdisciplinary studies, the intention behind this study is to deliver an analysis of the current situation in the aforementioned research directions. Water pollution [ 8 ] noted that pollutants are harmful substances that can include organic, inorganic, radioactive materials, and so on. Pollution degrades the quality of water, represents a disaster for aquatic ecosystems, contaminates groundwater sources for household consumption, and indirectly causes water-borne diseases and illnesses. While water pollution can be caused in several ways, industrial waste discharge and city sewage disposals have been noted as the most contributing factors to water pollution [ 8 ]. Indirectly, water pollution can be an effect of contamination from groundwater bodies or the atmosphere via rain [ 8 ]. Human agricultural practices and improper waste disposal systems are known sources of soil and groundwater pollution [ 9 ]. Furthermore, tourism-related marine activities, such as boating, snorkeling, and scuba diving, also contribute to water pollution through the release of oils, fuel residues, and chemicals [ 10 ]. The cumulative impact of these activities can degrade water quality, harming marine ecosystems. Research emphasizes the need for sustainable management practices to mitigate these adverse effects [ 11 ]. Additionally, the expansion of tourism infrastructure, including the construction of hotels, roads, and ports, can lead to habitat destruction and increased sedimentation in water bodies [ 12 ]. Construction activities introduce pollutants such as sediment, heavy metals, and chemicals into aquatic ecosystems, causing long-term damage. Literature underscores the importance of effective environmental impact assessments and sustainable development practices in the planning of tourism infrastructure [ 13 ]. Tourists also contribute to water pollution through the improper disposal of solid waste, including plastics, packaging materials, and other non-biodegradable items [ 14 ]. The transient nature of tourism exacerbates this issue, as waste management infrastructure may not be adequately equipped to handle the sudden influx of visitors. Studies emphasize the need for awareness campaigns and the implementation of responsible tourism practices to address this aspect of water pollution [ 15 ]. The severity of water pollution caused by the tourism industry is evident in the long-lasting ecological consequences observed in many popular tourist destinations [ 16 ]. Increased nutrient levels, eutrophication, loss of biodiversity, and disruption of aquatic ecosystems are among the documented impacts [ 17 ]. The severity is exacerbated by the cumulative effect of multiple stressors, emphasizing the interconnectedness of various tourism-related activities and their collective impact on water quality. Impact of tourism Tourism as a temporary, short-term based on the movement of people to destinations and their temporary stay outside the places where they normally live leads to excessive consumption of single-use plastic items such as food packaging, bottles, or hotel bathroom accessories [ 3 , 4 ]. Beyond its importance to the existence of the terrestrial life and its criticality in the composition of biosphere, water serves as a crucial source of tourist attraction in coastal and many vitreous destinations [ 18 ]. Water ultimately contributes to the experiential quality of tourism activities in water tourism destinations, however, pollution of water and beaches significantly reduces the quality of the experience of water tourism participants [ 5 , 19 ]. The predominant component of visible pollution in oceans with a share of about 80 % (e.g. Ref. [ 20 ], is plastics, transmitted to the seas and oceans mainly by rivers [ 21 ]. Due to its global rapid growth, transformation, and massification, tourism contributes substantially to the pollution of the environment, especially by plastics [ [22] , [23] , [24] , [25] ]. On the other hand, tourism itself suffers from this pollution, while visitors prefer clean destinations (e.g. Refs. [ 5 , [26] , [27] , [28] , [29] , [30] ], and some segments of visitors even virgin/authentic sites (Wang, 1999). According to the social exchange theory [ 31 , 32 ], the deteriorated life quality of local inhabitants increases their tourism irritation, and this results in a decrease in visitors' experience quality [ 33 , 34 ]. The relationship of tourism to water pollution and water resources in the form of a mental map summarizes Fig. 1 . Tourism-led growth hypothesis, which argues that tourism development is an indicator of economic growth and development, has been validated in academic scholarship. Thus, as tourism develops, the host nations also grow economically resulting in infrastructural development and an increased rate of industrialization [ 37 , 38 ]. According to Ref. [ 39 ]; the rate of industrialization and economic growth is often measured by the number of plastics in society. He argues that in this optics, the larger the share of plastics, the more developed the economy, and at the same time an increasing amount of plastic waste is destroying the environment. The degree of the problem of plastic pollution is documented by the rapidly increasing production of over 335 million tons of plastics worldwide in 2016 [ 40 ] and 400 million tons of plastics worldwide in 2018 [ 41 ], buying one million disposable plastic bottles every minute with only 20 % of disposable plastics being recycled since 2015 (United Nations, 2021), and discovering plastic pieces in almost every place on Earth, including Mariana Trench and Mount Everest [ 42 ]. Under different conditions of waste management, the development of plastic pollution on Earth until 2060 is modeled [ 43 ]. More specifically participation in adventure tourism generates a need for other longer-use plastic outdoor items such as a tent, sleeping bags, rafts/canoes, or surfboards. Both the demand and supply sides of the tourism market are contributing to plastic pollution, directly in destinations and resource regions [ 44 ]. applied SD models for single-use plastic reduction initiatives in the food sector in Thailand. The surge in single-use plastics is due to the urgent production of face masks and medical protective equipment during COVID-19 (Nikiema and Asiedu, 2022). According to WWF (2018), the most popular seaside destination for tourists in the world is the Mediterranean region, which is visited by more than 220 million tourists every year. The organization points out the fact, that during the tourist season, these 220 million people would cause about a 40 % increase in plastic waste in just three months. As stated by Rosian [ 45 ]; due to the semi-enclosed position of the Mediterranean Sea and a large number of estuaries such as the Nile, Ebro, Rhone, Po or Ceyhan, and Seyhan in Turkey, this sea is becoming a so-called "plastic trap", and this is the area with one of the highest concentrations of plastic pollution in the world. According to Ref. [ 46 ]; rural tourism's development can lead to pollution of water sources. They noted that commercializing rural areas for tourism purposes results in more visitors coming through, increased infrastructure investments, and changes to land use patterns—all factors that must be carefully managed when expanding rural tourism operations. These factors can contribute to water pollution through increased wastewater production, agricultural runoff, and poor waste management practices. Such pollutants contaminate rivers, lakes, and groundwater supplies, which affects their quality in rural areas [ 47 ]. Such pollutants contaminate rivers, lakes, and groundwater supplies, which affects their quality in rural areas [ 47 ]. [ 48 ] propose redefining rural resources as countryside capital, specifically discussing rural tourism as an example [ 49 ]. present evidence for sustainable rural tourism activities to minimize negative environmental impacts, particularly water pollution. Their work contributes to understanding integrated rural tourism as a concept. They assert that integrated rural tourism should take environmental sustainability into account and protect natural resources such as waterbodies to minimize pollution and maintain rural areas' attractiveness. Urban tourism pollution has also become an increasing problem. Tourism activities, including increased transportation, accommodation facilities, and waste generation, contribute to water pollution in urban areas. Urban water bodies may become more polluted as a result of wastewater discharge, poor waste management techniques, and tourist use of chemical products [ 50 ]. [ 51 ] highlighted one of the primary drivers behind tourism growth: increasing demand among visitors for new experiences and travel destinations. This demand may lead to increased tourism activities in urban areas, which in turn contributes to water pollution through waste generation, improper disposal methods, and strain on water resources (Mikhailenko et al.). (2020) conducted a literature review on cadmium pollution in tourism environments and found that tourism activities, including hotel wastewater management and increased traffic volumes, contribute significantly to its presence on beaches, coastal waters, and urban parks. However, pollution from these sources can have adverse consequences for tourism destinations [ 52 ]. Urbanization itself, which often coincides with urban tourism activities, further compounds water pollution issues [ 53 ]. assessed urbanization's impact on river water quality in China's Pearl River Delta Economic Zone and found that urban river waters were significantly more polluted compared to rural rivers. Urbanization leads to an increase in industrial and domestic wastewater discharge as well as pollution release from urban areas, all of which lead to reduced river quality [ 53 ]. Tourism and human society with accompanying processes in it can be viewed as complex systems. Therefore, different computer modeling techniques, including models of system dynamics, are applicable. According to Forrester (1961, 1969), system dynamics (SD) aids in understanding the nonlinear dynamics of complex systems over a period of time. Models are developed employing time delays, table functions, internal feedback loops, flows, and stocks. Stock and flow diagrams (SFD) and causal loop diagrams (CLD) are the two primary diagram forms that constitute these artefacts. Typically, CLD captures cardinal system variables and establishes their relationships. Systems Archetypes are universal CLD types that work well in most fields. SFD documents system dynamics and can be applied to a variety of tasks, including scenario evaluation, testing in extreme conditions, sensitivity analysis, boundary testing, and predicting future system behaviour.

Materials and methods System dynamics models provide an invaluable means of comprehending complex systems [ 54 ]. These mathematical representations of interactions and feedback loops within a system enable researchers to simulate and predict its behavior over time [ 55 ]. When applied to tourism-induced water pollution issues, system dynamics models can help researchers simulate plastic waste entering aquatic ecosystems while also assessing different interventions or policies implemented for pollution reduction [ 56 ]. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is an internationally recognized, rigorous approach for conducting systematic reviews [ 57 ]. The PRISMA review methodology was employed to thoroughly assess research approaches and results related to modeling tourism-generated water pollution [ 58 ]. PRISMA provides a checklist and guidelines to enable transparent and comprehensive reporting of systematic reviews, ensuring all relevant studies are identified, selected, and analyzed impartially and systematically [ 59 ]. A recent PRISMA review of scientific contributions published between 2010 and 2022 allowed researchers to synthesize existing research on system dynamics modeling of tourism-generated water pollution [ 58 ]. PRISMA analysis was chosen as part of this study due to its transparent and replicable process for conducting systematic reviews [ 60 ]. By adhering to PRISMA guidelines, researchers ensured their review was comprehensive, impartial, and followed a rigorous methodology [ 58 ]. This methodological approach proved particularly valuable when researching because it allowed for synthesizing existing evidence while simultaneously identifying research gaps or future opportunities [ 61 ]. The present study focuses on system dynamics models of the water pollution, generated by tourism. The PRISMA review [ 62 ] was conducted. The following research questions were formulated. Q 1 Which kind of SD models describing sources, transport, and distribution of pollution of water has already been published? Q 2 Which types of water environments (such as marine, brackish, freshwater, etc.) polluted by tourism-generated debris are frequently researched? Q 3 What were the models' purposes and temporal scales? Q 4 What is the geographic distribution of case studies? Q 5 What system dynamics diagrams and modelling platforms were used? What is the focus of studies on the relationship between tourism water pollution and aquatic ecosystems using SD? The initial search was undertaken using scientific databases Scopus and Web of Science in February 2023. The review includes full texts published in English, published after 2000. The selection criteria and data-gathering approach centered on system dynamics. in relation to the main topics: water and water ecosystems, pollution, and tourism. Cross-searching was carried out employing the domain-relevant search terms and system dynamics keyword. ( Table 1 ). The keywords and abstracts of articles were examined to exclude papers that failed to satisfy the selected inclusion criteria ( Table 2 ). In the first step, 313 results from scientific databases were identified. After removing 184 duplicates, 129 papers were obtained from which 82 papers were sought for retrieval. The rest of the 47 full-text papers were rejected after the title and abstract screening. As two full-texts were not accessible, only 80 papers proceeded to the full-text eligibility assessment stage. Seven papers were excluded in which no system dynamics diagrams or equations were presented, seven other papers were excluded where water pollution was not explicitly captured in the model. Finally, 66 papers (55 journals and ten conference contributions) were analyzed in the frame of both quantitative and qualitative research. Fig. 2 depicts the entire procedure while table 7 (Appendix) presents the selected studies. Finally, the general scheme (figure 8) situation regarding SD modelling of tourism-induced pollution and degradation of water resources and aquatic ecosystems was derived from the synthesis of the partial results.

Results The growing interest in SD modelling in tourism is significant. The majority (91F) of studies were published within the last decade (2012–2023), and over half of them (54 %) between 2018 and 2023. Notably, 2007, 2009, 2012, and 2021 stand out with zero publications, hinting at potential gaps or reduced research activity during those periods. However, a surge in research interest is evident from 2014 onwards, with a peak in 2018. The significant spike in 2018, with 15 papers, might be indicative of a peak in research output, potentially influenced by emerging issues, technological advancements, or increased funding. While certain years, such as 2014, 2015, and 2018, demonstrate a consistent and relatively high number of publications, others like 2007, 2009, and 2012 reveal a lack of research focus during those specific periods. The decline in the number of papers in 2020 and 2021 might be attributed to external factors, such as the global COVID-19 pandemic, which could have disrupted research activities and publication schedules. The overall trend suggests an increasing interest in the topic, especially from 2014 onwards, possibly indicating its growing importance, relevance, or complexity within the academic community. Interest in SD models grows in general, see e.g. SD review in healthcare [ 63 ], transportation [ 64 ], and engineering [ 65 ]. Answer to Q1: Which kind of SD models describing sources, transport, and distribution of pollution of water have already been published? Three categories of papers with respect to the main topics focused on by authors were identified. A large part of the papers is focused on sustainable tourism and carrying capacity. Usually, authors examine the effects of various potential policies on the ecotourism demand and environmental conditions. These models have been already explored by Ref. [ 66 ]. A certain number of models are focused on transport or traffic models, with pollution (of air, water) being one of the important side-effects. Waste production itself, including water pollution by plastics, was, optionally with respect to tourism, presented in the minority of papers. With respect to tourism itself, the following topics are studied: agritourism [ 67 ], cave tourism [ 68 ], city tourism [ [69] , [70] , [71] ], tourism [ [72] , [73] , [74] , [75] ], destination image [ 76 ], ecotourism, low-carbon, tourism, impact on the ecosystem [ [77] , [78] , [79] ], highly aggregated tourist crowds [ 79 ], international tourism [ 80 ], island tourism/small island tourism [ 81 , 82 ], lagoon ecosystem [ 83 ], national park, natural recreation [ 84 ], regional tourism, local tourism [ 85 ], world heritage [ 86 ]. In relation to pollution, the majority of papers discuss waste or pollution in general. Municipal solid waste is a typical type of waste presented in models. Other types of waste are water pollution, solid waste, plastic waste, marine pollution, air pollution, and carbon pollution. Different types of pollution sources have been studied for water-related ecosystems. Numerous research and various contexts have identified carbon emission as one of the sources of pollution. For instance, a study by Ref. [ 87 ] investigated the relationships of five subsystems in Jiuzhai Valley, and carbon emission was one of the parameters taken into account in the environmental representation subsystems and the same context was studied by Ref. [ 88 ] in promoting sustainable development. Number of tourists and carbon emissions have been found to be causally related. Using the bottom-up approach to calculate carbon emissions [ 89 ], found a causal relationship between transportation behavior and carbon mission in Karimunjawa, Indonesia. In their study of the Barents Sea Region [ 90 ], found that among other factors, carbon uptake and export were of interest to the stakeholders. They were concerned about the impacts of climate change on the fishery industry, tour operators, other tourism businesses, environmental, and other non-governmental organizations. In addition [ 73 ], discovered a connection between population quality, size, and greenhouse gas emissions in Baoding, China's city [ 91 ] conducted a study on the effects of historical and real-world behavior on the endogenous dynamics of the power consumption on the Azorean island of São Miguel. According to the results of their analysis, the island should take into account three crucial system components to accomplish its low-carbon goals: electrification of the transportation sector, increased tourism, and energy efficiency. Similar findings have been drawn from further studies, including [ 65 ] in Beijing [ 83 ], in the Chiku coastal zone [ 79 ], in Xingwen Global Geopark [ 92 ], in Galapagos Islands of Ecuador [ 73 ], in Dalian city, and [ 68 ] in Hinagdanan Cave. Plastic pollution Ever since plastic was commercially developed, there has been an accumulating buildup that has resulted in pollution. Human activities result in the production of plastic trash, which is then transported to the ocean and accumulates in the marine ecosystem [ 93 ]. Numerous studies have shown that tourism-led growth occurs in Small Island Developing States (SIDS), however [ 94 ], in the Maldives found that inorganic wastes and inorganic wastes are harmful to the destination. In Sagarmatha National Park and Buffer Zone in Nepal, environmental degradation is pervasive and is mostly attributed to the uncontrolled expansion of tourism-related activities. Solid wastes (including debris) are no longer the only source of pollution; it is also affecting water quality [ 95 ]. Similar research was conducted by Ref. [ 96 ] on the management of municipal solid waste (MSW), which includes plastic waste, in touristic islands (Balearic Islands). They found that the main drivers of the MSW generation were the tourist population, resident population, and Gross Domestic Product per capita. Solid waste and municipal waste In Sicily [ 97 ], asserted that factors influencing tourism demand include the urban environment, transportation infrastructure, natural resources, and cultural resources. In the urban environment, sources of pollution include solid wastes, crowding, and vehicles. Overcrowding, pollution, and water shortages may potentially have an impact on the viability of tourism on Cat Ba Island, according to Ref. [ 98 ]. This was also validated in Ref. [ 99 ] study of the Cat Ba Biosphere Reserve in Vietnam. The marine ecosystem and coastal environment in Cijin and Kaohsiung, Taiwan, have been significantly degraded by waste from tourism activities [ 74 , 75 ]. The waste and pollution subsystem in Gu et al.'s (2021) study of the Maldives divided solid waste generation into two categories (by locals and tourists), which is similar to Ref. [ 100 ]; Luo et al.'s (2020), [ 85 , 101 ]; Pizzitutti et al.'s (2016), and [ 77 ] study in Tunisia, Xingwen Global Geopark in China, Tibet, Chiang Mai City, Galapagos Islands of Ecuador, and Rawa Danau respectively The relationship between tourism dynamics and pollution dynamics is found by Ref. [ 102 ] as a source of waste loading in Pieh Marine Park, which was validated in Amsterdam [ 103 ] and South European island tourist economies [ 81 ]. Answer to Q2. Which types of water environments (such as marine, brackish, freshwater, etc.) polluted by tourism-generated debris are frequently researched? With respect to the water ecosystem, most papers discuss the pollution of seas and oceans. Other topics are rivers, canals, groundwater, domestic wastewater, and brackish water. Twelve publications on water discussed the marine, ocean, and sea, including the following: The study by Ref. [ 89 ] focused on Karimunjawa National Park, which is situated in the Java Sea's Karimunjawa Archipelago. While [ 94 ] research on the Maldives focused on the management of trash generation, Gu et al.'s (2021) study on tourist recovery post-pandemic in the Maldives took the Indian Ocean into account. Studies on ocean literacy and ocean protection by Refs. [ 93 , 104 ] respectively, focused on the ocean. The Pieh Marine Park in Indonesia served as the core of Nugroho et al.'s (2019) research on the long-term viability of marine protected areas. In a study on the effects of climate change on marine fish [ 90 ], took into account ocean warming, acidification, and other environmental factors. The degradation of the marine ecology and coastal environment in Cijin was the focus of the research by Ref. [ 74 ]; although with an emphasis on sustainable coastal tourism which was also addressed by Ref. [ 75 ]. In their 2018 study, Estay-Ossandon and Mena-Nieto also took into account the Balearic Islands while evaluating the Canary archipelago, one of the most popular tourist destinations in the European Union. In their study on coastal management [ 105 ], used the Dutch Wadden Sea as a case study. There were nine papers on drinking water, freshwater, and domestic water. These include the research conducted by Ref. [ 69 ] on sustainable development in a rural area of the Gucheng District of the City of Lijiang. Their findings of this study, which are similar to those of [ 100 ] study of Tunisia, showed that as the tourist population rises, drinkable water reduces and low water use may have an impact on locals' quality of life. According to Pizzitutti et al.'s (2017) research on the Galapagos Islands in Ecuador, the expansion of new urban areas is impacted by drinking water, sewage, and electricity. Fresh water supply is one of the sectors that add to the complexity of the tourism industry, according to a study on the sustainability of mass tourism in South European island tourist economies by Ref. [ 81 ]. Walsh et al. (2014) studied the well-known dangers to national parks by modeling human dynamics, biocomplexity, and global change. The availability of freshwater was a key consideration for the authors when selecting national parks. In Rawa Danau, Indonesia [ 77 ], conducted research on the sustainable management of the freshwater swamp forest as an ecotourism destination. The rest of the papers focus on less frequent topics such as canals in Amsterdam [ 103 ], brackish water in Hinagdanan Cave in the Bohol Island UNESCO Global Geopark [ 68 ], or underground water in the Cat Ba Biosphere Reserve in Vietnam [ 99 ]. Answer to Q3: What were the models' purposes and temporal scales? The temporal scale of the studies under consideration ranges between 6 months and 5 years, with most models working with a step of 1 year. The details on the temporal scale, the period, and the purpose of each research model are included in Table 3 . Other studies not presented in Table 3 inclu [ 67 , 101 ]; and [ 126 ]; whose purpose of the model is the decision support system [ 97 , 100 ]. analyzed the tourism sector in Tunisia, and Sicily respectively, while [ 127 ] evaluated natural destinations and their visitors. The purpose of [ 76 ] research model is to understand the complexity of Ethiopia's image as a tourism destination, while for [ 128 ]; to improve tourism in Slovenia. Furthermore, developing social-ecological system indicators was the aim of [ 105 ] model, for [ 99 ] identified sustainability leverage points, and [ 129 ] examined the condition of the endangered animals. The focus of [ 130 ] model is to reduce the amount of plastic pollution in the ocean in Indonesia [ 95 ], focus was on creating a waste plan, and Walsh and Mena's (2014) study model was aimed at analysing the threats to the national park. One of the purposes of the model is to study the safety of overcrowded areas which was conducted by Ref. [ 131 ]; carrying out a thorough investigation of the accidents involving densely populated tourist crowds that also identified the occurrence mechanism and mitigation strategies. Other purposes include. 1. Analysis of the state of the environment/ecosystem in relation to sustainable tourism as seen in Ref. [ 80 ]; where the authors applied the Amtoudi Oasis in Southern Morocco, Northern Sahar. A similar purpose was found in Ref. [ 78 ] study of Taleqan County in Alborz province, Iran. 2. Prediction: some of the articles such as [ 82 , 112 ] aimed at forecasting the need for recourses in agritourism and future municipal solid waste generation respectively. 3. Decision support and planning was another purpose identified in studies such as [ 85 , 131 ]; and [ 128 ]. [ 85 ] dynamically assessed future sustainability and compared the evolution of sustainability from 2014 to 2050 under various development strategies [ 131 ]. study also aimed at providing a high-quality management response for safety precautions for highly aggregated tourist crowds [ 128 ]. study also aimed at understanding how the Slovenian Tourism development plan and policies should be systematized and enhanced to enable more comprehensive innovation management. 4. Analysis of tourism in specific destinations towards improving destination management was found to be the motivation in studies such as [ 100 , 110 ]; and [ 127 ]. 5 [ 104 ]. study was geared toward educational purposes by increasing ocean literacy. 6. Simulate long-term period in relation to process: land use interactions and carbon emissions (e.g. [ 83 ], Temporal scale: The temporal scale of the model was not presented in 15 papers. The Time step is one year in 49 papers, while 6 papers’ time step is 1 month [ 116 ] simulated the period of 90 days (the shortest period among all models), and [ 122 ] operated with 12 month period. The longest period: 110 years from 1990 to 2100 was studied in Ref. [ 69 ]. Typically, simulation periods start between 2005 and 2015 (close to the date of publishing the paper) and simulations take tens of years steps, e.g. papers attempt to predict the future, e.g. the period 2008–2027 in Ref. [ 86 ]; 2012–2037 in Ref. [ 119 ] or 2014–2050 in Ref. [ 85 ]. Answer to Q4: What is the geographic distribution of case studies? Most models focus on particular destinations from all over the world, e.g., Brazil [ 80 ], Iran [ 78 ], Thailand [ 101 ], South Korea [ 72 ], Tibet [ 85 ], Nepal [ 95 ], Norway [ 90 ], Mexico [ 95 ]. There are also studies describing models of small island destinations, attractive to international visitors such as the Canary Islands [ 82 ], the Cayman Islands [ 118 ], Maledives [ 94 , 110 ] and Galapágos [ 119 ]. China and Taiwan locations are analyzed in 17 papers, followed by Indonesia (9 papers). Case studies from multiple locations were provided by Walsh et al. (2014), and the global ocean was studied by Ref. [ 93 ]. Location was not specified in the five papers. Answer to Q5: What system dynamics diagrams and modeling platforms were used? The distribution of the modelling platform reveals interesting insights into the preferences and trends within the field. Vensim emerges as the most prominently used software, constituting 46 % (23 papers). This dominance suggests a strong preference or perhaps a high level of functionality and user-friendliness associated with Vensim among researchers or practitioners in System Dynamics [ 132 ]. Following Vensim, Stella accounts for 18 % of the usage, indicating a notable but comparatively smaller share. Stella, known for its user-friendly interface and graphical modeling capabilities [ 133 ], seems to be a popular choice, albeit to a lesser extent than Vensim. Powersim also holds a substantial share, representing 16 % of the reported software usage. Powersim is recognized for its simulation and modeling capabilities [ 134 ], and its presence in a significant portion of the cases underscores its relevance in the System Dynamics modeling landscape. The "Not Specified, Own" category, encompassing 16 % of the cases, introduces an interesting dimension. This may imply that a notable proportion of researchers or modelers either use proprietary or customized software solutions tailored to their specific needs. The lack of specification may also indicate a diverse range of tools used by different individuals or groups within the System Dynamics community. MapSys and Simulink each contribute a modest 2 % to the overall distribution. MapSys, although less commonly used, might have niche applications within certain contexts, while Simulink, a powerful tool for model-based design [ 135 ], appears to have a relatively smaller footprint in the creation of System Dynamics models compared to other software options. More than one modelling platform was used by Refs. [ 98 , 103 , 107 ]; and [ 89 ]. Additionally, Causal loop diagrams (CLD) only were presented in 16 papers. CLD and archetypes were presented in two papers. Stock and flow diagrams (SFD) only were presented in 19 papers. CLD and SFD were presented in 34 papers. Answer to Q6: What is the focus of studies on the relationship between tourism and water pollution and aquatic ecosystems using SD? Focus of studies [ 96 ] considered how tourism contributes to waste production. Municipal solid waste generation in the Balearic Islands is investigated. The production of solid waste by tourists and locals until 2030 is forecasted. Similarly, [ 94 ]; explored environmental pollution in the Maldives with respect to the number of tourists per year until 2050 [ 85 ]. investigated sustainable tourism in Tibet under several scenarios up to 2050 using CLD and SFD. The simulation's outcomes include tourism enterprise value, tourist-related employment, number of tourists, and pollution. Using CLD and systems archetypes like shifting the burden (international aid), the tragedy of the commons (carrying capacities in tourism), and fixes that fail (tourism development) [ 99 ]. identified key sustainability factors in the tourist area of Cat Ba Biosphere Reserve, Vietnam. [ 81 ] focused on mass tourism sustainability in island economies. A complex SFD was created by the authors aimed at accommodation capacities, waste, energy and water supply, visitor numbers, and transport. The simulation provided predictions for the requirement for accommodation capacities, tourism impact on price, and the total number of tourists for 720 months under various scenarios. In collaboration with local organizations [ 123 ], sought to develop Bali's touristic villages sustainably. The simulation's results included the projection of sacred places, green space, settlements, and areas of paddy fields until 2030 under several scenarios. In their case study of Pieh Marine Park [ 102 ], focused on the marine protected areas' sustainability. Their initial SFD captured pollution, non-renewable resources, and renewable resources, while their CLD demonstrated a connection between the key elements of the marine park (coral reef condition, pollution, visitor numbers, and fish population). The primary SFD linked the marine park's key variables. The simulation was created to forecast pollution, fish, and coral populations up to 2040 under various scenarios. Similarly, using a sustainable fisheries model and a tourist model, the socioecological system in the Dutch Wadden Sea region was investigated by Ref. [ 105 ]. The touristic sub-model included variables that measured sustainability, investment in tourism, proportions of flora and fauna, visitor number, and satisfaction. Only a few studies explored tourism generally; for instance Ref. [ 73 ], examined ecological system security in the case study of Dalian, China's coastline tourist city. CLD demonstrated links between tourism-related variables, the environment, and economics. SFD focuses mainly on population size, visitor numbers, and GDP. The simulation predicts the marine population, tourism income, and number of visitors until 2028 under three possible scenarios. Other articles examined coastal tourism. In their 2018 study, You et al. focused on South Korean coastal regions' changing landscapes. Coastal forests, coastal grassland, and coastal sand dunes were shown to vary in relation to tourism infrastructure up to 2054 using SFD. The authors created two distinct scenarios, the first of which was centered on the value of ecosystem services and land erosion. The second scenario was updated to assess how the ecosystem services are impacted by the landscape plan. Several studies examined how tourism contributes to waste production [ 96 ]. conducted research on the generation of municipal solid waste in tourist islands using a case study of the Balearic Islands. According to several scenarios, the research estimated that visitors and locals will generate solid waste up to the year 2030. Using the Maldives as a case study [ 94 ], explored waste production. The primary factors in SFD's analysis of environmental pollution and economic growth were the tourism supply and demand, amount of waste, and number of visitors. The waste sub-model was also thoroughly processed and the simulation provided annual predictions for waste, revenue, and visitors up until 2050 under different scenarios [ 68 ]. applied SD modelling to identify a sustainable carrying capacity of the cave system in the Philippines, with an interesting ambition to develop a model archetype that “ can also be tailored-fit to address the uniqueness of characteristics and attributes of any tourism system ”. In relation to water, the authors mentioned “ water-related results from human activities” such as “alteration of water chemistry, alteration of cave hydrology and introduction of alien materials such as pollutants, nutrients, animal species, algae, and fungi.” Recent work focuses on the challenges posed by the COVID-19 pandemic and its negative impact on tourism (hand in hand with the positive effect on the natural environment). While [ 94 ] addressed the problem of tourism growth and related waste generation in Maldives [ 110 ], examined the tourism recovery strategies for the same destination. Small exotic islands are devastated by tourists, but nowadays their economies suffer from the lack of visitors [ 105 ]. adopted a group model-building approach as a diagnostic participative tool for understanding the determinants of characteristic social-ecological systems (SES). In some papers, tourism is not involved in models explicitly. For example, the Shanghai municipal solid waste model [ 124 ] operates with permanent residents and migration residents, but tourism as a phenomenon is not discussed. The limitation of SD models lies in insufficient empirical data; e.g. Ref. [ 110 ], compare four new tourism strategies ( social distancing, tax reduction strategy, travel bubble strategy, joint strategy ) which are so new that data are not available. Variables in models In Table 4 , various models explore the relationship between tourist-related variables, water-related variables, and pollution-related variables [ 121 ]. investigate tourists, tourists' satisfaction, and tourists' needs without delving into water or pollution factors [ 105 ]. consider the use value for tourists, the number of tourists, and spending per tourist, incorporating mussels and the degree of sustainability in tourist facilities [ 69 ]. focuses on tourists, tourism business owners, and tourism services, with an emphasis on water consumption and water quality. Walsh et al. (2014) distinguish domestic tourists, foreign tourists, and tourists in Galapagos, examining boat-based domestic tourists and tourists in Galapagos but excluding pollution-related variables [ 70 ]. assesses tourists' coming and leaving rates, omitting water or pollution considerations [ 102 ]. examine the number of tourists and tourist amenities, correlating them with fish population, coral reef coverage, and pollution-related variables such as water quality, waste, waste treatment, waste discharge rate of tourists, and fraction of waste polluting the environment [ 103 ]. explore tourism area, tourist attractions, tourists per year, tourist revenues, and tourist investments, integrating canal waste treatment and environmental state, pollution, and waste treatment [ 89 ]. consider the number of tourist subsystems, the number of domestic tourists, and the number of foreign tourists, linking them to CO 2 emissions from the ferry, CO 2 emission subsystems, total CO 2 emission from mini tour buses, and total CO 2 emission from private cars [ 67 ]. analyzes tourists' flow, mass tourism, and tourism infrastructure without explicit water-related or pollution variables, though environmental degradation factors are included. Table 5 highlights models where plastic waste is seldom represented in model variables [ 93 ]. focus on plastic waste in streams and oceans, initial plastic waste in the ocean, and target plastic waste levels, while [ 130 ] address plastic bag usage bans, plastic waste, and plastic waste piles at landfills. Table 6 , models frequently aim to identify feedback loops in various contexts [ 101 ]. examine the number of tourists, domestic tourists, international tourists, and total attractiveness in connection with the attractiveness of wastewater disposal and wastewater [ 100 ]. consider the number of tourists and tourism investments in relation to wastewater, pollution, and waste generation [ 127 ]. assess strong purist visitors, attractiveness of the site, moderate purist visitors, neutralist visitors, and non-purist visitors without explicitly mentioning water or pollution variables [ 129 ]. explore the number of tourists, hotels and restaurants, tourism revenue, attraction of CB islands, and tourism service, without incorporating water or pollution considerations [ 97 ]. investigates the number of tourists and the attractiveness of Sicily, connecting them to the attractiveness of Sicily itself and pollution-related variables like solid waste [ 128 ]. center on tourist destination development, sustainable, and spatial development without explicit water-related variables [ 131 ]. examine the pressure of tourist gatherings, the stimulation of attractive elements, the environmental pressure of traveling, and the psychological status of tourists, without explicitly considering water or pollution factors.

Discussion and summary Research released the general situation regarding SD modelling of tourism-induced pollution and degradation of water resources and aquatic ecosystems, which is illustrated by a general scheme ( Fig. 3 ). The need to balance tourism development with environmental protection was identified as the main drawing force while creating, disseminating, and using relevant knowledge as a relevant approach for both research and practice. The ICT and modelling have been implemented in tourism research and practice with the aim of achieving sustainability, responsibility, and competitiveness in water-related tourism destinations. Both economic and environmental aspects and actions are described as well as both causal and intervening conditions. ICT and modelling in tourism research and practice SD is an effective strategy for addressing environmental concerns related to tourism. SD emphasizes integrating economic, social, and environmental elements for long-term sustainability; many studies have explored its application in studies related to water pollution related to tourism. SD-based modeling has become an effective means of understanding the causes of waste generation in tourism destinations. By identifying key contributing factors, including tourist activities, infrastructure development and management practices, and waste disposal policies, these models can assist with developing strategies to minimize waste production and limit water pollution [ 137 ]. Effective collection and analysis of data related to tourism-related pollution of water resources and aquatic ecosystems are integral to informed decision-making. Tools and techniques, such as water quality monitoring systems and data analysis methods, can offer invaluable insight into the sources and impacts of pollution; using this data, targeted interventions to mitigate it can then be developed [ 138 ]. SD modeling can aid decision-making and policy development for solid waste and water quality management in environmentally sensitive tourism destinations. By simulating various scenarios, policymakers can analyze the potential impacts of tourism activities on water quality while identifying effective measures to decrease pollution. SD modeling also assists resource allocation while encouraging sustainable management practices [ 139 ]. Simulation scenarios are powerful tools for identifying and assessing solutions and measures related to tourism's impacts on water quality and management. By simulating various scenarios, policymakers can assess the efficacy of various interventions as well as identify the most suitable strategies to counter water pollution; this enables informed decision-making and proactive resource management [ 139 ]. Proactive planning and management require tools that allow us to predict future trends related to tourism's contribution to water pollution. By employing predictive models and forecasting techniques, policymakers can anticipate the potential impacts of tourism growth on water resources, giving policymakers insight into adaptive mechanisms and strategies needed to minimize water pollution while supporting sustainable tourism practices [ 78 ]. Tourism sustainability, responsibility, and competitiveness Knowledge-based decision-making is essential to optimizing tourism's environmental impacts. Research shows that residents' support for tourism development depends heavily on their perceptions and concerns regarding its impacts [ 140 ]. Policymakers can then make more informed decisions that minimize negative environmental effects while simultaneously maximizing benefits [ 141 ]. Reliable data is essential to effective decision-making in tourism-related environmental studies. Studies have emphasized the significance of collecting and analyzing tourism-related pollution of water resources and aquatic ecosystems, offering insights into the sources and impacts of pollution that enable policymakers to formulate targeted strategies for water quality management [ 142 ]. Optimizing destination resource allocation is critical to sustainable tourism development. Utilizing technology and data for resource optimization is an integral component of smart destinations, contributing to reduced environmental impacts of tourism [ 143 ] while simultaneously mitigating waste generation and water pollution [ 144 ]. Tourism requires quick and flexible responses to environmental challenges. Being responsive and adaptable to changing environmental conditions is key to mitigating tourism's negative impacts on water resources, according to studies [ 145 ]. By taking timely steps, destinations can prevent and mitigate water pollution issues. New visitor management options may also help minimize water pollution. Studies have investigated innovative strategies, like community-based tourism and cultural tourism, that engage visitors while simultaneously encouraging sustainable practices [ 146 ]. Engaging visitors in environmental conservation efforts allows destinations to reduce the negative impact on water resources. An approach that improves water-related ecosystems as complex systems with nonlinear behaviors is vital for understanding and controlling pollution in tourism destinations. Studies have highlighted the need for comprehensive environmental impact assessments that consider ecological, social, and economic considerations [ 147 ]. By adopting such a holistic strategy, policymakers can devise solutions that address complex interactions and feedback mechanisms related to pollution issues in tourism destinations. Economic aspects/actions Studies have clearly illustrated the negative consequences of natural resource degradation on the economic competitiveness and attractiveness of the tourism industry growth [ 148 ]. Degradation can negatively impact tourism industry growth as well as overall attractiveness [ 149 ]. Water pollution may result in declining quality that deters tourists and ultimately impacts economic viability. Water tourism plays an essential role in creating income and employment. Studies have highlighted its significant economic contributions, particularly at coastal and island destinations [ 150 ]. Accessible resources and the attractiveness of destinations that feature water are major influences that drive demand and produce economic benefits for communities [ 99 ]. The water-related ecosystem is an integral element of tourism services and destinations that rely heavily on aquatic environments, with quality and availability directly impacting tourist experiences and satisfaction levels [ 151 ]. Studies have highlighted the significance of maintaining clean and abundant water sources to maintain sustainability and competitiveness for tourism destinations dependent on aquatic features [ 152 ]. An integrated systems approach to assessing the socio-economic effects of water tourism can provide invaluable information for destination management. By considering the complex and dynamic nature of these destinations, such an assessment provides a thorough understanding of their interdependencies and feedback mechanisms, which in turn affect tourism's socio-economic impacts [ 153 ]. 10.13039/100014337 Furthermore , such an approach provides crucial support in decision-making and policy-creation processes to ensure sustainable management [ 154 ]. Environmental aspects/actions Tourism-induced alteration of habitats found in water-related ecosystems is a pressing environmental concern. Tourism activities expanding into coastal areas, wetlands, coral reefs, and other sensitive ecosystems may lead to habitat degradation and loss [ 155 ]. Studies have revealed how infrastructure development, pollution from tourism activities, and physical disturbances due to tourism activities can have adverse impacts on these habitats, altering biodiversity and biocomplexity [ 155 ]. Tourism's impacts on water resources and aquatic ecosystems have long been documented, from solid waste generation and trash accumulation to degraded water quality [ 156 ]. Studies have highlighted the significance of effective waste management practices to mitigate any negative consequences tourism activities may have on these environments [ 157 ]. Changes to water chemistry caused by tourism can also have serious repercussions, with the discharge of untreated wastewater, the use of chemicals in tourism-related activities, and the introduction of invasive species all having detrimental impacts on aquatic ecosystems [ 158 ]. Tourism-induced threats to biodiversity and biocomplexity in water-related ecosystems are becoming an increasing source of concern. Human presence, habitat alteration, and pollution associated with tourism activities may disrupt ecosystems and threaten species' survival [ 155 ]. Studies have noted the need for conservation efforts and sustainable management practices that preserve this vital natural resource [ 159 ]. Ecological security is of critical importance in tourism destinations for their long-term viability and the sustainability of eco-socioeconomic systems. It encompasses protecting natural resources such as water bodies for long-term tourism activities [ 73 ]. Studies have highlighted the significance of including ecological security principles in tourism policies and management strategies to foster sustainable development [ 160 ]. Water and waste management are essential elements of the sustainability of tourism destinations. Effective water management practices include conservation, wastewater treatment, and sustainable use of resources [ 161 ]. At the same time, proper waste management must also take place to prevent pollution of these waters [ 157 ]. Causal conditions Tourism is an influential source of water pollution and resource degradation [ 162 ]. Tourism activity in destinations has increased the production of waste such as sewage, solid waste, and chemical pollutants [ 156 ], which in turn have adverse impacts on water quality, ecosystems, and biodiversity [ 163 ], as well as on coastal regions particularly susceptible to impacts of pollution [ 164 ]. One of the greatest challenges associated with water pollution is access to accurate data [ 163 ]. Accurate data about its sources and impacts is essential for effective management and mitigation strategies, yet data collection efforts often fall short, especially in developing nations [ 164 ]. Without sufficient information available to assess its scope and devise targeted interventions, Studies conducted previously have highlighted the detrimental environmental impacts of tourism on water resources. One such research effort in China revealed that tourism activities led to an increase in water pollution at West Lake Basin due to an increase in tourist numbers and economic income associated with tourism [ 162 ]. A further investigation in Romania demonstrated a direct and significant relationship between tourist activities and environmental degradation and their subsequent degradation, emphasizing the necessity of sustainable tourism practices [ 165 ]. Asserting measures against pollution and degradation of water resources at tourism destinations requires taking an integrated approach. Environmental conservation and sustainable management practices should be prioritized [ 166 ]. This should include implementing efficient waste management systems, encouraging responsible tourism practices, and raising awareness among tourists and local communities regarding water resource conservation [ 165 ]. Furthermore, policymakers should enact policies and regulations that incentivize sustainable tourism practices while discouraging harmful activities [ 167 ]. Intervening conditions Environmental education and awareness play an essential role in fostering sustainable practices and mitigating the negative impacts of tourism on water-related ecosystems. Previous studies have illustrated its importance for changing tourists' behaviors and inculcating responsible environmental practices [ 168 ], with situational environmental education having positive influences on behavioral intentions as well as responsible environmental behavior [ 169 ]. Therefore, including environmental education initiatives in water tourism practices could significantly contribute to raising awareness while encouraging sustainable tourism practices. Environmental investments are essential in mitigating the negative environmental impacts associated with tourism pollution. Research has indicated that destination environmental attributes play an important role in shaping perceptions [ 170 ]. Environmental protection investments can enhance a destination's image and draw in tourists who prioritize sustainability. Studies have also highlighted the necessity for sustainable tourism development in small island developing states (SIDS) [ 171 , 172 ]. SIDS face unique challenges due to their vulnerability to climate change and limited resources [ 173 ]. Therefore, investments in environmental protection for SIDS are imperative for maintaining their unique ecosystems while guaranteeing tourism's long-term sustainability. Strategic planning plays a critical role in controlling the intensification of tourism-induced water pollution, helping anticipate and address its potential negative effects on water resources. Unfortunately, however, research on the use of strategic planning in tourism pollution remains limited compared to its application in other fields. One of the few studies that have been on pro-environmental behavior often uses quantitative approaches such as structural equations or regression analysis [ 174 ], suggesting more comprehensive investigations on its application in managing intensified tourism-induced water pollution. The use of systematic literature review in the tourism and hospitality field is gaining momentum as seen in studies such as [ 175 ] where the authors carried out a systemic review of systemic reviews in tourism. They found that multiple systematic reviews did not clearly explain their data-gathering process, which caused a lack of clarity in the data collection and study results. They suggested that future systematic reviews might be based on more reliable and transparent standards, which are essential to reducing implicit bias and researchers' prejudice, which was taken into consideration in thisstudy. Other tourism areas that this methodology has been used include augmented and virtual reality [ 176 ], disaster and climate change [ 177 , 178 ], ICT in sustainable tourism [ 179 ], and water quality indices [ 180 ].

Conclusions A review of SD in tourism has already been presented by Ref. [ 66 ] that demonstrated the effectiveness of system dynamics models for planning and making decisions in the tourism industry, identifying externalities driven by tourism, and forecasting both its positive and negative effects. Based on their study, system dynamic models in tourism-generated water pollution studies has been reviewed. The focus on SD is because when studying an ecosystem, it is important to analyze non-linear interactions and processes on a large scale and with their long-term impacts. These processes can be well captured by SD models which provide a new perspective. Although it is obvious that tourism contributes significantly to the plastic pollution of (not only water) ecosystems, it still has not been explored deeply using SD models. System dynamics models are either focused on pollution of the environment or tourism itself, but rarely both. Here a research gap of less deeply and systematically studied pollution processes has been identified, as such this study used a metamodel of plastic pollution in the water ecosystem caused by tourism activities using 68 related articles to proffer answers to all the research questions. The result of thereview indicates that carrying capacity and sustainable tourism are major topics of discussion in the papers. Typically, authors examined the effects of various political actions on the state of the environment and the demand for ecotourism. Air and water pollution are significant side effects in a number of models that are centered on transportation or traffic simulations. A small number of publications described waste generation as a whole, including plastic pollution of water as it relates to tourism. The majority of studies discussed ocean and sea pollution in relation to aquatic ecology. Rivers, canals, groundwater, household wastewater, and brackish water are other topics. The research under consideration spans a variety of periods, including 1-time unit, 6 months, and 5 years. Analysis of the state of the environment and ecosystem in relation to sustainable tourism, forecasting, decision planning and support, better destination management, education, and simulation of long-term periods in relation to process are some of the objectives of the models. Furthermore, China and Taiwan locations are the geographical locations that were mostly analyzed, followed by Indonesia, and Vensim, Stella, and Powersim are the most popular modelling platform used. Three variables were identified as the focus of the studies’ model: the number of tourists/visitors, plastic waste, and identified feedback loops. The contribution of the study is in three folds. Firstly, the importance of ICT in tourism research modelling has been identified, particularly, system dynamics, which is a tool for the effective collection and analysis of data associated with tourism-related pollution of water resources and aquatic ecosystems. This will support decision decision-making and policy development for solid waste and water quality management in environmentally sensitive tourism destinations, simulation scenarios as a tool for identifying and evaluating solutions and measures related to tourism impacts on water quality and water management. Secondly, the study's findings emphasize the importance of knowledge-based decision-making to optimize the environmental impact of tourism in increasing the destination's ability to optimally allocate resources and ensure flexible and quick responses to environmental challenges to achieve tourism sustainability and competitiveness. Lastly, environmental education and awareness in water-related destinations as well as investments in environmental protection in water-related destinations are identified as conditions that can intervene in tourism water-related pollution. Findings of this study will support future study directions by assisting scholars and decision-makers in understanding trends and developments in the water pollution impact of the tourism industry. It is recommended that future studies should accommodate other methodologies to further understand the impact of tourism on the water ecosystem. Other analytical methods such as the Theory-Context-Characteristics-Methods (TCCM) create room for exploring the uncovered or less attended areas and develop theoretical models from the perspective of less explored countries to be able to generalize the research in the subject domain. Future research can take into account the interaction of social and cultural aspects because it is still challenging to fully understand the natural ecosystem, human adaptability, and the impact of their connection with nature. Further exploration and refinement of system dynamics models can provide a better understanding of the complex dynamics of pollution in water ecosystems resulting from tourism activities. These models can be enhanced by incorporating variables such as waste management practices, tourism growth patterns, and the influence of socioeconomic factors. Finally, establishing long-term monitoring programs to assess the effectiveness of pollution mitigation measures and policies, while continuously evaluating the state of water ecosystems in tourism destinations, can inform adaptive management strategies and ensure the long-term sustainability of these environments. By addressing these research directions, the understanding of tourism-related pollution can be advanced, effective mitigation strategies, and promote sustainable practices in the tourism industry to protect and preserve water ecosystems. Limitation and future research direction Though this study provides invaluable insight into tourism-induced water pollution, several limitations should be kept in mind. First, its focus on system dynamics modeling may exclude other relevant approaches like agent-based or mathematical modelling that could shed additional light on this complex issue. Future research should compare and contrast various modeling techniques to gain a fuller understanding of this complex topic. Second, restricting itself solely to English-language publications may create a language bias and miss important insights from non-English literature. Tourism being an international phenomenon, research from diverse linguistic backgrounds may enrich the understanding of diverse cultural and environmental contexts; future studies could utilize multilingual research teams or translation services to fill this linguistic void. One limitation lies in the publication date range, primarily covering papers published from 2000 to 2022. While this timeframe captures recent developments, it may miss historical research that could offer context and long-term trends related to tourism-induced water pollution. Future studies should conduct retrospective analyses in order to incorporate previous studies. Plastic pollution may overshadow other pollutants such as chemical contaminants, nutrient runoff, and sedimentation that also have negative impacts on aquatic ecosystems. Future studies must aim for a more comprehensive examination of all the pollutants associated with tourism activities. To overcome these limitations and increase knowledge of tourism-induced water pollution, future research avenues should be explored. Adopting an interdisciplinary approach that incorporates various modeling techniques—system dynamics, agent-based modeling, and mathematical modeling—may give researchers a more in-depth view of its complexity. Using different modeling approaches allows researchers to capture different aspects of an issue, which enables more robust policy recommendations. Beyond pollution and system dynamics, several promising avenues should be investigated. An essential direction would be examining how climate change contributes to tourism-induced water pollution. Climate change impacts, such as altered precipitation patterns, rising temperatures, and sea-level rise, can exacerbate pollution dynamics in tourist destinations. Future research should investigate the interactions between climate change and tourism activities, specifically how changing weather conditions and extreme events could contribute to increased pollution incidents that negatively affect water ecosystems. By including spatial perspectives in future research, incorporating a spatial dimension may also deepen understanding of tourism-induced water pollution. Geospatial analysis and Geographic Information Systems (GIS) can be invaluable tools for mapping pollution hotspots, identifying vulnerable areas, and assessing tourism-related impacts on a geographical scale. By adopting this spatial perspective, researchers can offer targeted recommendations for managing pollution at particular destinations.

This study delves into the intricate dynamics of tourism-induced water pollution through a systematic literature review, aiming to unravel complexities using a system dynamics (SD) modeling approach coupled with the PRISMA analysis methodology. Employing a comprehensive PRISMA analysis of 68 pertinent articles, the study establishes a metamodel for comprehending plastic pollution in water ecosystems resulting from tourism. The methodology emphasizes economic and environmental dimensions, causal conditions, and interventions, with a specific focus on the role of Information and Communication Technology (ICT). The results highlight integrated strategies as crucial in mitigating tourism-induced water pollution. These strategies advocate for the incorporation of environmental conservation and sustainable management practices. The study underlines the pivotal role of environmental education, awareness, and investments in protection as effective interventions. The findings offer valuable insights for policymakers and stakeholders in the tourism industry, emphasizing the necessity for proactive planning and management. The study advocates for knowledge-based decision-making to optimize tourism's environmental impacts and underscores the significance of quick and flexible responses to environmental challenges. Keywords

Funding The financial support of the Specific Research Project Information and Knowledge Management and Cognitive Science in Tourism of FIM UHK is gratefully acknowledged. Data availability statement The data supporting the findings of this study are available upon request. Requests for access to the data can be directed to Martina Pásková ( martina.paskova@uhk.cz ) and will be considered in accordance with the applicable data protection and privacy regulations. It is important to note that certain restrictions may apply to the availability of specific datasets due to confidentiality or ethical considerations. The researchers are committed to promoting transparency and reproducibility in research and will make every effort to provide access to the data in a timely and responsible manner. CRediT authorship contribution statement Martina Pásková: Writing – review & editing, Writing – original draft, Supervision, Investigation, Data curation, Conceptualization. Kamila Štekerová: Writing – review & editing, Writing – original draft, Validation, Methodology, Investigation, Formal analysis, Conceptualization. Marek Zanker: Writing – review & editing, Writing – original draft, Validation, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Taiwo Temitope Lasisi: Writing – review & editing, Writing – original draft. Josef Zelenka: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Investigation, Funding acquisition, Conceptualization. Declaration of Competing interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Appendix Acknowledgments The authors wish to express their thanks to Zuzana Kroulíková, FIM UHK student, who assisted with the graphical elements.

CC BY

no

2024-01-16 23:43:44

Heliyon. 2023 Dec 20; 10(1):e23824

oa_package/e4/bb/PMC10788515.tar.gz

PMC10788522

38142520

Introduction Autonomic nervous system function is regulated by widely ramified networks of the central nervous system involving the brain and the spinal cord. Key areas encompass preganglionic sympathetic neurons from T1 to L2 thoracolumbar segments, the nucleus of the solitary tract, the rostral ventrolateral medulla as well as anterior limbic circuits, the latter also as a part of emotional and stress-related autonomic regulation ( Gibbons, 2019 ). Brain areas involved in autonomic cardiovascular control include thalami, insulae, amygdalae, cingulate cortex, hippocampus, the right angular and bilateral supramarginal gyri, the hypothalamus, midbrain and brainstem. It has been shown several times that very differently located focal brain lesions such as strokes can lead to disturbances in cardiac autonomic function, i.e. altered sympathetic and parasympathetic responses ( Akil et al., 2015 , Al-Qudah et al., Oct 2015 , Jimenez-Ruiz et al., May 2021 , Mo et al., Feb 2019 , Xiong et al., Jan 2018 ), sometimes leading to arrhythmia or cardiac failure. Such disturbances can be quantified by assessing the heart rate variability (HRV) ( Akil et al., 2015 , Ha et al., Jul 2018 , Hilz and Dutsch, Jan 2006 ), which was reported to be reduced by acute strokes ( Korpelainen et al., Nov, 1996 ). HRV after stroke can be determined during normal breathing by time-domain parameters such as the coefficient of variation (VC) and the root mean square difference of successive differences (RMSSD) of R-R intervals, or by parameters in the frequency-domain such as the spectral power of low (LF, 0.04–0.14 Hz) and high (HF, 0.15–0.50 Hz) frequency bands of trigonometric regressive spectral analyses. Theoretically, parameters in the frequency domain permit conclusions about the influences of the sympathetic and parasympathetic nervous systems on HRV. Changes in the HF band are thought to represent mainly parasympathetic influences and correlate with the parameters in the time domain, whereas the LF band represents both sympathetic and parasympathetic influences on HRV ( McCraty and Shaffer,Jan, 2015 ). There seems to be a right hemispheric dominance in HRV control. Recent lesion studies describe HRV alteration in the time domain more often in relation to damage to right versus left cortical and subcortical brain regions despite similar clinical outcomes ( Raphaely-Beer et al., 2020 ). This recent study also demonstrated that different parameters of HRV measurement were associated with different brain damage in voxel-based lesion symptom mappings. However, the mechanisms how the very different focal brain lesions can induce changes of HRV are still unknown. Fundamental work has shown that the control which the brain exerts on heart rate variability in healthy subjects can only be understood if network-based statistics were applied simultaneously to datasets of gray-matter morphometric, white-matter tractographic and functional connectivity networks ( Ruffle et al., Oct, 2021 ). We therefore hypothesize that not the single brain lesion determines HRV after stroke but the effect of that brain lesion on brain networks. In the present study we chose an approach which first determines which brain lesions have an influence on HRV in parallel independent component analyses (ICA). In a second step we sought to investigate whether these ICA derived lesions could be connected to common functional brain networks, which were assessed in age-matched healthy subjects ( Damoiseaux, 2017 ). We have chosen to use an approach with seven functional networks ( Schaefer et al., 2018 ). If our hypothesis is true, we expect, that the ICA lesion pattern, which is correlated to HRV, affects these brain networks differently than lesion patterns without affecting HRV.

Materials and methods Subjects and study design Stroke patients Patients with acute first-ever ischemic stroke at any cortical localization (n = 42; 16 women; mean age 65.7 ± 13.1 y; 2–7 days post-stroke) were recruited from the Department of Neurology, University Medical Center Mainz (Mainz, Germany) as part of a single-center project funded by the German Research Foundation (Deutsche Forschungsgemeinschaft (DFG)). Exclusion criteria for all patients were previous strokes or other lesions of the central nervous system, missing ability to provide informed consent or pre-existing cardiac arrhythmia precluding HRV analysis. Patients underwent standardized neurological examination and assessment of HRV. Patients' post-stroke National Institute of Health Stroke Scale score (NIHSS, max. 42 points) and the actual antihypertensive medication were recorded. Healthy controls for behavioral data Healthy controls (n = 20; 10 women; mean age 60.7 ± 10.3 y) were enrolled by meeting the following criteria: i) age > 50 years; ii) no chronic medical condition; iii) no intake of drugs for at least one week prior to examination except contraceptives, vitamins, and thyroid hormone-substitution; iv) no current or past neurologic or psychiatric disease. Healthy controls had no antihypertensive medication and no diseases known to influence HRV. Standard protocol approvals and patient consents The study followed the Declaration of Helsinki and was approved by the Ethics Committees of the Rhineland Palatinate Medical Association (No. 837.032.17 (10866)), Germany. Informed written consent was obtained from patients and healthy controls. Data acquisition Heart rate variability (HRV) HRV at rest was recorded during 5 min with standard electrocardiogram (ECG) electrodes (FAN, Schwarzer, Germany) attached to the extremities ( Haegele-Link et al., 2008 ). The patients sat in a reclining position with their limbs resting at heart level and breathed in their individual rhythmus. Ectopic heat beats were cleaned-up automatically by the software and manually after inspection, if necessary. As time domain parameters, the VC and RMSSD were calculated. As frequency domain parameters, the low (LF, 0.04–0.14 Hz) and high (HF, 0.15–0.50 Hz) frequency bands of R-R intervals (RRI) were standardly analyzed by Fast Fourier transform-based approach (FFT). The magnitude of LF and HF oscillations was determined as the integral under the power spectral density curves of RRI (ms 2 /Hz) for the LF and HF frequency bands, and was expressed as LF and HF powers of RRI (ms 2 ) ( Hilz and Dutsch,Jan, 2006 ). Structural MRI of patients MRI scans were acquired 2–7 days after stroke onset as part of a clinical routine examination. Scanning was performed either on a 3 Tesla Magnetom Skyra or a 1.5 Tesla Magnetom Sola (Siemens Healthineers, Erlangen, Germany) with a phased array head/neck coil. High-resolution T1-weighted anatomical scans (repetition time (TR) = 2.25 s; echo time (TE) = 3.83 ms; flip angle = 9°; 144 slices per slab; 1 mm 3 isotropic voxel size) were obtained to improve the spatial normalization of the lesion-positions onto the Montreal Neurological Institute (MNI) brain template. The stroke lesions were marked on diffusion-weighted sequences of routine structural MRI scans using MRIcroN ( Rorden et al., Jul, 2007 ) and exported in an SPM-readable format. The lesion volumes were co-registered together with the diffusion-weighted images to the volume-dataset using SPM 12 (The Welcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK), which is designed to work with MATLAB (The MathWorks, Inc.). Both the MRI scan and the lesion shape were mapped into stereotaxic space using the normalization algorithm of SPM12. This normalization effectively aligns the shape and size of each individual’s brain lesion to the same stereotaxic spacing ( Baier and zu Eulenburg, 2014 ). Resting-state functional MRI (rs-fMRI) of age-matched healthy controls RS-fMRI data of age stratified healthy controls (n = 50; 27 women; mean age 68.9 ± 4.7 y) from the AgeGain Study Group were used for functional connectivity analyses. Subjects were scanned using a 3 T-MRI scanner, TrioTim Magneton (Siemens Medical Systems, Erlangen, Germany). Anatomical scans were captured using a T1-weighted Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequence with the following parameters: sagittal slices = 176, scan time = 4.18 min, repetition time (TR) = 1900 ms, echo time (TE) = 2.52 ms, flip angle = 9°, field of view (FOV) = 250 mm, and voxel volumes = 1.0 × 1.0 × 1.0 mm. During the resting-state functional MRI (rs-fMRI) examination, participants were instructed to keep their eyes closed without thinking of anything in particular or falling asleep. T2-weighted scans were captured with the following parameters: Echo planar imaging (EPI) multiband sequence scan time = 11.02 min, transversal slices = 60, slice thickness = 2.5 mm, TR = 1000 ms, TE = 29.0 ms, flip angle = 56°, and FOV = 210 mm, multiband acceleration factor = 4. The 50 rs-fMRIs were pre-processed by the program Data Processing Assistant for Resting-State fMRI (DPARSFA ( Chao-Gan and Yu-Feng, 2010 ) implemented in MATLAB (MATLAB, 2016). After the removal of the first six images, we applied a series of steps including slice timing correction and realignment to eliminate the influence of head motion. All scans were checked for excessive head motion; participants did not show head motion more than 3 mm. The realigned images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF), spatially normalized to MNI space using Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL ( Ashburner, 2007 ), and resampled to 3 × 3 × 3 mm voxels. To reduce the influence of noise, we regressed out linear trend, 12 motion parameters, WM, CSF, and global signal as nuisance regressors. Later, the functional images were filtered with a bandpass filter between 0.1 and 0.01 Hz and smoothed with a 6-mm Gaussian kernel. Data analysis Behavioral data Behavioral data were analyzed using the SPSS software package (version 19 for Windows; IBM SPSS Inc., Chicago, USA). Statistical significance was defined at an alpha level of < 0.05. Group differences (patients vs. controls) were tested for age and HRV parameters by single one-way analysis of variance (ANOVA); for distribution of sex by cross-tabulation statistics. Right versus left hemisphere stroke patients, independent of lesion location, were compared regarding HRV parameters using one-way ANOVA. Some patients were regularly medicated by beta blocker (n = 2) or a combination of beta blocker and other antihypertensive drugs (n = 11), or by antihypertensive drugs excluding beta blocker (n = 19). The remaining 10 patients were not treated with antihypertensive drugs. Differences in each HRV parameter between the patient groups with and without antihypertensive medication, and healthy controls were analyzed by one-way ANOVAs (post-hoc group comparisons based on LSD estimation). The measures of heart rate variability are strictly age dependent. For creating a homogeneous data space, scores of VC, RMSSD, LF and HF bands were z-transformed based on the mean and standard deviation of the scores of the age-matched healthy subjects. Z-values of < -1, indicating 1 standard deviation lower than the mean of healthy controls, were considered “abnormal”. We only considered reduction of HRV of abnormal because there is no upper limit for HRV. The quantification of z-scores showed the highest frequency of impairment in the VC and in the LF bands. Therefore, subsequent lesion pattern and network analyses contrast patients having reduction of VC or LF band versus all other patients. Identification of lesion patterns by parallel independent component analysis (ICA) Independent component analysis (ICA) allows data-driven identification of hidden non-correlating components that underlie sets of measurements. The parallel ICA algorithm implemented in the fusion ICA toolbox ( Calhoun et al., Jan, 2006 ) was used to discover independent components (lesion patterns) from two inputs, here, namely the VC and LF values for each patient is the first input, and the lesion volumes (with actual spatial patterns without binarizing) derived from the MRI of the same patient is the second input. Two separate parallel ICAs were performed for the z-transformed continuous measures of VC and LF band as these parameters showed abnormal changes compared to the healthy controls. ICA optimization was based on the Infomax algorithm ( Anemüller et al., Nov, 2003 ), which maximizes the mutual entropy to enhance the independence between the components for the two inputs. Finally, to avoid overfitting because of too many estimated parameters, the learning rate of the correlation term is adaptively adjusted ( Liu et al., Jan, 2009 ). To determine the correct number of independent components, a modified version of the Akaike information criterion proposed by Li et al. ( Li et al., Nov, 2007 ) was applied. The components from each modality were selected to be the correlations with the highest significance. First, we used the Akaike information criterion to estimate the number of components and then to reduce the component number to reach a consistent level among the different test runs. The most frequently lesioned brain areas from the obtained lesion pattern were estimated using FSL (version 6.0.1) ( Woolrich et al., Mar 2009 , Smith et al., 2004 , Jenkinson et al., 2012 ). First, lesion volume maps from each patient thresholded at t-value > 3 were combined (using fslmaths command ) to form a single lesion map for the whole group. This obtained image was then masked (using fslmaths command ) by overlaying three different atlases (John Hopkins University white matter atlas ( Wakana et al., 2007 , Hua et al., 2008 , Mori et al., 2015 ), Harvard Oxford cortical and subcortical atlas ( Makris et al., Apr 2006 , Frazier et al., Jul 2005 , Desikan et al., 2006 , Goldstein et al., 2007 ) to obtain the volume (using fslstats command ) at each region of interest (ROI). Lesion areas with cluster sizes greater than 10 voxels were estimated. The percentage overlay was obtained by taking the ratio of the lesion volume at a ROI to the total lesion volume. Directed connectivity analysis using time resolved partial directed coherence For directed connectivity analysis, the lesion pattern for VC and LF, which were identified by the ICA, were seeded into the rs-fMRIs of healthy subjects (cohort of the German Age Gain Study Group described above). Connectivity analyses were performed for the patient groups with and without reduced HRV separately. The Schaefer connectivity atlas ( Schaefer et al., 2017 ), which parcellates the brain into seven networks (visual, somatomotor, dorsal attention, salience ventral attention, control, limbic and default network), was used for defining the target networks for connectivity estimation. The time series was extracted from the active voxels of the lesion pattern to form a pooled time series and estimate the connectivity between this seed region and the seven networks using time resolved partial directed coherence (TPDC). TPDC allows focusing on the temporal dynamics of the signal and analyze the directed connectivity at a specific frequency ( Anwar et al., 2013 ). It adopts the dual­extended Kalman filter (DEKF) ( Wan and Nelson, 2001 ) to estimate time­dependent autoregressive coefficients. In brief, DEKF in the TPDC is a predictor-­corrector algorithm that estimates the state of a process, i.e. functional connection. At each time point, one extended Kalman filter estimates the state and shares it with the other, the second one estimates the model parameters and feeds back to the first. By using two extended Kalman filters in parallel, we can estimate both state and model parameters of the system at each observed data point in the time series. Subsequently, using the Fourier transform of the estimated time­dependent multivariate autoregressive (MVAR) coefficients, partial directed coherence (PDC) can be calculated, as described in ( Baccalá and Sameshima,Jun, 2001 ). Prior to fitting any model to observed data, it is necessary to estimate the optimum number of model parameters. Choosing too few parameters may miss the true system dynamics, however, applying a higher model order than necessary may cause spurious results. Hence the best trade-off between model accuracy and number of parameters must be met. The model order to estimate the MVAR coefficients was fixed for all subjects to be 5. In order not to overestimate we checked the model order with the Akaike information criterion (AIC). Akaike improved his definition of FPE by introducing the minimization of the Kullback-Leibler information entropy, which is the distance between the fitted model and true data set ( Liddle, 2007 ). The best model is the one which gives minimum AIC value ( Akaike, 1974 ). After squaring the partial directed coherence (PDC) value, the normalized value falls between 0 and 1. By calculating PDC with estimated MVAR coefficients at each time point, the connectivity matrices corresponding to the time series were obtained. In the rs-fMRI dataset of the healthy subjects, we extracted frequency band of interest from 0.009 to 0.08 Hz and averaged the outcome across each time point to obtain robust connectivity values between brain regions. ( Anwar et al., 2016 ) The choice of this frequency range is based on several factors. Firstly, it is known that neuronal activity in the brain exhibits low-frequency oscillations (<0.1 Hz) and believed to reflect functional networks that are active in that region during task performance ( Greicius et al., 2004 , Biswal et al., Sep 2010 ). Secondly, the BOLD signal is relatively slow, with changes occurring over several seconds, which is believed to be related to underlying neuronal activity and functional connectivity in the brain ( Fox and Raichle,Sep, 2007 ). The low-frequency range (0.009–0.08 Hz) has been used in numerous fMRI studies to investigate functional connectivity in the human brain ( Fox and Raichle, Sep 2007 , Ding et al., 2022 ). After estimating the TPDC values, the significance level was calculated from the applied data using a bootstrapping method ( Kamiński et al., Aug, 2001 ). In short, we divided the original time series into smaller non-overlapping windows and randomly shuffled the order of these windows to create a new time series. The TPDC value is calculated based on a randomly shuffled time series for 1,000 times and the 99th percentile of the connectivity value was taken as the significance threshold. This process is performed separately for each subject. The resulting value was the significance threshold value for all connections. The open source MATLAB package autoregressive fit (ARFIT) ( Neumaier and Schneider, 2001 , Schneider and Neumaier, 2001 ) was used for estimating the autoregressive coefficients from the filtered signals. We applied the time reversal technique ( Kamiński et al., Aug 2001 , Haufe et al., 2013 ) as a second significance test on the connections already identified by TPDC using data-driven bootstrapping surrogate significance test. In addition, we have added the surrogate data based on the method for amplitude adjusted Fourier transform (AAFT) algorithm to generate the surrogate data as shown in the supplementary Fig. 1 (in black) ( Theiler et al., 1992 ). We estimated 1000 realizations of this new method and estimated the significance threshold with the 99th percentile which was the values with the range of TPDC (0.08–0.095) indicating the threshold initially used was 0.1 appropriate for defining the significant connections in this study. Medication status of patients (i.e. “hypertensive medication with beta blocker”, “other hypertensive medication” and “no medication”) was included as covariate in the connectivity analyses. Validation of connectivity using support vector regressor (SVR) prediction analyses For validation of the effectiveness of the connectivity values, we further applied support vector machine (SVM) analysis to predict the LF and VC scores used in the criteria for the patient group with abnormal changes and the group without. We performed a support vector regressor (SVR) analysis—a machine-learning-based multiple-regression method—that could associate the observed and trained values and determine the prediction accuracy ( Drucker et al., 1996 ). Here, we used the polynomial function kernel for this projection due to its good performance as discussed in ( Cortes and Vapnik ) and use the grid search (min = 1; max = 10) to find the few optimal input parameters and gamma (0.25). The selection was checked by taking 75 % of the data for training and 25 % for testing. To obtain the threshold for prediction accuracy, we devised an approach based on the statistical inference obtained from the Bayesian credible interval ( Curran, 2005 ). The 75 % threshold could differentiate the posterior distribution from the 95 % Bayesian credible interval (indicating the inclusion of 95 % of the data points). Here, the posterior distribution and the credible interval were obtained considering all connectivity values from all subjects from the group with abnormal values and the remaining patients and the highest density interval containing 95 % (range: 0.15–0.64) of the distribution. Hence, the prediction accuracy of the above (75 %) obtained after 10-fold cross-validation was considered a significant result.

Results Clinical characteristics of stroke patients Patient demographic characteristics, stroke location and size, and medical history are displayed in Table 1 . Mean lesion volume was 11.23 ml, range 0.14–97.5 ml. The National Institutes of Health Stroke Scale (NIHSS) mean score after acute medical/surgical intervention was 3.0 (range 0–10 points). Patients had hypertension in 74 %, hyperlipidemia in 29 %, diabetes mellitus in 31 % and were obese in 26 %; 36 % had a history of nicotine abuse relevant for the stroke. A clear separation of the sample could be made regarding antihypertensive drugs: n = 13 patients had a combination therapy including beta blockers, n = 19 without beta blockers; n = 10 patients did not take antihypertensive medication at the time of investigation. For all HRV parameters, no difference in scores was found between right (n = 26) and left hemispheric strokes (n = 16) (ANOVA: F(1,0) = [0.0–0.68], p > 0.41). No differences were found also for age (ANOVA: F (1,0) = 2.39, p = 0.13) and the distribution of sexes (χ = 0.79, p = 0.38) between the patients and healthy controls. Differences in resting HRV parameters in stroke patients versus healthy controls HRV of patients was lower than of healthy controls (ANOVA: F (1,0) = [5.20–10.64, p < 0.026). ( Supplementary Fig. 2 ). Patients were classified regarding hypertensive medication into the groups “beta blocker”, “other hypertensive medication” and “no medication” because of the potential effect of this medication on HRV. The patient groups were contrasted to the healthy controls. There was a main effect of group on VC (ANOVA: F(3,0) = 3.40, p = 0.024) and LF (F(3,0) = 3,87, p = 0.014), but not on RMSSD (F(3,0) = 2.58, p = 0.062) or HF (F(3,0) = 2.43, p = 0.074). Post-hoc comparisons are displayed for VC und LF in Supplementary table 1; all parameters including VC and LF did not differ between the medication-related patient groups. On a descriptive level, the patient group without medication displayed the lowest scores in VC and LF, further making a significant effect of beta blocker medication on HRV unlikely in the present investigation. Abnormal changes in resting HRV in stroke patients Fig. 1 shows the results of the z-values of the HRV parameters. The highest frequency of patients with abnormal impairment (z-score < -1) was found for LF (n = 21) and VC (n = 16). From the patients with abnormal LF, 13 patients displayed also abnormal scores in VC. For imaging analyses, the LF and VC groups with values < -1 were contrasted to the patients with values > -1. Brain lesion pattern associated with LF and VC The lesion distribution and the z-scores of LF and VC from all patients were included as two inputs into two separate parallel ICAs. The ICAs revealed for both VC and LF two very spatially similar and significantly covarying components (VC: r = 0.64, p < 0.001; LF: r = 0.61, p < 0.001). The brain lesion pattern comprised predominantly lesions in the right hemisphere ( Fig. 2 A-B). Table 2 shows the cortical, subcortical and white matter projections lesion areas with most frequent overlay, among those thresholded at t-value > 3 and that have cluster sizes greater than 10 voxels. Seed-based functional connectivity analyses Low frequency bands (LF) For the group with abnormal LF-scores (z-score < -1), the brain regions, which correspond to the ICA lesion pattern in these patients, have an influence on the limbic (LIMB, 0.55 ± 0.08) and salience ventral attention networks (SAL-VENT-ATTN; 0.61 ± 0.10) which was stronger than on the other five networks. This influence was reconfirmed by calculating the backward connections from these networks to the lesion pattern ( Fig. 3 A). In the group without abnormal changes in LF (z-score < -1), the strongest influences could be shown from the ICA lesion pattern to the control network (CONT; 0.54 ± 0.12) and the default mode network (DMN; 0.56 ± 0.09), which again was reconfirmed by backward connection calculation ( Fig. 3 B). The connectivity between brain regions corresponding to the ICA lesion patters and the resting state networks (both forward and backward connections) was different between the groups with and without pathological LF in LIMB, CONT, SAL-VENT-ATTN and DMN (p < 0.001, Fig. 4 ). Additionally, using SVM, the prediction of connectivity values for the group with abnormal LF changes reached significant accuracy (more than 75 %). The testing and overall accuracy was above 80 % for the 10-fold cross validation ( Supplementary Fig. 3 ). Variation coefficient (VC) No different impacts of the ICA lesion pattern could be determined between the groups with and without pathological VC scores (0.08 ± 0.09, p > 0.05, Fig. 5 A-B). Throughout, the association of these regions with the seven different networks and from the networks back to the lesions was weak ( Fig. 6 ).

Discussion Acute brain lesions might cause significant disturbances of cardiac autonomic function that eventually lead to increased mortality and poor functional outcome ( Lees et al., 2018 ). Given the robustness of the autonomic control of heart rate, which is necessary for survival, and the multitude of brain areas that are related to this autonomic control ( Ruffle et al., Oct, 2021 ), the mechanism explaining how single focal brain lesions could lead to HRV alterations remained obscure. We addressed this question and found that acute brain lesions, which are related to LF power, in particular in the right hemisphere might have effects on resting state cortical networks ( Yeo et al., Sep, 2011 ). This could one mechanism to explain how focal brain lesions influence global bodily function. HRV after stroke The present results indicate abnormally reduced cardiac autonomic regulation after acute stroke, with the most significant reductions in the LF (frequency domain) and the VC (time domain), quantified by HRV at rest. The results suggest that acute stroke affects both the sympathetic tone but also vasovagal activity. Although there are studies showing reduced HRV during different provocation tests like deep breathing or standing up ( Xiong et al., Dec, 2013 ) we opted to test HRV at rest because sensorimotor deficits acutely after stroke could interfere with the performance of such tests introducing selection bias and sources of variability. The present investigation is unique in that we controlled for antihypertensive medication including beta blockers. In LF, which represents both sympathetic and parasympathetic influences on heart rate variability, more patients showed abnormally low values than in VC, which mainly represents parasympathetic influences. Previous results indicate that strokes of similar size to those included in the present study regularly affect function parameters representing both sympathetic and parasympathetic factors but less robustly impact parameters indicating influence of only one branch of the ANS ( Xiong et al., 2014 ). Therefore, similar but also different results were reported before ( Chen et al., Mar 2013 , Zawadka-Kunikowska et al., Aug 2018 ). Decreased LF and HF bands in stroke were shown in a small sample of mainly medullary strokes ( Meglic et al., 2001 ). Another study reported unchanged LF bands in acute middle cerebral artery stroke but found changes in the very low frequency band (VLF) ( Giubilei et al., 1998 ). Changes in the VLF were reported to be risk factors for post-stroke infections for unknown reasons ( Bramer et al., Dec, 2019 ). The VLF (range < 0.04 Hz) is influenced by sympathetic and parasympathetic branches similar to the LF ( Usui and Nishida, 2017 , Baharav et al., Jun 1995 ). Lesions and pathological HRV Stroke lesions associated with LF and VC from all patients formed the same lesion pattern, mainly in the right hemisphere. Although there are reports about a right hemispheric dominance in cardiovascular control ( Tokgozoglu et al., Jul 1999 , Brunetti et al., Jun 2019 ) and older studies proposed a right hemispheric lateralization of autonomic control ( Meyer et al., 2004 ), this claim has been challenged by more recent data ( Jaremek et al., 2019 , Sposato et al., 2020 ). Honestly, our results could be affected by the low number of patients suffering left hemispheric stroke in our sample due to sampling bias (exclusion of aphasic patients). That both LF and VC were associated with lesions in mainly the same brain regions could have been expected because of a significant correlation between LF and VC and because in healthy subjects an analysis of gray or white matter co-varying with both HRV parameters revealed grossly the same regions. Only network-based statistics separated parasympathetic from sympathetic HRV parameters ( Ruffle et al., Oct, 2021 ). Brain regions associated with variance of LF or VC in the present study comprised the temporo-parieto-occipital region, basal ganglia and thalamus, and their interconnections, which include the corona radiata, the (posterior limb of the) internal capsule and the superior longitudinal fasciculus. Previous investigations described different and similar localizations of stroke being associated with reduced HRV spanning from lesions in the frontal lobe, the middle cerebral artery territory ( Tokgozoglu et al., Jul, 1999 ) including basal ganglia ( Raphaely-Beer et al., 2020 ) to the occipital cortex ( Wang et al., Sep, 2022 ). Functional connectivity to seven networks Our data so far indicates that there is not a circumscriptive cortex area or white matter tract that controls the autonomic outflow from the brain hemispheres. It rather supports the assumption that HRV must be controlled by networks, which could be affected by different stroke locations. The dysregulation of these networks may cause known cardiovascular complications after stroke, i.e. myocardial injury, myocardial infarction, heart failure, arrhythmias and sudden cardiac death ( Sposato et al., 2020 ). This is why we analyzed the connection of the resulting ICA lesion pattern on seven predefined functional brain functional networks, which were assessed in age-matched healthy subjects. Matching for age is most important because functional brain networks change with age even if subjects are clinically healthy ( Damoiseaux, 2017 ). We chose to use these seven functional networks ( Schaefer et al., 2018 ) for three main reasons. First, the most well-known and robust rs-fMRI parcellation, which uses global similarity approach, clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals ( Schaefer et al., 2018 ). Second, the atlas is based on 1489 participants and is in concordance with other atlas areas that were defined using histology and visuotopic fMRI. Third, to investigate the global network influence of the stroke lesions patterns, the parcellations were clustered into seven networks using a similar procedure to ( Yeo et al., Sep, 2011 ). In addition, there have been previous studies using this parcellation especially to look at stroke lesion affected networks in the brain ( Idesis et al., 2022 , Allegra et al., 2021 ). We found differences of the impact of the ICA lesion patterns on the 7 networks when contrasting patients with reduced LF versus those with normal LF. We did not find any difference when contrasting patients with reduced and normal VC. In patients with reduced LF, the interaction between lesions and both the LIMB and the SAL-VENT-ATTN was strongest, while in patients with LF in the normal range interactions with the DMN and CONT were predominating. We should not lay too much emphasis on interpreting the clinical consequences of these findings but the differences between both groups are so obvious that the findings support our hypothesis that it is not the lesion but the impact of a lesion on preexisting networks which might cause autonomic disturbances after acute brain damage.

Conclusion In conclusion, our results indicate that an interaction of brain lesions with existing resting state brain networks predicts the impairment of HRV after stroke, rather than the brain lesion itself.

These authors contributed equally to this work. Highlights • Acute cerebral stroke leads to abnormal reductions in low frequency bands of HRV. • Associated lesions location in the right temporo-parieto-occipital cortex, basal ganglia, thalamus, and interconnections. • Acute brain lesions related to abnormal HRV impact resting state cortical networks. • Abnormal low frequency bands associate with the limbic and the salient ventral attention network. Acute strokes can affect heart rate variability (HRV), the mechanisms how are not well understood. We included 42 acute stroke patients (2–7 days after ischemic stroke, mean age 66 years, 16 women). For analysis of HRV, 20 matched controls (mean age 60.7, 10 women) were recruited. HRV was assessed at rest, in a supine position and individual breathing rhythmus for 5 min. The coefficient of variation (VC), the root mean square of successive differences (RMSSD), the powers of low (LF, 0.04–0.14 Hz) and high (HF, 0.15–0.50 Hz) frequency bands were extracted. HRV parameters were z-transformed related to age- and sex-matched normal subjects. Z-values < -1 indicate reduced HRV. Acute stroke lesions were marked on diffusion-weighted images employing MRIcroN and co-registered to a T1-weighted structural volume-dataset. Using independent component analysis (ICA), stroke lesions were related to HRV. Subsequently, we used the ICA-derived lesion pattern as a seed and estimated the connectivity between these brain regions and seven common functional networks, which were obtained from 50 age-matched healthy subjects (mean age 68.9, 27 women). Especially, LF and VC were frequently reduced in patients. ICA revealed one covarying lesion pattern for LF and one similar for VC, predominantly affecting the right hemisphere. Activity in brain areas corresponding to these lesions mainly impact on limbic (r = 0.55 ± 0.08) and salience ventral attention networks (0.61 ± 0.10) in the group with reduced LF power (z-score < -1), but on control and default mode networks in the group with physiological LF power (z-score > -1). No different connectivity could be found for the respective VC groups. Our results suggest that HRV alteration after acute stroke might be due to affecting resting-state brain networks. Keywords

Limitations We acknowledge that our study has limitations: 1) The right hemispheric dominance of the lesions in our sample could be affected by sampling bias. Acute left-sided strokes often suffer from aphasia precluding participation in scientific studies. 2) We do not have an explanation for reduced VC in our patients other than there is no direct relation to brain function. 3) We performed a short HRV recording at rest, mainly for clinical reasoning, since patients were recruited from our intensive stroke unit and could be mobilized for limited time. 4) The controls for HRV and rsMRI were different. Although it would be advantageous to derive both measures from the same subjects and thereby to reduce variability, we regard our approach with highly significant interaction despite separate datasets as an argument for the robustness of the findings. 5) Several whole brain functional connectivity atlases exist, e.g. by Shen and colleagues (2013) from 79 healthy normal volunteers ( Shen et al., 2013 ) or by Glaser and colleagues (2016) based on the human connectome project curated with 210 young healthy subjects ( Glasser et al., 2016 ), the selection of which could alter the analysis due to different resolution of the atlases. We used the Schaefer and colleagues (2018) atlas due to three reasons: Firstly, they used a gradient-weighted Markov Random Field (gwMRF) model integrating local gradient and global similarity approaches ( Schaefer et al., 2018 ). Secondly, the atlas was derived using task-fMRI and rs-fMRI across diverse acquisition protocols, and they validated the gwMRF parcellations to be more homogeneous than four previously published parcellations. Thirdly, they were also able to validate them with the boundaries of certain cortical areas defined using histology and visuotopic fMRI. Finally, our findings may be correlative rather than causative for HRV alteration. Disclosure statement Dr. Welte-Jzyk reports no disclosures. Dr. Dimova reports no disclosures. Dr. Kronfeld reports no disclosures. Dr. Korczynski reports no disclosures. Dr. Koirala reports no disclosures. Dr. Steenken reports no disclosures. Dr. Kollmann reports no disclosures. Dr. Tüscher reports no disclosures. Dr. Brockman has received speakers’ fees and consulting honoraria from Stryker, Germany, all unrelated to the present work. Dr. Birklein has received speakers’ fees and consulting honoraria from Pfizer, Germany, and Alnylam, Europe, all unrelated to the present work. Dr. Muthuraman reports no disclosures. Funding The work was supported by the Deutsche Forschungsgemeinschaft (DFG, grant numbers Bi579/11–1 to FB, BA4097/3–1 to BB and MU4354/1–1 to MM). The funders had no role in method design, data selection and analysis, decision to publish, or preparation of the manuscript. CRediT authorship contribution statement Violeta Dimova: Writing – review & editing, Writing – original draft, Visualization, Methodology, Formal analysis, Data curation, Conceptualization. Claudia Welte-Jzyk: Writing – original draft, Formal analysis, Data curation. Andrea Kronfeld: Writing – review & editing, Visualization, Formal analysis, Data curation. Oliver Korczynski: Writing – review & editing, Visualization, Methodology, Formal analysis. Bernhard Baier: Writing – original draft, Visualization, Funding acquisition, Formal analysis, Conceptualization. Nabin Koirala: Writing – review & editing, Visualization, Methodology, Formal analysis. Livia Steenken: Writing – review & editing, Formal analysis, Data curation. Bianca Kollmann: Writing – review & editing, Methodology, Data curation. Oliver Tüscher: Writing – review & editing, Visualization, Methodology, Formal analysis. Marc A. Brockmann: Writing – review & editing, Visualization, Data curation. Frank Birklein: Writing – review & editing, Writing – original draft, Funding acquisition, Formal analysis, Data curation, Conceptualization. Muthuraman Muthuraman: . Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary data The following are the Supplementary data to this article: Data availability Data will be made available on request. Acknowledgment The authors thank Dr. Cheryl Ernest for proofreading and editing the manuscript.

CC BY

no

2024-01-16 23:43:44

Neuroimage Clin. 2023 Dec 19; 41:103558

oa_package/bd/69/PMC10788522.tar.gz

PMC10788524

38226210

Introduction background Gastrointestinal (GI) cancer is one of foremost cancer-related public health problem worldwide with greatly characterized by poor prognosis. . GI cancers account for approximately 5 million new cases of cancers and 3 million deaths worldwide in 2020. The highest liver, esophageal, and gastric cancer rates are reported in Asia, while pancreatic and colorectal cancers were more prevalent in Europe in 2020 [ 1 ] . The incidences of liver, pancreatic, and colorectal cancers are increasing in most countries [ 2 , 3 ] . Identifying novel, sensitive and specific cancer biomarkers for early diagnosis and estimating the prognosis of gastrointestinal cancers have developed particularly owned by more detailed discovery of cancer underlying molecular signaling pathways. Dysregulation of various signaling pathways and corresponding molecular mechanisms driven by numerous transformed and altered oncogenes and tumor suppressors have been described to be involved in GI development and progression [ 4 , 5 ] . Also, epigenetic alterations and dysregulation of DNA repair genes have been frequently involved in GI cancers. In addition to well-known signaling pathways, increasing evidences have demonstrated that non-coding RNAs, including long non-coding RNAs (lncRNAs) also play a fundamental regulatory role in the development and progression of GI cancers. LncRNAs have been confirmed to involve in GI cancers through interactions with numerous biological molecules. Moreover, these molecules may be served as potential molecular diagnostic and prognostic biomarkers as well as targets for GI cancers [ 4 , 5 ] Table 1 . The Hippo signaling pathway, as a well-recognized conserved signaling pathway, has been characterized to control tissue growth and organ size in physiological development, regeneration, and pathological conditions, including cancer. Initially, it was identified in Drosophila [ 6 , 7 ], but determining its conservation in mammals led to valuable discoveries of its role in cancer pathogenesis [ 8 ]. Accumulating evidences have emphasized the significance of Hippo signaling pathway in GI tissue homeostasis, while its aberration may be involved in GI cancer development and progression. A number of studies have revealed the biological role of Hippo pathway in GI cancer-related signaling pathways. In this regard, the Hippo signaling pathway effectors may interplay with common cancer signaling pathways to promote tumorigenesis [ 8 ]. Here, we review the biological role of this signaling pathway and its crosstalk with lncRNAs and highlight the molecular mechanisms and clinical significance of the crosstalking in the development of GI cancers. Hippo signaling pathway; cell proliferation and tumorigenesis The Hippo signaling pathway was first described as an imperative and conserved regulatory pathway in cell developmental processes, including organ size, tissue homeostasis, cell proliferation and apoptosis [ 6 , 7 ]. The central axis of Hippo signaling pathway consists of various proteins, including mammalian STE20-like protein kinase 1 and 2 (MST1 and MST2) and large tumor suppressor 1 and 2 (LATS1 and LATS2) that promote Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ) phosphorylation and accumulation in the cytoplasm [ 6 , 7 ] . YAP/TAZ may be affected by phosphorylation at different sites by upstream kinases, inducing the expression of target genes via binding to transcriptional enhanced associate domain (TEAD) protein family. In this manner, this signaling may involve in a variety of cellular processes, including cell growth, differentiation and proliferation. Therefore, YAP and TAZ phosphorylation inhibits their tumorigenic potential and regulation of TEAD and SMAD transcription factors [ 9 ] . When Hippo pathway is activated by stimuli, MST1/2 kinase is phosphorylated and subsequently phosphorylates MST1/2. Then, phosphorylated MST1/2 kinase induces phosphorylation of salvador homolog 1 (SAV1) to form a heterotetramer to more increase the LATS1/2 phosphorylation [ 6 , 7 ] . Activated LATS1/2 causes inactivation or degradation of YAP/TAZ through ubiquitination, and thus inhibits the transcription of downstream genes. In other words, when the Hippo pathway is inactivated, translocation of YAP/TAZ to the nucleus and binding to enhancer elements result in transcription of target genes [ 6 , 7 ] . The interaction between Hippo signaling pathway and vital target genes plays an imperative role in the regulation of various biological processes of vertebrate cells. An increasing number of studies have highlighted a critical role of Hippo pathway in the regulation of cell proliferation, apoptosis, and metastasis [ 6 , 7 ] . long non-coding RNAs (lncRNAs): mechanisms and biological functions in cancer development and progression LncRNAs are defined as RNA molecules longer than 200 nucleotides that modulate gene expressions at different levels, including transcriptional and post-transcriptional levels [ 10 ] . They can directly regulate gene transcription and recruit transcription factors or interact with mRNAs and proteins [ 11 , 12 ] . Several lncRNAs function as competing endogenous RNAs (ceRNAs), whose regulation of mRNAs depends on microRNAs (miRNAs). In other words, lncRNAs can sponge and sequester miRNAs and prevent their regulation of mRNAs [ 13 ] . LncRNAs have also been reported to interact with splicing factors and heterogeneous nuclear ribonucleoprotein (hnRNP) family proteins to regulate mRNA alternative splicing. The action mode of epigenetic regulations by lncRNAs most commonly includes chromatin remodeling or histone modification [ [13] , [14] , [15] ] . Indeed, lncRNAs are involved in regulating histone modifications at the chromatin level. In this regard, lncRNA can function as a framework that complex with modification enzymes, thereby regulating histone modifications such as methylation and acetylation. LncRNAs also can regulate DNA methylation by interacting with DNA methyltransferase at the DNA level [ [13] , [14] , [15] ] . Other molecular mechanisms include interaction with the transcriptional effectors to regulate gene expression, direct participation in the post-transcriptional regulation of mRNAs, regulation of RNA editing, activation of Dicer complex and induction of non-coding RNA-based regulatory machinery. It has been well documented that lncRNAs play a pivotal functional role in key cellular processes including, cell proliferation, apoptosis and differentiation. A number of studies have revealed the dysregulation of expression and indicated the biological role of lncRNAs in various cancers initiation and progression [ 13 ] . Cancer-associated lncRNAs are categorized as oncogenic and tumor-suppressive lncRNAs based on their roles in tumor cell proliferation, invasion, epithelial-mesenchymal transition (EMT), cancer stem cell (CSC) maintenance and drug resistance [ [13] , [14] , [15] ]. From a clinical point of view, it has also been shown in several studies that the expression pattern of these molecules change in cancer patients compared to healthy individuals, which point to their clinical values. Because of biological and clinical significance of lncRNAs in cancers, they have been indicated as diagnostic and prognostic biomarkers and provided promising targets for therapeutic strategies [ [13] , [14] , [15] ]. The role of lncRNAs in gastrointestinal cancers The prominent role of lncRNAs in gene expression highlights their potential to act as suppressors or promoters of proliferation, invasion, and metastasis of GI tumors. The cell proliferation, apoptosis, invasion, cell cycle, EMT, CSC and drug resistance may be regulated by lncRNAs in GI tract. The growing evidences from experimental, functional and computational studies indicate that lncRNAs play substantial roles in GI tumorigenesis. Furthermore, aberrant expression of lncRNAs has been reported to be correlated with the clinicopathological parameters, indicating them as a class of auspicious biomarkers in GI cancers [ 13 , 14 ]. As a modulator of various cellular processes involved in GI tumorigenesis, the Hippo pathway could be a target of lncRNAs ( Fig. 1 ). The present study reviews the cross-talk and interaction mechanisms between lncRNAs and the Hippo signaling pathway and highlighted clinical significance in GI cancers ( Fig. 2 ).

Conclusion Hippo signaling pathway is well-known as one of the most imperative pathways that contribute into the regulation of various cellular processes, including cell differentiation, migration and proliferation. Dysregulation of Hippo pathway resulted from aberrant expression of the corresponding molecular effectors may be involved in GI cancer development. Hence, targeting the signaling pathway may provide a potential tool for therapeutic strategy of GI cancers. However, the mechanisms of Hippo pathway regulation by non-coding RNAs in GI cancers is not yet well defined. LncRNAs, as a subclass of ncRNAs, exert numerous cellular functions and their dysregulation has confirmed to play role in carcinogenesis. The pivotal effectors of Hippo signaling, including YAP, TAZ, LATS1/2 and MST1 have been demonstrated to be targeted by lncRNAs. LncRNAs can interplay with Hippo pathway, as a key cancer-associated signaling pathway, to regulate the various cellular processes. The cross-talking between lncRNAs and Hippo signaling pathway involves in GI cancers development and progression. Considering the clinical significance of these lncRNAs, they have also been introduced as potential biomarkers in diagnostic, prognostic and therapeutic strategies in GI cancers. According to mechanisms of lncRNA-mediated regulation of Hippo signaling pathway and clinical significance, these non-coding RNAs may be served as potential targets for gene-based therapeutics in GI cancers. In order to endorse efficient therapeutic strategies for GI cancers by targeting biological axes involving lncRNAs and Hippo pathway, further functional and clinical studies in more details are required.

Co-author. Long non-coding RNAs (lncRNAs) play a significant biological role in the regulation of various cellular processes such as cell proliferation, differentiation, apoptosis and migration. In various malignancies, lncRNAs interplay with some main cancer-associated signaling pathways, including the Hippo signaling pathway to regulate the various cellular processes. It has been revealed that the cross-talking between lncRNAs and Hippo signaling pathway involves in gastrointestinal (GI) cancers development and progression. Considering the clinical significance of these lncRNAs, they have also been introduced as potential biomarkers in diagnostic, prognostic and therapeutic strategies in GI cancers. Herein, we review the mechanisms of lncRNA-mediated regulation of Hippo signaling pathway and focus on the corresponding molecular mechanisms and clinical significance of these non-coding RNAs in GI cancers. Keywords

cross-talk between lncRNAs and the Hippo signaling pathway in gastrointestinal cancers Functional and mechanistic studies have been confirmed that several lncRNAs maigh regulate Hippo signaling pathway through targeting some molecular effectors. Hippo pathway cascades also reciprocally might regulate the lncRNAs synthesis machinery. The molecular crosstalking between lncRNAs and Hippo signaling pathway has been established in various GI cancers. This regulatory mechanism eventually influences GI cancer development and progression, demonstrating a multifaceted biological connection between lncRNAs and Hippo signaling pathway. head and neck squamous cell carcinoma Head and neck squamous cell carcinoma (HNSCC) represents the seventh most common cancer worldwide, with approximately 930,000 new cases in 2020 [ 16 ] . The history of smoking, alcohol drinking, and human papillomavirus infection are proven risk factors for HNSCC [ [17] , [18] , [19] ] . Because of variety of clinical symptoms at the early stages and the lack of an applicable diagnostic biomarker, identification of molecular mechanisms in order to find diagnostic and therapeutic biomarkers is needed . The vast majority of malignancies, which are almost exclusively squamous cell carcinomas (SCCs), originate from of the head and neck that are part of the upper aero digestive tract (UADT). UADT is structured such that it consists of many primary sites, each of which is further split into multiple anatomic sub sites. Some examples of these sub sites are the oropharynx and the nasopharynx which are considered as parts of gastrointestinal tract. The Hippo signaling pathway has been confirmed to involve in HNSCC development and progression. In this regard, the Hippo regulatory role of lncRNAs has been reported in HNSCC tumorigenesis. LncRNA WWTR1-AS1 LncRNA WW domain-containing transcription regulator-1 antisense RNA 1 (WWTR1-AS1) is a natural antisense transcript (NAT). WWTR1-AS1 is significantly overexpressed in 37 HNSCC tissues compared to adjacent normal tissue, and it could promote cell proliferation and invasion in HNSCC cell lines SCC4, SCC9, SCC25, FaDu, and Cal27 . It has also been revealed that the overexpression of both lncRNA WWTR1 and WWTR1 mRNA, as its correspondence with TAZ, are associated with poor outcomes in 37 HNSCC patients. Therefore, lncRNA WWTR1-AS1 possibly corresponds to WWTR1. Moreover, the overexpression of this lncRNA was significantly associated with WWTR-1 expression in the TCGA-HNSCC dataset and clinical samples. Based on combination analyses, WWTR-1 was introduced as a recognized downstream regulatory target in the Hippo pathway [ 20 ] . LncRNA LEF1-AS1 The expression levels and functional role of lymphoid enhancer-binding factor 1 antisense RNA 1 (LEF1-AS1) have been investigated in oral squamous cell carcinoma (OSCC). The findings showed that LEF1-AS1 was significantly overexpressed in 20 OSCC tissues compared to the adjacent non-tumor tissues. LEF1-AS1 overexpression was associated with poor outcomes in OSCC patients. In this regard, knockdown of LEF1-AS1 inhibited cell survival and proliferation, promoted apoptosis, and suppressed tumor growth of CNE-1, CNE-1/T, HNE-2, and HNE-2/T cells . Furthermore, LEF1-AS1 influenced the Hippo signaling pathway by interacting with LATS1 and inhibiting its binding to MOB, which led to hindering YAP1 phosphorylation. Therefore, it was indicated that LEF1-AS1 inactivates Hippo signaling pathway in OSCC [ 21 ] . LINC01315 The expression of long intergenic non-protein coding RNA 1315 (LINC01315) is down-regulated in OSCC tissues [ 22 ] . Based on bioinformatic analysis of the GSE45238 dataset of the GEO database, it was hypothesized that miR-211 might interact with LINC01315 and affect OSCC development and progression. The miR-211 contains complementary sequences for LINC01315 and disks large homolog 3 (DLG3). The evaluation of OSCC and adjacent tissues demonstrated that the expression levels of DLG3 and LINC01315 are significantly higher, and the expression level of miR-211 is significan tly lower in the OSCC tissues [ 23 ] . Further analysis showed tha t LINC01315 competitively binds to miR-211, resulting in up-regulation of DLG3 expression. Also, LINC01315 knockdown enhanced proliferation, migration, and invasion and supp ressed apoptosis in OSCC cell lines SAS, SCC25, HN4, HN6, CAL-27, and NHOK . A previous study pointed to a possible relationship between up-regulation of DLG3 and the Hippo pathway in breast cancer [ 23 ] . The results showed that down-regulated DLG3 was associated with down-regulation of MST1, MST2, and LATS 1, and up-regulation and nuclear translocation of YAP protein [ 24 ] . LncRNA LUADT1 One lncRNA named lung adenocarcinoma-related transcript 1 (lncRNA LUADT1) has been revealed to involve in nasopharyngeal carcinoma (NPC) progression. Clinical investigations discovered that lncRNA LUADT1 and TEAD1 were significantly overexpressed, and miR-1207-5p was significantly down-regulated in 79 NPC tissues and 4 cell lines HONE-1, HNE-1, CNE1, CNE2. The bioinformatic and luciferase reporter assay showed lncRNA LUADT1 and TEAD1 have binding sites for miR-1207-5p. The knockdown of lncRNA LUADT1 inhibited cell proliferation, migration, and invasion, which was reversed by the inhibitory effect of miR-1207-5p. The effect of lncRNA LUADT1 in NPC progression was also verified in vivo . Regarding the Hippo pathway, LncRNA LUADT1 knockdown results in the LATS1 protein up-regulation and YAP1 and TAZ down-regulation. However, miR 1207-5p down-regulation has a contrary effect [ 25 ] . hepatocellular carcinoma HCC, the most common primary liver cancer, is the third leading cause of cancer death [ 16 ] . In the recent decade, the early treatment of HCC has progressed dramatically, improving the prognosis. Since most patients are diagnosed in later stages of the disease and are not eligible for surgical resection and conventional treatments [ 26 ] , identifying underlying molecular processes in HCC progression could develop novel diagnostic and therapeutic strategies. The Hippo signaling pathway has been confirmed to involve in HCC development and progression through regulating key Hippo-related genes, including Sav1, Mst1/2, Mob1a/b and Lats1/2. Moreover, the Hippo regulation role of lncRNAs has been reported in HCC tumorigenesis mainly by affecting YAP/TAZ [ 27 ] . LncRNA MALAT1 Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a lncRNA with high expression in many tumors and is associated with an increased risk of metastasis [ 27 ] . A recent study explored the relationship between YAP protein, serine/arginine-rich splicing factor 1 (SRSF1), and MALAT1 in 112 HCC patients and cell line HepG2 . It was demonstrated that YAP protein induces MALAT1 transcription through the TCF/β-catenin element located in the MALAT1 promoter region, which leads to tumor growth. Furthermore, SRSF1 down-regulates MALAT1 expression by facilitating the translocation of intra-nucleus accumulated YAP to the cytoplasm and accelerating MALAT1 degradation [ 28 ] . LncRNA uc.134 The lncRNA uc.134 was found with a low expression in HCC cell line with a high metastatic potential named HCCLM3. The expression of uc.134 was shown to be significantly decreased in 170 paraffin-embedded HCC compared to the adjacent tissues, and the lower uc.134 expressions was significantly associated with poor overall survival in HCC patients. Moreover, the reduction of mRNA levels of YAP target genes was observed in the overexpression of uc.134. The relationship between uc.134, LATS1, and pYAP was confirmed in 90 paraffin-embedded HCC samples. The investigation of the molecular mechanisms of uc.134 in HCC progression verified that CUL4A protein, which is an E3 ligase targeting LATS1 protein for degradation and ubiquitination [ 29 ] , bound to uc.134 to form an RNP complex. The overexpression of uc.134 was associated with CUL4A accumulation in the nucleus, while in uc.134 knockdown, CUL4A was observed in the cytoplasm. Thus, it was confirmed the interaction of LATS1 and CUL4A proteins in HCC cells may result in more stability of LATS1 protein in cells transfected with CUL4A and uc.134 compared to CUL4A alone. Altogether, the findings suggested that lncRNA uc.134 activates Hippo signaling by inhibiting CUL4A translocation from the nucleus to the cytoplasm, increasing LATS1 stability and reducing YAP target genes expression [ 30 ] . LncRNA PVT1 LncRNA plasmacytoma variant translocation 1 (PVT1) is associated with the development and progression of cancers. Functional studies on HCC cell line SMMC-7721 demonstrated that lncRNA PVT1 may promote liver cancer progression by inhibiting histone methylation on the MYC promoter, signifying it as potential target for therapeutic strategies of the malignancy. The potential genes associated with PVT1 in HCC have been investigated by bioinformatic analysis [ [13] , [14] , [15] ] . Moreover, PVT1 has been revealed to upregulate in HCC and significantly correlate with clinicopathological features of the patients, indicating it as a valuable diagnostic biomarker. Further analysis showed that PVT1 may function as an oncogene in HCC development probably via regulating the Hippo pathway. Altogether, findings indicated that DLC1 (deleted in liver cancer 1) and PVT1 genes are potentially involved in the Hippo signaling pathway [ 31 ] . LncRNA UCA1 Urothelial cancer associated 1 (UCA1) is one lncRNA upregulated in various cancers. The biological role of lncRNA UCA1 has been explored in HCC. After confirming significant UCA1 upregulation in 41 HCC tissues in comparison with adjacent tissues and a positive correlation of UCA1 overexpression with advanced stages of HCC, UCA1 was knocked down in HCC cell lines Huh-7, Hep3B, HepG2 and SMMC7721, resulting in inhibition of cell growth and induction of apoptosis. In this regard, the KEGG pathway analysis also demonstrated that UCA-related genes were significantly enriched in the Hippo signaling pathway [ 32 ] . LncRNA CRNDE Colorectal neoplasia differentially expressed (CRNDE) have some oncogenic properties in different cancers [ [33] , [34] , [35] , [36] ] . In several investigations, it has been demonstrated that CRNDE was significantly upregulated in 47 HCC tissues, and its overexpression was associated with poor prognosis [ 37 ] . The knockdown of CRNDE inhibited cell proliferation, migration, and chemoresistance in HCC cell lines C-9810, Bel-100, Bel-7405, Bel-7402, Huh-7, WRL68, SMMC-7721, HepG2 , and inhibited tumor growth and tumor metastasis in vivo . Moreover, to explore the CRNDE mechanism in HCC pathogenesis, the direct binding between CRNDE and SUZ12, EZH2, and SUV39H1 was documented. SUZ12 and EZH2 are subunits of polycomb repressive complex 2 (PRC2), which exert tumorigenic roles owing to histone methyltransferase activity and modulating target gene expression [ 38 ] . It has been validated that the complex of CRNDE with SUZ12, EZH2, and SUV39H1 directly targets the tumor suppressor genes, LATS2 and CELF2. Also, the regulation of CRNDE in HCC is mediated by LATS2 and Hippo pathway so that LATS2 overexpression can inhibit the effect of CRNDE on the progression of HCC [ 37 ] . LncRNA LOC107985656 The LOC107985656 is a recently reported lncRNA that its roles have been investigated in 30 HCC patients. The researchers demonstrated that LOC107985656 inhibits proliferation of HCC cell lines Huh 7, SMMC-7721, HepG2.2.15 and HepG2. Also, its expression was significantly downregulated in HCC tissues, and its low expression was associated with a poor prognosis. Moreover, LOC107985656 was shown to regulate the Hippo pathway. Although LOC107985656 knockdown did not affect YAP and TAZ mRNA levels in HCC cells, it significantly increased the YAP and TAZ protein expression and decreased the mRNA level of LATS1 and the levels of phosphorylated YAP and TAZ, leading to the inactivation of Hippo pathway. To investigate the underlying mechanism of LOC107985656 in regulating LATS1, the researchers predicted the miRNAs that may bind to LOC107985656 and LATS1 through the ceRNA mechanism. Ultimately, they showed that LOC107985656 activates the Hippo pathway by regulating the expression of LATS1 through the miR-106b-5p/LATS1 axis [ 39 ] . intrahepatic cholangiocarcinoma Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver malignancy after hepatocellular carcinoma (HCC). The incident rates of ICC are increasing annually [ 40 ] , followed by an increase in mortality rates [ 41 , 42 ] . Surgical resection is the only curative treatment option; however, the five-year overall survival rates are around 11–40 % [ 43 ] . Regarding systemic therapies, the standard of care includes gemcitabine and cisplatin as first-line, FOLFOX as second-line, and capecitabine as adjuvant therapy [ 44 ] . The data on target therapy in ICC is still limited, and the role of lncRNAs in this area needs to be explored. A number of molecular mechanisms have been described for ICC tumorigenesis and metastasis. The Hippo signaling pathway has been confirmed to contribute into ICC development and progression. The regulatory role of lncRNAs has also confirmed to involve in the Hippo-mediated tumorigenesis process. LncRNA MNX1-AS1 In a recent study, the role of lncRNA MNX1-AS1, also known as motor neuron and pancreas homeobox 1-antisense RNA1, was investigated and MNX1-AS1/c-MYC and MAZ/MNX1/Ajuba/Hippo pathway was introduced. Initially, the analysis of RNA-seq data of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases demonstrated that the expression of MNX1-AS1 and MNX1 were significantly upregulated and positively correlated in 33 ICC tissues. The in vivo and in vitro investigations showed that MNX1-AS1 might enhance the expression of MNX1 in ICC cell lines ( RBE, QBC939, and FRH0201) by recruiting transcription factors c-MYC and MAZ. After that, MNX1 promotes Ajuba protein expression, suppressing the Hippo pathway. The inhibition of the Hippo pathway and YAP1 increase leads to ICC tumorigenesis and progression [ 45 ] . LncRNA PAICC In another study, a competitive endogenous RNA (ceRNA) network of ICC was established. The analysis of the involved genes in the Hippo pathway in a GEO database showed that the expression of lncRNA-RP11 – 375I20.6, also named prognostic-associated ICC (PAICC) lncRNA, was upregulated in ICC. The expression analysis of PAICC and YAP1 showed that the expression levels of these genes were significantly higher in the 76 ICC tissues compared to adjacent healthy tissues [ 46 ] . Moreover, there was a significant positive correlation between PAICC and YAP1 expressions. In this regard, it was demonstrated that PAICC was significantly associated with poor prognosis in ICC patients, which gives insight into this lncRNA's oncogenic feature. The bioinformatic analysis showed that lncRNA-PAICC and PAICC have binding sites for miR-141-3p and miR-27a-3p thereby compete with these two miRNAs and down-regulates their expression in ICC cells. The dual-luciferase reporter assays confirmed that YAP1 is the downstream target gene of this ceRNA axis (PAICC/miR-141-3p and miR-27a-3p/YAP1). Thus, lncRNA-PAICC has an essential role in the proliferation and invasion of ICC through YAP1 regulation-mediated Hippo signaling pathway by sponging miR-141-3p/27A-3p [ 46 ] . gallbladder cancer Gallbladder cancer (GBC) is considered as a common and invasive of biliary tract malignancy with a poor prognosis diagnosis in late stages. Usually, traditional drug-based therapies are inefficient and the only curative approach for early-stage of the malignancy is whole surgical resection. Development of therapeutic strategies is remarkably reliant on the awareness from underlying molecular mechanisms and the early diagnostic biomarkers. Some epigenetic modulators such as miRNAs and lncRNAs have been revealed to involve in tumorigenesis and metastasis of GBC through regulating Hippo pathway, which could be valuable for diagnosis and therapy of the cancer [ 47 ] . MNX1-AS1 A recent study examined the clinical and biological importance of lncRNA motor neuron and pancreas homeobox1 antisense RNA 1 (MNX1-AS1) in gallbladder cancer (GBC). The results indicated that the expression levels of lncRNA MNX1-AS1 were increased in the 33 tumor tissues. This overexpression of the lncRNA was revealed to be correlated with poor survival of GBC patients [ 48 ]. Moreover, it was demonstrated that MNX1-AS1 could promote the proliferation and metastasis of GBC cells (RBE and QBC939) in vitro and in vivo . The functional studies confirmed that TEA domain family member 4 (TEAD4) may promote the expression of MNX1-AS1. In this way, MNX1-AS1 may recruit ubiquitin specific peptidase 16 (USP16) and promote insulin-like growing factor 2 mRNA-binding protein 3 (IGF2BP3) activation. Based on the findings, this signaling pathway axis might promote the tumor development and progression. In this regard, lncRNA MNX1-AS1 has been indicated as a valuable tool for diagnostic and therapeutic strategies of GBC [ 48 ]. pancreatic cancer Pancreatic cancer (PC) is an aggressive malignancy, accounting for 466,000 global deaths in 2020, and it is projected to become the second leading cause of cancer death by 2030 in the United States [ 49 ] . The mortality/incidence ratio of as high as 94 % and the 5-year survival rate of 9 % give insight into pancreatic cancer's highly fatal nature. The stage at the time of diagnosis has a very significant effect on the survival rate of pancreatic cancer [ 50 ] . A timely diagnosis and treatment of pancreatic cancer patients could become possible by identifying novel molecular biomarkers. Several studies documented the Hippo signaling pathway in PC tumorigenesis. Also, it has been found the Hippo regulatory role of lncRNAs in PC development and progression. LncRNA GAS5 LncRNA growth arrest-specific 5 (GAS5) is a tumor-suppressive lncRNA that has an essential role in the tumorigenesis of various cancers [ 51 ] . Gao et al. predicted that miR-181c-5p could be a direct target of GAS5 [ 52 ] . The miR-181c-5p was previously reported to be upregulated in pancreatic cancer, and it inhibited apoptosis and promoted chemoresistance by inactivating the Hippo signaling pathway [ 53 ] . Also, they demonstrated that GAS5 was downregulated, and miR-181c-5p was upregulated in drug-resistant pancreatic cancer cells SW1990/GEM and PATU8988/5-FU compared to drug-sensitive cells SW1990 and PATU8988 . It was verified that GAS5 directly binds to miR-181c-5p and negatively regulates it. GAS5 upregulation led to MST1 protein overexpression and increased YAP and TAZ phosphorylation, Hippo signaling activation, and inhibited tumor growth in vivo . At the same time, miR-181c-5p upregulation compromised GAS5-induced MST1, p-YAP, and p -TAZ overexpression [ 52 ] . LncRNA UCA1 The biological role of lncRNA UCA1 has also been investigated in PC. It has been established that UCA1 was upregulated in pancreatic cancer tissue, and its overexpression was associated with enhanced migration and invasion of cancer cells and poor prognosis. The investigation of UCA1 functional significance in PC cell lines BxPC-3, SW1990, PaTu8988, and PANC-1 showed that UCA1 induces YAP activation and binds to MOB1, LATS1, and YAP, forming a ribonucleoprotein complex. It was demonstrated that UCA1 inhibits YAP phosphorylation and promotes YAP translocation to the nucleus. Also, YAP increased UCA1 expression in pancreatic cells, indicating a positive feedback between Hippo signaling and lncRNA UCA1 [ 54 ] . LncRNA MALAT1 Zou et al. investigated the MALAT1 expression and its function in pancreatic cancer. They showed that lncRNA MALAT1 was upregulated in 15 pancreatic cancer tissues compared to the adjacent tissues. Furthermore, MALAT1 was demonstrated to promote proliferation, migration and invasion, and inhibit apoptosis in vitro (cell lines AsPC-1, PANC-1 and BxPC-3) , and promote tumor growth in vivo . The immunohistochemistry analysis showed that the expression levels of LATS1 and YAP1 were significantly higher in pancreatic cancer than adjacent tissue. The analyses of LATS1 and YAP1 and MALAT1 expression levels showed a negative correlation between LATS1 and MALAT1, and a positive correlation between YAP1 and MALAT1 [ 55 ] . LncRNA MVIH LncRNA associated with microvascular invasion in HCC (MVIH) is associated with microvascular invasion, proliferation and migration in various solid tumors [ [56] , [57] , [58] , [59] ] . In a recent study, the molecular mechanism of MVIH was investigated in PC. The expression of lncRNA MVIH in 70 patients with pancreatic cancer showed that lncRNA MVIH expression was significantly higher in the tumor tissues compared to the adjacent tissues and its overexpression was associated with poor prognosis. In vitro evaluation demonstrated that lncRNA MVIH was overexpressed in pancreatic cancer cell lines ( PSN-1, AsPC-1, PANC-1 and BxPC-3) and it promoted cell proliferation and invasion, and inhibited apoptosis. Moreover, the molecular mechanism of lncRNA MVIH and the involved signaling pathways were investigated. The RNA sequencing and bioinformatic analysis showed 196 differentially expressing genes (DEGs) in pancreatic cancer cell lines with overexpressed MVIH. Furthermore, KEGG enrichment analysis demonstrated that these DEGs were enriched in various cancer signaling pathways, including Hippo signaling pathway. The accordant DEGs associated with Hippo signaling pathways were SMAD4, PRKCZ, SNI2, FZD4, TGFB2, BIRC5, and AREG [ 60 ] . LncRNA MUF (LINC00941) The MSC-upregulated factor (lncRNA MUF) is a new lncRNA that has been previously revealed to involve in various cancers and promote cell proliferation and metastasis [ [61] , [62] , [63] , [64] , [65] , [66] ] . In pancreatic adenocarcinoma, the expression of lncRNA MUF is significantly higher in the tumor tissue compared to the adjacent normal tissue and its high expression correlates with poor prognosis [ 67 , 68 ] . One of the mechanisms of function of lncRNA MUF for promotion of pancreatic adenocarcinoma growth in cells (PANC-1, SW1990, CFPAC-1, and BxPC-3 ) is increasing aerobic glycolysis. The TEAD1 has been identified as the sole transcription factor of regulating glycolysis increased by lncRNA MUF transfection. Downstream genes of Hippo pathway were analyzed and demonstrated to be affected by this lncRNA. Furthermore, it was shown that lncRNA MUF interacts with MST1, leading to the MST1 dephosphorylation by protein phosphatase 2A (PP2A) and increasing YAP1 nuclear localization in pancreatic adenocarcinoma [ 67 ] . gastric cancer Gastric cancer (GC) is a lethal malignancy of gastrointestinal tract with a high recurrence rate. The prevalence and mortality of GC are growing in undeveloped and developing countries. A number of attempts have been completed for identification of molecular mechanisms and supportive biomarkers for diagnosis, prognosis and therapy of GC [ 47 ]. The regulatory feedback of lncRNAs/Hippo has also been revealed to involve in the GC tumorigenesis with a clinical significance [ 69 , 70 ] . LincRNA P21 The lincRNA P21 has been recognized as the direct transcriptional target of p53 that its low expression is linked with poor prognosis of several cancers [ 71 ] . In GC, lincRNA P21 was significantly downregulated in 40 tumor tissues in comparison with the adjacent normal tissue and its low expression was significantly associated with higher invasion depth grade and cancer metastasis. The in vitro study on biological function of lincRNA P21 showed that lincRNA P21 could inhibit cell growth, proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) in GC cell lines MGC-803 and MKN-45. Further investigation on possible mechanism of lincRNA P21 in suppressing GC indicated that silencing lincRNA P21 in GC cell lines resulted in the YAP protein and mRNA level increase and YAP nuclear translocation [ 72 ] . LncRNAs CYP4A22-AS1, AP000695.6, and RP11-108M12.3 In 2018, it was published an article on a three lncRNA signature that evaluates the prognosis of patients with GC. The expression levels of the three lncRNAs in GC and adjacent normal tissue on TCGA database showed that AP000695.6 a nd RP11 – 108M12.3 were associated with better OS, and CYP4A22-AS1 with poor OS. A prognostic nomogram using the three lncRNA signature, age, TNM, stage, residual tumor, and risk score was established which showed a superior performance compared to the conventional TNM staging. Moreover, a predictive model by machine learning predicted the survival with satisfactory results. Finally, the KEGG pathway analysis demonstrated that the Hippo pathway is strongly linked to the three lncRNA risk score [ 73 ] . LINC00662 Recently, a novel GC-associated lncRNA , named LINC00662, was identified using the TCGA database. The LINC00662 expression was significantly higher in GC tissues and cell lines. The higher expression of LINC00662 was also associated with poor prognosis of GC patients. The exploration of LINC00662 biological function showed that its knockdown in GC cell lines (MKN-45, MGC-803, SGC-7901, HGC-27, BGC-823, and AGS ) was associated with decreased cell proliferation and colony formation, and over sensitization of GC cells to 5-fluorouracil [ 74 ] . Regarding the Hippo pathway, th e LINC00662 knockdown was correlated to the downregulation of CTGF, CYR61, and YAP1 mRNA and protein expression. Via bioinformatic analysis, five miRNAs were selected that potentially had binding sites for LINC00662. Among the selected miRNAs, the expression of miR-497-5p was significantly lower in 30 GC tissues, and after the LINC00662 knockdown, miR-497-5p was upregulated. Upon the transfection of GC cells with mi R-497-5p, the YAP1 protein expression was significantly downregulated. Moreover, the luciferase reporter assay confirmed the direct binding of miR-497-5p to LINC00662 . Altogether, it was concluded that LINC00662 may be a potential GC biomarker that promotes tumorigenesis by reducing YAP1 expression and inactivating Hippo pathway through targeting miR-497-5p [ 75 ] . LncRNA HCG18 Recent studies have demonstrated that lncRNA HLA complex group 18 (HCG18) might act as ceRNAs of numerous miRNAs and promote cancer progression through several signaling pathways. The lncRNA HCG18 expression was significantly higher in 79 GC tumors than in normal adjacent tissues with a correlation to poor prognosis [ [76] , [77] , [78] ] . Also, it has been shown that HCG18 knockdown in GC cell lines AGS and MKN-28 decreased tumor proliferation, migration, and invasion, and suppressed tumor growth and metastasis. A binding site between HCG18 and miR-141-3p was determined via bioinformatic analysis, which was validated by luciferase reporter assay. There was a correlation between HCG18 and miR-141-3p expressions in GC cells, in such a way that HCG18 overexpression promoted the expression of miR-141-3p. Furthermore, HCG18 enhanced the proliferation, migration and invasion of GC cells through regulating miR-141-3p. Indeed, the downregulation of HCG18 resulted in miR-141-3p inhibition and significantly decreased the WIPF1, YAP and TAZ mRNA and protein expression levels [ 78 ] . LncRNA FER1L4 LncRNA Fer-1-like family member 4 (FER1L4) was found to be downregulated in GC tissues and its expression is associated with clinicopathological characteristics [ 79 ] . To identify the underlying mechanisms of FER1L4 in GC, the effect of FER1L4 overexpression on GC cell line SGC-7901 has been explored . Findings demonstrated that FER1L4 overexpression suppressed proliferation, invasion, migration, and metastasis of GC cells. Moreover, the FER1L4 overexpression in GC cell lines led to the activation of Hippo pathway through CXCR4/CXCL12 axis. The role of FER1L4 in the GC cell proliferation and invasion through interacting with YAP and modulating Hippo pathway has been revealed. The results demonstrated that YAP reversed the inhibitory effect of FER1L4 overexpression on cell cycle, invasion, migration and lymphatic metastasis [ 80 ] . LINC00649 Long intergenic nonprotein coding RNA 649 has been reported as an lncRNA that functions in cancer initiation and progression. A key ceRNA signaling axis identified in GC was LINC00649/miR-16-5p [ [81] , [82] , [83] ] . (LINC00649) is an lncRNA that was p reviously recognized as a prognostic biomarker of acute myeloid leukemia, prostate, and colorectal cancers. GC and adjacent normal tissues of 54 patients were evaluated by RT-qPCR and the results demonstrated that the expression of LINC00649 and YAP1 mRNA were significantly increased, while miR-16-5p expression was decreased in GC tissues. The functional experiments showed that LINC00649 overexpression in GC cell lines (MGC-803 and SGC-7901) resulted in inhibition of apoptosis, enhanced cell proliferation, migration, and EMT process in vitro, and promotion of tumor growth in vivo. They predicted that LINC00649 and YAP1 mRNA contain binding sites for miR-16-5p by bioinformatic analysis, which was conf irmed by luciferase reporter assay. The knockdown of LINC0649 inhibited YAP1 mRNA and protein expression, which was reversed by silencing miR-16-5p. In fact, LINC00649 might promote GC through miR-16-5p downregulation and YAP1 upregulation [ 69 ] . LncRNA RP11-323N12.5 Another lncRNA that based on the TCGA database is the most upregulated lncRNA in GC, is RP11 – 323N12.5. Also, it was demonstrated that the high RP11 – 323N12.5 expression was significantly associated with advanced stages of GC and worse disease-free survival. The researchers have reported a correlation between the expression level of RP11 – 323N12.5 and Hippo-associated genes. Altogether, the biological regulatory role of lncRNA RP11 – 323N12.5 in Hippo signaling pathway was indicated [ 74 ] . The RP11 – 323N12.5 upregulation was confirmed in 67 paired human GC and normal adjacent tissues and it was correlated with the overexpression of either YAP1 mRNA or protein levels in GC tissues. The overexpression and knockdown experiments showed that RP11 – 323N12.5 may regulate YAP1 transcription. The transcription factor that had binding sites for both RP11 – 323N12.5 and YAP1 gene promoter was c-Myc, as a mediator for inducing YAP1 promoter [ 74 ] . Moreover, YAP1 activation could promote RP11 – 323N12.5 transcription in GC cell lines MKN45 and MGC-803 through TEAD1 binding site in RP11 – 323N12.5 promoter region. It has been revealed that lncRNA RP11 – 323N12.5 could contribute to the upregulation of AXL, survivin or MMP9 that enhance cell proliferation, migration and invasion via YAP1. Another influence of RP11 – 323N12.5 on GC cells by YAP1 activation was promoting immunosuppression through Treg cell differentiation and myeloid-derived suppressor cells infiltration. The biological role of RP11 – 323N12.5 in tumor growth and immunosuppression through YAP1 was also established in vivo [ 74 ] . colorectal cancer Colorectal cancer (CRC) is a prevalent and deadly malignancy and the third leading cause of cancer-related death worldwide. The malignancy diagnosis is commonly concluded in the late clinical stages with hopeless therapy and poor prognosis of patients. Understanding the molecular characteristics of CRC is prerequisite for discovering effective targeted therapies [ 84 , 85 ] . Hippo signaling has been documented as a key molecular pathway for homeostasis of intestinal cell proliferation through cross-talking with some non-coding RNAs, including lncRNAs [ 86 ] . LncRNA B4GALT1-AS1 LncRNA B4GALT1-AS1 is the antisense counterpart of B4GALT1. The biological role of lncRNA B4GALT1-AS1 in the promotion of colon cancer cell stemness has been investigated. Since B4GALT1-AS1 is one lncRNA with a high expression in colon cancer cells ( HCT116, SW480 and SW620 ) compared to normal colon cells, it was chosen for further functional investigations. The knockdown of B4GALT1-AS1 in colon cancer cell lines decreased cell colony formation, but had no impact on cell viability. Moreover, B4GALT1-AS1 knockdown inhibited colon cancer cells migration, invasion, and EMT process through suppressing the expression of aldehyde dehydrogenase 1 (ALDH1) and other stemness markers. The effect of B4GALT1-AS1 on the colon cancer cells stemness was also confirmed in vivo . The RNA-sequencing data demonstrated that the Hippo signaling pathway was significantly upregulated in colon cancer cell lines compared to cell lines with B4GALT1-AS1 knockdown. Although B4GALT1-AS1 did not affect the YAP mRNA level, it significantly reduced the YAP protein level. They found out that YAP binds to B4GALT1-AS1, promotes YAP translocation from nuclear to cytoplasm, and decrease YAP transcriptional activity in colon cancer cells. Additionally, they showed that the inhibitory effect of B4GALT1-AS1 knockdown on cell clone formation, stemness markers expression, cell spheroid formation, and ALDH1 activity was reversed by YAP overexpression. In this regard, it was concluded that lncRNA B4GALT1-AS1 could promote colon cancer stemness via translocating YAP to nucleus to increase its transcriptional activity [ 87 ] . LncRNA GAS5 The YAP-binding lncRNA GAS5 was identified in CRC using RIP-sequencing. It was revealed that GAS5 expression is significantly decreased and YAPS and YTHDF3 expressions are significantly increased in 208 CRC tissues compared to normal adjacent tissues. The expression levels of the Hippo signaling-associated genes such as CTGF and CYR61, correlate with prognosis and survival of CRC patients. In CRC cell lines ( DLD1, LOVO, SW480, SW620, LS174T, HCT116, RKO and HT29 ), GAS5 expression had a significant inverse correlation with YAP expression. The gain and loss of function experiments confirmed that GAS5 downregulation was associated with YAP protein nuclear localization. Briefly, GAS5 directly binds to YAP protein and promotes its translocation from nucleus to cytoplasm, enhances YAP phosphorylation, and decreases the YAP total protein via accelerating its ubiquitination and degradation [ 74 ] . KEGG pathway analysis confirmed the strong association of GAS5 and YAP in the Hippo pathway. The in vitro and in vivo evaluation of GAS5 impact on CRC progression demonstrated that GAS5 overexpression could suppress CRC cell proliferation, invasion, and it decreases tumor growth. YTH-domain family member 3 (YTHDF3) is a target gene of YAP that stabilizes the N6-methyladenosine (m6A) RNAs. YTHDF3 was significantly downregulated in the YAP knockdown and GAS5 overexpressed CRC cells. YAP directly binds to YTHDF3 and promotes CRC cell proliferation and invasion, while GAS5 inhibits the YAP-mediated expression of YTHDF3. Interestingly, YTHDF3 binding to m6A-modified lncRNA GAS5 enhances the degradation of GAS5 [ 88 ] . LncRNA USP2-AS1 Recently, the biological and clinical significance of lncRNA USP2-AS1 have been investigated in colon adenocarcinoma. Findings showed that in 43 patients with CRC, the USP2-AS1 expression was significantly higher in the tumor tissues, and its level was associated with tumor grade and stage [ 89 ] . Previously, it was shown that two transcripts of USP2-AS1 bind to YAP1 [ 89 ] . Li et al. confirmed that these two transcripts of USP2-AS1 bind to YAP1 in colon adenocarcinoma cell lines SW480, SW620, and Lovo . The in vitro and in vivo experiments revealed that USP2-AS1 overexpression enhanced colon adenocarcinoma cell proliferation, invasion, and metastasis. Moreover, USP2-AS1 overexpression decreased the p -LATS1, LATS1, LATS2, and p-YAP1 levels and increased total YAP1 level in colon adenocarcinoma cell lines. The Hippo pathway target genes, CTGF, CYR61, and SOX9 were inhibited by USP2-AS1 knockdown, and vice versa, which was in accordance with the effect of USP2-AS1 overexpression on inactivation of Hippo pathway [ 89 ] . LINC00152 LncRNA LINC00152 has been reported as the most downregulated lncRNA in YAP1-suppressed CRC cell line HCT116 and the most upregulated in CRC datasets. The clinical investigations showed that 177 CRC patients with high expression of LINC00152 and FSCN1 had the worst prognosis, while if either LINC00152 or FSCN1 was downregulated; the prognosis was improved. Also, the biological function of LINC00152 has been investigated in CRC progression. LINC00152 was significantly overexpressed in CRC tissues compared to adjacent tissues in 83 patients, and its expression level was positively associated with YAP1 and CTGF levels, and poor overall survival of patients. To regulate LINC00152, YAP1 binds to TEAD1 that is predicted to have two binding sites for LINC00152 promoter. Furthermore, luciferase activity analysis demonstrated that TEAD1 binds to one of these sites and regulate the LINC00152 expression. In addition to YAP1, NF2, an upstream molecule of t he Hippo pathway, represses the LINC00152 expression [ 74 ]. The in vitro and in vivo analysis confirmed that LINC00152 has a role in enhancing proliferation and metastasis of CRC cells. The expression of Fascin actin-bundling protein 1 (FSCN1), that promotes CRC cell migration, was positively correlated with LINC00152 expression. Likewise, gain and loss of function experiments on LINC00152 increased and decreased the expression level of FSCN1, respectively. Both LINC00152 and FSCN have binding sites for three miRNAs, so two of them (miR-185-3p and miR-632) have more regulatory effect on FSCN1 and significantly lower expressions in the CRC tumor tissue compared to normal adjacent tissue. The luciferase activity analysis reports and in vitro experiments demonstrated that LINC00152 positively regulates FSCN1 via sponging with miR-185-3p and miR-632, and promotes cell prolifera tion, invasion, and metastasis of CRC cells [ 90 ] . LncRNA SNHG1 In a recent study, Xu et al. evaluated the lncRNAs small nucleolar RNA host gene 11 (SNGH11), ZFAS1, LINC00654, and LINC00909 circulating levels in patients with polyps, adenoma, and CRC. They revealed that the combination of these four lncRNAs provides a diagnostic tool with a satisfactory accuracy in diagnosing CRC at early stages as well as advanced stages. The examination of molecular mechanisms of SNHG11 in CRC pathogenesis showed that SNHG11 mRNA expression was higher in CRC cell lines derived from primary tumor compared to cell lines derived from CRC metastases. The in vitro analysis established that SNGH11 promotes cell proliferation, migration and invasion. Moreover, knockdown of SNHG11 led to changes in EMT markers, including E-cadherin overexpression and N-cadherin downregulation in cell lines LoVo, SW480, HCT116 and SW620 . Since EMT is related to Hippo pathway, the levels of phosphorylated-YAP and phosphorylated-LATS1 were evaluated after SNHG11 knockdown in CRC cell lines, which showed significant reductions. The in vivo assays also indicated that SNHG11 knockdown inhibited tumor growth in CRC mice models [ 91 ] . LncRNA AGAP2-AS1 and LINC-PINT LncRNA ankyrin repeat and PH domain 2 antisense 1 (AGAP2-AS1) is one lncRNA that was previously reported to have a role in promoting tumorigenesis of gastric, lung, and breast cancers [ [92] , [93] , [94] , [95] , [96] ] . In 66 patients with CRC, lncRNA AGAP2-AS1 was significantly overexpressed in the tumor tissues compared to para-tumor normal tissues, whereas LINC-PINT expression was significantly downregulated and negatively correlated with AGAP2-AS1 expression. AGAP2-AS1 overexpression downregulated LINC-PINT expression and its inhibition upregulated LINC-PINT expression in CRC cell lines RKO and HCT116 . Similarly, LINC-PINT overexpression and inhibition have been shown to downregulate and upregulate the AGAP2-AS1 expression, respectively. AGAP2-AS1 overexpression enhanced CRC cell proliferation, migration and invasion, whereas LINC-PINT overexpression had an inhibitory effect [ 69 ] . Future perspectives; GI cancer therapeutic strategies targeting lncRNAs A number of functional and clinical investigations revealed the imperative role of Hippo signaling pathway in tumor development and progression. A growing number of studies have indicated biological interaction between Hippo signaling pathway and lncRNAs. Moreover, the corresponding effectors involved in the biological crosstalking regulate tumor cell functions and have clinical values; their dysregulation is correlated with clinicopathological features and might be served as promising biomarker in diagnosis and prognosis of GI cancers [ 74 ]. In this regard, Hippo signaling/lncRNA interactions also improve our insight into other various tumor properties involved in EMT and chemo‐resistance. Taken together, Hippo/lncRNAs signaling axis may be indicated as groundbreaking clinical biomarker as well as an appropriate therapeutic target for GI cancers. Since the lncRNAs structures can be straightforwardly targeted by various practicable strategies, it may be endorsed the application of these molecules as innovative drugs [ 74 ]. The advantages of these molecules as biological tools for cancer therapy include their usage in low and non-toxic doses, easy manipulation and employment, and elimination of side effects due to restore lacking. Regarding to cancer therapeutic strategies, it may modify cancer-related suppressor lncRNAs in a locus-specific mode. Also, oncogenic lncRNAs may be adjusted or suppressed for remove their epigenetic effects [ 74 , 75 ]. Other strategies contain interfere with biological functions, use of lncRNAs regulatory elements and modification or restoration of expression levels. Distinct most relevant nucleic acid-based approaches are antisense oligonucleotides (ASOs), locked nucleic acid GapmeRs (LNA GapmeRs), antagonist to natural antisense transcripts (antagoNATs), aptamers, small interfering RNAs (siRNAs) and short hairpin RNA (shRNAs), deoxyribozymes and ribozymes. New genome engineering tools may involve zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system [ [13] , [14] , [15] ]. ASO-based targeting of the overexpressed lncRNAs in HCC and PC such as MALAT1, may be as an efficient approach to inhibit tumor progression, similar to what has been documented in breast [ 97 ] and lung cancer [ 98 ]. Furthermore, implication of LNAs for targeting lncRNA XIST, has probably advantages in targeting and GI anticancer therapeutic strategies [ 99 ]. AntagoNATs, as inhibitory oligonucleotides against to sense-antisense transcripts, may be implicated for reducing the epigenetic silencing effect of some oncogenic lncRNAs [ 100 ]. Thus, AntagoNATs can be designed for targeting dysregulated lncRNAs in GI cancers, such as HOTAIR and MALAT1 [ 101 ]. Mixmers and deoxy/ribozymes, another silencing approaches for targeting lncRNAs, are constructed of adjusted nucleotides to inhibit molecular interactions between lncRNAs and corresponding targets. Regarding the clinical role and significance of lncRNAs in GI cancers, such approach may be considered for targeting HOTAIR [ 102 ] and XIST [ 103 , 104 ]. Specific modified deoxyribozymes with a high catalytic activities have been suggested as inhibitors of N 6 -methyladenosine (m6A) modified-RNAs [ 105 , 106 ]. Because involving m6A modifications in lncRNAs MALAT1 [ 106 ], XIST [ 107 ], HOTAIR [ 108 ], GAS5 [ 88 ], or DANCR [ 109 ], this inhibitory structure may be as a targeting strategy for some GI cancers, including PC and CRC [ 110 ]. Sequence-specific suppression of lncRNAs MALAT1 [ 111 ], XIST [ 112 ], HOTAIR [ 113 ], NEAT1 [ 114 ] or UCA1 [ 115 ] using TALENs and CRISPR interference (CRISPRi) [ 116 , 117 ] may also has therapeutic potential, especially in HCC and PC. Other approaches for targeting the common GI cancer-associated lncRNAs include aptamers, nanobodies, and RNA decoys [ 118 ]. Interfering aptamers may be used to hinder lncRNA-protein interactions [ 119 ] and inhibit HOTAIR [ 120 ] and H19 [ 121 ], in GI cancers. Nanobodies have potential to interrupt lncRNA-RNA binding protein (RBP) interaction [ 122 ]. Nanobodies can be designed to specifically target structured RNA molecules [ 123 ], and since many lncRNAs such as MALAT1 [ 124 ], NEAT1 [ 125 ], XIST [ 126 ], or HOTAIR [ 127 ] are well-identified, this approach has a potential to use in GI cancers which those lncRNAs are dysregulated. Inhibition of the target/downstream proteins by functional lncRNA-RBP complexes constructed by RNA decoys or imitators of lncRNAs may also be used for anticancer strategies [ 128 ] . In this regard, a mimic of HULC, one lncRNA that potentially functions in HCC cancer, can effectively regulate the function of the lncRNA and corresponding homeostasis-related signaling pathways [ 129 ]. Data availability statement No data was used for the research described in the article. CRediT authorship contribution statement Farimah Fayyaz: Writing – original draft, Formal analysis, Data curation. Zahra Shokati Eshkiki: Writing – review & editing, Methodology, Investigation. Amir Reza Karamzadeh: Investigation, Data curation. Zahra Moradi: Writing – original draft, Data curation. Faezeh Kaviani: Writing – original draft, Formal analysis, Data curation. Abolfazl Namazi: Project administration, Methodology, Investigation. Roya Karimi: Software, Methodology. Seidamir Pasha Tabaeian: Writing – review & editing, Validation, Methodology, Investigation, Formal analysis, Conceptualization. Fatemeh Mansouri: Resources. Abolfazl Akbari: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Methodology, Formal analysis, Data curation, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Abbreviations CTGF connective tissue growth factor CYR61 cysteine-rich 61 GI gastrointestinal HNSCCs head and neck squamous cell carcinomas MST1/MST2 mammalian STE20-like protein kinase 1/2 LATS1/2 large tumor suppressor 1/2 (and LATS2) YAP Yes-associated protein TAZ transcriptional co-activator with PDZ-binding motif TEAD transcriptional enhanced associate domain LncRNA long non-coding RNA ceRNA competing endogenous RNA ICC intrahepatic cholangiocarcinoma HCC hepatocellular carcinom MNX1-AS1 motor neuron and pancreas homeobox 1-antisense RNA1 TCGA The Cancer Genome Atlas GEO Gene Expression Omnibus PAICC prognostic-associated ICC LEF1-AS1 lymphoid enhancer-binding factor 1 antisense RNA 1 OSCC oral squamous cell carcinoma LUADT1 lung adenocarcinoma-related transcript 1 NPC nasopharyngeal carcinoma MALAT1 metastasis-associated lung adenocarcinoma transcript 1 PVT1 plasmacytoma variant translocation 1 UCA1 urothelial cancer associated 1 CRNDE colorectal neoplasia differentially expressed PRC2 polycomb repressive complex 2 GAS5 growth arrest-specific 5 EMT epithelial-mesenchymal transition HCG18 HLA complex group 18 FER1L4 Fer-1-like family member 4 FSCN1 Fascin actin-bundling protein 1 SNGH11 small nucleolar RNA host gene 11 AGAP2-AS1 ankyrin repeat and PH domain 2 antisense 1 MNX1-AS1 motor neuron and pancreas homeobox1 antisense RNA 1 Acknowledgment This work was supported by Grant number 99-3-49-19418 from 10.13039/100012021 Iran University of Medical Sciences .

CC BY

no

2024-01-16 23:43:44

Heliyon. 2023 Dec 22; 10(1):e23826

oa_package/a9/1a/PMC10788524.tar.gz

PMC10788526

38226256

Background Monkeypox virus (mpox) is an Orthopoxvirus genus, including variola virus, mainly prevalent in tropical forests of Central and Western Africa, responsible for a new outbreak in non-endemic regions with 86956 cases worldwide on the 17 th of April 2023 [ 1 ]. So far, around 957 cases have been reported in Italy since the start of the outbreak [ 1 ]. Mpox causes a systemic illness with fever, headache, muscle aches, back pain, low energy, and swollen lymph nodes, followed by the development of mucocutaneous manifestations, which may last for two to four weeks. The rash usually evolves into vesicular, pustular, and sometimes ulcerative lesions followed by the formation of dark crusts and can involve all body parts. During the current outbreak, mpox has shown a case fatality rate of around 0.04 %, a percentage much lower than 1–3% reported during previous outbreaks in West Africa over the past few decades [ 2 ]. Complications such as bronchopneumonia, encephalitis, myopericarditis, secondary bacterial infections, sepsis, and corneal or conjunctival lesions are unusual manifestations of mpox infection. The Food and Drug Administration (FDA) approved live, non-replicating vaccinia to prevent mpox infection, which is also available in Italy for not-immunized high-risk categories. The FDA approves tecovirimat (TPOXX or ST-246) for treating smallpox in adults and pediatric patients, but its efficacy against mpox has not been formally evaluated in clinical trials [ 3 , 4 ]. Tecovirimat is currently available for compassionate use to treat non-variola Orthopoxvirus infections, including mpox, in adults and children of all ages. Tecovirimat is a drug targeting the V061 gene that encodes for membrane protein p37, which is responsible for forming extracellular enveloped virions. Tecovirimat, through the inhibition of the formation of the VP37 envelope-wrapping protein, hastens the infection of the host's cells [ 5 , 6 ]. In September 2022, the AIDS Clinical Trials Group (ACTG) began the Study of Tecovirimat for Human Monkeypox Virus (STOMP), a randomized, placebo-controlled, double-blinded trial on the safety and efficacy of tecovirimat for acute mpox infection [ 7 ]. We present an unusual case of mpox-related cardiac complication in a person living with HIV with previously unknown Lyme disease and treated with tecovirimat. This case may increase clinician awareness regarding mpox complications, mainly to look for other causes of carditis. It also provides additional evidence to treat people living with HIV with tecovirimat.

Discussion This case report discusses a rare but severe cardiac complication of mpox infection in an individual living with HIV. Although the incidence is unknown, mpox life-threatening complications such as severe pneumonia, encephalitis, and myocarditis encephalitis seem rare. Myopericarditis is an inflammatory condition affecting both the cardiac muscle and the pericardium, and it can arise following various infectious or non-infectious triggers. Typically, viral infections can lead to myopericarditis due to direct or indirect damage to cardiac structures. The severity of cardiac involvement can vary widely, ranging from acute fulminant presentation to milder cases with a benign course [ 9 , 10 ]. In this specific case, although the patient had a definite cardiac complication, clinical findings and cardiac MRI using the Lake Louise revised criteria do not fully support a diagnosis of myopericarditis [ 11 ]. Notably, there was a clear temporal association between the onset of cardiac alterations and the mpox infection. Nevertheless, mild myocarditis, which could lead to marginal changes in Cardiac MRI-derived T1 and T2 mapping, is not expected to reduce significantly the left ventricular ejection fraction (LVEF) (as it would require a more extensive myocardial injury), as observed in this case. Therefore, a definitive diagnosis of myocarditis as the single etiology of the myocardial compromise and dysfunction is challenging. Even the supposition of the occurrence of stress cardiomyopathy doesn't match the requirements for the diagnosis since regional wall motion abnormalities, which among other things, should extend beyond a single epicardial coronary artery distribution, were absent [ 12 ]. In this case, we could speculate that the initial and transient myocardial dysfunction, as indicated by a slight reduction in left ventricular ejection fraction (LVEF), elevation in cardiac troponin and NT-pro-BNP ( Table 1 ), and suggestive cardiac MRI findings, could represent the initial phase of myocardial injury related to mpox infection, which might have been impeded by the early onset of tecovirimat, resulting in successful recovery of cardiac function. However, at a certain point along the way, we thought other causes should also be investigated. Despite the resolution of acute symptoms and laboratory findings, the patient continued to experience episodes of bradycardia with atrioventricular (AV) block 2:1, as detected by Holter ECG monitoring. The persistence of involvement of the cardiac conduction system is unusual in cases of acute myocarditis. Recognizing that high-degree atrioventricular block is a common presentation of Lyme carditis, the patient underwent testing for Lyme disease. Serological results evidenced a previous Borrelia burgdorferi s.l. infection, leading to the decision to initiate antibiotic therapy. However, it was challenging to determine the precise role of previous Lyme disease in the cardiac abnormalities observed during the acute mpox infection. The treatment with tecovirimat was well-tolerated by the patient, with only mild and self-limiting nausea noted shortly after starting the medication. Subsequent cardiac MRI performed five days after initiating tecovirimat therapy showed evidence of mild myocardial involvement with interstitial edema. It remains unclear whether tecovirimat played a role in reducing myocardial inflammation. Limited clinical data exist on the use of tecovirimat for mpox. In an Italian study 19 out of 128 infected patients, of whom 7 people living with HIV (PLWH), were treated with antiviral therapy: 15 with tecovirimat and 4 with cidofovir based antiviral treatment. In tecovirimat treated patients, no side effects or alterations at blood tests were reported [ 13 ]. After reviewing the medical literature, myocarditis has been described in only a few cases of infections: the overall prognosis was good, with no mortality reported in all the described cases ([ [14] , [15] , [16] , [17] , [18] , [19] ]). To the best of our knowledge, this is the first case of treatment, with a 14-day cycle of tecovirimat, for an infection complicated by myocarditis in a PLWH and previously undiagnosed Lyme disease. Finally, like most patients with mild symptoms on presentation, our patient was in isolation at home. For those cases, we provided a dedicated email, daily check, and a phone number for communications. Although the complications are rare, maintaining regular contact with these patients and warning them to refer to ED in case of new symptoms, such as chest pain or neurological signs, is necessary.

Conclusions Cardiac complications are possible severe complications of mpox infection with very few described cases in the literature. The report emphasizes the importance of considering multiple factors and potential co-infections in complex clinical cases like this. Tecovirimat, an antiviral developed for the treatment of smallpox, has uncertain efficacy against mpox infection. However, its prompt use is recommended in complicated forms and may have provided a clinical benefit in this case. Finally, this report underscores the significance of regular follow-up and communication with patients with mpox infection, even in cases with initially mild symptoms, to ensure prompt evaluation and management of any new or concerning symptoms, particularly those related to the heart or nervous system.

Both authors have contributed equally. Cardiac involvement, such as myocarditis and pericarditis, can be a severe complication of monkeypox virus (mpox) infection and could be related to other co-infections with cardiac involvement. Tecovirimat is an antiviral specifically designed to inhibit smallpox infection diffusion and approved by the FDA for other Orthopoxvirus infections; its efficacy in mpox-infected patients is not well established. We present the case of a cardiac complication during mpox infection in a previously undiagnosed Lyme disease in a 42-year-old man living with HIV. Two days after the typical maculopapular rash, the patient reported a rise in body temperature up to 39 °C, chest pain without irradiation, and shortness of breath. We found an increase in troponin level, a slight reduction in ejection fraction, and grade 2 AV block (Mobitz 1 and 2) with frequent sinus pauses (the longest of 10.1 s). Given the suspicion of myopericarditis with cardiac conduction system involvement, the patient was admitted to the Intermediate Care Unit for continuous monitoring and further evaluation. Treatment included Ibuprofen 600 mg every 12 hours (bid) and colchicine 1 mg once daily for anti-inflammatory purposes. Concomitantly, treatment with tecovirimat was started at 600 mg bid for a total of 14 days. Cardiac MRI with gadolinium showed mild interstitial edema and pericardial enhancement. However, despite the clinical and laboratory resolution of the acute phase, bradycardia with episodes of AV block persisted at follow-up, suggesting the possibility of an additional etiology. Thus, the patient was investigated for Lyme disease because high-degree AV block is the most common presentation of Lyme carditis. Serological results evidenced a previous Borrelia burgdorferi senso latu. We decided to start treatment with doxycycline 100 mg every 12h, even pending the uncertainty of the role of a previous Lyme disease in determining the cardiac rhythm disturbances. At the evaluation on day 44, the patient was systemically well, and after cardiologist consultation, pace-maker implantation was not deemed indicated. This case underscores the importance of considering alternative causes of carditis when the clinical picture remains unclear or persists after the acute phase. Keywords

Case presentation Background In this case study, we describe the complex clinical presentation of a 42-year-old Caucasian man who has sex with men living with HIV-1 for almost 12 years, regularly on follow-up at the HIV clinic, Careggi University Hospital. He had been successfully managed with antiretroviral therapy and had an undetectable viral load (defined as HIV-RNA <50 cp/mL) for more than ten years. He has been on tenofovir alafenamide/emtricitabine/rilpivirine (TAF/FTC/RPV) since 2018; it was his third line of antiretroviral therapy. The last CD4 + T cell count was 1184 × 10^6 cell/liter (CD4/CD8 ratio 1.9). Six years prior, he had received treatment for early latent syphilis, and aside from his HIV status, he had no significant medical history, risk factors for cardiovascular disease, or illicit drug use. He had also been fully vaccinated against SARS-CoV-2 but remained unvaccinated against smallpox. Clinical presentation In early September 2022, the patient sought medical evaluation due to a low-grade fever (37.5°) and the sudden appearance of skin lesions at the base of his penis. He reported recent sexual activity, including condomless oral sex and protected anal intercourse with multiple male partners. Physical examination revealed vesicular and umbilicated lesions on his genitals and small lymphadenomegaly in the groin area. Importantly, no oropharyngeal lesions were detected ( Fig. 1 ). Diagnostic evaluation The PCR test for mpox-DNA on two skin lesions in the genital area turned positive. In contrast, a PCR test for mpox-DNA on the oropharyngeal swab was negative. Considering the absence of other symptoms, the patient was isolated at home according to the guidelines for managing cases published by the Italian Ministry of Health [ 8 ]. However, his condition worsened, with a gradual increase in body temperature up to 39 °C, chest pain, labored breathing, and shortness of breath. These symptoms prompted his referral to the emergency department (ED) for further analysis. Hospital admission and diagnosis Upon admission, the patient was hemodynamically stable and presented with continuous anterior chest pain exacerbated by deep breathing. The electrocardiogram (ECG) revealed sinus tachycardia with elevated PR segment in aVR lead and depressed in peripheral and thoracic leads. Echocardiography showed a slightly enlarged (left ventricle diastolic diameter of 59 mm) and a hypokinetic left ventricle with mildly reduced ejection fraction (EF 50 %). Notably, there was no evidence of pericardial effusion. Further imaging, including a chest CT angiography, ruled out pulmonary embolism and pneumonia. The first value of high-sensitivity cardiac troponin (HScT) was 128,00 pg/ml (reference value < 14 pg/ml) and peaked at the second determination after 3 h at 142,00 pg/ml. Main clinical and laboratory findings at hospital admission are reported in Table 1 . During initial ECG monitoring in the ED, persistent episodes of sinus pauses were recorded both during the day and the night time; the longest lasted 10.1 seconds and was associated with an atrioventricular block with two non-conducted P waves; other episodes of advanced AV block grade 2 Mobitz type 1 and 2 in a context of sinus bradycardia (heart rate 40–45, nadir 32 pulses/minute, while sleeping) were recorded. Diagnosis of myopericarditis Given the suspicion of myopericarditis with cardiac conduction system involvement, the patient was admitted to the Intermediate Care Unit for continuous monitoring and further evaluation. Treatment included Ibuprofen 600 mg every 12 hours (bid) and colchicine 1 mg once daily for anti-inflammatory purposes. Concomitantly, treatment with tecovirimat was started at 600 mg bid. Although the patient remained stable during the day, nighttime monitoring revealed recurring AV blocks with pauses lasting more than 5 seconds, necessitating treatment with low-dose dopamine and standby external cardiac pacing. Atropine was administered when significant bradycardia occurred, although cardiac pacing was never required. Exclusion of other infections Multiple tests were conducted to exclude other potential infections. Nasal swabs for influenza A and B virus, as well as SARS-CoV-2, returned negative results. PCR for CMV, Epstein Barr virus, and the serology for CMV, EBV, Coxsackievirus, Echovirus, Parvovirus B19, and Herpes virus 1/2 were carried out: all of those tested negative excluding CMV and EBV serology resulting IgG positive and IgM negative. Syphilis serology documented previous but not active infection. Progression and resolution After nine days of hospitalization, the patient's left ventricular ejection fraction began to improve, eventually reaching normal values (EF 63 %). Cardiac magnetic resonance (MRI) with gadolinium on day 12 showed slightly increased global T1 and T2 mapping values, consistent with interstitial edema due to myocarditis; no signs of focal gadolinium enhancement or T2 mapping alterations were detected, while minimal hyperintensity of pericardium without effusion in LGE sequences was evident; global biventricular function (EF 57 %) was normal ( Fig. 2 ). Coronary CT angiography was normal, troponin levels normalized, and inflammatory chest pain wholly resolved. The patient was discharged on day 19 with a follow-up plan that included continuous ECG monitoring. He completed the 14 days of treatment with tecovirimat. Discovery of Lyme disease Subsequent 24-h ECG monitoring (day 26th) revealed nine asymptomatic episodes of AV block 2:1 type, especially during the nighttime with a maximum RR of 3,44s. Previous serologies were repeated, including Borrelia spp. antibodies, the latter to cover the possibility of Lyme disease with cardiac involvement. The enzyme immunoassay (LIAISON Borrelia; Diasorin; Italy) for Borrelia burgdorferi sensu lato complex (s.l.) tested IgG-positive and IgM-negative. Western immunoblot (Anti-Borrelia EUROLINE-RN-AT; EUROIMMUN Medizinische Labordiagnostika AG; Lübeck) confirmed the result of the EIA test (IgG-positive). When questioned, the patient did not recall any tick bite or suspected clinical symptoms of Lyme disease, even though he frequently trekked in the countryside. We analyzed a previously collected (June 2022) serum sample, obtaining the same result in EIA and WB tests. Lyme disease treatment The patient was started on doxycycline therapy 100 mg bid, which he completed over 28 days. After electrophysiologist revaluation, no indications at pace-maker implantation were placed. Clinical reasoning drove the decision to delay pace-maker implantation based on two key considerations. Firstly, the potential for reversible cardiac rhythm changes during acute cardiac inflammation. Secondly, the lack of urgent symptoms like hypotension or syncope necessitating immediate implantation. During a 44-day follow-up, he remained in excellent condition, with normal cardiac parameters and C-reactive protein values. A new 24-h ECG monitoring revealed persistent sinus rhythm with 3 episodes of 2nd degree AV block lasting less than 2 seconds during night sleep. These results indicated progressive resolution of the cardiac disease process, and a new ambulatory ECG monitoring was ordered after 6 months. The patient, regularly followed up at the HIV clinic, is wholly asymptomatic and in good clinical condition. After reviewing the manuscript, the patient explicitly consented to the publication of the case provided that sensitive data were anonymized. Ethic statement After reviewing the manuscript, the patient explicitly gave written informed consent for the publication of the anonymized case details and images. Data availability statement Data associated with this study has not been deposited into a publicly available repository. Data will be available upon request. CRediT authorship contribution statement Filippo Lagi: Writing – review & editing, Writing – original draft, Formal analysis, Data curation, Conceptualization. Giuseppe Formica: Writing – review & editing, Writing – original draft, Formal analysis, Data curation, Conceptualization. Andrea Rostagno: Writing – review & editing, Investigation. Alessandro Milia: Writing – review & editing, Investigation. Silvia Pradella: Writing – review & editing, Supervision, Investigation. Giulia Guazzini: Writing – review & editing. Seble Tekle Kiros: Writing – review & editing, Investigation. Paola Corsi: Writing – review & editing. Alessandro Bartoloni: Writing – review & editing, Supervision. Lorenzo Zammarchi: Writing – review & editing, Supervision. Filippo Pieralli: Writing – review & editing, Writing – original draft, Supervision, Investigation. Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Professor L. Zammarchi currently serves as associate editor to the Infectious Diseases and Global Health section of the Journal If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CC BY

no

2024-01-16 23:43:45

Heliyon. 2023 Dec 21; 10(1):e23965

oa_package/4e/f3/PMC10788526.tar.gz

PMC10788527

38226398

Introduction Acinetobacter baumannii is the is the fourth most commonly occurring micro-organism in bloodstream infections (BSIs) associated with central venous catheter (CVC) in Brazil [ 1 ]. Infections caused by multi-resistant A. baumannii that produce oxacillinase-type carbapenemases (OXA) are currently considered a clinical and epidemiological emergency. In some wards, the presence of A. baumannii producing OXA-23 has acquired an endemic character, highlighting the need for studies focusing on the prevention of infections caused by this pathogen, as well as policies to control its spread [ 2 , 3 ]. In the context of BSIs caused by A. baumannii bla OXA-23 , infection prevention is crucial for ensuring patient safety. One of the important actions that healthcare professionals must consider is the disinfection of needleless connectors (NCs) as they are attached to catheter hubs. Disinfecting NCs involves using physical or chemical methods to minimize the number of pathogenic micro-organisms present on the surface [ 4 ]. A study conducted in São Paulo, Brazil, suggests that disinfecting NCs before and after handling them, along with other procedures to prevent contamination, is crucial to minimizing the contamination rate at the surface of NCs [ 5 ]. Another study found that bacterial contamination was present in 44% of the NCs in the intensive care unit (ICU) [ 6 ]. The guidelines on NC disinfection vary. The Centres for Disease Control and Prevention (CDC) [ 7 ], National Health Surveillance Agency (Anvisa, Brazil) [ 8 ], Infusion Nursing Society (INS) [ 9 ], Epic3: National Evidence-Based Guidelines for Preventing healthcare-associated infections [ 4 ] and Royal College of Nursing (RCN) [ 10 ] do not specify the optimal disinfection procedure for the surface of NCs. The evidence for successful NC disinfection ranges from a minimum of 5 s of scrub time, and there is not always a clear specification of the drying time that should be allowed or the type of disinfectant product that should be used (such as chlorhexidine >0.5 in 70% isopropyl alcohol (IPA) or 70% IPA). Disinfecting devices such as NCs used in peripheral inserted CVCs (PIVCs) and CVCs is crucial for safe nursing practice. However, most guidelines regarding NC disinfection practices are based on the standards followed in the wealthiest countries such as the USA, Australia and European countries [ 7 , 9 , 11 , 12 ]. It is important for other countries to conduct initial studies that reflect their respective clinical practices, especially in Latin American countries and other medium- or low-income countries. The Brazilian reality could be taken as an example for such studies. The aim of this study was to establish the efficacy of disinfection procedures in reducing the bacterial load of A. baumannii bla OXA-23 in NCs.

Methods An in-vitro experimental study tested three disinfection procedures on two different NCs artificially contaminated with a strain of A. baumannii bla OXA-23 LA216 [ 13 ]. The NCs used in this study were the two-way intermediate extender's hub (Polifix®, B. Braun), and the needle-free valve (Safeflow®, B. Braun). The disinfectant procedures included were as follows: (1) take a sterile gauze and apply 1 mL of 70% ethanol, use mechanical friction to rotate the gauze in clockwise and counterclockwise direction for 10 s (180°), allow the area to dry for 5 s; (2) take a sterile gauze and apply 1 mL of Incidin® (Dräger), use mechanical friction to rotate the gauze in clockwise and counterclockwise directions for 10 s (180°), allow the area to dry for 5 s; and (3) rotate the 70% IPA single-use cap (Site-Scrub®, Becton Dickinson, BD) eight times clockwise and counterclockwise (for a total of 10 s) (180°), followed by 5 s of drying time as per the manufacturer's instructions. It is important to note that all procedures were conducted under sterile conditions using sterile materials. Each disinfection experiment was conducted in triplicate for technical replicates, and on different days. Three biological replicates were performed to ensure the reliability and reproducibility of the proposed method. Non-treated controls (NTCs) and sterility controls (negative controls) were also performed in all experiments. The NTCs were performed with bacterial contamination, without using any treatment. Bacterial inoculum and contamination of NCs A well-characterized strain of A. baumannii bla OXA-23 [ 13 ] was cultured and prepared as per the recommended guidelines, Methods for Dilution Antimicrobial Susceptibility Tests for Bacteria That Grow Aerobically [ 14 ]. The initial bacterial suspension (iBS), which contains ∼1.5 × 10 8 CFU (colony forming units), was prepared by adjusting the turbidity of McFarland Scale 0.5 (Newprov®) and then measuring it electronically using the DensiCHEKTM turbidimeter (BioMerieux®). To contaminate the NCs, iBS was diluted 100 times by mixing 10 μL of BS-A with 990 μL of 0.9% sterile saline solution. The resulting work bacterial suspension (wBS) contained 1.5 × 10 6 cfu. The NC devices were then immersed in 1 mL of the wBS in 15-mL sterile conical centrifuge graduated tubes for a timed duration of 5 min. After contamination, the devices were removed from the conical tubes using forceps and left to dry in a closed Petri dish for 60 min at 35 ± 1°C in a bacteriological oven SL-101 (SOLAB). Disinfection procedures The devices, except for the non-treated controls, underwent three different disinfection procedures after being contaminated. These procedures were carried out according to the manufacturer's instructions or in line with the recommended guidelines of clinical practice, such as those of INS [ 9 ], CDC [ 7 ] and Anvisa (Brazil) [ 8 ]. All disinfection procedures were conducted by the researcher using the same dominant hand. Table 1 summarizes the disinfection procedures. When disinfecting with 70% ethanol or Incidin®, 1 mL of the respective disinfectant was pipetted over the gauze for both the needle-free valve and the two-way intermediate extender's hub (with cap) situated outside the NC. Using forceps, the NC device was held, and the gauze was rotated clockwise and counterclockwise for 10 s (180°) with mechanical friction. The devices were then left to dry for 5 s after disinfection. The 70% IPA single-use cap (Site-Scrub®) disinfection procedures were performed in accordance with the manufacturer's recommendations. Different approaches were used in the two NCs. For the needle-free valve, the instructions were to remove the seal of Site-Scrub®, hold the needle-free valve with forceps, and apply mechanical friction by placing the Site-Scrub® in the middle of the needle-free valve; then, rotate the Site-Scrub® clockwise and counterclockwise eight times for 10 s (180°). Similarly, for the two-way intermediate extender's hub, the seal of Site-Scrub® was removed, and the cap was removed from the two-way intermediate extender's hub. Then, holding the two-way intermediate extender hub device with forceps, mechanical friction was applied by rotating the Site-Scrub® clockwise and counterclockwise eight times for 10 s (180°) in the centre of the connector. After disinfection, both the NC needle-free valve and the two-way intermediate extender's hub were dried for 5 s. Bacterial quantification All of the treated NCs and controls were immersed in a 15-mL conical centrifuge tube filled with 2 mL of 0.9% saline solution. The tubes were sealed, and vigorously mixed at maximum speed for 5 min using a Phoenix MOD AT56 vortex mixer. Subsequently, they were placed in an ultrasonic bath (UltraCleaner 1400 Unique) operating at a frequency of 40 kHz for 10 min. After vortex homogenization, 100 μL of each sonicated suspension was evenly spread over tryptic soy agar (TSA) in Petri dishes using a sterile disposable Drigalski T-shaped handle. The handle was moved in a circular motion until the suspension was dried. The Petri dishes were then incubated at 35 ± 1°C for 24 h in a bacteriological incubator (SL-101 from SOLAB) before counting cfu. Statistical analyses The study compared the number of CFU recovered from treated NCs and NTCs. The database was created using Microsoft Excel® Software 2016 (USA), and statistical analyses were conducted using MedCalc® software, version 19.1.7 (Belgium). The Kruskal–Wallis non-parametric test was utilized to examine and compare independent groups, and the Conover test was used for post-hoc analysis to determine the interaction between the disinfection procedures. Statistically significant differences were considered when the P -value was less than 0.05.

Results Of the 90 experiments conducted, 82 were considered for the findings as eight technical outliers were excluded. All the negative controls displayed the sterilization of the materials used in the research. Thirty-seven experiments were performed using two-way intermediate extender's hub, while the needle-free valve was used in 45 experiments. During the study, it was observed that the NC two-way intermediate extender's hub (used in PIVC) and the needle-free valve (used in PIVC and CVC) showed different results when it came to the adherence of A. baumannii bla OXA-23 . The NC two-way intermediate extender's hub had a higher number of bacterial cells adhered, compared with the needle-free valve. The NTC in the two-way intermediate extender's hub presented 342 CFU, while the needle-free valve showed 110 CFU, which shows that 67.83% less bacterial cells adhered. This can be explained by the fact that the needle-free valve has fewer grooves as compared with the NC's design. The experiments conducted in the two-way intermediate extender's hub showed that all disinfection procedures were efficacious. Among them, the 70% IPA single-use cap was the most efficacious, reducing the bacterial load by 87.28%, while the least efficacious was sterile gauze with 70% ethanol, with only 48.54% efficacy ( Supplementary Table S1 ). There was no difference in efficacy between sterile gauze treated with 70% ethanol and sterile gauze treated with Incidin®, with 48.53% and 48.88%, respectively, of bacterial load reduction. The experiment showed that the disinfection procedures used in two-way intermediate extender's hub were efficacious with a significance level of P =0.000812. Figure 1 compares the reduction in CFU in the interquartile range (sample variation) and median among all disinfection procedures. The 70% IPA single-use cap was the most efficacious disinfection procedure for the two-way intermediate extender's hub. Related to the experiments conducted in the needle-free valve, it was observed that all disinfection procedures were efficacious. The three disinfection procedures exhibited varying degrees of reduction ranging from 94.54% (70% IPA single-use cap) to 97.27% (sterile gauze with 70% ethanol) ( Supplementary Table S2 ). Based on the samples presented, it can be observed that the variance in the methods used was noticeable. The experiment conducted with sterile gauze and 70% ethanol showed a higher variance than the other methods. However, all methods of disinfection were efficacious, and there were no significant differences between the different treatments, as shown in Figure 2 .

Discussion In this in-vitro study, all the tested disinfection procedures were efficacious in reducing the A. baumannii bla OXA-23 load in NCs in a controlled environment. This is important because A . baumannii bla OXA-23 is an opportunistic pathogen, that can survive for extended periods in hospital settings, especially on inanimate surfaces – such as the catheter's connectors [ 15 ]. Inadequate NC decontamination can result in device contamination, which can lead to BSI [ 7 ]. According to the RCN [ 10 ], the cleaning, disinfection and sterilization processes for NCs should follow local policy and comply with manufacturers' guidelines. The protocols for these processes should be clearly stated in the organizational policies and procedures. However, the current guidelines vary in recommendations for disinfection procedures, making it challenging to understand and follow the best practices for NC disinfection [ [7] , [8] , [9] ]. In Brazil, Anvisa recommends the use of alcohol-based antiseptic solutions for disinfection, but it does not specify examples of disinfectant products to use or how much to use [ 8 ]. The guidelines encourage scrubbing the hub for 5–15 s. This study followed Anvisa [ 8 ] and other international guidelines by using a 10-s friction time for all the procedures [ 4 , 9 , 10 ]. A previous systematic review [ 16 ] showed that the greatest risk for catheter contamination after insertion is the contamination of the NC, with 33–45% of NCs being contaminated. Moreover, it showed compliance with disinfection as low as 10%. The review recommended scrubbing with 70% alcohol for 5–60 s and disinfecting NCs before any connection. Another systematic review with meta-analysis [ 17 ] showed that using alcohol-impregnated caps and alcoholic chlorhexidine gluconate together is more effective in reducing the rates of central line associated blood stream infection (CLABSI) than using 70% alcohol wipes. In this experimental study, it was found that 70% IPA was the most efficacious disinfection procedure for the two-way intermediate extender's hub. However, it should be noted that the experiment was conducted without the external cap that usually covers the hub, which was not in accordance with the manufacturer's recommendations. This could potentially affect the results and should be taken into consideration when analysing the findings. A clinical trial conducted in the USA and registered in the National Library of Medicine showed that 70% IPA disinfection solution was effective in achieving zero colony formation in NCs across the 295 units analysed [ 18 ]. The study found that there was no significant difference between the effectiveness of disinfection achieved through a 5-s scrub or a 15-s scrub with IPA. All of the disinfection procedures were efficacious in reducing contamination of the needle-free valve, with rates of above 90% reduction. However, previous studies did not include the use of Incidin® as a chemical disinfectant because it is not a standard method in international guidelines for NC disinfection [ 7 , 9 ]. The research team acknowledges that other active measures, such as bundles, are necessary to control catheter-related infections [ 19 , 20 ]. In the study, it was found that the needle-free valve had 67.83% less bacterial load adherence than the two-way intermediate extender's hub when used as an NTC. The adherence of A. baumannii to the needle-free valve was also found to be less. This finding was not premeditated. The literature shows that depending on NC design, it can retain more microbial cells [ 21 ]. With a vast number of NCs available, it is important that nurses know which to use and how to disinfect them effectively. Future randomized controlled trials focusing on the practice of disinfection procedures in Brazil are a necessary step in the prevention of catheter-related BSI. It is essential to develop safer practices in Brazil to reduce infection rates. International studies typically focus on the use of individual sterile pads with pre-applied disinfectant solution, called wipes/swabs [ 9 , 7 , 11 , 12 , 22 ]. However, some Brazilian hospitals use gauze with disinfectant products for NC disinfection procedures. It should be noted that this study has some limitations. Firstly, the pressure used in each disinfection procedure was not measured, even though all disinfection procedures were performed with the dominant hand of a single researcher. It is important to consider that different pressures can lead to different outcomes, and further research is required to analyse this aspect [ 23 ]. Secondly, future studies should test different disinfection times to determine the reduction of bacteria. Additionally, it is important to highlight that the efficacy of the Site-Scrub® device was tested only with 70% IPA, and this may have affected the results. Therefore, the efficacy can be associated with both the disinfectant product used (70% IPA) and the Site-Scrub® device. Lastly, this study only focused on the A . baumannii bla OXA-23 strain and did not consider other prevalent micro-organisms, such as coagulase-negative Staphylococcus [ 5 , 24 ]. This decision was made due to the availability of the strains and the timeframe of the study. In conclusion, the study found that all three disinfection procedures were efficacious in reducing the bacterial load of A. baumannii bla OXA-23 . Among the three procedures tested, the most efficacious one in disinfecting the two-way intermediate extender's hub was the 70% IPA single-use cap, rotated clockwise and counterclockwise eight times (180°) for 10 s, followed by 5 s of drying time. This study also found that there was lower adherence of A. baumanni bla OXA-23 in the needle-free valve compared with the two-way intermediate extender's hub. This reduction amounted to almost 68%. One of the possible reasons is the needle-free valve design, which has fewer grooves. Based on this, it is recommended to use needle-free valves in nursing practice. It is important that future studies be conducted to consider procedure variations, such as the pressure during the disinfection procedure and the amount of disinfectant products used.

Summary Aim This study aimed to verify the efficacy of disinfection procedures to reduce Acinetobacter baumannii bla OXA-23 bacterial load in needleless connectors that had been experimentally contaminated. Methods Two-way intermediate extender's hub and needle-free valve were contaminated with Acinetobacter baumannii bla OXA-23 . To disinfect them, the following procedures were carried out: sterile gauze with 70% ethanol, sterile gauze with Incidin®, and 70% isopropyl alcohol single-use cap, with eight times friction for 10 s, followed by 5 s drying time. The statistical tests Kruskal–Wallis and post-hoc Conover were performed using MedCalc®. Results A total of 82 experiments were conducted. All tested disinfection procedures were efficacious in reducing the A. baumannii bla OXA-23 load. The 70% IPA single-use cap was found to be the best method for disinfecting the two-way intermediate extender's hub (87.28%), while all the methods were efficacious for the disinfection of the needle-free valve (more than 90%). During the inoculation period, A. baumannii bla OXA-23 showed less adherence to the needle-free valve during the inoculation period, probably due to the device's design. Conclusion The three tested disinfection procedures using sterile gauze with 70% ethanol, sterile gauze with Incidin®, and 70% IPA single-use cap were found to be efficacious in reducing the bacterial load of A. baumanni bla OXA-23 in needleless connectors. Proper disinfection of needleless connectors is a crucial nursing practice to prevent bloodstream infections, as it significantly reduces the bacterial load present in the device. Keywords

CRediT author statement Camila Biazus Dalcin: Conceptualization, Methodology, Investigation, Formal analysis, Writing - Original Draft, Review & Editing. Thaís Cristine Marques Sincero: Methodology, Formal analysis, Writing - Review & Editing. Caetana Paes Zamparette: Methodology, Formal analysis, Writing - Review & Editing. Daniela Cristina Tartari: Methodology, Formal analysis, Writing - Review & Editing. Sabrina de Souza: Methodology, Formal analysis, Writing - Original Draft. Thiago Lopes Silva: Methodology, Formal analysis, Writing - Original Draft. Andreia Tomazoni: Methodology Formal analysis, Writing - Review & Editing. Patrícia Kuerten Rocha: Conceptualization, Methodology, Formal analysis, Writing - Original Draft, Review & Editing, Supervision. Funding sources This work was supported by the 10.13039/501100002322 Coordination for the Improvement of Higher Education Personnel in Brazil (CAPES) – financial support through scholarships (COD FINANCE 001). Conflict of interest The authors state that there is no conflict of interest.

Supplementary data The following is the Supplementary data to this article: Acknowledgements The team would like to acknowledge Dr Thaís Cristine Marques Sincero, Laboratory of Applied Molecular Microbiology (MIMA) at the Federal University of Santa Catarina (UFSC), Brazil, for the donation of the ATCC strain and some materials, and for allowing the use of their equipment. Dr Patricia Kuerten Rocha, Laboratory of Teaching, Research, and Extension in Child and Adolescent Health (GEPESCA) at UFSC, Brazil, for material donation that helped us conduct this study. Dr Ana Gales, ALERTA Laboratory at Federal University of São Paulo (UNIFESP), Brazil for the permission to use a well-characterized control strain. Dr Marcos José Machado, UFSC, for his support with statistical analysis, and Mayara Lameira Vieira and Paula Giarola Fragoso de Oliveira for their invaluable assistance in the laboratory during the project development.

CC BY

no

2024-01-16 23:43:45

Infect Prev Pract. 2023 Dec 1; 6(1):100328

oa_package/70/39/PMC10788527.tar.gz

PMC10788531

38000659

Results Creation of dCas9-CtBP chimeras to regulate gene expression To investigate the function of the CtBP C-terminal IDR and differences in gene regulation by the CtBP(L) and CtBP(S) isoforms in Drosophila , we employed CRISPRi ( 17 ). These two isoforms are created through alternative splicing, with CtBP(L) having a ∼130 amino acid domain and CtBP(S) a ∼30 amino acid domain, which only share the first 20 residues with one another ( 8 ). We fused the coding sequence of each CtBP isoform to a nuclease dead Cas9 (dCas9) enzyme to recruit CtBP corepressors to target promoters using gene-specific guide RNAs (gRNA; Fig. 1 A ). dCas9-CtBP(L) and dCas9-CtBP(S) are expressed in S2 cells, according to Western blot ( Fig. S1 ). We expressed the chimeric proteins in the wing discs of third instar larvae (L3) using the nubbin - GAL4 driver, which is predominantly expressed in the L3 wing pouch. Flies homozygous for both nubbin-GAL4 and UAS:dCas9-CtBP were crossed to flies expressing two tandem gRNAs targeting diverse promoters ( Fig. 1 B ) ( 18 ). These gRNAs were obtained as fly lines from the Bloomington Drosophila Stock Center ( Table S1 ). We previously tested dCas9-Rb chimeras in L3 discs, where we observed gene-specific effects after targeting ∼30 different gene promoters; here, we targeted many of the same promoters with the CtBP isoforms ( Table S1 ) ( 19 ). The epithelial cells of the developing wing are a highly sensitive tissue that has been used to measure developmental perturbation of a number of regulatory pathways. To screen for genetic effects after targeting chimeras in cells of the L3 wing discs, we allowed the flies expressing the three transgenes to grow to adulthood and then assessed adult wing phenotypes from targeting each promoter, as has been previously done in Drosophila CRISPR activation screens ( 20 ). We note that the nubbin - GAL4 >UAS:dCas9-CtBP flies crossed to a nontargeting gRNA control fly line (QUAS) produced mild wing phenotypes, consisting chiefly of supernumerary bristles ( Fig. 2 A ). We presume that ectopic CtBP, even when fused to dCas9, may interact with diverse endogenous CtBP binding sites on the genome, leading to these mild phenotypes. The QUAS control gRNAs used here did not produce phenotypes with dCas9-Rb corepressor fusions tested previously, so the phenotypic effect is CtBP-specific ( 19 ). Diverse effects of CtBP isoforms We recruited CtBP(L) and CtBP(S) to a number of promoters, with specific effects observed only on a few promoters ( Table S1 ). Here, we detail the effects of targeting the E2F2/Mpp6 bidirectional promoter, the insulin receptor ( InR ) promoter, and the promoter of Acf , a nucleosome remodeling subunit ( Fig. 2 ). Targeting CtBP(S) to the divergent E2F2/Mpp6 promoter produced small wings with severe morphological defects, similar to that seen with dCas9-Rb fusions ( Fig. 2 B ) ( 19 ). Intriguingly, CtBP(L) did not produce this phenotype but instead produced much milder effects, including wings with ectopic veins and supernumerary bristles ( Fig. 2 B ). dCas9 alone did not produce any phenotypic effect, indicating that the observed phenotypes are CtBP specific. The clear difference between targeting the long and short isoforms on this promoter suggests that the long CTD may inhibit CtBP’s gene regulatory activities. The strong CtBP(S) effect is only seen when using two gRNAs; recruitment using the individual gRNAs at the same locus produced milder effects, such as ectopic veins seen with the CtBP(L) isoform when both gRNA were used ( Fig. S2 ). Interestingly, the number of wings with supernumerary bristles was less than that observed for the nontargeting control QUAS gRNA. We speculate that nonspecific CtBP overexpression effects are suppressed by targeting the chimeric protein to specific DNA locations using these single gRNAs. Targeting the InR promoter produced adult wings with mild phenotypes, similar to those produced with the nontargeting QUAS gRNA control, so this effect is difficult to distinguish from a mild overexpression phenotype rather than specific InR targeting ( Fig. 2 C ). Clearly, positioning the CtBP chimeras near the InR transcriptional start site does not strongly affect the wing, although we know that positioning dCas9-Rb chimeras at this promoter does impact development and transcription ( 19 ). This distinct effect is consistent with CtBP promoter selectivity, a property illustrated from recent high-throughput assays ( 16 ). Recruitment to the Acf promoter region generated a different spectrum of phenotypes. In this case, a significant proportion of wings from the dCas9 control cross showed supernumerary bristles—evidence that dCas9 alone can disrupt gene function in certain locations. Notably, the position of one of the gRNAs used here is 3′ of the initiation site for the divergently transcribed Mccc1 gene, a position from which transcriptional inhibition is possible by dCas9 ( 21 ). Over and above the background of this dCas9 effect, the CtBP fusions had unique, specific effects, with CtBP(S) causing a larger proportion of wings to be affected (80%) than CtBP(L) (60%; Fig. 2 D ). Results from these targeted promoters indicate that CtBP exhibits gene-specific effects, and that in some cases, CtBP(S) has a more pronounced effect than CtBP(L). CtBP(S) is a more potent transcriptional repressor of Mpp6 than CtBP(L) Given the noticeable difference in wing phenotype as a result of targeting the two CtBP isoforms to the E2F2/Mpp6 shared promoter, we measured transcript levels of both of these genes in the L3 wing disc using RT-qPCR. The two gRNAs targeting E2F2/Mpp6 bind at −577 and −672 relative to the E2F2 TSS, and at −18 and +57 relative to the Mpp6 TSS ( Fig. 3 A ). CtBP(S) targeting led to ∼50% repression of the Mpp6 gene, whereas CtBP(L) effects were significantly weaker (∼25%) and statistically indistinguishable from those of dCas9 alone ( Fig. 3 C ). Effects on E2F2 were more modest, with only ∼10% decrease in E2F2 expression resulting from targeting by dCas9 and dCas9-CtBP(L), and no statistically significant change after targeting with dCas9-CtBP(S) ( Fig. 3 B ). The greater impact on Mpp6 is likely a reflection of the inherent short-range of action of many transcriptional repressors and corepressors, which may influence chromatin structure over a span of a nucleosome ( 19 , 22 ). In this system, we did not find complete suppression of gene expression as noted in other transcriptional assays. However, an important caveat is that the level of repression measured may be an underestimate because the nubbin driver is expressed only in the wing pouch, while we used the entire wing disc for RT-qPCR analysis. Interestingly, although CtBP(L) repressed E2F2 and Mpp6 to the same extent as dCas9 alone, it clearly showed more pronounced phenotypic effects in the adult stage. It may be that the CtBP(L) does have some specific activity in this setting (the trend, though not statistically significant, was slightly stronger than dCas9 alone). Alternatively, CtBP(L) may exert an effect later in development that we do not measure at this timepoint. It is likely that the overt structural defects noted in the adult wing reflect perturbations to the complex gene regulatory networks that control wing development, which a single transcriptional measurement cannot capture. Position-sensitive CtBP repression in cell culture Many tests of CtBP function have relied on transiently transfected reporter genes; however, few studies have directly compared repression activity on the same genes in their endogenous chromosomal location. To further assess CtBP(L) and CtBP(S) function and compare our in vivo results to traditional reporter assays, we expressed the dCas9-CtBP chimeras in S2 cells, using an Mpp6 reporter which we have previously demonstrated is susceptible to repression by dCas9-Rb proteins ( 19 ). Here, we employed seven individual gRNAs to test for possible position effects on this 1 kb promoter region ( Fig. 4 A ). Both CtBP(S) and CtBP(L) showed strongest effects with gRNA 2 and 5; dCas9 alone did not mediate significant repression from the gRNA 2 position but did from gRNA 5, likely due to steric effects ( Fig. 4 , B – D ). The dCas9 control did not mediate repression from any other site, clearly different from the CtBP effects with gRNAs 1, 2, and 3. A simple distance effect, with stronger repression proximal to the transcriptional start site, was not evident. Additionally, CtBP(S) appeared to be more effective at the more distal gRNA 1 and B positions than near the TSS, at 4. Overall, it is striking that CtBP(L) performed similarly to CtBP(S) on this reporter, given the clear differences noted for activity in the native chromosomal context.

Discussion Here, we created novel dCas9-chimeras to CtBP corepressor proteins to compare their impact on gene expression in an in vivo system. Our study of Drosophila CtBP(L) and CtBP(S) isoforms using this CRISPRi approach has revealed that the two isoforms of this corepressor do exhibit different functional potential. Additionally, CtBP itself shows promoter selectivity, consistent with the findings of the Stark laboratory, where CtBP(S) was assayed against a wide spectrum of putative enhancers ( 16 ). Our data suggest that CtBP proteins are involved in selective modulation of their gene targets, consistent with a “soft repression” form of regulation that may characterize many repressive interactions in the cell ( 23 ). Evolutionary conservation of the CTD of CtBP indicates that this portion of the corepressor must be of importance; yet, most assays employed in previous studies have not identified a difference in function at the transcriptional level ( 6 , 7 ). One possible explanation is that the domain is involved in other aspects of CtBP biology, such as turnover or intracellular targeting, which may be overlooked in overexpression assays. Alternatively, its function in gene regulation may not have been identified yet, as the context in which CtBP has been assayed is limited; even the recent high-throughput assessment of GAL4-CtBP(S) using STARR-seq was carried out with transient transfections, and the significance of the CTD were not assessed ( 16 ). There may be diverse roles for this IDR; however, our results strongly point to a transcriptional regulatory potential for the unstructured CtBP CTD. Few studies have tested the impact of CtBP proteins with or without the conserved, long CTD on expression of endogenous genes, with the exception of genomic rescue experiments that demonstrated that viability is possible with either a CtBP(S) or CtBP(L) rescue construct ( 15 ). However, the survivors from genomic rescues employing single isoforms showed a variety of phenotypes, including elevated embryonic lethality and aberrant wing development, indicating that limiting expression to one isoform alone does not fully satisfy developmental demands. Here, by directly testing CtBP isoforms using CRISPRi on endogenous genes in Drosophila , we uncovered a striking difference between CtBP(L) and CtBP(S). On the Mpp6 promoter, CtBP(S) was a potent repressor of gene expression and caused a severe wing phenotype, while CtBP(L) was much milder in its transcriptional and phenotypic effects. Many studies probing IDR functions have relied on high-throughput assays to characterize IDRs en masse, and those focused on specific IDRs and proteins with disordered domains often use cell culture assays to uncover function. Therefore, it is important that with a direct comparison of our transcriptional effectors using transiently transfected reporters in S2 cells, we are unable to recapitulate the clear difference between CtBP(S) and CtBP(L) observed when targeting genes in a chromosomal context in the developing organism. Our finding that the CtBP(L) isoform is less active only on the chromatinized endogenous E2F2/Mpp6 regulatory region provides support for the notion that the CTD regulation is chromatin related. By combining an in vivo approach with CRISPRi, which is rarely done for dissecting mechanisms of gene regulation, we uncovered that the unstructured and highly conserved CTD of CtBP does in fact play a role in gene regulation. Additionally, our CRISPRi system ensures targeting to the promoter; thus, the CTD regulatory impact is likely to be at the level of transcriptional action, rather than promoter binding. What might be the molecular action of this IDR on CtBP itself? Biochemical assays have shown that this intrinsically disordered domain is not required for NAD(H) binding or oligomerization—properties which are necessary for in vivo functionality ( 7 , 23 , 24 , 25 ). The CTD of mammalian CtBP has been shown to be a target of posttranslational modifications, including phosphorylation and sumoylation, which may affect conformation or protein–protein interactions of this domain ( 8 ). It is interesting that a different eukaryotic dehydrogenase-like corepressor, NPAC/GLYR1, similar to CtBP, forms tetramers and possesses an IDR that is involved in functional contacts with histone-modifying lysine demethylases ( 26 ). A similar function for the CtBP CTD may be uncovered in the future, but deeper understanding will require further biochemical and molecular genetic studies.

The C-terminal binding protein (CtBP) is a transcriptional corepressor that plays critical roles in development, tumorigenesis, and cell fate. CtBP proteins are structurally similar to alpha hydroxyacid dehydrogenases and feature a prominent intrinsically disordered region in the C terminus. In the mammalian system, CtBP proteins lacking the C-terminal domain (CTD) are able to function as transcriptional regulators and oligomerize, putting into question the significance of this unstructured domain for gene regulation. Yet, the presence of an unstructured CTD of ∼100 residues, including some short motifs, is conserved across Bilateria, indicating the importance of maintaining this domain over evolutionary time. To uncover the significance of the CtBP CTD, we functionally tested naturally occurring Drosophila isoforms of CtBP that possess or lack the CTD, namely CtBP(L) and CtBP(S). We used the CRISPRi system to recruit dCas9-CtBP(L) and dCas9-CtBP(S) to endogenous promoters to directly compare their transcriptional impacts in vivo . Interestingly, CtBP(S) was able to significantly repress transcription of the Mpp6 promoter, while CtBP(L) was much weaker, suggesting that the long CTD may modulate CtBP’s repression activity. In contrast, in cell culture, the isoforms behaved similarly on a transfected Mpp6 reporter gene. The context-specific differences in activity of these two developmentally regulated isoforms suggests that the CTD may help provide a spectrum of repression activity suitable for developmental programs. Keywords Abbreviations C-terminal domain C-terminal binding protein CtBP-short CtBP-long guide RNA intrinsically disordered region Reviewed by members of the JBC Editorial Board. Edited by Brian D. Strahl

Eukaryotic transcription factors and cofactors are rich in unstructured domains; these proteins have a higher percentage of predicted intrinsically disordered regions (IDRs) than the average protein ( 1 ). Some of these IDRs have been shown to participate in specific transcriptional processes, sometimes through promoting the formation of phase separated condensates ( 2 ). For example, the C-terminal domain (CTD) of RNA polymerase II, a well-studied IDR, is a platform for association of factors involved in capping, splicing, and polyadenylation ( 3 ). The N-terminal IDR of the androgen receptor has also recently been found to be necessary for condensate formation and transcriptional activity on enhancers ( 4 ). IDRs in a plethora of other transcriptional regulators are thought to similarly play roles related to gene regulation, although most remain understudied ( 2 ). Recent high-throughput analyses to determine the function of IDRs across the eukaryotic proteome have uncovered important motifs, interacting partners, and putative gene regulatory functions of some of these uncharacterized IDRs ( 2 ). However, the specific roles of many IDRs present in these factors are still unknown. Tools to probe the function of certain IDRs and examine their gene regulatory roles in a physiologically relevant context and in a developing organism are necessary to delineate mechanisms of gene regulation by these IDRs and start to assign in vivo functions to them. A prominent IDR that has not been well-studied is the CTD of the C-terminal binding protein (CtBP). CtBP is a highly conserved transcriptional corepressor that plays a role in cell differentiation and apoptosis and has been implicated in a variety of human cancers ( 5 ). This IDR of approximately 100 amino acids is not necessary for oligomerization of CtBP and may not be necessary for gene regulation, putting into question the significance of the CtBP CTD ( 6 , 7 ). Yet, our recent study shows that the CtBP CTD is highly conserved across Bilateria, and despite possessing overall lower sequence conservation than other parts of the protein, it features conserved short linear motifs within this predicted unstructured domain ( 8 ). A few lineages such as roundworms and flatworms have novel, derived CTD sequences that are predicted to form intrinsic structures of unknown function. However, the deep conservation in primary sequence, length, and unstructured property of the CtBP CTD in bilaterians suggests that this IDR plays an important role, perhaps in gene regulation ( 8 ). Mammalian genomes encode the CtBP1 and CtBP2 paralogs, which play overlapping and nonredundant roles in regulating expression of genes involved in apoptosis, the epithelial to mesenchymal transition, and cell differentiation ( 9 , 10 , 11 , 12 ). The CtBP1 and CtBP2 CTDs exhibit 50% sequence conservation, which is much lower than that of the central core dehydrogenase domain, which is used for oligomerization, NADH binding, and in vitro dehydrogenase activity ( 6 , 8 ). Interestingly, CtBP isoforms without the CTD exist in certain tetrapods such as birds and amphibians ( 8 ). Likewise, in Drosophila , the single CtBP gene encodes multiple splice forms, including short isoforms that lack the CTD (CtBP-short, or CtBP(S)) and others that retain the long CTD (CtBP-long, or CtBP(L)) ( 8 , 13 ). These two major isoforms differing in the retention or loss of the IDR are coexpressed in fly development ( 13 ). Thus, Drosophila is an appropriate model system to test a possible role of the CtBP CTD in gene regulation and assign a function to this elusive IDR. Previous work using GAL4-CtBP fusions in the Drosophila embryo demonstrated that the two isoforms have similar repressive effects on an even-skipped -lacZ reporter, and both isoforms individually rescue a CtBP null fly, albeit with some different phenotypes in the wing ( 14 , 15 ). Thus, the CtBP CTD does not seem to play an essential role for completion of developmental programs under laboratory conditions. The expression pattern of the two isoforms exhibit developmentally distinct profiles; CtBP(S) is expressed throughout development, while CtBP(L) is highly expressed in the embryonic stage ( 13 ). The fact that short isoforms have been independently derived in other insects, such as Hymenoptera, and in other lineages in Bilateria suggests that expression of both isoforms is somehow important ( 8 ). The strict evolutionary conservation in these lineages of CtBP isoforms with and without the CTD indicates that both are functional, but a role in gene expression has remained unclear, compelling us to directly compare the activity of CtBP isoforms in vivo . Here, we have made use of precise genetic tools in Drosophila to probe the function of the fly CtBP isoforms, CtBP(L) and CtBP(S), to uncover the role of the C-terminal IDR in regulating gene expression. Specifically, we used the CRISPRi system in the developing fly to assess the function of chimeric dCas9-CtBP proteins targeted to diverse gene promoters in vivo . This method allowed us to compare the activity of the long and short isoforms on the same loci in fly wing tissue and compare the results to those targeted to transfected reporters in cell culture. We found that when assessed on endogenous targets, CtBP(S) is a more potent repressor of the Mpp6 promoter than CtBP(L) but that this difference in repression ability is not observed on a transiently transfected Mpp6 -luciferase reporter. Thus, in some contexts, the disordered CTD seems to provide a regulatory function, but the difference observed between endogenous gene regulation and transient transfections raises the possibility that the effect may be chromatin dependent. Additionally, gene promoters targeted here had differential sensitivity to CtBP recruitment, indicating a further level of regulatory specificity, in accord with recent high-throughput assays ( 16 ). Experimental procedures Plasmids used in this study To create UAS:dCas9-CtBP constructs, the FLAG-tagged (DYKDDDDK) coding sequences for CtBP(L) and CtBP(S) were used, as described previously ( 14 ). These coding sequences were amplified from their parent vector using 5′ Pac I and 3′ Xba I sites and inserted in place of Rbf1 in the UAS:dCas9-Rbf1 plasmid described previously ( 19 ). CtBP(L) is isoform F, and CtBP(S) is a combination of isoform E and J, based on Flybase nomenclature. The Mpp6 -luciferase reporter construct uses the Mpp6 promoter, which includes the Mpp6 5′UTR, to drive luciferase expression, as was described previously ( 19 ). The gRNA plasmids used in transfections were described previously and target different sites of the E2F2/Mpp6 bidirectional promoter ( 19 ). Transgenic flies Flies were fed on standard lab food (molasses, yeast, corn meal) and kept at room temperature in the lab, under standard dark-light conditions. The nubbin - GAL4 fly line was obtained from the Bloomington Drosophila Stock Center (BDSC; #25754) and was maintained as a homozygous line with a Chr 3 balancer obtained from BDSC #3704 (w[1118]/Dp(1; Y)y[+]; CyO/Bl [1]; TM2, e/TM6B, e, Tb [1] ). Homozygous UAS:dCas9-CtBP flies were generated by using the φ C31 integrase service at Rainbow Transgenic Flies Inc. #24749 embryos were injected with each dCas9-CtBP construct to integrate into Chr 3, landing site 86Fb. Successful transgenic flies were selected through the mini- white selectable marker expression in-house and maintained as a homozygous line with Chr 2 balancer (from BDSC #3704). nubbin - GAL4 and UAS:dCas9-CtBP homozygous flies were crossed to generate double homozygotes ( nubbin - GAL4 >UAS:dCas9-CtBP), using the Chr 2 and Chr 3 balancers (from #3704) These flies are donated to the Bloomington Drosophila Stock Center, and fly line numbers are indicated in Table S3 . sgRNA fly lines were obtained from the BDSC (fly line numbers indicated in Table S1 ). Homozygous nubbin-GAL4 >UAS:dCas9-CtBP flies were crossed to homozygous gRNA flies to generate triple heterozygotes (−/−; nubbin - GAL4 /sgRNA; UAS:dCas9-CtBP/+) that are used for all fly experiments described here. Genotyping flies All flies generated in this study were genotyped at the adult stage. Flies of each genotype were homogenized (1 fly/tube) in 50 μl squish buffer (1M Tris pH 8.0, 0.5 M EDTA, 5M NaCl with 1 μl of 10 mg/ml Proteinase K for each fly). Tubes were incubated at 37 °C for 30 min, 95 °C for 2 min, centrifuged at 14,000 RPM in an Eppendorf Centrifuge 5430 for 7 min, and stored at 4 °C. Following PCR amplification, amplicons were cleaned using Wizard SV-Gel and PCR Clean-Up System and sent for Sanger sequencing. Imaging adult wings Adult wings were collected from ∼50 male and female 1- to 3-day-old adults. They were stored in 200 proof ethanol in −20 °C until mounted. Wings were removed, mounted onto Asi noncharged microscope slides using Permount, and photographed with a Canon PowerShot A95 camera mounted onto a Leica DMLB microscope. Images were all taken at 10X magnification and using the same software settings. Wing disc dissections and RT-qPCR Fifty third instar wing discs per biological replicate were dissected from L3 larvae and placed in 200 μl Trizol (Ambion TRIzol Reagent) and stored in −80 °C until use. RNA was extracted using chloroform and the QIAGEN maXtract High Density kit and stored in −80 °C. cDNA synthesis was performed using applied biosystems High Capacity cDNA Reverse Transcription Kit. RT-qPCR was performed using SYBR green (PerfeCTa SYBR Green FastMix Low ROX by Quantabio) and measured using the QuantStudio 3 machine by applied biosystems. Two control genes were measured and averaged ( Rp49 , RpS13 ) for all samples to provide a normalization standard to account for differences in RNA content in individual samples. To assess specific effects of targeted dCas9 proteins on promoters, E2F2 and Mpp6 levels were also measured in control wing discs obtained from crossing dCas9 to a nontargeting gRNA (QUAS). Primers used are found in Table S2 . RT-qPCR was performed on three biological replicates with two technical duplicates. Student’s t test (two tailed, p < 0.05) was used to measure statistical significance. Error bars indicate SD Luciferase reporter assays Reporter assays were performed as described previously but with dCas9-CtBP(L) and dCas9-CtBP(S) effectors used here ( 19 ). Western blot Drosophila S2 cells were grown in 25 °C in Schneider Drosophila medium with glutamine (Gibco) containing 10% FBS and 1% penicillin-streptomycin (Gibco). 1.5 million cells were cotransfected with Effectene Transfection Reagent (Qiagen), according to manufacturer’s protocol. 250 ng of actin - GAL4 (Addgene #24344) and 250 ng of UAS:dCas9-CtBP effectors were cotransfected in 6-well plates. Cells were harvested 3 days post-transfection and lysed using S2 lysis buffer (50 mM Tris, pH 8.0; 150 mM NaCl; 1% Triton X-100), followed by boiling with Laemmli buffer. 100 μg of cell lysates were separated on a 4 to 20% resolving gel (Bio-Rad Mini-PROTEAN TGX Precast Gel #456–1094), transferred to a PVDF membrane for analysis using anti-FLAG (Sigma Aldrich #F3165, 1:10,000), and anti-CtBP (DNA208; ( 13 )). Blocking with both primary and secondary antibodies was performed in 5% milk-TBST (500 mM Tris-HCl, pH 7.4, 150 mM NaCl, 0.1% Tween 20). Blots were developed using HRP-conjugated GaM and GaR secondary antibodies (Pierce) and imaged using SuperSignal West Pico chemiluminescent substrate. Data availability The data supporting the findings of this study are available within the article and in the supplementary materials . Supporting information This article contains supporting information ( 13 ). Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article.

Supporting information Acknowledgments We would like to thank members of the Arnosti lab for their thoughtful suggestions and the Michigan State University RTSF and plasmidsaurus for sequencing plasmids. Author contributions A.-M. R. and D. N. A. conceptualization; A.-M. R., M. S. methodology; A.-M. R. data analysis; A.-M. R. writing–original draft; A.-M. R., M. S., and D. N. A. writing–reviewing and editing; D. N. A. formal analysis. Funding and additional information This work was supported by the National Institute for General Medical Sciences grant (number R01GM124137 ) to D. N. A., the National Institute of Child Health and Development grant (number F31HD105410 ) to A. M. R., and the BEACON luminaries grant to M. S.

CC BY

no

2024-01-16 23:43:45

J Biol Chem. 2023 Nov 23; 300(1):105490

oa_package/01/c5/PMC10788531.tar.gz

PMC10788534

38043798

Results Identification of NOTCH1 proximal interacting proteins using BioID in HEK293 cells Strong gain-of-function mutations in NOTCH1 leading to ligand-independent accumulation of NICD in the nucleus is a common event in human cancers, and expression of a truncated NICD in many different cell types in mice can drive spontaneous tumor formation ( 7 , 22 , 23 , 24 ). Therefore, understanding proximal interacting proteins in NOTCH1 complexes will be instrumental to define its role in tumorigenesis at the molecular level. To identify such proteins, we employed a second generation BioID system ( Fig. S1 ), which utilizes a modified, smaller Aquifex aeolicus biotin ligase (BirA∗- R40G), called BioID2 ( 18 ). The BioID2 was fused to the N terminus of the truncated NICD protein and BioID2-only was used as a control ( Fig. 1 A ). In order to minimize artificial interactions and protein instability caused by overexpression of the bait proteins, we utilized a doxycycline-inducible system in human HEK293 stable cell line allowing moderate and inducible bait protein expression ( Fig. S2 ). We chose to use HEK293 cells because it is a highly transfectable cell line and has been used successfully by us and others for large-scale BioID pull-downs of diverse types of bait proteins ( 15 , 21 , 25 , 26 ). Each HEK293 cell line was validated by immunofluorescence (IF) ( Fig. 1 B ) and Western blot (WB) ( Fig. 1 C ) for fusion-protein expression and biotinylation, revealing that their expression levels in nucleus and overall biotinylation were comparable. As expected, the BioID2 protein was localized to both the cytoplasm and the nucleus, whereas BioID2-NICD was localized to the nucleus only ( Fig. 1 B ). Each cell line was processed in biological triplicate and subjected to affinity purification of biotinylated proteins for identification of proximal prey proteins via semiquantitative tandem MS ( Fig. S2 ). Peptide and protein identification, intensity quantification, and data analysis were performed to identify and summarize proximal proteins in Table S1 , A and B . Overall, a total of 133 BioID candidate interaction proteins were identified ( Table S1 C ). The number and intensity of the recovered peptides indicate that MAML1 and GATAD2B are the closest components of the Notch activation complex, and their names are highlighted in larger font in Figure 1 D . Other major Notch pathway components such as RBPJ, MAML2, and NOTCH2 were also recovered. Prominently, from this list, 10 of the proteins were previously known interacting proteins (as determined from BioGRID ( 27 )) and are highlighted (red letters) in Figure 1 D . Altogether, these results validate our BioID-identification strategy. Identification of NOTCH1 proximal interacting proteins using BioID in NIH3T3 cells Crossover studies across different cell types and different species suggest that Notch1 may have a dynamic set of proximal interacting proteins that activate common and diverse target genes under different circumstances ( 28 , 29 , 30 ). To understand more about those Notch1-proximal proteins in different cell types, we performed BioID studies in the mouse embryonic fibroblast cell line NIH3T3 (also called 3T3) ( Figs. 2 A and S2 ). Each 3T3 cell line was validated by IF ( Fig. 2 B ) and WB ( Fig. 2 C ) for fusion-protein expression and biotinylation, revealing their expression levels in the nucleus and that overall biotinylation was comparable among three biological replicates. Raw and analyzed proteomic data were summarized in Table S2 , A and B . A total of 435 BioID candidate interaction proteins were identified ( Table S2 C ). The number and intensity of the recovered peptides indicated that MAML1 and GATA2B are the closest components of the Notch activation complex among many known NOTCH1 interactors, including SMCHD1, HCFC1, and SNW1. Other major Notch pathway components such as RBPJ and NOTCH2 were also recovered. Prominently, from this list, 28 of the proteins were previously known interacting proteins of NOTCH1 (as determined from BioGRID ( 27 )) and are highlighted (red letters) in Figure 2 D . Moreover, 59 common proximal interacting proteins were shared between HEK293 and 3T3 cells ( Fig. 3 A ). Altogether, these results validate our BioID-identification strategy in a second cell type. However, the majority of proteins identified in each cell type are distinct, supporting the reasoning that Notch has complex and dynamic relationships with various nuclear cofactors in any given context ( 7 ). Functional characterization of NOTCH1 core-proximal proteins reveals key pathways involved in human cancer and other diseases Constitutively active Notch in tumor cells may generate stronger signals of longer duration, resulting in gain-of-function interactions that do not exist under physiological conditions. Our BioID study attempted to mimic those conditions in tumor cells to capture previously unidentified proximal interacting proteins of Notch1. Furthermore, the common oncogenic role of NICD in various cell types suggests that NOTCH1 may regulate some common transcriptional programs and pathways through a shared set of common proximal proteins. This prompted us to focus on analyzing those common proteins identified in at least two cell types or studies, including those identified in HEK293 and 3T3, HEK293 and BioGRID, and 3T3 and BioGRID ( Fig. 3 A ). A total of 83 common Notch1 proximal interactors, referred to as core-proximal proteins in this study, were identified, and summarized in Table S3 A . Gene ontology analysis of these 83 core-proximal proteins revealed that the majority (79%) of them were localized in the nucleus, consistent with the nature of the NICD protein ( Fig. 3 B ). Notably, we identified the plasma membrane proteins, FLOT1 and MARCKS that can, like NOTCH1 and NOTCH2, also translocate into the nucleus ( 31 , 32 ). Likewise, candidate proteins listed in the cytoplasm, extracellular space and elsewhere may be able to translocate into the nucleus to interact with NICD ( Table S3 B ). For example, AKR1A1, RAI1, CFDP1, and RBM33 have been reported to have functional roles in the nucleus ( 33 , 34 , 35 , 36 ). Protein function analysis showed that many of the proximal proteins have roles in transcription regulation and enzyme processes ( Fig. 3 C ). Approximately 39% of the core-proximal proteins have other functions ( Table S3 B ). Not surprisingly, the disease most associated with NOTCH1 core-proximal proteins was predicted to be cancer ( Fig. 3 D ). Other diseases are linked to nearly every major system of our body and inflammatory response, consistent with the important role of Notch1 signaling in development, homeostasis, and viral infection ( Table S3 C ). Ingenuity pathway analysis (IPA) predicted 37 canonical signaling pathways for Notch1 core-proximal proteins ( Table S3 D ). “Notch signaling” and “DNA methylation and transcriptional repression signaling” were the top two most prominent of the predicted signaling pathways for Notch1 proximal proteins followed by many interesting pathways such as sumoylation, granzyme A, TR/RXR, BER, adipogenesis, and WNT/β-catenin signaling pathways ( Fig. 3 E ). However, cross talk between Notch signaling and other pathways remains to be determined. Protein networks of NICD proximal interactors reveal key regulators and modular complexes that contribute to pleiotropic Notch functions To understand the functional and biochemical relationships between the identified interactors of NICD, we conducted PPI network analysis of 83 core-proximal proteins ( Table S4 A ). We observed that most of the identified NICD-proximal proteins are significantly associated ( Fig. S3 ) and are related to several functional classes of proteins ( Fig. 4 ). These include chromatin-modifying interactors as subunits of chromatin-remodeling modular complexes SWI/SNF ( e.g. npBAF) and nucleosome remodeling and deacetylating (NuRD), and complex subunits in regulation of the mitotic cell cycle. Some proteins have been previously reported to be physically associated with NOTCH1 such as histone deacetylase (HDAC)1, GARAD2B, CHD4, SMARCA4, SMARCC2, PDS5A, and SMCHD1 ( 14 ). PHF21A (a subunit of the corepressor of repressor element-1 silencing transcription deacetylase complex (CoREST) and BHC corepressor complex that acts by deacetylating and demethylating specific sites on histones) and the histone demethylase Jumonji domain containing 1C (JMJD1C) were also detected ( 37 , 38 , 39 ). Notably, among NICD core-proximal proteins we found abundant transcriptional regulatory proteins that regulate gene expression at stages of transcriptional initiation and elongation ( Table S4 B ). These include well-characterized coactivators, such as NCOA6 and SNW1, and corepressors, such as NCOR1 and NCOR2, subunits of the negative elongation factor complex, as well as known (FOXK1, TRPS1, RAI1, and ZNF281) or putative transcription factors (ZNF687, WIZ, ZMYM4, and DIDO1). For example, direct genomic targets of TCF20 and TRPS1, a lineage-specific transcription factor, have remained poorly characterized because it may affect transcription positively or negatively as a component in various chromatin complexes depending on the cell types ( 40 , 41 , 42 ). Our NICD core-proximal interactors also comprise proteins involved in DNA repair and replication including WRNIP1, replication factor C (RFC)1, TOP2B, and C11orf30 (also known as EMSY). Previous studies have reported that RFC1 and TOP2B are physically associated with NICD, and NICD is also functionally associated with the RFC complex ( 14 , 43 ). Our data also highlight interactions with proteins involved in RNA processing, such as RNA-binding proteins (RBM10 and XPO5) and subunits of spliceosomal complex (DHX15 and DDX17). Moreover, interactions between NICD and components of other signaling pathways, such as the Rho GTPase family member RhoG and the WNT canonical signaling central mediator β-catenin (CTNNB1), were also recovered. In agreement with others’ reports ( 14 , 21 , 44 , 45 ), we also uncovered interactions with protein-modifiers (MARCKS, USP7, USP34, PPIL4, and PIAS2). For example, USP7 has previously been implicated in the regulation of NOTCH1 protein stability and activation ( 44 , 45 ). Hence, NICD interacts with diverse complexes and regulators that may reflect pleiotropic Notch functions. Essential interactors in the NOTCH1 protein network as potential drug targets The centrality-lethality hypothesis postulates that protein nodes with higher centrality in a network are more likely to produce a lethal phenotype when removed than nodes with lower centrality ( 46 ). The essential protein nodes (or interactors) can be identified by measuring higher value of betweenness centrality ( 47 ). Here, we analyzed high-betweenness nodes in the NICD proximal protein interaction network ( 48 ). We found HDAC1 to be the central node with the highest betweenness centrality measure, followed by CHD4, SNW1, SMARCA4, and TOP2B ( Fig. 5 A ). HDAC1 also has the highest closeness centrality measure in the network ( Table S5 A ). This is not surprising since HDAC1 and HDAC2 (HDAC1/2) are part of numerous modular complexes that contribute approximately half of the total deacetylase activity of the 18 HDACs found in mammalian cells ( 49 , 50 ). To validate interactions and physical closeness of HDAC1 and NOTCH1 proteins in cells using an additional approach, we performed in situ proximity-based ligation assay (PLA) in human SJSA-1 osteosarcoma cells. We found that significant and specific nuclear fluorescence signals were detected when SJSA-1 cells were probed with NOTCH1 and HDAC1 antibodies ( Fig. 5 B , bottom row, and Fig. 5 C ), whereas addition of NOTCH1 or HDAC1-specific antibodies alone produced only background levels of fluorescence ( Fig. 5 B first and second row). Independently, their PLA interaction was validated in 293T cells ( Fig. S4 A ), suggesting that it is not restricted to one cell type. To further functionally characterize newly identified interactions related to HDAC1, we applied in vivo chemical crosslinking and endogenous coimmunoprecipitation (Co-IP) to examine whether GATAD2B, an understudied component of the NuRD complex, can directly interact with NOTCH1 in MOLT-4 and MB157 cell lines. Cells from both present high expression of NICD protein with activating mutations of NOTCH1 ( 8 , 14 , 30 ). We chose 3,3′-Dithiodipropionic acid di(N-hydroxysuccinimide ester (DSP), a homogeneous bifunctional cell-permeable cross-linker with a 12-Å (1.2 nm) spacer arm, which allows cleavage of cross-linked products and to identify labile proximity-protein interactions in live cells ( 51 , 52 , 53 ). Here Co-IP analysis revealed that endogenous GATAD2B was readily detectable in MOLT-4 cells ( Fig. 5 D ) and MB157 cells ( Fig. 5 E ). Interestingly, we also observed that endogenous DDX15 coprecipitated with endogenous RBPJ in MOLT-4 cells ( Fig. S4 , B and C ). Unlike its family member DDX5 ( 54 ), an ATP-dependent RNA helicase, the role of DDX15 in its functional interaction with the NOTCH1 complex and in T-ALL leukemia cells is unclear. Our data suggest that HDAC1 and some other identified interacting proteins such as GATAD2B in this study may be essential partners for NOTCH1 function and may serve as important therapeutic targets in NOTCH1-dependent cancers. On the other hand, for drug repurposing considerations, we sought to gain an unbiased understanding of how many proximal proteins of NOTCH1 in this study could be targeted by currently available drugs or agents that are Food and Drug Administration (FDA)-approved or examined in clinical trials or preclinical studies. We cross-referenced our Notch1 proximal proteins with potential therapeutic targets annotated in CLUE drug library ( 55 ) and IPA database ( 56 ). We identified a total of 10 targets, including five targets with 15 known FDA-approved drug interactions with potential for therapeutic use or testing in Notch1-dependent cancers ( Fig. S5 and Table S5 , B and C ). For example, our data support current clinical trials and ongoing studies to treat NOTCH1-dependant T-ALL by repurposing FDA-approved HDAC inhibitor drugs, including Vorinostat, Romidepsin, Belinostat, and Panobinostat, which specifically target HDAC1 together with one or more other HDACs ( 57 , 58 ). However, continued investigation is needed to validate these potential targets and the possible impact of drugs or agents on NOTCH1-dependent cancers.

Discussion We have applied an innovative and alternative approach to define the biochemical composition of the nuclear Notch complexes in live cells. Our BioID study has complemented previous characterization of NICD partners and PPIs using conventional low or high throughput methods such as reconstituted complex, yeast two-hybrid, and tandem affinity purification ( 13 , 14 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 ). Moreover, our BioID findings provide a framework to further define the complex architecture and elucidate NOTCH1 regulation and mechanisms of action. The core Notch-activation complex NICD/RBPJ/MAML1 together with a number of nuclear coregulators initiates transcription of Notch target genes, which execute Notch functions ( 3 , 4 , 7 , 67 ). Our BioID data expand our understanding of multiple functionally relevant protein complexes involved in different steps of the transcriptional activation process such as transcriptional initiation, chromatin remodeling, elongation by RNA polymerase II, and DNA replication and repair ( Fig. 4 ). Consistent with reports by others (Yatim et al ., 2012), we found that the NICD interacts with components of SWI/SNF remodeling complex including SMARCA4 and SMARCC2 (also known as BRG1/BAF190 and BAF170). Moreover, we also found NICD interacting with unreported ARID1A and SMARCE1 (also known as BAF250 and BAF57). Interestingly, recurrent mutations of ARID1A and NOTCH1 have been frequently associated with many types of cancer ( 68 , 69 , 70 , 71 , 72 ). However, our study did not identify the reported coactivator AF4p12 and transcription factors such as IKAROS and RUNX1, which may have tissue-specific roles in T-ALL ( 14 ). Instead, our data revealed other unreported nuclear coregulators, including TCF20, LIN54, TRPS1, DIDO1, and RAI1 that may participate in Notch-mediated transcriptional activation by serving as upstream “pioneer” transcription factors that can bind to and open up repressed chromatin or downstream “settler” transcription factors that act through regulatory elements. Additionally, TCF20 can form a complex with RAI1 ( 42 ). Individually, de novo nonsense and frameshift variants of TCF20 have been reported in individuals with intellectual disability and postnatal overgrowth ( 73 ). Mutations in RAI1 are associated with Smith–Magenis syndrome, a developmental disorder characterized by mental retardation and craniofacial and skeletal abnormalities ( 74 ). Further studies are needed to better understand the functional interaction of the TCF20/RAI1 complex with the Notch-activation complex in these diseases. It remains largely unclear how the strength of the Notch response is regulated by the relative abundance of activating and repressive complexes as well as the competition between them ( 4 ). The current view is that RBPJ is a transcriptional repressor that interacts with many nuclear corepressor proteins such as HDAC1 ( 75 ) in the absence of Notch signaling, whereas once bound to the nuclear NICD, RBPJ is converted into a transcriptional activator ( 7 ). Interestingly, our studies indicate that NICD may directly interact with components in different corepressor complexes, including NuRD (GATAD2A, GATAD2B, CHD4, HDAC1, MTA1, and MTA2), CoREST (HDAC1, CTBP2, and PHF21A) and SMRT/NCOR (NCOR1 and NCOR2). NuRD and CoREST are two of four canonical corepressor complexes containing HDAC1/2 ( 76 ), whereas in our BioID study we did not observe NICD interacting with the components of the two canonical Sin3 and MiDAC complexes. Although NuRD has long been accepted as a transcriptional repressor, more recent data have shown that it is prevalent at enhancers and promoters of active gene loci and is likely associated with active transcription ( 77 , 78 ). It may be interesting to explore how repressive complexes such as NuRD interact with NOTCH1-RBPJ activating complex in the recently discovered long-range super-enhancer complexes ( 79 , 80 ). The results of our PLA and Co-IP analyses suggest that HDAC1 and GATAD2B may be part of the Notch activating complex or the Notch inhibitory complex, or both ( Fig. 4 , B – E ). Moreover, SMRT/NCOR is a corepressor complex containing HDAC3, which can positively regulate Notch signaling through controlling NICD protein acetylation and stability ( 81 ), but our study did not detect NICD-HDAC3 interaction. Instead, consistent with previous findings on the physical interaction between HDAC1 and NICD in leukemia cells ( 14 ), we validated NICD-HDAC1 interactions in SJSA-1 and 293T cells ( Figs. 5 , B and C and S4 ). SJSA-1 cells possess WT NOTCH1 but are highly sensitive to Notch inhibitors and a HDAC1 inhibitor ( 82 , 83 ). On the other hand, in a Drosophila wing study, depletion of HDAC1 causes reduced expression of Notch and its target genes, suggesting that HDAC1 positively regulates Notch signaling by promoting Notch transcription ( 84 ). Consistent with the Drosophila study, our recent work and others indicate that HDAC1 function is required for the positive regulation of Notch signaling-meditated cell differentiation in vascular and bone cells ( 85 , 86 ). Thus, it will be important to determine whether HDAC1 can positively regulate Notch signaling by either controlling NICD stability and/or transcription levels in the context of solid tumors. Several histone modifiers identified in this study provided evidence supporting that histone H3 lysine (H3K) modifications play a critical role in the epigenetic regulation of Notch target genes ( Fig. 4 ). Previous studies show that Notch activation results in the acquisition of active marks, including acetylation of H3K27 ( 79 ) and H3K56 ( 87 ) in Notch-regulated enhancer elements and trimethylation (me3) of H3K4 in the Notch-regulated gene promoters ( 88 ). In corresponding regions, repressive marks such as H3K27Me3 are lost ( 89 ). In T-ALL cells, Yatim et al . found two histone demethylases: LSD1/KDM1A functions as a corepressor when associated with CSL-repressor complex ( via removing active mark H3K4me2) and as a NOTCH1 coactivator upon Notch activation ( via removing repressive mark H3K9me2); PHF8/KDM7B may promote epigenetic modifications by removing repressive mark H3K27me2 ( 14 ). In our study, neither LSD1 nor PHF8 was detected, but interestingly, we identified the histone demethylase JDJM1C/KDM3C ( Fig. 4 ). Unlike LSD1 and PHF8, JMJD1C is a specific demethylase toward either active mark H3K9me1 or repressive mark H3K9me2, which participates in the progression of various tumors ( 90 ). As the net effect of JMJD1-mediated changes in H3K9 methylation status on gene transcription is unpredictable and may vary depending on the cellular context ( i.e. , gene promoter, cell type, or physiological state), further investigation of the epigenetic role of JMJD1C as a NOTCH1 coactivator or corepressor may be required. NICD protein stability, activity, and localization are tightly regulated by various posttranslational modifications including phosphorylation, methylation, hydroxylation, acetylation, and ubiquitinylation ( 7 ). The current NICD proteasomal degradation model demonstrates the importance of phosphorylation and ubiquitination at the C-terminal PEST domain site by the kinase CDK8 and the E3 ligase FBXW7, respectively ( 91 , 92 , 93 ). In addition, several studies showed that NICD protein stability is also regulated by deubiquitinating enzymes such as USP7 and USP8 in T-ALL and breast cancer ( 44 , 45 , 94 ). However, at sites outside the PEST domain, how posttranslational modifications affect NICD stability and turnover remains poorly understood ( 4 ). In this BioID study, various candidate protein modifiers and enzymes were identified ( Table S3 ). As expected, CDK8 and FBXW7 were not recovered due to the lack of a PEST domain for our bait protein NICD. Remarkably, we identified several E3-type ligases and deubiquitinating enzymes, such as TRIM33, RBBP6, PIAS2, and USP34, which may affect Notch1 activity. It will be important to determine whether NICD is a substrate and how these interactions with E3 ligases and deubiquitinating enzymes affect NICD turnover. Notably, absence of the PEST domain and inactivation of FBW7 are common mechanisms for strong gain-of-function in NOTCH1 in human cancers such as T-ALL ( 8 ), breast cancer, and adenoid cystic carcinoma ( 9 , 10 , 11 , 12 ). Therefore, another important question is whether deregulation of these interactions contributes to NICD tumorigenesis. Further characterization of these interactions may reveal mechanisms regulating NOTCH1 protein stability and turnover. In the postgenomic and postproteomic era, one of the challenges is to study protein-protein functional interactions in living cells. We performed high-throughput BioID studies of the NOTCH1 nuclear interactome using two cell models, HEK293T and NIH3T3, which have unique advantages but also inherent limitations. On the one hand, we rationalized that low-level expression of endogenous Notch signaling in a background with a WT Notch1 genetic background might minimize interfering interactions from overexpressed NICD and its partners. Studies by many groups have shown that HEK293T and NIH3T3 cells naturally have lower Notch activity, making these two cell lines suitable for studying various components and mutants of Notch pathway function in various diseases, including noncancer conditions and cancers ( 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 ). In our case, HEK293T and NIH3T3 are the model systems of choice for studying the Notch1 nuclear interactome using high-throughput methods such as BioID, with minimal interference from the endogenous expression of Notch1. On the other hand, we should be cautious in extrapolating our BioID results to other cell types without support from other experimental data, as Notch signaling may differ in noncancer and cancer cells ( 2 , 7 ). Moreover, we fully agree and appreciate the future necessity of studying the nuclear interactome of NOTCH1 in the cell lines with NOTCH mutations. We emphasize here that additional efforts and manipulations may be required in further experiments such as BioID to avoid interference from endogenous mutant NICD highly expressed in NOTCH1-driven cell lines such as MOLT-4 and MB157 ( 8 , 14 , 103 , 104 ).” Since gain-of-function mutations in NOTCH1 can transform normal cells into tumor cells in many different cell types ( 7 , 22 , 23 , 24 ), we rationalized our analysis to focus on common NOTCH1 interactors between cell types ( Figs. 3 and 4 ). We also provided one proof-of-principle example for the first time in this study that GATAD2D and NOTCH1 may directly interact in NOTCH1-mutated MOLT-4 and MB157 cancer cells ( Fig. 5 , B – E ). MOLT-4, an acute lymphoblastic leukemia cell line, possess a cis combination of the L1601PΔP heterodimerization mutation and PEST domain deletion and are highly sensitive to Notch and pan-HDAC inhibitors ( 103 , 104 ). MB157 and MDA-MB-157 cell lines, both of which were derived from the same patient with triple-negative breast cancer, possess a NOTCH1 rearrangement associated with high levels of activated NOTCH1 protein and are also highly sensitive to Notch and pan-HDAC inhibitors ( 30 , 105 ). To date, the role of GATAD2B in those NOTCH1-addicted cancers is unclear, although GATAD2B has been identified as a metastatic driver in lung cancer ( 106 ). In the future, it will be necessary to investigate the relative contribution of the common interactors such as GATAD2B to the cell type-specific and context-specific functions of NOTCH1. It also requires further investigation into how the cell type-specific interactors identified in this study contribute to cell type-specific mechanisms in the context of cancer cell survival and therapy. In summary, our data support BioID as an excellent method to examine PPIs of NOTCH1 in living cells and demonstrate that it can serve as a powerful tool for probing the large multiprotein complexes that regulate chromatin structure and gene expression. We have identified a large set of nuclear proteins associated with NICD, including transcriptional factors, coactivators and corepressors, which are associated with many functional complexes. Furthermore, we found that NICD is associated with several protein modifiers and components of other signaling pathways that may affect Notch signaling and function. Importantly, biochemical and bioinformatic analyses led to the identification of multiple available drugs that may have therapeutic utility against Notch1-dependent cancers, although substantial research is needed to assess whether and how they affect Notch1 biological function. Together, the nuclear interactome of Notch1 oncoproteins discovered in this study in two different cell types should be a valuable resource for the field as we seek to uncover the mechanisms that fine-tune Notch signaling in tumorigenesis and provide therapeutic targets for Notch-addicted tumors.

Notch signaling plays a critical role in cell fate decisions in all cell types. Furthermore, gain-of-function mutations in NOTCH1 have been uncovered in many human cancers. Disruption of Notch signaling has recently emerged as an attractive disease treatment strategy. However, the nuclear interaction landscape of the oncoprotein NOTCH1 remains largely unexplored. We therefore employed here a proximity-dependent biotin identification approach to identify in vivo protein associations with the nuclear Notch1 intracellular domain in live cells. We identified a large set of previously reported and unreported proteins that associate with NOTCH1, including general transcription and elongation factors, DNA repair and replication factors, coactivators, corepressors, and components of the NuRD and SWI/SNF chromatin remodeling complexes. We also found that Notch1 intracellular domain associates with protein modifiers and components of other signaling pathways that may influence Notch signal transduction and protein stability such as USP7. We further validated the interaction of NOTCH1 with histone deacetylase 1 or GATAD2B using protein network analysis, proximity-based ligation, in vivo cross-linking and coimmunoprecipitation assays in several Notch-addicted cancer cell lines. Through data mining, we also revealed potential drug targets for the inhibition of Notch signaling. Collectively, these results provide a valuable resource to uncover the mechanisms that fine-tune Notch signaling in tumorigenesis and inform therapeutic targets for Notch-addicted tumors. Keywords Abbreviations acetonitrile American Type Culture Collection proximity-dependent biotin identification coimmunoprecipitation Co-repressor of Repressor Element-1 Silencing Transcription deacetylase complex 3,3′-Dithiodipropionic acid di(N-hydroxysuccinimide ester formic acid histone H3 lysine histone deacetylase immunofluorescence ingenuity pathways analysis Jumonji domain containing 1C mastermind-like protein 1 nucleosome remodeling and deacetylase proximity-based ligation assay protein-protein interactions recombination signal binding protein for immunoglobulin kappa J region restriction enzyme replication factor C T-cell acute lymphoblastic leukemia/lymphoma Western blot Reviewed by members of the JBC Editorial Board. Edited by Eric Fearon

Notch signaling is an evolutionarily conserved intercellular communication mechanism across invertebrates and vertebrates that regulate cell fate determination, proliferation, differentiation, and death programs ( 1 ). In normal mammalian cells, there are four Notch receptors (named Notch1-Notch4), which are single pass transmembrane proteins that can be activated by physical interaction with a transmembrane ligand on juxtaposed cells, resulting in the ligand-induced proteolytic cleavages of the receptor and the release of the COOH-terminal portion of the Notch intracellular domain (NICD) ( 2 ). The NICD enters the cell nucleus, binds to a transcription factor recombination signal binding protein for immunoglobulin kappa J region (RBPJ) (also known as CBF1/Suppressor of Hairless/Lag-1 [CSL]), and then interacts with a coactivator mastermind-like protein 1 (MAML1) to form a stable ternary complex NICD/RBPJ/MAML1, which serves as a required platform for recruiting auxiliary coregulators to assemble a larger Notch transcriptional complex to activate downstream target genes ( 3 , 4 ). Nevertheless, the short half-life of NICD and the lack of amplification in stoichiometric signal transduction render the Notch pathway sensitive to precise regulation influenced by dose, duration, and the epigenetic context of the signal ( 5 ). Moreover, how the NICD precisely activates transcription and interacts with its partners in the nucleus remains incompletely understood. Derailed Notch signaling is associated with congenital, late-onset disorders and cancer ( 6 ). Recent genomic studies have identified cancer-specific gain- or loss-of-function mutations in Notch genes and implicated distinct roles for Notch, ranging from oncogenic to tumor suppressive, depending on cancer type ( 7 ). The oncogenic role of strong gain-of-function mutations in NOTCH1 has been experimentally demonstrated in T-cell acute lymphoblastic leukemia/lymphoma (T-ALL) ( 1 ). These mutations occur in the juxtamembrane negative regulatory region and/or the C-terminal PEST degron domain of the NOTCH1 receptor, leading to the constitutive generation of high levels of NICD and ligand-independent Notch activation ( 8 ). Similarly, strong gain-of-function mutations in NOTCH1 have been found in several solid tumors, including breast cancer and adenoid cystic carcinoma ( 9 , 10 , 11 , 12 ). Importantly, deregulated Notch signals with a long duration in tumor cells may lead to the activation of a large set of target genes, perhaps through interacting with auxiliary coregulators and protein modifiers that are not recruited by the WT Notch protein under normal conditions ( 13 , 14 ). Given its role in cancer and its therapeutic applications in a variety of disorders, it is valuable to identify the protein components of the NOTCH1 transcription complex and its functional protein-protein association network. In the current study, we investigated a nuclear interactome for NOTCH1 oncoprotein in live cells using proximity-dependent biotin identification (BioID), which was developed to overcome barriers imposed by conventional screening methods for protein-protein interactions (PPIs) ( 15 ). The BioID method can be used to characterize the nuclear environment occupied by an oncogenic protein such as NOTCH1 and a history of its PPIs in living cells ( 16 ). Here, we fused a second-generation mutant biotin ligase (BioID2) to the “bait” protein NICD, which can release biotinoyl-AMP into the proximal environment to covalently label lysine residues of the bait within ∼ 10 nm. These biotinylated proteins including poorly soluble nuclear chromatin cofactors can be selectively isolated using harsh lysis conditions, then captured by streptavidin affinity, and identified by mass spectrometry (MS) ( 17 ). Since the average globular protein diameter is less than 10 nm, these candidates identified by the BioID method favor direct binding partners and components of protein complexes in which the bait lodges ( 18 ). Due to its applicability to weak/transient PPIs and insoluble proteins, the BioID method has rapidly become widely used to define the composition of many different protein complexes and PPIs in different cellular compartments, including the identification of transcription factor complexes in the nucleus ( 19 , 20 , 21 ). Hence, the nuclear interactome of Notch1 generated in this study will benefit further investigations of the molecular mechanisms of NOTCH1 functions and regulation that govern Notch transcriptional activity in normal and cancer cells. Experimental procedures Plasmids and cloning All cloning was performed utilizing the In-Fusion Recombination system (Takara Bio). Empty pCW57.1 vector was a gift from David Root (Addgene #41393). To generate the negative control, myc-BioID2 was amplified by PCR from the previously generated myc-BioID2 pBabe puro ( 18 ) and inserted into the pCW57.1 vector using Nhe I and Age I restriction enzyme (RE) sites with an EcoRI RE site built into the reverse primer to allow for subsequent cloning. The mouse intracellular NICD fragment (amino acids 1749–2293, lacking the C-terminal PEST domain) was amplified by PCR from pBs-mNotch1-1C (gifted by Douglas Melton, Addgene #15079) and inserted into the BioID2-only pCW57.1 vector using Eco RI and Age I RE sites to make BioID2-NICD pCW57.1. The pRetroX-Tet3G system (Cat. No. 631188) was obtained from Takara Bio, Inc. Myc-BioID2 was PCR amplified from myc-BioID2 pBabe puro and inserted into pRetroX using the BamHI and EcoRI RE sites with a NaeI RE site built into the reverse primer to allow for subsequent cloning. NICD was PCR amplified from pBs-mNotch1-1C and inserted into BioID2-only pRetrox using the NaeI and EcoRI RE sites to make BioID2-NICD pRetroX. Cell culture and stable cell line generation HEK293 Phoenix cells were obtained from National Gene Vector Biorepository. All other cell lines were obtained from the American Type Culture Collection (ATCC). MB157 (ATCC; CRL-7721), Phoenix, 293T (ATCC; CRL-3296), HEK293 (ATCC; CRL-1573), and NIH3T3 (ATCC; CRL1658) cells were cultured in Dulbecco's modified Eagle's medium with 4.5 g/L glucose, L-glutamine, and sodium pyruvate (Corning) and supplemented with 10% (v/v) fetal bovine serum (HyClone). SJSA-1 (ATCC; CRL-2098) cells were cultured in minimum essential medium-α medium (HyClone, SH30265FS) containing 10% fetal bovine serum (Thermo Fisher Scientific, ES009B) and 1% Penicillin-streptomycin (HyClone, SV30010). MOLT-4 (ATCC; CRL-1582) cells were grown in RPMI-1640 Medium (ATCC; 30–2001) and 10% fetal calf serum. All cells were maintained at 37 °C with a humidified atmosphere containing 5% CO2 and routinely tested for mycoplasma contamination. Stable cell lines were generated using lentiviral transduction (for HEK293, pCW57.1) with the ViraSafe Lentiviral Packaging System (Cell BioLabs, Inc; VPK-206) or retroviral transduction (for NIH3T3, pRetroX-Tet3G). Phoenix (retroviral) or 293T (lentiviral) cells were transfected with each construct using Lipofectamine 3000 (Thermo Fisher Scientific) according to the manufacturer's recommendations and incubated at 37 °C for 4 h. Then, the transfected cells were supplemented with fresh medium and further incubated at 37 °C for 72 h. Viral media was filtered through a 0.45 μm filter and added to HEK293 or NIH3T3 cells along with Polybrene (4 μg/ml; Santa Cruz Biotechnology). Forty-eight hours after transduction, puromycin (0.5 μg/ml; Thermo Fisher Scientific) or G418 (for 3T3 pRetroX system, 0.5 mg/ml; Corning) was added to target cells for 72 h (puromycin) or 7 days (G418), and viable cells were collected. Expression of BioID2-only and BioID2-NICD fusion proteins and functional biotinylation after addition of 50 μM biotin and 1 μg/ml doxycycline were further verified using IF and WB. Immunofluorescence Cells grown on 1.5 mm glass coverslips were fixed with 3% (w/v) paraformaldehyde/phosphate-buffered saline for 10 min and permeabilized with 0.4% (w/v) Triton X −100/PBS for 15 min. To detect BioID2 fusion proteins, chicken anti-BioID2 (1:5000; BID2-CP-100; BioFront Technologies) was used ( 18 ). The anti-BioID2 antibody was detected using Alexa Fluor 568–conjugated goat anti-chicken (1:1000; A11041; Thermo Fisher Scientific). Alexa Fluor 488–conjugated streptavidin (1:1000; S32354; Thermo Fisher Scientific) was used to detect biotinylated proteins. DNA was detected with Hoechst dye 33342. Coverslips were mounted using 10% (wt/vol) Mowiol 4 to 88 (Polysciences). Epifluorescence images were obtained using a Nikon Eclipse NiE microscope (40 × /0.75 Plan Apo Nikon objective) with a charge-coupled device camera (CoolSnap HQ; Photometrics) linked to a workstation running NIS-Elements software (Nikon). All images were processed in Adobe Photoshop CC 2023 ( https://www.techspot.com/downloads/6043-adobe-creative-cloud-photoshop.html ) (Adobe) for cropping and brightness/contrast adjustment when applicable. WB analysis of biotinylated proteins Total cell lysates (1.2 × 10 6 cells) for WB were prepared in SDS–PAGE sample buffer, boiled for 5 min, and sonicated to shear DNA. Proteins were separated using 4 to 20% gradient gels (Mini-PROTEAN TGX; Bio-Rad) and transferred to nitrocellulose membrane (Bio-Rad). After blocking with 10% (vol/vol) adult bovine serum and 0.2% Triton X-100 in PBS for 30 min, the membrane was incubated with chicken anti-BioID2 primary antibody (1:5000; BID2-CP-100; BioFront Technologies). Anti-BioID2 primary antibody was detected using horseradish peroxidase–conjugated anti-chicken (1:40,000; A9046; Sigma-Aldrich) antibody. Biotinylated proteins were detected with horseradish peroxidase-conjugated streptavidin (1:40,000; ab7403; Abcam). The signals from antibodies were detected using enhanced chemiluminescence via a UVP BioImaging System (UVP). BioID pull-downs and digestion of biotinylated proteins Large-scale BioID pull-downs were performed as previously described ( 17 ). Briefly, three biological replicates were performed for each cell line with distinct samples for each replicate ( Fig. S2 ). For each large-scale BioID2 pull-down sample, two 10 cm dishes at 80% confluency were incubated with 1 μg/ml doxycycline for 24 h and then additionally supplemented with 50 μm biotin for 18 h. Cells were washed twice with PBS, lysed in 8 M urea 50 mM Tris pH 7.4 containing protease inhibitor (87785: Thermo Fisher Scientific) and DTT, incubated with a universal nuclease (88700: Thermo Fisher Scientific), and sonicated to further shear DNA. Lysates were precleared with Gelatin Sepharose 4B beads (17095601; GE HealthCare) for 2 h and then incubated with Streptavidin Sepharose High Performance beads (17511301: GE HealthCare) for 4 h. Streptavidin beads were washed four times with 8 M urea 50 mM Tris pH 7.4. Ten percent of the beads were collected for WB analysis and the other 90% were resuspended in 50 mM ammonium bicarbonate containing 1 mM biotin for MS analysis. Beads were thawed and resuspended with 8 M urea, 50 mM ammonium bicarbonate, and cysteine disulfide bonds were reduced with 10 mM tris (2-carboxyethyl) phosphine (TCEP) at 30 °C for 60 min. Cysteines were alkylated with 30 mM iodoacetamide for 30 min at room temperature in the dark. After alkylation, urea was diluted to 1 M urea and proteins were digested overnight with a MS-grade Trypsin/Lys-C mix (Promega). Finally, the beads were pulled down and the peptide-containing solution was collected into a new tube. The beads were then washed once with 50 mM ammonium bicarbonate to increase peptide recovery. After digestion, samples were acidified with formic acid (FA) and subsequently desalted using an AssayMap C18 cartridges mounted on an Agilent AssayMap BRAVO Liquid Handling System (Agilent). Briefly, C18 cartridges were conditioned first with 100% acetonitrile (ACN) and then with 0.1% FA. Samples were then loaded onto conditioned C18 columns, washed with 0.1% FA, and eluted with 60% ACN, 0.1% FA. Finally, organic solvents were removed in a SpeedVac concentrator prior to LC-MS/MS analysis. Liquid chromatography and mass spectrometry (LS-MS) assay Dried samples were reconstituted with 2% ACN-0.1% FA and quantified by NanoDrop spectrophometer (Thermo Fisher Scientific) prior to LC-MS/MS analysis using a Proxeon EASY nanoLC system (Thermo Fisher Scientific) coupled to an Orbitrap Elite mass spectrometer (Thermo Fisher Scientific). Peptides were separated using an analytical C18 Acclaim PepMap column (75 μm x 250 mm, 2 μm particles; Thermo Fisher Scientific) using a 117-min gradient, at a flow rate of 300 μl/min, consisting in: 1% to 6% B in 1 min, 6% to 23% B in 72 min, 23% to 34% B in 45 min, 34% to 48% B in 2 min, and 48% to 98% B in 2 min (A = FA, 0.1%; B = 80% ACN: 0.1% FA). The MS was operated in positive data-dependent acquisition mode. MS1 spectra were measured in the Orbitrap with a resolution of 60,000 (AGC target: 3e4; maximum injection time: 100 ms; mass range: from 375 to 1400 m/z). After the survey scan, up to 10 of the most intense precursors ions were fragmented by CID in the ion trap cell (Isolation window: 2 m/z; charge state: + 2; normalized collision energy: 35%). Resulting fragments were detected in the Ion trap cell with a rapid scan (AGC target: 1e4; maximum injection time: 100 ms). Precursor dynamic exclusion was set to 30s, with a 10 ppm mass tolerance around the precursor. MS data analysis All mass spectra from were analyzed with MaxQuant software ( https://www.maxquant.org/ ) version 1.5.5.1. MS/MS spectra were searched against the Homo sapiens Uniprot protein sequence database (version January 2018) and GPM cRAP sequences (commonly known protein contaminants). Precursor mass tolerance was set to 20 ppm and 4.5 ppm for the first search where initial mass recalibration was completed and for the main search, respectively. Product ions were searched with a mass tolerance of 0.5 Da. The maximum precursor ion charge state used for searching was 7. Carbamidomethylation of cysteines was searched as a fixed modification, while oxidation of methionines and acetylation of protein N-terminal were searched as variable modifications. Enzyme was set to trypsin in a specific mode and a maximum of two missed cleavages was allowed for searching. The target-decoy-based false discovery rate filter for spectrum and protein identification was set to 1%. Common background proteins were removed, including keratins, tubulins, histones, and ribosomal proteins ( 107 ). Proteins were classified as candidate interactors if they were identified in at least two of three triplicate samples and label-free quantification intensities were at least 3-fold greater compared to control ( 16 , 108 , 109 ). Functional and network analyses of significant interactors For functional annotation analysis, pathways, diseases, drug targets, and gene ontology analyses were performed by IPA ( http://www.ingenuity.com ) with default parameters. Candidate interactors were converted to official gene symbol and then selected as the identifier in this tool. H. sapiens was selected as the species of origin. Assignment of previously identified NOTCH1 interactors was based on annotation in the BioGRID database ( https://thebiogrid.org/ ) ( 27 ). Using the Broad Institute's CLUE Drug Repurposing Hub database (version 4/3/2023, https://www.broadinstitute.org/drug-repurpose-hub ), we annotated those known compounds or drugs in the database to target our candidate Notch1 protein interactors. For network analysis, The STRING software ( www.string-db.org ) was utilized for detecting protein interaction clusters, complexes, and subnetworks (accessed on 12 April 2023) ( 110 ). The betweenness centrality values were calculated using the NetworkAnalyzer Cytoscape plugin ( 48 ). Significant interactors were input using symbol ID. Organism was set to H. sapiens . Networks were visualized using either default or yFiles Radial Layout in Cytoscape (v3.8.2) ( 111 ). Proximity-based ligation assay PLA was performed according to the manufacturer’s instructions (Sigma-Aldrich) ( 112 , 113 ). Briefly, a total of 1 × 10 4 SJSA-1 or 293T cells were seeded overnight onto a 4-well glass chamber slide (Thermo Fisher Scientific). Cells were fixed with 4% paraformaldehyde in PBS for 10 min. Cells were then permeabilized and blocked with blocking solution for 60 min, and probed overnight in humidified chamber at 37 °C with antibodies directed against Notch1 (C-20, sc-6014, Santa Cruz Biotechnology) and/or HDAC1 (10E2, sc-81598, Santa Cruz Biotechnology). Cells were then treated with Duolink In Situ Red Starter Mouse/Rabbit kit (Sigma-Aldrich) as per manufacturer’s instructions. Cells were then washed, and the nuclei were stained with 4′,6-diamidino-2-phenylindole (DAPI). Images of the nuclei, proximity ligated foci were acquired using Z-stack images captured with an Olympus FV300 upright confocal microscope (Olympus). Images were cropped using ImageJ software ( https://imagej.net/ij/download.html ) (National Institutes of Health). The fluorescence intensity of proximity ligated foci was measured by ImageJ software using 8 bit images. Briefly, the tracing tool was used to outline individual cells, and the “measure” function was used to obtain mean fluorescence intensity of each proximity ligated foci. Total fluorescence intensity in each cell was normalized by cell area and plotted as a dot in the graph. Statistical analysis of data was done by unpaired Student’s two-sided t test. In vivo cross-linking, endogenous Co-IP, and immunoblotting In vivo cross-linking procedures to isolate weak protein complex have been described previously in detail ( 51 , 52 , 53 ). Briefly cells were washed once in prewarmed (37 °C) PBS and incubated with 1 mM DSP (D3669, Sigma-Aldrich) in PBS at 37 °C for 10 min in a CO 2 incubator. The reaction was quenched with 20 mM Tris in PBS at room temperature for 10 min. After the cross-linking, nuclear protein extraction and Co-IP procedures were performed using the Nuclear Complex Co-IP Kit (54001, Active Motif) according to the manufacturer's instructions. Protein concentration was determined using the Pierce BCA protein assay kit (23225, Thermo Fisher Scientific). Nuclear extracts (250–500 μg) were immunoprecipitated using 1 to 5 μg of NOTCH1 antibody (sc-6014, Santa Cruz) and normal IgG control antibody (31235, Thermo Fisher Scientific). Co-IP proteins were resolved on 7.5% SDS-PAGE gels (4561024, Bio-Rad) and analyzed by a previously described WB system ( 83 ) using primary antibodies against GATAD2B (1:1000, PA5-53536, Thermo Fisher Scientific), or RBPJ (1:500, sc-271128, Santa Cruz), or DDX15 (1:500, sc-271686, Santa Cruz). The membranes were incubated with secondary antibodies StarBright Blue 700 Goat Anti-Rabbit IgG (1:2,500, 12004162, Bio-Rad) and StarBright Blue 520 Goat Anti-Mouse IgG (1:2,500, 12005867, Bio-Rad). Signals from Blots were measured using a ChemiDoc MP Imaging System (Bio-Rad). Chameleon Duo Pre-Stained Protein Ladder (928–60000, Li-Cor Biosciences) was used as a molecular weight marker. Data availability All relevant data are contained within this research article and in the supporting information. Supporting information This article contains supporting information ( 14 ). Conflicts of interest Sanford Research has licensed BioID reagents developed by K. J. R. to BioFront Technologies. The remaining authors declare that they have no conflicts of interest with the contents of this article.

Supporting information Acknowledgments We thank members of the Tao Lab for critical reading of the manuscript and Bethany Mordhorst for scientific and software technical discussions. We thank L-J Pilaz and KC Pratiksha for sharing reagents. We also thank Alexandre Campos and the Sanford Burnham Prebys Proteomics Core for the MS data. This research was funded by Sanford Health, 10.13039/100000002 NIH grant R35GM126949, 10.13039/100000057 NIGMS grant P20GM103620, and 10.13039/100000054 NCI Cancer Center Support Grant P30CA042014. The Imaging Core and Biochemistry Core at Sanford Research, which facilitated these studies, are supported by Institutional Development Awards from the 10.13039/100000057 National Institute of General Medical Sciences and the 10.13039/100000002 National Institutes of Health under grant P20GM103620. Author contributions H. M. T., F. F., D. G. M., P. B., L. H., K. J. R. and J. T. investigation; H. M. T., F. F., D. G. M., K. J. R. and J. T. methodology; H. M. T., F. F. D. G. M., L. H., K. J. R. and J. T. formal analysis; H. M. T., F. F., D. G. M., P. B., L. H., K. J. R., and J. T. writing–review and editing; H. M. T., K. J. R. and J. T. funding acquisition; H. M. T. and J. T. writing–original draft preparation; K. J. R. and J. T supervision; J. T. conceptualization. Funding and additional information The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

CC BY

no

2024-01-16 23:43:45

J Biol Chem. 2023 Dec 1; 300(1):105522

oa_package/84/f1/PMC10788534.tar.gz

PMC10788540

37992807

Results tACE is required for normal ATP production in sperm To assess the effect of tACE on mouse sperm metabolism, we first determined the levels of intermediate metabolites in CKO and WT sperm by mass spectrometry ( 20 ). We found that 64 metabolites were significantly different between CKO and WT sperm ( p < 0.01). Sixty-one metabolites were low in CKO sperm, while three metabolites (mannose, sorbose, and myo-inositol) were high in CKO sperm than WT ( Fig. 1 A ). Similarly, we also found a significant reduction in carbon metabolite production ( e.g. citric acid, aspartic acid, malic acid, and glyceric acid) in WT sperm when treated with the ACEi ramipril. Importantly, the amount of AMP, ADP, and ATP was decreased in CKO and ramipril treated WT sperm as compared to untreated WT sperm. In CKO sperm, the levels of ATP, ADP, AMP, and adenosine were respectively, 9.4, 10.4, 4.9, and 5.7-fold lower than WT sperm ( Fig. 1 , B and C , p < 0.05). To verify the mass spectrometry data, the level of cellular ATP was measured by chemical assay in additional samples with or without treatment with ramipril. Again, we found a 3.1-fold reduction of ATP in CKO sperm thanthe WT sperm. Ramipril eliminated the difference between CKO and WT ( Fig. 1 D ). Similar experiments were performed using losartan, an AT1 receptor antagonist, to determine the role of the Ang II AT1 receptor. Losartan had no effect on ATP production in CKO and WT sperm ( Fig. 1 D ), indicating that Ang II AT1 receptor does not mediate the effect of tACE on sperm ATP production. tACE affects mitochondrial proteins regulating energy production Mitochondrial metabolic pathways are the major source of ATP production in animal cells including sperm. Since tACE affects ATP production in sperm, to assess whether tACE affects mitochondrial functions, we measured mitochondrial proteins using a mass spectrometry MitoPlex panel ( 21 ). This assay determines the levels of 37 mitochondrial proteins critical to central carbon chain metabolism and overall mitochondrial function. We found that 11 mitochondrial proteins were significantly decreased in CKO sperm as compared to WT sperm, including oxoglutarate dehydrogenase (ODO1), citrate synthase (CISY), malate dehydrogenase (MDHM), hexokinase 1 (HXK1), succinate dehydrogenase complex subunit A (SDHA), fumarate hydratase (FUMH), carnitine palmitoyl transferase II (CPT2), cytochrome b-c1 complex subunit 2 (QCR2) and ATP synthase subunit alpha (ATPA) ( Figs. 2 , A and B and S1 , p < 0.05). MitoPlex data were further validated by Western blot analysis, which identified CKO sperm to be significantly depleted of mitochondrial proteins as compared to WT sperm ( Figs. 2 C and S2 ). Importantly, most of these proteins are associated with oxidative metabolism. To determine which exact biological processes can be influenced by tACE activity, we carried out two different analyses, Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology analysis using MitoPlex data ( Fig. 2 D ). These analyses showed that the Krebs cycle was significantly affected in CKO sperm ( Fig. 2 D ). As part of metabolite profiling by mass spectrometry, we determined the levels of intermediate metabolites of the Krebs cycle, which showed that CKO sperm produced significantly lower levels of Krebs cycle intermediates, including citric acid (12.6-fold), cis -aconitic acid (3.1-fold), NAD (3.1-fold), α-ketoglutaric acid (1.3-fold), succinate (1.5-fold), and L-malic acid (2.2-fold) ( Fig. 3 A ), as compared to WT sperm. Thus, these results indicate that the Krebs cycle is one of the main metabolic pathways influenced by tACE activity. To examine whether differences in ATP, Krebs cycle metabolites, and mitochondrial proteins were due to differences in overall cellular protein content, the amount of protein per cell was determined chemically, we found no difference in protein content between CKO and WT sperm ( Fig. 3 B ). We also determined mitochondrial number and morphology (size) by staining mitochondria with MitoSOX red dye and analyzing them by flow cytometry and confocal microscopy. The fluorescent intensity parallels the count and integrity of mitochondria in the sperm midpiece. Again, we found no difference between CKO and WT sperm ( Fig. 3 , C and D ). This suggests that tACE influences mitochondrial metabolism rather than its biogenesis. PPARγ mediates the effect of tACE on sperm mitochondrial metabolism PPAR family proteins are closely associated with mitochondrial function and energy homeostasis ( 22 ). Particularly PPARγ has been reported to control energy production and thus is important for sperm physiological functions including motility, the acrosin activity, and survival ( 23 , 24 , 25 , 26 , 27 ). To examine whether tACE affects the protein level of PPARγ, we performed Western blot analysis of CKO and WT sperm protein lysates and found a significantly reduced level of PPARγ in CKO sperm as compared to WT sperm ( Figs. 4 A and S3 ). Transcriptional activity is repressed during spermiogenesis; however, the various mRNAs are transcribed for spermiogenesis in advance before terminating of nuclear transcription ( 28 ). Therefore, to investigate how tACE increases PPAR levels, we first determined PPARγ transcription (mRNA level). We found that the mRNA level of PPARγ was significantly decreased in CKO sperm as compared to WT sperm ( Fig. 4 B ). Then we also assessed the protein stability of PPARγ and the degradation rate by the proteasome using cycloheximide (translation inhibitor) or MG-132 (proteasome inhibitor). However, there was no difference between WT and CKO sperm ( Fig. S4 ). Next, we examined if PPARγ mediates the effect of tACE on sperm metabolism. First, we measured the level of metabolites in CKO and WT sperm pretreated with PPARγ inhibitor GW9662 for 12 h using mass spectrometry. As shown by heatmap analysis, we found no difference in intermediate metabolites between CKO and WT sperm treated with the PPARγ inhibitor ( Fig. 4 C ). In both CKO and WT sperm, ATP levels were decreased after PPARγ inhibition, and there was no difference between CKO and WT groups ( Fig. 4 D ). In contrast, PPARγ agonist treatment significantly increased ATP production in WT sperm than the untreated group, while no effect was found on CKO sperm ( Fig. 4 E ). Thus, agonist and antagonist had opposite effects on energy production in WT sperm. However, both had no significant effect on CKO sperm due to a minimal PPARγ level. Next, we determined the mitochondrial proteins in CKO and WT sperm treated with GW9662 using Western blot analysis and found that PPARγ inhibition eliminated the difference between CKO and WT sperm. Specifically, the levels of mitochondrial proteins related to oxidative metabolism including CISY, FUMH, ODO1, SDHA, ATPA, and CPT2 were decreased and similar in both CKO and WT sperm after treatment ( Figs. 4 F and S3 ). These data suggest that PPARγ plays a central role in the tACE-mediated regulation of mitochondrial metabolism. tACE induces ATP production via oxidative phosphorylation Because tACE is required for normal production of ATP and Krebs cycle intermediates, we examined whether there was a difference in mitochondrial function between WT and CKO sperm. For this, we measured cellular respiration rate in live cells using the Agilent MitoXpress oxygen consumption assay. After seeding and adhering sperm to a XF96 plate, respiratory parameters were measured as described previously ( 20 , 29 , 30 ). The rates of total ATP production and ATP production by oxidative metabolism (ATP OxPhos. ) in CKO sperm were about 7-fold less than WT sperm (0.22 pmol versus 1.47 pmol; p < 0.001, n = 10); this difference between the groups was eliminated when the assay was performed in the presence of the PPARγ inhibitor GW9662 ( Fig. 5 , A and B ). However, there was no difference in ATP production by glycolysis (ATP Glyco. ) between CKO and WT sperm ( Fig. 5 , A and B ). To confirm if the difference in oxygen consumption between CKO and WT sperm was due to direct mitochondrial changes, we measured maximal oxygen consumption rates (OCRs) with carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone (FCCP). After blocking ATP synthase with oligomycin, the addition of FCCP measures maximal respiratory rates when mitochondria are uncoupled from ATP synthesis. Indeed, there was a clear difference in maximal oxygen consumption, which averaged 55% lower in CKO sperm than the WT sperm (28.2 ± 10.6 pmol of O 2 /min/1.0 × 10 5 sperm (CKO) versus 64.2 ± 17.1 pmol of O 2 /min/1.0 × 10 5 sperm (WT), p < 0.01) ( Fig. 5 C ). Since glycolysis is another major pathway of ATP production in sperm, we further verified whether tACE influences glycolysis by directly measuring extracellular acidification rate (ECAR), which reflects the rate of glycolysis. We found no difference in glycolysis and glycolytic capacity between CKO and WT sperm ( Fig. 5 , D – F ). Also, we did not observe a significant effect of PPARγ inhibition on glycolysis in these groups ( Fig. 5 , D – F ). These results indicate that tACE specifically induces ATP production by mitochondrial oxidative phosphorylation, but not by glycolysis, and PPARγ mediates these effects. tACE regulates sperm physiological function and fertilization Since the tACE-PPARγ axis controls energy metabolism in sperm, we evaluated whether PPARγ mediates the effect of tACE on sperm physiological function. First, we determined the effect of tACE on the number of sperm. The number of sperm in CKO mice was roughly the same as in WT mice (∼1.5 × 10 6 /cauda, Figure 6 A ). The sperm size was also similar in CKO and WT mice ( Fig. 6 B ). Next, we measured sperm motility since ATP plays a crucial role in it ( 31 ). The sperm motility of CKO sperm is significantly lower than that of WT sperm, but this difference was not observed in the presence of the PPARγ inhibitor GW9662 ( Fig. 6 C and Video S1 ). Since acrosin, a sperm-specific acrosomal proteinase, has an essential role in the fertilization process that is dependent on mitochondrial energy ( 32 ), we assessed whether tACE affects acrosin activity. We found a significant difference in acrosin activity, which averaged 40% lower in CKO sperm than the WT sperm (62.3 ± 6.7 mIU/1.0 × 10 6 sperm (CKO) versus 102.9 ± 5.1 mIU/1.0 × 10 6 sperm (WT), p < 0.01) ( Fig. 6 D ). Again, no difference was observed between CKO and WT sperm with PPARγ blockade ( Fig. 6 D ). To verify the role of tACE and Ang II, we performed these assays with either WT sperm treated with or without ramipril (an ACE inhibitor) or losartan (an Ang II AT1 receptor antagonist) for 12 h. While ramipril treatment significantly reduced sperm motility and acrosine activity, no effect was found with losartan treatment ( Fig. 6 , E and F ). Further, blocking other known ACE-mediated peptide pathways, such as bradykinin/bradykinin 2 receptor (B2R), substance p/NK1R, and Ac-SDKP, had no effects on ATP production, motility, and acrosin activity of WT sperm ( Fig. 6 , G – I ). To determine the effect of tACE and PPARγ on fertilization, the rate of CKO and WT sperm fertilization was determined using in vitro fertilization (IVF). To block PPARγ, sperm were pretreated for 12 h with or without GW9662. Sperm were then transferred into a culture drop containing cumulus-oocyte complexes collected from the oviducts of WT mice. At 6 h after IVF, the rate of fertilization was measured by comparing the number of zygotes to the total number of eggs. Zygotes developed into 2-cell, 4-cell, and morulae stage embryos at 24 h after the IVF as shown in the images ( Fig. 6 J ). The CKO sperm showed an average fertilization rate of 12.9 ± 1.65% as compared to 62.5 ± 6.9% for WT sperm. We found that treatment with GW9662 significantly reduced the rate of fertilization of WT sperm (equivalent to CKO) ( Fig. 6 J ). Similar experiments were conducted with ramipril or losartan treatment. As with CKO sperm or PPARγ blockade, ramipril treatment also reduced the rate of fertilization of WT sperm ( Fig. 6 J ). In contrast, there was no effect of losartan treatment on sperm fertilization. To determine in vivo fertilization, we performed an artificial insemination (AI) test. To block tACE and PPARγ, WT male mice were administered ramipril or GW9662, and sperm were prepared in the presence of these drugs. AI was performed with WT female mice. Normal WT sperm produced a 50% pregnancy rate, but tACE or PPARγ inhibition reduced it to less than half (10–20%) ( Fig. 6 K ). We also noted a significant reduction in the number of embryos/pregnancies with ramipril or GW9662 treatment, while no effect of losartan was observed. The effect of tACE inhibition on the metabolism and function of human sperm Finally, a pilot clinical study was conducted to examine the role of tACE in human sperm and validate our findings in mice. Sperm collected from 13 healthy volunteers at our fertility clinic were washed, counted, and prepared for the analysis as described in Experimental procedures . Sperm were treated for 12 h with either GW9662 or ramipril or losartan. We found that inhibition of tACE or PPARγ significantly suppressed ATP production in human sperm ( Fig. 7 A ). Consistent with low ATP, GW9662 or ramipril treatment also decreased biological functions of human sperm with lower motility, and acrosin activity as compared to the untreated group ( Fig. 7 , B and C , Video S2 ). However, AT1R blockade by losartan had no effect on human sperm. These findings suggest that even short-term treatment with ACEi may reduce sperm's ability to generate ATP and their physiological functions, and that long-term effects of these drugs should be evaluated in patients as they may affect male fertility.

Discussion Sperm motility and function are governed by cellular ATP levels, and mitochondrial dysfunction suppresses sperm motility ( 33 ). There are two major metabolic pathways, glycolysis and oxidative phosphorylation, to generate ATP in sperm. Oxidative phosphorylation occurs in the midpiece, while glycolysis occurs in the head and flagellum of sperm ( 34 ). Indeed, the head and flagellum lack respiratory enzymes and ATP is only produced by glycolysis ( 11 , 35 ), while in midpiece, ATP is mainly produced by oxidative phosphorylation. Mitochondrial respiration is positively correlated with ATP production and sperm motility/velocity ( 11 , 35 ). This study demonstrates that tACE affects sperm metabolism. What is striking is that tACE is required for maintaining metabolic intermediates. A critical function is the regulation of cellular ATP. Based on mass spectrometry and chemical analysis, this is linked to the catalytic activity of tACE since its catalytic inactivation (CKO) reduced ATP levels. Further, treatment of mice with an ACEi reduced sperm ATP. In contrast, an Ang II AT1 receptor antagonist does not affect sperm ATP. It has been established that ACE is a promiscuous peptidase that has hundreds of substrates ( 36 ), but the effect of ACE on sperm is not due to angiotensin peptides, given the repeated ineffectiveness of an AT1 receptor antagonist and genetic ablation of all angiotensin peptides (angiotensinogen KO) on sperm motility and fertilization ( 2 ). In contrast, some studies indicate that the presence of Ang II in semen plasma stimulates sperm capacitation, and AT1 receptor blockade reduces sperm motility in mice ( 37 , 38 , 39 , 40 , 41 ). Given that ACE can affect sperm ATP, we examined metabolic pathways that may be responsible. Sperm use both glycolysis and oxidative phosphorylation for their energy needs. The mitochondria form a compact helix of 50 to 75 pieces of wrapped mitochondrial sheath in the sperm midpiece, which is essential for fertility in both humans and mice ( 42 , 43 ). It has been shown that ATP OxPhos is involved in sperm maturation, motility (activation), and fertilization, while ATP Glyco , in the head and flagellum, is involved in capacitation and motility (hyperactivation) ( 34 , 44 ). ATP OxPhos induced activation of motility is required for hyperactivation of motility by ATP Glyco ( 13 , 34 ). In sperm, tACE is expressed in both the head (the acrosomal region, the equatorial segment, and the postacrosomal region) and midpiece ( 45 , 46 ). Our analysis revealed that CKO sperm exhibited a downregulation of metabolic intermediates of the Krebs cycle, particularly citric acid, cis -aconitic acid, NAD, α-ketoglutaric acid, succinate, and L-malic acid. It appears that tACE increases sperm ATP by activating oxidative metabolism, rather than glycolysis as determined by oxygen consumption analysis of CKO versus WT sperm. Further, our analysis revealed that in sperm with tACE inactivation, there is downregulation of some mitochondrial enzymes critical for the Krebs cycle and electron transport chain, including ODO1, CISY, MDHM, HXK1, SDHA, FUMH, CPT2, QCR2, and ATPA. Predictively, these data are consistent with observations that the maximal rate of oxidative respiration is significantly decreased in CKO sperm. Thus, mitochondrial energy production is directly correlated with ACE activity. Further, we analyzed how tACE induces the level of mitochondrial proteins and ATP. PPARγ transcription factor regulates energy homeostasis in sperm ( 24 , 25 , 26 ). It is also well-known that PPARγ plays a critical role in sperm motility, and fertilization ( 47 ). Generally, PPARγ interacts with a coactivator and stimulates transcription of several biological response related genes that play a role in adaptive thermogenesis, mitochondrial biogenesis, and oxidative metabolism ( 48 ). Interestingly, PPARγ is also mainly localized in the sperm midpiece and postacrosomal region and is not expressed in the sperm head and flagellum ( 17 ). It is important to note that only PPARγ from the PPAR family is significantly decreased in asthenospermia patients whose sperm show low motility ( 23 , 24 ). Our findings suggest that the lack of tACE causes critically low levels of PPARγ in CKO sperm. To understand the mechanism of how tACE maintains high PPARγ levels, there could be two possibilities: either tACE increases PPARγ transcription or it increases translation including protein stability. Our data suggested that tACE influences PPARγ transcription with significantly low PPARγ mRNA in CKO sperm than the WT sperm. Generally, sperm is considered transcriptionally inert because it gets repressed due to sperm chromatin packaging during spermiogenesis. However, the various mRNAs needed during the stages of spermiogenesis are transcribed in advance before nuclear transcription is terminated ( 28 ). Therefore, the regulation of PPARγ through tACE could be at the early stages of sperm development such as spermatids or spermatocytes. Several reports demonstrated that transcription is terminated gradually with the compaction of chromosomal structure. In fact, recent studies revealed that the PPARγ mRNA level is positively correlated to sperm motility ( 24 ). These reports support our findings that tACE may regulate PPARγ at the mRNA level. Concerning PPARγ protein stability, ribosomal complexes are not sufficiently present to support mRNA translation in sperm, but some mRNAs can be translated to support sperm function ( 49 , 50 ). Sperm also has an ubiquitin–proteasome system for capacitation ( 51 ). To assess the role of tACE on PPARγ stability, we used cycloheximide to inhibit translation. PPARγ stability was not different between WT and CKO sperm. Also, the proteasomal degradation rate is similar between WT and CKO sperm as measured using proteosome inhibitor MG-132. Thus, these observations suggest that tACE regulates PPARγ at the RNA level before translation. However, further studies are required to identify at which stage of sperm development tACE acts and how it affects PPARγ mRNA levels. By using PPARγ antagonist or agonist, we have demonstrated that PPARγ mediates the effect of tACE on sperm metabolism. While PPARγ blockade eliminates the difference between CKO and WT sperm in terms of ATP and mitochondrial protein level, agonist treatment significantly increased ATP production in WT sperm. Agonist had no significant effect on CKO sperm, perhaps due to a very low PPARγ level. Since PPARγ acts as an E3 ubiquitin ligase as well as a transcription factor ( 52 ), further study is required to verify the mechanism how PPARγ regulates mitochondrial protein. Sperm is a special cellular system. There is no cell line representing sperm nor an established protocol for genetic manipulation of these cells. To confirm the role of PPARγ in tACE-mediated energy production, we have tried extensively to transfect sperm with PPARγ plasmid or anti-PPARγ siRNA, but it seems impossible to transfect these cells. Due to this limitation, we cannot further validate our findings through genetic manipulation of PPARγ. However, other studies using epigenetic/genetic approaches have shown that PPARγ-mediated energy metabolism is critical for sperm physiological function and male fertility in both mice and humans ( 23 , 24 , 25 , 26 , 27 ). Therefore, we can expect any reduction of PPARγ by tACE in sperm will reduce sperm metabolic activity and functions. Similarly, in other cellular systems, such as HEK-293 cells, which can be genetically manipulated, ACE overexpression under a cumate-inducible promoter strongly induces ATP ( 53 ). In contrast, ACE overexpression had no effect on ATP production in these cells with PPARγ silencing ( Fig. S5 ). We posit that ACE activates a generalized mechanism—OXPHOS—energy production across different cellular systems ( e.g. , sperm or epithelial cells) through increasing PPARγ level. However, genetic approaches need to be established for further validating a direct involvement of PPARγ in tACE-mediated energy production in sperm. Ang II is an important product of the ACE C-domain, which is well-known for regulating blood pressure. However, male mice lacking angiotensinogen have normal fertility ( 2 ), indicating that Ang II or any Ang peptides do not mediate tACE function in sperm fertilization. In agreement with this observation, inhibition of tACE, but not the Ang II AT1 receptor, reduced sperm ATP and biological function. These results are similar to our previous findings that Ang II AT1 receptor does not meditates the metabolic and immune functions of ACE in myeloid cells ( 18 , 20 ). We also found that blocking three other well-studied ACE-mediated peptide pathways (bradykinin/B2R, substance p/NK1R, and Ac-SDKP) showed no effects on sperm function. At present, we do not know the peptides that regulate PPARγ and sperm metabolism. Identifying this peptide is required to reveal the precise mechanism of how tACE regulates male fertility. ACEi are used by millions of patients for the treatment of hypertension or cardiovascular diseases, and some of them are young reproductively active males. Moreover, men have a higher prevalence of hypertension than women among adults aged 18 to 39 (9.2% of the total population compared with 5.6%, respectively) and 40 to 59 (37.2% compared with 29.4%, respectively) ( 10 ). Therefore, it is clinically important to examine the effect of these drugs on male fertility. Our study examines the short-term effects of ACEi or ARB on sperm fertilization as measured by IVF and artificial insemination. Treatment with ACEi resulted in a significant reduction in pregnancy in mice. In humans, as in mice, in vitro treatment with ACEi reduced ATP levels, motility, and acrosin activity in sperm, while ARB treatment had no effect on sperm physiology. In fact, a clinical study in patients enrolled in an IVF program reported that sperm with reduced tACE level failed to fertilize ova ( 54 ). Although ACE affects many physiological systems, any reduction in sperm metabolism and fertilization might be expected to contribute to an increased risk of male infertility. Therefore, our findings have clinical implications and suggest that the long-term effect of ACEi on male fertility should be further explored.

Testis angiotensin-converting enzyme (tACE) plays a critical role in male fertility, but the mechanism is unknown. By using ACE C-domain KO (CKO) mice which lack tACE activity, we found that ATP in CKO sperm was 9.4-fold lower than WT sperm. Similarly, an ACE inhibitor (ACEi) reduced ATP production in mouse sperm by 72%. Metabolic profiling showed that tACE inactivation severely affects oxidative metabolism with decreases in several Krebs cycle intermediates including citric acid, cis-aconitic acid, NAD, α-ketoglutaric acid, succinate, and L-malic acid. We found that sperms lacking tACE activity displayed lower levels of oxidative enzymes (CISY, ODO1, MDHM, QCR2, SDHA, FUMH, CPT2, and ATPA) leading to a decreased mitochondrial respiration rate. The reduced energy production in CKO sperms leads to defects in their physiological functions including motility, acrosine activity, and fertilization in vitro and in vivo . Male mice treated with ACEi show severe impairment in reproductive capacity when mated with female mice. In contrast, an angiotensin II receptor blocker (ARB) had no effect. CKO sperms express significantly less peroxisome proliferators–activated receptor gamma (PPARγ) transcription factor, and its blockade eliminates the functional differences between CKO and WT sperms, indicating PPARγ might mediate the effects of tACE on sperm metabolism. Finally, in a cohort of human volunteers, in vitro treatment with the ramipril or a PPARγ inhibitor reduced ATP production in human sperm and hence its motility and acrosine activity. These findings may have clinical significance since millions of people take ACEi daily, including men who are reproductively active. Keywords Abbreviations angiotensin-converting enzyme ACE inhibitor artificial insemination Ang II-AT1R blocker ATP synthase subunit alpha bradykinin 2 receptor citrate synthase C-domain KO carnitine palmitoyl transferase II extracellular acidification rate carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone fumarate hydratase human chorionic gonadotropin in vitro fertilization oxygen consumption rate oxoglutarate dehydrogenase 1 pregnant mare serum gonadotropin peroxisome proliferators–activated receptor gamma somatic ACE testis angiotensin-converting enzyme Reviewed by members of the JBC Editorial Board. Edited by Qi-Qun Tang

Angiotensin-converting enzyme (ACE) is a zinc-dependent dipeptidyl carboxypeptidase. There are two isoforms of ACE: somatic ACE (sACE) and testicular ACE (tACE). These isoforms are transcribed from the same gene through the action of alternative promoters. sACE is composed of two homologous catalytic domains (N domain and C domain), while tACE is approximately half the size of sACE and contains only the C-domain ( 1 ). tACE plays a critical role in fertilization in that absence of tACE causes defects in sperm passage through the oviduct and in binding to the zonae pellucidae ( 1 , 2 , 3 ). Several studies demonstrated that tACE affects sperm motility ( 4 , 5 , 6 ), capacitation ( 7 , 8 ), the acrosome reaction ( 8 ), and sperm-oocyte fusion ( 9 ). However, the mechanism by which ACE regulates sperm motility and fertilization is not known. The C-domain of ACE cleaves angiotensin I to angiotensin II (Ang II) which increases blood pressure. Millions of people take ACE inhibitor (ACEi) or Ang II-AT1R blockers (ARBs) daily for treating hypertension, diabetes, and other cardiovascular diseases. Some of these patients are young adults who fall in an active reproductive age group (below 45 years old) ( 10 ). Therefore, evaluating the effect of ACEi on sperm functions and fertilization is clinically very important. However, mice lacking angiotensinogen (source for all angiotensin peptides produced by ACE) have normal fertility, indicating that neither Ang II nor any other ang peptide mediate the biological function of tACE in sperm ( 2 ). Sperm motility and fertilization are heavily dependent on energy metabolism. ATP energy is not only required for axonemal dynein (a cytoskeletal motor protein) to drive sperm motility ( 11 , 12 ), but also essential for sperm capacitation and fertilization ( 13 ). Sperm, rich in mitochondria, use oxidative phosphorylation as the major source of ATP production. Not surprisingly, mitochondrial activity (site of oxidative phosphorylation) correlates with sperm motility and capacitation ( 14 ). Mitochondrial defects are one of the causes of asthenospermia in men, resulting in low sperm motility and infertility in patients ( 15 ). Our group is investigating the metabolic role of both tACE and sACE. We found that C-domain activity of ACE affects ATP production in myeloid cells and thus influences their immune response ( 16 , 17 , 18 , 19 , 20 ). This led us to investigate the role of tACE in sperm metabolism and whether it is associated with sperm physiological functions. Our study shows that tACE is required for normal energy production in sperm. Specifically, tACE increases mitochondrial ATP production by inducing oxidative phosphorylation, which in turn influences sperm motility and fertilization. The level of peroxisome proliferators–activated receptor gamma (PPARγ) is very low in C-domain KO (CKO) sperm and WT sperm treated with ACEi compared with WT sperm with normal ACE activity. Blockade of PPARγ activity eliminates metabolic and functional differences between CKO and WT sperm, suggesting PPARγ mediates the effect of tACE on sperm. A reduction in the number of pregnant mice was also observed when mice were treated with an ACEi. Furthermore, in human sperm, ACEi treatment reduced ATP production and impaired physiological functions. These studies indicate that tACE regulates sperm functions through energy production and that ACEi treatment may reduce male fertility. Experimental procedures Mouse and human sperm collection All animal and human studies were approved by the Institutional Animal Care and Use Committee or Institutional Research Ethics Board of Cesar-Sinai Medical Center. The Declaration of Helsinki principles were followed in all human studies. CKO and WT control mice were used in this study. CKO mice were generated by using point mutation to inactivate the catalytic activity of tACE or the C-domain of sACE, as described previously ( 1 , 36 , 55 ). Male C57BL/6J mice (8 weeks old) with proven fertility were used for sperm collection and the sperm were collected by placing cauda epididymidis in prewarmed Enhance W media for 1 h and allowing sperm to swim out, as described previously ( 56 , 57 ). After filtering through a 100 μm filter, sperm suspension was layered on a two-layer (40–80%) gradient (PureSperm 40/80, Nidacon) in a 14 ml tube. The tubes were centrifuged at 1000 g for 20 min at room temperature. After sperms were collected from the supernatant and were resuspended in Enhance W media, the sperm suspension was counted using a hemacytometer. Human sperm were donated by thirteen healthy male participants at Cedars Sinai fertility clinic. Ejaculated samples were washed twice with Enhance W media and then filtered through a 100 μm filter to remove substrates present in the epididymal fluid. A hemocytometer was used to count sperm after centrifuging samples and dissolving pellets in fresh media. The number of sperm isolated from everyone ranged from 15 to 100 million. A large-bore pipette tip was used in all procedures to prevent damage to sperm membranes. Metabolite array by mass spectrometry After collection and washing, sperm pellets containing ten million purified sperm were treated with 700 ml of cold 40% acetonitrile, 40% methanol, and 20% water. Then samples were vortexed vigorously for 5 min at 4 °C and spun at 10,000 g for 10 min at 4 °C. The supernatant was removed and placed in a SpeedVac until dry. To resuspend, 20 ml of methanol was added, followed by vortexing, and finally, 80 ml of water was added along with a final vigorous vortex. For LC–MS analysis, 4 ml of sample volume was injected. Analysis method was described previously ( 20 ). Briefly, cell metabolite extractions were analyzed with an Agilent 6470A triple quadrupole mass spectrometer, operating in negative mode, connected to an Agilent 1290 ultra-high-performance liquid chromatography (UHPLC) system (Agilent Technologies). The analytical column used was an Agilent ZORBAX RRHD Extend-C18 1.8 mm 2.1 × 150 mm coupled with a ZORBAX Extend Fast Guard column for ultra-high-performance liquid chromatography Extend-C18, 2.1 mm, 1.8 mm. The MassHunter Metabolomics dMRM database and method was used to scan for polar metabolites within each sample (Agilent Technologies). The resulting chromatograms were visualized in Agilent MassHunter Quantitative Analysis for QQQ (Agilent Technologies). The final peak areas were manually checked for consistent and proper integration. MitoPlex assay Mitochondrial proteomic analysis was described previously ( 20 , 21 ). Briefly, sperm pellets (n = 5 per mouse genotype, WT versus CKO) were lysed in 8 M urea dissolved in 50 mM Tris–HCl buffer, pH 8.0. Lysis was facilitated by high-pressure treatment on a Pressure BioSciences barocycler (model 2320EXT), with 60 1-min cycles consisting of 50 s at 45,000 p.s.i. followed by 10 s at atmospheric pressure. Peptides were prepared as previously described ( 20 ). A total of 8 mg of digested peptides, injected twice as duplicate technical replicates, were separated on a Prominence UFLCXR HPLC system (Shimadzu Corp) with a Waters Xbridge BEH30 C18 2.1 mm × 100 mm, 3.5-mm column flowing at 0.25 ml/min and 36 °C coupled to a QTRAP 6500 (SCIEX). Raw data were processed using the Skyline software package (Skyline Daily, version 19.1.1.309) to select peak boundaries and quantify the area under the curve for each fragment monitored. Ingenuity pathway analysis Significantly different metabolites and mitochondrial proteins ( p < 0.01 and p < 0.05, respectively) between CKO and WT sperm were imported to the Ingenuity Pathway Analysis Tool (IPA Tool; Ingenuity Systems, Redwood City, CA, USA; http://www.ingenuity.com ), and then mapped to well-known biological networks using the Ingenuity Pathway Knowledge Base derived from known functions and interactions of genes published in the literature. Functional and pathway enrichment analysis of mitochondrial proteins MitoPlex proteins were analyzed for their functional enrichment and biological processes using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, which used DAVID database ( https://david.ncifcrf.gov/ ), an online tool for gene annotation, function visualization, and large volume data integration ( 58 , 59 ). To describe gene product attributes, Gene Ontology clusters included three complementary biological concepts (biological process, molecular function, and cellular component). Western blot analysis Sperm were lysed with radioimmunoprecipitation assay buffer containing protease and phosphatase inhibitors (Thermo Fisher Scientific). The polyvinylidene difluoride membranes were incubated with specific antibodies including CISY rabbit mAb (Cell Signaling Technology, 14309S), FUMH rabbit polyclonal antibody (Proteintech, 11375-1-AP), ODO1 rabbit polyclonal antibody (Proteintech, 15212-1-AP), SDHA rabbit mAb (Cell Signaling Technology, 11998T), CPT2 rabbit mAb (Abcam, ab231162), ATPA mouse mAb (Invitrogen, 459240), GAPDH rabbit polyclonal antibody (Sigma-Aldrich, G9545), PPARγ rabbit polyclonal antibody (Invitrogen, PA3-821A). Protein bands were measured using an Odyssey Infrared Imaging System (ODYSSEY CLx, Li-COR). The fluorescence intensity was evaluated using Image Studio Lite version 5.2 ( https://www.licor.com/bio/image-studio-lite/ ). OCR and ECAR assessment For OCR assay, Agilent MitoXpress Xtra (MX-200-4, Agilent) reagent was reconstituted in 1 ml growth medium then diluted in 10 ml prewarmed growth medium. For ECAR assay, Agilent pH-Xtra reagent (PH-200-4, Agilent) was reconstituted in 1 ml distilled water then diluted in 10 ml prewarmed respiration buffer (PH-200-4, Agilent). Sperm (5 × 10 5 sperm/well) were centrifuged (600 g for 5 min) onto 96-well plates coated with Cell-Tak (Corning, catalog no. C354240) according to the manufacturer’s instructions. After 12 h incubation at 37 °C with or without 10 mM GW9662, medium was replaced in each well with 100 μl of the MitoXpress Xtra reagent or pH-Xtra reagent then sealed by overlaying with 100 μl prewarmed HS oil (MX-200-4, Agilent) in OCR assay. The plates were then immediately measured kinetically on a FLUORstar (BMG Labtech) plate reader (prewarmed to 37 °C, Ex 380 nm, Em 650 nm) for 120 min. Oligomycin (2 μM), FCCP (500 nM), antimycin A (1 μM) with rotenone (200 nM) (AA/ROT), glucose (10 mM) and 2-deoxy-d-glucose (2DG, 50 mM) were added acutely to the wells, and the kinetic data were analyzed by performing linear regression over the linear part of the kinetic data. Respiratory parameters and ATP production rates were calculated as described previously ( 20 , 29 , 30 ). Quantitative real-time PCR The mRNA was extracted from sperm using RNeasy Kit (Qiagen). Quantitative real time PCR was performed using OneStep RT-PCR Kit (Qiagen), according to the manufacturer’s instructions. Specific primer for PPARγ (Mm00440940_m1) was purchased from Thermo Fisher Scientific. The mRNA levels were normalized to the internal control β-actin (Mm02619580_g1). Group of mice were treated with 40 mg/l ramipril for 1 week to block tACE activity before isolation of sperm. Protein stability assays To assess PPARγ protein stability, sperm were seeded in 6-well plate (1.0 × 106 sperm/well) and incubated with a translation inhibitor cycloheximide (20 μg/ml) or proteasome inhibitor MG-132 (50 μM). At the indicated time points, sperm were harvested and PPARγ protein levels were analyzed by Western blot. Analysis of intracellular ATP content and ATP production rate Mouse or human sperm were seeded in 96-well plate (5 × 10 5 sperm/well) and incubated for 12 h with or without GW9662 (10 μM), pioglitazone (10 μM), ramipril (10 μM), and losartan (100 μM). ATP was measured using the Cell Titer-Glo 2.0 kit (Promega) as recommended by the manufacturer’s protocol. Measurement of mitochondrial number, size, and morphology For flow cytometry, sperm were suspended in prewarmed staining solution (0.1% bovine serum albumin in PBS) containing MitoSOX Red (Thermo Fisher Scientific). After incubation for 10 min at 37 °C and 5% CO 2 , sperm were rinsed three times with prewarmed PBS and then analyzed with flow cytometry (CYTEK NL-3000). Data were analyzed with FlowJo version 10.8.1 ( https://www.flowjo.com/solutions/flowjo/downloads/previous-versions ). For confocal microscopy, sperm were seeded on 8-well Chamber Slide (Nunc) with Cell-Tak and then centrifuged for 1 min at 700 g . After incubation with MitoSOX Red for 10 min at 37 °C and 5% CO 2 , sperm were washed with prewarmed PBS and then with PBS containing 4% formaldehyde for 30 min. After rinsing with PBS three times, the sperm were permeabilized with 0.1% Triton X-100 at room temperature for 20 min and washed three times with PBS. They were then incubated with Phalloidin-Green (Hello Bio) for 30 min, rinsed three times with PBS, and incubated with ProLong Gold Antifade Reagent with 4′,6-diamidino-2-phenylindole (Life Technologies) for 2 h. Fluorescence localization was observed using a Leica Stellaris 8-STED Super-resolution Confocal Microscope (Leica). Image analysis for the fluorescence localization was performed using LAS AF Lite (Leica). Data were processed by CellProfiler and analyzed by GraphPad Prism software ( https://www.graphpad.com/features ). Acrosin activity assay Acrosin activity was assessed by the method of Aquila et al. ( 25 ). Purified mice or human sperm were washed with Enhance W media and centrifuged at 700 g for 3 min. Sperm were resuspended (1 × 10 7 sperm/ml) in different tubes and incubated for 12 h with or without either 10 μM GW9662 or 10 μM ramipril or 100 μM losartan. After incubation, sperm were centrifuged at 700 g for 10 min. Then sperm were resuspended in 1 ml of substrate–detergent mixture (23 mmol/L Nα-benzoyl- DL -arginine p -nitroanilide in dimethyl sulfoxide and 0.01% Triton X-100 in 0.055 mol/L NaCl, 0.055 mol/L Hepes at pH 8.0, respectively) and incubated for 3 h at room temperature. After incubation, 100 μl benzamidine (0.5 M) was added to each of the tubes and then centrifuged at 1000 g for 30 min. The supernatants were collected and the acrosin activity was measured spectrophotometrically at 410 nm. The acrosin activity was determined as described by Aquila et al. ( 60 ) and presented as μIU/10 6 sperm. Inhibitors To investigate the role of the ACE substrate pathways bradykinin/B2R, substance p/NK1R and Ac-SDKP on sperm function, WT mice were treated i.p. for 5 days (1 dose/day) before sperm isolation, as follows: the B2R blocker HOE-140 (Sigma-Aldrich) at 100 μg/kg/day, Neurokinin 1 (NK1) receptor blocker L-733060 (Tocris) at 20 mg/kg/day, or prolyl oligopeptidase inhibitor KYP-2047 (Sigma-Aldrich) at 10 mg/kg/day. Sperm motility Using a light microscope, sperm motility was measured using live videography and real-time movement of sperm. Motility of sperm is calculated as a percentage of total motile sperm using a LPIXEL Image J Plugin. Videos of sperm motility are shown in Videos S1 and S2 . To verify the role of tACE, Ang II and PPARy, groups of samples were treated for 12 h with either 10 μM ramipril or 100 μM losartan or 10 μM GW9662 before analysis. In vitro fertilization IVF was performed by the method of Nakao et al. ( 61 ). Female mice were intraperitoneally injected 7.5 IU/100 μl pregnant mare serum gonadotropin (PMSG, Prospec-Tany Technogene). At 48 h after PMSG injection, mice were intraperitoneally injected 7.5 IU/100 μl human chorionic gonadotropin (hCG, Prospec-Tany Technogene). At 15 h after the hCG injection, their oviducts were collected and transferred to human tubal fluid medium on Ovoil in 60 mm 3 dish. Cumulus–oocyte complexes were collected from the oviducts and transferred into a drop of sperm suspension (5 × 10 5 sperm) and covered with Ovoil. After 6 h incubation at 37 °C in 5% CO 2 , the oocytes were collected and washed three times in 100 μl drops of human tubal fluid covered with Ovoil. After 24 h co-incubation, the fertilization rate was calculated by the formula: fertilization rate (%) = the total number of two-cell embryos/the total number of oocytes. Groups of male mice were treated with 40 mg/l ramipril or 600 mg/l losartan in drinking water for a week before sperm isolation. For PPARγ blockade, isolated sperm were pretreated with GW9662 for 12 h before inoculation with oocytes. Artificial insemination (AI) After superovulation by PMSG (7.5 IU) and hCG (7.5 IU) as described in IVF section, purified sperm were transferred to the female mice (2 × 10 6 sperm/50 μl Enhanced W) using a blunt 19-gauge needle inserted through the vagina. The transfer was performed without the use of anesthesia or analgesia. Cell culture HEK-293 cells were obtained from the American Type Culture Collection and cultured at 37 °C in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum in a humidified atmosphere containing 5% CO2. To create HEK-ACE cell line, HEK-293 cells were stably transfected with PiggyBac plasmid expressing ACE under a cumate-inducible promoter ( Fig. S5 A ) using Lipofectamine LTX (15338030, Invitrogen) according to the manufacturer's protocol. Stable transfected cells were selected with 1 μg/ml puromycin (Sigma) in complete Dulbecco’s modified Eagle’s medium. The PPARγ siRNA (Cat. # AM16708) was purchased from Invitrogen. Cells were transfected using Lipofectamine RNAiMAX (13-778-150, Invitrogen) and Opti-MEM (31-985-062, Gibco) according to manufacturer recommendations. Data availability All data generated or analyzed during this study are included either in this article or in the supplementary information files . Supporting information This article contains supporting information . Conflict of interest The authors declare that there is no conflict of interest regarding the publication of this article.

Supporting information Acknowledgments We thank Proteomic and Metabolomics Core team at Cedars-Sinai for performing metabolites and MitoPlex array. Author contributions T. S., S. A. B., D. Y. C., S. S., E. N., J. F. G., and Z. K. investigation; T. S. and Z. K. methodology; T. S., K. E. B, and Z. K. formal analysis; T. S. and Z. K. writing–original draft; E. A. B., J. D. M., E. T. W., J. L. C., M. D. P., and W. G. T. resources; K. E. B. and Z. K. writing–review and editing; Z. K. supervision. Funding and additional information This study was supported by the Department of Pathology-Mini-grant (229154) and Startup Fund (233040), 10.13039/100013015 Cedars-Sinai Medical Center , Los Angeles, United States to Zakir Khan. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

CC BY

no

2024-01-16 23:43:45

J Biol Chem. 2023 Nov 20; 300(1):105486

oa_package/65/03/PMC10788540.tar.gz

PMC10788541

38016514

For many decades, our understanding of G protein-coupled receptor (GPCR) activity and cyclic AMP (cAMP) signaling was limited exclusively to the plasma membrane. However, a growing body of evidence has challenged this view by introducing the concept of endocytosis-dependent GPCR signaling. This emerging paradigm emphasizes not only the sustained production of cAMP but also its precise subcellular localization, thus transforming our understanding of the spatiotemporal organization of this process. Starting from this alternative point of view, our recent work sheds light on the role of an endocytosis-dependent calcium release from the endoplasmic reticulum in the control of nuclear cAMP levels. This is achieved through the activation of local soluble adenylyl cyclase, which in turn regulates the activation of local protein kinase A (PKA) and downstream transcriptional events. In this review, we explore the dynamic evolution of research on cyclic AMP signaling, including the findings that led us to formulate the novel three-wave hypothesis. We delve into how we abandoned the paradigm of cAMP generation limited to the plasma membrane and the changing perspectives on the rate-limiting step in nuclear PKA activation. Keywords Abbreviations A-kinase anchoring protein Adenylyl cyclase Bacterial photoactivated adenylyl cyclase Cyclic nucleotide-gated ion channels Adenosine 3′,5′-cyclic monophosphate Clathrin-coated pits Corticotropin-Releasing Hormone Receptor 1 cAMP response element-binding protein Exchange Protein Directly Activated by cAMP 1 Prostaglandin E2 receptor 4 Endoplasmic reticulum Follicle-stimulating hormone receptor G-protein coupled estrogen receptor Guanosine triphosphate G-protein-coupled receptor GPCR-coupled kinase Inositol trisphosphate receptor Inositol trisphosphate Phosphodiesterase Protein Kinase A Phospholipase C Plasma membrane Popeye domain-containing proteins P-enolpyruvate carboxykinase Phosphodiesterase 4D5 Parathyroid hormone receptor Regulatory subunit type Iα Protein kinase A regulatory subunit type Iα Sphingosine-1-phosphate receptor Soluble adenylyl cyclase Trans-Golgi network Thyroid stimulating hormone receptor Reviewed by members of the JBC Editorial Board. Edited by Kirill Martemyanov

The beginning Adenylyl cyclase (AC) and its product, adenosine 3',5′-cyclic monophosphate (cAMP), were initially identified by Earl W. Sutherland's group during investigations into the mechanism of action of the hyperglycemic hormones, epinephrine and glucagon ( 1 , 2 ). They discovered that hormone-stimulated AC activity resides on the plasma membrane (PM) and that various hormones stimulate cAMP synthesis in different cell types ( 3 , 4 , 5 , 6 , 7 , 8 , 9 ). These findings established the foundation for the concept of a two-messenger system, with hormones acting as the first messengers and specific intracellular intermediate elements as the second messengers ( 9 ) ( Fig. 1 ). In the 1960s, Rodbell and Birnbaumer challenged the prevailing idea originally proposed by Sutherland’s group that hormone binding and AC activities resided within the same molecule, and each hormone activated its specific “cis”-AC. Through experiments involving a purified suspension of adipose cells, they observed a nonadditive response when different hormones increased cAMP levels. This observation led them to propose that the receptor and AC were separate entities ( 10 , 11 , 12 , 13 ). These studies were further supported by thoughtful fusion experiments conducted by Orly and Schramm in the mid-1970s, which bolstered the understanding of receptor and AC independence ( 14 , 15 , 16 ). Finally, the independent purification of the receptor and AC in the 1980s by the Lefkowitz and Pfeuffer groups, respectively, provided conclusive confirmation of their distinct nature ( 17 , 18 , 19 , 20 ). The ideas put forth by Rodbell and Birnbaumer were the first conceptualization of a signal transduction unit, consisting of three essential elements: a “discriminator” ( i.e. , receptor), an “amplifier” ( i.e. , catalytic AC), and an as-yet-unidentified “transducer” intermediate capable of translating binding energetics into enzyme activation ( 10 ). While the first transducer candidates were membrane phospholipids, the investigators came across the “GTP effect.” The addition of ATP, later known to be contaminated with considerable levels of GTP, reduced glucagon binding to membranes leading them to hypothesize that the transducer was the site of action of GTP ( 10 ). Gilman and Lefkowitz later observed that the GTP effects were specific to agonists ( i.e. , GTP shift), which led to the development of the first "ternary complex model" ( 21 , 22 , 23 ). This model aimed to describe the allosteric communication between ligand binding and nucleotide release. The concept of the GTPase cycle, as we understand it today, was initially proposed by Cassel and Selinger in the mid-1970s. They experimentally demonstrated the hormone's effect on steady-state GTPase and nucleotide release, which are the two primary regulatory branches of the cycle ( 24 , 25 , 26 ). But it was not until the pioneering work of Gilman and Rodbell, that the identity of the mysterious “transducer” was defined, with the purification of a regulatory element interposed between receptors and the AC ( 27 , 28 , 29 , 30 ). The cyclase activity was reconstituted in the Cyc - and UNC variants of S49 lymphoma cells, followed by purification of the “G/F” (now Gs) protein ( 31 , 32 ). The full in vitro reconstitution with purified components completed the story establishing receptor, G protein, and AC as the minimal signal transduction unit ( 33 ) ( Fig. 1 ). The first wave In 1989, the cloning of the first enzyme responsible for cAMP synthesis marked a significant breakthrough, leading to the discovery of additional transmembrane adenylyl cyclase isoforms (tmAC1-9) encoded by the ADCY1-9 gene family, each with diverse regulatory properties ( 34 ) ( Fig. 1 ). These isoforms are all under the regulatory influence of the master controller, Gαs which is activated by a subset of G protein-coupled receptors (GPCRs). In the “classical view” of the cAMP pathway, agonist binding to GPCRs leads to conformational changes that communicate allosterically to the nucleotide-binding site in the G-protein, resulting in the exchange of bound GDP for GTP on the Gαs subunit and the dissociation of Gαs-GTP and Gβγ dimer subunits. The active Gαs-GTP subunit stimulates one or more isoforms of the tmAC, which results in cAMP production that in turn binds and activates a set of effectors, including Protein Kinase A (PKA), Exchange Protein Directly Activated by cAMP 1 (Epac1), the cyclic nucleotide-gated ion channels (CNG), Popeye domain-containing proteins (POPDC) and the recently identified olfactory marker proteins (OMP) ( 32 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 ). Upon cAMP binding to PKA regulatory subunit (PKA-R), the catalytic subunit (PKA-C) is released and can diffuse into the nucleus, phosphorylate transcription factors, and initiate the transcription of cAMP-specific genes ( 45 ). Studies about the kinetics of GPCR responses reported that short-term agonist exposure generates reversible GPCR “desensitization,” requiring higher doses of agonist to re-generate a comparable cAMP response without necessarily involving a substantial reduction in the number of receptors on the cell surface ( 46 , 47 ). In contrast, long-term agonist exposure caused endocytosis of a significant proportion of the receptors followed by its lysosomal proteolytic degradation requiring de novo protein synthesis to restore the original response ( 48 ). However, a non-destructive process of receptor “sequestration” to endosomes was also described using cellular fractionation and radioligand binding assays. A substantial part of our knowledge of GPCR desensitization comes from the works of Lefkowitz and colleagues, who elucidated that catecholamine-induced AC desensitization was associated with β2 adrenergic receptor (β2AR) phosphorylation ( 49 ). Ligand-bound receptor endocytosis is initiated by GPCR-coupled kinase (GRK)-mediated phosphorylation which promotes the binding of members of the β-arrestin family ( 50 , 51 , 52 ). The binding of β-arrestins to phosphorylated GPCRs blocks Gαs coupling, and by the recruitment of endocytic machinery proteins [ e.g. , adaptor protein 2 (AP2) and clathrin heavy chain], the receptor is driven to clathrin-coated pits (CCPs) leading to its internalization via endocytosis ( 53 , 54 , 55 , 56 ) ( Fig. 1 ). Central to this classical view was the concept that the PM was the exclusive site from which GPCR/Gs/tmAC signaling originated and endocytosis was the mechanism for reducing or terminating signaling. Therefore, trafficking of the receptor in and out of the PM was a suitable way to explain how cells dealt with the persistent or recurrent stimulus of some "first messengers". The second wave In 1998, Lefkowitz’s group showed that endocytosis is required for β2AR-dependent activation of the mitogen-activated protein (MAP) kinases Erk1 and Erk2. In HEK293 cells expressing β-arrestin or dominant negative dynamin mutants, β2AR stimulation failed to activate MAP kinases without affecting the “plasma membrane-delimited processes” such as receptor coupling to G proteins ( 57 ). These original findings suggested that endocytosis serves not only as a mechanism to terminate signaling but also as a necessary process to convey signals to the downstream effectors ( 58 , 59 , 60 ). In 2006, it was described that Ste2, a pheromone-activated GPCR of budding yeast can produce Gαs-dependent signaling from endosomes ( 61 , 62 ). In the following years, evidence for “non-classical” endocytosis-dependent GPCR signaling was also found in mammalian cells ( 63 , 64 ). In 2009, three independent investigations showed that the thyroid stimulating hormone (TSHR), the parathyroid hormone (PTHR), and the sphingosine-1-phosphate (S1PR) receptors continue to generate Gαs-dependent signals after internalization ( 65 , 66 , 67 ) ( Fig. 1 ). Disruption of endocytosis can reduce or eliminate sustained cAMP production depending on the system. Through the use of conformational nanobody biosensors and optogenetic approaches, researchers have confirmed the absence of the GPCR-dependent transcriptional response in cells where GPCR/Gs activation is restricted to the plasma membrane (PM) which linked for the first time, endosomal cAMP generation with a specific function ( 65 , 68 , 69 , 70 , 71 ). Findings regarding temporal and spatial changes in Gs signaling and cAMP production have led to the concept of “first” and “second” waves of cAMP ( 72 ). Regardless of their ordinal denotation, they both refer to the signal source: the first wave originates from the PM, and the second, upon internalization, arises from internal compartments like endosomes or the trans-Golgi network (TGN). However, the term "second wave" is often vaguely used synonymously with the sustained elevation of cellular cAMP, which can be affected by pharmacological or genetic disruption of endocytosis (which is sustained in time, but still “first” wave) The time after agonist introduction required to detect a measurable effect of endocytosis disruption on cAMP signaling may be related to the time required for a pool of GPCR-tmAC to be sorted to the specific domain from which the complex is fully activated and initiate signaling. While this is the case for β2AR and PTHR, other GPCRs, like the dopamine receptor D1 (DRD1), show a more generalized influence over the cAMP response ( i.e. , affecting both the initial and sustained phases). An alternative interpretation may be that some GPCRs require active endocytic mechanisms for “acute” signaling ( i.e. , the first wave), while others may require endocytosis (or components that act after the complex has departed PM) for the second wave of cAMP signaling, and therefore blocking of endocytosis has a measurable effect at later time points ( 73 , 74 ). Although the number of sensors aimed at measuring GPCR activation and cAMP signals in specific compartments is increasing, the existence of first and second waves as discrete entities may be difficult to evidence since they occur in adjacent compartments and it could be some overlapping and interactions between the mechanisms that generate them. Dynamic changes in understanding β-arrestins While the involvement of β-arrestins in receptor internalization and desensitization is still a significant aspect of their function, they are also recognized as multifaceted signal transducers ( 75 , 76 , 77 , 78 ). Recent single-molecule studies showed unexpectedly, a spontaneous association of β-arrestin with the plasma membrane that facilitated the interaction with GPCRs and complex trapping at the CCPs ( 77 ). Upon internalization, GPCRs are first transported to the early endosomal compartment. From there, they have three possible routes based on their interactions with various partners ( 1 ): ubiquitination and subsequent transport to multivesicular bodies and lysosomes (degradation) ( 2 ); retrieval back to the PM (recycling/resensitization) ( 3 ); passage to TGN via the retromer complex (retrograde transport) ( 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 ). Remarkably, endosomal β-arrestin-bound GPCRs can stimulate Gs signaling, despite their mutually exclusive binding. Although full validation in cells is still missing ( 87 ), structural studies have revealed that β-arrestin can assume different active conformations when bound to GPCRs. Some of these conformations allow the formation of a large complex that includes both Gs and β-arrestin, known as a GPCR–Gs–β-arrestin megacomplex or megaplex ( 88 , 89 ) ( Fig. 1 ). Furthermore, these different conformations are associated with distinct sets of GPCRs. Class A GPCRs transiently bind β-arrestin, promoting rapid recycling and signal desensitization. On the other hand, class B GPCRs exhibit higher affinity binding to β-arrestin, enabling prolonged Gs signaling from intracellular compartments ( 90 , 91 ). In class B GPCRs, the stable association of β-arrestin serves as an endosomal scaffold for capturing released GβƔ upon activation, allowing multiple rounds of Gs activation. This mechanism has been proposed for receptors such as PTHR and V2R ( 66 , 92 , 93 , 94 ). Additionally, recent findings have uncovered a new role for PI(4,5)P2 (PIP2). While the recruitment of β-arrestin to the PM increases PIP2 levels and stabilizes β-arrestin-GPCR complexes, facilitating GPCR internalization, it has been discovered that transient β-arrestin interaction with class A GPCRs, as opposed to stable class B GPCRs, requires simultaneous PIP2 binding for efficient complex internalization ( 95 , 96 , 97 ). Lower PIP2 levels upon endocytosis facilitate β-arrestin dissociation, allowing its recycling to the PM. However, despite the well-established role of endosomal β-arrestin-dependent signaling, accumulating experimental evidence supports the existence of a β-arrestin-independent component in class B GPCRs. Recent reports indicate that the recruitment of β-arrestin to GPCRs in endosomes, although dependent on agonist activation, may not be strictly necessary for endosomal signaling ( 98 , 99 ). Further research is required to elucidate the mechanistic details underlying the generation of the second wave of (intracellular) cAMP, and its therapeutic potential in the development of drugs with improved specificity and efficacy ( 100 , 101 , 102 , 103 , 104 ). Trans-Golgi network: A signaling crossroads Conventionally, the TGN has been recognized as a platform for protein sorting during the secretory pathway, temporarily housing and/or modifying newly synthesized proteins en route to the PM. However, during retrograde transport, proteins diverge from the endocytic pathway and enter the TGN ( 105 , 106 , 107 ). Despite signaling from endosomes, the interaction of β2AR with components of the retromer complex appears crucial to its downstream signaling, while for PTHR signaling, it steers the receptor's transit toward the TGN, ultimately terminating the signal. Conversely, retrograde transport to the TGN facilitated by the retromer complex and effective signaling from this compartment was reported for TSHR and S1PR, both exhibiting no Gs activity at the endosomal compartment ( 74 , 92 , 108 , 109 ). In the context of TSHR signaling, Gs proteins are not internalized but rather there is a resident pool located at the TGN where they can interact and activate tmAC3 ( 65 ). For S1PR, it was described that newly synthesized receptors become trapped at the TGN after binding agonists that have been internalized and sorted therein, implying that receptors that never reached the PM could be activated within the cell ( 67 ). After reaching the TGN, the fate of GPCRs may diverge. For instance, SSTR2a returns to the PM and remains in an active conformation ( 110 ), whereas the G-protein coupled estrogen receptor (GPER) is sorted for lysosomal degradation ( 111 , 112 ). Furthermore, while several GPCRs reside within the TGN only transiently, β1AR, and the delta-opioid receptor (DOR) exhibit sustained localization in this compartment ( 113 , 114 ). An intracellular interplay The exposure of GPCRs to their ligands can vary greatly depending on the ligand's ability to cross the PM and the receptor's trafficking properties, which may result in transient or sustained periods away from the PM or even prevent the receptor from reaching the cell surface, as observed with newly synthesized S1PRs. However, the question of how PM and intracellular signaling complexes may be differently regulated and what mechanisms can generate sustained signaling from the endosome/TGN while terminating the signal at the PM remains open. While the players involved ( e.g. , Gs, β-arrestins, etc.) may be the same, the sorting of these components to different compartments may decide the location and duration of cAMP production and the activation of downstream pathways. Although most studies in the field focus on monitoring GPCRs upon endocytosis, much less is known about the fate of tmACs after internalization, the actual enzyme involved in the generation of cAMP. In HEK-293 cells, β2AR activation and internalization from PM also trigger the internalization of Gs and tmAC9, which is sufficient to induce downstream events without the involvement of any other tmAC isoforms. Interestingly, β2AR trafficking necessitates β-arrestin but not Gs, whereas Gs activation is required for the internalization of tmAC9 independent of β-arrestin ( 115 ). Therefore, although components of the signaling unit may employ distinct internalization mechanisms, there seems to be a coordinated internalization of the signaling components that allows them to coincide temporally and spatially in the intracellular milieu. Interestingly, it was recently shown that upon stimulation, endocytosed β2AR can recruit rapidly accelerated fibrosarcoma/mitogen-activated protein kinase kinase (Raf-MEK) and activate an endosomal extracellular signal-regulated kinase (ERK) pathway pool that propagates its signal to the nucleus ( 116 ). Only in recent times have we started to comprehend the significant impact of dictating the intracellular position of GPCRs and their signaling partners on cellular responses. It is becoming increasingly clear that the specific downstream targets and transcription patterns that will be activated can be determined by changing the subcellular location of cAMP production and maximizing its concentration near definite downstream elements of the pathway. The third wave In 2010, emerging evidence indicated soluble adenylyl cyclase (sAC; ADCY10) as an additional source of cAMP downstream of activated GPCRs ( 117 ). Both the follicle-stimulating hormone receptor (FSHR) and the prostaglandin E2 receptor 4 (EP4R) were found to activate sAC in a Gαs- and tmAC-dependent manner ( 118 , 119 ). FSHR triggers sAC via PKA-mediated activation of the Cystic Fibrosis Transmembrane Regulator (CFTR), leading to bicarbonate influx ( 119 , 120 ), an established sAC activator ( 121 ). Conversely, EP4R activates the PLC pathway, resulting in calcium (Ca 2+ ) release from the ER, which also acts as an sAC activator ( 122 ). Additionally, the Corticotropin-Releasing Hormone Receptor 1 (CRHR1) was reported to activate sAC through Ca 2+ increase, but in a Gαs-independent manner. While CRHR1 also stimulates tmACs via the activation of Gs proteins, evidence suggests that upon internalization, this receptor can generate sustained signaling that relies entirely on sAC, rather than tmAC ( 123 ). Interestingly, while PKA and Epac1 are necessary for sAC activation downstream of FSHR and EP4R, respectively, in the CRHR1 pathway, both PKA and EPAC function as downstream effectors of sAC ( 118 , 119 , 123 ). Previous studies conducted in our laboratory revealed that the TSH-triggered mitogenic response of thyroid cells relies on a synergistic Epac1-PKA activation, facilitated by radixin as a scaffolding unit for both cAMP effectors ( 124 , 125 ). This complex resides in a submembrane compartment close to one or more tmACs and utilizes Rap1b as a signal integrator. In a recent article, we demonstrated that TSHR stimulation initiates a PLC/IP3/IP3R pathway in a Gq-independent and internalization-dependent manner, resulting in the release of Ca 2+ from the ER, which then enters the nucleus and activates nuclear sAC ( 126 ). Pharmacological and genetic inhibition of sAC, which specifically affects nuclear but not cytosolic TSH-mediated cAMP increase, completely blocked nuclear cAMP accumulation, nuclear PKA activity increase, CREB phosphorylation, and cell proliferation ( Fig. 2 , right) ( 126 ). Furthermore, our findings indicate that cell proliferation can be supported solely by the optogenetic generation of nuclear cAMP, irrespective of upstream events occurring at the PM or in the cytosolic compartment. These results have led us to hypothesize that nuclear sAC generates a "third wave" of cAMP, activated downstream of PM (first wave) and endosomal/TGN-generated cAMP (second wave), and serves as the sole source of TSH-mediated nuclear cAMP accumulation ( 126 ). The internalization of the signaling complex positions cAMP production close to an ER cisternae and the nucleus, generating a compartment where: (a) cAMP concentration is enough to activate a local PLC isoform, probably via Epac1/Rap1b/PLCε ( 127 , 128 , 129 , 130 , 131 , 132 ), generating IP3 and triggering IP3R-mediated Ca 2+ release; (b) the released Ca 2+ enters the nucleus which, unlike cytosolic tmAC-generated cAMP, is not affected by PDE restriction and can readily reach the nuclear compartment to rapidly activate sAC ( 126 ) ( Figs. 1 and 2 , right). Evolving perspectives on the rate-limiting step determining nuclear PKA activation The role of cAMP in transcriptional regulation was first established in Escherichia coli based on the pioneering work of J. Monod on diauxic growth ( 133 , 134 , 135 ). In mammalian cells, studies in the early 1980s focused on the effect of the permeable analog dibutyryl-cAMP on the transcription of specific genes such as prolactin, P-enolpyruvate carboxykinase, and tyrosine aminotransferase ( 136 , 137 , 138 , 139 ). It was discovered that cAMP mediates the transcriptional control of these genes through a conserved cAMP response element (CRE) ( 140 , 141 ). Further investigations using the somatostatin promoter in PC12 cells led to the identification of CREB (cAMP response element-binding protein) as a 43 kDa nuclear protein that binds to the CRE domain ( 142 ). CREB belongs to the family of basic leucine zipper domain transcription factors ( 143 ). A connection between PKA-mediated phosphorylation and CREB was rapidly uncovered. It was observed that forskolin-mediated effects on transcription were not observed in PKA-deficient cell lines, and microinjection of the purified catalytic C-PKA subunit triggered an agonist-independent but CRE-dependent transcriptional response. Furthermore, PKA was found to directly phosphorylate CREB in vitro and in vivo at S133, an event crucial for CREB's transcriptional activity. These findings solidified the role of PKA-CREB signaling in the transcriptional regulation of genes containing CRE elements ( 143 , 144 , 145 , 146 , 147 , 148 , 149 ). How does a signal that originates at the PM reach the nucleus? Enzymatic and immunological studies consistently revealed that PKA acts as the primary downstream effector of cAMP, with its activity significantly enhanced within the nuclear compartment ( 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 ). Evidence suggested that upon cAMP generation and cytosolic activation of PKA, the C-PKA subunit is released from the complex and translocates to the nuclear compartment ( 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 ). However, skepticism arose regarding some of these studies due to potential experimental artifacts ( 169 , 170 ). The development of FRET-based cAMP sensors marked a significant advancement in the field. FlCRhR, a protein-based reagent in which both C-PKA and R-PKA are labeled with donor and acceptor fluorophores, pioneered this technique ( 171 ). The introduction of these reagents into living cells enabled the visualization of cAMP gradients in cells for the first time, offering direct experimental evidence supporting the previously proposed concept of cAMP compartmentalization. Microinjection of labeled PKA subunits also helped to clarify their distribution; while holoenzyme and R-PKA were solely cytosolic, a fraction of the C-PKA pool was observed in the nucleus. Raising cAMP levels with hormones or incubation with permeable cAMP analogs increased the proportion of C-PKA within the nucleus ( 171 , 172 , 173 , 174 ). Nuclear C-PKA entry was not saturable, nor affected by temperature or ATP depletion, arguing for a purely diffusive mechanism ( 175 ). The development of an anti-pS133 CREB antibody played a crucial role in establishing a correlation between PKA activation, nuclear translocation, and transcriptional events ( 176 ). Stimulation with secretin, forskolin, and the cAMP analog 8-Br-cAMP resulted in a gradual increase in the nuclear entry of C-PKA and pCREB levels. These changes reached a steady state approximately 30 to 40 min after stimulation and showed a linear correlation with the activation of cAMP-sensitive promoter reporters. Based on the kinetic parameters of PKA determined in vitro , it was expected that CREB phosphorylation would occur within seconds to minutes. However, the slow kinetics observed in cells indicated that nuclear translocation of C-PKA might be the rate-limiting step for downstream phosphorylation and subsequent transcriptional events ( Fig. 2 , left). More recently, the use of targeted versions of genetically encoded FRET-based cAMP and PKA sensors has revealed novel kinetic properties. While agonist stimulations elicit rapid parallel elevations of cAMP levels both at the PM and nucleus, PKA exhibits a slower rise in the latter compartment ( 177 ). This observed pattern provided further evidence supporting the notion that the slow diffusional translocation of C-PKA represented the rate-limiting step. However, the discovery of a resident pool of PKA in the nucleus, which forms a complex with AKAP and PDE4 ( 178 ), that was later characterized as AKAP95-PDE4D5-PKA ( 179 ), brought about a significant shift in focus from C-PKA translocation to the diffusion of cAMP as the limiting factor ( Figs. 1 and 2 , middle). Moreover, isoproterenol stimulation induces PDE4D5's departure from the nucleus, mediated by its binding to the internalized GRK-phosphorylated receptor-β-arrestin complex ( 70 , 179 ). By altering the cytosolic/nuclear distribution of PDE, this new mechanism provided a path linking endocytosis with nuclear cAMP signaling. Nonetheless, reduced PDE activity can solely elevate nuclear cAMP levels when nuclear synthesis and/or entry occur at a basal rate, yet these studies did not investigate the precise origin of nuclear cAMP. While ubiquitously expressed, sAC is currently recognized as the sole cyclase isoform that has been detected in the nucleus. Thus, nuclear cAMP accumulation is mediated by either sAC-mediated local synthesis or by its diffusion from the cytosol ( 159 , 180 , 181 ). We have recently reported that in thyroid cells, stimulation by TSH led to a rapid nuclear cAMP accumulation and PKA activation within 1 to 2 min ( 126 ). Remarkably, this response was found to be entirely dependent on the activity of a nuclear-located sAC ( 126 ). These findings suggest that neither C-PKA translocation nor cAMP diffusion, but rather the activation of nuclear sAC, serves as the rate-limiting event in this process ( Fig. 2 , right). Why is a small molecule like cAMP unable to enter the nucleus? Despite its high diffusivity in water, cAMP exhibits limited diffusion within cells, resulting in a short-range effect from its source ( 182 ). Evidence indicates the involvement of factors such as phosphodiesterases (PDEs), buffering proteins, and physical barriers ( 183 ). PDEs are enzymes found throughout the cytosol that play a crucial role in regulating cAMP levels. They form small nanodomains where the concentration of cAMP is maintained below the effectors’ activation constants. These nanodomains, estimated to have a radius of less than 100 nm using advanced techniques like the “nanoruler” FRET approach ( 184 ), create localized environments that prevent non-specific activation of adjacent cAMP effectors. Only when agonist stimulation saturates the capacity of PDEs can the concentration of cAMP in these nanodomains reach levels required for effector activation. Within an experimental setting, PDE inhibition decreases the system's ability to effectively counteract elevated cAMP levels, dismantling low-concentration microdomains. Similarly, non-physiological stimulation of cyclases, using forskolin or cAMP analogs, makes it impossible for PDEs to match the rate of cAMP degradation with its production. cAMP demonstrates limited mobility within cells, as proven by studies using fluorophore-labeled cAMP ( 185 , 186 ). The constrained mobility of cAMP also results from binding to partnering molecules that function as buffers, preserving low cAMP levels during rest; this buffering ability, which is approximately 20 μM, gives rise to buffered diffusion involving association-dissociation cycles. This process allows for cAMP diffusion following stimulation-mediated saturation of the buffering capacity. Moreover, recent discoveries have revealed that cAMP binding to RIα-PKA (protein kinase A regulatory subunit type Iα) triggers the formation of molecular condensates known as cytosolic "droplets". These droplets have significantly higher concentrations of cAMP compared to the bulk cytosol, leading to reduced mobility of cAMP within them ( 187 ). Furthermore, the preferential binding of PDE8 to cAMP-bound RIα-PKA forms stable complexes with enhanced hydrolytic activity ( 126 ). This process, known as substrate channeling, allows for the hydrolysis of cAMP within the complex before its release into the bulk cytosol. While in vivo demonstration of channeling within droplets is still pending, compelling evidence of its existence has emerged in in vitro studies, further enriching our understanding of the intricate dynamics at play. These factors, combined, may explain why highly diffusive molecules like cAMP encounter challenges in reaching high effective concentrations near their nuclear effectors, despite their potential to diffuse through the larger nuclear pores. How then does cytosolic cAMP activate nuclear soluble cyclase? Endocytosis plays a pivotal role in facilitating the transmission of information from endosomal cAMP to the nucleus, thereby initiating transcriptional activation. According to the prevailing model, the proximity of endosomes to downstream effectors and the nucleus enables cAMP to activate adjacent C-PKA molecules, followed by a gradual translocation to the nucleus, taking over 20 min and accounting for only 1 to 2% of total C-PKA ( 188 ). This internalization-dependent activation of nuclear events is consistent with optogenetic investigations utilizing targeted bPAC, a photoactivatable cyclase, which revealed that only endosomal, rather than PM, cAMP synthesis is associated with nuclear transcription ( 189 ). Furthermore, a recent insightful approach involving the relocation of endosomes from a perinuclear to a peripheral position demonstrated the essential requirement of endosomal proximity to the nucleus for effective signal propagation toward transcription. The researchers hypothesized that, upon GPCR activation, moving endosomes closer to the nucleus plays a pivotal role in circumventing PDE hydrolysis, which is more pronounced in the cell periphery. This positioning facilitates cAMP production in proximity to downstream effectors and/or allows for efficient cAMP entry into the nucleus ( 188 , 190 ). In our recent findings in thyroid cells, following TSHR internalization, intracellular cAMP triggers a Gq-independent PLC pathway, leading to IP3/IP3R-mediated release of Ca 2+ from the ER. Notably, it is the released Ca 2+ and not cAMP itself that diffuses into the nucleus, stimulating sAC and activating a nuclear pool of PKA. This cascade ultimately culminates in CREB phosphorylation and the transcription of cAMP-dependent pro-proliferative genes ( 126 ). We propose that the positional effect of endosomes serves as an efficient trigger for the aforementioned cAMP-Ca 2+ interplay. Currently, ongoing investigations focus on identifying the specific tmAC isoforms involved, elucidating its regulation, and unraveling the mechanisms underlying the internalization-dependent cAMP-Ca 2+ crosstalk. Concluding remarks In summary, we discussed new experimental results and proposed a new three-wave cAMP signaling model. In this new model, GPCR/Gs activation initiates an internalization-dependent activation of PLC, leading to IP3 generation. This, in turn, triggers an IP3R-mediated Ca 2+ release from neighboring ER cisternae that enters the nucleus, where it activates nuclear sAC, generating the newly proposed third wave of cAMP ( Fig. 2 , right). While our studies did not focus on the role of PDEs, in the three-wave cAMP model, it is implicit that these enzymes limit and spatially confine the generated cAMP in the cytosol and/or the nucleus. Such coordinated processes likely ensure the generation of the necessary cAMP levels to activate downstream effectors and orchestrate precise cellular responses. In conclusion, deeper investigation into the regulatory mechanisms that dictate the spatial arrangement of ACs and PDEs holds the potential to unveil a sophisticated and dynamic landscape of microdomains with higher or lower cAMP concentration. These microdomains may exhibit mobility, interplay, synergy, or antagonism, profoundly influencing the activity of downstream effectors, gene expression, and ultimately, cellular fate. Elucidating these intricacies may provide insights into the fundamental principles governing gene expression and cellular signaling, opening new avenues for understanding and manipulating cellular responses in health and disease. Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article.

Acknowledgments The references incorporated into this review were chosen with a focus on their pertinence to the subjects discussed in this article. Emphasis was placed on seminal research, recent progress, and works that elucidated fundamental principles within the parameters of this review. Nonetheless, it is important to acknowledge that due to the extensive breadth of available literature, certain valuable contributions may not have been included, and for this omission, we extend our regrets. Author contributions D. L. A. supervision, conceptualization; writing – reviewing and editing; project administration; funding acquisition; A. P. and X. Z. investigation, validation; A. P. visualization, writing – original draft. Funding and additional information This work was supported by 10.13039/100000002 National Institutes of Health Grants R01 GM130612 and GM148449 to D. L. A. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

CC BY

no

2024-01-16 23:43:45

J Biol Chem. 2023 Nov 26; 300(1):105497

oa_package/4b/06/PMC10788541.tar.gz

PMC10788543

38072063

Statistical methods GraphPad Prism 9.0 (GraphPad Software, Inc) was used to generate graphs and perform statistical analysis in this study. We used the unpaired two-tailed t test for comparisons between two groups and one-way ANOVA for multigroup comparisons. p < 0.05 was considered statistically significant.

Results Ent and the iron-responsive exometabolome in UPEC To define the iron-responsive exometabolome of UPEC and its relationship to the ent- encoded biosynthetic pathway, we compared small molecule profiles in conditioned media from the model UPEC strain UTI89 and its isogenic biosynthesis-deficient mutant, UTI89Δ entB ( 21 ), in low and high iron conditions ( 32 ) using LC–MS. Sparse principal component analysis (sPCA) was performed on these data to determine whether exometabolite composition distinguishes the different conditioned media. sPCA yields a series of principal components (PCs), mathematical terms that are a series of independent linear combinations of features associated with feature variability between specimens. Here, PC1 is a mathematical expression of exometabolites comprising the largest mode of exometabolomic variation (26.8% of total variation) between conditioned media, with PC2 being the next largest, and so forth ( Figs. 1 A and S1 A ). In a two-dimensional score plot of PC2 versus PC1, exometabolomes of low iron media conditioned by wildtype UTI89 formed a discrete cluster of values separated along PC1 from the profiles of other conditions. This is the greatest group-wise separation among the conditioned examined and is consistent with a distinctive iron-responsive exometabolome in UTI89 dominated by ent -associated biosynthetic products. Logistic regression of PC1 values to classify these two PC1 exometabolome clusters yielded a prediction accuracy of 1.0 (SD = 0, Fig. S1 B ) and an area under the receiver operating characteristic curve of 1.0 (SD = 0, Fig. S1 C ) with fourfold crossvalidation. PC1 differences did not correspond to intergroup differences in growth density ( Fig. S2 ). The distinctive PCA grouping of wildtype UTI89 grown in low iron corresponds with detection of Ent, the canonical eponymous product of the Ent biosynthesis pathway ( Fig. 1 B ). Together, these results are consistent with a prominent role for the Ent biosynthetic pathway in defining the iron-responsive UTI89 exometabolome. Multiple Ent-associated products define the UTI89 exometabolome The ent- associated exometabolites that define PC1 are of interest and may be identified by loading analysis, which identifies the magnitude of each exometabolite’s contribution (the loading) to a PC value. For PC1, loading analysis identifies multiple exometabolites contributing to PC1 ( Fig. 1 C ). Detailed mass spectrometric and chromatographic analyses of the 13 molecular features with the largest PC1 loadings associated with the UTI89 exometabolome under iron-restricted conditions ( Figs. S3–S12 ) identified a series of 10 DHBS polymers ( Fig. 2 A ) consistent with Ent and salmochelin biosynthesis ( 46 , 47 , 48 ) ( Table S1 ). These included cyclic and linear DHBS trimers with 0, 1, or 2 C-glucosylations, DHBS dimers with 0, 1, or 2 C-glucosylations, and monomeric DHBS previously reported in an avian pathogenic E. coli strain. Unlike the avian pathogenic E. coli strain, UTI89 did not produce triglucosylated Ent products ( 49 ), consistent with interstrain differences in the Ent exometabolome that are not explained by iroA alone. To more precisely quantify these exometabolites, we constructed a high-resolution targeted LC–MS/MS multiplexed selected reaction monitoring (LC–MRM) method ( Table 1 ). We confirmed that all 10 products were present in low iron media conditioned by wildtype UTI89, were significantly diminished in high iron media conditioned by UTI89, and were undetectable in any media conditioned by UTI89Δ entB ( Figs. 2 B , S13 , and S14 , p < 0.001). In an iroA- null strain (UTI89Δ ybtS Δ iroA ) that lacks the C-glucosylation pathway, C-glucosylated exometabolites were absent, whereas nonglucosylated exometabolites were elevated, ( Figs. 2 B and S14 , p < 0.001), consistent with the precursor–product relationship between these exometabolites. Together, these results connect iron-associated biosynthetic activity in UPEC to multiple Ent-related exometabolites extending beyond the canonical trimeric DHBS products. Outer membrane importers differentially affect Ent-associated exometabolites While trimer products are consistent with the Ent biosynthetic pathway, the specific origin of short-length dimeric and monomeric products, (DHBS) 2 , G 2 -(DHBS) 2 , G 1 -(DHBS) 2 , and DHBS is unclear. We considered that these truncated products could reflect premature release from the biosynthetic pathway (anabolic production) ( 11 , 50 ), spontaneous extracellular hydrolysis, or intracellular esterolysis of imported ferric catechol siderophores (catabolic production) ( 46 , 47 , 51 ). To distinguish these possibilities, we compared UTI89 with UTI89Δ tonB , an isogenic mutant with a deficiency in siderophore import at the outer membrane. In E. coli and related Gram-negative bacteria, the TonB–ExbB–ExbD complex energizes outer membrane transporters to import ferric siderophores ( 52 ). Relative to UTI89, UTI89Δ tonB cultures exhibit a strikingly dichotomous effect on Ent-associated exometabolites, with elevated trimer concentrations and diminished dimer and monomer concentrations ( Fig. 3 ). These differences were not associated with differential growth density between groups ( Fig. S15 ). These results are consistent with intracellular dimer and monomer production in events that are downstream from extracellular trimer import. Coculture with import-proficient UTI89 complements the UTI89ΔtonB phenotype To further test the hypothesis that monomer and dimer exometabolites are products of siderophore catabolism, we devised a coculture system in which UTI89Δ tonB is poised to serve as a siderophore producer and Ent-deficient UTI89Δ entB as a siderophore consumer. We hypothesized that UTI89Δ entB import of UTI89Δ tonB -derived exometabolites would counteract the UTI89Δ tonB dimer and monomer deficiency phenotype. Compared with UTI89Δ tonB -conditioned media, media conditioned by the UTI89Δ tonB + UTI89Δ entB coculture contained significantly greater monomer and dimer concentrations and variably lower trimer concentrations ( Fig. 3 ). As such, the combined ent exometabolome of UTI89Δ tonB + UTI89Δ entB more closely resembled that of wildtype UTI89 than either mutant alone. Different levels of Ent-associated products were not associated with growth density differences between groups ( Fig. S15 ). These results are consistent with extracellular UTI89Δ tonB -derived trimers as public goods that are imported by UTI89Δ entB , which partially catabolizes them and releases esterolysis products to the extracellular space ( 47 , 51 ). Monomer and dimer production during trimer-dependent growth Ent-associated trimers contain two or three serine–serine ester bonds and three serine–DHB peptide bonds ( Fig. 2 A ) with potential for hydrolysis to yield free DHB and serine, which may become new metabolic substrates in the cytoplasm. Despite this catabolic potential, UTI89 releases incompletely hydrolyzed trimer catabolites. To determine whether this occurs during siderophore-dependent growth, we measured the Ent-associated exometabolomes of siderophore-null UTI89 (UTI89Δ entB Δ ybtS ) cultures with trimer supplementation. Growth of this strain was rendered siderophore dependent by addition of bovine serum albumin, a biologically relevant nonspecific binder of labile iron ions ( 53 , 54 ). Compared with siderophore-free controls, Ent, MGE, or DGE addition stimulated UTI89Δ entB Δ ybtS growth ( Fig. 4 ) and were progressively consumed during culture ( Fig. 5 , A , D , and G ), consistent with their canonical siderophore activity. Dimer and monomer production varied with the specific trimer provided. Ent supplementation yielded neither dimer nor monomer ( Fig. 5 , B and C ), MGE supplementation yielded (DHBS) 2 , G 1 -(DHBS) 2 , and DHBS ( Fig. 5 , E and F ), and DGE yielded G 1 -(DHBS) 2 , G 2 -(DHBS) 2 , and DHBS ( Fig. 5 , H and I ). Dimer C-glucosylation products are structurally consistent with the C-glucosylation structure of each trimeric substrate. These results are consistent with dimer and monomer production from esterolysis following cyclic trimer-mediated iron delivery. The lack of dimer or monomer generation from Ent is unexpected based on production by Ent-producing UTI89Δ ybtS Δ iroA ( Fig. 2 B ). The nature of this discrepancy is unclear and may arise from unappreciated catabolic differences, regulatory pathways, or intracellular trafficking connected to these different strains, the different culture conditions, or combinations thereof. UTI89 uses exogenous DHB to synthesize Ent It is unclear why UTI89 foregoes complete catabolic reclamation of intracellular trimer constituents to instead release incompletely hydrolyzed trimer catabolites to the extracellular space. Bonacorsi et al. ( 55 ) have connected enhanced bacterial DHB production for siderophore biosynthesis as a virulence-associated activity in neonatal meningitis–associated E. coli , suggesting that UPEC could similarly benefit from DHB reclamation. To determine whether UPEC can use exogenously derived DHB to support trimer biosynthesis, we derived an experimental system to monitor its incorporation. Specifically, we used a reverse isotope-labeling strategy to detect incorporation of unlabeled carbon atoms from exogenous DHB during culture with 13 C 3 -glycerol as the carbon source. We found that addition of 200 μM DHB led to the appearance of a new Ent isotopolog with an m/z value 21 atomic mass units lower than 13 C-substituted Ent, consistent with 12 C 7 -DHB incorporation at all three catechol sites ( Fig. 6 and Table S2 ). DHB supplementation also yielded lower levels of singly and doubly substituted isotopologs that are 7 and 14 atomic mass units lower, respectively ( Fig. S16 and Table S2 ). These results expand upon previous findings that the Ent deficiency of entA -deficient K12 E. coli cultures could be reversed by media supplementation with DHB ( 56 , 57 ). Direct incorporation of an isotopically distinctive precursor shows that a UPEC strain Ent biosynthetic pathway can directly incorporate DHB from a nonendogenous source. This suggests that DHB incorporation is not limited to a tightly compartmented intracellular site supplied exclusively by endogenous biosynthesis. Analogous incorporation of exogenously supplied 13 C-labeled 2-hydroxybenzoic acid or 2-aminobenzoic acid into the exometabolites yersiniabactin and escherichelin has been previously observed ( 11 , 58 ), suggesting a generalized aromatic metabolite scavenging potential in UPEC. These observations are consistent with the potential metabolic value of complete Ent hydrolysis in UPEC. Siderophore activity of purified dimers We hypothesized that UPEC forego complete trimer hydrolysis because the resulting dimers retain valuable siderophore activity. This would enable biosynthesis of one trimer molecule to support multiple rounds of iron import. To test this, we evaluated the siderophore activity of purified dimers in the siderophore-dependent growth condition described previously. We observed that supplementation with either of two dimer metabolites, (DHBS) 2 or G 2 -(DHBS) 2 , restored bacterial growth in iron-deficient conditions, with slower growth kinetics for G 2 -(DHBS) 2 dimer than those observed for (DHBS) 2 dimer and trimers ( Figs. 4 and 7 A ). DHBS production was generated from (DHBS) 2 supplementation and catabolism only ( Fig. 7 , B – E ). Glucosylated N -DHBS (G 1 -DHBS), which was expected to be generated from G 2 -(DHBS) 2 hydrolysis, was poorly resolved in the LC–MS/MS conditions used here, likely because its high hydrophilicity renders it poorly resolved in reversed-phase liquid chromatography. Together, these data are consistent with siderophore activity by both C-glucosylated and nonglucosylated dimers.

Discussion Multiple bacterial siderophore systems release exometabolites in addition to their canonical biosynthetic end products. Here, we find that UPEC have the potential to hydrolyze Ent trimers to recover raw materials for new biosynthesis, yet limit this process to instead generate and secrete incompletely hydrolyzed Ent (dimer), which is released as a siderophore. This suggests a bacterial “choice” between complete hydrolysis to maximize catabolic reclamation of biosynthetic substrates and incomplete hydrolysis to generate a dimeric catabolite that retains siderophore activity. The former lowers the biosynthetic cost of new trimer biosynthesis, whereas the latter yields another siderophore. The balance between these fates (complete or partial hydrolysis) may reflect evolutionary adaptation or, possibly, active regulation. Siderophore function, as classically understood, is a metabolically costly process in which siderophore biosynthesis and secretion occurs because there is a chance some of these siderophores will diffuse back as iron complexes to support nutritional demands. For Ent and related siderophores, iron release requires hydrolysis by intracellular esterases, suggesting a diminished return on biosynthetic investment compared with siderophores that are nondestructively “recycled” and resecreted ( 37 , 47 ). The aforementioned results suggest that a more nuanced situation has evolved in which trimer hydrolysis proceeds only to the extent necessary for iron release so that a catabolite may be secreted for additional rounds of siderophore-mediated iron delivery. The growth-promoting siderophore activity of dimers observed here is supported by a previous report of (DHBS) 2 -mediated 55 Fe localization to E. coli ( 59 ). Additional supportive evidence was reported for iron-dependent growth of Campylobacter jejuni , an Ent nonproducer that uses (DHBS) 2 from E. coli as a siderophore in an example of siderophore “piracy” by this organism ( 60 ). The siderophore activity of dimers is thus associated with another example of metabolic cost avoidance. Although not measured in the present work, it is possible that the loss of a catechol group lowers the iron (III) affinity of Ent-associated dimers relative to trimers, representing a possible trade-off between metabolic efficiency and effector function. A 1:1 dimer–iron complex provides catechol hydroxyl ligands for four of the six iron (III) coordination sites. This tetradentate coordination is observed for other siderophores such as pyochelin from Pseudomonas aeruginosa ( 61 , 62 ) and azotochelin from Azotobacter vinelandii ( 63 ). Despite this possible drop in affinity relative to Ent ( K d ≈ 10 −52 M), we observed comparable iron acquisition capability by (DHBS) 2 dimers. Affinity differences between dimer and trimers could be consequential if associated with differential iron (III) scavenging from complexes encountered in tissue, urine, or other microenvironments. The entire series of ent -associated exometabolites, not trimers alone, should be considered in future studies of iron sequestration mechanisms in human and animal hosts. Incomplete trimer hydrolysis by UPEC suggests that inefficiency in siderophore esterase and peptidase systems has evolved to support dimer-associated iron acquisition. The extent of hydrolysis may vary with the specific trimer and the hydrolases recruited during iron recovery. We found that siderophore-null UTI89 consumed purified Ent without significant monomer or dimer secretion, whereas purified glucosylated Ent trimers (MGE and DGE) resulted in abundant monomer and dimer formation. It remains unclear whether these differences reflect higher order metabolic interactions or unappreciated regulatory process affecting hydrolase activity, possibly responsive to Ent C-glucosylation. Complete hydrolysis of C-glucosylated trimers could be evolutionarily disfavored because of the likely inability to use C-glucosylated DHB as an Ent biosynthetic pathway. Lin et al. ( 47 ) previously reported that purified Fes and IroD can hydrolyze Ent trimer to produce DHBS monomer and (DHBS) 2 dimer, and IroE can hydrolyze Ent to produce (DHBS) 2 dimer. We used a tonB deletion mutant, rather than an outer membrane transport mutant, to assess the effect of siderophore import because of uncertainty over which of the many TonB-dependent transporters import which of the many Ent-associated products investigated here. Among E. coli , FepA, IroN, Cir, and Fiu have, to date, been described to import catechols, though their specificity is not completely defined. Among these, only FepA is conserved among all E. coli. and is known to mediate ferric Ent import ( 64 , 65 ), whereas IroN is known to mediate import of glucosylated Ent trimers ( 66 ). Cir and Fiu have been demonstrated to mediate Ent breakdown product import ( 67 , 68 , 69 , 70 , 71 ). Monomeric DHBS-iron(III) complex import has been described by Fiu, FepA, and Cir in E. coli ( 71 ) and by IroN and FepA receptors in Salmonella typhimurium ( 72 ). As for Ent dimers, (DHBS) 2 is found to be taken up by E. coli ( 59 ), though its specific uptake routes are unclear. Recently, the relevance of nontrimer catechol uptake is exemplified by the clinical antibiotic efficacy of β-lactam agents containing one iron-chelating monomeric catechol moiety, such as cefiderocol ( 73 , 74 , 75 ). The substrate specificity for these transporters and their relationship to the network of Ent-associated exometabolites described here is incompletely understood. Further investigation of this may yield deeper functional insights into Ent system function. In conclusion, the exometabolite network described here is consistent with a series of regulatory and functional adaptations that minimize costs of Ent-mediated iron delivery in E. coli cells. Ent biosynthesis, a metabolically costly process, is activated under iron-restricted conditions by ferric uptake regulator repressor regulation. At low bacterial density, E. coli have the ability to render Ent a private good, available only to the producing organism, and minimizing diffusional loss ( 76 ). Submaximal siderophore hydrolysis in UPEC to release dimers extends the iron delivery potential of Ent and its derivatives. Together, these results are consistent with a biochemical network connecting intracellular and extracellular E. coli metabolomes to cost-effectively support iron-dependent growth. These findings may help explain why Ent expression can be sustained as the universal siderophore system in urinary E. coli isolates. Aspects of this network may be useful in devising new antimicrobial therapeutics for UPEC and related bacteria.

Uropathogenic Escherichia coli (UPEC) secrete multiple siderophore types to scavenge extracellular iron(III) ions during clinical urinary tract infections, despite the metabolic costs of biosynthesis. Here, we find the siderophore enterobactin (Ent) and its related products to be prominent components of the iron-responsive extracellular metabolome of a model UPEC strain. Using defined Ent biosynthesis and import mutants, we identify lower molecular weight dimeric exometabolites as products of incomplete siderophore catabolism, rather than prematurely released biosynthetic intermediates. In E. coli , iron acquisition from iron(III)–Ent complexes requires intracellular esterases that hydrolyze the siderophore. Although UPEC are equipped to consume the products of completely hydrolyzed Ent, we find that Ent and its derivatives may be incompletely hydrolyzed to yield products with retained siderophore activity. These results are consistent with catabolic inefficiency as means to obtain more than one iron ion per siderophore molecule. This is compatible with an evolved UPEC strategy to maximize the nutritional returns from metabolic investments in siderophore biosynthesis. Keywords Abbreviations 2,3-dihydroxybenzoic acid N-(2,3-dihydroxybenzoyl)serine enterobactin LC–MS/MS multiplexed selected reaction monitoring principal component sparse principal component analysis uropathogenic Escherichia coli urinary tract infection Reviewed by members of the JBC Editorial Board. Edited by Joan B. Broderick

Urinary tract infections (UTIs) are among the most common outpatient and inpatient infections encountered by physicians ( 1 , 2 , 3 , 4 ). Escherichia coli is the bacterial species most commonly associated with UTI, accounting for about 70 to 95% of clinical cases ( 5 , 6 ). Clinical E. coli isolates associated with UTI that exhibit polymorphisms in conserved genes ( 7 , 8 , 9 ) and carry accessory genes associated with increased pathogenic potential are designated as uropathogenic E. coli (UPEC) ( 2 , 4 , 10 ). Prominent among these virulence-associated adaptions are iron uptake systems, such as siderophores, which use distinctive chemical groups to competitively bind iron and render it selectively bioavailable to support bacterial growth ( 2 , 3 , 10 , 11 , 12 , 13 , 14 ). In UPEC, siderophore iron-acquisition systems have been identified as both colonization and virulence factors during UTI pathogenesis ( 15 , 16 , 17 , 18 , 19 ). The enterobactin (Ent), salmochelin, yersiniabactin, and aerobactin siderophore systems have all been associated with E. coli strains causing extraintestinal infections ( 20 , 21 , 22 ). Siderophores are specialized secreted metabolites (exometabolites) that are synthesized by nonessential bacterial pathways and competitively chelate extracellular iron(III) during the iron-limited growth conditions characteristic of infection microenvironments ( 16 , 17 , 23 , 24 ). The resulting iron(III)–siderophore complexes are selectively imported by bacterial transporters as an iron source. E. coli and many other Gram-negative bacteria actively transport iron–siderophore complexes through outer membrane receptors using the cytoplasmic membrane–localized TonB–ExbB–ExbD complex, which transduces energy from the proton motive force ( 25 , 26 , 27 ). Siderophore biosynthesis and transport systems are regulated by the ferric uptake regulator, a transcriptional repressor that downregulates siderophore gene transcription in conditions associated with high cytosolic iron ( 28 ). All UPEC carry the conserved Ent system and may encode up to three additional siderophore systems, each associated with chemically distinctive exometabolomes ( 29 , 30 , 31 ). Biosynthesis of these additional exometabolites incurs additional metabolic demands ( 32 ), suggesting that their sustained presence in clinical populations is associated with siderophore-specific payoffs. For example, the salmochelin system, encoded by genes in the iroA cassette, glucosylates Ent to improve its aqueous solubility and evade sequestration by the host immune protein lipocalin-2–siderocalin–NGAL ( 14 , 33 , 34 ). The yersiniabactin system in UPEC supports multiple nonsiderophore functions not associated with Ent or salmochelin ( 35 , 36 ). Yersiniabactin production incurs metabolic costs, which appear to be mitigated by an ability to recycle the intact siderophore to support multiple rounds of metal ion import ( 37 ) and an additional quorum-sensing regulatory input that emphasizes biosynthesis in diffusionally restricted or crowded environments where the siderophore is more likely to remain nearby ( 38 ). Ent is detectable in the urine of patients with UTIs, where its synthesis is required to evade growth inhibition by lipocalin-2 ( 13 , 14 ). Ent achieves exceptional iron(III) affinity ( K d ≈ 10 −52 M) with three catechol (1,2-dihydroxybenzene) groups that provide all six coordination sites for iron(III) ( 10 , 39 ). Ent is synthesized by a nonribosomal peptide synthetase system encoded by entABCDEF . This nonribosomal peptide synthetase system is a molecular assembly line that synthetizes Ent by repeatedly forming enzyme-bound N -(2,3-dihydroxybenzoyl)serine (DHBS) and linking them via ester bonds until a cyclic trilactone core composed of three DHBS is released ( 40 , 41 ). In UPEC expressing the iroA cassette, the glucosyltransferase IroB further modifies Ent catechols with up to three distinctive C-linked glucoses ( 10 , 42 ). Iron retrieval from imported iron(III) Ent complexes (with or without C-glucose modifications) requires dissociation through both esterase-catalyzed Ent hydrolysis (by Fes and/or IroD) and iron(III) reduction to iron(II) ( 43 , 44 , 45 ). In this study, we examined the Ent biosynthetic pathway’s contribution to the iron-dependent UPEC exometabolome. We measured targeted mutant strains and chemical complementation with purified products to assess the catabolic origins of short-length catechol exometabolites. To assess the nutritional potential of siderophore catabolism, we used reverse stable isotope labeling to find that 2,3-dihydroxybenzoic acid (DHB) from outside the biosynthetic pathway could be used for Ent biosynthesis. Finally, we used a siderophore-dependent growth condition to evaluate the siderophore potential of nontrimeric Ent metabolites found in the UPEC exometabolome. Our findings are consistent with a catabolic network that has evolved to maximize the iron delivery potential of Ent biosynthesis. Experimental procedures Bacterial strains and culture conditions We examined exometabolite production, consumption, and use with the well-characterized cystitis-derived model UPEC strain UTI89 and its previously described isogenic mutants UTI89Δ entB , UTI89Δ tonB , and UTI89Δ entBΔybtS ( Table S3 ) ( 11 , 13 , 21 , 77 ). UPEC strain CFT073 was used for bacterial secondary metabolite production because of its high yield of C-glucosylated products ( Table S3 ) ( 11 , 13 ). Bacterial cultures were grown from single colonies in LB broth for overnight under 37 °C, washed with PBS, back-diluted 1:1000 into filter-sterilized M63 minimum media, inoculated with 200 μl into 96-well microplates, and incubated under 37 °C for in the indicated assays. Experimental cultures were conducted in M63 minimum media containing 0.2% glycerol as a carbon source and 10 μg/ml nicotinic acid (low iron), with 100 μM FeCl 3 (high iron), or with 10 μM bovine serum albumin addition (siderophore dependent) ( 21 , 32 ). Bacterial growth was quantified by the absorbance at 600 nm using a Spectrophotometer (Beckman Coulter, DU-800) or an incubated microplate reader (Tecan Spark). Untargeted LC–MS Untargeted full scan LC–MS profiling was performed to characterize the extracellular metabolome (exometabolome) in media conditioned by UTI89 and UTI89Δ entB under low and high iron conditions. Conditioned medium was collected by centrifugation and filtration through 0.22 μM filters with storage at −80 °C. Samples were thawed on ice for LC–MS analysis with a Shimadzu Prominence UFLC-coupled AB Sciex 4000 QTrap mass spectrometer with a Turbo V electrospray ionization source. LC separation was performed on an Ascentis Express phenyl-hexyl column (100 × 2.1 mm, 2.7 μm; Sigma–Aldrich) with solvent A (HPLC-grade water + 0.1% formic acid; Sigma–Aldrich) and B (90% acetonitrile + 0.1% formic acid; Sigma–Aldrich) at 0.35 ml/min in a 36 min gradient as follows: solvent B increased from 2% to 35% by 23 min, then increased to 98% by 33 min, and finally held steady at 98% for another 3 min. Electrospray ionization -MS was performed in negative ion–enhanced MS mode, scanning from 50 to 1500 m/z . A quality control sample was injected first and every 10 samples thereafter to assess instrument stability. MarkerView, version 1.2.0 (Sciex) was used for peak alignment, generating the list of peaks for computational metabolome comparison analysis in the next section ( 13 , 14 , 32 ). Computational metabolomic comparison Exometabolome comparisons between four groups of samples, including UTI89 grown in low and high iron media (wildtype and wildtype + Fe, respectively) and the Ent-null mutant UTI89Δ entB in low and high iron media ( entB and entB + Fe, respectively), were performed on a combined computational model consisting of an sPCA followed by a logistic regression classification. The computation was performed in R and Python, using the scikit-learn module and mixOmics package, respectively ( 78 , 79 , 80 , 81 ). Of note, sparsity penalization was enforced in the PCA dimensionality reduction step to prevent overfitting for this metabolome metadata consisting of much higher component dimensions than the number of samples ( 82 , 83 ). The iron-responsive submetabolome in UTI89 extracellular space was identified by the loading analysis of all identified metabolites. Product ion scan and targeted LC–MS/MS Product ion scan measurements were conducted to characterize chemical structures of the 10 Ent-associated molecules. The LC separation as aforementioned but with a flow of 0.5 ml/min and a 16 min gradient as follows. Solvent B increased from 5% to 56% by 10 min, then increased to 98% by 12 min, and finally held steady at 98% for another 4 min. MS/MS product ion spectra of each negative ion was obtained in the enhanced product ion mode ( 84 , 85 ). Targeted LC–MS/MS MRM analyses were performed to validate the identities of 10 Ent-associated metabolites that were determined by the full-scan comparative metabolomic analysis as described previously. MRM parameter protocols ( Table 1 ) were established based on the results of product ion scan for each of the 10 targeted Ent-associated metabolites ( 11 , 13 , 14 , 21 ). Exometabolite purifications Ent-associated exometabolites were generated by growing CFT73 in M63/0.2% glycerol medium supplemented with DHB (Sigma–Aldrich) and 100 μM dipyridyl at 37 °C for 18 h. Culture supernatant was collected and separated by four consecutive steps, including a DEAE-sepharose resin (Sigma), an Amberlite XAD16N resin (20∼60 mesh; Sigma), an Kromasil Eternity 5-PhenylHexyl column (250 × 4.6 mm, 5 μm; Nouryon), and an Ascentis Express Phenyl-Hexyl column (100 × 4.6 mm, 2.7 μm; Sigma–Aldrich) to achieve the purification of five Ent-associated molecules, including Ent, MGE, DGE, [(DHBS) 2 , and G 2 -(DHBS) 2 , as previously described ( 11 , 47 ). Culture supernatant was first applied to a methanol (20%)-conditioned DEAE-sepharose column (Sigma). The column was washed with water and then eluted with 7.5 M ammonium formate. The DEAE eluate was supplemented with 120 mM sodium dithionite, incubated with methanol-conditioned Amberlite resin (XAD16N; Sigma–Aldrich) overnight, and eluted with 100% methanol. The eluate was concentrated in a rotatory evaporator (R-100 Rotavapor; BUCHI), lyophilized (Labconco), resuspended in HPLC-grade water plus 0.1% formic acid, and further purified on a Bio-Rad BioLogic DuoFlow 10 system equipped with a QuadTec UV–Vis detector and a Kromasil Eternity-5-PhenylHexyl column (Sigma–Aldrich). The Kromasil column was run at 0.30 ml/min with HPLC-grade water plus 0.1% formic acid (solvent A) and acetonitrile plus 0.1% formic acid (solvent B) using gradient as follows. Solvent B held steady at 2% for 1.0 ml, then increased to 15% over 1 ml, then increased to 52% over 40 ml, and finally increased to 100% over 1 ml. The DuoFlow elute was finally separated by another Ascentis Express Phenyl-Hexyl column in a Shimadzu Prominence UFLC system coupled with an SPD-M20A Prominence Diode Array detector. In order to purify the compounds with different properties, the LC separation was performed by injecting solvent A (HPLC-grade water + 0.1% formic acid; Sigma–Aldrich) and B (90% acetonitrile + 0.1% formic acid; Sigma–Aldrich) at 0.5 ml/min with a 44 min gradient under two scenarios as follows. Solvent B increased from 2% to 35% or 44% by 35 min, then increased to 98% B by 38 min, and finally held steady at 98% for another 6 min. Fractions containing purified molecules were measured via UV–Vis detection at 319 nm, pooled together, dried down by lyophilization, and stored in −80 °C freezer. On day of use, samples were resuspended in HPLC-grade water plus 0.1% formic acid, and concentrations were calculated by Beer–Lambert law using UV–Vis absorbances at 319 nm with an extinction coefficient of 11,200 M −1 cm −1 . Purity was confirmed by targeted LC–MS/MS measurements ( 11 , 86 , 87 , 88 ). Exogeneous DHB for synthesizing Ent in isotope-labeling assay To determine whether UPEC can synthesize Ent from DHB that is not immediately generated by endogenous DHB biosynthesis ( 40 , 41 , 89 ), we grew UTI89 from single colonies in LB broth for 12 h at 37 °C, washed with PBS, back-diluted 1:1000 into 13 C 3 -glycerol M63 minimum media with or without the supplement of 200 μM 12 C-DHB in a 96-well plate, and grown at 37 for 24 h. Targeted LC–MS/MS of Ent was conducted to monitor the incorporation of 12 C from incorporation of unlabeled DHB ( Table S2 ) by comparing 13 C-substituted Ent isotopologs into which 0, 1, 2, or 3 12 C 7 -DHB were incorporated. Data availability The computer codes for the analyses in this study are available in Github ( https://github.com/QL5001/EntMetabolome_script ; branch name: main; commit ID, e555df2). All other data generated and analyzed in this study are included in the published article and supporting information. Supporting information This article contains supporting information ( 11 , 13 , 14 , 21 , 46 , 47 , 51 , 86 , 90 , 91 , 92 ). Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article.

Supporting information Author contributions Z. Z. and J. P. H. conceptualization; Z. Z., J. I. R., and L. K. S. methodology; Z. Z. investigation; Z. Z. writing–original draft; J. P. H. writing–review & editing; Z. Z. visualization; J. P. H. supervision; J. P. H. funding acquisition. Funding and additional information J. P. H. acknowledges funding from the 10.13039/100000030 Centers for Disease Control Prevention Epicenters Program Grant (CU54 CK 000162) and the 10.13039/100000002 National Institutes of Health grants R01DK099534 and R01DK111930. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Centers for Disease Control and Prevention or the National Institutes of Health.

CC BY

no

2024-01-16 23:43:45

J Biol Chem. 2023 Dec 10; 300(1):105554

oa_package/91/40/PMC10788543.tar.gz

PMC10788561

38043801

Results Characteristics of putative S. constricta opsins and Gα proteins Initially, a total of 28 opsin-like sequences (named Sc_opsin1 - 28 ) were screened from the S. constricta genome. Following the removal of sequences with a similarity of over 98% and those lacking 7 TM helixes, a final set of 23 opsin homologs were selected as the targeted genes ( Tables S1 and S2 ). Through amino acids (aa) sequence alignment, these homologs were found to encompass most of the conserved aa and domains characteristic of typical opsins ( Fig. 1 ). These features included a K residue in the TM7 domain for chromophore binding, two cysteines (C) for disulfide bond formation, a counterion site with a negatively charged aa (glutamic acid, E) for stabilizing the protonated Schiff base ( 9 , 29 ), the NPXXY motif for maintaining structural integrity and stability of the visual pigment ( 30 ), the typical HPK/NKQ pattern of r/c-opsins ( 31 , 32 , 33 ), and the E/DRY motif for stabilizing the inactive-state conformation of opsins ( 34 ). These results suggest that S. constricta opsins have undergone conserved evolution and likely possess potential phototransduction functions. By constructing a phylogenetic tree, we categorized the opsin homologs from S. constricta into five distinct groups: two r-opsins (Sc_opsin1 and 5), one neuropsin (Sc_opsin25), one peropsin (Sc_opsin4), two retinochromes (Sc_opsin7 and 27), and seventeen xenopsins ( Fig. 2 ). When compared to the opsin families of four other marine bivalves ( Fig. S1 and Table S1 ), it was found that the xenopsin subfamily was significantly expanded within the genome of S. constricta . However, the Go-opsin, originally identified in the scallop Patinopecten yessoensis ( 18 ), was not present. Additionally, we identified a total of 19, 11, 15, and 16 opsin homologous sequences within the genomes of M. mercenaria , M. philippinarum , C. gigas , and M. yessoensis , respectively ( Tables S1 and S3 ). This observation indicates a considerable divergence of the opsin family composition among marine bivalves ( Fig. S1 ). Meanwhile, a total of 6 Gα protein sequences were identified within the S. constricta genome: Gαq, Gαo, Gαi, Gαs1, Gαs2, and Gα12 ( Table S2 ). The phylogenetic tree revealed the grouping of S. constricta Gα proteins with the corresponding Gα proteins of Homo sapiens , Drosophila melanogaster , Platyneresis dumerilii , and Maritigrella crozieri ( Fig. S2 A ). Notably, the specificity of Gα proteins is primarily determined by their C-terminal aa sequence ( 35 , 36 ). Consequently, we aligned the S. constricta Gα protein sequences with those of H. sapiens ( Fig. S2 B ). The results demonstrated a pronounced conservation of the C-terminal aa sequence within the S. constricta Gα proteins, indicating their conserved functions throughout evolution. Temporal and spatial expression patterns of putative S. constricta opsins As shown in Figure 3 and Table S4 , the expression of putative opsins exhibited significant variations throughout the developmental stages of S. constricta . When considering the expression patterns of different opsins at a specific developmental stage, the zygotes were characterized by strong representation of Sc_opsin17 , followed by Sc_opsin27 , 22 , and 7 ( Fig. 3 A ). The trochophore larvae and veliger larvae predominantly featured Sc_opsin7 , followed by Sc_opsin23 , 17 , and 27 ( Fig. 3 , B and C ). The umbo larvae exhibited high expression of Sc_opsin5 and 7 , followed by Sc_opsin1 , 2 , 17 , and 18 ( Fig. 3 D ). The creeping larvae were dominated by Sc_opsin5 , followed by Sc_opsin7 , 1 , 18 , 12 , 2 , 17 , and 14 ( Fig. 3 E ). The single pipe larvae were represented by Sc_opsin7 , 5 , and 18 , followed by Sc_opsin1 , 12 , and 27 ( Fig. 3 F ). Finally, the juvenile clams demonstrated dominance of Sc_opsin7 and 5 , followed by Sc_opsin1 , 13 , 18 , 27 , and 12 ( Fig. 3 G ). Regarding the expression patterns of the same S. constricta opsin across different developmental stages ( Fig. S3 ), most opsins , including Sc_opsin1 , 2 , 3 , 4 , 7 , 11 , 17 , 19 , 20 , 22 , 23 , 24 , and 27 , displayed significantly high expression levels in the trochophore larvae and veliger larvae. However, Sc_opsin5 displayed elevated expression in the umbo larvae, while Sc_opsin12 , 13 , and 14 exhibited high expression levels in the creeping larvae. Sc_opsin18 showed high expression in the umbo larvae, creeping larvae, single pipe larvae, and juvenile clams. In contrast, the remaining opsins demonstrated relatively low and showed no significant differences among all developmental stages. As exhibited in Figure 4 and Table S5 , the expression of putative opsins also displayed significant variations across different tissues of S. constricta . Considering the expression patterns of different opsins within the same tissue, we found that the siphon exhibited representation of Sc_opsin7 , followed by Sc_opsin1 and 12 ( Fig. 4 A ). In the gill tissue, Sc_opsin7 dominated, followed by Sc_opsin11 and 1 , then 22 , 14 , and 17 ( Fig. 4 B ). Within the mantle, Sc_opsin7 led the expression, followed by Sc_opsin11 and 13 , then Sc_opsin27 and 1 ( Fig. 4 C ). In the intestine, Sc_opsin11 dominated, followed by Sc_opsin7 , and then Sc_opsin17 and 1 ( Fig. 4 D ). The labial palp featured representation by Sc_opsin7 , followed by Sc_opsin11 , 18 , 14 , and 1 ( Fig. 4 E ). Finally, the foot tissue was characterized by dominance of Sc_opsin1 and 7 , followed by Sc_opsin12 , 25 , 27 , and 4 ( Fig. 4 F ). Shifting focus to the expression patterns of the same S. constricta opsin within distinct tissues ( Fig. S4 ), we observed that Sc_opsin1 , 7 , and 25 exhibited high expression levels in the foot, while Sc_opsin5 and 12 were notably expressed in the siphon. Sc_opsin11 and 17 were prominently expressed in the intestine, and Sc_opsin18 displayed elevated expression in the labial palp. In contrast, the remaining opsins showed relatively low expression levels and no significant differences among all tissues. Expression plasticity of four cloned putative S. constricta opsins As depicted in Figure 5 , the expression of opsin genes ( Sc_opsin1 , 5 , 7 , and 12 ) was influenced by different light spectra. Generally, these four S. constricta opsins consistently exhibited the highest expression in juveniles acclimated to yellow light, with only slight variations in response to other light spectra. Specifically, Sc_opsin1 showed the highest expression under yellow light, while it did not significantly differ under other light spectra ( Fig. 5 A ). Sc_opsin5 displayed the highest expression under yellow light and in the dark, with no significant differences under other light spectra ( Fig. 5 B ). Sc_opsin7 had the highest expression under yellow light, followed by white light, and the lowest expression under other light spectra ( Fig. 5 C ). Finally, Sc_opsin12 exhibited the highest expression under yellow light, followed by white and red lights, with no significant differences under other light spectra ( Fig. 5 D ). Heterologous expression of four cloned putative S. constricta opsins in HEK293T cells As shown in Figure 6 , the 7 TM proteins of putative S. constricta opsins were successfully expressed in HEK293T cells, as confirmed by immunocytochemistry. Specifically, in the negative control group transfected with the empty vector, no red fluorescence associated with the 1D4 tag was detected ( Fig. 6 A ). However, in the positive control group transfected with the plasmid containing H. sapiens Opn4, red fluorescence was observed and colocalized with the membrane fluorescence (green color) as expected, at least partially ( Fig. 6 B ). Similar immunocytochemistry results were found when cells were transfected with the plasmids containing S. constricta opsins, as illustrated in Figure 6 , C – F . These results suggest that the HEK293T cells can serve as an effective tool for further investigating the phototransduction function of S. constricta opsins, as previously reported ( 37 , 38 ). Phototransduction pathways driven by four cloned putative S. constricta opsins The phototransduction pathway of opsin is mediated by the distinct types of Gα protein, such as Gαq, Gαs, and Gαi, with which it is coupled. In particular, the Gαq cascade leads to an elevation in cytoplasm Ca 2+ levels, the Gαs cascade causes an increase in cAMP concentration, while the Gαi/o/t (hereafter referred to as Gαi) cascade results in a decrease in cAMP levels and a slight elevation in cytoplasmic Ca 2+ concentration. However, it is important to note that pertussis toxins selectively deactivate the Gαi cascade without affecting the Gαq or Gαs cascades. To clarify the phototransduction pathways of putative S. constricta opsins and their coupled Gα proteins, real-time monitoring of Ca 2+ and cAMP levels was conducted in HEK293T cells expressing S. constricta opsins when exposed to light stimulation. It’s worth noting that as the Gα protein evolution is conserved ( Fig. S2 ), no S. constricta Gα proteins were transfected into the HEK293T cells. In terms of the Gαq cascade, the cytoplasmic Ca 2+ levels were significantly increased (>100,000 fold) in HEK293T cells expressing H. sapiens Opn4 when exposed to light irradiation, as expected, compared to the negative control ( Figure 7 , Figure 8 , Figure 9 , Figure 10 A ). Similar results were observed in cells expressing Sc_opsin1 ( Fig. 7 A ) and Sc_opsin5 ( Fig. 8 A ) but not in cells expressing Sc_opsin7 ( Fig. 9 A ) and Sc_opsin12 ( Fig. 10 A ). Meanwhile, the addition of pertussis toxins did not have any effect on the increase of Ca 2+ in those cells ( Figure 7 , Figure 8 , Figure 9 , Figure 10 B ). These findings suggest that Sc_opsin1 and 5 may be functional in phototransduction by coupling with the Gαq protein to increase the cytoplasmic Ca 2+ levels. Regarding the Gαs cascade, the cytoplasmic cAMP levels were significantly increased (>100,000 fold) in HEK293T cells expressing JellyOp when exposed to light irradiation, as expected, compared to the negative control ( Figure 7 , Figure 8 , Figure 9 , Figure 10 C ). Moreover, the increase in cAMP in those cells was not influenced by the addition of pertussis toxins ( Figure 7 , Figure 8 , Figure 9 , Figure 10 D ). However, no significant differences in cAMP changes were observed in cells expressing the four S. constricta opsins ( Figure 7 , Figure 8 , Figure 9 , Figure 10 C ) when compared to the negative control. Hence, it can be concluded that Sc_opsin1, 5, 7, and 12 do not couple with Gαs protein to increase cAMP levels. As far as the Gαi cascade is concerned, given the inherently low basal cAMP level in HEK293T cells, the cAMP level was artificially elevated by treating cells with forskolin before light irradiation ( Figs. 7–10 , E and F ). The cAMP level was significantly decreased in HEK293T cells expressing H. sapiens RH1 when exposed to light irradiation, as expected, compared to the negative control ( Figure 7 , Figure 8 , Figure 9 , Figure 10 E ). Similar results were observed in the cells expressing Sc_opsin12 ( Fig. 10 E ), but not in cells expressing Sc_opsin5 ( Fig. 8 E ) and Sc_opsin7 ( Fig. 9 E ). Interestingly, in cells expressing H. sapiens RH1, there was a subsequent increase in cAMP levels over time, whereas in cells expressing Sc_opsin12, the cAMP levels continued to decrease ( Fig. 10 E ). Additionally, the decrease of cAMP in those cells was completely inhibited by the addition of pertussis toxins ( Figure 7 , Figure 8 , Figure 9 , Figure 10 F ). These results suggest that Sc_opsin12 may play a functional role in phototransduction by coupling with the Gαi protein to decrease the cAMP levels. Notably, the artificially elevated cAMP levels were also decreased significantly ( p < 0.05) in cells expressing Sc_opsin1 when exposed to light irradiation ( Fig. 7 E ). However, this decrease was not pronounced as observed in the positive control. This suggests that, in addition to mediating the Gαq cascades, Sc_opsin1 may also play a role in mediating the Gαi cascades to decrease the cAMP level to some extent. Critical aa for phototransduction function of putative S. constricta opsins Using the Sc_opsin5 as an example, two mutants, K356H (altering K356 at TM7) and N362K (modifying N362 at NPXXY), were constructed and subsequently transfected into HEK293T cells. As shown in Figure 11 , A and B , the two mutant proteins could be successfully expressed in HEK293T cells. Regarding the function of signal transduction, the Gαq-mediated increase in Ca 2+ remained efficiently functional in cells expressing the Sc_opsin5 mutant N362K ( Fig. 11 C ). In contrast, the same increase in Ca 2+ was not observed in cells expressing the K356H mutant ( Fig. 11 C ). This result suggests that the retinal binding site is also essential for the phototransduction function of S. constricta opsins, at least for Sc_opsin5. Spectral sensitivity of phototransduction function of putative S. constricta opsins Using the S. constricta Gq-opsins (Sc_opsin1 and 5) as examples, cells expressing Sc_opsin1 or 5 were exposed to flashes of different light spectra. As depicted in Figure 12 A , compared to the initial level, the Ca 2+ level in cells expressing Sc_opsin1 showed the highest increase when flashed with white, yellow, and green lights (>100,000 fold), followed by blue light (>50,000 fold), and then red and violet lights (>10,000 fold). Similarly, as shown in Figure 12 C , compared to the initial level, the Ca 2+ level in cells expressing Sc_opsin5 exhibited the highest increase when flashed with white, blue, and green lights (>100,000 fold), followed by yellow light (>50,000 fold), while no responses were observed when flashed with red and violet lights. Furthermore, to enhance the interpretation of the response versus wavelength relationship, we presented the averages of the maximum values under each light irradiation condition in Figure 12 , B and D , connecting them with straight lines. These results suggest that the phototransduction intensities of S. constricta opsins are highly dependent on the light spectrum, even for the same types of opsins.

Discussion Marine bivalves represent a highly diverse and evolutionarily successful group of organisms in the marine ecosystem. Confronted with the challenging light environment, these organisms have evolved a wide range of photoreceptor organs ( 39 ), making them a valuable source for studying the evolutionary adaptation to marine photoecology. In the present study, our aim was to investigate the photoreceptor molecule opsins and their underlying phototransduction mechanisms in a representative eyeless species, S. constricta . Molecular system of phototransduction is conserved in S. constricta Gene duplication, followed by subsequent functional divergence of opsins, has played a crucial role in expanding the photoreceptive capabilities of animals ( 40 , 41 ). In this study, the opsin genes were found to be abundant in the five marine bivalves under investigation, as shown in Table S1 and Fig. S1 . This finding underscores the significance of light in their developmental processes and survival. Notably, a novel opsin group known as xenopsin was identified and found to be significantly expanded in S. constricta compared to the other four bivalves, while the c-opsin was absent. Xenopsins have been recently identified in several protostomes, including mollusks, brachiopods, rotifers, platyhelminths, annelids, and cnidarians ( 5 , 11 , 37 , 42 ). It has been discovered that xenopsin exhibits similarity to c-opsin and is functional in coupling with Gαi protein to drive the light signal transduction in flatworms ( 37 ). Furthermore, unlike other bivalves, S. constricta lacks Go-opsin, which is initially identified in ciliary photoreceptors. This opsin type induces hyperpolarization through a cGMP-gated channel, akin to vertebrate rhodopsins and cone opsins ( 18 , 43 , 44 ). Therefore, it is speculated that the expanded presence of xenopsins within S. constricta may potentially compensate for the absence of other opsin types. Additionally, Gq-opsins have been recognized as the primary photoreceptors involved in phototransduction in invertebrates ( 19 , 45 , 46 ). In this study, two Gq-opsins (Sc_opsin1 and 5) were identified in the genome of S. constricta , whereas the other four marine bivalves investigated here possessed 4 to 6 Gq-opsins. This disparity may be also attributed to the significant expansion of xenopsins in S. constricta , which likely alleviated the selective pressure on Gq-opsins. Overall, the distinct differentiation in the composition of opsin families among the five marine bivalves might be closely linked to their specific light environments. This, in turn, could contribute to the emergence of lineage-specific biological features. Moreover, homologous sequences of retinochrome, peropsin, and neuropsin were also identified in the S. constricta genome. Previous studies have demonstrated that retinochrome and peropsin serve as photo-isomerases, specifically converting all-trans retinal into cis-retinal to restore opsin to its active state, without interacting with any type of G proteins ( 16 , 47 , 48 ). Therefore, a similar function of photo-isomerases might also occur for S. constricta ’s retinochrome and peropsin. On the other hand, neuropsin has been shown to be a bistable UV-responsive photopigment ( 49 ) and is expressed in the mammalian retina, brain, and even ears ( 50 ). However, its function in marine bivalves remains unclear thus far. Importantly, the phototransduction pathway of a specific opsin is mediated by distinct types of Gα proteins to which it is coupled. In this study, a total of 6 Gα proteins belonging to five classes were identified. All of them contained the corresponding conserved C-terminal sequences found in mammalian Gα proteins, indicating the conserved evolution of the Gα protein and their functions. Taken together with the afore-mentioned results of S. constricta opsins, it can be concluded that a functional and complex photosensitive system likely exists in this eyeless bivalve species. Expression of S. constricta opsins is dependent on developmental stages and tissues Investigating gene expression patterns, especially across various developmental stages and tissues, can provide valuable insights into predicting their potential functions. In teleosts, it has been observed that opsins’ expression varies significantly during development, likely as an adaptation to changes in the light environment ( 51 , 52 ). A similar phenomenon was noted in S. constricta opsins, which might also be closely linked to the shifting light conditions throughout its development. During the life cycle of S. constricta , it progresses through distinct stages of “planktonic-metamorphosis-attachment-benthic”, marked by significant changes in light exposure, transitioning from relatively strong and longer wavelength spectra to dimmer and shorter wavelength spectra. Notably, a majority of S. constricta opsins exhibited high expression levels in the trochophore larvae and veliger larvae stages, which are critical for the bivalve’s metamorphosis. Additionally, specific opsins were also prominently expressed in other corresponding developmental stages of S. constricta . These findings imply that opsins likely play a crucial regulatory role in S. constricta ’s development. Collectively, these results underscore the importance of an appropriate light environment for the successful breeding and cultivation of S. constricta . Meanwhile, as a representative eyeless marine bivalve, S. constricta displays pronounced photosensitivity ( 25 , 26 , 27 , 28 ), although the underlying photosensitive tissues have yet to be elucidated. Recently, studies have demonstrated the photosensitivity of the eyeless C. gigas ( 53 ). Subsequently, a rhodopsin-like gene was identified in C. gigas , showing high expression in the mantle tissue. Notably, the photosensitive capability of C. gigas was significantly hindered upon knockdown of this gene ( 22 ). Likewise, sea urchin tube feet, considered their photosensitive organs, express r-opsins and the paired box 6 (PAX6) protein ( 54 , 55 ). Furthermore, certain eyeless cnidarians have exhibited photosensitivity, with opsin expression linked to extraocular photoreception ( 56 , 57 ). Hence, the tissues expressing opsins could be potentially serve as sites for nonvisual photosensitivity in organisms. In this study, more than four opsins were found to be highly expressed in peripheral tissues like the mantle, siphon, and foot of S. constricta , suggesting their potential role as photosensitive tissues in this bivalve. Notably, several opsins also displayed high expression in internal tissues like the intestine and labial palp. This suggests that these opsins might have roles beyond light sensitivity in S. constricta , such as functions related to taste, hearing, and thermosensation, as indicated in other studies ( 58 , 59 , 60 ). Additionally, only Sc_opsin7 exhibited relatively higher expression across all tissues, underscoring its pivotal role in S. constricta ’s photosensitive system. Responsiveness of S. constricta opsins to light spectra is evident It was hypothesized that if S. constricta opsins were functional in phototransduction, their expression would be influenced by the environmental light spectra, as reported in other aquatic animals ( 61 , 62 , 63 ). As anticipated, the expression of the four cloned S. constricta opsins exhibited distinct variations in juvenile S. constricta after 1 week of acclimation to different light spectra. Remarkably, their highest expression levels were consistently observed under yellow light conditions. This finding aligns with our previous study, which demonstrated that the growth, feeding rate, digestion ability, and antioxidant capability of juvenile S. constricta peaked when cultured under yellow light ( 26 ). Similar patterns have been documented in other studies, where opsin expression showed a positive correlation with growth ( 61 , 62 ). This relationship could be attributed to the activation of the phototransduction pathway when opsin perceive light, subsequently triggering feeding behavior and other growth-related metabolic processes. Supporting this hypothesis, increased transcripts of growth hormone (GH), insulin-like growth factor (IGF-I), and neuropeptide Y (NPY) were observed in Epinephelus malabaricus when reared under beneficial blue light ( 61 ). However, in juvenile S. constricta , the expression levels of these four opsins generally remained unchanged when exposed to light spectra other than yellow light. This could be attributed to species-specific variations in opsin responses or potentially influenced by the duration of acclimation. For instance, reports indicate that opsin expression in African cichlids Metriaclima mbenji can rapidly change in response to varying light environments within a short span of 3 days ( 64 ). In contrast, certain teleosts such as Cyprinella lutrensis requires a longer acclimation period (30 days) to adapt to external light changes ( 65 ). Additionally, we found distinct variations in the expression levels of S. constricta opsins between white and yellow light conditions, despite white light containing all spectra, including yellow. This phenomenon might arise from the competition or inhibition effects that different light spectra within white light, except for yellow, could have on influencing the perception of the yellow spectrum by Sc-opsins . Alternatively, it’s possible that the intensity of the yellow spectrum within white light is relatively weaker compared to that of pure yellow light. This disparity in intensity could also contribute to the observed variations in the expression of Sc-opsins , as previously reported in other aquatic animals ( 66 ). Phototransduction function of S. constricta opsins is intricately mediated by specific Gα proteins To date, investigations into the phototransduction pathways driven by marine bivalve opsins have predominantly focused on identifying critical components, such as Gα proteins and downstream enzymes ( 17 , 18 , 67 ). However, direct evidence of Gα protein cascades remains limited. To our knowledge, only one study has reported the existence of such evidence in the context of the scallop P. yessoensis opsin2 (AB006455.1) ( 68 ). Specifically, this study revealed a light-dependent increase in cAMP level observed in HEK293T cells expressing the scallop P. yessoensis opsin2. Importantly, this response remained unaffected by the treatment of pertussis toxin ( 68 ). In this study, we confirmed that Sc_opsin1 and 5 belong to the Gq-opsin category, coupling with Gαq protein, while Sc_opsin12 falls into the Gi-opsin classification, coupling with Gαi protein. Additionally, Sc_opsin1 was found to function partially as a Gi-opsin as well. Similar observations have been reported previously, demonstrating that, like other GPCRs, opsins are capable of activating different members of Gα proteins, thereby initiating both Ca 2+ and cAMP signal transduction cascades ( 69 ). This diversity in the biological functions of opsins could be closely linked to their ability to couple with multiple Gα proteins, leading to different phototransduction pathways with varying intensities and kinetics ( 68 , 70 ). However, in cells expressing Sc_opsin7, no luminescence related to cAMP and Ca 2+ changes were detected upon exposure to light. This suggests that Sc_opsin7 might not couple with any Gα protein cascade. This observation aligns with the phylogenetic analysis, which places Sc_opsin7 within the retinochrome group. This group functions as photo-isomerases, without coupling with any type of G proteins ( 16 , 47 , 48 ). However, it cannot be excluded that poor surface expression of Sc_opsin7 in HEK293T cells might mask its potential function in phototransduction, which requires further investigation. Furthermore, although both H. sapiens RH1 and Sc_opsin12 led to a light-dependent decrease in cAMP levels in HEK293T cells, a distinct difference in kinetics was observed. A similar phenomenon has been reported in the lamprey Petromyzon marinus parapinopsin, where blue light irradiation induced a continuous decrease in cAMP level in HEK293S cells ( 71 ). This divergence in kinetics might arise from the incompatibility of the light signal termination mechanism (such as GPCR kinases and arrestins) in HEK293T/S cells with exogenous opsins. Another explanation could be that the activated Sc_opsin12/ P. marinus parapinopsin remains stable or bistable in the phototransduction system ( 10 ). Moreover, reports suggest that to adapt to dim light, vertebrate rod opsins exhibit a prolonged signaling state, resulting in slower response kinetics, transduction pathway, and recovery of visual sensitivity after bleaching, compared to cone opsins. This adaptation greatly enhances their photosensitivity ( 72 ). Based on these observations, we speculated that the extended and sustained Gα protein cascade triggered by Sc_opsin12 might serve similar roles to those of vertebrate rod opsins. This prolonged response could be advantageous for amplifying photosensitivity to detect dim light within the natural habitat of S. constricta . K residue at TM7 is essential for the phototransduction function of S. constricta opsins As anticipated, the Sc_opsin5-K356H mutant was unable to induce light-dependent changes in Ca 2+ levels. This deficiency can be attributed to the fact that the K residue at TM7 serves as the binding site for the opsin’s chromophore. It’s worth noting that studies on the evolution of opsins have proposed that the common ancestor of opsins lacked the chromophore-binding site represented by the K residue. This evolutionary development occurred later in the history of opsins ( 73 ). Supporting this hypothesis, placopsins ( 73 ) and pseudopsins ( 74 ) are both devoid of the critical K residue. Similarly, in our study, two S. constricta xenopsins (Sc_opsin18 and 23) also lacked the K residue at the retinal-binding site. Given the multifaceted functions of opsins, including roles unrelated to light sensitivity such as mechanoreception, chemoreception, and thermoception ( 7 , 75 ), the perspective that the retinal-binding domain is an absolute requirement for opsins has been called into question. Regarding the NPXXY domain, numerous studies have reported its association with G protein binding ( 9 , 76 ). However, our current study indicates that the Gαq protein cascade remains effectively driven by the Sc_opsin5-N362K mutation. This suggests that, at least for Sc_opsin5, the NPXXY domain might be not essential for the photosensitivity of S. constricta opsins. Nevertheless, it is imperative to conduct further studies to validate this hypothesis. One potential approach is to completely delete this domain and observe the resulting effects. Therefore, beyond comprehensive sequence alignment and evolutionary analysis, it is essential to conduct relevant biochemical or cellular experiments to rigorously ascertain the exact function or functional domains of these new putative opsins. Phototransduction function of S. constricta opsins exhibits sensitivity to different light spectra It is widely recognized that each opsin possesses a specific absorption for an optimal light spectrum, known as the wavelength of maximum absorbance (λmax). The precise determination of λmax often requires direct micro-spectrometric measurements in the opsin’s natural environment or by measuring the λmax of the recombinant visual pigment through in vitro purification ( 21 , 77 ). However, these methods remain challenging for GPCR proteins like opsins due to their extremely low expression levels in situ and in vitro . Given the high sensitivity achieved through luminescence detection, our study directly measured the photosensitivity of two representative S. constricta Gq-opsins (Sc_opsin 1 and 5) in response to various light spectra by monitoring Ca 2+ luminescence in HEK293T cells. As anticipated, the increased in Ca 2+ levels significantly differed in cells expressing Sc_opsin 1 or 5 when exposed to different light spectra. This approach proved to be effective and suitable for predicting opsin λmax. Specifically, both Sc_opsin1 and 5 exhibited the highest photosensitivity under white light, which might be attributed to the comprehensive spectral composition of white LED light. Distinctly, besides white light, Sc_opsin1 displayed increased photosensitivity under yellow and green lights, while Sc_opsin5’s photosensitivity was heightened under blue and green lights. These outcomes suggest that the Sc_opsin1’s preference for λmax might be approximately within the range of ∼515 to 596 nm, while Sc_opsin5’s λmax could lie around ∼440 to 535 nm. Furthermore, while red and violet lights induced a slight increase in Ca 2+ levels in cells expressing Sc_opsin1, no response was observed in cells expressing Sc_opsin5. Although it’s widely accepted that nearly all opsins exhibit a significant shoulder in the blue-violet region of the absorption spectra, the elevated absorbance in the blue-violet range may not be solely due to photopigment activity. It could potentially result from varying amounts of an “endogenous absorbing” pigment ( 78 ). Therefore, S. constricta opsins, including opsin5, may also exhibit absorbance in the blue-violet part when examined in the absorption spectra, similar to other photopigments. However, it’s worth noting that the absorbance spectrum of the opsin protein is distinct from its spectral sensitivity during activation. The results in Figure 12 can only suggest the functional responses of Sc_opsins under various light irradiations. Taken together, these findings imply that Sc_opsin1 and 5 may work in tandem to guide the Gαq cascade in S. constricta , enabling it to adapt to the dynamic light environment of its aquatic habitat. In summary, this study presents the first molecular and functional evidence for nonvisual photosensitivity in marine bivalves. The findings strongly underscore the vital roles that nonvisual photosensitivity plays in the growth and development of S. constricta . Despite lacking conventional eyes, S. constricta employs opsins to discriminate light spectra, thereby guiding the Ca 2+ and cAMP signaling pathways. Moreover, the outcomes propose the potential existence of a collaborative photosensitive system mediated by opsins in S. constricta . This system enables rapid responses to transient or subtle shifts in the external light environment. Beyond advancing our understanding of opsin molecular biology and evolution, these results contribute valuable insights into the evolutionary adaptation of marine bivalves to their aquatic photoecology and shed light on their light requirement throughout their life histories.

Phototransduction is based on opsins that drive distinct types of Gα cascades. Although nonvisual photosensitivity has long been known in marine bivalves, the underlying molecular basis and phototransduction mechanism are poorly understood. Here, we introduced the eyeless razor clam Sinonovacula constricta as a model to clarify this issue. First, we showed that S. constricta was highly diverse in opsin family members, with a significant expansion in xenopsins. Second, the expression of putative S. constricta opsins was highly temporal-spatio specific, indicating their potential roles in S. constricta development and its peripheral photosensitivity. Third, by cloning four S. constricta opsins with relatively higher expression ( Sc_opsin1 , 5 , 7 , and 12 ), we found that they exhibited different expression levels in response to different light environments. Moreover, we demonstrated that these opsins (excluding Sc_opsin7) couple with Gαq and Gαi cascades to mediate the light-dependent Ca 2+ (Sc_opsin1 and 5) and cAMP (Sc_opsin12) signaling pathways. The results indicated that Sc_opsin1 and 5 belonged to Gq-opsins, Sc_opsin12 belonged to Gi-opsins, while Sc_opsin7 might act as a photo-isomerase. Furthermore, we found that the phototransduction function of S. constricta Gq-opsins was dependent on the lysine at the seventh transmembrane domain, and greatly influenced by the external light spectra in a complementary way. Thus, a synergistic photosensitive system mediated by opsins might exist in S. constricta to rapidly respond to the transient or subtle changes of the external light environment. Collectively, our findings provide valuable insights into the evolution of opsins in marine bivalves and their potential functions in nonvisual photosensitivity. Keywords Abbreviations fetal bovine serum growth hormone G protein-coupled receptor insulin-like growth factor neuropeptide Y transmembrane Reviewed by members of the JBC Editorial Board. Edited by Kirill Martemyanov

Light is a crucial environmental factor that impacts both terrestrial and aquatic ecosystems on Earth. Consequently, light perception plays a critical role in the development and survival of the entire animal kingdom. For example, visual photosensitivity enables animals to identify mates, predators, and preys, while nonvisual photosensitivity allows them to regulate circadian rhythms, physiological metabolism, and even behaviors ( 1 , 2 ). However, due to the rapid development of modern society, light pollution has emerged as a significant concern. To effectively harness light, it is imperative to comprehend how animal sense and respond to it. Opsins are the primary molecules that regulate light sensitivity and utilization in animals, enabling them to perform various biological functions ( 3 ). Specifically, opsins belong to the G protein-coupled receptors (GPCRs) superfamily and possess seven transmembrane (TM) helixes, characterized by a lysine (K) residue at the seventh helix ( 3 ). Through this K residue, opsins form functional visual pigments (photopigments) when covalently bound to a vitamin A-derived chromophore, such as 11-cis-retinal, via a Schiff base ( 3 , 4 , 5 , 6 ). When photopigments absorb light (photons), the chromophore undergoes isomerization from a cis to an all-trans state, resulting in a conformational change in the opsin. This conformational change allows the opsin to bind to a corresponding specific heterotrimeric G protein, leading to the dissociation of the G protein. Subsequently, the alpha subunit of the G protein (Gα protein) dissociates and interacts with downstream second messenger systems, triggering the depolarization or hyperpolarization of the cell membrane potential ( 7 , 8 , 9 , 10 ). With the increasing availability of animal genomes, research on the classification and evolution of the opsin family has reached deeper levels than ever before. To date, the opsin family can generally be divided into five major lineages: the rhabdomeric (r-) opsins (also known as Gq-opsins, which are Gq-protein-coupled opsins), the ciliary (c-) opsins, the Cnidops, the Group 4 opsins [including the Go-opsin, retinal G protein-coupled receptor opsin (RGR opsin), peropsin, retinochrome, and neuropsin], and the xenopsins ( 4 , 5 , 11 ). However, compared to vertebrates and arthropods ( 12 , 13 ), the evolution and function of opsins in marine bivalves are still poorly understood. Besides, previous studies have primarily focused on species with well-developed eyes, such as cephalopods ( 14 , 15 ), gastropods ( 16 ), and scallops ( 17 , 18 , 19 , 20 , 21 ). In contrast, the photosensitivity and underlying molecular basis of eyeless marine bivalves have been largely overlooked ( 22 ), including their potential phototransduction pathways. The razor clam Sinonovacula constricta (Lamarck 1818) is a typical eyeless marine bivalve species found along the western Pacific coast ( 23 ). It holds significant economic and nutritional value ( 23 ). Despite lacking eyes and adopting a burrowing lifestyle after metamorphosis, S. constricta demonstrates robust photosensitivity throughout its life, as established by our lab and other researchers. Specifically, S. constricta larvae exhibit positive responses to light during their pelagic phases ( 24 ). Optimal light intensity benefits S. constricta by shortening spawning time, increasing spawning capacity, enhancing the survival rate of planktonic larvae, and promoting juvenile growth ( 25 ). Interestingly, yellow light significantly stimulates the growth, digestion ability, and antioxidant capability of juvenile S. constricta ( 26 ). In adult S. constricta , a rhythmic fluctuation of melatonin exists, entrained by photoperiod ( 27 ). Additionally, adult S. constricta possesses a light-entrained circadian clock ( 28 ). Hence, S. constricta has potential as a model organism for studying the nonvisual photosensitivity in marine bivalves. In the present study, we characterized the complete repertoire of the opsin family in S. constricta using its genomic data ( 23 ). Additionally, we investigated the Gα protein family in this bivalve, as it plays a crucial role in coupling with specific opsins to activate their respective phototransduction pathways. To gain insight into opsin differentiation in marine bivalves, we further identified the opsin family in four other typical bivalves from their genomes. Those include three eyeless species ( Mercenaria mercenaria , Modiolus philippinarum , and Crassostrea gigas ), as well as one species featuring numerous non-cephalic eyes ( Mizuhopecten yessoensis ). Subsequently, we analyzed the temporal and spatial expression patterns of S. constricta opsins based on transcriptomic data ( 23 ). We also cloned four representative S. constricta opsins with relatively higher expression and studied their expression patterns in response to different light spectra. Furthermore, we investigated the phototransduction pathways mediated by the cloned S. constricta opsins and determined their spectral sensitivity. These results are valuable for understanding the evolution of opsins in marine bivalves and illuminating the nonvisual photosensitivity and light requirements of these organisms. Ultimately, this research could facilitate the flexible application of light in breeding and farming practices for marine bivalves. Experimental procedures All animal experiments in this study were approved by the Animal Research and Ethics Committees of Ningbo University. Genomic identification of putative S. constricta opsins and Gα proteins In terms of the putative S. constricta opsins, two approaches were employed. First, the homologous genes were obtained by blasting against the S. constricta genome ( 23 ), using the aa sequences of typical opsins from H. sapiens , D. melanogaster , Branchiostoma floridae , M. yessoensis , Argopecten irradians , and Euprymna scolopes ( Table S6 ) as queries. Secondly, all potential opsin sequences were directly retrieved from the S. constricta genome based on functional annotation ( 23 ). Subsequently, sequences obtained through the afore-mentioned methods with aa identities greater than 98% were excluded, retaining the longest sequence for further analysis. Following this step, the candidate opsins underwent additional validation through searching against NCBI BLAST and were submitted to the GPCRHMM webserver ( https://gpcrhmm.sbc.su.se/ ). Ultimately, only those opsins with clear annotations and containing the essential 7 TM helixes characteristic of typical opsins were considered as putative S. constricta opsins. When it comes to the putative S. constricta Gα proteins, similar strategies as mentioned above were employed. Notably, the typical Gα proteins from H. sapiens and D. melanogaster ( Table S6 ) were selected as queries. The detailed sequences of the putative S. constricta opsins and Gα proteins are shown in Table S2 . Furthermore, to elucidate the distribution and divergence of the opsin family in marine bivalves, putative opsins from three other eyeless bivalves M. mercenaria (genome accession number: GCF_014805675.1), C. gigas (GCF_902806645.1), and M. philippinarum ( 79 ), as well as one species featuring numerous non-cephalic eyes of M. yessoensis (GCF_002113885.1), were identified using similar methods as described above, based on their genomes. Detailed sequences of their putative opsins are given in Table S3 . Sequence and phylogenetic analyses of putative S. constricta opsins and Gα proteins To provide essential insights for predicting the functions and evolution of the putative S. constricta opsins and Gα proteins, we conducted multiple sequence alignment and phylogenetic tree construction. For putative S. constricta opsins, the aa sequence alignment was performed using Clustalx 2.1 software. The phylogenetic tree construction was performed using the maximum-likelihood method through SeaView software (PhyML algorithm) ( 80 ), and visualized with Figtree v1.4.3 and Adobe Photoshop CS (version 6.0). The branch lengths of the tree topology were computed by minimizing the sum of squared differences between evolutionary and patristic distances. Notably, for the phylogenetic analysis, well-classified typical opsin sequences from representative species were selected as the intergroup, whereas melatonin sequences from H. sapiens , B. floridae , P. dumerilii , Strongylocentrotus purpuratus , and S. constricta were utilized as the out-group. Additionally, the aa sequences of all genes used for the phylogenetic analysis underwent alignment using Clustalx 2.1 software. Subsequently, the aligned dataset was trimmed to exclude the N- and C-terminal sequences, retaining only the TM helixes and loop regions for further phylogenetic tree construction. As for the Gα proteins, aa sequence alignment was conducted using Clustalx 2.1 software. The phylogenetic tree construction was performed using MEGA 7 software, employing the maximum-likelihood method based on the JTT matrix-based model. The confidence in the resulting branch topology of the phylogenetic tree was measured through bootstrapping, which involved 1000 iterations. Analysis of temporal and spatial expression patterns of putative S. constricta opsins To reveal the potential roles of putative opsins in S. constricta development and to identify potential photosensitive tissues, we analyzed their temporal and spatial expression patterns using our previously published transcriptome data. For the temporal expression analysis, transcriptome data from various developmental stages, encompassing zygotes, trochophore larvae, veliger larvae, umbo larvae, creeping larvae, single pipe larvae, and juvenile clams were available at SRA under accession numbers SRR8325910 to SRR8325916 ( 23 ). In terms of spatial expression analysis, transcriptome data from different tissues, including siphon, gill, intestine, labial palp, mantle, and foot (muscle) were available at GEO with accession numbers GSM7511488 to GSM7511505. To quantify the abundance of putative S. constricta opsin genes, we employed FPKM (Fragments Per Kilobase of transcript per Million mapped reads) values. These values were detailed in Table S4 for temporal expression and Table S5 for spatial expression. The data were then visualized using GraphPad Prism 7 software, allowing for a comprehensive understanding of the expression patterns. Cloning of four representative putative S. constricta opsins with relatively higher expression Based on the expression abundance data derived from the transcriptome analysis ( Figs. 3 and 4 ), we cloned four putative S. constricta opsins with relatively higher expression levels for further functional investigations. These included S. constricta opsin1 , 5 , 7 , and 12 (designed based on their recording order). Additionally, the rationale behind choosing these four specific opsins was guided by insights from the phylogenetic analysis ( Fig. 2 ). Specifically, Sc_opsin1 and 5 belonged to Gq-opsins, a well-recognized category responsible for primary photoreception in invertebrates ( 19 , 45 , 46 ). Sc_opsin12 belonged to xenopsins, known to employ a signaling cascade similarly to c-opsins ( 5 , 11 , 37 , 42 ). While Sc_opsin7 belonged to Group 4 opsins, which are generally associated with photo-isomerase activity ( 16 , 47 , 48 ). It’s worth noting that another xenopsin, opsin13, did indeed exhibit relatively high expression in juvenile S. constricta ( Fig. 3 G ). However, its expression was notably low in the tissues of adult S. constricta , especially in external tissues like the siphon ( Fig. 4 A ) and foot ( Fig. 4 F ), which are considered potential photosensitive tissues. These results strongly suggest a higher likelihood of phototransduction function for opsin12 compared to opsin13. Consequently, we chose to focus on opsin12 rather than opsin13. Furthermore, as Gq-opsins are widely recognized as functional opsins in phototransduction among invertebrates, we have included both of them in this study. First, total RNA was extracted from fresh mixed tissues of adult S. constricta , including foot, siphon, and labial palp, using the Total RNA Kit II (Omega). The quality and concentration of the extracted RNA were evaluated using the NanoDrop One (Thermo). Secondly, a total of 1 μg RNA was reverse transcribed into cDNA using the HiScript III first Strand cDNA Synthesis Kit (Vazyme). Third, the open reading frames (ORFs) of the selected opsins were amplified using the synthesized cDNA as a template. Specific primers were designed using Premier 5 software and are listed in Table S7 . The amplification was run on a PCR instrument (Eppendorf) using the MightyAmp DNA Polymerase Ver.3 (TakaRa). Fourth, the PCR products were separated and size-screened using 1% agarose gel electrophoresis and the bands of expected size were excised, purified, and subsequently cloned into the pMD 18-T vector (TaKaRa). The constructed vectors were transformed into competent Escherichia coli DH5α cells and plated on solid LB medium containing 100 μg/ml ampicillin. Finally, the positive colonies were identified, cultivated, and the plasmids were isolated. The cloned inserts were sequenced by Hangzhou Youkang Biotechnology Co, Ltd to verify their sequences. Analysis of expression response of four cloned putative S. constricta opsins to different light spectra To unravel the photosensitive adaptability of the cloned putative S. constricta opsins , we conducted three independent biological experiments, each in triplicate. The average shell length (mean ± SD) of the juveniles in the three batches was 693.79 ± 10.05 μm, 701.23 ± 8.11 μm, and 705.07 ± 6.34 μm, respectively. These juveniles were obtained from Fujian Dalai Seedling Technology Co, Ltd and were acclimated under various light spectra conditions. Further details about the juvenile culture can be found in our previous publication ( 26 ). Briefly, the juveniles were initially acclimatized for 3 days within aquariums (dimensions: 20 × 20 × 20 cm) in a completely dark environment. These aquariums contained a layer of fresh sea mud (1 cm) and seawater (15 psu, practical salinity units) with a depth of 15 cm. The breeding density of the juveniles was maintained at 2 to 3 individuals per square centimeter. Following this period, the aquariums were exposed to various light spectra treatments for a week each. These treatments encompassed complete darkness, as well as white light (with a peak at 400–800 nm), red light (with a peak at 627 nm), yellow light (with a peak at 591 nm), green light (with a peak at 523 nm), cyan light (with a peak at 501 nm), blue light (with a peak at 463 nm), and violet light (with a peak at 397 nm) ( Fig. S11 ). The LEDs emitting different light spectra were procured from Shenzhen Yamingjie Intelligent Technology Co, Ltd and were positioned on the top of the aquariums at a height of 20 cm above the water surface. The light intensity was consistently set at 10.665 ± 0.089 μmol/m 2 /s, as established from our previous findings ( 25 ). The photoperiod was set as 12 h light (8:00 AM–20:00 PM):12 h dark. Throughout the entire acclimation period, the juveniles were fed twice a day (at 8 AM and 6 PM) with a mixture of microalgae, specifically Isochrysis galbana and Chaetoceros calcitrans (1:1, v/v), at a concentration of approximately 300 to 500 cells/μl. Prior to each feeding, half of the culture seawater was replaced. The experimental was carried out within an air-condition room, sustaining a temperature of 19 °C ± 0.5 deg. C. Continuous aeration was ensured to provide optimal conditions for the specimens. At the end of the experiment, the juvenile clams were subjected to a 1-day fasting period and subsequently collected within their respective light spectra environments. Notably, for the dark treatment, both the feeding and collection procedures were conducted under dim red light. The collected individuals were immediately frozen in liquid nitrogen and then stored at −80 °C for subsequent gene expression analysis. The relative expression of the cloned putative S. constricta opsins were carried out by quantitative real time PCR (qPCR) using the specific primers in Table S7 . In brief, total RNA was extracted from the collected samples following the procedure described earlier. Then, 1 μg RNA was reverse transcribed into cDNA using the PrimeScript RT Master Mix (Perfect Real Time, TaKaRa). The qPCR was conducted on a quantitative thermal cycler (Longgene Q2000A) utilizing the TB Green Premix Ex Taq II (TaKaRa). The procedure of qPCR consisted of an initial denaturation step at 95 °C for 30 s, followed by 40 cycles of denaturation at 95 °C for 5 s and annealing at 60 °C for 30 s. Subsequently, a melting curve analysis was performed, gradually increasing the temperature from 58 to 95 °C at a rate of 1.8 °C per minute. Finally, the relative mRNA expression of the target genes was normalized by the housekeeping gene β-actin using the 2 −ΔΔCT method ( 81 ). Analysis of phototransduction pathways driven by four cloned putative S. constricta opsins To elucidate the phototransduction pathways driven by the four cloned putative S. constricta opsins, we employed a comprehensive approach. This involved the construction of luminescent reporter vectors for both Ca 2+ and cAMP, alongside recombinant expression vectors for the opsins. Subsequently, luminescence signals driven by S. constricta opsins expressed in HEK293T cells were detected using a Varioskan Flash multifunction microplate reader (Thermo). These signals were measured following transient light irradiation. The detailed methods employed were outlined below. Construction of expression vectors A luminescent calcium reporter (Aequorin) was engineered by employing the photoprotein aequorin derived from Aequorea Victoria (NCBI accession number: AEVAQ440X) ( 82 ). The construction procedure adhered to the methodology outlined in a previous publication ( 38 ). For a luminescent cAMP reporter (pGlosensor 22F), procurement was made from Promega (E2301). In the construction of the expression vectors, we initially inserted a six-base linker (GCTGCA) and a 24-base tag protein encoding the 1D4 epitope (ETSQVAPA) into the C-termini of the mammalian expression vector pcDNA3.1 (Invitrogen). Subsequently, the ORFs of the four cloned putative S. constricta opsins (excluding termination codons) were integrated into the pcDNA3.1 vector with 1D4 tag. This integration was achieved using primers that featured Hind III/ Sac II restriction sites ( Table S7 ). It’s important to note that the base sequences of S. constricta opsins were retained without undergoing humanization. Meanwhile, for the purpose of detecting the Gαq, Gαi, and Gαs-coupled phototransduction pathway, the H. sapiens melanopsin (Opn4), H. sapiens rhodopsin (RH1), and Jellyfish opsin (referred to as JellyOp), respectively, were chosen as positive controls ( 37 , 38 ). Their sequences were directly synthesized by Hangzhou Youkang Biotechnology Co, Ltd. Furthermore, to illustrate the critical functional aa in the phototransduction pathway of S. constricta opsins, we specifically targeted the K356 residue in the TM7 domain responsible for retinal binding ( 3 ), and the asparagine (N362) within the NPXXY motif, recognized for maintaining the structural integrity and stability of visual pigment ( 30 ), within Sc_opsin5. Mutations were introduced at those positions, with histidine (H) and K being employed as substitutions, respectively. The corresponding mutant sequences were directly synthesized by Hangzhou Youkang Biotechnology Co, Ltd. When necessary, the recombinant plasmids were transformed into E. coli DH5α cells and sequenced as mentioned above. Ultimately, E. coli DH5α cells containing the recombinant plasmids with accurate sequences were further utilized to isolate the corresponding recombinant plasmids using the Endo-free Plasmid Mini Kit II (Omega). Heterologous expression in HEK293T cells detected by immunocytochemistry To confirm the successful expression of S. constricta opsins, HEK293T cells (National Infrastructure of Cell Line Resource) transfected with the corresponding recombinant pcDNA3.1 plasmids were subjected to immunocytochemistry. In brief, HEK293T cells were initially seeded in six-well cell culture plates (Jet Biofil) containing preloaded tissue-culture treated 24 mm coverslips (Solarbio). Cells were cultured in high glucose dulbecco's modified Eagle's medium (DMEM, Corning) supplemented with 10% fetal bovine serum (FBS, Corning) and 100 IU/ml penicillin-streptomycin (Solarbio), and maintained at 37 °C in a humidified incubator with 5% CO 2 . After reaching 80% confluent 24 h post-seeding, cells were transiently transfected with recombinant plasmids of H. sapiens Opn4 (the positive control), empty vector (no opsin, the negative control), or the corresponding S. constricta opsin at a concentration of 2500 ng/well, using Lipofectamine 3000 (Thermo) according to the manufacturer’s instructions. Each treatment was performed in triplicate. Subsequently, 10 h after transfection, the culture medium was replaced with DMEM supplemented with 10% FBS and 10 μM 9-cis retinal (Sigma), and cells were further incubated for an additional 30 h. Importantly, all subsequent steps were carried in a dark or dim red-light environment as needed. Following incubation, cells were gently rinsed twice with 1×PBS and then fixed with 4% paraformaldehyde for 20 min. After fixation, cells were washed twice with 1×PBS, followed by permeabilization using 1×PBS containing 0.1% TritonX-100 (Beyotime) for 5 min. Next, cells were blocked with 1×PBS containing 5% BSA (Sigma) for 1 h at room temperature, followed by overnight incubation at 4 °C with the monoclonal 1D4 rhodopsin antibody (diluted 1:500 in PBS) (Thermo, MA1-722). Subsequently, cells were gently washed six times with 1×PBS and then incubated with goat anti-mouse Alexa 647 secondary antibody (diluted 1:500 in PBS) (Abcam, ab150115) for 1.5 h at room temperature. After another three washes with 1×PBS, cells were stained with the cell membrane probe 3,3′-dioctadecy loxacarbocyanine perchlorate (DiO, Beyotime) at 37 °C for 10 min. Following three washes with 1×PBS, cells were further incubated with 0.5 μg/ml 2-(4-Amidinophenyl)-6-indolecarbamidine dihydrochloride (DAPI, Beyotime) for 5 min at room temperature. Finally, cells were gently washed twice with 1×PBS, cover-slipped using Fluoromount-G (Beyotime), and then subjected to fluorescence detection. Fluorescence images were captured using a Zeiss laser scanning confocal microscope (LSM880, 294 Carl Zeiss) equipped with a × 63 objective lens. Luminescent second messenger assays The luminescent second messenger assays were conducted following previously described methods ( 37 , 38 ). Initially, HEK293T cells were seeded in 96-well white opaque cell culture plates (Biosharp) with each well containing 200 μl of DMEM and 10% FBS. Upon reaching 80% confluent, the cells were co-transfected with the relevant reporter and pcDNA3.1-1D4-opsin at a concentration of 100 ng/plasmid/well using Lipofectamine 3000. Each treatment was carried out in a minimum of three independent biological experiments, with each experiment including three technical replicates. Subsequently, after 10 h of transfection, the culture medium was substituted with DMEM containing 10% FBS and 10 μM 9-cis retinal (Sigma), and incubated for an additional 24 h. Notably, from this point onward, all procedures were conducted in a dark or a dim red-light environment as needed. The specific procedures for detecting different phototransduction pathways were described below. For the Gαq-mediated Ca 2+ increase signal pathway: The cells were co-transfected with Aequorin and pcDNA3.1-1D4-opsin plasmids. After the 24 h incubation, the culture medium was replaced with CO 2 -independent DMEM (Thermo) containing 10% FBS and 10 μM coelenterazine h (MCE, HY-D1024 for Figure 7 , Figure 8 , Figure 9 , Figure 10 , Figure 11 , Figure 12 ; GlpBio, GC43292 for Figs. S5–S10 ), followed by an additional 2 h incubation. Subsequently, the cells were subjected to the luminescence measurement. After an initial 10 s equilibration period, a white LED (same with the one in Fig. S11 ) was used to flash the cells at approximately 20 μmol/m 2 /s for 5 s. Immediately after the flash, luminescence was recorded for 210 s with a cycle of 2 s. It’s important to note that during the recording well exposed to a flash of light, the other wells within the same plate were shielded from light to prevent exposure to the flash. For the Gαs-mediated cAMP increase signal pathway: The cells were co-transfected with pGlosensor 22F and pcDNA3.1-1D4-opsin plasmids. After the 24 h incubation, the culture medium was replaced with the CO 2 -independent DMEM containing 10% FBS and 2% GloSensor cAMP reagent (Promega, E1290). Subsequently, the cells were incubated for an additional 2 h before luminescence measurement commenced. After a 10 min equilibration period, the cells in the plate were exposed to a 5 s flash of white LED light. Following the flash, luminescence reading was taken every minute for a duration of 40 min. For the Gαi-mediated cAMP decrease signal pathway, the overall procedures mirrored those described for the Gαs-coupled cAMP increase signal pathway. However, there was an exception. Due to the challenge of measuring cAMP decrease from the baseline cAMP luminescence, the cells were treated with 2 μM forskolin (Sigma) to artificially elevate the cAMP levels before light exposure. The luminescence values in the test were subsequently normalized based on the maximum value induced by the forskolin treatment. Moreover, to further confirm the specific Gα protein involved in the signal pathway, the cells were subjected to treatment either with or without 100 ng/ml pertussis toxin (Glpbio, GC17532) during the incubation with the retinal. This pertussis toxin selectively inactivates the Gαi-mediated signal pathway without affecting the Gαs or Gαq pathways. Furthermore, to reveal the sensitivity of S. constricta opsins’ phototransduction to various light spectra, the cells were exposed to different light conditions. This involved flashing the cells with red, yellow, green, blue, and violet lights (consistent with those in Fig. S11 ) at approximately 20 μmol/m 2 /s, in addition to white light. Statistical analysis Statistical analysis was conducted using SPSS 20 software. For the assessment of Sc_opsin expression under different light spectra, we employed one-way ANOVA, followed by Tukey’s test for post hoc analysis. In the case of repeated measure data, like cAMP levels, we utilized repeated measures ANOVA ( 83 ). Statistical significance was considered when p < 0.05. Data availability All relevant data can be found in the main text and supporting information. Supporting information This article contains supporting information . Conflict of interest The authors declare that they have no conflict of interest.

Supporting information Author contributions F. K. conceptualization; F. K. investigation; F. K. writing-original draft; Z. S. R. and J. L. X. supervision; Z. S. R. and J. L. X. resources; Z. S. R. and J. L. X. funding acquisition; Z. S. R., M. Q. Z., and K. L. formal analysis; Z. S. R., M. Q. Z., and K. L. validation; F. K., Z. S. R., M. Q. Z., K. L., D. S. C., X. J. Y., and J. L. X. writing-review & editing. Funding and additional information This research was supported by the 10.13039/501100001809 National Natural Science Foundation of China (32102763), Ningbo Science and Technology Research Projects , China (2019B10006), and the earmarked fund for CARS-49. We are especially grateful to Dr Pingping Zhan for the guidance in fluorescence imaging and to Jiaxing Zhang for the assistance in drawing S. constricta pictures.

CC BY

no

2024-01-16 23:43:45

J Biol Chem. 2023 Dec 1; 300(1):105527

oa_package/75/51/PMC10788561.tar.gz

PMC10788580

38221782

INTRODUCTION Skin photoaging is characterized by roughness, dryness, uneven color, and wrinkles caused by long‐term ultraviolet radiation on the skin. 1 Photoaging is also a potential risk factor for various skin inflammatory, immune, and neoplastic diseases. 2 A convenient, rapid, and accurate diagnostic method is critical to preventing and treating photoaging and related skin diseases. Photoaged skin can show changes in clinical appearance, histopathology, immunohistochemistry, and gene expression. However, there is currently no gold standard for photoaging diagnosis and severity evaluation. Although clinical evaluation methods are relatively convenient, their accuracy depends on practitioner experience, and there is substantial subjectivity; the results between evaluators lack comparability. 3 Pathology and immunohistochemistry analyze the degree of histopathological changes in the skin and the expression levels of related molecules 4 , 5 ; however, because they are time‐consuming, invasive, and lack standardized quantitative standards, they are limited to research and unsuitable for clinical use. Dermoscopy is a non‐invasive diagnostic technique used for detecting photoaging. 6 , 7 The Hu 8 and Isik 9 dermoscopy scores are currently used methods for evaluating photoaging. To explore the accuracy of dermoscopy in photoaging evaluation, we analyzed the correlation between dermoscopy scores and clinical evaluation methods, immunohistochemistry, Masson staining, and age in photoaging evaluation to determine whether dermoscopy can link clinical and histopathological aspects when applied to photoaging and promote dermoscopy for evaluating photoaging in skin.

MATERIALS AND METHODS Donors From January to June 2021, 40 patients underwent surgery in the Department of Dermatology, Burns, Orthopedics, and Plastic Surgery of the Second Affiliated Hospital of Kunming Medical University. Their skin samples were collected from the face, elbow extension, outer calf, armpit, abdomen, groin, or thigh. All donors provided informed written consent. Donors who met any of the following criteria were excluded: visible skin lesions at the sampling site; history of local topical medication at the sampling site within the past 3 months; systematic use of retinoids, anti‐inflammatories, or immunosuppressants within the previous 6 months; history of hormone replacement therapy; history of drug abuse; systemic diseases such as diabetes, smoking, alcohol abuse. The Medical Ethics Committee of the Second Affiliated Hospital of Kunming Medical University approved the study (No.: Shen‐PJ‐2020‐127).

RESULTS Clinical and pathological donor data The 40 donors included 25 males and 15 females. The general information, Fitzpatrick classification, clinical grading of photoaging (Figure 1A–C ), pathology, and immunohistochemistry (Figure 1G–L ) of the donors are displayed in Tables 1 and 2 . For the convenience of statistical analysis, clinical grades I to IV were assigned 1−4 points, and grades 1−5 were assigned 1−5. Donors with a wrinkle rating of 5−7 were 0 in both groups, while donors with a pigment rating of 0 were 0 in both groups and were omitted from Table 1 . Age and histopathology indicators were not normally distributed, and the median and quartile were used for statistical description (Table 2 ). Dermoscopic characteristics of the donors The dermoscopic features evaluated by Hu and Isik scores are displayed in Table 3 (Figure 1D–F ). The positive dermoscopic manifestation is given one point, and the negative is given zero points. Due to the presence of telangiectases in Hu and Isik dermoscopic scores, to evaluate the impact of repeated scoring of it on the results, we included “Hu+Isik‐telangiectases.” The total scores of the four dermoscopes were not normally distributed and were statistically described by the median and quartile. Correlation analysis Spearman rank correlation analysis was performed among age, dermoscopic score, clinical grading score, and histopathological results (Figure 2 ).

DISCUSSION Skin aging can be caused by external factors such as ultraviolet radiation, smoking, and exposure to harmful chemicals. Ultraviolet radiation has the most potent effect on the exogenous factors leading to skin aging, and aging caused by ultraviolet radiation is called photoaging. 16 Compared with endogenous aging, photoaging skin results in relaxation, significant dryness, and peeling. There are also unique manifestations of photoaging, such as skin thickening, excessive keratinization, pigmentation, uneven pigmentation, erythema, and telangiectasia. 17 , 18 Dermoscopy is a non‐invasive image analysis technology that uses polarized or unpolarized light to visualize pigmentation patterns, vascular structures, and other epidermis and dermis morphological features that the naked eye cannot detect. 19 Hu et al. classified the xerosis of photoaging skin observed using dermoscopy as mild, moderate, and severe. 8 Uneven pigmentation was described as small brown globules, reticular pigmentation, or homogeneous pigmentation in a patchy distribution. Vascular telangiectasia was classified as linear and branching vessels. Isik et al. described 12 types of dermoscopic manifestations of photoaging, including diffuse erythema, hyperpigmented macules, yellow discoloration, white line, telangiectases, and super wrinkles, and developed a dermoscopic photoaging scale (DPAS). 9 Compared with Hu's scale, Isik's scale is more diverse. Respati et al. correlated DPAS with sociodemographic characteristics (age, sex, skin type, smoking habits) and sun index scores and found that cheek preference, male, active smoking, Fitzpatrick type IV skin, and increased age had higher DPAS scores. 20 There was no correlation between DPAS scores and the sun index. There were some similarities and overlaps between Hu's and Isik's dermoscopy photoaging evaluation, including linear vessels, branching vessels, and telangiectases; however, there are no studies of the correlation between Hu's and Isik's methods. We found a robust positive correlation between the methods’ total scores ( r ‐values greater than 0.9). The repeated scoring of telangiectases had little effect on the correlation between the total score of Hu's plus Isik's and other items. The items were less correlated except for linear vessels and telangiectases, suggesting that they are independent. There was a moderate correlation between telangiectases and lentigo ( p = 0.63). Although these manifestations originate from different histopathological foundations, their high correlation suggests that they may share a common or related mechanism of occurrence, which merits further research. Age is an essential factor in accelerating skin aging. 21 In the absence of precise criteria for evaluating photoaging, age affects photoaging severity. In our correlation analysis, age had a variable correlation with clinical evaluation and histopathology. There was a weak correlation between Isik's total score, hyperpigmented macules, super wrinkles, and age ( r = 0.37, 0.4, and 0.34, respectively). However, there was no correlation between Hu's total score and terms under Hu's dermoscopy and age. This finding suggests that Isik's score correlates more with age than Hu's score. Glogau's scale and Chung's photographic scales for grading wrinkles and dyspigmentation 12 were applied for clinical evaluation. These scales focus on pigmentation and wrinkles to evaluate photoaging visually. Correlation analysis revealed a strong or moderate correlation among the three scales. The accuracy of these methods is substantially affected by the subjective experience of clinicians and the visibility of skin aging. In dermoscopic scores, wrinkles and pigmentation are the primary features of photoaging. The advantage of dermoscopy is that it visualizes and refines pigmentation and wrinkles, substantially reducing subjectivity's influence. Furthermore, dermoscopy is conducive to earlier detection of slight pigmentation and wrinkles not readily recognizable to the naked eye. We observed high correlations between dermoscopic total scores and clinical scales. Xerosis, superior wrinkles, diffuse erythema, telangiectasis, and reticular pigmentation were significantly correlated with the three clinical scales. Histopathology is a bridge connecting clinical and pathological mechanisms and genes. Masson staining can reveal the distribution of epidermal structure and dermal fibers. The photoaged epidermis shows irregular thickening or thinning; the epidermis is flat, the collagen fibers in the dermis are reduced, and the vascular network is disordered, curved, and dilated. Immunohistochemistry can detect MMP expression, which leads to collagen destruction, reduction of dermal collagen fibers, 17 wrinkle formation, increased reticular fibers, and elastic fiber degeneration. 22 The accuracy of the pathological evaluation is better than the clinical scales; however, it is invasive, takes a long time, and is difficult to use. Khan et al. used collagen density to quantify photoaged skin in mice before and after treatment. 5 Sachs et al. used elastic proliferation to evaluate the degree of skin photoaging. 23 Hughes et al. commented that elastic hyperplasia of skin tissue is the most common evaluation index of photoaging and analyzed the correlation with epidermal thickness, p53 positive cell ratio, Masson staining, and other histopathological tests. 24 The histopathological tests of skin photoaging vary, and there is no quantitative standard. Until now, a correlation analysis between histopathology and age, clinical evaluation, dermoscopy, and other tests has not been reported. In the present study, we found a correlation between Masson staining and MMP‐1 immunohistochemistry detection and age, which partially confirms that pathological indicators and age can reflect the severity of skin photoaging. The Masson staining positively correlated with the Glogau scale and dermoscopic features. The correlations between the four dermoscopic features of hypo/hyperpigmented macules ( r = 0.41), white lines ( r = 0.4), xerosis scale ( r = 0.34), superior wrinkles ( r = 0.31), and Masson were more significant than that of Glogau scale ( r = 0.32), supporting the advantages of dermoscopic evaluation of photoaging. In the correlation analysis of MMP‐1, it was only correlated with two dermoscopic terms: small brown globules ( r = 0.42) and superficial wrinkles ( r = 0.31). MMP‐1 had no significant correlation with clinical scales, suggesting that dermoscopy and histopathology, which are invasive but closer to gene and pathogenesis detection, correlate better than clinical evaluation. Superior wrinkles correlated with Masson, MMP‐1, various clinical scales, and other dermoscopy terms. Further research should determine whether superior wrinkles can increase its weight in the photoaging score of dermoscopy. Our samples were taken from exposed (such as the face, elbow, and outer calf) and non‐exposed areas (such as thighs, abdomen, and armpits). Despite the so‐called non‐exposed parts, there were individual differences and almost no completely non‐exposed samples. Furthermore, the characteristic pathological manifestations of actinic keratoses are such that they might significantly impact the Masson and MMP‐1 tests. Therefore, we excluded skin appearing to contain actinic keratosis as the sampling site; this decision resulted in zero observations of this phenomenon on Isik's score. Because the testing was invasive, there were relatively willing donors. Finally, there is no gold standard for diagnosing skin photoaging, and our data types are diverse, which limits the selection of statistical methods. The testing efficiency of Spearman rank correlation analysis is lower than that of Pearson correlation analysis, which may be one of the reasons for the generally low correlation coefficients. Dermoscopy serves as a bridge between clinical and histopathological tests. It can reveal the microscopic structure from the epidermis to the superficial layer of the dermis invisibly and dynamically. 25 We found that the total Hu and Isik dermoscopy scores were highly correlated, and their correlation with histopathology was higher than that of clinical scales. These findings suggest that dermoscopy can evaluate skin photoaging. However, some dermoscopic terms were not strongly correlated with clinical and histopathological features; therefore, they can be simplified when formulating new dermoscopic photoaging evaluation criteria in the future.

Abstract Background There are no standards for evaluating skin photoaging. Dermoscopy is a non‐invasive detection method that might be useful for evaluating photoaging. Objective To assess the correlation between the dermoscopic evaluation of photoaging and clinical and pathological evaluations. Methods The age, clinical evaluation (Fitzpatrick classification, Glogau Photoaging Classification, and Chung's standardized image ruler), histopathology (Masson staining and MMP‐1 immunohistochemistry), and dermoscopy (Hu's and Isik's) of 40 donor skin samples were analyzed statistically, and Spearman rank correlation analysis was performed. Results There was a robust correlation between the total Hu scores and Isik dermoscopy. The correlation of dermoscopy with histopathology was higher than that of clinical evaluation methods. There is a strong correlation between telangiectases and lentigo. Xerosis, superficial wrinkle, diffuse erythema, telangiectases, and reticular pigmentation were significantly correlated with the three clinical evaluation methods. Superficial wrinkles were correlated with Masson, MMP‐1, various clinical indicators, and other dermoscopic items. Conclusion There is a good correlation between dermoscopy and clinical and histopathological examination. Dermoscopy might help evaluate skin photoaging. Zhao J , Zhang X , Tang Q , et al. The correlation between dermoscopy and clinical and pathological tests in the evaluation of skin photoaging . Skin Res Technol . 2024 ; 30 : e13578 . 10.1111/srt.13578

METHODS Clinical and dermoscopic evaluation of photoaged skin Before surgery, clinical and dermoscopic photographs (DermLite DL4 portable dermoscopy) were taken from the surgical sites, and the Fitzpatrick classifications of the donors were recorded. 10 Clinical evaluation of photoaging was conducted using the Glogau Photoaging Classification 11 and Chung's photographic scales for grading wrinkles and dyspigmentation. 12 The dermoscopic evaluation methods of Hu 8 and Isik 9 were used to evaluate photoaging. Pathological and immunohistochemical evaluation of photoaging skin The entire layer of skin (0.5 cm 2 ) was surgically removed, and the surgical site was more than 0.5 cm from the edge of the lesion. The skin tissue was fixed in 10 mL 4% paraformaldehyde phosphate buffer for 24 h, embedded in paraffin, and sliced, followed by matrix metalloproteinases‐1 13 (MMP‐1, Proteintech, 10371‐2‐AP), immunohistochemistry, and Masson staining 14 (Solarbio, G1340) according to the manufacturer's instructions. The results of MMP‐1 and Masson were analyzed by positive area percentage (positive area/tissue area). 15 Statistical analysis Statistical analysis was performed using SPSS 26.0 and R 4.3.0. For continuous variables with normal distribution, mean ± standard deviation was used. For continuous variables with non‐normal distribution, median and quartile were used. Categorical variables were expressed as a rate (%) or proportion (%). Correlation analysis was performed using Spearman rank correlation analysis, and p < 0.05 defined statistical significance. CONFLICT OF INTEREST STATEMENT The authors have no conflict of interest to declare. ETHICS STATEMENT The patients in this manuscript have given written informed consent to publication of their case details. The Medical Ethics Committee of the Second Affiliated Hospital of Kunming Medical University approved the study (No.: Shen‐PJ‐2020‐127).

ACKNOWLEDGMENTS This study was supported by the National Natural Science Foundation of China (No. 81960568), Ten Thousand Talent Plans for Young Top‐notch Talents of Yunnan Province (No. YNWR‐QNBJ‐2020‐264), Medical Reserve Talents of Yunnan Health Commission (No. H‐2019033) and Yunnan Technology Talent and Platform Plan for Academician and Expert Workstation (No. 202305AF150010). DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request.

CC BY

no

2024-01-16 23:43:47

Skin Res Technol. 2024 Jan 14; 30(1):e13578

oa_package/6b/97/PMC10788580.tar.gz

PMC10788587

37715348

INTRODUCTION Many people with wounds initially seek care from their community‐based healthcare providers (CHPs) who are often not specialised in wound care. 1 , 2 , 3 , 4 Wounds are also initially treated by individuals themselves and their circles of care. 2 , 5 Despite the rapidly growing prevalence and burden of wounds, a relatively small segment of wounds is treated by a qualified wound care provider (QWCP). 3 Types of providers caring for wounds are described in Figure 1 . Variable levels of care can cause individuals' wounds to rapidly become stalled, not following the normal or desired trajectory of healing, and develop into a hard‐to‐heal wound (HTHW). 6 A HTHW is defined as any wound that has not healed by 40%–50% after 4 weeks of good standard of care (SOC). 7 HTHWs translate into an increased financial burden to the healthcare system (staff time, dressings and dressing supply usage and related medications costs) and increased cost to the individual (lost time from work, dressing supply costs and medication costs), as well as a humanistic burden including pain, emotional and physical distress, anxiety, sleep disturbance, reduced mobility, social isolation, and even disabilities and amputation. 8 , 9 , 10 , 11 , 12 , 13 Although delayed healing is common, it is frequently not recognised early enough by the CHP or patient, posing a major problem that increases cost and healthcare utilisation. 14 In addition, CHPs may lack appropriate dressing materials in their practice to provide good SOC wound treatment. Failure to adequately address wounds not progressing towards healing increases the subsequent risk of non‐healing and places the patient at increased risk of wound complications. 15 For example, if oedema is not controlled, a small skin tear on a lower limb of a patient with chronic stasis can quickly become chronic and complex with the potential to be a HTHW. 16 While simple wounds that result from an injury can in most cases be successfully treated by a CHP, patients with a HTHW should be referred early to a QWCP. 7 QWCPs are medical professionals, including nurses, physicians, surgeons, podiatrists and physical therapists, who have received specialised wound care training and certification (differing by care setting and country) and who have access to advanced wound care treatments and technologies not typically available in a primary healthcare facility. Many situations stall the referral process and prolong the time between initial wound presentation and a visit to a QWCP or multidisciplinary wound care team. In all cases, CHPs can play a critical initial role by providing a thorough assessment and good standard wound care to help prevent deterioration and assist in reversing the trajectory towards healing. The aim of this publication is to provide evidence‐based wound care recommendations and suggestions for toolkit items within a wound healing framework that can easily be adopted into a CHP's practice for timely prevention and treatment of HTHWs.

METHODS An advisory panel of QWCP experts met to discuss and develop simplified recommendations for managing HTHWs. The sponsor of this panel, 3M Health Care, invited panel members based on their clinical experience in wound care. Panel members were selected from Europe, North America, Australia and Africa. The advisory panel meeting was held in Atlanta, GA, between 17 and 18 June 2022. The participants consisted of eight nurses, one physiotherapist and three physicians, all with extensive experience and specialisation in wound care. Three members of the panel attended remotely, and the remainder met in person. The meeting was chaired by a moderator (author DB) and recorded for follow‐up. During the meeting, each panellist discussed the relevant literature, presented their individual clinical experiences and made suggestions for improving management of HTHWs. The information presented during the meeting was summarised by a medical writer into an outline that was distributed to panel members for input. Follow‐up communication with the panel members continued via e‐mail and remote online meetings to review and solicit input on each draft. In cases of ambiguity in editing, the moderator determined the final text to be included in the manuscript. The final draft of this manuscript was approved by all panel members.

RESULTS Following is a description of HTHWs along with practical, evidence‐based SOC wound care recommendations developed by panel members for any CHP who provides wound care. Instituting these recommendations into practice could make giant strides towards HTHW prevention and positive treatment outcomes. Healing versus non‐healing (hard‐to‐heal) wounds Acute wounds normally heal within 4–6 weeks with appropriate care. An expected healing trajectory that can be applied by clinicians to all wounds is 40%–50% wound size reduction at 4 weeks. 7 By contrast, HTHWs are wounds that have not shown approximately 40%–50% wound size reduction within 4 weeks of evidence‐based SOC. Multiple intrinsic and exogenous factors can cause dysregulation of the normal stages of healing in all wound types leading to HTHWs (Table 1 ). Most HTHWs are determined as “healable”, meaning they have adequate blood supply and the cause(s) can be treated. However, a small fraction of HTHWs are “non‐healable” as they have an inadequate blood supply and/or a cause that cannot be corrected or treated. Other HTHWs are deemed “maintenance” if there is an adequate blood supply to heal the wound, but the patient cannot or will not follow the plan of care and/or the healthcare system does not have appropriate resources. 17 The focus of this publication is on the prevention and management of HTHWs that are considered “healable”. Recommendations for optimal standard of care in preventing and managing HTHWs Recommendation 1 Predict hard‐to‐heal status early, by identifying and addressing, when possible, person‐related factors known to delay wound healing. In addition to wound characteristics that predict hard‐to‐heal status, early identification of the type of person with a higher risk of having a HTHW is critical in preventing deterioration of the wound. Usually, HTHWs occur on elderly patients and/or patients with comorbidities, including those listed in Figure 2 . Patient and wound complexity increase the likelihood of hard‐to‐heal status. Recommendation 2 Use clinical signs to identify a HTHW as early as possible. Knowledge of the major clinical indicators of failing wound treatment is essential for early intervention. Biofilm, a microbial colony encased in a self‐produced polysaccharide matrix, is known to be present in most HTHWs. 18 , 19 Biofilms increase the risk of infection and are associated with the stalled healing of HTHWs due to the production of destructive enzymes and toxins that promote a chronic inflammatory state within the wound. 20 Clinical signs of biofilm typically mirror clinical signs of HTHWs, which are listed in Table 2 . Early recognition of these subtle clinical signs and prompt referral of patients to receive biofilm‐based wound management are vital for timely wound healing. Recommendation 3 Refer patients to a QWCP as soon as a HTHW is suspected, that is, before or at 4 weeks if not healed or surface area not reduced by 40%–50%. Whenever a HTHW is suspected, the earliest possible referral to a QWCP or multidisciplinary wound care team is recommended if the wound fails to progress. 2 , 15 While the traditional timeline for classifying a HTHW has been 4–12 weeks, the current literature overwhelmingly supports quicker identification and intervention by 4 weeks. 7 , 20 , 21 , 22 A slow or non‐healing trajectory can be predicted before 4 weeks with a basic understanding of normal wound healing progression and factors that lead to impaired healing. 15 , 23 , 24 Recommendation 4 Perform a thorough holistic patient, wound and periwound assessment, including basic bedside vascular screening examinations and tests if applicable. Holistic patient assessment, wound assessment, accurate diagnosis, treating underlying causes, thorough wound bed preparation and ongoing evaluation of the outcomes of treatment interventions are cornerstones of effective SOC wound management. 25 , 26 Holistic patient assessment is a patient‐centred approach that identifies whole patient needs and past medical and surgical history, assesses the anatomy, and records the wound history. 25 The wound assessment should include a detailed description of the wound and accurate measurements. Observations, actions, interactions, interventions and outcomes should be documented in detail, including dates, times and photographs. A structured wound assessment should also include a description of the periwound integrity, which can be an important determinant in decreasing wound size. 27 Assessing blood supply to a wound is recommended in cases where vascular disease, either arterial or venous, is suspected. 28 This includes palpating the dorsalis pedis, posterior tibial and/or peroneal nerve, as well as performing the capillary refill test and a pallor/rubor test (at a minimum) or an audible waveform (if a handheld Doppler is available). If any of these tests cannot be performed, or abnormalities are detected during tests, patients should be referred to a QWCP. Pathologies underlying wounds differ vastly, and the foundation of successful treatment lies in ensuring, when possible, that this is corrected or addressed by use of pressure relief, offloading, revascularisation and/or compression. 29 Arterial supply should be optimised to the extent possible. Recommendation 5 Deliver best practice standard of care when treating any wound. With the growing prevalence of wounds, CHPs play an increasingly important role in wound management. The fundamental principle in wound management across healthcare settings emphasises delivering the utmost care aligned with evidence‐based practices and clinical guidelines. Practitioners should rely on current evidence, staying updated on research, trials and guidelines specific to wound care. Individualising treatment is crucial, considering patients' unique characteristics. Collaboration among various disciplines, including qualified wound care providers, ensures comprehensive management. Thorough assessment, considering dimensions, exudate, infection and patient symptoms, is pivotal. Patient education on wound care, participation and regular follow‐ups for plan adjustments are key, as are ethical considerations and continuous professional development. Following these guiding principles, while adhering to local and regional policies as well as national and international guidelines, helps ensure a high SOC in wound management. Recommendation 6 Follow the “TIMERS” framework for optimal preparation of the HTHW and periwound for healing. “TIMERS” (Tissue debridement, Infection or inflammation control/reduction, Moisture balance, Edge effect to advance epithelialisation and wound closure, Regeneration/repair of tissue to close the wound, and Social factors to be considered) is an established framework that is intended to guide clinicians in optimal assessment and preparation of the wound and periwound for healing. 7 , 17 “Periwound” refers to the area surrounding a wound that may be affected by wound‐related factors and/or underlying pathology. 27 Panel members adapted the TIMERS framework to include SOC recommendations specific to CHPs and QWCPs when performing wound care. The steps for product and dressing selection within this framework are illustrated in Figure 3 . Recommendation 7 Cleanse the HTHW and periwound with a skin‐friendly cleanser. Rigorous cleansing of the wound surface and periwound (including unattached non‐viable tissue) requires the active removal of skin contaminants, debris, fragments of dressings and microorganisms. 20 The wound and periwound should be vigorously cleansed with a skin‐friendly (pH 4–6) cleanser, preferably an antiseptic solution cleanser +/− surfactant with low cytotoxicity. To ensure the area affected by the pathologies and wound‐related factors is adequately cleansed, a volume of 50–100 mL per cm of wound length is recommended. 20 , 27 Recommendation 8 Remove unhealthy tissue from the wound bed. Unhealthy tissue (e.g., eschar, slough and necrotic) should be removed from the wound mechanically with gauze or a debridement pad. 30 If gauze is painful, unhealthy tissue can be removed with debridement pads, wipes or foam. Autolytic debridement with a hydrogel, hydrocolloid, alginate, occlusive or semi‐occlusive dressing could be considered per clinician skills, patient choice and circumstances. If available, use of a medicated/antimicrobial dressing that can impact biofilm reformation post debridement is strongly recommended. After debridement, the wound and periwound skin should be rinsed, ideally with an antiseptic solution. 18 Antiseptic solution is preferable to saline for wound cleansing/hygiene. If sharp debridement is indicated and the required skill level or sharp instruments are not available, the patient should be referred to a QWCP. Indications for sharp debridement are listed in Table 3 . Recommendation 9 Manage infection and inflammation or refer as needed. Localised infection (biofilm) is present in the majority of HTHWs. Early intervention designed to prevent infections or treat them at the first signs is needed to switch at least a segment of these wounds back towards a healing path. All interventions to manage infection/infection risk should follow an approach based on antimicrobial stewardship principles. 20 , 31 Cleanse, soak and manage infection according to the level of the bioburden assessed using the wound infection continuum. 20 An appropriate medicated/active or non‐medicated dressing with antimicrobial properties/mechanisms is recommended. Medicated wound dressings contain antimicrobial agents such as polyhexamethylene biguanide (PHMB) or medical grade honey that kill or inhibit microbial growth. Non‐medicated wound dressings have retention properties or biochemical interactions within the dressing that reduce or kill the microorganisms. Examples of non‐medicated wound dressings include dialkyl carbamoyl chloride (DACC), carboxymethycellulose (CMC), hydroconductive and super‐absorbent polymer dressings. Based on the stage of the infection continuum, for example, spreading or systemic infection, a referral may be needed for systemic antibiotic management, prescribed according to culture sensitivity and administered topically simultaneously with a medicated or non‐medicated dressing with antimicrobial properties. 32 A standard wound culture will not identify the presence of biofilm. However, if a standard culture is taken, the Levine method is recommended, where the swab is firmly pressed down into the wound and rotated over a 1‐cm 2 area to express fluid from the tissue. 20 Inflammation is an indication in wounds that are at risk of infection or are infected. 32 Although inflammation is a necessary step in the wound healing process, a commonality among hard‐to‐heal wounds is prolonged inflammation within the wounded area, even without infection. 33 It is important to use consistent assessment tools for determining infection versus inflammation. 34 Early recognition of the signs and symptoms of inflammation and prompt intervention are essential to enhance wound healing. Protease diagnostic testing and protease modulating dressings are recommended if appropriate. Recommendation 10 Manage moisture in the wound and periwound to create a healthy, moist environment for healing. Excessive exudate production or too little exudate or moisture in a wound can disrupt healing and potentially damage the periwound area. Protecting the periwound from excess moisture is key to avoiding periwound damage. 27 The periwound is particularly susceptible to moisture‐associated skin damage (MASD) when wound drainage volume exceeds the fluid‐handling capacity of the dressing. 35 Skin breakdown, erythema and erosion often occur in skin that has been damaged by wound exudate. 36 Maceration may also occur when moisture is trapped against the skin for a prolonged period, which may appear as a white margin around the wound, causing the skin to soften and wrinkle. 37 A skin barrier/liquid barrier film should be used to protect the periwound from adhesive damage, excess moisture or adhesion of non‐adhesive dressings (Figure 3 ). Strategies to prevent periwound damage should consist of appropriate dressing selection, sizing and correct usage, to optimise healing and limit further damage (Figure 3 ). CHPs should refer to a QWCP if periwound damage is complex, beyond their knowledge and skill, or persists despite good SOC. 27 For uncontrolled periwound damage due to drainage, the patient should be referred for consideration of negative pressure wound therapy. Recommendation 11 Apply appropriate advanced wound dressing according to wound characteristics, for example, moisture level and wound depth. Dressing selection is an essential component of the treatment plan. The literature supports the use of moisture‐retentive dressings, such as hydrocolloids, for dry, shallow wounds. Superabsorbent, foam and alginate dressings are options for highly exudative wounds, and hydrogel dressings can benefit deeper, dry wounds that may contain nonviable tissue (Figures 3 and 4 ). 7 , 38 Learning to apply and remove these dressings correctly in various clinical scenarios is essential in achieving healing. Figure 5 shows a HTHW that is returned to a positive healing trajectory with good SOC wound treatment. Although wet‐to‐dry dressings using gauze were the standard treatment for many wounds for decades, this treatment method is no longer recommended. Numerous studies have shown wet‐to‐dry gauze negatively impacts the healing environment and leads to increased risk of infection, increased dressing change frequency, greater pain at dressing changes and delayed healing. Maintaining a moist healing environment with modern dressings is considerably more effective in promoting an optimal healing environment. 30 Gauze may still play a role in advanced wound care as a secondary dressing for low exudating wounds, or for mechanical debridement of wounds to disrupt biofilm and treat local infection when procedural pain is minimised and managed. Recommendation 12 Arrange for compression therapy as appropriate over wounds of patients with poor venous return, including lower leg venous insufficiency ulcers. Patients with a venous disorder, lower limb oedema, thrombosis, lymphedema or lipedema typically benefit from compression therapy in conjunction with an appropriate absorptive dressing. 39 An ankle brachial pressure index (ABPI) test is highly recommended to determine the need for compression. If it is determined that a HTHW patient could benefit from compression, the patient should immediately be referred. If an ABPI test cannot be performed, the patient should also be referred to a QWCP for further investigation and care. Normal ABPI range is 0.9–1.1, but ABPIs can be falsely elevated due to calcified vessels or diabetes. Patients with ABPI < 0.5 should not receive compression therapy and should be referred to a vascular surgeon for possible revascularisation. Recommendation 13 Manage wound and periwound skin to promote epithelial advancement of the wound edges. Adequate management of exudate, underlying pathology and bioburden are necessary to achieve epithelial advancement from the wound margins. If wound edges are rolled, cliffed or callused, appropriate debridement is recommended. If this is beyond the scope of practice, due to lack of knowledge or clinical skills, or against local policies, and particularly with respect to a periwound callus on the foot, the patient should be referred early to a wound care provider. If tunnelling or undermining is noted, these spaces should be probed to exclude sinus or tracking, and loosely packed with selected dressing material. If this is outside the scope of practice, early referral is recommended. Recommendation 14 Refer the repair and regeneration step of the framework to a QWCP for advanced adjunctive therapies. If the wound has not healed or the wound size has not reduced by 40%–50% by week 4, the patient should be referred to a QWCP for advanced therapies. The aim of the repair and regeneration step is to promote wound closure by providing a matrix to support cell infiltration, stimulating cell activity using advanced adjunctive therapies including biophysical therapies, for example, negative pressure wound therapy, oxygen therapy and tissue‐based products. 40 , 41 Recommendation 15 Be attentive to the patient's over‐arching social situation. Low mobility, the death of relatives and friends, an increasing lack of family cohesion and retirement can lead to feelings of social isolation and loneliness for many people with HTHWs. Pain, odour and discharge can also contribute to low self‐esteem, depression and social stigma. The link between social isolation, poor treatment adherence and low wound healing rates in patients is well documented. 42 , 43 Improved clinical outcomes may be achieved through CHPs who engage and empower the patient, the patient's family and others in the patient's circles of care to help care for the wound. 5 The benefits of patient empowerment have been widely promoted in numerous programmes and publications across healthcare. 44 , 45 , 46 , 47 Getting patients to communicate their ideas, concerns and expectations about their own diagnosis and treatment exemplifies a patient‐centred approach that has been shown to provide insight into the reasons for the visit as well as to help establish the right diagnosis. 48 Active listening by the CHP to identify patients' short‐term goals and biggest impediments to good wound care can help motivate patients and optimise treatment. Patient involvement in established social outreach groups, such as a leg club, that emphasise social interaction, participation, empathy and peer support has also been shown to positively influence wound healing and prevention. 47 Referral for advanced pain and symptom management, and special dressings/solutions to address odour may be necessary to improve patient adherence. 5 , 49 Figure 6 shows a summary of recommendations for CHPs using the TIMERS framework, including optimal products to be included in wound care toolboxes for CHPs providing SOC and for QWCPs providing advanced wound care.

DISCUSSION Increases in age‐ and lifestyle‐associated conditions including diabetes, obesity and vascular disease as well as healthcare system resource limitations have contributed to a global rise in the prevalence of hard‐to‐heal wounds. Curbing the humanistic and financial burden of HTHWs increasingly involves CHPs who are often the initial contact for people with wounds. However, most literature regarding HTHWs published during the past decade is intricate and aimed at people who specialise in wound care. With current trends of nursing shortages, lack of continuity of care and fast turnover of the workforce, there is an urgent need to provide clear recommendations for CHPs who encounter wounds. The recommendations and flow charts in this document are an attempt to whittle down to the most up‐to‐date basics of SOC wound care, which if followed could considerably impact people suffering with wounds, as well as healthcare resource utilisation worldwide. HTHWs are defined as any wound that has not healed by 40%–50% after 4 weeks of evidence‐based SOC. They occur in patients with multiple comorbidities and typically display increases in devitalised tissue, infection, exudate, maceration, wound malodour or pain, or no change in wound size. These recommendations underscore the use of person‐ and wound‐related signs to identify a HTHW and to signal the earliest possible referral to a QWCP or multidisciplinary wound care team whenever a HTHW is suspected. When the referral process is stalled and during the period between initial wound presentation and a visit to a QWCP, these recommendations are meant to help guide CHPs in playing a critical initial role by undertaking a thorough assessment, addressing local infection and inflammation and providing an optimal wound healing environment for timely prevention and treatment of HTHWs. Treatment recommendations for SOC include cleansing the wound and periwound with a non‐cytotoxic antiseptic or pH‐balanced surfactant solution post regional skin hygiene, followed by prompt mechanical wound debridement as appropriate. For draining wounds, the periwound should be protected with a barrier product. When increased risk of an HTHW is identified, healing is delayed or infection is suspected, a topical antimicrobial/antiseptic agent should be used. For highly draining wounds, a superabsorbent/gelling fibre dressing is recommended. Alginate or foam dressings are recommended for wounds with medium drainage, and hydrocolloid, sheet hydrogel or thin foam dressings for minimal drainage (Figure 3 ). CHPs may lack appropriate products in their practice to provide good SOC wound treatment, and these recommendations suggest modest additions of basic wound care products to assemble a toolkit. According to these recommendations, a basic toolkit for wound care should include antiseptic/surfactant wound/skin cleansers, debridement products, a barrier product to protect the periwound, a selection of absorptive dressings appropriate to the level of exudate observed to ensure a moist wound environment (Figure 4 ), and a secondary cover dressing if needed. Armed with a toolkit and basic knowledge of SOC practices in wound care, CHPs may play an integral role in providing optimal outcomes for people with wounds. In translating these actionable evidence‐based recommendations into practice for CHPs, several key implementation strategies should be considered. First, it is essential to facilitate easy access to the document through digital platforms and training sessions to ensure widespread dissemination among CHPs. Second, fostering a culture of continuous learning and professional development through workshops and case discussions can aid in understanding nuances of the recommendations. Third, incorporating the recommendations into electronic health record systems can serve as a digital prompt during patient encounters, helping to ensure adherence to the guidelines. Fourth, regular audits and feedback mechanisms can help monitor the application of recommendations and identify any barriers or challenges faced by CHPs. Lastly, fostering collaboration among CHPs and qualified wound care providers through multidisciplinary meetings can provide a platform for knowledge exchange, addressing queries and sharing best practices. By adopting these implementation strategies, CHPs may be empowered to identify and treat HTHWs in a manner that aligns with evidence‐based guidelines, ultimately improving patient outcomes and healthcare quality. While these recommendations are based on best available evidence and the consensus of panel members, they do not exclude other approaches as being within a standard of practice. Adherence to any given method of wound management should be determined after taking numerous factors into account, including conditions at the relevant practice (staff levels, experience, product availability, etc.) and characteristics of the individual patient.

Abstract It is common for community‐based healthcare providers (CHPs)—many of whom have not received specialised training in wound care—to deliver initial and ongoing management for various wound types and diverse populations. Wounds in any setting can rapidly transition to a stalled, hard‐to‐heal wound (HTHW) that is not following a normal healing trajectory. Failure to recognise or address issues that cause delayed healing can lead to increased costs, healthcare utilisation and suffering. To encourage early intervention by CHPs, a panel of wound care experts developed actionable evidence‐based recommendations for CHPs delineating characteristics and appropriate care in identifying and treating HTHWs. A HTHW is a wound that fails to progress towards healing with standard therapy in an orderly and timely manner and should be referred to a qualified wound care provider (QWCP) for advanced assessment and diagnosis if not healed or reduced in size by 40%–50% within 4 weeks. HTHWs occur in patients with multiple comorbidities, and display increases in exudate, infection, devitalised tissue, maceration or pain, or no change in wound size. CHPs can play an important initial role by seeing the individual's HTHW risk, addressing local infection and providing an optimal wound environment. An easy‐to‐follow one‐page table was developed for the CHP to systematically identify, evaluate and treat HTHWs, incorporating a basic toolkit with items easily obtainable in common office/clinic practice settings. A flow chart using visual HTHW clinical cues is also presented to address CHPs with different learning styles. These tools encourage delivery of appropriate early interventions that can improve overall healthcare efficiency and cost. Beeckman D , Cooper M , Greenstein E , et al. The role community‐based healthcare providers play in managing hard‐to‐heal wounds . Int Wound J . 2024 ; 21 ( 1 ): e14402 . doi: 10.1111/iwj.14402

CONFLICT OF INTEREST STATEMENT Dimitri Beeckman, Emily Greenstein, Patricia Idensohn, Robert Klein, Norbert Kolbig, Kimberly LeBlanc, Catherine Milne, Terry Treadwell, Dot Weir and Wendy White are all paid consultants for 3M. Matthew Cooper is an employee of 3M.

ACKNOWLEDGEMENTS The authors thank Karen Beach (3M) for assistance with manuscript preparation. DATA AVAILABILITY STATEMENT Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

CC BY

no

2024-01-16 23:43:47

Int Wound J. 2023 Sep 15; 21(1):e14402

oa_package/ba/1b/PMC10788587.tar.gz

PMC10788588

38226397

INTRODUCTION In endoscopy training, trainees typically learn through didactic lectures and apprenticeships. However, this method of procedural training is often unstandardized; it results in variable technical skills depending on the expertise of the supervising physician. 1 Opportunities for training are also highly dependent on the caseload of individual institutions and the availability of training physicians. Simulation‐based learning provides trainees with the opportunity to train procedural skills safely and effectively even before they begin performing endoscopy in patient settings. The few existing simulation‐based training programs usually focus exclusively on technical skills and rarely incorporate supporting educational curricula that emphasize competency and improvement in clinical practice. 2 , 3 Simulation‐based training coupled with mastery learning, a form of competency‐based education in which learners are required to meet or exceed a predetermined level of skill before completion of training, 4 has been shown to improve clinical skills and reduce the risk of procedure‐associated injury for a variety of procedural skills. Although simulation‐based mastery learning (SBML) has been used in various surgical specialties, it is rarely used in endoscopy. 5 , 6 , 7 Our research group has pioneered the use of SBML to facilitate the safe and efficient acquisition of basic and advanced procedural skills among endoscopy practitioners and trainees. 8 , 9 , 10 Our experience with a structured esophagogastroduodenoscopy (EGD) SBML course for novice gastrointestinal (GI) fellows demonstrates the efficacy of an SBML course in helping trainees rapidly acquire upper endoscopy skills compared to traditional apprentice‐based training. 11 During the coronavirus disease 2019 (COVID‐19) pandemic, many institutions temporarily halted routine endoscopic procedures to ensure patient and provider safety and to redeploy practitioners to other areas of immediate clinical need. These disruptions reduced caseload volume in endoscopy and inadvertently created a vacuum in educational and training activities for the trainees. Marasco et al reported that the lack of appropriate training for young trainees during the pandemic will not only widen the gap of deprived countries, but will also have a negative impact on them psychologically, resulting in burnout. 12 , 13 To adapt to the restrictions of the COVID‐19 pandemic, we delivered our training program using virtual training mechanisms. Virtual training can be used beyond the pandemic to supplement face‐to‐face training when travel opportunities and resources are not available. There are no published studies showing the outcomes of virtual training for simulation‐based mastery learning in endoscopy. Herein, we share our observations from conducting an SBML EGD training course for novice fellows that was delivered using virtual coaching.

METHODS Participants We conducted an upper endoscopy training program for novice trainees (1st year GI fellows). The trainees were recruited from seven academic medical centers in San Francisco, US; Singapore, Singapore; Manila, Philippines; Jakarta, Indonesia; and Bangkok, Thailand (Figure 1 ). The course was conducted over a 1 week period (July 2020). The trainees were relieved of their clinical duties for the duration of the training program. We collected demographic information including age, gender, training track, dominant hand, and previous EGD and colonoscopy experience. Historical control We compared our data to data obtained from our previous experience with a historical cohort ( n = 6) that underwent the SBML curriculum through in‐person training at two sites in the United States and Singapore. The entire curriculum was delivered by in‐person coaches and with no virtual interventions. The core curriculum, which focused on standard EGD, was administered over the course of 1 week, similar to the course time frame for the virtual cohort (July 2019). The in‐person historical cohort was given the opportunity for an additional week of training that covered more advanced endoscopic techniques. Herein, we compare the results for only the EGD curriculum. Course curriculum We used the mastery learning framework to design our curriculum (Figure 2 ) which was described extensively in Nguyen‐Vu et al. 9 Two expert‐level endoscopists determined the necessary elements to perform high‐quality upper endoscopy: appropriate diagnosis of common cancers and diseases, adequate endoscope tip control (fine motor movements), thorough mucosal examination of the upper GI tract, high‐quality photodocumentation, biopsy and clipping (Figure 3 ). All students were given access to an online learning management system (Canvas, Salt Lake City, UT). Trainees completed the online modules concurrently with their simulation‐based training. For the written self‐assessments, they were required to achieve a score above 80% before attending the technical session. To train endoscope tip control, we utilized a previously validated simulator that was designed to facilitate rapid acquisition of fine endoscopic motor movements. 14 The trainee was required to target the stickers “A‐Z” using proper endoscope handling technique with only one hand controlling the endoscope. We collected the amount of time taken for each attempt to complete the simulator activity (completion time) and the number of attempts to reach competency (120 s) and mastery (100 s). We aimed to teach the trainees how to perform a standardized EGD (a systematic process of performing a high‐quality mucosal examination of the upper GI tract). We emphasized that EGD should be performed deliberately and that every section of the upper GI tract must be examined completely. We used an upper GI simulator model and evaluated their skills using a previously validated assessment tool. 15 Photodocumentation refers to the photographic screenshots taken from the endoscopy processor. We believe that high‐quality photodocumentation includes photos taken from distances close up, medium, and long‐view to achieve a robust understanding of the lesion (morphology, surface pattern, histology, etc.) and its location. The trainees were introduced to the techniques of biopsy and clipping using the upper endoscopy simulator model. They were taught how to utilize one hand to control the endoscope and the other hand to control the tool. The trainees were instructed to biopsy or clip various regions of the stomach (i.e. antrum and fundus). Virtual coaching mechanism We conducted daily virtual group lectures (Zoom, San Jose, CA, USA) to introduce the technique (1‐2 h). Then, we conducted small group sessions with approximately two trainees per group to provide more individual guidance and feedback (1–3 h). Both the trainees and instructors were able to view each other's endoscopy monitor as well as monitor their hands on the endoscope (Figure 4 ). We also used a merged reality software (Help Lightning, Birmingham, AL, USA) to provide real‐time synchronous feedback. This allowed for a more interactive experience, as the trainer was able to transpose an image onto the trainee's visual field, simulating a hands‐on training session. The small group sessions were moderated by virtual coaches (n = 3) who were all experienced practicing endoscopists (Roy Soetikno, YungKa Chin, and Mark De Lusong). At least one virtual coach was available on standby for any questions and additional guidance requested by the trainees. Minimum passing standards The fellows were taught the techniques in order of increasing difficulty (Figure 2 ). The trainees were provided with iterative assessment and feedback throughout the training period. They were required to meet the set minimum passing standard (MPS) for each technique prior to moving on to the next topic. The MPS to meet competency for endoscope handling, which was based on expert endoscopists’ performance, was to complete one full trial run on the simulator in under 120 s. 14 After reaching competency, they continued to practice endoscope handling as a warm‐up for the following modules and aimed to reach mastery level (under 100 s). To meet competency for the EGD examination, trainees were required to score at least a “4” (Scale: 1‐Very Poor to 6‐Excellent) using a previously validated assessment tool by Neumann et al. 15 We chose to use this tool as it was previously validated to assess simulation‐based EGD skills as opposed to clinical EGD skills. On the final day of the program, the trainees then completed a final written assessment on Canvas. Four endoscopy educators collaborated to create the assessment which consisted of 20 multiple‐choice questions derived from their assigned articles and lectures. The questions assessed indication, 3 management, 5 anatomy, 5 and diagnosis. 7 The assessment has been previously evaluated to determine a significant difference between first‐year trainees and second‐ and third‐year trainees. 11 Then, the trainees were assessed on their technical EGD skills on Zoom. 15 The graders were experienced endoscopists who were not involved in their training. We assessed interrater reliability by having them rate 10 random EGD videos. We considered a kappa score >0.60 to be adequate. Feedback survey After the trainees completed the final written and technical skills assessment, we delivered a feedback survey to the trainees and faculty regarding the strengths and weaknesses of the virtual coaching program. The survey consisted of 24 items that were open‐ended or rated on a 10‐point Likert scale. Clinical performance evaluation One month after the course, we began evaluating the trainees’ performance in clinical EGD using the ASGE's Assessment of Competency in Endoscopy (ACE) Tool. 16 The trainees were asked to collect the ACE tool for every EGD they performed or assisted in. The supervising endoscopist completed the ACE tool immediately after the trainee's procedure. We compared the scores to those from the historical cohort.

RESULTS We enrolled 21 novice trainees in our training program (Table 1 ). Most trainees had no prior experience performing EGD or colonoscopy in patients. All trainees ( n = 21, 100%) completed the training program and met the MPS for endoscope handling, standard EGD examination, photo‐documentation, and biopsy. For endoscope handling analysis, we excluded four trainees in the virtual coaching cohort who had experience with the tip control simulator prior to the training program. The trainees reached the MPS for competency after 31.4 ± 29.1 attempts and mastery after 51.9 ± 36.7 attempts, similar to the historical cohort that had undergone the training with direct coaching (Table 2 ). For the overall knowledge‐based assessment, the mean score for the virtual coaching group was 81.9%±8.9%, similar to those trained through direct coaching only (78.3 ± 8.2%, p = 0.385). For standard EGD, the mean score for the general assessment of the UGI tract was 4.6 + 0.6, which was similar to the scores of the historical cohort (4.7 + 0.5, p = 0.55; Table 2 ). The interrater reliability was adequate with a kappa score of 0.82. The average score (out of 6.0) for the overall mark was highest for the esophagus (5.1 ± 0.7), and lowest for the duodenum (4.5 ± 0.8). Feedback (trainees) The average overall satisfaction rating for the course, including the online learning management system, virtual coaches, and simulation‐based practice sessions, was 9.3 ± 1.2 (out of 10) with 90% of the trainees indicating interest in attending similarly structured courses for other endoscopic techniques. The trainees reported high satisfaction with the realism of the virtual coaching set‐up (9.2 ± 0.95 out of 10), the helpfulness of their virtual coaches (9.49 ± 0.79), and the scheduling availability of their virtual coaches (9.22 ± 0.92). Twelve (57%) of the trainees indicated that the length of the course was appropriate, while 29% ( n = 6) felt that it was too short and 14% felt it was too long. Feedback (faculty) The local trainers and program directors rated the program highly. They were satisfied with the effectiveness of the overall training program (9.2 ± 0.4 out of 10.0) and found that the program was feasible for their site (9.0 ± 0.9). They felt that the bowl simulator was helpful in training endoscope handling (9.4 ± 0.5) and preparing novice fellows for EGD (9.1 ± 1.0). 89% of the respondents ( n = 8) strongly agreed that they would like their site to participate in this program in the future. They rated the realism of virtual coaching in simulating direct coaching as 8.8±0.8 and their satisfaction with the effectiveness of the virtual instructor as 9.1 ± 0.8. 22% of faculty ( n = 2) strongly agreed that the virtual coaching mechanism was easy to set up while 67% ( n = 6) agreed and 11% ( n = 1) were neutral. After setting up, all trainers at least agreed that the mechanism was easy to use. A majority (89%, n = 8) at least agreed that virtual coaching can be used for training practicing endoscopists and would participate in a training program with virtual coaching to learn techniques like endoscopic mucosal resection or endoscopic suturing. Clinical performance evaluation We collected 33 clinical EGD evaluations from six fellows (29%) in the virtual coaching group and 94 evaluations from six fellows (100%) from the direct coaching group. Collecting clinical evaluations from the supervising physicians was not feasible for most of our fellows due to the limited resources and procedures during the COVID‐19 pandemic. For the first 30 clinical EGDs, the trainees in the virtual coaching group received similar scores as the direct coaching group (2.3 ± 0.8 vs. 2.2 ± 0.7; p = 0.25; Table 2 ).

DISCUSSION In the 1980s, a renowned educational psychologist, Benjamin Bloom, described a breakthrough learning method that combined mastery learning and intensive one‐on‐one mentoring. 17 The students performed 98% better (on average) than those who learned using the traditional method. This increase in learning is massive; no other learning method could produce as much. The application of Bloom's learning method could have a significant impact on endoscopy. If it can be scaled in endoscopy, it can facilitate the dissemination of endoscopy knowledge and skills more effectively and efficiently, and could potentially close the disparity in the availability and quality of endoscopy. While mastery learning with one‐on‐one mentoring produces the most significant results, Bloom is concerned with the feasibility of such a system as one‐one‐one mentoring is logistically difficult for the trainer with additional responsibilities. Herein, we describe a proof of concept that we can use evidence‐based education principles with modern communication software to train upper endoscopy more efficiently and effectively. In a prior study, we have shown that the direct coaching SBML program has resulted in significant improvement in trainee EGD skills compared to trainees who were taught with the traditional apprentice‐based training system. 11 In this current study, virtual coaching appears to be as feasible and effective as direct coaching for the SBML program for novice gastroenterology trainees. The method of delivery for the training program (virtual coaching vs direct coaching) resulted in no significant difference in their cognitive assessments, simulation‐based EGD assessments, or the first 30 EGDs performed in clinical practice compared to trainees who underwent the program in person. To better illustrate the value of the virtual coaching training program, future studies will assess the difference in outcomes between trainees in the program compared to trainees who undergo traditional apprentice‐based training at the patient bedside. A particular strength of the multicenter study, wherein the training programs were delivered across different centers in North America and Southeast Asia, is that we were able to demonstrate the feasibility and effectiveness of SBML with virtual coaching in endoscopy training despite differences in clinical and social settings. Our program allowed us to continue intensive endoscopy training during the COVID‐19 pandemic when routine procedures that trainees typically learn from were vastly canceled. Beyond the COVID‐19 pandemic, virtual coaching has the potential to bridge the training and quality gap worldwide, especially for those in rural and underserved areas. It may be worthwhile for certain trainees and trainers to consider this type of training when the opportunity to meet in person (due to financial, travel, or time restraints) is limited. A limitation of our study is that we received limited clinical EGD evaluations from the virtual coaching group. The COVID‐19 pandemic heavily impacted and reduced clinical volume, thus limiting the trainees’ opportunities to perform EGDs in the clinic. Consequently, clinical follow‐up through ACE forms represented only a fifth of our virtual coaching cohort. In addition, our study included a small sample size for the control cohort. Due to the COVID‐19 pandemic restricting unnecessary gatherings, we could not continue recruitment for in‐person training. As such, we acknowledge the limited sample size when interpreting the assessment of statistical significance in this study. Our findings suggest that virtual coaching may be a feasible and effective method for novice first‐year gastroenterology fellows to learn cognitive and technical EGD skills. Presently, there are limited resources available to comprehensively educate on endoscopy procedures. 18 Standalone recorded procedure videos are available online for viewing, but this at best can only help with the cognitive portion of endoscopy training. The availability of SBML with VC would be able to bridge the gap for technical skills training. 19 Virtual coaching can be applied broadly in endoscopy training. Even after the pandemic era, it can improve access to endoscopy training with experts and has the potential to provide high‐quality training to trainees from almost any location. In order for the SBML with VC training program to be more widespread and adaptable, industry partners and local institutions play crucial roles in ensuring the availability of simulation models and other infrastructures. Future randomized studies, with consistent clinical evaluations, to compare traditional apprentice‐based training with our SBML program with virtual coaching or direct coaching are needed to better understand the effectiveness of this method of training in endoscopy.

Abstract Introduction Our simulation‐based mastery learning (SBML) curriculum, delivered in person, has been shown to successfully train novices in structured esophagogastroduodenoscopy (EGD). SBML with virtual coaching (VC) has the potential to improve the effectiveness and efficiency of endoscopy training and expand access to trainees from around the world. We share our observations conducting an EGD training course using SBML with VC. Methods We conducted a 1‐week virtual SBML course for novice trainees across seven academic centers in the USA and Asia. The cognitive component was delivered using an online learning platform. For technical skills, a virtual coach supervised hands‐on training and local coaches provided assistance when needed. At the end of training, an independent rater assessed simulation‐based performance using a validated assessment tool. We assessed the clinical performance of 30 EGDs using the ASGE Assessment of Competency in Endoscopy tool. We compared the trainees’ scores to our cohort trained using in‐person SBML training using non‐inferiority t‐tests. Results We enrolled 21 novice trainees (mean age: 30.8 ± 3.6 years; female: 52%). For tip deflection, the trainees reached the minimum passing standard after 31 ± 29 runs and mastery after 52 ± 37 runs. For structured EGD, the average score for the overall exam was 4.6 ± 0.6, similar to the in‐person cohort (4.7 ± 0.5, p = 0.49). The knowledge‐based assessment was also comparable (virtual coaching: 81.9 ± 0.1; direct coaching: 78.3 ± 0.1; p = 0.385). Over time, our novice trainees reached clinical competence at a similar rate to our historical in‐person control. Conclusions VC appears feasible and effective for training novice gastroenterology trainees. VC allowed us to scale our SBML course, expand access to experts, and administer SBML simultaneously across different sites at the highest standards.

CONFLICT OF INTEREST STATEMENT Tonya R. Kaltenbach: Consultant for Verily Life Sciences and Research Support from Olympus. Roy M. Soetikno: Consultant for Olympus and Fujifilm. Amandeep Shergill: Consultant for Boston Scientific. The remaining authors declare no conflict of interest.

CC BY

no

2024-01-16 23:43:47

DEN Open. 2024 Jan 14; 4(1):e317

oa_package/3c/78/PMC10788588.tar.gz

PMC10788594

37933591

INTRODUCTION Cassava ( Manihot esculenta ) is an important tropical crop with annual production of about 315 million tonnes in over 30 million hectares. Africa accounts for 65% of the total global cassava production, with Nigeria being one of the major producers, contributing up to 20% the global total (FAOSTAT, 2022 ). Other major cassava growers are Angola, Brazil, China, the Democratic Republic of the Congo, Ghana, Indonesia, Mozambique, Vietnam and Thailand (Figures 1 and 2 ) (FAOSTAT, 2022 ). Cassava is rich in carbohydrates and can be grown in poor soil conditions, making it a valuable source of food and income for more than 800 million people in rural areas (Nassar & Ortiz, 2010 ). It is a major source of staple food for human consumption after rice, maize, wheat and potato, and is also used as animal feeds and for production of commercial starch and biodegradable plastics. Cassava is a flowering hardy perennial shrub native to South American countries, domesticated about 8000 years ago and brought by Portuguese traders to west African countries during the sixteenth century. It is related to the Euphorbiaceae family and genus Manihot , which comprises about 98 species extending from shrubs to tree‐like relatives, including Manihot glaziovii for rubber production (Léotard et al., 2009 ; Nassar, 2008 ; Olsen & Schaal, 2007 ). It is a heterozygous crop species with 2n = 36 chromosomes and mostly polyploid in nature, cultivated as an annual crop in tropical and subtropical countries for its edible tuberous roots (El‐Sharkawy, 1993 ). Cassava is a hardy crop that can be grown in a variety of conditions, making it an important crop for smallholder farmers who often have limited access to resources such as irrigation, fertilizers and pesticides. It is one of the most drought‐tolerant crops, growing on marginal nutrition‐depleted soils of acidic nature, with low production cost and the ability to survive in any environments. Cassava is extensively cultivated within latitudes 30° north and south of the equator, at 1500–2000 m a.s.l., in a temperature range of 25–29°C, with rainfall from 1000 to 1500 mm annually in the poor marginal soils (Onwueme & Sinha, 1991 ). Cassava is not severely affected by drought, but the changing climate can have a tremendous impact on cassava production due to the evolution of pathogens and pests, as well as extreme temperatures. Cassava production is already greatly hindered by diseases such as cassava mosaic disease (CMD) and cassava brown streak disease (CBSD), the two major viral diseases of cassava (Figure 2 ). The crop is vegetatively propagated through stem cuttings ranging from 5000 to 20,000 cuttings per hectare, depending on the cropping system and purpose (Keating et al., 1988 ). However, this practice can also be a major source of spreading viral diseases such as CMD and CBSD. These viral diseases can cause significant yield losses, affecting food security and the livelihoods of smallholder farmers. To address this challenge, there is a need to develop disease‐resistant cassava varieties that can withstand the changing climate and resist viral diseases. In recent years, advances in molecular genetics and genomics have provided new tools and techniques for the development of improved cassava varieties. For instance, researchers have used RNA interference (RNAi) technology to control viral diseases. In addition, modern breeding approaches such as marker‐assisted selection and genome editing can accelerate the development of disease‐resistant cassava varieties. These techniques can help to identify and select desirable traits such as disease resistance, and rapidly develop improved varieties with higher yields and better nutritional content. With the increasing human population, which is projected to reach 9.8 billion in 2050 and 11.2 billion by 2100, there is a pressing need to increase food production to feed the population. Because cassava is one of the main staple food crops for Africa and some tropical countries, there is a need to develop strategies that will increase cassava production under extreme climate. Recent progress and prospective on the application of molecular genetics and genomics for developing new varieties of cassava that are resistant to diseases and pests, and improve yield, quality and nutritional value have been promising. This article presents an overview of recent progress and prospective on the application of molecular genetics and genomics for developing cassava varieties resistant to diseases and pests.

CONCLUSIONS Cassava, which is a major food security crop for millions of people in Africa and other tropical regions, faces a challenge posed by viral diseases, which have remained the primary cause of the crop's low productivity. Observed breakdown in resistance for some traits, such as CMD resistance, requires a regular re‐evaluation of existing traits to ensure they are coping with the continued pressures. Innovative strategies such as gene pyramiding and diversification of resistance sources can provide effective options for enhancing cassava resilience to diseases. For instance, using genomic tools such as SSR, SNP genotyping by sequencing and modern biotechnologies such as genome editing and genetic engineering enable the prospect of modifying the existing genes in susceptible cassava varieties and conferring disease resistance, thereby revolutionizing cassava improvement efforts. A thorough understanding of the mode of action and potential target genes is necessary for the integration of biotechnology technologies such as traditional genetic engineering and genome editing. While significant progress has been made in identifying target genes and QTLs, more studies are required to fully elucidate the mode of action of these genes and their potential as targets for genome editing. Based primarily on data from other crops, several possible targets for genome editing in cassava have been described here. It is now necessary to identify the cassava homologues of these targets. Overall, the best method for combating cassava diseases and pests may be a holistic approach that combines traditional breeding methods and biotechnology innovations for cassava improvement to sustainably enhance cassava productivity and ensure food security for millions of people in the tropics.

Abstract Cassava ( Manihot esculenta ) is one of the most important sources of dietary calories in the tropics, playing a central role in food and economic security for smallholder farmers. Cassava production is highly constrained by several pests and diseases, mostly cassava mosaic disease (CMD) and cassava brown streak disease (CBSD). These diseases cause significant yield losses, affecting food security and the livelihoods of smallholder farmers. Developing resistant varieties is a good way of increasing cassava productivity. Although some levels of resistance have been developed for some of these diseases, there is observed breakdown in resistance for some diseases, such as CMD. A frequent re‐evaluation of existing disease resistance traits is required to make sure they are still able to withstand the pressure associated with pest and pathogen evolution. Modern breeding approaches such as genomic‐assisted selection in addition to biotechnology techniques like classical genetic engineering or genome editing can accelerate the development of pest‐ and disease‐resistant cassava varieties. This article summarizes current developments and discusses the potential of using molecular genetics and genomics to produce cassava varieties resistant to diseases and pests. Combating cassava diseases and pests requires a holistic approach that combines traditional breeding methods, genomics and biotechnology innovations such as conventional genetic engineering and genome editing. Ntui , V.O. , Tripathi , J.N. , Kariuki , S.M. & Tripathi , L. ( 2024 ) Cassava molecular genetics and genomics for enhanced resistance to diseases and pests . Molecular Plant Pathology , 25 , e13402 . Available from: 10.1111/mpp.13402

CASSAVA DISEASES AND PESTS Cassava production is mainly constrained by two viral diseases, CMD and CBSD (Figure 2 ). These viruses are transmitted by insect vectors, mainly whitefly ( Bemisia tabaci ), and stem cuttings as planting materials (Legg et al., 2002 ). CMD is caused by viruses of the family Geminiviridae and genus Begomovirus . Yellow spots on newly opened leaves and retarded growth of the plant are typical symptoms of CMD‐infected cassava (Figure 3 ). CBSD is caused by two viruses, cassava brown streak virus (CBSV) and cassava brown streak Uganda virus (CBSUV) belonging to Potyviridae family and Ipomovirus genus (Mbanzibwa et al., 2009 ; Winter et al., 2010 ). The virus causes light yellowing and curling of leaves, retarded growth, stem lesions and severe necrosis in the roots, making them unacceptable for human consumption. These viral diseases and their vector whiteflies are prevalent throughout the growing season with varying severity, causing production losses up to 30%–50% (Patil & Fauquet, 2009 ). Cassava is propagated through stem cuttings and farmers obtain planting material from their own farms or surplus material from their neighbours. This practice leads to the accumulation and transmission of various pathogens, particularly viruses from the infected low‐quality planting material. Cassava green mite ( Mononychellus tanajoa ), an indigenous pest, also causes symptoms similar to viral diseases and reduces crop yield in the infested field. The cassava green mite became established as a major pest of cassava across equatorial Africa in the early 1970s (Bellotti et al., 1999 ). Cassava bacterial blight Cassava bacterial blight disease (CBBD), caused by the bacterium Xanthomonas axonopodis pv. manihotis , is the most widespread bacterial disease of cassava (Katie et al., 2015 ). Since 1912, when it was first reported in Brazil, the disease has spread extensively to every part of the world where cassava is grown, including Asia, Africa and South America. The disease spreads from one area to another through infected cuttings, raindrops, use of contaminated farm tools, chewing insects and the movement of humans and animals through plantations, especially during or after rain. The disease was first reported in Africa in Madagascar in 1946 (Livoi et al., 2018 ) and has now become a major constraint to cassava production (Figure 2 ), with yield losses of up to 100% reported in some countries (Livoi et al., 2018 ). Infected leaves exhibit angular, localized water‐soaked regions. Under severe disease conditions, there is significant defoliation, leaving bare stems referred to as candle sticks. The disease is systemic, with infected stems and roots exhibiting a brownish discolouration. Bacterial exudation (which appears as gum) can easily be seen on the bottom leaf surfaces of infected leaves as well as on the petioles and stems during times of high humidity. Wet weather is favourable for the development and spread of the disease. Management of the disease involves cultural practices, varietal resistance, biological control and sanitation practices. However, no durable broad‐spectrum resistance genes are available to breeders (Veley et al., 2023 ). Cassava root rot disease Cassava root rot disease (CRRD) is caused by a complex of soilborne pathogens and is one of the most destructive diseases of cassava, causing up to 100% yield losses in susceptible varieties (Hohenfeld et al., 2022 ). Several fungal species, including Phytophthora drechsleri , Polyporus sulphureus , Fusarium oxysporum , Lasiodiplodia theobromae , Fusarium solani and Macrophomina phaseolina , have been reported to cause CRRD (Akrofi et al., 2018 ). Environmental factors such as high temperatures, high humidity, waterlogging conditions in the soil and low soil fertility have been reported to promote CRRD (Akrofi et al., 2018 ). The disease symptoms include dark‐brown patches in the storage root tissue, wilting, browning and defoliation of the leaves. When the majority of the storage roots have decayed, the rot extends to the base of the plant and then there is lodging of the whole cassava plant. When only a few roots are affected, the cassava plants appear healthy and so the impact caused by the disease at this stage is not visible until harvested. Cassava whiteflies B. tabaci is a whitefly species complex that causes severe damage to cassava. B. tabaci causes direct damage to cassava by sucking plant sap and removing plant nutrients, thereby weakening the plants. Damage may be more severe when plants are under water stress. In addition, they excrete a sugary honeydew that serves as a food source for sooty moulds that inhibit photosynthesis and respiration (Nelson, 2008 ). The honeydew also contaminates the plant leaves, reducing their market value or eliminating their viability for sale. When B. tabaci infections are severe or prolonged, infested plants may wilt, turn yellow, become stunted or even die. B. tabaci is responsible for transmitting serious cassava viruses that cause CMD and CBSD, which in combination lead to significant yield loss (Maruthi et al., 2002 ). BREEDING FOR RESISTANCE TO DISEASES AND PESTS Breeding efforts for disease resistance improvement In the major cassava‐growing regions, its production is limited by viral diseases (CBSD, CMD) and bacterial blight (CBB). This section summarizes the extensive efforts in breeding for improvement against these three major diseases. The resistance to CMD has been well characterized and was initially introgressed into M. esculenta from M. glaziovii in the late 1930s in Tanzania's Amani breeding centre (Jennings, 1957 ). Breeding efforts have progressed through the years in national research centres and at the Consultative Group on International Agricultural Research (CGIAR) centres, International Institute of Tropical Agriculture (IITA) and International Center for Tropical Agriculture (CIAT) (Lokko et al., 2007 ). Three types of CMD resistance exist in cassava: CMD1 , which is controlled by a recessive gene; CMD2 , a major dominant gene; and CMD3 , which has CMD2 in addition to a quantitative trait locus (QTL) (Utsumi et al., 2012 ). The CMD resistance present in the tropical Manihot species (TMS) series has been bred into other African genotypes (Jha et al., 2020 ; Turyagyenda et al., 2013 ; Utsumi et al., 2012 ). Resistant cultivars have also been identified in farmer‐preferred cultivars, exemplified by efforts in Benin and Nigeria (Utsumi et al., 2012 ; Xiao et al., 2019 ). Recently, there have been observations of breakdown in CMD2 resistance when genotypes go through tissue culture (Li et al., 2017 ). The CMD2 resistance is the dominant resistance, and these observations indicate why there is breakdown even as efforts to identify other sources of resistance are enhanced. CBSD is the most devastating cassava disease in Africa (Collard et al., 2005 ). Unlike CMD, whose resistance breeding is well elaborated and implemented, CBSD tolerance is not as elaborately implemented mainly due to low levels of resistance, lack of appropriate CBSD characterization in resistant genotypes as well as genotype × environment interactions. The sources of resistance came from species M. glaziovii and M. melanobasis breeding efforts that began in Tanzania in the late 1950s and early 1960s. These early breeding efforts were entirely based on the polygenic inheritance nature of CBSD resistance. Efforts to characterize and map the resistance in farmer‐preferred cultivars in Tanzania and cultivars from other regions have resulted in the identification of loci in a number of these cultivars (Ruan et al., 2018 ; Wu et al., 2019 ). Due to complexity in the inheritance of CBSD resistance, efforts to characterize and map resistance will continue into the near future even as breeding efforts continue. Efforts in breeding for resistance to CBB were initiated in early 1970s at IITA (Hahn et al., 1974 ). The resistance to CBB, just like CBSD, is polygenic, with regions of resistance identified in close proximity to CMD2 (Rabbi et al., 2014 ). Mapping of sources of resistance in 150 lines from intraspecific crosses in cassava identified eight QTLs that could be used to assist in breeding (Jorge et al., 2001 ). However, the level of resistance linked to the eight QTLs was observed to have seasonal variations and additional sources of resistance may need to be mapped. Recent research has identified and characterized CBB resistance genes denoted as MeLRR s. Four MeLRR s were assessed on their ability to regulate resistance to X. axonopodis pv. manihotis infections in Arabidopsis thaliana . Despite the variations, the four MeLRR s were able to positively regulate disease resistance (Zhang et al., 2022 ). Such resistance genes could be bred into cassava or overexpressed through genetic engineering approaches. There are mainly two major pests affecting cassava, whiteflies and mites, the former being the insect vector for two devastating cassava viruses, CBSV and CMV (Chalwe et al., 2015 ; Koros et al., 2018 ; Nukenine et al., 2002 ). In a study involving a 39‐year time‐series within which were major episodes of whitefly pandemics, increases in episodes of diseases transmitted by whiteflies were observed and these correlated with improved conditions of insect proliferation (Parry et al., 2020 ; Rabbi et al., 2014 ). Cassava breeding efforts for resistance to insect pests are limited because most of the focus has been on breeding for resistance to diseases (Houngue et al., 2019 ; Nzuki et al., 2017 ; Parry et al., 2020 ). There are African and South American genotypes that have been reported to have some level of resistance to whiteflies (Beyene et al., 2016 ; Ndunguru et al., 2016 ). Ten cassava genotypes evaluated in Uganda showed resistance to whitefly infestation and feeding damage, and it was concluded that these can be used as parental materials in breeding programmes for both whitefly and viral disease resistance (Beyene et al., 2016 ). In yet another study, a South American genotype MEcu72 and three Ugandan genotypes were observed to have resistance to whiteflies. In a similar study at the IITA in Nigeria, two genotypes, 96/1089A and TMS 30572, were observed to have supported the lowest number of whiteflies (Ariyo et al., 2005 ). These studies attest to the presence of resistance to whiteflies in genotypes from within the major cassava‐growing regions. These can be harnessed and integrated into breeding programmes within these regions for improved productivity. Cassava green mites (CGM), unlike whiteflies, are vectors for a limited number of diseases, but are still devastating to cassava, resulting in up to 80% loss in productivity (Ezenwaka et al., 2018 ; Kayondo et al., 2018 ). They are especially destructive during the dry season (Praveen, 2018 ), which is of particular importance with projections that climate change will result in drier conditions. A substantial number of studies have identified resistance to mites in cassava genotypes (Kayondo et al., 2018 ; Masumba et al., 2017 ; Somo et al., 2020 ). Over 300 out of 5000 cultivars in the CIAT germplasm were observed to have some degree of resistance to CGM (Fang & Xiong, 2015 ). In another study at IITA Tanzania, 58 out of 377 clones tested under natural resistance to CGM were observed to have class I and II resistance (Shirima et al., 2020 ). Some of the clones from Zanzibar identified with CGM resistance were also observed to be high yielding and resistant to CMD, and had acceptable consumer quality (Shirima et al., 2020 ). The studies on resistance to CGM, just like in whiteflies, point towards possible breeding for their tolerance or resistance. Screening for tolerance to multiple pests has not been extensively reported and the possibility of having resistance to multiple pests (pyramiding) would not only enable an efficient way to use resources but would also save the time used in breeding. Genetics and genomics characterization of resistance to cassava pathogens and pests In recent years, molecular and genomics studies of pathogens and pests have been carried out to enhance the breeding of cassava for resistance (Ezenwaka et al., 2020 ). These studies have broadened the understanding of traits behind resistance and have also informed breeding approaches in different cassava‐growing regions. In this section, some of these studies and their applications to cassava improvement against the pests and diseases are explored. The molecular basis for resistance to CMD is perhaps the best characterized of all the cassava diseases. Three regions that have been consistently associated with resistance to CMD were originally identified in the breeding programme in Amani, Tanzania (Ceballos et al., 2020 ). The first resistance region denoted CMD1 is a recessive polygenic region that has been mapped using simple‐sequence repeat (SSR) markers (Mohan et al., 2013 ). CMD1 was originally introgressed from the wild cassava relative M. glaziovii in Tanzania. The second, and most important, source of resistance ( CMD2 ) is a major monogenic and dominant region identified in African landraces within a narrow geographical region in West Africa. CMD2 has been mapped to chromosomes 8 and 12 using single‐nucleotide polymorphism (SNP) markers (Nzuki et al., 2017 ). This source of resistance has further been fine‐mapped using genotyping‐by‐sequencing, the results of which correlate with previous less‐detailed markers (Rabbi et al., 2014 ). There have been fears of instability of this resistance due to the narrow mode of its origin and the fast rate of cassava mosaic geminiviruses evolution. These fears are further exacerbated by recent observations that there is loss of CMD2 resistance in plants that have undergone somatic embryogenesis in tissue culture (Beyene et al., 2016 ). Furthermore, two sequences enhancing geminivirus symptoms, and which are now considered to be satellite viruses, have also been observed to result in breakdown of CMD2 resistance (Ndunguru et al., 2016 ). The third region of CMD resistance, CMD3 , comprises two additive regions to CMD2 that are thought to be epistatic in their mode of operation (Wolfe et al., 2016 ). To ensure sustained resistance, integrating the monogenic and polygenic sources of resistance has been proposed as a viable improvement approach (Rabbi et al., 2014 ). In the face of an evolving virus, the search for additional sources of resistance or integrating biotechnology techniques like genome editing to enhance the resistance could equally be viable options. Resistance to CBSD has so far been found to be purely polygenic, unlike CMD (Shirima et al., 2020 ). The resistance for root necrosis and leaf symptoms seems to be in different chromosomes, as studies have consistently identified. In a cross between a Tanzanian landrace, Kiroba and the breeding line AR37‐80, for example, two QTLs associated with CBSD root necrosis and seven associated with leaf symptoms were mapped to chromosomes V and XII for the former and chromosomes IV, VI, XVII and XVIII for the latter (Nzuki et al., 2017 ). Similar QTLs, albeit in different chromosomes, were observed in crosses between the farmer‐preferred cultivars Namikonga and Albert (Masumba et al., 2017 ). The polygenic nature of these CBSD QTLs has further been corroborated in a study using SNP markers generated through genotyping‐by‐sequencing where two regions in chromosome 4 and 11 were linked to CBSD resistance (Kayondo et al., 2018 ). It is clear from these studies that CBSD resistance is still not as explored as CMD resistance. It is not clear, for example, the total as well as the individual contributions of these polygenic regions to CBSD resistance. There is therefore more effort needed in the identification of the roles of the different polygenic regions in CBSD resistance considering that this is the most devastating disease in cassava. The basis for tolerance to CGM lies in traits like pubescent leaves, large compact shoot apices and improved leaf retention as well as stay green (Ezenwaka et al., 2018 ). It is thought that the natural predator of CGM, Typhlodromalus aripo , is attracted to leaf trichomes in pubescent leaves as they release volatile organic compounds (Ezenwaka et al., 2020 ). Two SSR markers (NS 1099 and NS 346) are strongly associated with CGM resistance (Choperena et al., 2012 ). In another study, two QTLs located on chromosomes V and X involved in CGM resistance were identified in F 1 hybrids from crosses between Tanzanian landrace Kiroba and a breeding cultivar AR37‐80 (Nzuki et al., 2017 ). In a study using 42,204 SNP markers in F 1 progenies of CGM‐resistant and ‐susceptible parents, one significant QTL (S12_7962234) located in chromosome 12 was identified (Ezenwaka et al., 2020 ). Nine novel genes were further linked to this QTL. In more recent studies, genome‐wide targeted approaches have been used to map CGM resistance. A genome‐wide association study to CGM resistance using a panel of 845 advanced breeding lines identified 35 SNP markers associated with CGM resistance and leaf pubescence in chromosome 8 (Ezenwaka et al., 2018 ). This genome‐wide study identified 17 genes linked to the CGM resistance in chromosome 8. Efforts should be geared towards identification of the exact mechanisms involved in resistance in QTL and SNPs in chromosome 8. MODERN BIOTECHNOLOGICAL TOOLS FOR ENHANCING RESISTANCE TO DISEASES AND PESTS Conventional breeding strategies to develop cassava for tolerance to pests and diseases is a major challenge because of the crop's poor flowering nature, polyploidy, vegetative propagation and heterozygosity, which prevent the transfer of desirable agronomic traits into the crop. To overcome these challenges, conventional breeding should be complemented with genetic engineering and genome‐editing techniques (Figure 4 ) to develop disease‐ and pest‐resistant cassava. In this section we will discuss the genetic engineering and genome editing strategies available for producing pest‐ and disease‐tolerant cassava. Improvement of cassava for resilience to diseases by genetic engineering The RNAi‐based silencing mechanism has been the main genetic engineering tool used to generate high‐level resistance to both CMD and CBSD (Chavarriaga‐Aguirre et al., 2016 ). RNAi, or posttranscriptional gene silencing, was developed as a mechanism for effective control of pathogens in crops (Susi et al., 2004 ). During the last two decades, RNAi has gained significant prominence as the method of choice for researchers to engineer pathogen resistance in crops. RNAi has an advantage over overexpression as it regulates gene expression via mRNA degradation, translation repression and chromatin remodelling through small noncoding RNAs, targets endogenous as well as exogenous genes and can be used in a highly targeted tissue‐specific manner to combat pathogens. To engineer disease resistance by RNAi, a construct is designed such that when the transgene is expressed in the plant, it produces double‐stranded RNAs (dsRNAs). These dsRNAs are further processed by a Dicer (ds‐specific ribonuclease) to short interference RNA (siRNA) of 21–25 bp long. The siRNAs are then transported to a RNA‐induced silencing complex (RISC) where they are bound to the Argonaute proteins, which recognize and degrade homologous mRNA (Bonfim et al., 2007 ; Susi et al., 2004 ). The transgene can either target the plant host factors or the pathogen genes. Most RNAi studies on disease resistance are based on pathogen‐derived resistance, in which plants are transformed with genes or sequences derived from the pathogen to block the expression of the specific gene in the pathogen. For example, most existing cases of genetically engineered crops with resistance to viral pathogens via RNAi have targeted the coat protein, the movement protein or the replication protein of the virus. The RNAi‐mediated resistance to CMD and CBSD mostly involved posttranscriptional silencing of coat protein ( CP ) genes, or the AC1 ( Rep ), AC2 ( TrAP ) or AC3 ( REn ) genes implicated in the replication of viral DNAs (Chavarriaga‐Aguirre et al., 2016 ). The first report highlighting the use of RNAi to develop resistance to CMD was demonstrated by Zhang et al. ( 2005 ) using the easy‐to‐transform model cultivar TMS60444. The authors developed transgenic plants with increased resistance to African cassava mosaic virus (ACMV) by antisense RNA technology targeting the viral mRNAs of Rep ( AC1 ), TrAP ( AC2 ) and REn ( AC3 ). Viral DNA replication assays in detached leaves as well as ACMV infection in transgenic plants showed strong reduction or inhibition of the replication of two isolates of ACMV in most of the transgenic lines (Zhang et al., 2005 ). Thereafter, Vanderschuren et al. ( 2007 ) introduced resistance to ACMV using an RNAi construct targeting the common region of ACMV DNA‐A into the cultivar TMS60444. Similarly, Vanderschuren et al. ( 2009 ) engineered transgenic TMS60444 with resistance to ACMV by expressing ACMV AC1‐homologous hairpin dsRNAs. Transgenic lines accumulated high levels of AC1‐homologous small RNAs and exhibited ACMV immunity under high viral pressure. Kasetsart University 50 (KU50), an elite cultivar widely grown by many farmers in Asia for its high dry matter content, is highly susceptible to CMD caused by the Sri Lankan cassava mosaic virus (SLCMV) (Dutt et al., 2005 ). Ntui et al. ( 2015 ) engineered KU50 cultivar for resistance to SLCMV by RNAi‐mediated silencing of the AV1 coat protein and AV2 pre‐coat protein genes. Transgenic lines accumulated high levels of siRNA and displayed increased resistance to SLCMV, and no virus load could be detected in uninoculated new leaves of the infected resistant lines. RNAi technology was shown to generate high‐level resistance to CBSD, a major cassava disease in East Africa (Vanderschuren et al., 2012 ; Yadav et al., 2011 ). Transgenic TMS60444 lines expressing inverted‐repeat constructs of highly conserved sequences of CBSV and CBSUV of the viral CP (Vanderschuren et al., 2012 ) or full‐length coat protein (FL‐CP) of CBSUV (Yadav et al., 2011 ) demonstrated increased resistance to CBSD after viral inoculation. Due to immunity against CBSD, Vanderschuren et al. ( 2012 ) adapted this technology to generate transgenic cassava lines combining resistance to both CBSD and CMD. They expressed the hairpin construct in a CMD‐resistant farmer‐preferred Nigerian landrace TME 7 (Oko‐Iyawo). All transgenic TME 7 lines showed immunity against CBSV and CBSUV infections. The resistance was maintained when plants were co‐inoculated with East African cassava mosaic virus (EACMV), a geminivirus causing CMD. The RNAi technology described above represents an important approach to tackling the problem of CMD and CBSD. Unfortunately, loss of CMD resistance in these transgenic plants has been reported in the field. Although the cause of such loss is unknown, it is hypothesized to be epigenetic regulation of the CMD2 locus during the production of transgenic and non‐transgenic cassava plants through somatic embryogenesis. These findings indicate that cassava breeders need to look for alternative sources of CMD resistance in cassava, probably the use of cytokinin meta ‐topolin [6‐(3‐hydroxybenzylamino) purine] to induce in vitro shoots on non‐embryogenic explants (Chauhan & Taylor, 2018 ), or work with CMD1 and/or CMD3 resistant cultivars. Success in obtaining resistance to CBSV using RNAi technology has been achieved. Cassava with resistance to CBSD using RNAi technology has undergone field trials in Uganda and Kenyan, and very high levels of resistance were demonstrated (Wagaba et al., 2017 ). In 2021, Kenya approved CBSD‐resistant cassava for environmental release. The approval is a significant step to getting disease‐resistant cassava into the hands of Kenyan farmers to address food security challenges (NBA [National Biosafety Authority], Kenya, 2021 ). Controlling the whitefly, which is a vector for CMVs and CBSV, would represent an alternative for the management of CMD and CBSD. The use of transgenic technology to control lepidopteran pests in maize, soybean, canola and cotton (James, 2015 ) has paved the way for controlling insect pests in crops. Although genetic engineering approaches have not been used to control whitefly and other insect pests of cassava, several insect genes have been identified that could be targeted for silencing in whitefly (Chavarriaga‐Aguirre et al., 2016 ; Jekayinoluwa et al., 2020 ). In nymphs and adults of Aleurotrachelus socialis feeding on the whitefly‐resistant cassava landrace Ecu72, several differentially expressed genes have been identified (reviewed in Jekayinoluwa et al., 2020 ). Among the up‐regulated genes were chitinases, lipoxygenases, LOX5 and methyl‐transferases such as cafeoyl‐CoA‐o‐methyltransferase. Cafeoyl‐CoA‐o‐methyltransferase gene is involved in lignin synthesis. Given that salicylic acid, jasmonic acid and ethylene control several of the cellular biochemical paths that respond to pathogens and pests, the overexpression and/or down‐regulation of genes such as LOX5 or cafeoyl‐CoA‐o‐methyltransferase in cassava could be an important pathway for controlling whitefly. Developmental genes play important roles in insect development and function. During insect development, several genes are either expressed or down‐regulated at different stages of the insect's lifecycle (Jekayinoluwa et al., 2020 ). Overexpression or down‐regulation of the genes throughout the insect's lifecycle could interfere with the insect's development and hence reduce virus transmission. For example, silencing the midgut gene Rack1 in green peach aphid reduced the growth of gut cells and subsequently decreased nutrient uptake (Pitino et al., 2011 ). The salivary enzyme alkaline phosphatase, first identified in the saliva of a Russian wheat aphid, plays a major role in the penetration and feeding mechanism of the insect (Cooper et al., 2011 ). Blockage in the expression of salivary sheath protein ( shp ) required for the ingestion of phloem sap by RNAi led to decreased growth, fecundity and survival of grain aphid (Abdellatef et al., 2015 ). Flight is an important activity that allows insect vectors to transmit diseases from plant to plant. During flight, essential genes such as 3‐ketoacyl‐CoA thiolase, phosphoenolpyruvate carboxykinase and glycogen phosphorylase‐like isoform 2, involved in lipid metabolism, increase in wing muscles. RNAi‐mediated silencing of such genes in citrus aphid impacted wing development (Shang et al., 2016 ). In Aphis gossypii , the abnormal wing disk ( awd1 and awd2 ) genes play a significant role in the development and differentiation of the insect. The genes encode a nucleoside diphosphate kinase and were reported to be significantly up‐regulated in wingless than in winged morphs (Yang et al., 2014 ). Loss of function of awd in Drosophila caused lethality (Yang et al., 2014 ), indicating the significance of these genes in the mobility and dispersal of insects. In green peach aphid, RNAi‐mediated silencing of the acetylcholinesterase ( MpAChE2 ) gene, a serine hydrolase that regulates acetylcholine in insects, birds and mammals, resulted in resistance of transgenic plants to aphids (Guo et al., 2014a ; Guo, Wang, et al., 2014 ). The implication of these studies is that these genes could be silenced in whitefly to interfere with the feeding mechanism, movement and development of the insect, leading to death and hence reduced CMV and CBSV transmission. Genome‐editing strategies to develop disease‐resistant cassava In recent years, genome editing, the ability to perform controlled/precise changes in the genome of an organism using specific nucleases, has become the tool of choice to modify plants. Several nucleases, including meganucleases, zinc finger nucleases (ZFNs), transcription activator‐like effector nucleases (TALENs) and the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas associate protein (Cas) (CRISPR/Cas), have been developed to achieve effective genome editing in organisms (Tripathi et al., 2019 ). Among these nucleases, CRISPR/Cas9, which was developed from the adaptive immunity system of Streptococcus pyogenes , is widely used as the most effective genome‐editing tool in plants because of its simplicity, design flexibility, high efficiency and ability to edit multiple genes simultaneously (multiplexing) (Ntui et al., 2020 ; Tripathi et al., 2019 ). The CRISPR/Cas9 technology comprises two basic components: the Cas9 nuclease and the gRNA (guide RNA). The Cas9 recognizes target DNA by gRNA–DNA pairing between the 5′ leading sequence of gRNA and the target sequence. It also recognizes the protospacer adjacent motif (PAM) sequence and starts editing upstream of the sequence. The PAM is a three‐nucleotide sequence, usually NGG or NAG, where N can be any nucleotide base, and serves as a recognition segment for Cas9 to start editing upstream. Usually, Cas9 shows more affinity to NGG than NAG. The gRNA directs the endonuclease Cas9 to induce precise double‐stranded break (DSB) cleavage at a target site; repair of this site by the cell's own natural repair mechanism of homology‐directed repair (HDR) or nonhomologous end joining (NHEJ) can produce a user‐desired mutation or genetic outcome. The NHEJ repair, which is error prone, creates random insertions and deletions (SNPs, indels) and results in frameshift mutations and targeted gene knockouts. The HDR pathway is more precise in the repair of a DNA sequence, leading to gene knock‐in, gene replacement or insertion of foreign genes or DNA sequences. Based on the type of repair, the editing is classified into three types: SDN1, SDN2 or SDN3 (Modrzejewski et al., 2019 ). SDN1, which is based on NHEJ results in random mutations in the host genome, causes gene silencing, gene knock‐out or alteration in the gene function. When the repair template identical to the DSB is added and the repair is via HDR, resulting in nucleotide substitution or targeted indels, it is referred to as SDN2. In SDN3, the DSB is repaired via HDR using a repair template that is longer than the homologous sequences in which the DSB is made, resulting in the targeted insertion of foreign genes. The ability of CRISPR/Cas9 to create DSBs at sequence‐specific targets in the DNA or RNA molecules makes it an excellent tool to engineer disease and pest resistance in crops. Recently, CRISPR/Cas variants with different editing strategies, such as Cas12a (Cpf1), Cas13, CRISPR activation (CRISPRa), CRISPR interference (CRISPRi), base editing and prime editing, have been developed and used for editing in plants (Joshi et al., 2020 ; Tripathi et al., 2022 ). The first report on CRISPR/Cas9 editing of cassava was established using the phytoene desaturase ( PDS ) gene (Odipio et al., 2017 ). PDS is an enzyme in the carotenoid biosynthesis pathway involved in the conversion of colourless phytoene into lycopene, a coloured compound in the pathway (Kaur et al., 2018 ). Knockout of PDS usually results in the production of albino phenotypes (Kaur et al., 2018 ; Ntui et al., 2020 ). Odipio et al. ( 2017 ) edited PDS in the model cultivars TMS60444 and TME 204, and obtained a mutation frequency of 90%–100%, with most of the plants exhibiting an albino phenotype. Their report opened avenues for genome editing of cassava for resistance to CMD and CBSD. Gomez et al. ( 2019 ) generated transgenic cassava plants expressing Cas9 and gRNAs targeting nCBP‐1 and nCBP‐2 , which are isoforms of eIF4E . The eukaryotic translation initiation factor ( eIF ) gene family, including eIF4E and its paralogue eIF(iso)4E, also known as cap‐binding protein, are essential susceptibility genes required for the cellular infection cycle of potyviruses, which have single‐stranded, positive‐sense RNA (ssRNA+) genomes. In plants, some host genes classified as susceptibility genes ( S genes) facilitate pathogen invasion and thus are considered essential for compatible plant–pathogen interactions (Zaidi et al., 2020 ). During pathogen invasion, these genes are activated by the pathogen to favour pathogen growth and promote symptom development. Editing of S genes has been reported to confer resistance to the corresponding pathogen and, in some cases, broad‐spectrum resistance (Kim et al., 2018 ; Peng et al., 2017 ). Transgenic cassava plants generated by editing the susceptibility gene eIF4E ( nCBP‐1 and nCBP‐2 ) exhibited partial resistance against CBSD (Gomez et al., 2019 ). Other susceptibility genes, such as mildew resistance locus O ( MLO ) (Wang et al., 2014 ), ERF transcription factor, WRKY and MYB , PMR4 (Santillán Martínez et al., 2020 ), Sugar Will Eventually be Exported Transporters ( SWEET ) (Oliva et al., 2019 ), Lateral Organ Boundaries ( CsLOB1 ) (Jia et al., 2016 ; Peng et al., 2017 ), as well as fungal receptor genes such as downy mildew resistance 6 ( DMR6 ) (Tripathi et al., 2021 ) or their promoters can be edited in cassava to develop resistance to other pathogens. Editing of viral genes is an important strategy to develop resistance against viruses. DNA as well as RNA viral genes have successfully been edited by Cas9, Cas12a or Cas13a (Aman et al., 2018 ; Kalinina et al., 2020 ; Khatodia et al., 2017 ; Tripathi et al., 2019 ; Yin & Qiu, 2019 ; Zhang et al., 2019 ). Ali et al. ( 2015 ) were among the first to use CRISPR/Cas9 to induce resistance to viruses. They designed gRNAs targeting the viral Rep, coat protein and conserved intergenic region (IR) of tomato yellow leaf curl virus (TYLCV). The gRNAs were integrated to tobacco rattle virus (TRV) vector and delivered to Nicotiana benthamiana plants overexpressing Cas9 by agroinfiltration. N. benthamiana plants having mutations in the target sequences were resistant to TYLCV (Ali et al., 2015 ). Similarly, Ji et al. ( 2015 ) engineered Arabidopsis and N. benthamiana resistant to beet severe curly top virus. Editing of IR and CI coding regions in tobacco resulted in complete resistance to cotton leaf curl Multan virus (Yin et al., 2019 ). Later, N. benthamiana plants agroinfiltrated with a multiplexed CRISPR/Cas9 construct targeting the Rep, and βC1 gene of the beta satellites exhibited delayed symptoms and lower virus titres of cotton leaf curl virus (CLCuV) (Khan et al., 2020 ). In contrast, editing of AC2 and AC3 genes, which encode the transcription activator protein and the replication enhancer protein of ACMV, respectively, failed to generate resistance against the virus in transgenic cassava (Mehta et al., 2019 ). Instead, the authors observed that CRISPR/Cas9 editing resulted in the formation and escape of new (CRISPR‐resistant) ACMV variants that were probably generated due to post‐cleavage repair. Altogether, this study showed that direct targeting of viral genes is a powerful tool for engineering resistance to viruses; however, in some cases, it may trigger rapid evolution of the virus, resulting in the development and release of new pathogenic virus forms, as reported by Mehta et al. ( 2019 ). In this regard, adequate knowledge of the roles of viral genes will be necessary to identify potential crucial genes for editing. One of the major devastating diseases of cassava is CBSD caused by RNA virus variants. The recent identification of the RNA‐only targeting Cas13 is a welcome addition to the genome‐editing arsenal that could directly benefit cassava improvement against RNA‐virus diseases such as CBSD. Cas13 has successfully been used to target plant viruses (Mahas et al., 2019 ). The presence of transcribed RNAs in DNA viruses also means that Cas13 could also be used to target not only RNA viruses but also transcribed DNA‐genome viruses such as CMV. PATHOGEN EVOLUTION DYNAMICS AND CASSAVA IMPROVEMENT Breakdown in resistance against CMV has already been reported (Ndunguru et al., 2016 ), a trend that is expected for other major cassava pathogens as they evolve. Integrating durable resistance against the major pests and diseases of cassava should therefore be informed by pathogen evolution and host–pathogen interactions. Constant surveillance of the major cassava pathogens to establish their evolutionary trajectories is an important way this can be achieved. Efforts have been going on to achieve pathogen evolution and surveillance, although at minimal scale. Minimal efforts to integrate pathogen evolution data to mainstream cassava improvement have been achieved so far. However, efforts to track diversity through surveillance of pathogens are underway. The CBSV and UCBSV evolution was assessed through genomics where two virus variants with different evolutionary trajectory but corresponding to UCBSD outbreaks were identified (Mbanzibwa et al., 2011 ). Additional studies using genomics have observed that CBSV has a faster genome evolution compared to UCBSV, a difference that was correlated with disease severity and host plant diversity (Alicai et al., 2016 ). Molecular and serological approaches have also been used to identify Sri Lanka cassava mosaic virus (SLCMV) variants in China (Wang et al., 2020 ). Surveillance has also identified co‐infections and pest resurgence within cassava farms in Congo (Bisimwa et al., 2019 ). SLCMV surveys have also been conducted in Thailand, with observations revealing a relatively high level of similarity to SLCMV (Saokham et al., 2021 ). A combination of surveillance and evolutionary analyses was able to identify a new cassava mosaic virus named African cassava mosaic Burkina Faso virus (ACMBFV), a recombinant between tomato leaf curl Cameroon virus and cotton leaf curl Gezira virus (Tiendrébéogo et al., 2012 ). Pathogen evolution has been observed to result in enhanced pathogenicity and reduced tolerance/resistance in cassava. Modern breeding approaches that incorporate high‐throughput sequencing technologies, genetic engineering and genome‐editing technologies can be used to enhance resistance durability. PAY‐OFF GAPS ASSOCIATED WITH MOLECULAR GENETIC TOOLS Cassava yields in Africa are mostly small as a result of many factors, including abiotic, biotic and associated crop management practices. Biotic factors such as diseases and pests cause a wide gap between the expected yield and that which farmers achieve. However, this gap becomes smaller as farmers adopt better agronomic practices, including increasing fertilizer, irrigation or the use of pest‐ and disease‐resistant cultivars (Srivastava et al., 2023 ). The molecular genetics and genomics tools described here have the potential to reduce the yield gap by producing disease‐ and pest‐resistant cultivars. The deployment of resistant cultivars provides an efficient means to control disease and pests. However, the advantages of using the resistant variety may be outweighed by a yield penalty, in which case the susceptible variety outperforms the resistant one in the absence of disease or pest. The problem with this is that using the resistant variety is only advised if the disease manifests and is severe enough for the resistant variety to outperform the susceptible variety. The likelihood of a disease or pest invasion is decreased when the resistant variety is planted, which provides an additional benefit. As a result, from the viewpoint of a grower community, the cropping density for the resistant variety is likely to be at an ideal pay‐off (Vyska et al., 2016 ). Although there are not enough scientifically derived data to definitively assign yield estimates to the cassava improvement methods discussed here, and consequently their economic impact on cassava production, they are nonetheless important factors to closing the cassava yield gap. For example, when the potential for an outbreak is uncertain, planting the resistant variety reduces the probability of an outbreak occurring and hence lowers the yield gap. FUTURE PERSPECTIVES Currently, the method of choice for producing cassava with disease resistance through genome editing is by plasmid delivery of CRISPR/Cas reagents. This method is laborious, and many farmers' preferred genotypes are still recalcitrant to genetic transformation. Techniques like in planta transformation or agroinfiltration could be used. Platforms based on viral vectors could be used to deliver CRISPR/Cas9 constructs quickly and effectively. CMV could be modified to carry the CRISPR/Cas9 reagents into the plant genome through agroinfiltration. This method has been demonstrated in tomato and tobacco (Ali et al., 2015 ). Production of DNA‐free genome‐edited cassava could boost its productivity and acceptability. Until now, cassava genome editing has been based on plasmid delivery of CRISPR/Cas9 reagents, which are integrated into the genome and thus the product is regulated as a genetically modified organism. This may reduce its acceptability in many countries. Cassava is vegetatively propagated, hence transgenes cannot easily be eliminated by segregation as in sexually propagated crops, even with CRISP/Cas9‐mediated plasmid delivery. This will be a significant obstacle to creating cassava genotypes that are resistant to diseases and pests using genome editing. However, direct delivery of preassembled Cas9 protein‐gRNA ribonucleoproteins (RNPs) into cassava cells may be able to overcome these restrictions because the RNPs are rapidly broken down by indigenous proteases after being delivered, leaving no signs of foreign DNA elements behind. The mutant genotypes will not encounter any significant regulatory problems. Recently, researchers have developed a CRISPR/Cas editing system in which grafting a wild‐type shoot to a transgenic donor rootstocks produced DNA‐free genome‐edited lines (Yang et al., 2023 ). In this system, a transgenic genome‐edited root is produced. On grafting the root with a wild‐type shoot, the Cas9 and the gRNA transcripts are transported from the transgenic rootstock to the shoot, where they create mutations in the shoots without integration. The resulting shots and seeds are foreign DNA‐free genome‐edited lines. Using this method, the stress of going through tissue culture is avoided. Cassava breeders/biotechnologists could explore the possibilities of using this method to produce foreign DNA‐free genome‐edited cassava. Grafting in cassava has already been demonstrated (Souza et al., 2018 ). Despite being used minimally in plants, nanobody (Nb)‐mediated virus resistance is emerging as a new way of generating resistance. The stable overexpression of grapevine fanleaf virus‐specific Nbs in N. benthamiana and grapevine, for example, conferred resistance to the virus in both plants (Hemmer et al., 2018 ). The small sizes of Nbs could allow for their delivery through viral vectors and thus circumvent the need for a tissue culture process involved in cassava genetic engineering. CONFLICT OF INTEREST STATEMENT The authors declare no competing interests exist.

ACKNOWLEDGEMENTS The authors wish to thank the CGIAR Roots, Tubers and Banana Program. DATA AVAILABILITY STATEMENT Data sharing is not applicable to this article as no new data were created or analysed.

CC BY

no

2024-01-16 23:43:47

Mol Plant Pathol. 2023 Nov 7; 25(1):e13402

oa_package/f4/37/PMC10788594.tar.gz

PMC10788595

38226125

Introduction Human immunodeficiency virus (HIV) infection first appeared in 1981 in the United States through manifestations of opportunistic infections or neoplasms in young men who had sex with men or who used intravenous drugs [ 1 ]. Epidemiologically, HIV infection has so far been responsible for more than half a million deaths in both children and adults of both genders due to HIV-related causes according to the 2022 report of the World Health Organization regarding the global HIV epidemic [ 2 ]. However, despite the alarming increase in cases in the 1980s, with a peak in 1997, effective therapy and understanding of transmission methods have made it possible to reduce cases by up to 50% in the last years. The introduction of triple antiretroviral therapy (zidovudine + didanosine, zidovudine + zalcitabine, zidovudine + lamivudine) in 1996 displayed effectiveness in the long-term and reduced mortality and morbidity of the HIV infection. At that time, the HIV epidemic was severely affecting the healthcare system in the United States and African countries [ 3 ].

Discussion Vasculitic manifestations of shingles are rare and often associated with a severe prognosis. They generally affect the cerebral vessels and can cause damage to large and small vessels [ 6 ]. Shingles can affect both the central nervous system, causing encephalitis, and the peripheral nervous system, leading to post-herpetic neuralgia, segmental paresis, and Guillain-Barré or Hunt syndrome, respectively [ 7 , 8 ]. Leukocytoclastic vasculitis is a small vessel vasculitis responsible for approximately 37% of vasculitic-type phenomena due to VZV infection. However, manifestations of this type are extremely rare, especially distributed at the level of the limbs. Only a few cases of shingles-related vasculitic eruptions have been reported in the literature [ 9 ]. Differential diagnosis of our patient's lesions was difficult. The lesions could have been interpreted as leukocytoclastic vasculitis in the context of VZV infection (either post-vaccination or in the context of HIV infection) or as hemorrhagic shingles in the context of HIV-induced immunosuppression. SARS-CoV-2 and VZV association The SARS-CoV-2 virus has been the focus of medical attention for the past three years, with both the infection and the vaccine being associated with multiple complications or side effects that can present as skin manifestations. Thus, considering the anamnesis, the presence of the flu-like syndrome, and the short duration of onset after the second dose of the BNT162b2 Pfizer BioNTech vaccine, the first diagnosis considered was that of a post-vaccination reaction. There are several reported cases of zoster eruptions post-SARS-CoV-2 immunization. In these situations, the rash occurred more frequently in the first two weeks following the first dose, a phenomenon explained by a progressive post-vaccine lymphopenia, with a decrease in CD4+ and CD8+ lymphocytes responsible for cellular defenses that prevent the reactivation of the zoster virus from the dorsal ganglia roots [ 10 ]. Reactivations after the second dose are, however, less common, with most cases reported affecting the cephalic extremity [ 11 , 12 ]. However, our patient presented with moderate lymphopenia in the context of the HIV infection, which could explain a shingles reactivation following immunization on the background of pre-existing immunosuppression. This diagnosis does not change the therapeutic management of the current eruption. Association of leukocytoclastic vasculitis and shingles Another considered diagnosis was that of leukocytoclastic vasculitis occurring synchronously with shingles, affecting the same dermatomes, as a revealing phenomenon of HIV infection. Several pathophysiological mechanisms have been proposed to explain the development of this manifestation. Viral infections can be responsible for the occurrence of vasculitis by altering endothelial cells. In cases of synchronous occurrence, the most plausible mechanism is considered to be the invasion of blood vessels employing nerve fibers that run from the dorsal root to the vessel and along which the viral material is transported [ 13 ]. The distribution of the lesions and the histopathological aspect supported this diagnosis; however, due to the rarity of this manifestation, as well as the patient's inability to chronologically describe the evolution of the lesions, the post-shingles vascular cytopathic phenomenon became a more likely diagnosis [ 14 ]. Severe immunodepression and VZV association The last diagnosis considered was that of hemorrhagic shingles as a revealing phenomenon of HIV infection that occurred in the context of immunosuppression and coagulation disorders caused by both thrombocytopenia and changes in S protein levels that the patient exhibited [ 15 ]. Hemorrhagic shingles is a rare condition, most often associated with the administration of antiplatelet or anticoagulant drugs, conditions that cause thrombocytopenia, or even with the SARS-CoV-2 infection [ 16 , 17 ]. No cases of hemorrhagic shingles associated with SARS-CoV-2 vaccines have yet been reported. Although affecting only the skin in this case, hemorrhagic shingles remains a life-threatening condition and can be complicated in a large number of cases by hemorrhagic encephalitis or mesenteric infarction, thus requiring early antiviral treatment and close follow-up [ 18 , 19 ]. To our knowledge, there has been another report of VZV reactivation in an HIV-positive individual after the second dose of the SARS-CoV-2 Pfizer vaccine; however, the patient was already in the acquired immune deficiency syndrome (AIDS) stage of the HIV infection, and thus not discovered with HIV primoinfection as in our case [ 20 ].

Conclusions In our case, shingles was a harbinger of HIV infection. The patient was diagnosed with secondary leukocytoclastic vasculitis, which manifested as a vasculitic-like rash and hemorrhagic vesicles. In the absence of the patient's SARS-CoV-2 immunization, which could have exacerbated the lymphopenia and accelerated viral reactivation, we cannot infer the length of time for which the HIV infection could have remained dormant, thus delaying the administration of antiretroviral therapy. Thus, even if shingles is a common condition in people over 60 years, atypical manifestations should warrant investigation for underlying conditions.

Herein, we report the case of a 69-year-old patient who presented to our dermatology clinic for a skin eruption characterized by grouped hemorrhagic vesicles and erosions covered by hemorrhagic crusts on an erythematous background located on the lower right limb. The lesions were small, clustered, and variable in size (diameters between one and 10 mm) and located at the level of the L4-L5 dermatomes. The rash had started three to five days after the complete COVID-19 vaccination scheme with the BNT162b2 Pfizer BioNTech vaccine and had been accompanied by a flu-like syndrome. The histopathological examination established the diagnosis of leukocytoclastic vasculitis potentially in the context of a cytopathic zoster phenomenon. The atypical aspect of the zosterian eruption required additional laboratory work-up to identify possible causes of immunosuppression, i.e., screening for the presence of the human immunodeficiency virus (HIV) infection, solid cancers, as well as measurement of serum immunoglobulin concentrations, which revealed that the subject was HIV-positive. Antiviral treatment was started, with a favorable evolution of the lesions, and the patient was referred to an infectious diseases clinic for initiation of antiretroviral therapy (ART).

Case presentation The initial nonspecific clinical picture with an influenza-like syndrome, the long period of the viral set point that can last for years, as well as the subsequent polymorphic manifestations, make the diagnosis of HIV infection challenging. Skin manifestations are one of the most common complications of the disease, covering a wide range of manifestations, from bacterial and viral infections to malignancies and rashes in the context of drug toxicity. Of these, herpes zoster, caused by the reactivation of the varicella-zoster virus (VZV), can indicate the presence of an HIV infection. Shingles are 15 to 19 times more common in HIV-positive patients than in the general population and may present atypically in the setting of HIV infection, for example, verruciform cutaneous lesions with hyperkeratosis or necrosis of the integument [ 4 , 5 ]. We present the case of a 69-year-old male who presented to our dermatology clinic with a painful, pruritic rash on the right lower limb with a two-week onset. The medical history of the subject was relevant for the presence of a non-secretory pituitary adenoma diagnosed 20 years ago and treated with radiotherapy and transsphenoidal surgical excision. As a result of these interventions, the patient developed pituitary insufficiency on the gonadotropic line and was prescribed substitution treatment with testosterone with a favorable evolution. The dermatological examination identified a rash consisting of small sanguinolent collections of hemorrhagic vesicles, erythematous macules, and erosions covered by hemorrhagic crusts, of variable sizes (diameters between one and 10 mm). The lesions were grouped, dermatomal, separated through apparently intact skin, and located mainly at the level of the L4 and L5 dermatomes of the right lower limb (Figure 1A -C). Otherwise, the clinical examination was within normal limits. The onset of the rash occurred within three to five days after complete COVID-19 immunization with the BNT162b2 Pfizer-BioNTech vaccine. The patient also reported the presence of a flu-like syndrome (myalgia, distress) before the onset of the rash, as well as the presence of local pain and burning in the affected limb. The patient had no history of SARS-CoV-2 infection. Laboratory findings before the presentation in our clinic, performed in another medical facility, revealed elevated markers of inflammation, presence of pancytopenia, elevated D-Dimer concentrations, and decreased free S protein levels (Table 1 ). Due to the clinical aspect and the unilateral distribution, which met both the criteria for vasculitis and shingles, we decided to perform a punch biopsy. The pathology report established the diagnosis of leukocytoclastic vasculitis as a potentially isotopic phenomenon to the development of shingles (Figure 2A ,B). Given the low frequency of this disorder, its occurrence in immunosuppressed patients or subjects suffering from blood cancers, as well as the laboratory data reported above, the patient was screened for the presence of HIV and tested positive for the infection. The subject denied the use of toxic substances with intravenous administration, as well as at-risk sexual behaviors in the past. The diagnosis of vasculitic shingles was established and was considered a revealing manifestation of latent HIV infection. Treatment with oral acyclovir (4 g/day for 7 days) was started with a favorable evolution of the lesions. The patient was referred to an infectious disease clinic for disease staging and initiation of specific antiretroviral treatment.

The authors acknowledge Dr. Leventer Medical Center and Dr. Tiberiu Tebeica for their help in obtaining and interpreting the histopathological images.

CC BY

no

2024-01-16 23:43:47

Cureus.; 15(12):e50609

oa_package/1f/d4/PMC10788595.tar.gz

PMC10788596

38226079

Introduction Benign prostatic hyperplasia (BPH) is the non-malignant enlargement of the prostate gland. It refers to stromal and glandular epithelial hyperplasia that occurs in the periurethral transition zone of the prostate. It clinically manifests with irritative (frequency, urgency, nocturia) and obstructive symptoms (straining to initiate urination, hesitancy, a weak and interrupted urine stream, and a sensation of incomplete bladder emptying) [ 1 ]. It is a disease prevalent in older men, with a previously reported age-specific prevalence of 8%, 50%, and 80% in the age groups of 30-39, 50-59, and 80-89 years, respectively [ 2 ]. Analysis of data from the Global Burden of Disease 2019 found that the absolute burden peaked in men aged 65-69 years and the age-specific prevalence was highest in men aged 75-79 years [ 3 ]. Despite the increase in the absolute burden of cases, the global age-standardised prevalence (2380 per 1,00,000 population in 2019, -0.77% change from 2000) and disability-adjusted life years (DALY) (48.9 per 1,00,000 population in 2019) attributed to the disease remained largely unchanged between 2000 and 2019. India has reported a high burden of 3480 (2640-4470) cases per 1,00,000 population. This reflects a 0.78% decrease in age-standardised prevalence from 2000, but a 90.9% increase in the number of cases from 95,50,000 in 2000 to 1,82,00,000 in 2019 [ 3 ]. Previous literature has reported several factors associated with benign prostatic hyperplasia including genetics, high dairy, poultry, protein, and energy intake, physical inactivity, sedentary lifestyle, and obesity [ 4 , 5 ]. Moderate alcohol intake and smoking appear to have an inverse association with BPH. Access to health care, level of education, socioeconomic status, and presence of other chronic diseases and co-morbidities were significant predictors for health-related quality of life among older BPH patients [ 5 ]. Co-morbidities including dyslipidemia, cardiovascular disease, diabetes mellitus, and metabolic syndrome among others have been found to be associated with increased occurrence of BPH [ 6 - 8 ]. Multimorbidity is a term used to describe the coexistence of multiple health conditions in an individual, which has been gaining increasing prominence [ 9 ]. It is an emerging global public health challenge with advancing medical science, increasing life expectancy, ageing populations, epidemiological transition and the rising prevalence of chronic conditions. Data from a previous nationally representative survey among adults aged 15-49 years have found the prevalence of multimorbidity in India to be 7.2%, with prevalence peaking up to 16% in some states [ 10 ]. In older populations, the prevalence ranges from 10.1-25.8% [ 11 ]. Temporal trends over the years suggest that population growth and ageing have a major impact on the prevalence and DALYs associated with benign prostatic hyperplasia at the global level [ 3 ]. This may ring especially true for India in the near future, where recent estimates suggest that 10.5% of the population was older than 60 years in 2022, and is expected to double to 20.8% by 2050 [ 12 ]. This also means that the proportions of those with chronic diseases and multi-morbidities are expected to rise in the coming years. The extent of the role that the burden of multiple conditions might play in the development of BPH needs to be studied further along with the different factors associated with the same among the older population in India. With this in mind, we analysed data from a nationally representative survey to determine the association between BPH and multimorbidity among older adults (45-59 years) and elderly (>60 years) population in India.

Materials and methods This was an analytical cross-sectional study comprising a secondary analysis of the Longitudinal Ageing Study in India (LASI) first-wave data from 35 Indian states and union territories (UTs), except Sikkim, approved by the Indian Council of Medical Research [ 11 ]. As a secondary data analysis of LASI, ethical approval was not needed for the current study. LASI was a nationally representative longitudinal survey that collected detailed information on the psychological, social, economic, and health aspects of ageing in India. It was created to provide comprehensive and globally comparable survey data on ageing in the Indian context. The National Institute on Ageing, the Government of India's Ministry of Health and Family Welfare, and the United Nations Population Fund provided funding for the study. The University of Southern California, the International Institute for Population Sciences, and the Harvard T.H. Chan School of Public Health worked together on executing the survey methodology [ 11 ]. Wave 1 of the LASI covered a sample of 72,250 individuals aged 45 and above and their spouses. The study, which is one of the biggest of its kind in the world and the first of its kind in India, evaluated the scientific evidence in the context of variables like demographics, household economic status, chronic health conditions, symptom-based health conditions, functional health, mental health (cognition and depression), biomarkers, healthcare utilisation, family and social networks, social welfare programmes, employment, retirement, satisfaction, and life expectations. LASI Wave 1 adopted a three-stage sampling design in rural areas and a four-stage sampling design in urban areas. In each state/UT, the first stage involved the selection of primary sampling units (PSUs), that is, sub-districts (tehsils/talukas), and the second stage involved the selection of villages in rural areas and wards in urban areas in the selected PSUs. In rural areas, households were selected from selected villages in the third stage. However, sampling in urban areas involved an additional stage. Specifically, in the third stage, one census enumeration block (CEB) was randomly selected in each urban area. In the fourth stage, households were selected from this CEB. To ensure the inclusion of an adequate number of those aged over 65 years, an oversampling of households with at least one member over 65 years of age was done [ 11 ]. Outcome variable Self-reported BPH was assessed by questioning, “Have you ever been diagnosed with any of the following urogenital conditions or diseases?”, with options including BPH. Explanatory variables For this study, data was extracted only of male participants aged 45 years and above. The explanatory variables of interest were any co-morbidity and multimorbidity. The following chronic health conditions were considered while accounting for multimorbidity: hypertension, diabetes, chronic lung diseases (e.g. chronic obstructive pulmonary disease, asthma, chronic bronchitis, other chronic lung problems), chronic heart disease (e.g. congestive heart failure, myocardial infarction, heart attack, other chronic heart diseases), dyslipidaemia (high cholesterol), and thyroid disorders. To assess the presence of chronic health diseases or conditions, the interviewer asked the question “Has any health professional ever diagnosed you with the following chronic conditions or diseases?”. This question required a dichotomous (No/Yes) response. Participants having at least two chronic health conditions were described as multimorbidity. Covariates Following variables were taken as covariates to assess adjusted association: Age-group (years 45-59, >= 60), minimum educational qualification (illiterate, less than primary, primary completed, middle completed, secondary school, higher secondary, and diploma/ graduate), residence (rural, urban), marital status (unmarried, married/live-in, widow/separated/divorced), monthly per capita expenditure (MPCE) (poorest, poorer, middle, richer, richest) quintile, health insurance (no, yes), occupation (unemployed, professional and semi-professional: legislators and senior officials, professionals, technicians and associate professionals, clerical and skilled: clerks, service workers and shopkeepers, skilled agriculture and fishery workers, craft and related trade worker, plant and machine operator, unskilled), physical activity (everyday, once per week, one to three times per week, once per month, never), BMI <18.5, 18.5-22.9, 23-24.9, 25-29.9, >30, self-rated health (excellent, very good, good, fair, poor,), tobacco usage (no, yes), and alcohol consumption (no, yes). After adjusting missing data by row-wise deletion and excluding BMI outliers, we included participants who had documented their BPH status. The details are provided in Figure 1 . Thus, this study included information from 27,541 participants. Statistical analysis Data was analysed with Stata Statistical Software: Release 17 (StataCorp LLC, College Station, Texas, United States). Characteristics of participants were described as mean (standard deviation) for continuous variables and frequencies and percentage for categorical variables (age group, minimum education, MPCE quintile, occupation, BMI). Univariate logistic regression was conducted between the outcome variable and each explanatory variable. To avoid multicollinearity among explanatory variables, a variance inflation factor (VIF) was applied. VIF > 5 indicates a high correlation between a given explanatory variable and other explanatory variables in the model, which might create problems with the regression analysis. Variable with VIF>5 (e.g. marital status) was excluded from the final association. P-values <0.05 were considered statistically significant. Variables with univariate p-value of <0.2 were taken for further multivariable logistic regression. The association was calculated in the overall population and was further categorised as per age group.

Results A total of 27,541 study participants were included in the analysis. Their mean ± SD age (years) was calculated to be 60.06 ± 10.55 (45-59 years age group = 51.39 ± 4.27, ≥60 years age group = 68.89 ± 7.21). Among the study population, BPH was self-reported by 410 males (1.49%), of which 144 (1.04%) were between 45-59 years old and 266 (1.95%) were over the age of 60 years. On univariate analysis, BPH in the overall population (≥45 years) was significantly associated with age group, education status, MPCE quintile, having health insurance, occupation, and physical activity. Among the population aged ≥ 60 years, BPH was significantly associated with education status, place of residence, MPCE quintile, having health insurance, occupation, and BMI categories (Table 1 ). Table 2 depicts the prevalence of different co-morbidities and multi-morbidity in the study population and its association with BPH. Two-thirds (66.06%) of the population had some form of morbidity, while multimorbidity with at least two co-morbidities was prevalent in 34.65%. In the elderly age group, multimorbidity with at least two co-morbidities and at least three co-morbidities was prevalent in 43.95% and 10.32% of the population, respectively. BPH was significantly associated with having hypertension, diabetes, chronic heart disease, dyslipidemia, and thyroid disorders in the study population. It was also associated with multi-morbidity having at least two, three, and four co-morbidities. Among participants aged 45-59 years, BPH was significantly associated with hypertension, chronic heart disease, and thyroid disease. It was also associated with co-morbidity and multimorbidity with at least two co-morbidities . Among participants aged ≥60 years, BPH was significantly associated with having hypertension, diabetes, dyslipidemia, and thyroid disease. It was also associated with having any co-morbidity and multimorbidity. Bivariate and multivariable logistic regression analysis was conducted to explore the association between BPH and multi-morbidity in the study population. Model 1 was adjusted for age, while model 2 was adjusted for all the factors found to be associated with BPH with p-value < 0.2 in Table 1 . Compared to those having no morbidity, the odd of having BPH increased with thr presence of any other morbidity and with an increasing number of co-morbidities included in the multi-morbidity (Table 3 ). Those with at least two co-morbidities, were twice as likely (aOR = 2.19; 95%CI 1.78-2.72), and those with at least four co-morbidities were almost six times as likely (aOR = 5.78; 95%CI 2-16.72) to have BPH as compared to those with no co-morbidities. Similar results were seen when subgroup analysis was conducted among older adults and the elderly. Table 4 depicts the results of the bivariate and multivariable logistic regression analysis to explore the strength of the association of BPH with the presence of any co-morbidity and multi-morbidity in the study population. Among both the 45-59 and >60 years age groups, those with multimorbidity with at least two or more co-morbidities were more than twice as likely to have BPH as compared to those with no morbidity.

Discussion The projected increase in the population of older and elderly adults over the next few decades will be accompanied by an increase in the prevalence of chronic non-communicable diseases as well as benign prostatic hyperplasia [ 12 ]. The commonality of the risk factors behind several of these chronic diseases has heralded the co-occurrence of multiple conditions simultaneously, now described as multi-morbidity. The national representative LASI is a first-of-its-kind study on ageing in India, and the data collected from older and elderly adults allowed the exploration of the association between BPH and multi-morbidity in the Indian population [ 11 ]. The prevalence of BPH in the study population older than 45 years was 1.49%, which is lower compared to the Global Burden of Disease estimates of 3.4% (2.6-4.4%) [ 3 ]. The lower estimation may be due to the self-reported nature of the data on BPH in our study. Multimorbidity was reported by 34.65% of the study population. A meta-analysis of community-based studies found multimorbidity among 31% of the Asian male population [ 13 ]. In the population over the age of 60 years, multimorbidity was reported among 51% globally as compared to 43.95% in our analysis. The difference may be explained by the variations in definitions of multi-morbidity across studies. Multimorbidity is known to have an impact on both physical and mental components of health-related quality of life [ 14 ]. Previous studies have also shown benign prostatic hyperplasia and its symptoms to be associated with poor quality of life [ 15 ]. Our analysis found that those with multi-morbidity were more likely to have BPH, with the odds increasing with the increase in the number of co-morbidities. This pattern of association was significant for both older adults from 45-59 years and the elderly over 60 years of age. BPH was found to be significantly associated with hypertension, diabetes, chronic lung disease, chronic heart disease, dyslipidemia, and thyroid disorders in our analysis. Previous studies from across the world have also found BPH to be significantly associated with several chronic diseases. Peng et al. in Taiwan found that male asthmatics were 1.4 times more likely to have BPH, though the odds decreased with increasing age [ 16 ]. Associations have also been reported between BPH and chronic kidney disease, chronic obstructive pulmonary disease, hypertension, thyroid disorders and metabolic syndrome [ 8 , 17 - 21 ]. Age and multiple co-morbidities are important predictors for requiring pharmacological treatment for alleviation of BPH symptoms [ 22 ]. Treatment for BPH has also been found to increase the risk for cardiovascular disease in patients, which only adds to the burden of co-morbidities [ 23 ]. Therefore, it is evident that the co-existence of BPH and multimorbidity is detrimental to the health and quality of life of patients and is not just an association of chance. Our analysis also found that a higher proportion of those with secondary school education or higher, residing in urban areas, having health insurance, and belonging to richer and richest MPCE quintiles reported having BPH. Similar factors were identified in studies conducted in China [ 24 ], Korea [ 4 ], and the United States [ 25 ]. The association may be explained by better health-seeking behaviour among these sub-populations, coupled with wider access to appropriate screening and diagnostic services for BPH. Smoking and alcohol consumption have been reported to play a protective role in some studies [ 24 , 26 ] but no such association was found in our analysis. A lower proportion of those who engaged in daily physical activity reported BPH, which was corroborated by previous studies [ 24 , 4 ]. With the expected increase in the ageing population, accompanied by an increase in the number of co-morbidities due to the epidemiological transition in India, it is prudent to take steps to improve awareness regarding BPH and its symptoms among the general population. This should be coupled with the provision of affordable and accessible screening and diagnostic services for BPH so that there is an appropriate diagnosis and treatment for the condition. Targeted screening of high-risk groups, i.e. older and elderly adults with multi-morbidity may be considered for this purpose. All of this can be achieved by bringing benign prostatic hyperplasia under the ambit of the National Programme for Prevention and Control of Non-Communicable Diseases (earlier known as the National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases and Stroke) [ 26 ], or the National Programme for Health Care of the Elderly [ 27 ]. This will help prioritise a disease of ageing that has so far not found due prominence, and help improve the health-related quality of life amidst the ever-increasing burden of multimorbidity. To the best of our knowledge, this secondary data analysis, conducted on data from a nationally representative sample is the first to explore to explore the association between BPH and multimorbidity among the Indian male population. However, there are certain limitations. The survey was cross-sectional in nature, it is only possible to establish associations without drawing any causal inference between variables. The outcome variable of benign prostatic hyperplasia is self-reported and not based on any objective diagnostic technique or criteria which may have resulted in misclassification of study participants. This is also the case with several of the reported co-morbidities that have been taken into account for multimorbidity. Since the data was already collected, it was not possible to gather information on health-related quality of life and similar indicators to provide deeper insight into the impact of BPH in those with multimorbidity.

Conclusions Self-reported BPH was found to be strongly associated with multi-morbidity, with the odds of having BPH increasing from twice as likely in individuals with at least two co-morbidities to almost six times as likely in individuals with at least four co-morbidities. The association was found to be stronger in those aged above 60 years. The inclusion of BPH within the framework of a national health programme is a policy decision that is the need of the hour. It would help to improve awareness of the disease and make screening and diagnostics more affordable and accessible. Health technology assessment of high-risk screening strategies for BPH may be conducted among patients with multimorbidity. Further research into the possible pathophysiology and interactions of different chronic diseases in the development of BPH is warranted to better understand the epidemiology of the disease and design therapy to better treat multimorbidity as a whole. Research into the impact on the quality of life of those affected by both BPH and multimorbidity will also help highlight this as a priority problem for the decision-makers.

Introduction Population ageing is expected to be accompanied by an increase in multi-morbidity, i.e. the co-occurrence of multiple chronic conditions simultaneously. Benign prostatic hyperplasia (BPH) is a non-malignant disease prevalent in ageing men. Both BPH and multi-morbidity are known to have a significant impact on quality of life. The objective of this study was to determine the association between BPH and multimorbidity among older adults and the elderly population in India. Methods This is an analytical cross-sectional study involving secondary data from the nationally representative Longitudinal Ageing Study in India (LASI) Wave I 2017-18. Multivariable logistic regression analysis was conducted to study the association between BPH and multimorbidity while accounting for other associated factors. Results Compared to those having no co-morbidities, the odds of having BPH increased with the increasing number of co-morbidities. Those with at least two co-morbidities were twice as likely (aOR=2.19; 95%CI 1.78-2.72), and those with at least four co-morbidities were almost six times as likely (aOR=5.78; 95%CI 2-16.72) to have BPH as compared to those with no co-morbidities. The association was stronger among males >60 years. Conclusion Self-reported benign prostatic hyperplasia was found to be strongly associated with multi-morbidity. The need of the hour is the inclusion of BPH within the framework of a national health programme. Health technology assessment of high-risk screening strategies for BPH may be conducted among patients with multimorbidity. Research into the impact on the quality of life of those affected by both BPH and multimorbidity will help highlight this as a priority problem for decision-makers.

This is a secondary data analysis of the Longitudinal Ageing Study in India (LASI) wave 1, 2017–18 (https://www.iipsindia.ac.in/lasi).

CC BY

no

2024-01-16 23:43:47

Cureus.; 15(12):e50608

oa_package/ff/d0/PMC10788596.tar.gz

PMC10788597

37991155

INTRODUCTION Grapevine ( Vitis vinifera ) has established a deep connection with human culture in its long history spanning over 5000 years (Nascimento et al., 2019 ). Nowadays, grapevine is one of the most widely distributed fruit crops all around the world and comprises many varieties for wine production, table grapes and raisins for human consumption (Brilli et al., 2018 ; Xiang et al., 2021 ). Because of the huge market for these commodities, the grapevine industry is of great importance to economic expansion and increasing income in many countries and areas, with a global market size of over €29 billion (Nascimento et al., 2019 ). Grapevines are susceptible to numerous pathogenic microorganisms, leading to various diseases. Downy mildew disease, caused by the obligately biotrophic peronosporomycete Plasmopara viticola , is one of the major threats in vineyards and causes huge losses in yield worldwide, especially in viticulture areas with relatively warm and humid climate conditions (Blasi et al., 2011 ; Yu et al., 2012 ). P. viticola was originally endemic on wild Vitis species of North America and was introduced into the Bordeaux area in 1871, probably with the acquisition of American grapevine rootstocks used as breeding stock for phylloxera resistance (Gessler et al., 2011 ; Liu, Weng, et al., 2019 ). Subsequently, P. viticola was detected in the Bordeaux area in 1878 and rapidly spread across Europe, leading to a severe pandemic throughout the continent in the following decade (Boso & Kassemeyer, 2008 ; Gessler et al., 2011 ). In the field, P. viticola can infect all green tissues of grapevine, including leaves, inflorescences, fruit clusters, and young bunches, reducing the assimilation rate through a reduction in green leaf area and an influence on gas exchange in other green leaf tissues, resulting in significant losses in grapevine productivity and quality (Blasi et al., 2011 ; Moriondo et al., 2005 ; Yu et al., 2012 ). Typically, diseased leaves display yellow or reddish‐brown lesions on the upper surface, corresponding to white pathogen growth on the lower surface. Sometimes lesions are oily, somewhat angular and are located between the veins. The leaf lesions become brown and die with age (Musetti et al., 2005 ). Because of grapevine's ability to be transformed and micropropagated via somatic embryogenesis, as well as its relatively small genome size relative to other perennials, this species has become a potential model organism for fruit crops in scientific research (Velasco et al., 2007 ). Additionally, P. viticola is considered a good candidate for the study of host adaptation of biotrophic pathogens (Dussert et al., 2016 ). In the past decade, hot issues of grapevine downy mildew and its cause, P. viticola , such as environmentally friendly control measures, pathogenesis and disease resistance, have received increasing attention and a great deal of progress has been made. In the current paper, we summarize and discuss the advances in understanding P. viticola from multiple aspects, including its infection cycle, effector biology and control measures.

CONCLUSION P. viticola has become a serious threat to the viticulture globally. A comprehensive insight into the infection strategies and conditions (such as temperature and humidity), pathogenicity mechanism and plant defence response contributes to establish efficient disease management strategies against downy mildew. Decoding the genome of P. viticola helps researchers to identify and characterize key pathogenicity‐related genes that potentially serve as chemical fungicide targets. Revealing the pathogen–host interactive regulation also facilitates the matching of avirulence and resistance genes, which provides important genetic resources for disease resistance breeding. Identification of plant‐derived chemical compounds also provides large numbers of valuable and attractive candidates for the development of environmentally friendly fungicides. Even though great progress in downy mildew control has been made, there is still work to be done to overcome obstacles in plant breeding and disease management. For example, the high risk of P. viticola breaking R gene‐mediated resistance and the sustainability of resistant grapevine varieties makes it a challenging project to incorporate multiple resistance genes into susceptible species to extend the resistance duration without the loss of desirable phenotypic traits in grapevine breeding. Moreover, appropriate formulations are urgently required to maintain the duration and efficiency of plant‐derived compounds against P. viticola .

Abstract Plasmopara viticola is geographically widespread in grapevine‐growing regions. Grapevine downy mildew disease, caused by this biotrophic pathogen, leads to considerable yield losses in viticulture annually. Because of the great significance of grapevine production and wine quality, research on this disease has been widely performed since its emergence in the 19th century. Here, we review and discuss recent understanding of this pathogen from multiple aspects, including its infection cycle, disease symptoms, genome decoding, effector biology, and management and control strategies. We highlight the identification and characterization of effector proteins with their biological roles in host–pathogen interaction, with a focus on sustainable control methods against P. viticola , especially the use of biocontrol agents and environmentally friendly compounds. A review and discussion of recent understanding of Plasmopara viticola from multiple aspects, including infection cycle, disease symptoms, genome decoding, effector biology, and management and control strategies. Peng , J. , Wang , X. , Wang , H. , Li , X. , Zhang , Q. , Wang , M. et al. ( 2024 ) Advances in understanding grapevine downy mildew: From pathogen infection to disease management . Molecular Plant Pathology , 25 , e13401 . Available from: 10.1111/mpp.13401

INFECTION CYCLE The life cycle of P. viticola comprises an asexual multiplication phase that occurs during the plant vegetative period and a sexual phase that ensures the survival of the pathogen over winter (Díez‐Navajas et al., 2007 ). The primary sources of inoculum in spring derive from overwintering sexual oospores (Jürges et al., 2009 ; Vercesi et al., 1999 ). However, a rapid sequence of asexual propagation by sporangia under optimal conditions, such as high humidity and warm temperatures, causes severe epidemics and renders P. viticola a serious threat to viticulture (Jürges et al., 2009 ). The extremely efficient cycle of asexual propagation is responsible for the rapid spread of P. viticola worldwide (Islam et al., 2011 ). During the growing season, the asexually formed, lemon‐shaped sporangia release four to eight flagellate zoospores that swarm within the water film on the lower surface of the leaf (Jürges et al., 2009 ; Unger et al., 2007 ). On susceptible hosts, the motile zoospores are specially targeted to the stomata, where they shed their flagella and encyst (Jürges et al., 2009 ; Liu et al., 2015 ). The phenomenon of zoospores locating to the stomata is mediated by host cues (Islam et al., 2011 ; Kiefer et al., 2002 ). The encysted zoospores generate germ tubes that reach into the substomatal cavity, where they dilate into an infection vesicle (Kiefer et al., 2002 ; Liu et al., 2015 ; Yu et al., 2012 ). From the substomatal vesicle, a primary hypha emerges and develops into a mycelium that spreads inside the leaf tissue, extending mainly into the intercellular spaces of the spongy parenchyma and forming haustoria that penetrate the host cell wall (Jürges et al., 2009 ; Kiefer et al., 2002 ). Next, masses of hyaline sporangia are produced from sporangiophores at the lower leaf surface and are released and spread via wind currents or raindrops (Kortekamp, 2006 ). These sporangia start secondary infections as soon as weather conditions are favourable for their development and if protection is omitted (Kortekamp, 2006 ). At the end of autumn, numerous oospores, which represent the resting spores of P. viticola , form within fallen leaves and berries, allowing P. viticola to overwinter (Kortekamp, 2006 ). The life cycle of P. viticola is shown in Figure 1 . PATHOGENICITY GENES IN P. VITICOLA The assembled genomes of several P. viticola isolates, including PvitFEM01 (NCBI SAMN06627059; Brilli et al., 2018 ), INRA‐PV221 (NCBI SAMN05415085; Dussert et al., 2019 ) and JL‐7‐2 (NCBI SAMN06231250; Yin, An, et al., 2017 ), are available in the National Center for Biotechnology Information (NCBI) database. The genome sizes of these isolates are 83.54, 92.94 and 101.3 Mb, containing 38,298, 15,960 and 17,014 protein‐coding genes, respectively. The differences may be caused by the large number of repetitive elements in their genomes, which could be the co‐evolutionary result of P. viticola and grapevine originating from different geographic regions. With respect to pathogenesis, only a couple of pathogenicity‐related genes, such as PvCHS1 and PvCHS2 (Werner et al., 2002 ), have been characterized, even though thousands of protein‐coding genes have been predicted (Dussert et al., 2019 ; Yin, An, et al., 2017 ). Therefore, the pathogenic mechanism of major P. viticola genes in susceptible genotypes is still poorly understood, which is partially attributed to the strictly biotrophic lifestyle of P. viticola , which makes this pathogen difficult to study in the laboratory (Chen et al., 2020 ; Liu, Lan, et al., 2018 ; Liu, Zhang, et al., 2018 ; Nascimento et al., 2019 ). Molecular research on the pathogen has therefore mainly focused on identifying secreted efforts during infection and deciphering the underlying mechanisms of grapevine– P. viticola interactions. EFFECTOR BIOLOGY OF P. VITICOLA Effectors are a large group of secreted pathogenicity‐related factors that can manipulate plant defence responses and modulate host cellular process to promote pathogen colonization in host plants (Lo Presti & Kahmann, 2017 ). Many effectors have been inferred to enter plant cells based on the physical interaction with host R proteins containing the nucleotide‐binding sites and leucine‐rich repeats (NB‐LRR) or the physiological effects, including activating programmed cell death or suppressing the activities of different cell death inducers when expressed intracellularly (Kale & Tyler, 2011 ). Effector proteins are classified into two groups based on their final destinations: cytoplasmic and apoplastic. The cytoplasmic effector proteins locate to different intracellular compartments and play various roles during pathogen host–interactions. The apoplastic effectors are well known to inhibit the activities of host‐secreted hydrolases or interrupt the functions of host receptors (Ma et al., 2017 ; Oh et al., 2009 ; Tian et al., 2004 ). Cytoplasmic effectors Cytoplasmic effectors belonging to different types have been identified in P. viticola ; the most notable effectors are typically characterized as RxLR and CRN (crinkling and necrosis‐inducing or Crinkler) proteins (Jiang & Tyler, 2012 ; Yin, An, et al., 2017 ). Functional characterization of the two kinds of proteins has been widely performed in P. viticola . RxLR proteins RxLR proteins are defined by a conserved N‐terminal motif similar in sequence, position and function to a host translocation signal RXLX(E/D/Q) present in the malaria parasite Plasmodium falciparum that enables delivery of effector proteins into human erythrocytes (Hiller et al., 2004 ; Schornack et al., 2010 ). Usually, the RxLR protein has an N‐terminal signal peptide, followed by an RxLR motif or its variant, and an EER motif. In P. viticola , dozens of RxLR proteins have been functionally characterized in different isolates, including JL‐7‐2, ZJ‐1‐1 and CSIRO‐L‐2 (Yin et al., 2015 ), YL (Yin et al., 2019 ), PvitFEM01 (Brilli et al., 2018 ) and INRA‐PV221 (Dussert et al., 2016 ). Comparative analyses revealed that the number of RxLR proteins in P. viticola (Yin, An, et al., 2017 ), as well as Hyaloperonospora arabidopsidis (Baxter et al., 2010 ), Plasmopara halstedii (Sharma et al., 2015 ) and Pseudoperonospora cubensis (Savory et al., 2012 ), is less than in other plant‐pathogenic oomycetes, such as Phytophthora infestans (Haas et al., 2009 ), Phytophthora ramorum and Phytophthora sojae (Jiang et al., 2008 ; Tyler et al., 2006 ). The difference in RxLR protein number among these pathogens may be associated with their functional redundancy. Additionally, RxLR proteins appear to be absent from necrotrophic pathogens, such as Pythium ultimum (Lévesque et al., 2010 ), Pythium insidiosum (Adhikari et al., 2013 ; Krajaejun et al., 2011 ) and Saprolegnia parasitica (Jiang et al., 2013 ). The proliferation indicates RxLR genes have undergone a dramatic expansion in the Phytophthora and downy mildew lineage, which is thought to be a crucial innovation during the evolution of the biotrophic ancestor of Phytophthora spp. and the downy mildew lineage (Anderson et al., 2015 ). A high percentage of predicted RxLR proteins in P. viticola shows low similarity to RxLR proteins identified from other oomycetes, such as H. arabidopsidis , P. infestans and P. sojae , implying that RxLR proteins in P. viticola may have become more specific as a result of strong selection pressure during the evolution of P. viticola (Yin, Liu, et al., 2017 ). Functional analyses have also uncovered some common or specific characters of RxLR proteins in P. viticola . For example, suppression of plant immunity is the major activity of the RxLR secretome identified in P. viticola (Table 1 ), a feature shared by the RxLR secretome of H. arabidopsidis (Fabro et al., 2011 ; Pel et al., 2014 ). This is reasonable as the biotrophic oomycetes, including P. viticola , may have evolved to generate a relatively high percentage of RxLR effectors to suppress elicitin‐triggered cell death, keeping the host tissue alive for sustainable access to nutrients (Xiang et al., 2016 ). This inference was further exemplified by the inhibitory regulation among RxLR effectors shown in Figure 2 . Moreover, the elicitor activity of RxLR proteins is associated with grapevine species, which can be supported by the fact that protein RxLR_PVITv1008311 without a signal peptide from P. viticola isolate PvitFEM01 elicits a cell death response in resistant Vitis riparia but not in susceptible grapevine V. vinifera (Brilli et al., 2018 ). The different responses may result from the differences in the recognition of P. viticola effectors between the two grapevines. Although a number of RxLR effectors have been identified, the regulatory mechanisms between RxLR effectors with their interactive targets from plant cells have only been investigated for a couple of effectors. RxLR effectors PvRxLR111 with PvRxLR50253 target and stabilize grapevine proteins VvWRKY40 with VpBPA1 to suppress plant immunity through decreasing H 2 O 2 accumulation and promote pathogen infection (Ma et al., 2021 ; Yin et al., 2022 ). Another RxLR protein PvRxLR131 targets V. vinifera BRI1 kinase inhibitor 1 (VvBKI1) in the plasma membrane as a strategy for promoting infection (Lan et al., 2019 ). However, it is challenging to determine whether the RxLR proteins have virulence functions in susceptible grape cultivars and characterize their correlations with correspondent resistance (R) proteins, even though the gene‐for‐gene relationship between an avirulent RxLR gene with its cognate resistance (R) gene has been well described in other pathogenic oomycetes, such as P. sojae Avr1a and Avr3a (Qutob et al., 2009 ), Avr1b‐1 and Avr1k/Rps1k (Song et al., 2013 ), Avr3b (Dong et al., 2011 ), Avr3c (Dong et al., 2009 ), Avr4/Rps4 (Dou et al., 2010 ), Avr6/Rps6 (Dou et al., 2010 ), H. arabidopsidis ATR13/RPP13 (Allen et al., 2004 ), ATR1 NdWsB /RPP1 (Rehmany et al., 2005 ), ATR39/RPP39 (Goritschnig et al., 2012 ) and P. infestans Avr1/R1 (Du et al., 2015 ), Avr2/R2 (Gilroy et al., 2011 ), Avr4/R4 (van Poppel et al., 2008 ), Avr‐blb1/Rpi‐blb1 (Vleeshouwers et al., 2008 ) and AVRblb2/Rpi‐blb2 (Oh et al., 2009 ). CRN proteins CRN proteins are small, secreted proteins first identified in P. infestans and described as causing a crinkling and necrosis phenotype when ectopically expressed in planta (Torto et al., 2003 ; Xiang et al., 2021 ). CRN proteins have a conserved N‐terminal LXLFLAK motif and a conserved HVLVXXP motif followed by variable carboxyl (C)‐terminal sequences (Haas et al., 2009 ; Xiang et al., 2021 ). CRN proteins are conserved and ubiquitously present in all sequenced plant‐pathogenic oomycete species, including Saprolegniales (Gaulin et al., 2008 ; Schornack et al., 2010 ), Pythiales (Cheung et al., 2008 ; Lévesque et al., 2010 ), Albuginales (Kemen et al., 2011 ; Links et al., 2011 ) and Peronosporales (Mafurah et al., 2015 ; Rajput et al., 2015 ), in contrast to the RxLR effectors that have only been identified in Peronosporales and Albuginales (Yin et al., 2015 ). The difference suggests that the CRN protein family may have arisen before the emergence of haustoria and disseminated into other microorganisms by horizontal gene transfer, whereas the RxLR effectors emerged and diversified in accordance with the evolution of haustoria (Schornack et al., 2010 ; Sun et al., 2011 ; Yin et al., 2015 ). Recent data have revealed that CRN proteins are present in other pathogenic and free‐living eukaryotes, including Batrachochytrium dendrobatidis (Sun et al., 2011 ), Batrachochytrium salamandrivorans (Farrer et al., 2017 ), Rhizophagus irregularis (Voß et al., 2018 ), members of Viridiplantae and amoebozoans (Zhang et al., 2016 ), suggesting that CRN proteins may be more ubiquitously distributed than predicted. However, CRNs are absent in animal‐pathogenic oomycetes, suggesting that the evolution and occurrence of this kind of protein may be associated with virulence and adaption on susceptible plants (Gaulin et al., 2018 ; Voß et al., 2018 ). In terms of P. viticola , an array of CRN‐like genes have been cloned and characterized from isolates JL‐7‐2 (Yin, An, et al., 2017 ), PvitFEM01 (Brilli et al., 2018 ) and YL (Xiang et al., 2021 ). Sequence alignments revealed that 27 PvCRN genes from isolate YL share high similarities in nucleotides with their orthologues from another three P. viticola isolates, JL‐7‐2, INRA‐PV221 and PVitFEM01. The high level of intraspecific nucleotide polymorphism among the CRN ‐ like genes from these four P. viticola isolates is considered to be a reflection of pathogen evolution adaptation to different grapevine genotypes in distinct geographic areas (Xiang et al., 2021 ). Moreover, it was found that gene duplication ( PvCRN27 and PvCRN29 , PvCRN10 and PvCRN11 ) and fragment recombination of CRN s occurred during adaptive evolution in P. viticola , which is analogous to the CRN genes in P. sojae (Shen et al., 2013 ) and P. infestans (Haas et al., 2009 ). Gene recombination was mainly generated with three different patterns. In the first pattern, CRN genes contain a highly conserved N‐terminal sequence, but differ in the C‐terminal sequence; these genes include PvCRN31 and PvCRN11 , PvCRN21 and PvCRN22 , PvCRN12 , PvCRN35 and PvCRN17 . The second recombination pattern is that CRN genes have a highly conserved C‐terminal sequence but display diversity in the N‐terminal coding sequence, such as PvCRN1 , PvCRN4 and PvCRN30 . Finally, a novel CRN gene is composed of distinct fragments from at least two other PvCRN genes, which can be evidenced by the genes PvCRN15 and PvCRN16 (Xiang et al., 2021 ). To some extent, this phenomenon may explain the CRN family expansion and sequence divergence of the three oomycetes when compared to other fungi and oomycetes. Although the first CRN protein was characterized as a crinkling and necrosis‐inducing factor on expression in planta, a characteristic of plant innate immunity (Haas et al., 2009 ; Torto et al., 2003 ), an array of studies has revealed that this is not a common feature for CRN proteins or their C‐terminal domain, and one set of CRN proteins even displays the opposite function. For example, PsCRN63 (Liu, Ye, et al., 2011 ), PcCRN4 (Mafurah et al., 2015 ), PiCRN8 (van Damme et al., 2012 ) and PcCRN83_152 (Amaro et al., 2018 ) induce cell death, but some other CRN effectors, such as VmEP1 (Li et al., 2015 ), PsCRN115 (Liu, Ye, et al., 2011 ), PsCRN70 (Rajput et al., 2014 ) and PsCRN161 (Rajput et al., 2015 ), suppress cell death triggered by other elicitins, indicating that CRN proteins possess diverse functions beyond cell death induction (Amaro et al., 2018 ; Stam et al., 2013 ; Voß et al., 2018 ). In P. viticola , most characterized PvCRN proteins suppress or attenuate cell death triggered by other elicitins when transiently expressed in Nicotiana benthamiana (Table 2 ), which is also inconsistent with the initially documented roles of CRN proteins. Additionally, although many PvCRN genes have been identified in P. viticola , the molecular functions have been explained for only a couple of PvCRN genes. For example, the CRN protein PvCRN17 competed with VCIA1 to bind with VAE7L1, demolishing the cytosolic iron–sulphur (Fe‐S) cluster assembly (CIA) Fe‐S cluster transfer complex to suppress Fe‐S protein‐mediated defence responses (Figure 2 ). In future, the most important and urgent task is to identify the host targets of PvCRN effectors and investigate their molecular functions, which drives the identification of unknown components in plant immunity and metabolism, as well as promoting biotechnology innovations. YxSL [ RK ] proteins Besides RxLR and CRN motifs, YxSL[RK] is another conserved motif that has been identified in the secreted and non‐secreted proteins of oomycete species including P. ultimum (Lévesque et al., 2010 ), P. infestans and P. sojae (Adhikari et al., 2013 ), and S. parasitica (Jiang et al., 2013 ). The YxSL[RK] motif shares similarity in sequence and position with the canonical RxLR motif and appears to be a signature for a novel family of secreted proteins that function as effectors (Adhikari et al., 2013 ; Lévesque et al., 2010 ). However, whether the YxSL[RK] motif defines a host‐translocation domain as noted for RxLR effectors remains to be determined (Lévesque et al., 2010 ). P. viticola contains a relatively high number (25) of putative secreted YxSLK[RK] proteins compared to the other biotrophic oomycetes P. halstedii (16), H. arabidopsidis (14) and Albugo laibachii (9), but a much lower number than Phytophthora species, including P. infestans (43), P. capsici (45) and P. sojae (61) (Brilli et al., 2018 ). However, the molecular roles and underlying mechanisms of this kind of protein have not yet been revealed. Apoplastic effectors Oomycetes not only secrete large numbers of typical RxLR and CRN effectors targeted to the host cytoplasm to alter host physiology and facilitate pathogen colonization, they also release an extensive range of apoplastic effectors that interact with extracellular targets and surface receptors to facilitate infection (Jiang & Tyler, 2012 ; Yin et al., 2015 ). The genome of sequenced oomycetes has revealed large complex families of apoplastic effectors, including secreted hydrolytic enzymes such as lyases, proteases, lipases and glycosylases that probably degrade plant tissue, enzyme inhibitors to protect against host defence enzymes, necrotizing toxins such as necrosis‐ and ethylene‐inducing peptide‐like proteins (NLPs), Phytophthora cactorum factors and secreted cysteine‐rich proteins, that are implicated in pathogenesis during symptom development (Haas et al., 2009 ; Jiang & Tyler, 2012 ; Tyler et al., 2006 ). The first characterized member of NLP family, the Nep1 protein, was isolated from culture filtrates of Fusarium oxysporum (Bailey, 1995 ). Experimental tests demonstrated that Nep1 was capable of inducing ethylene biosynthesis as well as necrosis in a wide variety of Dicotyledoneae but not in Monocotyledoneae (Bailey, 1995 ). Since then, more NLPs have been identified in various phytopathogenic microorganisms, including fungi, bacteria and oomycetes (Xiang et al., 2022 ). According to the induced phenotypes, NLPs can be classified into two groups: the cytotoxic NLPs, which are able to permeabilize the cellular membrane of dicotyledonous plants and cause necrosis as well as a myriad of other defence responses (Seidl & Van den Ackerveken, 2019 ), or the noncytotoxic NLPs, with the ability to activate cell death‐independent immunity (Seidl & Van den Ackerveken, 2019 ; Xiang et al., 2022 ). It was assumed that obligately biotrophic pathogens generally contained the noncytotoxic NLPs, as the biotrophs rely on living plant tissues for their growth and reproduction (Schumacher et al., 2020 ; Seidl & Van den Ackerveken, 2019 ). However, functional analyses of this kind of protein from obligate biotrophs were only performed on a couple of NLPs in P. viticola (Askani et al., 2021 ; Schumacher et al., 2020 ; Xiang et al., 2022 ) and H. arabidopsidis (Cabral et al., 2012 ). For example, a few NLP genes have been identified in P. viticola and most were highly expressed during the early stages of infection, suggesting that these genes may play major roles during pathogen penetration or initial colonization inside host tissues (Askani et al., 2021 ; Schumacher et al., 2020 ; Xiang et al., 2022 ). However, whether PvNLP genes contribute to virulence for P. viticola is still unknown. Several tested NLPs (PvNLP1–8) are known to be unable to cause necrosis in N. benthamiana (Askani et al., 2021 ; Schumacher et al., 2020 ), which is in line with the noncytotoxic effect of tested NLPs of H. arabidopsidis (Cabral et al., 2012 ). Conversely, Xiang et al. ( 2022 ) recently reported that PvNLP7 was able to cause necrosis and enhance P. capsici resistance in N. benthamiana with H. arabidopsidis resistance in Arabidopsis . Further research is necessary to resolve these controversial issues. Additionally, even though the major NLPs identified in P. viticola displayed noncytotoxic phenotypes, some of the NLPs suppressed plant growth and enhanced plant resistance against downy mildew, which implies that these NLPs may play roles in different ways independent of necrosis. RNA Apart from effector proteins, bidirectional cross‐species small RNA (sRNA)‐mediated gene regulation during the compatible interaction has also been revealed in P. viticola . The sRNAs generated by P. viticola trigger the cleavage of grapevine genes and, vice versa, the sRNAs processed from grapevine transcripts target P. viticola messenger RNAs (Brilli et al., 2018 ). The shuffling of low molecular weight RNA between P. viticola with its host implies that bidirectional communication of sRNAs is an important invasion or resistance strategy adopted by both organisms during the infection. However, the bidirectional exchange pathway and mechanism of sRNAs have not yet been revealed. MANAGEMENT AND CONTROL STRATEGIES In the history of grapevine downy mildew disease management, an array of commodities aimed at killing the pathogen directly or activating induced system resistance indirectly has been developed and widely used in the field. Based on their composition and physicochemical properties, these commodities can be classified into two groups: chemical fungicides and biological control agents. Alternative measures aimed to reduce the use of chemical fungicides but retain good control over the causal agent, including breeding disease‐resistant grapevine varieties and the use of resistance inducers, have received more attention during recent years. Here, we briefly summarize the main developments in these management strategies and discuss their advantages and disadvantages in practical usage. Chemical fungicides In organic viticulture, chemical control is the most effective method currently used to control grapevine downy mildew (Battiston et al., 2018 ; Selim, 2013 ). In the history of grapevine downy mildew control, the copper sulphate‐based Bordeaux mixture represents the first milestone and it is considered to be the first oomycete fungicide obtained during the development history of phytomedicine (Millardet, 1885 ; Selim, 2013 ). Afterwards, a series of copper or sulphate compounds, including Burgundy mixture (Masson, 1887 ), kurtakol (Lustner, 1922 ), copper salt of oxyquinoline (Meyer, 1932 ) and copper oxide (Osterwalder, 1939 ), were invented and applied to control P. viticola . Thanks to the development of new stable compounds, reduced costs and decreased phytotoxicity, many acupric fungicides, including captan, methiram, maneb, mancozeb, propineb, captafol, folpet and dichlofluanid, have been developed and their use has become prevalent among grapevine growers (Gessler et al., 2011 ). After the 1970s, systemic fungicides, including cymoxanil (Serres & Carraro, 1976 ), acylalanine metalaxyl (Vial et al., 1978 ; Wicks, 1980 ), aluminium ethylphosphite or fosetyl‐Al (Boubals et al., 1979 ), phenylamide oxadixyl (Gisi et al., 1983 ), dimethomorph (Wicks & Hall, 1990 ) and azoxystrobin (Bugaret et al., 1998 ), were greeted with enthusiasm in the market, partly because of their resistance to rainfall wash‐off and their outstanding curative effects against established infections (Boubals & Lafon, 1981 ; Gessler et al., 2011 ). In the past two decades, many new active ingredients, including famoxadone (Andrieu et al., 2000 ), benthiavalicarb‐isopropyl (Reuveni, 2003 ), fluopicolide (Gouot, 2006 ) and mandipropamid (Lamberth et al., 2006 ), have been developed and applied because of their high efficiency against downy mildew and favourable toxicological features (Figure 3 ). Because of health and environmental concerns, as well as the detrimental effect on wine quality of long‐term use of copper‐based fungicides, the usage of cupric fungicides is currently restricted by European Union Regulation 473/2002 and copper‐based formulations used in organic farming are limited to 6 kg/ha per year in most European countries (Garde‐Cerdán et al., 2017 ; Kortekamp, 2006 ). The development of novel copper‐based formulations appears to be a promising approach to enhance control efficiency and minimize the side effects caused by copper (Battiston et al., 2019 ; La Torre et al., 2010 ). The advent of nanotechnology provides an innovative perspective to develop pesticides that share slow‐release systems to optimize their distribution and persistence, therefore enhancing the protective effect and control efficiency. For example, Cu(II) compounds formulated with synthetic nanostructured hydroxyapatite have resulted in reduced disease severity and higher efficacy even under rain‐washed conditions (Battiston et al., 2018 , 2019 ). Although promising results were achieved by the engineered nanoparticles, it is necessary to evaluate the cytotoxicity and genotoxicity of such particles within the plant tissues, as some reports have claimed adverse effects of these nanoparticles on the growth and development of tested plants (Lee et al., 2008 ; Lin & Xing, 2008 ). Besides new formulations, the development of alternative strategies to reduce the use of classic chemical fungicides for grapevine downy mildew protection also seems to be an urgent and promising task. Beneficial microorganisms Plant resistance can be triggered or strengthened after the recognition of pathogenic or beneficial microbes through pathogen‐ or microbe‐associated molecular patterns by host‐specific receptors (Lakkis et al., 2019 ). Several beneficial microorganisms, including Lysobacter capsici (Puopolo et al., 2013 ; Segarra et al., 2015 ), Bacillus subtilis (Li et al., 2019 ; Shen et al., 2016 ), Trichoderma harzianum (Perazzolli et al., 2012 ; Roatti et al., 2013 ), Pseudomonas fluorescens (Lakkis et al., 2019 ; Shoresh et al., 2010 ) and Fusarium proliferatum (Bakshi et al., 2001 ; Perazzolli et al., 2012 ), have been developed as attractive candidates in the biological control of P. viticola (Figure 3 ). Among them, B. subtilis is one of the most commercialized biological control agents (Li et al., 2019 ). These biocontrol agents mediate plant resistance by producing various bioactive compounds, such as fengycin and surfactin (Li et al., 2019 ), khatmiamycin (Abdalla et al., 2011 ), staurosporine (Islam et al., 2011 ), banchromene (Tatong et al., 2014 ), cryptosporiopsin A, hydroxypropan‐2′,3′‐diol orsellinate and cyclic pentapeptide (Talontsi et al., 2012 ), oligomycins and pamamycin homologues (Dame et al., 2016 ), to inhibit P. viticola directly or activate induced systemic resistance, which is associated with priming phytohormone (salicylic acid, 1‐aminocyclopropane‐1‐carboxylic acid, abscisic acid) production, stilbenic phytoalexin and callose accumulation, and expression of defence‐related genes (Lakkis et al., 2019 ; Perazzolli et al., 2012 ; Roatti et al., 2013 ). Although many biocontrol microorganisms display a control effect against downy mildew under experimental conditions, the use of these biocontrol agents in agriculture is still far from widespread because of the unmanageable and changeable abiotic stresses (Roatti et al., 2013 ). Various factors, including environmental factors, production cost, the time period that microorganisms can be stored in packaging, their survival and activity on the plant and in soils, can comprehensively impact the control efficiency (Perazzolli et al., 2012 ; Roatti et al., 2013 ; Segarra et al., 2015 ). A growing amount of research has revealed that appropriate formulation helps to enhance the efficiency of biocontrol agents. For example, application of L. capsici AZ78 in combination with a low dose of a copper‐based fungicide leads to higher control efficiency against grapevine downy mildew (Puopolo et al., 2013 ). Use of L. capsici AZ78 together with corn steep liquor, lignosulfonate and polyethylene glycol in the formulation improves the survival of L. capsici AZ78 cells by one order of magnitude and ensures a high level of protective efficacy (Segarra et al., 2015 ). T. harzianum T39‐induced resistance is attenuated by the combined abiotic stress of heat and drought (Roatti et al., 2013 ), therefore the optimized formulation is a crucial step in biopesticide development and is an efficient way to maintain persistence in terms of biological control under field conditions. Pathogen‐resistant grapevine breeding Grapevine distributed in different geographic areas exhibited susceptibility and resistance against P. viticola at various levels. Generally, the level of grapevine resistance to P. viticola is divided into five classes: immune, extremely resistant, resistant, partly resistant and susceptible (Yu et al., 2012 ). All the traditional cultivars of V. vinifera , which is the most widely cultivated grapevine species and suitable for wine and table grape production, are susceptible to downy mildew, although variations of susceptibility are observed among different cultivars or even between clones of the same variety (Blanc et al., 2012 ; Blasi et al., 2011 ; Boso et al., 2014 ). In contrast, the North American and Asian Vitis species belonging to the Euvitis subgenus or Muscadinia subgenus exhibit variable levels of resistance to P. viticola , ranging from moderate resistance, such as V. rupestris , to high resistance, including V. rubra , V. candicans , V. amurensis , V. riparia , V. cinerea and Muscadinia rotundifolia (Blasi et al., 2011 ; Gessler et al., 2011 ). In nature, control of downy mildew on these traditional grapevine varieties generally relies on the massive use of pesticides (Peressotti et al., 2010 ). However, routine use of fungicides is becoming increasingly restrictive because of their heavy cost to grapevine production, high risk to human health and adverse impacts on environment (Blanc et al., 2012 ; Peressotti et al., 2010 ). Moreover, a growing number of fungicide‐resistant P. viticola strains have been detected in the vineyard, reducing the efficiency of fungicide application (Blanc et al., 2012 ). Therefore, the search for alternative methods to control the disease is important for viticulture (Peressotti et al., 2010 ). In this context, plant breeding for disease resistance based on the introgression of resistance traits from ancestral species into domesticated varieties appears to be an attractive and environmentally friendly way to control grapevine downy mildew (Blanc et al., 2012 ; Vezzulli et al., 2019 ). During the last 20 years, research on the genetic basis of resistance varieties has seen great progress. For example, 31 quantitative trait loci associated with downy mildew resistance have been described in grapevine with different genetic backgrounds (Koledenkova et al., 2022 ; VIVC, 2023 ). Additionally, a set of resistance genes ( R genes) belonging to the nucleotide‐binding site/leucine‐rich repeat (NBS‐LRR) family, such as VaRGA1 (Li et al., 2017 ; Tian et al., 2019 ), RGA5 (Fan et al., 2015 ), VqCN (Zhang et al., 2018 ), VpRPW8s (Lai et al., 2018 ) and a leucine‐rich repeat receptor‐like kinase (LRR‐RLK) family member VaHAESA (Liu, Zhang, et al., 2018 ), have been functionally deciphered. Some R genes, such as MrRPV1 , have been introduced into susceptible grapevine for P. viticola resistance (Feechan et al., 2013 ). Besides the typical R proteins, other resistance‐related proteins, such as transcription factors VvWRKY2 (Mzid et al., 2007 ), VvWRKY11 (Liu, Yang, et al., 2011 ), VvWRKY1 (Marchive et al., 2013 ), MrWRKY30 (Jiang et al., 2015 ), VvWRKY33 (Merz et al., 2015 ), MrCBF2 (Wu et al., 2017 ), pathogenesis‐related proteins VpPR10.1 (Ma et al., 2018 ; Su et al., 2018 ), VpPR10.2 (He et al., 2013 ), VaTLP (He et al., 2017 ), aldehyde dehydrogenases VpALDH2B4 (Wen et al., 2012 ), glycoproteins (Guillier et al., 2015 ) and biomarkers (Batovska et al., 2009 ), are also involved in downy mildew resistance (Figure 4 ). However, introgression of these resistance factors into the traditional susceptible cultivars is a difficult project. On the one hand, hybridization between resistant and susceptible species is hampered by their difference in chromosome number. On the other hand, introgression of resistance genes to susceptible species leads to linkage drag of undesired agronomic traits from resistant species that may remain even after successive cycles of backcrossing (Blanc et al., 2012 ). Moreover, limited understanding of the resistance‐breaking isolates also affects the deployment of resistant varieties in nature. It is therefore challenging work to incorporate resistance durability and maintain important agronomic traits in grapevine breeding (Batovska et al., 2009 ; Peressotti et al., 2010 ). Spray‐induced gene silencing of pathogen genes The crosstalk of sRNA between plant hosts with their fungal and oomycete pathogens has been investigated in some pathosystems (Brilli et al., 2018 ; Wang et al., 2016 ), providing new insight into disease management in crops. For example, external application of double‐stranded (ds)RNA has been developed as a promising tool to protect plants against various pathogens, such as Fusarium graminearum (Koch et al., 2016 ), Sclerotinia sclerotiorum (McLoughlin et al., 2018 ) and Botrytis cinerea (Nerva et al., 2020 ). In grapevine, the application of dsRNA PvDCL1/2 displayed both protective and curative properties against P. viticola (Haile et al., 2021 ). These tests provide promising tools by which RNA‐based resistant plants or agrochemical alternatives for plant disease management can be developed. However, the mechanism behind the uptake and transport of externally applied dsRNA into host plants remains unclear. Natural compounds for disease control Except for the aforementioned measures adopted to control grapevine downy mildew disease, various types of nature or synthetically produced compounds, including carbohydrate polymers, lipids and (glyco)peptides, that exhibit toxic or prohibitive effects on P. viticola infection have been developed and applied alone or with other copper‐based formulations to control downy mildew in grapevine (Garde‐Cerdán et al., 2017 ). Here, we review the inhibitory effects and functional mechanisms of previously characterized compounds. Laminarin Laminarin, a natural linear β‐1,3‐glucan oligosaccharide extracted from the brown alga Laminaria digitata , deprived of antimicrobial activity, elicits defence in tobacco (Klarzynski et al., 2000 ), grapevine (Aziz et al., 2003 ; Gauthier et al., 2014 ), Arabidopsis (Ménard et al., 2004 ), alfalfa (Cardinale et al., 2000 ), rice (Inui et al., 1997 ) and bean (Mithöfer et al., 1999 ). Defence reactions elicited by laminarin in grapevine cells include calcium influx, alkalinization of the extracellular medium, oxidative burst, activation of mitogen‐activated protein kinases, expression of pathogenesis‐related genes, increase in chitinase and β‐1,3‐glucanase activities, and production of phytoalexins (resveratrol and ε‐viniferin) (Aziz et al., 2003 ; Gauthier et al., 2014 ). Although laminarin is able to elicit defence responses in grapevine, protection against P. viticola is unsatisfactory, which could result from the low penetration rate of hydrophilic compounds into the leaf, and laminarin acts solely as an elicitor of plant defence rather than as a toxic compound against oomycetes (Paris et al., 2019 ). PS3 PS3, a sulphated derivative of laminarin, is considered to be the most efficient polysaccharidic resistance inducer against grapevine downy mildew among the reported elicitors (Héloir et al., 2018 ). PS3 triggers grapevine resistance via a priming phenomenon in which the compound does not elicit classical early signalling events but triggers an enhanced and prolonged plasma membrane depolarization in grapevine cells and causes much more effective resistance against downy mildew (Chalal et al., 2015 ; Gauthier et al., 2014 ). The difference in defence responses triggered by laminarin and PS3 may result from the distinct systems evolved by plants to perceive the two compounds (Ménard et al., 2004 ). Recently, some reports have claimed that the formulation of resistance inducers plays a critical role in their cuticular diffusion and control efficacy against plant diseases. For example, the penetration efficacy of PS3 through leaf cuticle, stomata, anticlinal cell walls and trichomes can be enhanced by a highly ethoxylated surfactant Dehscofix CO125 (DE) and its content is much higher on the abaxial surface of the leaf than on the adaxial surface, which is helpful to guide its practical use in the field (Paris et al., 2016 ). Essential oils Essential oils (EOs) are another efficient and promising natural protection alternative (Rienth et al., 2019 ). Terpenes and terpenoids are the main categories of EO compounds and other rare categories including nitrogen‐ and sulphur‐containing compounds, coumarins and homologues of phenylpropanoids (Nazzaro et al., 2017 ). The antimicrobial activity of EOs might be caused by the properties of terpenes/terpenoids, which are capable of disrupting the cell membrane, causing cell death or inhibiting the sporulation and germination of fungi (Nazzaro et al., 2017 ; Rienth et al., 2019 ). A growing amount of evidence indicates that the efficiency of EOs tested in the greenhouse is usually inconsistent with that in the field, which may be attributed to EO degradation caused by light, heat, oxygen, humidity, metal contaminant, application time and poor rain‐fastness (Rienth et al., 2019 ; Turek & Stintzing, 2013 ). For example, grapevine treated with sage extract ( Salvia officinalis ) provides a high level of sustained disease control efficacy against P. viticola . However, due to the degradation caused by long‐term rainfall, the control efficiency can be significantly reduced in rainy years (Dagostin et al., 2010 ). β‐Aminobutyric acid β‐aminobutyric acid (BABA) has been well known as a resistance inducer to protect a wide range of plant species against biotic and abiotic stresses (Cohen, 2002 ; Hamiduzzaman et al., 2005 ; Zimmerli et al., 2008 ). In penetrated plant cells BABA is thought to block the translocation of nutrients into the haustoria, thereby inhibiting mycelial growth and sporangial production (Hamiduzzaman et al., 2005 ; Steiner & Schönbeck, 1997 ). However, BABA‐mediated resistance in plants is most probably based on the priming mechanism rather than direct antimicrobial activities (Conrath et al., 2002 ; Hamiduzzaman et al., 2005 ; Ton et al., 2005 ). In response to P. viticola , BABA primes the production of NADPH oxidase‐dependent reactive oxygen species and the deposition of callose and lignin (Dubreuil‐Maurizi et al., 2010 ; Hamiduzzaman et al., 2005 ). However, BABA does not elicit typical defence‐related early signalling events such as any variation of cytosolic calcium content, nitric oxide production, reactive oxygen species production, mitogen‐activated protein kinase (MAPK) phosphorylation and defence‐related gene expression in grapevine cells (Dubreuil‐Maurizi et al., 2010 ). Chitosan Chitosan, a totally or partially deacetylated derivative of chitin, confers high protection against grapevine diseases caused by B. cinerea and P. viticola (Aziz et al., 2006 ; Romanazzi et al., 2002 ; Trotel‐Aziz et al., 2006 ). The polycationic β‐1,4‐linked‐ d ‐glucosamine polymer forms a semipermeable film that functions as a physical barrier around infection sites, thereby inhibiting pathogens and inducing defence responses in the host tissues (Garde‐Cerdán et al., 2017 ; Krzyzaniak et al., 2018 ). It is thought that the activity of chitosan results from its binding to membrane receptors and is dependent on the molecular weight and the degree of N ‐acetylation (Aziz et al., 2006 ; Kauss et al., 1989 ). In grapevine, treatment with chitosan triggers a variety of defence reactions, including the stimulation of lipoxygenase, phenylalanine ammonia‐lyase, chitinase and β‐1,3‐glucanase activities as well as the accumulation of phytoalexins and pathogenesis‐related proteins (Aziz et al., 2006 ; Trotel‐Aziz et al., 2006 ). Other protective compounds, including soybean and casein hydrolysates (Lachhab et al., 2014 ), glutamate fermentation by‐product (peptidoglycan; Chen et al., 2014 ), phenolic compounds (preformed gallocatechin derivatives and induced flavonoids; Dai et al., 1995 ), protein derivatives (Cappelletti et al., 2016 ), glycyrrhizin (Tröster et al., 2017 ), benzothiadiazole and fosetyl‐aluminium (Dufour et al., 2016 ), dehydroeffusol (Thuerig et al., 2016 ), vitamin B1 (Boubakri et al., 2012 ), vitamin B2 (Boubakri et al., 2013 ), O ‐methylated flavanols and hydroxycinnamic acids (Andreu et al., 2018 ), larixyl acetate and larixol (Thuerig et al., 2018 ), also display effective protective efficiency against downy mildew. The compound or its main active constituent can impose direct fungicidal or inhibitory activity (antifungal activity) (Andreu et al., 2018 ; Boubakri et al., 2012 ; Dufour et al., 2016 ) and/or trigger indirect effects including oxidative burst, cytosolic calcium variations, mitogen‐activated protein kinases activation, upregulation of an array of defence response genes, callose and lignin deposition, phytoalexin accumulation, phytohormone production, modification of grapevine phyllosphere microbial communities and hypersensitive response‐like cell death. Some natural products have a dual mode of action (elicitor of grapevine defences and antimicrobial), suggesting their potential as ecofriendly candidates in the control of grapevine downy mildew (Boubakri et al., 2012 ; Krzyzaniak et al., 2018 ). Even though some of these compounds exhibit ideal inhibitory activities against P. viticola , whether or not these compounds or their active constituents have an effect on the qualitative parameters of grape, must and wine needs further evaluation. CONFLICT OF INTEREST STATEMENT The authors are not aware of any affiliations, memberships, funding or financial holdings that might be perceived as affecting the objectivity of this review.

ACKNOWLEDGEMENTS This study was supported by the Outstanding Scientist Project of Beijing Academy of Agriculture and Forestry Sciences grant JKZX202204, the Beijing Talent Program for J.Y. and the National Technology System for Grape Industry CARS‐29. DATA AVAILABILITY STATEMENT Data sharing is not applicable to this article as no new data were created or analysed.

CC BY

no

2024-01-16 23:43:47

Mol Plant Pathol. 2023 Nov 22; 25(1):e13401

oa_package/4f/8b/PMC10788597.tar.gz

PMC10788615

37721067

Introduction Exposure to ionising radiation can lead to adverse health effects in human beings. Therefore, accurately measuring the level of ionising radiation to which one is exposed is important. The amount of radiation received by specific individuals can be assessed through the use of biodosimetry (BD) ( 1 ) . This refers to techniques that quantify the level of biological damage in an individual and converts this to an amount of dose absorbed by that individual. For example, by correlating the number of chromosome aberrations induced after irradiation to the dose used to produce that damage, one can, in principle, determine an unknown dose to an individual. This correlation comes in the form of a dose–response calibration curve. At Health Canada (HC), these curves are produced by irradiating biological samples in custom-designed water-equivalent phantoms inside a cabinet X-ray machine. When collecting the data to build these curves, it is important to carefully consider the experimental setup as this can affect the accuracy of the curve. In the HC lab, two different phantoms are used that vary in terms of their internal geometries and their material composition. Analyzing the difference in ion chamber output when placed in these phantoms can indicate whether the phantoms can be used interchangeably, or if there is a significant influence on the dose that needs to be considered. While the differences between these phantoms can be explored through measurements in the laboratory, an alternative strategy is to use computational simulations. Monte Carlo (MC) computational methods can predict dose by computing energy deposition from a very large ensemble of radiation tracks modelled in detail, based on known radiation transport cross sections. Since the exposure system involves an X-ray source, the EGSnrc MC toolkit ( 2 ) was chosen to create the model because of its well-established accuracy and efficiency in photon and electron transport simulations. In addition, it includes several variance reduction techniques that can further boost simulation efficiency. The model can be validated using laboratory measurements, and its applications can then be extended beyond the comparison of these two phantoms. Once validated, computational simulations become versatile tools as one can change different aspects of the simulation environment to explore factors that could influence laboratory results, without the need for experimental measurements. With this in mind, the validated MC model can be used to further investigate aspects of the experimental setup such as the positioning of the ion chamber in the field, the effect of irradiating multiple samples simultaneously and other factors that could affect the dose output. This paper describes the MC code that was developed to model the HC X-ray system. It further describes how the MC model was then used to compare two different experimental setups used at HC for biological irradiation through laboratory measurements.

Materials and methods The setup at HC used to irradiate blood samples consists of three major components that must be modelled: the cabinet X-ray machine, the ionisation chamber and the two water-equivalent phantoms. The source of radiation used to irradiate blood samples is an X-ray photon source, produced by the XRAD-320 cabinet X-ray machine (XRAD, Precision X-ray, Madison, United States). The XRAD is capable of delivering a maximum X-ray energy of 320.0 keV and a maximum X-ray tube current of 15.00 mA. In addition to the 2 mm of inherent beryllium filtration attenuating the beam, measurements were made with three different beam filter configurations: Filter 1: 2.0 mm aluminum Filter 2: 1.5 mm aluminum +0.25 mm copper +0.75 mm tin Filter 3: 2.5 mm aluminum +0.13 mm copper Accumulated charge measurements (in nC) were taken using the PTW TW30010 (PTW, Freiburg, Germany) ionisation chamber in conjunction with the PTW UNIDOS T10002 (PTW, Freiburg, Germany) electrometer as an analog to absorbed dose. For all measurements in this study, exposure time was 2 minutes, which corresponded to charge accumulation rates from 3.32 to 35.66 nC/min depending on phantom used, amount of filtration and beam energy. The ionisation chamber was calibrated by the Measurement Science and Standards group at the National Research Council Canada (NRC), 8 May 2020. The calibration coefficient provided by the NRC was 48.07 mGy/nC for a generating potential of 250 kV, meaning the dose rates were in the range of 0.16–1.71 Gy/min. For each measurement, the ion chamber was placed inside the solid water phantoms that are square slabs of side length 15 cm and various thicknesses (0.1–3.0 cm). An image of the experimental setup can be seen in Figure 1 , where the main components of the XRAD that were modelled are labelled, along with the ion chamber and phantom in beam path. In addition, uncertainties on all lab measurements were estimated by considering sources of error from both the instruments and the experimental setup. This was accomplished by combining the error from setting the source-to-surface distance (SSD) with the error from setting the field size. The statistical error from the lab measurements was also consider, but it was found to be too small in relation to the setup errors. Both the SSD and field size errors were estimated by measuring dose values at a variety of different SSDs and field sizes around the values of interest to the actual measurements. By quantifying the dose variation across these distances and field sizes, a dose output error value could be associated with the uncertainty in setting the SSD and field size. To replicate this setup in the form of an MC simulation, the EGSnrc toolkit was used. More specifically, the applications egs_chamber ( 3 ) and BEAMnrc ( 4 ) were used to create two different models of the setup. The first of these models, called the ‘BEAMnrc Model’, uses the application BEAMnrc to simulate the XRAD-320 itself and uses this as a source in the application egs_chamber where the ion chamber and phantom geometries were modelled. Specifications were derived through assistance from the manufacturer, as well as careful examination of previous work done by Azimi et al. ( 5 ) and Lee & Ye ( 6 ) . The view of the model of the XRAD-320 from the BEAMnrc graphical user interface is shown in the left of Figure 2 , and the individual components (A, B, C) of the X-ray setup shown in Figure 1 are equivalently labelled in the MC model. Notably, the ion chambers have been explicitly labelled in Figure 2 as they can be seen more clearly than in Figure 1 . To improve the efficiency of the simulations in the XRAD, two variance reduction techniques were optimised and used in the BEAMnrc code: directional bremsstrahlung splitting (DBS) was enabled alongside bremsstrahlung cross-section enhancement (BCSE) to offset the inefficiency of bremsstrahlung production in the X-ray target at these energies. For these techniques, the parameters were optimised with the BCSE factor set to 100 and a splitting field radius of 12 cm. The optimal splitting number was found to be approximately 100,000. The BEAMnrc input file of the XRAD was then used as the source of X-ray photons in the egs_chamber application. The second model, called the ‘SpekPy Model’, replaces the entire X-ray tube portion of the XRAD-320 with an equivalent spectral point source of photons. The source spectrum is created using SpekPy ( 7 ) , markedly increasing the efficiency of the simulation, bypassing the explicit modelling of the inefficient bremsstrahlung conversion process. The rest of the XRAD-320 is modelled in egs_chamber using egs++, and a set of C++ class libraries implemented in EGSnrc to define elaborate simulation geometries. Typically, a simulation consisted of at least 10 9 source particles, with all values being compared in a ratio always having the same number of source particles in their respective simulations. The phantoms and the ionisation chamber were also modelled using egs++ geometry in egs_chamber. Two different types of solid water phantoms were modelled, one with a single slot for either a blood vial or the ion chamber and the other with eight slots, shown on the right side of Figure 2 , allowing for the irradiation of seven blood vials and the ion chamber simultaneously. Notably, the multi-slot phantom contains a layer of a water-equivalent material polystyrene in the middle, instead of being fully composed of solid water like the single-slot phantom. Two additional variance reduction techniques were used, namely photon cross-section enhancement (XCSE), and range-based Russian roulette (RR), to improve the efficiency of the simulation. An enhancement factor of 512 was used in photon XCSE, along with a rejection factor of 512 for RR. A thin cylindrical shell was defined around the air gap containing the ion chamber, and every region therein was enhanced with XCSE. To compare the two setups used for irradiating blood samples, the ratio of the dose output from the ion chamber using the two phantoms was measured in the lab and calculated in EGSnrc for each model. To examine the difference between the setups, multiple filter configurations were used in the X-ray cabinet, and ratios were calculated for each filter defined previously. An additional form of validation that is standard for X-ray beams is the determination of the half-value layer (HVL) of a given material. The HVL refers to the thickness of a material that reduces the incoming radiation intensity by half. For this study, different thicknesses of copper (0.5, 1.0, 2.0 and 2.5 mm) were placed in the beam path by securing the piece of metal to the bottom of the XRAD-320 exit window. Measurements were taken with filter 1 in place. In addition, a measurement was taken with no copper in place to which the rest of the measurements could be normalised. These measurements were then plotted and fit using MATLAB R2021b, and the thickness at which the electrometer reading dropped to a relative value of 0.5 was calculated. Due to this not being a monoenergetic beam, the attenuation curve could not be modelled by a simple exponential, and the curves were fit with a more complicated function to find the HVL. The exact same setup was recreated in the EGSnrc models but was carried out with a larger number of thicknesses (0.05–2.5 mm).

Results and discussion Radiation dose output ratios between the ion chamber in the multi-slot and the single-slot phantoms were measured in the lab and simulated in EGSnrc for all three filters and represented in Figure 3 . The lab results were compared to the output of each of the simulations by taking the difference between them and dividing by their combined uncertainty. This provided a measure of the number of standard deviations each simulation result differed from their respective lab measurement, with a difference of less than 2 standard deviations being considered acceptable agreement. For the BEAMnrc model, the ratio for filter 2 was found to be in agreement with lab measurement, while the other two filters were not. The SpekPy model provided ratios for filters 1 and 2 that were in agreement lab measurements, while the filter 3 ratio was not. The general trend between both models was that they consistently underestimated the dose output when compared to the equivalent lab measurements, with the SpekPy model yielding better results. The most likely cause of discrepancy between the simulations and laboratory measurements is an inaccuracy in the assumptions made for the specifications of the model. Mainly this includes the lack of knowledge on the spacing of the different components along the beam path, as well as not accounting for the backscatter from the enclosure between the monitor chamber and the jaws. These geometrical issues may result in the energy spectrum of the X-ray beam in the simulation differing from the spectrum of the lab beam due to the difference in attenuation along the beam path. This could cause an underestimation of the output by the simulation depending on how the spectra differ. Although this cannot be truly confirmed without measuring the output spectrum in the lab, it appears to be the most likely explanation for the discrepancy. Another possibility is due to the age of the XRAD, the filter might have deteriorated enough to affect the dose being output, causing a mismatch between the simulation and lab. Comparing between simulations, the expectation was that BEAMnrc would agree better with lab measurements due to the much more accurate geometrical modelling of the X-ray production, but this is not the result found in this study. Due to the SpekPy model originating from a point source, there would be fewer photons scattered away from passing through the sensitive region of the ion chamber than for the BEAMnrc model. This would cause an increase in the dose recorded from the SpekPy model and might explain the discrepancy seen between the models. Using the ratios to compare the two phantoms, the largest difference was for filter 1, where the multi-slot phantom increased the dose by around 6.7%. In contrast, the smallest difference was for filter 2 with around 0.48% higher dose being found in the multi-slot phantom. Although almost all of the results from both lab and simulation agreed that using the multi-slot phantom increases the overall dose deposited. Initially, this seems counterintuitive because the multi-slot phantom contains more gaps of air, and hence less solid water surrounding the ion chamber for photons to scatter into the sensitive region and increase the measured dose. However, this can be explained by considering the composition of the phantoms in question. The single slot phantom consists entirely of RW3, while the multi-slot phantom has a 3 cm layer of polystyrene in the middle of the phantom with the rest being RW3. Both materials are water equivalent, but they are slightly different in that polystyrene is approximately 1.5% more dense than RW3 ( 8 ) . When considering ratios very close to unity, this type of disparity can cause the ratios to flip. As an additional method of validation, the HVL of copper was determined. The attenuation data from the laboratory and each of the EGSnrc models are plotted in Figure 4 , and each data set was fit with a cubic spline function in MATLAB R2021b. The HVL calculated was 0.5931 mm for the laboratory measurements, 0.5711 mm for the BEAMnrc model data and 0.5635 mm for the SpekPy model data. The BEAMnrc HVL differed from the lab value by 3.71%, while the SpekPy HVL differed by 4.99%. Looking at the curves, it appears to that, in general, lab measurements predict a higher output until the thicknesses of copper exceeds 1.5 mm and then the simulations predict a higher dose. The trends with thin copper are in line with previous observations that the models underestimate the dose. To account for the trends with thicker copper, similar arguments as earlier can be made about the inaccuracies in the model with regard to backscatter and component positioning. A combination of errors can result in either an increase or a decrease in the relative dose output measured. Overall, the discrepancy in HVL calculations between lab and simulations is relatively larger than the discrepancies seen for the phantom output ratios. This further indicates that the issue lies within in the internal geometry definitions of the XRAD-320. With the MC model now established with a good degree of accuracy for low levels of filtration, it can be used to compare variations of other aspects of the experimental setup at HC. One example is varying the position of the ionisation chamber in terms of its distance from the center of the field. This type of analysis could be done with relative ease in EGSnrc as it involves changing only a few parameters that define the position of the geometry that creates the ion chamber and rerunning the simulation. In general, any change can be made to the overall simulation geometry to explore any setup variation of interest much faster than one could analyze the same scenario with lab measurements.

Results and discussion Radiation dose output ratios between the ion chamber in the multi-slot and the single-slot phantoms were measured in the lab and simulated in EGSnrc for all three filters and represented in Figure 3 . The lab results were compared to the output of each of the simulations by taking the difference between them and dividing by their combined uncertainty. This provided a measure of the number of standard deviations each simulation result differed from their respective lab measurement, with a difference of less than 2 standard deviations being considered acceptable agreement. For the BEAMnrc model, the ratio for filter 2 was found to be in agreement with lab measurement, while the other two filters were not. The SpekPy model provided ratios for filters 1 and 2 that were in agreement lab measurements, while the filter 3 ratio was not. The general trend between both models was that they consistently underestimated the dose output when compared to the equivalent lab measurements, with the SpekPy model yielding better results. The most likely cause of discrepancy between the simulations and laboratory measurements is an inaccuracy in the assumptions made for the specifications of the model. Mainly this includes the lack of knowledge on the spacing of the different components along the beam path, as well as not accounting for the backscatter from the enclosure between the monitor chamber and the jaws. These geometrical issues may result in the energy spectrum of the X-ray beam in the simulation differing from the spectrum of the lab beam due to the difference in attenuation along the beam path. This could cause an underestimation of the output by the simulation depending on how the spectra differ. Although this cannot be truly confirmed without measuring the output spectrum in the lab, it appears to be the most likely explanation for the discrepancy. Another possibility is due to the age of the XRAD, the filter might have deteriorated enough to affect the dose being output, causing a mismatch between the simulation and lab. Comparing between simulations, the expectation was that BEAMnrc would agree better with lab measurements due to the much more accurate geometrical modelling of the X-ray production, but this is not the result found in this study. Due to the SpekPy model originating from a point source, there would be fewer photons scattered away from passing through the sensitive region of the ion chamber than for the BEAMnrc model. This would cause an increase in the dose recorded from the SpekPy model and might explain the discrepancy seen between the models. Using the ratios to compare the two phantoms, the largest difference was for filter 1, where the multi-slot phantom increased the dose by around 6.7%. In contrast, the smallest difference was for filter 2 with around 0.48% higher dose being found in the multi-slot phantom. Although almost all of the results from both lab and simulation agreed that using the multi-slot phantom increases the overall dose deposited. Initially, this seems counterintuitive because the multi-slot phantom contains more gaps of air, and hence less solid water surrounding the ion chamber for photons to scatter into the sensitive region and increase the measured dose. However, this can be explained by considering the composition of the phantoms in question. The single slot phantom consists entirely of RW3, while the multi-slot phantom has a 3 cm layer of polystyrene in the middle of the phantom with the rest being RW3. Both materials are water equivalent, but they are slightly different in that polystyrene is approximately 1.5% more dense than RW3 ( 8 ) . When considering ratios very close to unity, this type of disparity can cause the ratios to flip. As an additional method of validation, the HVL of copper was determined. The attenuation data from the laboratory and each of the EGSnrc models are plotted in Figure 4 , and each data set was fit with a cubic spline function in MATLAB R2021b. The HVL calculated was 0.5931 mm for the laboratory measurements, 0.5711 mm for the BEAMnrc model data and 0.5635 mm for the SpekPy model data. The BEAMnrc HVL differed from the lab value by 3.71%, while the SpekPy HVL differed by 4.99%. Looking at the curves, it appears to that, in general, lab measurements predict a higher output until the thicknesses of copper exceeds 1.5 mm and then the simulations predict a higher dose. The trends with thin copper are in line with previous observations that the models underestimate the dose. To account for the trends with thicker copper, similar arguments as earlier can be made about the inaccuracies in the model with regard to backscatter and component positioning. A combination of errors can result in either an increase or a decrease in the relative dose output measured. Overall, the discrepancy in HVL calculations between lab and simulations is relatively larger than the discrepancies seen for the phantom output ratios. This further indicates that the issue lies within in the internal geometry definitions of the XRAD-320. With the MC model now established with a good degree of accuracy for low levels of filtration, it can be used to compare variations of other aspects of the experimental setup at HC. One example is varying the position of the ionisation chamber in terms of its distance from the center of the field. This type of analysis could be done with relative ease in EGSnrc as it involves changing only a few parameters that define the position of the geometry that creates the ion chamber and rerunning the simulation. In general, any change can be made to the overall simulation geometry to explore any setup variation of interest much faster than one could analyze the same scenario with lab measurements.

Conclusions From both the lab measurements and simulations, it was found that the choice of phantom configuration does influence dose, but in all cases this effect is relatively small, especially when considering a highly attenuating filter. Using the multi-slot phantom increases the amount of dose absorbed when compared to the single-slot phantom. There remain some issues with both models consistently underestimating the dose output that could likely be addressed through more accurate modelling around the X-ray beam path. Additional validation of the models through the calculation of the HVL of copper showed discrepancies relatively larger than those seen for the phantom ratios, further justifying the need for investigating of the materials in the beam path. The next step in this project is to finalise the validation of this X-ray setup model. Once complete, this model can be used in conjunction with TOPAS-nBio, an MC software that specialises in modelling biological damage, to calculate dose–response curves.

Abstract When using biodosimetry techniques to assess absorbed dose from an ionising radiation exposure, a calibration curve is required. At Health Canada (HC), these curves are generated for a variety of radiation qualities and assays to translate biological damage into absorbed dose. They are produced by irradiating biological samples in custom-designed water-equivalent phantoms inside a cabinet X-ray machine. In the HC lab, two different phantoms can be used for irradiation that differs in material composition and internal geometry. To ensure consistency, the impact of using the phantoms interchangeably was investigated. This was done through lab measurements and the development of a Monte Carlo (MC) model. Differences up to 6.7% were found between the two experimental setups, indicating the need for careful consideration if using these setups interchangeably in the laboratory. Once validated, the MC model can be used to investigate different aspects of the experimental setup without the need for laboratory measurements.

Acknowledgements The authors would like to knowledge all of the individuals in the Carleton Laboratory for Radiotherapy Physics (CLRP) for their assistance on the project through helpful discourse. In addition, the authors would like to thank Dr. Ernesto Mainegra-Hing for his explanations of several EGSnrc applications. Data availability The data underlying this article will be shared on reasonable request to the corresponding author. Funding This work was supported by the Canadian Space Agency. Conflict of interest The authors have no conflicts of interest to declare.

CC BY

no

2024-01-16 23:43:48

Radiat Prot Dosimetry. 2023 Sep 18; 199(14):1551-1556

oa_package/38/25/PMC10788615.tar.gz

PMC10788616

38142529

Introduction According to 2020 global cancer statistics, prostate cancer is the second most common malignancy after lung cancer in men worldwide, over 90 % of which are prostatic adenocarcinoma [1] . Besides the urothelium of the urinary tract, urothelial carcinoma can also originate from prostatic stroma, prostatic ducts, and the mucosa of prostatic transitional urothelium, the latter being defined as primary urothelial carcinoma of the prostate (PUCP) [2] . PUCP is extremely rare, reportedly accounting for approximately 1 % to 5 % of prostatic malignancies [ 3 , 4 ]. Since PUCP was first described as Bowen's disease in 1952 [5] , only limited data on this type of tumor have been published, nearly all as case reports. Pathology and immunohistochemistry are the main diagnostic modalities. Several immunohistochemical markers have been reported to aid diagnosis, including GATA-3, P63, and high-molecular weight cytokeratin [ 6 , 7 ]. Because few patients with PUCP have high serum PSA concentrations [ 8 , 9 ], the opportunity for early diagnosis is missed in most patients. This, together with the characteristic extreme aggressiveness and strong tendency to invasion, means that most patients have evidence of local progression or distant metastasis at the time of diagnosis [10] . Considering its poor prognosis, a general understanding drawn from studying numbers of patients with this disease from multiple institutions is important. In the present study, we explored the features, treatment, and outcomes of PUCP in patients from multiple centers to provide insights into this disease.

Material and methods Study cohort We retrospectively selected patients who were pathologically diagnosed with PUCP between January 2011 and April 2022 in the Affiliated Hospital of Qingdao University, Beijing Hospital, and Shandong Provincial Hospital Affiliated to Shandong First Medical University. Patients with a history of bladder or urethral urothelial carcinoma were excluded to guarantee that the urothelial carcinoma had originated in the prostate. Characteristics of patients We collected relevant data for the selected PUCP patients, including age, body mass index, initial symptoms, results of DRE, histories of hypertension, diabetes, drinking, and smoking, serum tumor marker concentrations, results of urinalysis, imaging findings, diagnostic modalities, histopathology, immunohistochemistry, TNM stage, and treatment. All patients were followed up until March 2023 or death. Statistical analyses The collected clinical information was analyzed as descriptive statistics such as proportion. Overall survival (OS) was defined as time from the date of pathologic diagnosis to the time of last follow-up or death from any cause. Progression-free survival (PFS) was defined as the time from the date of pathologic diagnosis to clinical progression or death from any cause. The Kaplan–Meier method was used to assess OS and PFS. We further analyzed differences in OS and PFS between patients with different TNM stage disease according to AJCC stage. The log-rank test was used to analyze survival differences among these variables. Two-sided P-values <0.05 were considered to denote significant differences in all statistical tests. Statistical analyses and graphics were performed using R software (version 4.1.0).

Results Clinical characteristics The study cohort comprised 18 patients with pathological diagnoses of PUCP from January 2011 to April 2022, including seven in the Affiliated Hospital of Qingdao University, seven in Beijing Hospital, and four in Shandong Provincial Hospital Affiliated to Shandong First Medical University. These patient's characteristics are listed in Table 1 and their relevant personal, clinical, and immunohistochemical data are summarized in Table 2 . Twelve (66.7 %) patients had T4 disease, nine (50.0 %) N1, and five (27.8 %) patients M1 at the time of diagnosis. The mean age of included patients was 72.4±7.8 years and the mean body mass index 25.3±3.6. Dysuria and urinary frequency were the most common symptoms of PUCP, each of these being reported in 14 (77.8 %) patients. Seven (38.9 %) patients had gross hematuria, and six (33.3 %) presented with painful urination. Eleven patients underwent DRE, abnormal nodules being detected in four (36.4 %) of them. Eight (44.4 %) patients had a history of hypertension, six (33.3 %) a history of diabetes, four (22.2 %) a history of drinking, and seven (38.9 %) a history of smoking. Laboratory and imaging findings Serum tumor markers were examined in all patients. However, only two (11.1 %) had high total PSA concentrations and none (0 %) had increased PSA density. Further, six patients were tested for serum prostatic acid phosphatase; rising PAP was found in only two (33.3 %) of them. In contrast, most patients showed abnormalities on urinalysis. One patient did not undergo urinalysis. Urine was positive for erythrocytes in 15 (88.2 %) patients, for leukocytes in 12 (70.6 %), and for protein in 15 (88.2 %). B-ultrasound was the most commonly performed imaging examination (18 of 18); however, it detected tumors in only 10 (55.6 %) of the 18 patients. In B-ultrasound examinations, the tumors presented with low or mixed signals and unclear borders. Similarly, tumors were detected in only two of four patients who underwent enhanced lower abdominal CT or CT urography. Both were stage IV tumors and showed as irregular masses with heterogeneous density and uneven enhancement. Nine patients underwent MRI, which detected tumors in eight (88.9 %) of them. The tumors appeared as irregular low-signal lesions in T2-weighted images and irregular hyperintense foci in diffusion-weighted images. Additionally, whole body bone imaging revealed bone metastases in two (28.6 %) of seven patients. Pathology and immunohistochemistry PUCP was pathologically confirmed in all study patients, pathological diagnoses being made on tissue obtained by TURP in 13 (72.2 %) patients and by needle biopsy of the prostate in five (27.8 %) patients. A representative hematoxylin and eosin stained section is shown in Fig. 1 a. The results of immunohistochemistry are expressed as “number positive/total tested” and were as follows: GATA-3 (9/11) ( Fig. 1 b), PSA (0/17) ( Fig. 1 c), prostate specific acid phosphatase (0/3), prostate-specific membrane antigen (0/2), P63 (11/13) ( Fig. 1 d), CK7 (10/13), CK20 (8/13), CK34βE12 (3/6), P504S (5/9), and alpha methyl acyl CoA racemase (6/13). Considering above results, all patients were high-grade urothelial carcinoma. Treatment and prognosis Information on treatment was not available for one patient. Of the remaining patients, two (11.8 %) with T1N0M0 tumors received no treatment after a pathological diagnosis had been made, three (17.6 %) with T1–2N0M0 tumors underwent radical cystectomy and bilateral lymphadenectomy alone, one (5.9 %) with a T4N1M0 tumor underwent radical prostatectomy plus bilateral lymphadenectomy and adjuvant radiotherapy, and the remaining 11 (64.7 %) received systematic therapy. Of the 11 patients who received systematic therapy, three received gemcitabine plus cisplatin combined with radiotherapy, three received gemcitabine monotherapy, two received goserelin as systematic hormonal treatment, one received gemcitabine, cisplatin, and docetaxel combined with radiotherapy, one received gemcitabine combined with cisplatin, and one with a T4N1M1 tumor received targeted therapy combined with immunotherapy and radiotherapy. Follow-up information was not available for one patient. In the remaining 17 patients, the median OS was 42 months (95 % CI: 28.74–55.26) ( Fig. 2 a), and the median PFS 25 months (95 % CI: 0–55.63) ( Fig. 2 b). According to log-rank tests, the OS rate did not differ significantly between patients with T1–2 and T3–4 disease (p=0.21) ( Fig. 3 a). However, the PFS rate was significantly higher in T1–2 patients than in T3–4 patients (p=0.035) ( Fig. 3 b). Further, OS and PFS did not differ significantly between patients with and without regional lymph node metastases (p=0.37 and p=0.28, respectively) ( Fig. 3 c,d), or between patients with and without distant metastases (p=0.48 and p=0.28, respectively) ( Fig. 3 e,f). Eight of eighteen patients in our cohort received chemotherapy solely or chemotherapy combined with other treatment, and two patients did not have information of progression to analyze objective response rate. The objective response rate with chemotherapy at three months after diagnosis was 66.7 % (4/6), and was 33.3 % (2/6) at six months after diagnosis.

Discussion Although the incidence of involvement of the prostate by urothelial carcinoma is reportedly between 12 % and 48 %, PUCP is rare [11] , [12] , [13] . Because of the low sensitivity and specificity, both underdiagnosis and misdiagnosis of PUCP is common. In our study, over half of patients had T4 tumors or lymph nodule metastasis, and nearly a third of patients had distant metastasis, at the time of diagnosis. One review of six patients with PUCP found distant metastases in all six, which demonstrates the hidden nature and extreme aggressiveness of PUCP [14] . Two case reports have suggested that PUCP patients are nearly 10 years younger than those with prostatic adenocarcinoma at the time of diagnosis [ 10 , 15 ]. However, our patients’ mean age was 72.4 years, which differs little from that of patients with glandular adenocarcinoma of the prostate. The average age of 69.1 years at diagnosis in one reported PCUP cohort is consistent with our findings [14] . Most of the symptoms of PUCP are non-specific lower urinary tract symptoms, including dysuria, urinary frequency, nocturia, and pain on urination [ 10 , [15] , [16] , [17] , [18] ]. Gross hematuria can also occur [ 2 , 9 , 16 , 17 ]. In our cohort, the most common symptoms of PUCP were dysuria and urinary frequency (77.8 %), followed by gross hematuria (38.9 %) and pain on urination (33.3 %). These symptoms are similar to those of benign prostatic hyperplasia or prostatic adenocarcinoma, making the differential diagnosis challenging. Although hard tumor nodules were discovered on DRE in four patients, this did not enable distinguishing between PUCP and prostatic adenocarcinoma. Additionally, several particular symptoms have been reported in some PUCP patients. Zhang et al . reported a patient with PUCP with sustained fever for over one month [2] . Wadhwa et al . reported a patient with atypical rectal bleeding and an overlying rectal ulcer detected by DRE [8] . Further, a patient with PUCP reportedly developed a firm, nontender, metastatic nodule in the abdominal wall adjacent to his umbilicus during hospitalization [19] . Although only one third of our study patients had gross hematuria, erythrocytes were detected in 88.2 % of patients on urinalysis. In addition, 70.6 % and 88.2 % of our study patients were also positive for leukocytes and protein, respectively, on urinalysis. It seems that abnormal findings on urinalysis are a universal characteristic of PUCP. Maruyama et al. have also reported a PUCP patient who was positive for leukocytes, erythrocytes, and protein on urinalysis [18] . As for imaging findings, the reported diagnostic sensitivity of imaging in PUCP patients is inconsistent between different modalities. Using urological ultrasound, Yang et al. identified enlarged, irregularly shaped prostate glands suggestive of neoplasm [17] , whereas Tan et al. only found homogeneous enlarged prostates by transrectal ultrasonography [9] . In another study, tumor nodules were not identified by transrectal ultrasonography, but enhanced CT showed patchy hypodensity [8] . In our cohort, B-ultrasound and enhanced CT detected abnormalities in 55.6 % and 50 % of patients, respectively, which also shows that these two diagnostic modalities are insensitive. MRI is the most strongly recommended radiological examination for prostatic adenocarcinoma, having good sensitivity for detection of this condition, especially for tumors that are over 10 mm in diameter [20] , [21] , [22] . In our series, abnormalities suggestive of tumors were found by MRI in 88.9 % of PUCP patients. Other studies of PUCP have found hypointense masses on T2-weighted images and high signal nodules on diffusion-weighted images on MRI [ 2 , 17 , 18 , 23 ]. One recently published article stated that both the prostate tumor and its metastases showed intense fluorodeoxyglucose uptake on positron emission tomography-CT [23] . However, these lesions were indistinguishable from prostatic adenocarcinoma. The lack of specificity of radiological features makes it difficult to distinguish PUCP from other types of prostate cancer. The tumor marker PSA is of significant diagnostic value for cancer detection and has revolutionized diagnosis of prostatic adenocarcinoma [ 24 , 25 ]. In the case of PUCP, the findings are conflicting. Some studies have reported that PUCP patients have normal serum PSA concentrations [ 2 , 10 , 15 , 16 , 18 , 23 ], whereas others have found high serum PSA concentrations in patients with PUCP [ 8 , 9 , 17 , 19 ]. Only two (11.1 %) patients in our study had high serum total PSA concentrations and no patient had elevated PSA density, which is remarkably different from the findings in patients with prostatic adenocarcinoma. Besides, Sołek et al . identified a PUCP patient with high β-human chorionic gonadotropin concentrations [16] . Dong et al. reported high concentrations of carcinoembryonic antigen in one case [23] . Even though we discovered high serum total PSA concentrations in two patients, no patient showed immunohistochemical positivity for PSA, prostate specific acid phosphatase, or prostate-specific membrane antigen. Other researchers have also generally found negativity for PSA and P501s in samples of PUCP [ 26 , 27 ]. Rather, we found that immunohistochemistry for CK7, CK20, GATA-3, and P63 was more likely to be positive. Although PSA has significant value in pathological diagnosis, there are a variety of non-specific markers for urothelial carcinoma. GATA-3 is a urothelial marker that can differentiate urothelial carcinoma from prostatic adenocarcinoma [28] . P63 and HMWCK, including 34βE12, have also been shown to be markers of urothelial carcinoma [ 7 , 26 ]. Fichtenbaum et al . have reported that CK5/6 and double-stained CK7/CK5 can discriminate between urothelial carcinoma in situ and invasive urothelial cancer in the prostate [29] . Our findings indicate that PUCP patients are prone to have negative PSA and positive P63, GATA-3, CK7, and CK20 on immunohistochemistry and that needle biopsy of the prostate is necessary. Because no standard treatment has yet been established, there are multiple treatment strategies for PUCP. In our series, radical cystectomy was the most commonly performed surgical procedure, and gemcitabine plus cisplatin combined with radiotherapy the most commonly administered systematic therapy, these approaches being quite different to those used for prostatic adenocarcinoma but similar to those used for urothelial bladder cancer. Considering all our patients had histologically proven high-grade urothelial carcinoma, conservative treatment was contraindicated. Some urologists propose TURP to the bladder neck to remove all gross tumor, followed by BCG instillation to treat any localized residual PUCP [ 30 , 31 ]. ICUD-EAU International Consultation recommended that radical cystectomy should be performed in patients with early stage PUCP and gemcitabine combined with cisplatin should be the first-line chemotherapy regimen for advanced-stage PUCP [32] . The 10-year OS rate of patients with typical prostatic adenocarcinoma is over 70 % according to a recent large study [33] . However, in one study of only six patients with PUCP, the median OS was only 4.6 months [14] . In our cohort, the median OS and PFS were 42 months and 25 months, respectively, indicating that the prognosis is worse than that of prostatic adenocarcinoma. However, patients in our cohort had significantly prolonged OS and PFS compared with the six PUCP patients Mallén et al. reported [14] . It should be noticed that only two of six patients received radical cystectomy in Mallén's cohort, and others only received radical prostatectomy, palliative TURP, or BCG instillation. The only one patient who received radical prostatectomy in our cohort also progressed 2 months later and died only 8 months after diagnosis. We hypothesized that the application of radical cystectomy and chemotherapy of gemcitabine combined with cisplatin prolonged the prognosis of our patients. Besides, this article was published nearly 20 years ago. The more advanced surgical technology and nursing level might also bring survival advantages for our patients. Cancer is prone to develop at the junction between the urothelial and columnar epithelium in the prostatic ducts; thus, PUCP may originate from prostatic duct urothelium [34] . Unlike the bladder urothelium, the prostatic duct urothelium lacks a lamina propria, facilitating penetration of the basal membrane and invasion of the prostatic stroma by tumor [35] . Our TNM subgroup analyses revealed only that the PFS rate was significantly higher in T1–2 patients than in T3–4 patients (p=0.035). We found no significant differences in OS between any TNM subgroups or in PFS in patients with or without lymph node and distant metastases, possibly because of our small sample size. Liedberg et al. have proposed a unique staging system for PUCP that differs from the AJCC staging system for prostatic adenocarcinoma. One study of the impact of involvement of different sites in the prostate on the prognosis of urothelial carcinoma demonstrated that stromal involvement is associated with the worst outcomes [36] . More large studies should be conducted to explore the proposed unique staging system for PUCP. As far as we know, this is the first multi-center study to explore the features, treatment, and outcomes of PUCP. However, several limitations of this study need to be discussed. First, its retrospective design may have led to bias in data selection and incomplete follow-up information. Second, although this is the largest series of PUCP reported so far, the cohort size was still too small to allow extensive exploration of treatment protocols and prognostic factors. Third, due to the lack of information, we did not describe the genomic characteristics of PUCP. The unique genomics of PUCP and the comparison with prostatic adenocarcinoma should be further analyzed in the future. Finally, patients were collected from different institutions, potentially resulting in heterogeneity of the detection and diagnostic criteria of clinical characteristics. In the future, these should ideally be balanced and analyzed in larger, well-designed prospective studies of patients. Despite these restrictions, our findings could contribute to a better understanding of PUCP.

Conclusions PUCP, a rare but highly aggressive type of prostate cancer, should be considered in men with abnormalities on MRI and normal serum PSA concentrations. Typical immunohistochemistry findings are positivity for GATA-3 and P63, and negativity for PSA. Radical cystectomy, chemotherapy with gemcitabine and cisplatin, and radiotherapy can be effective. Higher T stage is a significant risk factor for PFS. Large, well-designed prospective studies should be performed in the future.

Objectives To explore the features, treatment, and outcomes of primary urothelial carcinoma of the prostate (PUCP) in a multicenter study. Methods The clinical and imaging features, pathological findings, treatment, and outcomes of patients diagnosed with PUCP from January 2011 to April 2022 at three institutions were collected and analyzed. The Kaplan–Meier method and log-rank test were used to assess survival rates of the overall group and survival differences between groups according to TNM stage. Results The study cohort comprised 18 patients with PUCP of mean age 72.4±7.8 years. Dysuria and urinary frequency were the most common symptoms (77.8 %). Sixteen (88.9 %) patients had normal serum total PSA concentrations. Most patients showed abnormalities on urinalysis. MRI was the most accurate diagnostic imaging method (88.9 %). As to immunohistochemistry findings, GATA-3 (81.8 %) and P63 (84.6 %) were positive in most examined patients; however, no lesions were positive for PSA. Three (17.6 %) patients with T1N0M0 and T2N0M0 tumors underwent radical cystectomy. Eleven (64.7 %) patients which almost all had T4 tumors received systematic therapy, most of them receiving chemotherapy with gemcitabine and cisplatin, and radiotherapy. The median overall survival was 42 months, and the median progression-free survival 25 months, the latter being significantly longer in patients with T1–2 than in those with T3–4 disease (p=0.035). Conclusion PUCP, a rare but highly aggressive type of prostate cancer, should be considered in men with abnormalities on MRI and normal serum PSA concentrations. Positive GATA-3, P63, and negative PSA are typical immunohistochemistry features. Radical cystectomy and systematic therapies can be effective. Keywords

Funding This study was partly funded by the 10.13039/501100007129 Natural Science Foundation of Shandong Province (ZR2021MH354), Medical and health research program of Qingdao (2021-WJZD170). The funders had no roles in study design, data collection and analysis, decision to publish, or preparation of the manuscript. CRediT authorship contribution statement Junjie Ji: Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. Tian Liu: Formal analysis, Methodology, Investigation, Writing – review & editing. Yu Yao: Software, Methodology. Wen Liu: Data curation, Investigation. Hao Ning: Data curation, Investigation. Tongyu Wang: Data curation, Visualization. Guiming Zhang: Conceptualization, Funding acquisition, Project administration, Methodology, Writing – review & editing. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments We thank Dr Trish Reynolds, MBBS, FRACP, from Liwen Bianji (Edanz) ( http://www.liwenbianji.cn/ ), for editing the English text of a draft of this manuscript.

CC BY

no

2024-01-16 23:43:48

Neoplasia. 2023 Dec 23; 47:100961

oa_package/a1/71/PMC10788616.tar.gz

PMC10788620

38226014

Introduction The tumour microenvironment (TME) provides essential cues to direct and control tumour progression and provide the basis of key hallmarks of cancer [ 1 ]. The complexity of the TME derives from both cellular and noncellular components. Cellular components are namely stromal cells including fibroblasts, immune cells, bone and endothelial cells, and non-cellular components include the extracellular matrix components, oxygenation of the tissue and cytokines [ 2 ]. Biomimetic extracellular matrix (ECM) composition and stromal cells are required to recreate the TME in engineered tissue models [ 3 ]. Several different techniques have been studied to mimic cell-cell interactions in the TME both in vitro and in vivo . Two-dimensional (2D) monolayer co-cultures are widely used as in vitro TME models, however they lack many physiological properties, including the tissue architecture. The use of 3D models has made it possible to recapitulate the physiological conditions found in the TME. Furthermore, multicellular 3D models have overcome some of the limitations of 2D model counterparts [ 4 , 5 ]. One of the challenges of multicellular 3D models is the uncertainty around deciphering cell-specific signalling, in other words how cells synchronise their signalling and network with other cells [ 5 ]. Thus, novel strategies to unravel this complex communication between tumour and stroma include rapidly evolving technology in high-plex profiling for the development of molecular spatial profiling. The spatial profiling allows cell-type specific characterisation of heterogenous cell populations in the TME. GeoMx Digital Spatial Profiler (DSP) is a platform to spatially resolve biology of the tissue of interest by using digital quantitation of target analytes [ 6 , 7 ]. This system utilises barcoded DNA oligos attached to in situ hybridisation probes for RNA. The attachment is done by a detection reagent, an ultraviolet (UV)-photocleavable linker [ 8 ]. The tissue is covered with the detection reagent and the customizable fluorescent morphology markers and then visualised. The regions of interest (ROIs) are used to image the sample following UV light exposure-induced release of the barcoded oligos. These oligos can then be collected by instrument quantitation using nCounter or next generation sequencing (NGS) [ 8 ]. The ability to select regions of interest means that the interaction of tumour and stroma can be visually dissected on a section and interrogated using this technology. The GeoMx DSP works well with small sample size and the process itself is non-destructive, therefore the same section can be profiled multiple times [ 7 ]. The ROI selection is adjusted based on research of interest. It has been used to study various neoplasms including lung, prostate, breast, and liver cancers and allows for a high level of characterisation of heterogeneous tissue. To our knowledge, this technique has not been successfully utilised in any bioengineered in vitro samples, including odontogenic tumours, but the use of a spatial transcriptomics platform will give insight and demystify the crosstalk between tumour and stroma cells. This study utilises GeoMx DSP to spatially resolve tumour-stroma interaction in vitro 3D tumouroids of ameloblastoma and their native stromal cells. Ameloblastoma (AM) is a benign odontogenic tumour of the jawbone, which is rare but locally aggressive [ 9 ]. Ameloblastoma tumour cells interact with the bone and gingival fibroblast stroma, leading to resorption of the surrounding maxillofacial jawbones [ 10 ]. These interactions regulate the development and progression of the disease, and it is essential to understand the precise mechanisms. Studies on 3D ameloblastoma tumouroids have provided novel findings related to disease mechanism [ 11 ]. The use of plastic compression to generate tissue dense collagen scaffolds is a key innovation in developing biomimetic tissue models [ 12 , 13 ]. The plastic compression technique is applied to cell-seeded collagen hydrogels to expel excess fluid, without any loss in cell viability. Plastic compression results in a significant increase in collagen density and an increased stiffness, or youngs modulus, so that collagen scaffolds more closely mimic native human tissue values [ 14 , 15 ]. The tumouroid model generated using plastic compression also allow for compartmentalisation of the tumour and stroma in tumouroids [ 16 ]. Through the careful bioengineering of a connected tumour and stroma compartment, where biophysical features of tissue are re-capitulated, it is possible to study the boundary between these components to profile key pathways in tumour cells which are altered in the presence of and through the interaction with specific stromal cells. The pathways analysed in this study were chosen based on our pre-existing gene data [ 16 ]. Using tumouroid models of ameloblastoma and other cancers, we have already validated invasive marker genes such as matrix metalloproteinases (MMPs) [ 11 , 15 ]. Due to the large volume of data generated, this study carefully analyses previous data generated using tumouroid-stroma models to focus on developing clear research questions. These are namely ECM remodelling, invasion, and immune regulation. This powerful model is fully appreciated when focused regions of interest and cell specific analysis can be conducted at the tumour-stroma interface. By using GeoMx DSP it is possible to analyse key cell populations at this interface and investigate larger cohorts of different markers.

Methods Cell culture Cell culture conditions were 37 °C, 5 % CO 2 , and 21 % O 2 . The immortalised plexiform ameloblastoma cell line, AM-1 was provided by Professor Harada [ 17 ]. Keratinocyte serum free medium 1 X (KSFM) supplemented with KSFM supplements (bovine pituitary extract (BPE) and epidermal growth factor (EGF), human recombinant) was used to culture the AM-1 cells. Primary gingival fibroblasts, Human, Adult (HGF) (PCS-201-018TM) were purchased from ATCC and cultured in Dulbecco's modified Eagle medium (DMEM). Primary human osteoblasts (hOB) from Promocell® (Heidelberg, Germany) were cultured in Promocell® osteoblast growth medium with supplement mix. All media types contained 10 % foetal bovine serum (FBS), 100 units/mL penicillin, and 100 μg/mL streptomycin (GibcoTM through Thermo Fisher Scientific, Loughborough, UK). 3D model fabrication 3D models were engineered using monomeric type I collagen (First Link, Birmingham, UK). and RAFTTM protocol was followed throughout the process. A collagen/cell mix was prepared from 10 X Minimal Essential Medium (MEM) (Sigma-Aldrich, Dorset, UK), collagen type I, neutralising agent (N.A) and the cells. N.A was composed of 17 % 10 Molar NaOH (Sigma-Aldrich, Dorset, UK) and 83 % 10 M HEPES buffer (GibcoTM through Thermo Fisher Scientific, Loughborough). The collagen/cell mix had final volumes of 80 % collagen, 10 X MEM, 6 % N.A. and 4 % cells and was kept on ice until it was crosslinked. The first step in the fabrication of the complex tumouroids was creating the tumour mass of 240 μL of cell/collagen mix with 5 × 10 4 AM-1 cells. The mix for the tumour mass was then set into 96-well plates (Corning® Costar®, Sigma-Aldrich, Dorset, UK) and incubated in 37 °C for 15 min to allow crosslinking. This step was followed by 15 min of plastic compression using RAFTTM absorbers at room temperature (Lonza, Slough, UK). Then the stromal gel mixes containing either no cells (acellular) or 1 × 10 5 HGFs or 1 × 10 5 hOBs were prepared. Cells and collagen were mixed thoroughly to ensure an even distribution of cells throughout the 3D matrix. The first layer, 650 μL of the stromal gel mix was cast on 24-well plate (Corning® Costar ®, Sigma-Aldrich, Dorset, UK). The tumour mass was placed in the middle of the first stromal layer and covered by a second stromal layer of 650 μL of the stromal gel mix ( Fig. 1 A). Following crosslinking of the tumouroids for 15 min at 37 °C, 24-well RAFTTM absorbers (Lonza, Slough, UK) were used to plastic compress them for 15 min. The gels were supplied with 2 mL of media, which was changed by 50 % every 48 h. The culture period was 14 days. Sample preparation for spatial profiler The protocol from Ref. [ 8 ] ‘GeoMxTm RNA Assay: High Multiplex, Digital, Spatial Analysis of RNA in FFPE Tissue’ was followed throughout. The sample preparation section was specific to tissue samples. Therefore, this study has established the sample preparation steps for 3D in vitro samples. 3D samples were formalin fixed and processed using a processor (Thermo Fisher Scientific, Loughborough, UK) and embedded. The embedded blocks were sectioned into 5 μm sections and these were trimmed appropriately to mount to the VWR Superfrost Plus Slides (Catalogue number 48311–703). The tumour-stroma boundary was visible by eye, therefore during sectioning the area covering tumour-stroma boundary was targeted ( Fig. 1 B). From each sample, minimum of 4 sections were collected to maximise the number of cells captured in each slide due to the fact that the cells were not distributed evenly. The invasion from tumour stroma boundary was confirmed by Haematoxylin and eosin (H&E) staining ( Supplemental Figure 1A ). The sample was 200 μm and the thickness of the tumour mass was 100 μm. The sections were selected from the tumour mass alignment ( Supplemental Figure 1B ). The sections were placed within a defined area (36.2 mm long x 14.6 mm wide) in the middle of the slide. Selection of region of interest Tumour-stroma boundary shown in Fig. 1 B was chosen as the ROIs for each tissue type. Since the sections covered the tumour-stroma boundary, random ROIs were chosen from each section, with cell-dense areas prioritised. The cellular composition can be segmented into areas of illumination (AOI) by dividing ROIs based on the fluorescent signal of individual morphology marker by filtering the UV-light [ 18 ] ( Fig. 2 A). NanoString GeoMx Digital Spatial Profiler The epithelial cell marker pan-cytokeratin (PanCK) was used to identify tumour cells in the samples. PanCK-positive or PanCK-negative cells were profiled individually [ 18 ] ( Fig. 2 B &C). Histology Formalin fixed 3D samples were processed overnight using a processor (Thermo Fisher Scientific, Loughborough, UK). The next steps were embedding and sectioning into 5 μm sections. The sections were mounted to Superfrost Plus Slide and the slides were baked at 64 °C for 2 h and then deparaffinised. This was followed by Haematoxylin and eosin (H&E) staining and application of mounting medium for imaging. Assay quality control and statistical analysis All steps of the assay control and statistical analysis were conducted on GeoMx Digital Spatial Profiler (DSP) Software and Phyton. The sequencing quality is determined based on sufficient saturation and sensitivity of low expressors. Initially raw probe counts were assessed for sequencing quality control (QC) where all of the under-sequenced samples from AOI count analysis were eliminated from the following QCs. The next step was probe QC which is to target mRNAs by multiple probes and the outlier probes were removed. The data was normalised using third quartile (Q3) normalisation. This normalises individual counts to the 75th percentile of signal from their own AOI. The expression levels were presented as counts that quantify RNA level from the readouts of the barcode. The data was evaluated for signal to Limit of Quantitation (LOQ) ratio to test the reliability of the targets. LOQ was calculated as GeoMean (NegProbes) x GeoSD (NegProbes) 2 . Then, the signal from each probe was divided by the LOQ of each AOI. Normalised data was statistically assessed by t -test (non-paired) with the BH test correction type and tested for by factors. To generate gene volcano plots a custom script for volcano plots by GeoMx Script Hub was used. A p-value of <0.05 was considered statistically significant and the log 2 fold change log 2 (FC) value > 0.5 was considered as the notable fold change. The graphs were plotted as log 2 (FC) as x-axis and adjusted p-value as y-axis. Heatmaps were created in Python using hierarchical clustering to visualise statistically significant group gene expression profiles. All statistically significant genes were included in the heatmaps for each pathway unless stated otherwise. Individual genes were plotted using GraphPad Software (La Jolla, CA, USA) and their statistical tests were completed using the GeoMx Digital Spatial Profiler (DSP) Software. The pathway networks in Supplemental Material were created using DSP Software, Pathway Analysis feature and the networks were presented based on enrichment score. Selection of genes for pathway panels All pathway panels were created using set gene lists available in DSP Reactor Target Groups. Invasion pathway gene panel was created from the cell migration genes and included all MMPs. Matrix remodelling pathway gene panel was composed of ‘ECM proteoglycans’, ‘Matrix Remodelling’, and ‘ECM Interactions’ groups that are defined in Reactor Target Groups. Immune system pathway gene panel included all Immune System Reactor Target Group.

Results The ameloblastoma transcriptome is altered in the presence of stromal cells Tumour-stroma models were engineered using AM-1 cells as a central tumour mass. The central tumour mass was surrounded by specific stromal compartments of dense collagen I with either no cells, gingival fibroblasts (HGF) or osteoblasts (hOB) ( Fig. 1 A). This resulted in 3 sets of cultures to compare, with the acellular stroma essentially acting as a control. The GeoMx Digital Spatial Profiler (DSP) was used to evaluate the effects on tumour cells of adding specific populations of stromal cells. For the profiler, the area covering the tumour mass-stroma boundary was sectioned ( Fig. 1 B) in order to focus and capture tumour cells invading into the surrounding stroma. In each section, 3 regions of interest (ROIs) were selected for comprehensive cancer transcriptome analysis ( Fig. 2 A). The ROIs contained both CK+ and CK- cells, and CK + cells were verified with ∼5–6 timers higher KRT5 expression compared to CK- cells ( Fig. 2 B&C). The introduction of different physiologically relevant stromal types induced significant changes in the transcriptome of tumour cells. Out of the 1813 transcriptome genes analysed, 1415 genes were above LOQ ( Supplemental Figure 2 ). Volcano plots were generated to overview the changes in the expression profile of AM-1 cells when interacting with different stroma types. Only genes with log 2 fold-change (log 2 FC) more than 0.5 were further analysed ( Fig. 3 A&B&C) . Initial screening of these volcano plots indicated that the introduction of stromal cells in tumour adjacent compartments induced significant changes (45.3 %) in the transcriptome of AM-1 cells compared to acellular stroma. 15.3 % of the whole transcriptome was significantly altered when a fibroblast stroma was introduced to the AM-1 tumour mass and 36.7 % of genes changed with a bone stroma (the hOBs) ( Fig. 3 ). The Venn Diagrams in Fig. 3 D demonstrate the number of genes that were significantly downregulated or upregulated with bone stroma and/or fibroblast stroma compared to acellular stroma. The number of genes downregulated with bone stroma was higher than with fibroblast stroma ( Fig. 3 D). Considering there were 1415 genes, to better prioritise targets in the case of ameloblastoma the rest of the analysis was segmented based on different signalling pathways. Having a fibroblast stroma or osteoblast stroma caused enrichment in many different pathways and all of these pathways presented in pathway networks ( Supplemental Figures 3, 4 and 5 ). The networks showed greatest enrichment in pathways such as DNA repair, extracellular matrix organisation, DNA replication, immune system, and cell cycle. Adding stromal cells cause significant changes in ameloblastoma invasion Invasion is a tumour specific characteristic driven by different pathways, including epithelial to mesenchymal transition (EMT), migration and cell adhesion pathways [ 19 ]. Tumour cells, including ameloblastoma cells, are known to invade to their surrounding stroma within the 3D tumouroid [ 11 ]. Since the sectioned area covered the tumour-stroma boundary, the AM-1 cells that were migrating into the surrounding stroma were spatially profiled. The invasion of AM-1 cells to their surrounding stroma by day 14 was shown in Fig. 4 A. The invasion data supports previous findings on the invasion of AM-1 cells into different stromal compartments, namely acellular, fibroblast stroma (HGF) and bone stroma (hOBs). AM-1 cell invasion was significantly higher where a fibroblast stroma was present (355 39 compared to an acellular stroma (255 66 p < 0.05) or indeed to a bone stroma (189 39 , p < 0.0005) ( Fig. 4 B). The statistically significant change in gene expression (p < 0.05) of the invasion of ameloblastoma cells into either an acellular stroma or a bone stroma was 28.6 %, between an acellular stroma and fibroblast stroma it was 21.4 %. These changes indicated that adding stromal cells induced a decrease in specific invasion genes ( Supplemental Table 1 ) ( Fig. 4 D). A heatmap covering EMT, cell migration and MMPs was generated for AM-1 (ameloblastoma cells), which were the PanCK + tissue segments. Different stroma types directly impacted the expression profiles of AM-1 tumour cells. AM-1 tumouroids with bone stroma exhibited the greatest change in invasion markers compared to other stroma types ( Fig. 4 C&D). Introducing stromal cells induced an enrichment of certain migration genes. For example, Rho-associated protein kinase ( ROCK1) was enriched where a bone stroma was present and this has previously been found to be overexpressed in cell migration and invasion in neoplasms [ 20 ]. One of the main invasion markers matrix metalloproteinases 3 ( MMP3 ) [ 21 ] was ∼2-fold upregulated where a fibroblast stroma was present compared to a bone stroma, which correlates with the invasion distance data ( Fig. 4 E). The expression of other invasion markers, MMP1 and MMP9 , were higher where a fibroblast stroma was present compared to a bone stroma. Interestingly, there was no significant change in some of the other main invasion markers such as MMP11 and MMP7 with different stroma types ( Fig. 4 C). Besides cell migration and adhesion targets, other invasion markers were also assessed. The invasion marker, bone morphogenic protein (BMP2) [ 22 ] was ∼2-fold upregulated in AM-1 tumouroids with a bone stroma compared to a fibroblast stroma (p < 0.05) and an acellular stroma (p < 0.05) ( Fig. 4 F). The invasion and metastasis marker, the signal transducer and activator of transcription 3 (STAT3) [ 23 ] was significantly upregulated with a bone stroma compared to a fibroblast stroma (p < 0.005) ( Fig. 4 G). Matrix remodelling ability of the tumour cells is dependent upon their stroma Tumour cells rely on the interactions with their ECM during cell migration and invasion. There are ∼300 unique matrix macromolecules such as collagens, proteoglycans and glycoproteins including laminins. Remodelling of the basement membrane, which is mainly composed of collagen IV and laminins, is essential for tumour invasion [ 24 ]. The four main mechanisms of tumorigenic ECM remodelling are ECM deposition, chemical modifications, proteolytic degradation and force-mediated physical remodelling [ 24 ]. Therefore, the next set of analyses was based on changes related to matrix remodelling targets. The heatmap for the expression of ECM Proteoglycans targets in AM-1 cells in tumouroids showed varied enrichment levels in particular with the addition of a bone stroma. Certain ECM proteoglycan genes such as the metastatic marker amyloid precursor protein (APP) [ 25 ] was significantly upregulated in the presence of a bone stroma. AM-1 cells in the presence of a fibroblast stroma exhibited the greatest enrichment for ECM proteoglycan targets compared to a bone stroma and an acellular stroma ( Fig. 5 A). 83.3 % of the genes altered in AM-1 cells within a fibroblast stroma were upregulated, where this percentage of upregulated genes was only 28.6 % when a bone stroma was present. Overall, 50 % of the ECM proteoglycan genes were altered by introducing stromal cells ( Supplemental Table 2 and Fig. 6 A). A similar pattern was observed in ECM interaction targets as well as the matrix remodelling targets ( Fig. 5 B&C). Introduction of a fibroblast stroma induced a 57.1 % increase among the altered ECM interaction pathway genes in AM-1 tumour cells, whereas in the presence of a bone stroma there was only a 33.3 % increase. The percentage of genes altered, specifically the ECM interaction pathways, in AM-1 cells by the addition of stromal cells was 40.7 % ( Supplemental Table 3 ) and in the matrix remodelling pathway this was 40.0 % ( Supplemental Table 4 ). Addition of either a bone or fibroblast stroma caused significant upregulation of ECM genes involved in tumour progression [ 26 , 27 ] including Integrin αvβ6 (ITGB6) and ITGB4 ( Fig. 6 A&B). The epithelial-to-mesenchymal transition marker that is highly expressed in primary and metastatic cancers, CD44 [ 28 ], was significantly upregulated where a fibroblast stroma was present compared to a bone stroma (∼2-fold) (p < 0.0005) ( Fig. 5 D). The expression of a metastasis marker, the laminin subunit beta-3 (LAMB3,) was ∼3-fold higher with the fibroblast stroma compared to a bone stroma (p < 0.0005) ( Fig. 5 E). Among matrix remodelling targets, the expression of collagen genes such as collagen type 3 Alpha 1 Chain ( COL3A1) and COL6A3 in AM-1 tumouroids with a fibroblast stroma were higher compared to acellular stroma and bone stroma ( Fig. 5 C). The matrix remodelling gene Filamin A (FLNA) [ 29 ], was significantly upregulated where a bone stroma was present compared to an acellular stroma (p < 0.05) ( Fig. 5 F). Increasing stromal complexity induced enrichment of immune markers by AM-1 tumour cells The ECM remodelling by tumour cells influences the inflammatory tumour environment. Components of the ECM act as inflammatory stimuli and drive immune response [ 24 ]. Therefore, from the cancer transcriptome, the immune pathways have a significant role in understanding how tumour cells communicate with their stroma. The heatmap of the immune system pathway indicate enrichment of the targets by AM-1 cells in the presence of both a bone stroma and a fibroblast stroma compared to an acellular stroma ( Fig. 7 A). Addition of either a fibroblast or bone stromal compartment to the AM-1 tumouroid induced changes in the expression of 49.3 % of genes in the immune system pathway compared to an acellular stroma ( Supplemental Table 5 ). In particular, the fibroblast stroma induced a significant upregulation in 54.9 % of the significantly changed immune system pathway genes in AM-1 cells compared to where an acellular stroma was present. Of the genes that were differentially expressed in the presence of different stromal compartments, 85.05 % were higher where a fibroblast stroma was present. Whereas the presence of a bone stroma resulted in significant changes to 40.6 % of all immune genes, of which 81 % were downregulated ( Supplemental Table 5 ) and ( Fig. 7 B). The presence of stromal cells resulted in the upregulation of certain oncogenes and downregulated the expression of tumour suppressors, which are part of the immune system pathways. The oncogene, MYC [ 30 ] was ∼2-fold upregulated in AM-1 tumouroids with a fibroblast stroma (p < 0.005) or a bone stroma (p < 0.005) compared to an acellular stroma ( Fig. 7 C). The expression of another oncogene, Superoxide Dismutase 1 (SOD1) [ 31 ] was significantly higher in AM-1 cells cultured with a bone stroma compared to an acellular stroma ( Fig. 7 D). The tumour suppressor markers early growth response 1 (EGR1) ( Fig. 7 E) and dual specificity phosphatase 6 (DUSP6) ( Fig. 7 F) [ 32 ] were downregulated by ∼2-fold in the presence of a bone stroma compared to a fibroblast stroma (p < 0.005). The expression of EGR1 was also significantly lower where a bone stroma was present compared to an acellular stroma (p < 0.005) ( Fig. 7 E).

Discussion Developing 3D models that recapitulate tumour-stroma interactions are essential for modelling the biomimetic tumour microenvironment in vitro . 3D tumouroid models allow compartmentalisation where different cell types can be added to distinct compartments to increase model complexity. In these complex tumouroids, mixed cell populations are pooled and then analysed for gene and protein markers [ 11 , 33 ]. To date, spatial profiling of the multicompartment 3D models have not been explored. It is difficult to study how the introduction of specific stromal compartments alters or affects tumour cells. This study is the first to capture the region of interest within a bioengineered 3D model and specifically analyse the tumour-stroma boundary. Bioengineered tumouroids are the first 3D in vitro tumour model to be analysed using spatial transcriptomics. Key to this is the sample preparation of spatial transcriptomics which requires embedding and sectioning of the sample. There are limited 3D models that can be processed for histology [ 11 , 34 , 35 ]. Frozen sectioning is used for spheroid models [ 36 ]. It is also important to consider the fact that the cell number of 3D models are much lower than normal tissue, and this makes it difficult to section the area of interest. This study described a novel protocol for how to utilise 3D tumouroids for spatial transcriptomics analysis. Within tumouroids the tumour borders of the tumour mass are visible by eye, thus locating the tumour stroma boundary within the tumouroids is possible during sectioning. This study assessed changes in the cancer transcriptome of the tumour cells within the 3D tumouroids as the stromal complexity increased. The regions of interests were the boundary between the ameloblastoma tumour mass and the surrounding stromal compartment. By focusing on this region, it was possible to understand the changes in the tumour cells that are invading into the surrounding stroma. The volcano plots generated from the spatial data showed that there are changes in the expression of specific genes in AM-1 tumour cells with different stroma ( Fig. 3 ). Following generation of volcano plots and heat maps, several pathways from the cancer transcriptome were identified as being significantly altered by the introduction of different stroma. Initially, the changes in the invasion pathway targets were compared to the invasion distance data. The introduction of a fibroblast stroma caused upregulation in invasion markers including MMP3 [ 21 ] and this upregulation was in line with the observed and quantified increase in the invasion distance of AM-1 tumouroids where a fibroblast stroma was present compared to an acellular stroma and a bone stroma. MMPs are well-studied in the case of ameloblastoma, however there is not much data on MMP-3 and most of the reported literature is on MMP-2, -7, and -9 [ 37 , 38 ]. Therefore, this study suggests MMP-3 as an invasive marker for ameloblastoma. The reason for not observing a change in other known MMPs may be because some of these are involved in the earlier stages of invasion. Although AM-1 cells invaded the shortest distance into a bone stroma, several invasion genes and metastasis genes such as RHOA, BMP2 and STAT3 were upregulated. These markers are associated with later migration compared to MMPs. For example, BMP-2 has been associated with tumour progression in the late stages of gastric cancer [ 39 ]. Invasion and matrix remodelling are closely linked [ 24 ], therefore it is essential to understand how genes in specific pathways change by adding different stromal cells. Tumour cell-influenced matrix remodelling prepares the TME for tumorigenesis and metastasis. Tumour cells can cause direct or indirect breakdown of the ECM to invade or migrate quicker [ 24 ]. ECM features such as porosity, crosslinking and density also affect cell migration [ 40 ]. All these properties were altered with the addition of either a bone or fibroblast stromal compartment within AM-1 tumouroids. Fibroblast stroma led to the greatest enrichment in ECM remodelling targets compared to bone stroma ( Supplemental Table 4 ). This clearly correlated with measured invasion into the fibroblast stroma ( Fig. 4 B). Collagen alignment aids the invasion of tumour cells and collagen chains modulate tumour formation and metastasis [ 41 , 42 ]. EMT enhances tumour cell mobility, invasion, and metastasis, therefore upregulation of CD44 with a fibroblast stroma ( Fig. 5 D) is expected when taking into consideration the corresponding invasion distance data ( Fig. 4 B). Our data shows that the bone stroma induce changes in AM-1 cells in some of the matrix remodelling genes such as COL27A1, a gene that is overexpressed by tumour cells and induces ECM production [ 43 ]. This might be associated with slow migration of the AM-1 cells into the bone stroma compared to into a fibroblast and acellular stroma. Finally, introducing stromal cells induced high enrichment in pathways related to immune system ( Fig. 6 A). Similar enrichment has recently been reported in invasive seminoma germ cell tumours [ 44 ]. Upregulation of the oncogene MYC in the presence of either stromal cell, indicated the importance of increasing the complexity of 3D models. Interestingly, the bone stroma induced the downregulation of tumour suppressor genes within AM-1 cells. It is known that tumour enrichment of tumour markers are linked to enrichment of immune markers [ 7 ]. This study highlights how tumour cells are affected and influenced by specific stromal cells within their micro-environment. As tumour cells come into contact with a stromal cell or sense changes in the stroma, significant changes occur. The fact that it is possible to process 3D tumouroids using methods similar to tissue samples with optimised protocols along with the ability to conduct spatial analysis, highlight the power of this bioengineered 3D model. The spatial transcriptome data has been used to profile the tumour-stroma boundary within the 3D models. Prior to this work, it was not possible to dissect out and analyse CK + cells or from a mixed cell population in 3D tumouroid. This technique allows for the capture of a region of interest, namely the tumour-stroma boundary. This work will guide future studies that are interested in the applications of spatial transcriptomics in vitro 3D models.

Stromal cells are key components of the tumour microenvironment (TME) and their incorporation into 3D engineered tumour-stroma models is essential for tumour mimicry. By engineering tumouroids with distinct tumour and stromal compartments, it has been possible to identify how gene expression of tumour cells is altered and influenced by the presence of different stromal cells. Ameloblastoma is a benign epithelial tumour of the jawbone. In engineered, multi-compartment tumouroids spatial transcriptomics revealed an upregulation of oncogenes in the ameloblastoma transcriptome where osteoblasts were present in the stromal compartment (bone stroma). Where a gingival fibroblast stroma was engineered, the ameloblastoma tumour transcriptome revealed increased matrix remodelling genes. This study provides evidence to show the stromal-specific effect on tumour behaviour and illustrates the importance of engineering biologically relevant stroma for engineered tumour models. Our novel results show that an engineered fibroblast stroma causes the upregulation of matrix remodelling genes in ameloblastoma which directly correlates to measured invasion in the model. In contrast the presence of a bone stroma increases the expression of oncogenes by ameloblastoma cells. Graphical abstract 3D model set-up for GeoMx DSP. Keywords

Limitations The main limitation is that the GeoMx DSP does not have the same specificity as the single cell sequencing since the platform has 1–10 cells in each spatial spot for analysis. Future steps, will include comparing the transcriptome of ameloblastoma in different locations within the tumouroids, for instance deep within the hypoxic core of the tumour mass, or invasive cells within the stroma. The spatial analysis of the whole 3D tumouroid model will enable us to understand the differences in expression patterns within the tumouroid. Ethics approval and consent to participate Not Applicable. Consent to publish Not Applicable. Availability of data and materials The authors confirm that data and material in this study are presented in main manuscript. Funding D.B. receives funding from BISS Charitable Foundation . G.A. receives funding from 10.13039/501100000266 EPSRC , 10.13039/100015980 EP /W522636/1. CRediT authorship contribution statement Deniz Bakkalci: Conceptualization, Formal analysis, Investigation, Methodology, Visualization, Writing - original draft, Writing - review & editing. Georgina Al-Badri: Data curation, Formal analysis, Methodology, Writing - review & editing, Software. Wei Yang: Methodology, Software. Andy Nam: Formal analysis, Methodology. Yan Liang: Methodology, Software. Syed Ali Khurram: Conceptualization. Susan Heavey: Conceptualization, Methodology. Stefano Fedele: Conceptualization, Resources, Funding acquisition. Umber Cheema: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Project administration, Supervision, Validation, Visualization, Writing - review & editing. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Abbreviations AM Ameloblastoma AOI Area of Illumination (AOI) APP Amyloid Precursor Protein BPE Bovine pituitary extract BMP2 Bone Morphogenic Protein 2 CK Cytokeratin COL3A1 collagen type 3 Alpha 1 Chain DMEM Dulbecco's modified Eagle medium DSP Digital Spatial Profiling DUSP6 Dual specificity phosphatase 6 (DUSP6) ECM Extracellular matrix EGR1 Early Growth Response FBS Foetal bovine serum HGF Primary gingival fibroblasts hOB Human osteoblasts IF Immunofluorescence ITGB6 Integrin αvβ6 (ITGB6) H&E Haematoxylin and eosin KRT5 Keratin 5 LAMB3 laminin subunit beta-3 LOQ Limit of Quantitation MEM Minimal Essential Medium MIQE Minimum Information for Publication of Quantitative Real-Time PCR Experiments MMPs Matrix metalloproteinases M Molar Min Minutes N.A Neutralising agent MMP3 matrix metalloproteinases 3 MRC5 Human lung fibroblasts PanCK Pan Cytokeratin PTHLH Parathyroid Hormone Like Hormone RANK The tumour necrosis factor (TNF) superfamily members receptor activator of nuclear factor kappa-B receptor RANKL The tumour necrosis factor (TNF) superfamily members receptor activator of nuclear factor kappa-B ligand (TNFSF11) ROCK1 Rho-associated protein kinase ROI Region of Interest RT Room temperature SD Standard deviation SEM Standard error mean SOD1| Superoxide Dismutase 1 STAT3 the signal transducer and activator of transcription 3 TGF-β Transforming growth factor THBS1 Thrombospondin 1 TME Tumour microenvironment TNF Tumour necrosis factor Supplementary data The following is the Supplementary data to this article. Data availability No data was used for the research described in the article. Acknowledgements H&E staining was conducted with the guidance of UCL IQPath.

CC BY

no

2024-01-16 23:43:48

Mater Today Bio. 2023 Dec 21; 24:100923

oa_package/e0/2f/PMC10788620.tar.gz

PMC10788621

38226015

Introduction The human body is a highly complex system composed of heterogenous tissues and organs. When the body encounters its limits in regeneration capabilities, donor tissues and organs are needed. One of the most essential senses for humans is vision. Clear vision is provided by the human cornea which is the outermost layer of the eye [ 1 ]. If the cornea is damaged, it can lead to corneal blindness. Losing vision has serious effects on the quality of life of individuals, affecting their independence, employment, mental health and social function [ 2 ]. The human cornea is one of the most transplanted tissues, and yet there is a severe shortage of donor corneas for treating corneal blindness. In fact, only 1 patient out of 70 in need receives the donor cornea, creating a serious need for artificial corneas [ 3 ]. The corneal stroma comprises 90 % of the human cornea and has the key role in transparency and mechanical strength providing clear vision. These crucial features are based on the highly organized collagen type I fibrils which are arranged in layers perpendicular to each other. Human corneal stromal keratocytes (hCSKs) grow between the collagen fibrils, maintaining the corneal stroma and its properties [ 1 ]. Thus, it is essential to mimic this complex and precise microstructure to fabricate artificial corneas to benefit the patients in need. Three-dimensional (3D) bioprinting has become the state-of-the-art biofabrication technology to manufacture artificial tissues with the cellular architecture and spatial organization mimicking the native tissues. In 3D bioprinting, a bioink composing of cells and biomaterials is printed layer-by-layer based on a pre-designed 3D model in automated and repeatable manner [ 4 ]. Therefore, 3D bioprinting technology offers a highly potential solution to the severe shortage of donor corneas. Several 3D bioprinting technologies have been explored to fabricate the human cornea, including extrusion-based [ 5 , 6 ], inkjet-based [ 7 ], laser-assisted [ 8 ] and stereolithographic bioprinting [ 9 , 10 ]. Prior research in corneal 3D bioprinting shows that several technical aspects of fabricating artificial corneas are well-established. However, many previous studies focus on the curved shape of the cornea [ 5 , 7 , 11 , 12 ], or its mechanical and optical properties [ 10 ], and fail to show efficient tissue formation after printing. Importantly, the field lacks research in mimicking the heterogenous microstructure of the corneal stroma, including the detailed organization of the collagen fibrils essential for clear vision. Therefore, novel strategies are needed to combine the mechanical stability with hierarchical composition of the native corneal stroma in corneal tissue engineering (TE). Even though 3D bioprinting has tremendous potential for regenerative medicine, novel multi-material solutions combining multiple biomaterials into one structure is required to mimic the highly heterogenous composition of native tissues [ 13 , 14 ]. Widely accepted method to fabricate heterogenous 3D constructs is to combine thermoplastic polymer, such as polycaprolactone (PCL), with a hydrogel bioink [ [15] , [16] , [17] ]. As an emerging technology, melt-electrowetting (MEW) has been explored to fabricate thermoplastic polymer framework with high organization to mimic the corneal stroma [ 18 ], and it can also be combined with hydrogel-based bioinks in bioprinting [ 19 ]. Thermoplastic polymer frameworks provide mechanical support and can guide cellular growth, making it a potential strategy to mimic the organization of the corneal stroma. However, the use of thermoplastic polymers in cornea TE is limited by the requirements for the transparency [ 20 ]. Moreover, they often require surface modification to demonstrate sufficient cell attachment [ 21 ]. To fabricate heterogenous structures without thermoplastic polymers, it is possible to print different bioinks or cell types in different layers of the 3D construct [ 22 , 23 ]. Bioprinting alternating layers of bioinks with different compositions has been previously explored for cornea using laser-assisted bioprinting [ 8 ]. However, the precise organization of corneal stromal fibrils and cellular organization within layers cannot be achieved with this approach. More recent approaches to achieve cellular organization include encapsulating mechanically fragmented electrospun microfibers within gelatin-methacrylamide (GelMA) [ 24 ] and patterning cells ultrasonically in alginate or GelMA [ 25 ]. Nevertheless, these methods have not been applied to corneal TE. In addition, even though these methods support cell alignment, the drawbacks include a decrease in the transparency [ 24 ], and the lack of sufficient tissue formation [ 24 , 25 ]. Moreover, a question remains in the mechanical stability and handling of the structures which enables transplantation [ 25 ]. Here, we developed a novel strategy for multi-material 3D bioprinting to manufacture native-like tissue constructs with heterogenous design that can withstand handling. To the best of our knowledge, multi-material approach has never been applied in corneal stroma bioprinting. The developed strategy was applied to bioprinting of a cell-laden and acellular hyaluronic acid (HA) -based bioink and human adipose tissue -derived stem cells (hASCs). The bioinks had different crosslinking densities, and thus, different stiffnesses. The heterogenous design of the 3D structures was inspired by the native corneal stromal microstructure. Therefore, to mimic the organization of collagen fibrils and corneal stromal cells, the cell-laden and acellular bioink with different stiffnesses were printed as alternating filaments in perpendicular layers to create composite structures. Bioinks were characterized, and the mechanical properties, transparency, handling and swelling of the bioprinted structures were investigated. Cell orientation and growth as well as tissue formation within the bioprinted composite structures were studied to evaluate the ability of the multi-material bioprinting strategy to mimic the heterogenous microstructure of native corneal stroma. Finally, the feasibility of the composite structure for corneal TE in an ex vivo porcine corneal organ culture model was demonstrated.

Materials and methods Synthesis of the crosslinking components HA-Aldehyde (HA-ALD) was synthesized according to the previously reported protocol [ 26 ]. The synthesis of HA with dopamine and carbohydrazide modification (HA-DA-CDH) was conducted as reported previously [ 27 ]. The synthesized and lyophilized components were stored at −20 °C before use. Preparation of the bioinks The bioinks were mixed as previously reported [ 28 ] with slight modifications. Briefly, the crosslinking components HA-DA-CDH and HA-ALD were diluted in 1 X PBS (Dulbecco's Phosphate Buffered Saline, DPBS, Carl Roth). For the soft bioink, both components were dissolved into concentration of 9 mg/ml, whereas for the stiff bioink concentration of 14 mg/ml was used. For printing hASCs, the cells were resuspended in the desired volume of cell culture medium and mixed into the soft bioink. 3D bioprinting setup After mixing, the bioinks were transferred in 30 cc barrels (Nordson EFD) with pistons and 32 G blunt needles (0.5′′, CELLINK). Before printing, the soft and stiff bioinks were pre-crosslinked for 70 min and 40 min, respectively. Pre-crosslinking times were optimized for bioinks based on the difference in crosslinking component concentrations and crosslinking rates to obtain optimal biofabrication window. Printing was done with extrusion-based bioprinter 3D-Bioplotter (EnvisionTEC) on 35 mm petri dishes (TC-treated, Corning®) at room temperature (20 °C). The 3D models with 80 μm slicing interval were created with Perfactory RP software. The inner structures of the printed layers were designed in Visual Machines software. The printing pressure and speed for soft and stiff bioinks were 1.0 bar and 4.0 bar, and 7 mm/s and 6 mm/s, respectively. The pre-flow values of the soft and stiff bioinks were set to 0.1 s and 0.3 s, and the post-flow values to 0.1 s and 0.2 s, respectively. The biofabrication window of 1 h was obtained for both bioinks. The printed structures were stabilized at 37 °C with 5 % CO 2 at humid environment before adding cell culture medium or 1 X PBS to cover the structure. Bioink characterization To analyze the printability and shape fidelity of the bioinks, grids with six perpendicular layers and 2.5 mm distance between filaments were printed and analyzed immediately after printing and after 7 days as described previously by Mörö et al. [ 28 ]. The thickness of the filaments and the pore factors of the grids were determined from the images by using ImageJ Fiji software. Nine filaments as well as six pores from four grid replicates were analyzed in both timepoints (n = 4). Shear-thinning properties of the bioinks, including cell-laden soft bioink, were analyzed by measuring their viscosities with HR-2 Discovery hybrid rheometer (TA Instruments). Continuous flow rate with shear rate ranging from 0.01 to 10 s −1 and 20 mm parallel plate geometry with 1 mm gap were used. The bioinks were prepared as described above. The measurements were carried out within 1 h after starting the first measurement, 500 μl bioink sample size was used, and three replicates per bioink were measured (n = 3). The transparency of the bioinks was analyzed by measuring their transmittance with a UV/VIS spectrophotometer (Lamda 35 UV/VIS Spectrophotometer, Perkin Elmer). The bioinks were prepared as described above. Before 1 h pre-crosslinking, the bioinks were transferred into cuvettes and centrifuged at 1000 g for 1 min to remove excess air. Air was used as blank in the transmittance measurements. Sufficient adhesion between two bioinks is crucial for the handling and structural stability of the bioprinted construct. In a simple gel block fusion test, the examined hydrogel disc is cut in half using a scalpel, followed by rejoining the pieces back together and observing the healing process visually [ 29 ]. The bioinks were prepared as described above, and red food dye was mixed to the stiff bioink to a concentration of 4.2 μl/ml. Soft and stiff bioinks were pre-crosslinked in syringes for 24 h. Thereafter, the gel discs were pushed out and cut in half, and the halves from different bioinks were combined. After 24 h of self-healing at room temperature, the adhesion between the halves was studied visually and by lifting the structures with a spatula and pulling the halves apart with tweezers. The adhesion was further studied by conducting compression tests with HR-2 Discovery hybrid rheometer as described by Mörö et al. [ 28 ]. The halves from different bioinks (soft + stiff) were combined and after 24 h, axial compression with 12 mm parallel plate geometry and displacement rate of 1 mm min −1 was carried out. Same measurements were conducted to soft + stiff disk immediately after joining the halves, as well as uncut disks from soft and stiff bioinks. All measurements were carried out in triplicates (n = 3). The force curves were plotted against compression percentage. Cell culture Due to the abundancy and immunomodulatory properties [ 30 ], differentiation capability towards hCSKs [ [31] , [32] , [33] , [34] , [35] , [36] ], potential in preserving the corneal transparency [ 37 ] and promising results from human clinical studies for treating corneal stroma pathologies [ 38 , 39 ], hASCs were selected as a cell source in this study. The hASCs were isolated from subcutaneous adipose tissue samples. The isolation, expansion and characterization of the hASCs has been previously described by Refs. [ 8 , 40 ]. Thereafter, hASCs were cultured in basic medium (BM) composed of DMEM/F-12 supplemented with 5 % human serum (Serana), 1 % penicillin/streptomycin (GibcoTM) and 1 % Glutamax (Thermo ScientificTM) at 37 °C with 5 % CO 2 . The hASCs were cultured and passaged in T75-flasks (NuncTM EasYFlaskTM, Thermo Scientific) until used for printing at passage 5 with a cell density of 9×10 5 cells ml −1 in the soft bioink. The printed cell-laden structures were cultured in BM. Printing of the 3D structures The printing setup used for bioprinting of 3D structures is described in section 2.3 . The different bioinks used for bioprinting are summarized in Fig. 1 (a). Four cylindrical 3D models were designed for different analyses ( Fig. 1 (b)). The 3D models were bioprinted with the bioinks into uni-material structures ( Fig. 1 (c)) and multi-material structures that are from here on referred to as composites ( Fig. 1 (d)). For stability and handling tests, acellular soft-only uni-material structures and acellular soft + stiff composites were printed. For analyzing mechanical properties and swelling behavior, acellular soft-only and stiff-only uni-material structures as well as acellular and cell-laden soft + stiff composites were printed. For exploring the visual transparency, cell-laden soft composites and soft + stiff composites were printed. For transmittance measurements, acellular and cell-laden soft + stiff composites were printed. For determining cytocompatibility, cell-laden soft composites and soft + stiff composites were printed. For characterizing filament structure, cell-laden soft + stiff composites were printed. In ex vivo organ culture, cell-laden soft + stiff composites were used. For all printed structures, the inner pattern of one printed layer was a continuous filament, and the filaments were printed perpendicularly in alternating layers. The filament strand distance was 0.35 mm in uni-material structures and 0.7 mm for alternating filaments in composites. Two contours with 0.2 mm distance were printed in each 3D structure. In composites, the contours were printed from the acellular stiff or soft bioink. The stabilization time was 90 min for all 3D structure types. Analysis of the 3D structures The stability and handling of the bioprinted structures in 1 X PBS was analyzed after 7 days post-printing. For the analysis, the PBS was removed, and the structures were handled with a spatula. The stability of the printed structures was evaluated visually. Visual transparency of the structures was analyzed after 1 and 7 days post-printing. The structures were cultured in BM and rinsed with 1 X PBS before taking photographs against a paper with text in natural lighting. Transparency was further studied with absorbance measurements of acellular and cell-laden composites after 1 and 7 days post-printing. After culturing the structures in BM, 5 mm cylindrical pieces were punched, rinsed with 1 X PBS and measured on 96 well plate with Spark® multimode plate reader (Tecan) at wavelength range of 400–700 nm. Measurements were carried out in triplicates (n = 3). The transmittance values were calculated from absorbance values as described previously by Kim et al. [ 41 ] and Kutlehria et al. [ 10 ]. PBS was used as control. The mechanical properties of four structure types cultured in BM were assessed with HR-2 Discovery hybrid rheometer by measuring the amplitude and frequency sweeps on day 1, 7 and 14 after printing. 12 mm parallel plate geometry with a gap of 1 mm was used. Amplitude sweeps were performed with constant frequency of 1 Hz and the oscillation strain ranging from 0.01 % to 50 %. Frequency sweeps were performed with frequency ranging from 0.1 Hz to 10 Hz and with a constant strain of 1 % based on the amplitude sweeps. Amplitude sweeps were performed once per structure type per timepoint, and frequency sweeps were performed in triplicates (n = 3). The printed structures were trimmed before measuring to prevent over- or underfilling. Swelling behavior of four structure types was analyzed by weighing the structures on petri dishes on day 1, 7 and 14. The initial weight was determined by measuring the weight of the printed structure after 1 h stabilization period and 30 min immersion period in BM. All the measurements were done in triplicates (n = 3). To evaluate the post-printing stability of the soft and stiff filaments within the composites, soft + stiff composites with 0.5 μm fluorescent particles (yellow-green, FluoSpheresTM, Invitrogen) were printed. Fluorescent particles were mixed in the soft bioink as 0.17 % (v/v). The printed structures in 1 X PBS were imaged after 1 and 7 days post-printing with Leica Dmi8 (Leica Microsystems). From the z stack images, three layers were separated and converted as maximum intensity projections (MIPs) to illustrate the formation and stability of the soft filaments within the composites. The image editing was done in ImageJ Fiji. Cell viability and proliferation evaluation Cell viability and proliferation in the printed structures was evaluated with LIVE/DEAD® Viability/Cytotoxicity Kit for mammalian cells (Thermo Fischer Scientific) and PrestoBlueTM viability assay (Thermo Fischer Scientific). These analyses were performed on two cell-laden composites. LIVE/DEAD staining was performed on day 1 and 7 after printing, and PrestoBlueTM assay on day 1, 7 and 14. LIVE/DEAD staining was carried out according to the instructions from the manufacturer [ 42 ]. After 30 min incubation at 37 °C, the samples were imaged with confocal microscope (LSM 800, Zeiss). PrestoBlueTM staining was carried out according to the manufacturer's instructions [ 43 ]. After 1 h incubation at 37C°, the absorbance of three replicates (n = 3) was measured with a multiplate reader (Victor2 Microplate reader, Perkin Elmer). Immunofluorescence staining To analyze the cell morphology and maturation as well as tissue formation after printing, immunofluorescence (IF) staining with phalloidin-tetramethylrhodamine B isothiocyanate (Sigma-Aldrich) and anti-connexin 43 (rabbit, Sigma-Aldrich) were used. Phalloidin stains the actin of the cytoskeleton and connexin 43 stains the gap junctions between cells. In addition, Hoechst 33,342 (Invitrogen) was used to stain the cell nuclei. The cell morphology and tissue formation were analyzed from the two cell-laden composites. Printed samples were fixed on day 1, 7 and 14 after printing with 4 % paraformaldehyde for 1 h at room temperature, followed by washing again with 1 X PBS three times. Thereafter, the fixed samples were immersed in 5 % bovine serum albumin (BSA, Sigma) in 1 X PBS with 0.1 % Triton X-100 (Sigma) over night at room temperature for permeabilization and blocking. Primary antibody solution with anti-connexin 43 1:100 was prepared in 5 % BSA in 1 X PBS, and the samples were incubated at 4 °C for 3 days. Next, the samples were washed with 1 X PBS for 2 days. Secondary antibody solution containing anti-rabbit Alexa 488 (Molecular Probes) 1:400, phalloidin 1:100 and Hoechst 1:1200 was prepared in 5 % BSA in 1 X PBS, and the samples were incubated at room temperature overnight. Finally, the samples were washed again with 1 X PBS for 1 day and mounted with Vectashield® Antifade Mounting medium (Vector Laboratories) on glass bottom dishes (MatTek). The samples were imaged with Zeiss confocal microscope and the z stack images were deconvoluted with Huygens Essential software (Scientific Volume Imaging) and edited in ImageJ Fiji as MIPs. 3D views of the stack images were visualized in Imaris (Oxford Instruments). Porcine cornea ex vivo organ culture and analysis The porcine cornea ex vivo organ culture model was used as a transplantation platform as previously described with slight modifications [ 8 , 27 ]. After porcine corneas were dissected from the eyes in aseptic conditions and disinfected, they were cultured in BM supplemented with 0.25 μg/ml amphotericin B (Thermo Fisher Scientific) at 37 °C with 5 % CO 2 overnight. On the next day, cell-laden soft + stiff composites with yellow-green fluorescent particles as 0.17 % (v/v) in the stiff bioink and hASCs in soft bioink were printed. The structures were allowed to stabilize 4 h at 37 °C with 5 % CO 2 before transplantation into dissected porcine corneas. Transplantation was carried out on a Barron artificial anterior chamber (Katena products Inc., USA). A crescent knife (Bauch&Lomb Inc. USA) was used to make a stromal pocket to the center of the cornea and a 5 mm piece of the composite was punched and transplanted into the pocket. The printed structures were further stabilized in the pockets for 2 h before immersing corneas in BM. The ex vivo organ culture was carried out for 14 days (n = 5). Porcine cornea without stromal pocket was used as control (n = 1). For analysis, the corneas were fixed with 4 % PFA solution for 3 h at RT, washed with 1 X PBS for 2 h and immersed in 20 % sucrose solution overnight at 4 °C. On the next day, the corneas were transferred from sucrose to Tissue-Tek OCT (Science Services, Germany) and incubated overnight at 4 °C. Thereafter, the corneas were snap frozen at liquid nitrogen and stored at −80 °C. Cryosections of 10 μm were prepared with a microtome on EprediaTM SuperfrostTM Plus slides (Epredia). The cryosections were air-dried for 30 min before IF or hematoxylin and eosin (H&E) staining. Mouse anti-human STEM121 (Takara) 1:80 primary antibody was used in IF staining to detect printed hASCs in porcine cornea ex vivo organ cultures after transplantation. Secondary antibody solution contained anti-mouse Alexa 647 (Molecular Probes) 1:400, phalloidin 1:100 and Hoechst 1:1000. The cryosections were mounted with ProlongTM Gold Antifade Mountant (Invitrogen) and imaged with Leica Dmi8. H&E staining was done with KD-RS3 automatic slide stainer (KEDEE) with a standard protocol for cryosections, with Mayers hematoxylin Plus (Histolab) and 0.2 % eosin (Histolab) incubations of 3 min and 30 s, respectively. After staining, the cryosections were mounted with DPX new mounting medium (Sigma-Aldrich) and DAKO coverslipper (Agilent) and imaged with Nikon Eclipse TE200S microscope (Nikon Instruments). Statistical analysis The statistical significance of shape fidelity analysis, frequency sweeps and PrestoBlueTM cell proliferation analysis were determined by Mann-Whitney U test. P -values ≤0.05 were considered statistically significant. SPSS software (IBM) was used for the statistical data analysis. All data is presented as mean values with ±standard deviation. Ethical issues This study was conducted under approvals from Regional Ethics Committee of the Expert Responsibility area of Tampere University Hospital that allow to extract and use hASCs for research purposes (R15161).

Results Both bioinks demonstrate excellent printability and shape fidelity The printability was assessed from grid structures. The grids were clear, and the filaments were uniform with both bioinks ( Fig. 2 (a)). The used printing pressure of the stiff bioink was 4-times higher than the pressure of the soft bioink. After 7 days in PBS, the grids were still visible and intact, indicating great shape fidelity. Shape fidelity was further assessed by analyzing filament thickness ( Fig. 2 (b)) and pore structure of the grids ( Fig. 2 (c)). The filament thicknesses on day 0 and 7 were 0.38 ± 0.04 mm and 0.44 ± 0.03 mm for the soft ink, respectively, and 0.31 ± 0.03 mm and 0.42 ± 0.06 mm for the stiff ink, respectively. The filament thickness of the stiff bioink on day 0 was significantly lower compared to the soft bioink (p ≤ 0.05), which indicates better shape fidelity during printing. The filament thickness of both bioinks increased during the 7 days due to swelling and there was no significant difference between the filament thicknesses of the bioinks on day 7 (p ≤ 0.05). The Pr demonstrates the shape of the pore, with Pr = 1 indicating perfect rectangular shape and Pr < 1 indicating more circular shape. The Pr of the soft bioink was significantly lower (p ≤ 0.05) compared to the Pr of the stiff bioink on both day 0 and 7 ( Fig. 2 (c)). This indicates more circular shape of pores for the soft bioink, which is supported by the images of the grid structures ( Fig. 2 (a)). On day 0, the Pr values of the soft and stiff bioinks were 0.87 ± 0.01 and 0.94 ± 0.02, respectively. On day 7, the Pr values of the bioinks decreased to 0.84 ± 0.01 and 0.90 ± 0.02, respectively. Even though the decrease in the Pr values demonstrate the pores becoming more circular due to filament swelling, the Pr values remained close to 1. Both bioinks demonstrated shear-thinning properties as the viscosity decreased when the shear rate was increased ( Fig. 2 (d)). The peak viscosities of the soft and stiff bioinks were 99 ± 152 Pa s and 1628 ± 1339 Pa s, which indicates that the material is softer and easier to extrude. Thus, the soft bioink demonstrated more suitable rheological properties for cell printing since high printing pressure was not required to initiate extrusion of the material. To compare, the viscosity of the stiff bioink was over 10-times higher than the one of the soft bioink. Nevertheless, the viscosity of the stiff bioink decreased when the shear rate was increased, and therefore the excellent printability shown in Fig. 2 (a) was supported by the viscosity measurements. However, higher viscosity of the stiff bioink indicates high shear stress when printing, which is supported by the printing pressure data. Therefore, the stiff bioink was not chosen for cell printing with high resolution printing needle. Importantly, the addition of cells to the soft bioink did not hamper its shear-thinning properties ( Fig. 2 (d)) nor significantly alter the peak viscosity where it was 92 ± 125 Pa s for the cell-laden soft bioink. The transparency of the bioinks was analyzed by measuring their transmittance ( Fig. 2 (e)). The transmittance of the soft and stiff bioinks was 75–97 % and 70–92 %, respectively, within the visible light wavelength range. The higher crosslinking density of the stiff bioink decreased the transmittance value slightly compared to the soft bioink but the difference was not significant and both bioinks demonstrated excellent transparency. The adhesion between the two bioinks was studied with a gel block fusion test by combining gel disk halves from soft and stiff bioink together ( Fig. 2 (f)). After 24 h, the disk halves were firmly attached to each other. The adhesion between them was strong enough to hold the structure's own weight when lifted with a spatula and to prevent rupturing when the structure was pulled apart with tweezers. Furthermore, when further evaluating the adhesion between the soft and stiff bioinks with a compression test, the gels with 0 h adhesion were notably weaker compared to gels with 24 h adhesion ( Fig. 2 (g and h)). After 24 h adhesion, the axial force and compression percentage at the breaking point were 0.19 ± 0.06 N and 51.4 ± 3.6 %, respectively. After 0 h adhesion, the axial force and compression percentage at the breaking point were 0.13 ± 0.003 N and 31.5 ± 1.9 %, respectively. Thus, the gels withstood higher axial force as well as deformation after 24 h adhesion. This data together with the gel block fusion test demonstrates sufficient adhesion between the different bioinks, and thus, bioink filaments of the printed 3D composite. Due to this, the filaments printed from different bioinks do not pull apart and the multi-material composite remains solid. Moreover, the compression test of uncut soft and stiff control gels ( Fig. 2 (i and j)) demonstrated that both gels withstand similar compression (69.3 ± 3.9 % for soft, 60.8 ± 3.2 % for stiff), even though the stiff gel withstands 1.7-times higher axial force (0.48 ± 0.15 N) than the soft gel (0.28 ± 0.13 N). Therefore, the crosslinking density and bioink stiffness does not hamper the deformation capability. Multi-material 3D bioprinting strategy and cellular growth enhances the handling and mechanical stability of the 3D bioprinted constructs The difference in the important handling properties between a soft-only uni-material structure and a soft + stiff composite ( Fig. 3 (a)) was analyzed by printing acellular structures and handling them with a spatula on day 7 after printing ( Fig. 3 (b)). The soft-only structure convoluted when trying to lift it with a spatula, and therefore, could not be handled. The soft + stiff composite was stable, did not convolute and was easily lifted with a spatula. The transparency of cell-laden soft-only uni-material structure and soft + stiff composite was investigated visually, and the transparency of acellular and cell-laden soft + stiff composite with transmittance measurements. There was no difference in visual transparency between the structures when inspected visually 1 day after printing and the text remained visible below the structure during culture ( Fig. 3 (c)). However, the proliferating cells caused the structures to become cloudier during 14 days of culture. In addition, the soft-only uni-material structure shrunk significantly during culture ( Fig. 3 (c) top row), which was not observed in the composite. The transmittance of cell-free composites was 76–87 % on day 1 and 70–87 % on day 7, and the transmittance of cell-laden composites 74–86 % on day 1 and 67–84 % on day 7 ( Fig. 3 (g)). The transmittance of PBS was measured at 89–91 %. The difference in transmittance between structures with or without cells was only maximum of 2 % on day 1 and maximum of 3 % on day 7. A slight decrease in transmittance from day 1 to day 7 occurred regardless of cells, and the decrease was maximum of 5 % without cells and 7 % with cells. Even though the transmittance decreased, it remained still above 66 %. With follow-up culture up to 14 days, it was observed that the cells had a significant effect on the mechanical properties (p < 0.05) ( Fig. 3 (e)) and swelling behavior ( Fig. 3 (f)). The storage modulus demonstrating the mechanical strength of the structures decreased in the case of acellular soft-only and stiff-only uni-material structures, as well as acellular composite without cells. The storage moduli on day 1, 7 and 14 were 14.63 ± 12.13 Pa, 11.28 ± 7.80 Pa and 5.71 ± 4.21 Pa for the acellular soft-only structure, respectively, and 78.59 ± 5.55 Pa, 60.93 ± 10.34 Pa and 21.96 ± 3.74 Pa for the acellular stiff-only structure, respectively. The storage modulus of the acellular soft + stiff composite remained between the moduli of soft-only and stiff-only structures on each timepoint (64.28 ± 23.78 Pa on day 1, 58.55 ± 34.18 Pa on day 7, and 10.5+±6.53 Pa on day 14). However, the storage modulus of the cell-laden soft + stiff composite increased during inspected timepoints (59.78 ± 4.98 Pa on day 1, 83.62 ± 22.79 Pa on day 7, and 141.41 ± 184.36 Pa on day 14). On day 1, the storage modulus of cell-laden composite was similar to the acellular composite. However, on day 14, the storage modulus was 14 times higher in cell-laden composites compare to the acellular composites (p < 0.05). The swelling behavior supported the differences seen in the mechanical properties. Interestingly, the soft-only structure showed lower swelling than the stiff-only structure or the acellular composite, although lower crosslinking density usually results in higher swelling [ 44 ]. However, the data could indicate faster material degradation due to lower crosslinking density resulting in lower amount of material, and thus, decreased swelling. The results of the mechanical properties of the structures support this data because the storage modulus of the soft-only structure is significantly lower in each timepoint compared the moduli of other structure types (p ≤ 0.05). The cell-laden composite showed decreased swelling compared to the other explored structures. This data indicates that the cellular component in the bioink has a significant effect on the mechanical properties and swelling behavior of the bioprinted structures. The filament structure within the composite was evaluated by printing fluorescent particles in the soft bioink ( Fig. 3 (d)). The soft bioink was chosen for the visualization because its organization is more likely to be altered by the stiffer filament, which would result in nonuniform filaments. However, the soft filament was observed to be continuous within the layers, and the structure did not change during the 7 days in vitro indicating that the composites maintain their printed form. Importantly, the filament structure mimics the organization of the collagen fibrils in the native corneal stroma where the fibrils are arranged in layers perpendicular to each other [ 1 ]. The complex organization of corneal stroma can be mimicked with the multi-material bioprinting strategy The ability of the multi-material 3D bioprinting strategy to guide cellular growth in the bioprinted structures was explored by printing cell-laden composites using either stiff or soft bioink as the acellular bioink ( Fig. 1 (c)). The cells were printed in the soft bioink with both structure types. Cytocompatibility of the multi-material bioprinting strategy was studied with LIVE/DEAD staining on day 1 and 7 post-printing. High cell viability (>98 %) with hardly any dead cells was observed in both printed structure types ( Fig. 4 (a)). The cell proliferation within the two composites was further studied with PrestoBlueTM analysis on day 1, 7 and 14 post-printing. The proliferation increased significantly during 14 days of culture (p ≤ 0.05), and there was no significant difference between the different printed composites in any timepoint ( Fig. 4 (b)). This data indicates excellent cytocompatibility of the bioinks with hASCs. Importantly, the multi-material bioprinting did not hamper the cell viability during the printing process. The cell growth and tissue formation were further studied in the printed composites with IF staining. Phalloidin staining did not show visible differences in cell morphology or orientation on day 1 post-printing ( Fig. 4 (c)). In addition, the cells were in the cell-laden soft filament with both structure types. The cell morphology was already elongated to some degree on day 1. Completely elongated cells were detected on day 7 with no rounded cells visible ( Fig. 4 (d)). However, cells were no longer within the original filament organization with the soft-only composite and proliferated within the whole structure. With the stiff filament guiding the cell growth, the structural organization remained during 7 days of culture. However, it was observed that after 7 days, the organization was gradually lost due to high cell proliferation in the printed structures ( Fig. S1 ). Tissue formation within the soft + stiff composite was evaluated with IF staining of gap junction protein connexin 43 ( Fig. 4 (e)). Positive staining against connexin 43 was observed on day 1 and 7 after printing, with increased expression during culture. This indicates an increase in cell-cell interactions within the printed structure. In addition, the cellular organization and network formation in layer-like fashion was observed in the 3D illustration of a confocal image ( Fig. 4 (f)). The effect of the multi-material 3D bioprinting strategy on cell growth was further illustrated by adding fluorescent particles to the stiff filament and staining the cells with phalloidin. The cells grew along the stiff filament and formed network-like structures ( Fig. 4 (g)). Integration of the 3D bioprinted composite to the host tissue After demonstrating the cellular growth within the 3D bioprinted composite, the integration of the 3D structure to ex vivo porcine cornea was investigated to avoid unnecessary animal studies. The bioprinted cell-laden soft + stiff composites were transplanted after 4 h post-printing into stromal pockets as shown in Fig. 5 (a). The integration was evaluated after 14 days in culture with IF and H&E staining from cryosections ( Fig. 5 (b–g)). Importantly, the bioprinted composites were easily transplanted without additional support, sutures, or tissue glue. In IF staining, human stem cell marker STEM121 was used to visualize the human cells from the bioprinted composite ( Fig. 5 (b and c), green). Fluorescent particles mixed in the bioink were used to detect the whole bioprinted composite in the ex vivo model ( Fig. 5 (b and c), magenta). Fluorescent particles and cells negative for STEM121 were seen attached to the bioprinted composite ( Fig. 5 (c), arrows indicating STEM121-negative cells). This could indicate that the bioprinted composite is attached to the surrounding porcine ex vivo tissue and the STEM121-negative porcine cells are migrating towards the bioprinted composite. Moreover, H&E staining of the porcine cornea ex vivo cryosection with the bioprinted composite ( Fig. 5 (d)) shows tight attachment between the composite and host tissue. The composite (purple) is in contact with the surrounding tissue (red) all around the structure without ruptures. In addition, based on the H&D staining, the architecture of the control porcine ex vivo cornea ( Fig. 5 (e)) is similar to the one with the bioprinted composite ( Fig. 5 (d)). In higher magnification images of H&E staining of the bioprinted composite in the corneal stromal pocket (Fig. (f–g)), tight attachment of the bioprinted structure to the porcine cornea ex vivo tissue can be seen with cells (*) are located in between the bioprinted structure and the host tissue and across the sample edge.

Discussion Multi-material 3D bioprinting revolutionizes medical additive manufacturing by shifting the paradigm of bioprinting from simple uni-material structures to complex, native-like tissue constructs. The heterogenous composition and organization of the corneal stroma is fundamental for the normal structure and function of the human cornea [ 1 ] and its disruptions can lead to corneal blindness. Donor corneas are scarce, and thus, artificial corneas are in desperate need. Here, we developed a novel multi-material 3D bioprinting strategy for bioprinting corneal stroma structures. To mimic the native microstructure of the corneal stroma, cell-laden and acellular bioinks with varying stiffness were bioprinted in alternating filaments and perpendicular layers to create composites. This innovative strategy builds upon prior work where multi-material bioprinting of hydrogel bioinks has been mostly explored to provide spatial placement of different cell types without guidance for their growth in microscale upon maturation [ 16 , 22 ]. Therefore, our approach advances 3D bioprinting of cornea and other complex human tissues. In addition to achieving the native-like microstructure, the effects of the multi-material bioprinting strategy on cellular growth after printing as well as the handling and mechanical strength of the structures were investigated. This was the first time the multi-material extrusion-based bioprinting of bioinks with different mechanical properties was explored in cornea TE. In the previous research done by others, the 3D bioprinting of corneal stroma mimicking structures have been explored only with the uni-material approach applied to extrusion-based [ 5 , 6 ], inkjet-based [ 7 ] or stereolithography-based bioprinting [ 9 , 10 ]. However, achieving the complex and heterogenous nature of human tissues requires bioprinting multiple bioinks with different mechanical and biological properties [ 14 ]. In our previous study, we explored the multi-material approach in laser-assisted bioprinting by printing alternating layers of acellular and cell-containing bioinks [ 8 ]. Even though this approach led to corneal stroma mimicking structures in cross sections, the cellular organization within layers was not fully achieved. In addition, the mechanical properties of the printed structures were not sufficient to withstand handling as such and additional supportive membrane was required for handling. Building on this research, here we focused on achieving the heterogenous microstructure and layered organization, providing a disruptive solution to manufacture corneal stromal structures that withstand mechanical handling. One of the enduring challenges in bioprinting is developing bioinks that fulfill the physicochemical requirements for their printing application, as well as the biological requirements associated with the embedded cells [ 45 ]. Prior research generally confirms that high mechanical stress, such as shear stress during bioprinting process, increase cell death [ 46 , 47 ]. Shear stress is affected by the printing nozzle diameter, printing pressure and viscosity of the bioink [ 47 ]. The resolution in extrusion-based bioprinting is typically limited in the range of hundred micrometers to millimeters [ 45 ] resulting in limited biomimicry. To challenge the resolution limit and to mimic the native-like collagen fibril organization of corneal stroma, we used a 100 μm printing nozzle. Due to the small printing nozzle, we designed a low viscosity bioink for bioprinting hASCs with low printing pressure. This bioink demonstrated shear-thinning properties also with cells which is important in extrusion-based bioprinting to reduce shear stress and prevent cell death [ 45 ]. The viscosity of the cell-laden soft bioink was similar to the viscosity of the acellular soft ink, the difference in the average peak viscosities being only 7 Pa s. This indicates that the cells do not affect the viscosity or shear-thinning of the soft bioink, at least with the relatively low cell density of 0.9 million cells ml −1 that was used in this study. Consequently, high viability of hASCs was achieved after printing which demonstrates the ability of the bioink to protect the delicate stem cells during printing. In addition to protecting stem cells from shear stress during bioprinting, suitable mechanical properties after printing are also vital. It is well known that the mechanical properties of the environment affect the cellular functions [ 48 ] and stem cell behavior [ 49 ]. Importantly, bioinks with high mechanical strength do not necessarily allow stem cell migration or growth resulting in poor tissue formation in printed structures [ 46 ]. Therefore, bioprinting human stem cells requires softer bioinks that allow cellular growth and interaction since cell proliferation, cellular interactions and tissue formation are essential to manufacture functional bioprinted tissues. Previously in corneal bioprinting, the research focus has been on evaluating the cellular viability rather than demonstrating cellular interactions or tissue formation after printing [ [5] , [6] , [7] , [9] , [10] , [11] ]. Here, by bioprinting hASCs in the soft bioink with low crosslinking density, we achieved high cell proliferation and expression of gap junction protein connexin 43, indicating that the soft bioink supports tissue formation. Moreover, the cell morphology and connexin 43 expression in the soft composite on day 7 was similar as was previously seen in soft-only uni-material structures ( Fig. S2 ). This is in line with our previous results with a bioink with slightly higher crosslinking degree [ 28 ]. Consequently, the soft bioink was favorable for stem cell bioprinting and shows great promise for additive manufacturing of stem cells. Despite great cytocompatibility and tissue formation of hASCs in the soft bioink, its mechanical properties as such were not sufficient for fulfilling the physicochemical requirements for cornea TE. The structures bioprinted only with the soft bioink suffered from inadequate mechanical properties for handling and shrinkage during culture due to cell proliferation. Employing multi-material bioprinting strategy to manufacture composites with the cell-laden soft bioink and the stiff acellular bioink, the handling of the structures improved significantly which is vital for the transplantation of artificial corneas. Moreover, no shrinking of the cell-laden composites was observed during in vitro cultures. Importantly, the multi-material approach did not hinder the cell viability or proliferation after printing. Consequently, the multi-material bioprinting strategy allowed us to combine the distinct mechanical properties of bioinks without compromising the cellular growth and tissue formation and furthermore, opened the opportunity to guide cellular growth in 3D bioprinted structures and achieve the heterogenous design. Uni-material bioprinting approach cannot achieve and maintain the highly organized arrangement of cells and ECM which is crucial for fabricating transparent native corneal stroma mimicking structures. This was also detected here as there was no cellular organization without the stiff acellular bioink. Therefore, alternating filaments of cell-laden soft bioink with acellular stiff bioink were printed to demonstrate the cellular organization after printing, and the printed filaments were perpendicular in the adjacent layers to mimic the lamellar structure of the native cornea stroma. Herein, it was shown that the cellular growth was more organized when stiff bioink was used in the guiding acellular filaments. However, the organization decreased after one week of culture. At this timepoint, the composites were stable with intact filaments indicating that the decrease in the cellular organization is due to high proliferation of hASCs. In native cornea, hCSKs are quiescent with extremely low proliferation [ 50 ]. In addition, stem cell differentiation is known to reduce their proliferation capacity [ 51 ], and we have observed the decrease in the proliferation capacity in our previous research when differentiating hASCs towards hCSKs [ 28 ]. Thus, bioprinting of hCSKs or hASCs differentiated towards hCSKs with lower proliferation could improve the maintenance of organized cellular structures in long-term cultures in future studies. Bioink transparency is a prerequisite in corneal applications and advantageous for other TE applications to allow constant monitoring and imaging of the 3D bioprinted structures during tissue maturation. In previous research on heterogenous microstructure of corneal stroma, combination of biofabrication technologies have been explored. Fernández-Pérez et al. [ 52 ] electrospun PCL and porcine cornea -derived ECM to scaffolds with varying fiber organization and Gao et al. [ 18 ] used MEW technology and PCL for corneal stroma TE. These studies showed great advances in cell organization of corneal stromal keratocytes. However, the use of abundant non-transparent PCL fibers results in scattering of light and loss of transparency. In addition, manual cell seeding is required in both biofabrication technologies, causing limitations in the spatial distribution of the cells and limiting the scalability and automatization of these processes. To overcome these issues, we combined the multi-material 3D bioprinting strategy with the bioinks with proper transparency. Both bioinks demonstrated transmittance above 75 % throughout the wavelength range of visible light, which is considered excellent in corneal transparency classification [ 53 ]. In addition, the transmittance value for human cornea is reported to range from 75 % to 90 % in the visible light wavelength range [ 54 ]. Despite the bioink transparency being sufficient for corneal applications, high hASC proliferation led to cloudy appearance of the bioprinted structures after 14 days of culture. Similar phenomenon with 3D bioprinted hASCs has been reported previously with laser-assisted 3D bioprinting [ 8 ]. This phenomenon was detected in the transmittance measurements of bioprinted structures with and without cells as the transmittance decreased slightly. However, the transmittance of cell-laden composite day 7 was still excellent or above reasonable (67–84 %) in corneal transparency classification [ 53 ], indicating that the cell proliferation did not significantly hinder the transparency. Furthermore, bioprinting hCSKs or hASCs differentiated towards hCSKs with lower proliferation and maintaining the cellular organization in long-term cultures could also enhance the transparency during culture. Moreover, corneal transparency is decreased if swelling occurs [ 54 ]. Yazdanpanah et al. [ 55 ] pointed out that biomaterials used in corneal TE need to have low swelling. Here, the swelling of the bioprinted cell-laden composite was detected to be lower compared to the acellular structure types. This can be due to the high cell proliferation and tissue formation occurring after printing which leads to decreased amount of porosity and less space to swell. However, the long-term transparency and degradation of bioprinted structures should be investigated in corneal in vivo model in future studies. In addition to transparency, the mechanical strength of the corneal stroma is one of its key properties [ 1 ]. The average storage modulus of native porcine corneal stroma has been reported to range from 2 to 8 kPa when studying the effect of increasing compressive modulus on the storage modulus [ 56 ]. Even though the developed multi-material bioprinting strategy demonstrated significant improvement in handling, and thus potential for transplantation, the storage moduli of acellular and cell-laden composites on day 1 post-printing were 0.064 ± 0.024 kPa and 0.069 ± 0.005 kPa, respectively. Therefore, the values are significantly lower than in the native corneal stroma. Moreover, the storage moduli of all the acellular structure types decreased upon culture post-printing. However, interestingly, the storage modulus of cell-laden composite structure increased up to 0.141 ± 0.184 kPa after 14 days of culture. Even though the value is still lower than the values reported for the native cornea stroma, the data reported here demonstrates that when the cells can proliferate, alter the bioprinted environment and interact, the mechanical strength increases upon culture. The increase in the mechanical strength of cell-loaded 3D bioprinted structures during culture has also been demonstrated previously with primary hCSKs and gelatin methacrylate bioink [ 6 ]. Therefore, the bioink itself does not necessarily need to match the mechanical requirements of the native tissue. In addition, it has been previously suggested that it may not be necessary for bioengineered tissue to match all the mechanical properties of the native cornea to be therapeutically effective [ 57 ]. However, this suggestion should be validated in vivo setting in future studies with cell-laden composites. Due to the employment of multiple materials in the composites, material interactions at the interfaces must be considered. Strong interfacial adhesion improves the toughness and fatigue-resistance of bioprinted constructs [ 58 ]. The sufficient handling of the composites indicated successful adhesion of alternating filaments, and this was further confirmed by a gel block fusion test and compression test. This finding of strong interfacial adhesion was supported by the mechanical characterization, where the storage modulus of the acellular composite was in the similar range as with the stiff-only uni-material structures. Thus, the multi-material 3D bioprinting strategy is a highly potential solution for fabricating mechanically robust, heterogeneously designed, cell-laden solid 3D structures. The strategy also supports tissue formation and guides cellular growth, and therefore it is a crucial technological advancement for creating artificial corneas with native-like microstructure. After demonstrating the advantages of the multi-material 3D bioprinting strategy compared to uni-material approaches in corneal TE, we explored the integration of the bioprinted composite to host tissue in porcine ex vivo cornea organ culture model. Integration of the artificial cornea to the host tissue is crucial to prevent graft failure. The advantages of ex vivo tissue models have been demonstrated in several different tissues, such as cornea [ 59 ], skin [ 60 ], cartilage [ 61 ] and bone [ 62 ]. Available ex vivo models are economical and ethical approaches to study the interaction between the host tissue and the transplanted material. Importantly, unnecessary animal studies can be avoided with ex vivo models. Here, the transplantation of the composites was successfully done in stromal pockets, which is a generally used surgical technique to study biocompatibility of the bioengineered corneal implants in vivo [ [63] , [64] , [65] , [66] , [67] ]. After transplantation, the composite remained in place during ex vivo organ culture. Moreover, porcine cells from the native tissue (negative for human stem cell marker STEM121) were seen attached to the bioprinted composite already after 14 days. This indicates migration of the porcine cells towards the bioprinted composite. Migration of host cells and strong stromal adhesion of bioengineered corneas in ex vivo models have been previously reported to be indicative of tissue biocompatibility [ 57 ]. In addition, the architecture of the 3D bioprinted composites resembled the architecture of the native cornea stroma in H&E staining. The composites were tightly attached to the host porcine stroma. These results indicate good integration of the bioprinted composite to the host tissue. However, long-term in vivo performance and integration assessment is needed in future to fully evaluate the suitability of these multi-material 3D bioprinted composites for cornea TE.

Conclusions Multi-material 3D bioprinting will revolutionize the field of translational additive manufacturing since uni-material bioprinting approaches cannot mimic the heterogenous nature of native human tissues. This study advances the research in additive manufacturing of human tissue constructs with heterogenous design specifically in the field of corneal TE. Here, a novel multi-material 3D bioprinting strategy was developed using HA-based bioinks with varying stiffnesses. The developed multi-material bioprinting strategy was applied in 3D bioprinting human corneal stroma. The combination of soft and stiff bioink resulted in 3D bioprinted structures with good physicochemical and biological properties for corneal TE applications. Bioprinting a cell-laden soft bioink together with an acellular stiff bioink into alternating filaments and perpendicular layers allows mimicking the organization of the heterogenous microstructure in the corneal stroma. In addition, the soft bioink promoted cellular growth and tissue formation of human stem cells in the multi-material 3D bioprinted composites, whereas stiff bioink provided mechanical support as well as guidance of cellular organization upon culture. This was the first study where multi-material 3D bioprinting strategy was explored for 3D bioprinting of the human corneal stroma. Therefore, it holds great potential as a biofabrication solution for manufacturing organized, heterogenous microstructures of native tissues in vitro .

Shared last authorship. Three-dimensional (3D) bioprinting offers an automated, customizable solution to manufacture highly detailed 3D tissue constructs and holds great promise for regenerative medicine to solve the severe global shortage of donor tissues and organs. However, uni-material 3D bioprinting is not sufficient for manufacturing heterogenous 3D constructs with native-like microstructures and thus, innovative multi-material solutions are required. Here, we developed a novel multi-material 3D bioprinting strategy for bioprinting human corneal stroma. The human cornea is the transparent outer layer of your eye, and vision loss due to corneal blindness has serious effects on the quality of life of individuals. One of the main reasons for corneal blindness is the damage in the detailed organization of the corneal stroma where collagen fibrils are arranged in layers perpendicular to each other and the corneal stromal cells grow along the fibrils. Donor corneas for treating corneal blindness are scarce, and the current tissue engineering (TE) technologies cannot produce artificial corneas with the complex microstructure of native corneal stroma. To address this, we developed a novel multi-material 3D bioprinting strategy to mimic detailed organization of corneal stroma. These multi-material 3D structures with heterogenous design were bioprinted by using human adipose tissue -derived stem cells (hASCs) and hyaluronic acid (HA) -based bioinks with varying stiffnesses. In our novel design of 3D models, acellular stiffer HA-bioink and cell-laden softer HA-bioink were printed in alternating filaments, and the filaments were printed perpendicularly in alternating layers. The multi-material bioprinting strategy was applied for the first time in corneal stroma 3D bioprinting to mimic the native microstructure. As a result, the soft bioink promoted cellular growth and tissue formation of hASCs in the multi-material 3D bioprinted composites, whereas the stiff bioink provided mechanical support as well as guidance of cellular organization upon culture. Interestingly, cellular growth and tissue formation altered the mechanical properties of the bioprinted composite constructs significantly. Importantly, the bioprinted composite structures showed good integration to the host tissue in ex vivo cornea organ culture model. As a conclusion, the developed multi-material bioprinting strategy provides great potential as a biofabrication solution for manufacturing organized, heterogenous microstructures of native tissues. To the best of our knowledge, this multi-material bioprinting strategy has never been applied in corneal bioprinting. Therefore, our work advances the technological achievements in additive manufacturing and brings the field of corneal TE to a new level. Graphical abstract Highlights • The novel strategy for multi-material bioprinting was inspired by the native human corneal stroma. • Cell-laden and acellular bioinks with different stiffnesses were printed in alternating filaments. • The cell-laden bioink allowed cellular growth and tissue formation within filaments. • The acellular bioink guided cellular growth and enhanced structural stability. • The 3D structures with heterogenous design mimicked the organization of corneal stroma. Keywords

Funding This work was supported by grants from the 10.13039/501100004012 Jane and Aatos Erkko Foundation (HS and 10.13039/100011405 AM , 2020); 10.13039/501100002341 Academy of Finland (324082 10.13039/100011405 AM , 336666 SM, 326588 SM, 312413 SM, 337607 SM); 10.13039/501100003125 Finnish Cultural Foundation (PP); and 10.13039/501100013510 Eye and Tissue Bank Foundation (PP). CRediT authorship contribution statement Paula Puistola: Conceptualization, Investigation, Methodology, Visualization, Writing - original draft, Writing - review & editing. Susanna Miettinen: Resources, Writing - review & editing. Heli Skottman: Funding acquisition, Project administration, Resources, Supervision, Writing - review & editing. Anni Mörö: Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing - review & editing. Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Heli Skottman reports financial support was provided by Jane and Aatos Erkko Foundation. Anni Mörö reports financial support was provided by 10.13039/501100002341 Academy of Finland . Susanna Miettinen reports financial support was provided by 10.13039/501100002341 Academy of Finland . Paula Puistola reports financial support was provided by 10.13039/501100003125 Finnish Cultural Foundation . Paula Puistola reports financial support was provided by 10.13039/501100013510 Eye and Tissue Bank Foundation . Anni Mörö reports a relationship with StemSight Oy that includes: equity or stocks. Heli Skottman reports a relationship with StemSight Oy that includes: equity or stocks. Anni Mörö has patent #PCT/FI2022/050,403 pending to Assignee. Based on the Act on the Right in Inventions in Finland, all authors employed by Tampere University have given all rights to the University and thus have declared no competing interests. Anni Mörö and Heli Skottman are co-founders and shareholders in StemSight Ltd without any connection to the technology and results reported in this manuscript. The other authors declare no conflicts of interests.

Supplementary data The following is the Supplementary data to this article. Data availability Data will be made available on request. Acknowledgements Tampere University Imaging and Histology Facilities are thanked for providing equipment and assistance for this study. In addition, the authors acknowledge the Tampere CellTech Laboratories for their service. The authors thank Outi Melin, Hanna Pekkanen, Anna-Maija Honkala and Sari Kalliokoski for technical assistance. All schematic illustrations were created with BioRender.com (graphical abstract, Figs. 1 and 3(a) and 5(a) ).

CC BY

no

2024-01-16 23:43:48

Mater Today Bio. 2023 Dec 22; 24:100924

oa_package/3c/30/PMC10788621.tar.gz

PMC10788624

38142584

Introduction Urban expansion and densification and increasing needs for transportation have led to a general rise in exposure to environmental noise from vehicles, trains, and aircraft. A recent assessment of the exposure to transportation noise in the European Union, as part of the Environmental Noise Directive (END), demonstrates the scale of the problem: over 113 million individuals, constituting approximately 20 % of the population, reside in areas exposed to transportation noise (L den ) exceeding 55 dB [ 1 ]. However, this noise mapping only includes agglomerations with >100,000 inhabitants and areas along major roads, railways, and airports outside of urban centers, so this number is highly likely an underestimation [ 1 ]. In 2018, an expert panel appointed by the World Health Organization (WHO) published a report summarizing the evidence up to the year 2015 of the effect of environmental noise on various health outcomes [ 2 ]. They concluded that there was ‘high-quality evidence’ to support an association between road traffic noise and ischemic heart disease (IHD), with a relative risk (RR) of 1.08 (95 % confidence interval (CI): 1.01; 1.15) per 10 dB higher noise. For railway and aircraft noise, the quality of evidence was ranked as low to very low. When evaluating other cardiometabolic diseases as well as various other outcomes, such as sleep, birth outcomes, and mental and cognitive health, the WHO expert panel concluded that the evidence was of very low to moderate quality, primarily due to the scarcity of cohort and case-control studies on transportation noise and incident disease. Since 2015, available evidence has increased substantially, particularly from studies investigating the effects of road traffic noise on incident stroke and type 2 diabetes as well as cardiovascular mortality [ [3] , [4] , [5] , [6] , [7] ]. Also, newer studies have suggested that environmental noise may be a risk factor for diseases not evaluated by the WHO expert panel, such as heart failure, breast cancer, and tinnitus [ [8] , [9] , [10] , [11] , [12] ]. While mechanistic studies on noise-induced damage in humans are scarce, a substantial number of animal studies have provided deep mechanistic insights [ 13 ]. Preclinical research has identified the activation of inflammatory cells, the formation of reactive oxygen species (ROS), and oxidative damage as significant drivers of noise-associated health complications. Studies in animals have also confirmed human data on noise-triggered stress response pathways [ 14 , 15 ] and reduced sleep quality with dysregulation of the circadian clock [ 16 ]. These central disease-relevant pathophysiological mechanisms will be addressed briefly in the subsequent section. With this position paper, we aim to provide an overview of the latest epidemiological research on the health effects of transportation noise. We also take a position on the urgent need for action for better population protection. Furthermore, we provide a detailed description of key publications within each specific outcome area (summarized in Table 1 ) to highlight important findings and exemplify high-quality study designs in estimating the health effects of transportation noise. The second part of the review highlights pathophysiological mechanisms linked with noise-triggered chronic disease, primarily based on evidence from experimental preclinical studies. The mechanistic part focuses on oxidative stress and adverse redox signaling, particularly in the cardiovascular system and the brain. Overall, we highlight the important contribution of noise to the exposome, which represents the sum of all environmental exposures with the associated biochemical changes and health outcomes across the entire lifespan [ 17 ].

Quality assessment of applied methods for detection of reactive oxygen and nitrogen species and associated oxidative damage Redox biomarkers reported for noise exposure The postulated key role of ROS formation for noise-induced pathophysiology is supported by a broad range of oxidative stress markers and read-outs detected in noise-exposed animals ( Fig. 17 ). Classical markers comprise 3-nitrotyrosine-, malondialdehyde- or 4-hydroxynonenal-positive proteins, 8-isoprostane as well as 8-hydroxy-(deoxy)guanosine (8-OH-(d)G) in different tissues and plasma/serum (reviewed in Refs. [ 45 , 531 ]). In addition, eNOS S-glutathionylation and uncoupling of nNOS were found in noise-exposed mice. These indirect oxidative stress markers were accompanied by direct measurement of O 2 •− formation by high-performance liquid chromatography (HPLC)-based quantification of 2-hydroxyethidium and of H 2 O 2 and peroxynitrite by various other fluorescence staining/chemiluminescence-based techniques. Important redox biomarkers are listed and scored according to their reliability and usefulness in biological samples in Table 3 . Most of these biomarkers were also described for various CVD conditions [ 345 , 532 ], neurodegenerative disease [ 42 , 346 ], metabolic disorders [ 39 , 40 ], and different forms of cancers [ 41 , 347 ]. When looking at the table, it becomes evident that redox biomarkers were not measured frequently in noise-exposed human subjects, which warrants future efforts into this direction. Quality of the noise-relevant redox markers Rigorous application of the assays used to assess the extent of oxidative stress/oxidative damage and meaningful interpretation of the experimental results require a knowledge of the principles of the assays used, their limitations and the factors controlling the detected signal intensity. Below, is a short description of the assays used to assess noise-induced oxidative stress, with the major limitations identified and the recommendations of the experimental approaches to be used. ROS detection Oxidative stress is described as an imbalance between the oxidant (ROS) production and scavenging, resulting in increased steady-state levels of the oxidants with concomitant increased oxidative modification of biomolecules. Therefore, the detection of ROS, e.g. O 2 •− and H 2 O 2 , is one of the most direct assays for oxidative stress. As ROS is an umbrella term for multiple chemical species of different chemical reactivities and biological roles, whenever possible, the identity of the detected ROS should be established, and different chemical probes and assays must be applied to different types of ROS [ 533 , 534 ]. It should be emphasized that all ROS are short-lived in the biological setting, and any detection attempt requires the application of the appropriate probe at the time of ROS production. Measurement of ROS using appropriate redox probes can be carried out in a wide range of experimental models, from enzymatic assays, cellular organelles, cultured cells in vitro , and isolated tissues to live animals [ 427 , 430 , 535 ]. The analytical methods for the most commonly measured ROS, specifically O 2 •− and H 2 O 2 , are described in section 2.2.4 just after description of the sources of O 2 •− and H 2 O 2 being active in noise exposure conditions. Ex vivo determination of the expression and activity of enzymatic ROS generating and scavenging systems An experimentally more straightforward but less direct approach to estimate the position of the redox balance in vivo is to measure ex vivo the expression and activity of the enzymes, which are known to be involved in ROS generation and/or metabolism. Among the major sources of ROS that may contribute to oxidative damage are NADPH oxidases (source of O 2 •− and H 2 O 2 ), mitochondrial electron transport chain (source of O 2 •− and H 2 O 2 ), xanthine oxidase (source of O 2 •− and by dismutation also H 2 O 2 ), MAO (source of H 2 O 2 ), nitric oxide synthases (source of O 2 •− , H 2 O 2 and peroxynitrite), and myeloperoxidase (source of HOCl). Among the ROS detoxifying/metabolizing enzymes, the most assayed are superoxide dismutases, and others specialized in the degradation of H 2 O 2 (or in some cases other peroxides) such as catalase, glutathione peroxidases, and the components of peroxiredoxins/thioredoxins pathway. The assays applied may involve the determination of the enzyme expression at the transcriptional and/or protein level and establishing the status of their posttranslational modification, known to affect the enzymatic activity (e.g., phosphorylation of NADPH oxidase 2 complex assembly components, glutathionylation and phosphorylation of NOS enzymes, acetylation of mitochondrial superoxide dismutase (SOD2)), and bioavailability of cofactors (e.g., BH 4 for NOS enzymes). However, monitoring the enzymatic activity is the preferred approach, and intact pieces of tissues (e.g., blood vessels), tissue homogenates, isolated organelles (e.g., mitochondria), or membranes have been used to assess such activity. It is essential to supply the enzymes with appropriate substrates for constant activity over the incubation/measurement period and to use specific inhibitors to confirm/establish the identity of the enzyme. Typically, a kinetic assay to determine the reaction rate is preferred, as opposed to an end-point measurement. Biomarkers of oxidative stress Separate from ROS measurements and enzymatic activity assessment, another important experimental approach is to measure products of modification of biomolecules by cellular oxidants [ 345 , 536 , 537 ]. This is typically associated with (but not limited to) oxidative damage to cell components. The major advantage of using of oxidative stress biomarkers is the assessment of endogenous products of the action of ROS and no need to apply any chemical probe to the model used. This opens a potential for non-invasive assessment of such biomarkers in body fluids, allowing a straightforward expansion of such studies to humans. The four major biomolecule classes known to be affected by cellular ROS are small molecule antioxidants (e.g., reduced glutathione (GSH)), lipids, proteins, and DNA. Glutathione and ascorbate oxidation. Measurement of GSH and/or GSH/glutathione disulfide (GSSG) ratio has been widely used to assess the occurrence of redox stress in tissues. Both enzymatic assays and GSH detection using fluorescence probes or HPLC/liquid chromatography-mass spectrometry (LC-MS)-based analyses were reported [ 538 ]. Chromatographic techniques offer high selectivity and sensitivity and are preferred [ 539 ]. Care should be taken to avoid GSH degradation/modification during sample storage and processing. Conversion of another small molecule antioxidant, ascorbate, to its oxidation products, ascorbyl radical and/or dehydroascorbic acid, has also been utilized to assess oxidative stress in vivo [ 540 , 541 ]. Lipid peroxidation products. Analysis of the end products of lipid peroxidation is commonly applied to assess the extent of oxidative stress in vivo [ 542 , 543 ]. At the same time, enzymatic lipid peroxidation is catalyzed, e.g., by lipoxygenases. The most commonly detected products of lipid peroxidation include malondialdehyde (MDA), 4-hydroxynonenal (4-HNE) and isoprostanes [ 544 ]. Various detection methods have been applied, but their detection by LC-MS-based techniques is recommended as highly specific, resulting in the highest confidence in signal assignment to any specific product among the techniques used [ 545 ]. For determination of the extent of chemical lipid peroxidation, a specific product of oxidation of arachidonic acid, 8-iso-prostaglandin F 2α (8-iso-PGF 2α ), has been proposed as the most reliable biomarker and has been extensively used [ 546 ]. The possibility of forming the same product in enzymatic reaction catalyzed by prostaglandin-endoperoxide synthases (PGHS) led to the proposal to profile different oxidation products of arachidonic acid and use the 8-iso-PGF 2α /PGF 2α ratio for the determination of the relative contribution of chemical and enzymatic pathways to the total detected pool of 8-iso-PGF 2α [ 547 ]. It should be emphasized that LC-MS-based analyses are recommended and enable profiling of the different lipid peroxidation products in a single run. Post-translational modification of proteins. Many amino acid residues in proteins are prone to oxidative modification, which may form relatively stable and specific end products of potential value as biomarkers of oxidative stress [ 548 , 549 ]. Among the most common modifications serving such a purpose are newly formed protein carbonyls, tyrosine nitration (a marker of peroxynitrite and/or myeloperoxidase/NO 2 − /H 2 O 2 ) and chlorination (a marker of HOCl), formation of dityrosine links and protein hydroperoxides (markers of one-electron oxidizing species), protein glutathionylation and oxidation of thiols to sulfenic, sulfinic and sulfonic acids (markers of thiol oxidizing agents, including H 2 O 2 , ONOO − , and HOCl), oxidation of methionine to methionine sulfoxide (a marker of H 2 O 2 , HOCl, one-electron oxidants), and formation of protein carbonyls (a general marker of protein amino acid oxidation). It should be noted that some modifications listed may also be formed in enzymatic systems, including cysteine and methionine residues oxidation [ 550 ]. Protein glutathionylation may result from the reaction of GSH with oxidized/nitrosated protein thiols or vice versa. Protein carbonyls may be formed due to the reaction of proteins with the electrophilic products of lipid peroxidation, including 4-HNE or protein glycation. Many modifications mentioned may be detected using specific antibodies, either by immunoblotting or via ELISA. In specific cases, probes for specific modification can also be used (e.g., dinitrophenylhydrazine, DNPH, for protein carbonyls). Still, LC-MS-based detection and quantification is recommended as it offers the most rigorous analysis of the modification type and detection of multiple modifications in a single protein [ 548 ]. The combination of chemical labeling of specific modification sites with standard enrichment methods (e.g., antibody-, biotin-, click chemistry-based) enables high confidence in the identification of the proteins modified and analyses of the type(s) and site(s) of modification. Due to the possibility of intramolecular electron/charge transfer, the site of the detected protein modification may differ from the site of initial interaction with the oxidant. Nucleic acid oxidation. The intracellular oxidizing environment may also result in oxidative modification of the nucleic acids, DNA and RNA [ 551 ]. While the comet assay widely monitors cellular DNA damage, it lacks specificity to cellular oxidants. Measurement of the extent of conversion of 2’-deoxyguanosine to 8-hydroxy-2’-deoxyguanosine (8OHdG) is the most widely accepted experimental approach to monitor DNA oxidation [ 552 ]. The measurement requires DNA isolation and digestion, followed by determining 8OHdG, either by ELISA or LC-MS/MS. Based on the multi-laboratory assay comparison, ELISA-based quantification of 8OHdG is discouraged, while mass-spectrometric analyses are recommended [ 553 ]. Induction of cellular antioxidant response. Upon exposure to oxidants or electrophiles, the cell may adapt by boosting its potential to detoxify such species, for example, by increased expression of antioxidant enzymes. One of the pathways linking oxidative/electrophilic stress to the abovementioned adaptive response includes NRF-2 protein and its nuclear target, antioxidant/electrophile response element (ARE/EpRE) [ 554 ]. Therefore, markers of ARE activation, including the expression of the downstream protein targets at the gene and protein level, have been used as markers of oxidative stress [ 555 ]. It should be noted, however, that such an adaptive response may result in the resolution of oxidative stress. Thus, the accurate interpretation of the data may be difficult. Furthermore, plasma levels of cellular antioxidants (both small molecule and enzymatic) may result from the damage of specific tissues, not necessarily related to oxidative stress. Besides the induction of direct antioxidative defense mechanisms, such as superoxide dismutases or glutathione system enzymes, oxidative stress is often accompanied by an induction of various repair systems. This includes the systems responsible for the detoxification of harmful intermediate oxidation product (e.g., 4-HNE) [ 556 , 557 ], or degradation and repair systems for damaged macromolecules. In particular the components of the proteasomal system are under the control of the Nrf2 system [ 558 ] or are induced under oxidative stress/inflammatory conditions [ 559 ]. However, there are no systematic studies on the role of these repair systems under noise conditions in the cardiovascular system. Proteotoxic stress was investigated in the cochlear cells [ 560 , 561 ], also interesting due to the existence of extremely long-living proteins in the cochlear. Therefore, the impact of noise on antioxidative repair systems is still an open question. Additional considerations Probe availability/biodistribution. Under most conditions, redox probes can intercept only a fraction of the pool of any given oxidant due to the competition with intra-/extracellular targets/scavengers of the oxidant. Therefore, the probe's tissue level is one factor controlling the amount of the oxidant intercepted and, thus of the detectable product formed. The bioavailability of the probe should be experimentally verified, and measured for each sample due to the possible differences between the treatment groups and the variations between individual animals. Some probes, including DHE, are rapidly oxidized in the blood due to high reactivity towards heme proteins, and site/tissue-specific probe administration by direct injection may be a preferred approach. Expressing the results as the ratio of the product formed to the detected probe level may help address the differences in probe availability. Similarly, the concentration of various biomolecules being oxidatively modified should be considered when assessing the biomarkers of oxidative stress, as those may be modulated by the diet used and changes in metabolism. This may be reflected in raised levels of the biomarkers, even when the level of oxidants remains unchanged. Again, “normalizing” the data to the level of the biomolecules undergoing oxidative modification may be used to address such variability. Metabolism and biodistribution of probe-derived products and biomarkers. The concentration of any analyte (redox probe, the product formed, any biomarker) at any given time in a specific site/tissue is a product of the rate of its formation and/or uptake and the rate of its degradation/efflux. Therefore, the potential pathways of the loss of the analyte should be considered, as their modulation may be misinterpreted as a change in the rate of production of the analyte of interest. For example, decreased activity of the proteasomal system may result in increased accumulation of the post-translationally modified proteins. Determination of oxidative stress in humans. Given the large variety of oxidants formed, considering the various locations of formation and the various kinetics of reactions and transportation of oxidized products into the circulation it is widely accepted that in an ideal setting a set of different parameters should be determined to get a clear result about oxidative processes [ 345 , [562] , [563] , [564] ]. This avoids also the influence of some non-oxidative pathways on the results.

Conclusions, redox outlook, and future perspectives The evidence on health effects of road traffic noise has increased substantially since the evaluation conducted by a WHO appointed expert group in 2018. In contrast, although a few new studies have been published, less research progress has been observed in the railway and aircraft noise fields, and the evidence for these two exposures in relation to all health outcomes are still of very low to moderate quality. The evidence has strengthened for long-term exposure to road traffic noise as a risk factor for IHD, although the excess risk seems lower in recent studies compared to the risk estimate reported in the WHO report. Four outcomes that have recently received increased attention in the noise research field are incident heart failure, stroke, and type 2 diabetes, as well as all-cause mortality. While studies on heart failure, diabetes, and all-cause mortality consistently find associations with road traffic noise, results are less consistent for stroke. Although recent studies found road traffic noise associated with higher CVD mortality, others failed to see an association. Generally, studies assessing road traffic noise across the exposure range using high-quality input data and address-level precision find noise associated with a high risk of cardiometabolic diseases, highlighting the importance of an accurate noise exposure assessment in future studies. Emerging outcomes in a noise context include dementia, cancer, and tinnitus, which deserve more attention in future studies. Interestingly, for dementia, breast cancer, tinnitus, and diabetes, new studies suggest that noise at the least exposed façade, as an indicator for disturbance of sleep, is more strongly associated with these diseases. In contrast, noise at most exposed façade seems to be a more substantial (or similar size) risk factor for CVD. The believed mechanisms behind the harmful effects of noise on the development of various diseases (e.g., CVD, diabetes, and dementia) include the well-defined “noise reaction model“, with neuronal activation involving the HPA axis and the sympathetic nervous system, followed by a classical stress response via cortisol and catecholamines. Furthermore, noise-induced annoyance (emotional perception), sleep deprivation and/or fragmentation can initiate the stress pathway. Major downstream pathophysiological processes of noise-induced stress are inflammation and oxidative stress induction. The most important sources of ROS (e.g., O 2 •− and H 2 O 2 ) formation are the phagocytic NADPH oxidase with a potential contribution of mitochondria and uncoupled NOS enzymes. In contrast, xanthine oxidase involvement has not been observed as part of the noise-induced stress response. Major oxidative damage pathways following noise exposure comprise the uncoupling of NOS enzymes (loss of protective nitric oxide), lipid peroxidation, oxidative DNA damage, and nitration of protein tyrosine residues. Based on preclinical data, noise-induced oxidative damage also represents a potential target of non-pharmacological and pharmacologic interventions (e.g., by antioxidant effects of physical exercise, intermittent fasting, and drug-based activation of antioxidant pathways centered on NRF-2/HO-1 or AMPK). Accordingly, advanced knowledge of adverse redox mechanisms and oxidative damage by noise exposure, e.g., including redox-dependent activation of inflammatory pathways or impairment of circadian rhythms, may allow the successful development of preventive strategies. However, it has to be mentioned that most mechanistic data stem from animal studies, which suffer from major limitations previously reviewed in detail [ 13 ]: differences in hearing range between species, difficulties to properly quantify noise annoyance or perception, and generally higher sound pressure levels applied in animal research. These limitations may complicate the comparison of noise effects in humans with those in animals. More research at the preclinical and clinical level on the health effects of transportation noise and the mechanistic pathways behind them is urgently needed to construct a full picture of the health consequences of this widespread exposure (key points are summarized in Textbox 4 ). However, we already have extensive evidence showing that road traffic noise is associated with a higher risk of CVD and diabetes. New research has indicated effects on other significant diseases with massive personal and societal costs. Recently, the EU evaluated that approximately 20 % of the population was exposed to transportation noise levels exceeding 55 dB, which is very likely underestimated as the EU mainly estimates noise exposure in larger urban agglomerations. Due to this sizeable number of people exposed to high noise levels, recent calculations have shown that transportation noise contributes considerably to the environmental burden of disease [ 179 ]. Importantly, the calculated "burden of disease” will increase substantially if the emerging research on noise and major diseases, such as dementia, breast cancer, and depression, are confirmed in future studies. This stresses the importance of prioritizing actions to better protect the population from high levels of transportation noise via mitigation measures that include lowering speed limits and reducing traffic-flows, noise barriers along major roads, noise-reducing asphalt, low noise-emitting tires, and noise-reducing windows, in addition to enhanced focus on preventing future noise problems in urban planning. These mitigation strategies are especially important to protect the vulnerable groups, e.g. patients with pre-established chronic disease, in light of the data reported by Olbrich et al. indicating a higher aircraft noise-associated risk of recurrent cardiovascular events after acute coronary syndrome [ 604 ].

These authors contributed equally and are joint senior authors. Transportation noise is a ubiquitous urban exposure. In 2018, the World Health Organization concluded that chronic exposure to road traffic noise is a risk factor for ischemic heart disease. In contrast, they concluded that the quality of evidence for a link to other diseases was very low to moderate. Since then, several studies on the impact of noise on various diseases have been published. Also, studies investigating the mechanistic pathways underlying noise-induced health effects are emerging. We review the current evidence regarding effects of noise on health and the related disease-mechanisms. Several high-quality cohort studies consistently found road traffic noise to be associated with a higher risk of ischemic heart disease, heart failure, diabetes, and all-cause mortality. Furthermore, recent studies have indicated that road traffic and railway noise may increase the risk of diseases not commonly investigated in an environmental noise context, including breast cancer, dementia, and tinnitus. The harmful effects of noise are related to activation of a physiological stress response and nighttime sleep disturbance. Oxidative stress and inflammation downstream of stress hormone signaling and dysregulated circadian rhythms are identified as major disease-relevant pathomechanistic drivers. We discuss the role of reactive oxygen species and present results from antioxidant interventions. Lastly, we provide an overview of oxidative stress markers and adverse redox processes reported for noise-exposed animals and humans. This position paper summarizes all available epidemiological, clinical, and preclinical evidence of transportation noise as an important environmental risk factor for public health and discusses its implications on the population level. Graphical abstract Highlights • Transportation noise is a significant environmental risk factor for many non-communicable diseases • This position paper summarizes the clinical and epidemiological evidence of noise health effects • Noise induces central pathomechanisms related to adverse redox signaling • This position paper provides details on noise-mediated activation of oxidant sources and damage markers • More human studies on noise exposure, redox biological changes, and health outcome are needed Keywords

Abbreviations 2-hydroxyethidium 4-hydroxynonenal 8-iso-prostaglandin F 2α 8-hydroxy-2’-deoxyguanosine (also 8-OH-(d)G) adrenocorticotropic hormone AMP-activated protein kinase angiotensin II tetrahydrobiopterin brain and muscle Arnt-like protein 1 burden of disease cardiovascular disease confidence interval circadian locomotor output cycles protein kaput corticotrophin-releasing hormone C-reactive protein cryptochrome enzyme-linked immunosorbent assay environmental noise directive endothelial nitric oxide synthase endothelin-1 flow-mediated dilatation forkhead box O protein (transcription factor) disability-adjusted life years decibel (A-weighted) dihydroethidium 5,5-dimethyl-1-pyrroline-N-oxide global burden of disease reduced glutathione high annoyance heme oxygenase 1 hypothalamic–pituitary–adrenal axis high-performance liquid chromatography hazard ratio high sleep disturbance ischemic heart disease interquartile range interleukin inducible nitric oxide synthase ATP-sensitive potassium channel equivalent A-weighted sound pressure level liquid chromatography-mass spectrometry equivalent A-weighted sound pressure level over 24 h with a penalty of 10 dB(A) for nighttime noise (23.00–07.00) and a penalty of 5 dB(A) for evening noise (19.00–23.00) noise at the most exposed façade noise at the least exposed façade N G -nitro- l -arginine methyl ester lysozyme M major adverse cardiovascular events monoamine oxidase malondialdehyde myocardial infarction mitochondrial permeability transition pore nuclear factor kappa B non-Hodgkin's lymphoma noise-induced hearing loss neuronal nitric oxide synthase nitric oxide synthase (isoforms 1 (neuronal), 2 (inducible), 3 (endothelial)) NADPH oxidase (e.g. isoforms 1, 2, 3, 4, 5) NOX isoform 2 (phagocytic NADPH oxidase) nuclear factor E2 related factor-2 odds ratio cytosolic regulator of NOX2 SHC-transforming protein 1 period positron emission tomography-computed tomography protein kinase C fine particulate matter renin–angiotensin–aldosterone system reactive oxygen species relative risk Study on Air Pollution and Lung and Heart Diseases in Adults sympathetic nervous system mitochondrial superoxide dismutase sound pressure level tumor necrosis factor alpha World Health Organization Health impact of transportation noise Central pathomechanisms While a link between the environment and various diseases was established decades ago, the field has continued to refine our understanding of risks that impact disease burden, including air [ 18 ] and noise pollution [ 13 ]. Specifically, environmental and lifestyle risk factors are intimately tied to cardio- and cerebrovascular disease [ 19 ]. Several studies have shown that noise below the level that induces direct physical damage can increase the risk of various diseases, most likely through the pathway proposed by Wolfgang Babisch in the ‘noise reaction model’ ( Fig. 1 ) [ 20 ]. Babisch proposed that noise could work through an ‘indirect pathway’ to elicit subconscious stress responses and noise annoyance that in turn exacerbate risk factors and could lead to the development of cardiovascular disease (CVD), such as myocardial infarction (MI), heart failure, persistent hypertension, arrhythmia, and stroke [ 21 , 22 ]. Noise can also disturb sleep, ‘hijacking’ a pathway that increases the risk of ischemic heart disease (IHD) [ 23 ] and atrial fibrillation [ 24 ]. Arousal caused by noise activate physiological stress response systems, namely the hypothalamic–pituitary–adrenal (HPA) axis and the sympathetic nervous system (SNS). The mediators of these pathways are cortisol and catecholamines, respectively ( Fig. 2 ), which can then subsequently activate the renin–angiotensin–aldosterone system (RAAS) and have immediate effects on the cardiovascular system, including increase in heart rate and vasoconstriction [ 25 , 26 ]. Although not yet proven in humans, there is some evidence that living in close proximity to major roadways is associated with higher left ventricular mass, which may be due to air pollutants or another component of roadway proximity, such as noise [ 27 ]. The connections between HPA, SNS, and RAAS activation and inflammation and oxidative stress in the vasculature and brain have been reviewed elsewhere [ 28 , 29 ]. One end-product of RAAS is angiotensin II, a potent (transient) vasoconstrictor and vascular regulator with well-acknowledged inflammatory and pro-oxidative properties. Angiotensin II activates circulating monocytes, which then increase circulating levels of interleukin (IL)-1β, IL-6, and reactive oxygen and nitrogen species [ 14 , 29 , 30 ]. Through this mechanism, stressors can lead to arterial hypertension and blunted endothelial function linked with increased oxidative stress and impaired nitric oxide bioavailability [ 31 ]. Over time, this can result in a super-sensitivity of vessels to stress hormone-induced vasoconstriction [ 32 ]. In addition, angiotensin II also causes cardiac hypertrophy and medial thickening in hypertensive mice, directly by effects on cell growth factors and indirectly by pressure overload [ 33 , 34 ], a property also shared by endothelin-1 [ 35 , 36 ]. Structural remodeling and hypertrophy induced by these vasoconstrictors contributes to the development of heart failure [ 37 , 38 ]. Notably, chronic oxidative stress and low-grade inflammation also represent pathomechanistic hallmarks of diabetes [ 39 , 40 ], cancer [ 41 ], and neurodegenerative diseases [ 42 ], making these adverse processes central disease-drivers in the majority of non-communicable diseases. The underlying mechanisms of noise-induced stress reactions, development of cerebrovascular inflammation, and oxidative stress are discussed in detail in the second part of this position paper (reviewed previously [ 29 , 43 ]). There, we highlight the important contribution of impaired circadian rhythm, stress response, inflammation, and oxidative stress to the effects of transportation noise on disease development ( Fig. 2 ). A 2020 study was designed to address the neurobiological link between noise exposure, inflammation, and major adverse cardiovascular events (MACE). Stress-associated neural activity (as the ratio of amygdala to regulatory cortical metabolic activity) and the degree of arterial (aortic) inflammation was quantified in 498 healthy adults without active cancer or clinical CVD by evaluating clinical 18 F-fluorodeoxyglucose positron emission tomography-computed tomography (PET–CT) imaging [ 46 ]. In this study, increased noise exposure at the individuals home address was independently linked with metabolic activity of the amygdala (relative to regulatory cortical activity), arterial inflammation, and a higher risk of MACE after accounting for air pollution, socioeconomic factors, and established CVD risk factors. Analyses indicated that higher noise exposure was associated with MACE via heightened amygdala activity and arterial inflammation ( Fig. 3 ) [ 47 , 48 ]. Notably, the same pathway has also been implicated in the link between perceived stress and socioeconomic disparities (e.g., lower education or income) and CVD [ 49 , 50 ]. Health effects of exposure to traffic noise in humans In the following section, we provide an overview of some of the key scientific advancements since 2015, focusing on cardiometabolic diseases as well as diseases that are emerging in a noise context, with emphasis on results from cohort and case-control studies. We will touch upon the importance of conducting a valid noise exposure assessment, having a sufficient number of observations, and applying an extensive confounder control, as these are prerequisites for achieving reliable results. As the shape of the exposure-response function for transportation noise and disease is crucial for health impact assessment, we provide detailed descriptions of key papers that report such data, estimated based on assessment of noise levels throughout the exposure span. Recent studies have investigated health effects using a “new” noise indicator - noise at the least exposed façade (L den Min) - in addition to noise at the most exposed façade (L den Max), corresponding to the noise indicator used in most previous studies. As people often select a bedroom facing away from a busy road (if possible), L den Min is hypothesized to be a proxy of bedroom noise exposure, thus better capturing exposure during sleep. This is important because health effects of noise are believed to be partially mediated through sleep disturbance [ 51 , 52 ]. We describe some of the key studies assessing effects of L den Min. A definition of these and other important noise metrics are provided in Textbox 1 . Ischemic heart disease incidence The most comprehensive human evidence on adverse health effects of transportation noise, besides annoyance and sleep disturbances, relates to IHD. IHD includes acute myocardial infarction (MI) and angina pectoris, which share a similar pathophysiology and contribute to heart failure. MI is the most common outcome studied in relation to transportation noise and has the advantage of clear diagnostic criteria and a high probability of hospital care, leading to very good coverage in patient registries. The only epidemiological evidence on cardiovascular effects that was judged by the WHO in 2018 to be of high quality was the association between road traffic noise and incidence of IHD [ 2 ]. Seven longitudinal studies from Europe were included in the quantitative assessment, primarily based in large cities, such as Berlin, Bristol, Copenhagen/Aarhus, and Stockholm [ 2 ]. The weighted mean road traffic noise level in the reference category in the studies was 53 dB L den and the association exceeding this level appeared approximately linear with a RR of 1.08 (95 % CI: 1.01; 1.15) per 10 dB L den . The majority of the studies focused on MI, thus, it is uncertain to what extent this risk estimate also applied to other types of IHD. Several studies on road traffic noise and MI/IHD have been published after the WHO meta-analysis. One systematic review and meta-analysis on MI focused on 13 studies, including those in the WHO review, comprising a total of seven cohort studies, five case-control studies and one cross-sectional study [ 53 ]. Excluding one conference report, the overall RR per 10 dB L den was 1.03 (95 % CI: 1.00; 1.05), with significant heterogeneity between the studies. More recent findings, not included in the two reviews, also indicated lower risk estimates than in the WHO review or no clear associations [ [54] , [55] , [56] , [57] , [58] ]. All but one of these studies were strictly registry-based and did not contain any information on lifestyle, e.g., smoking, increasing the risk of residual lifestyle confounding compared to the studies in the two reviews, which generally included such data. A particular issue in relation to confounding for road traffic noise concerns air pollution, i.e., fine particulate matter (PM 2.5 ), which is a risk factor for CVD. Several of the studies on road traffic noise and MI/IHD were adjusted for air pollution which led to attenuation of the associations in some cohorts. However, a recent systematic review of 52 studies concluded that there was little evidence for a confounding effect of air pollution on CVD [ 59 ]. While the review also concluded that noise associations are mostly not confounded by air pollution, more studies investigating potential interactions between noise and air pollution are needed to investigate whether there are intertwined health effects and pathophysiological mechanisms, as suggested by other reviews [ 60 , 61 ]. A cumulative effect on risk for MI by noise, air pollution and lack of green space was recently published [ 62 ]. Most studies on road traffic noise and MI/IHD did not make a detailed evaluation of exposure-response relationships. However, this was assessed in a pooled analysis of nine cohorts from Denmark and Sweden [ 63 ]. Several cohorts in this pooled study were included in the two reviews mentioned above [ 2 , 53 ], but longer follow-up periods resulted in a substantially greater number of cases in the pooled analysis. The adjusted hazard ratio (HR) for IHD was 1.03 (95 % CI: 1.00; 1.05) per 10 dB L den road traffic noise exposure during five years prior to the cardiovascular event. A higher risk was indicated for IHD excluding angina pectoris cases, with a corresponding HR of 1.06 (95 % CI: 1.03; 1.08), while it was 1.02 (95 % CI: 0.99; 1.05) for MI. A threshold of around 55 dB L den was proposed in the exposure-response relation for road traffic noise and IHD ( Fig. 4 ). Such a threshold in the exposure-response function may contribute to explaining the lower risk estimates in studies published after the WHO review, as these studies often had a lower proportion of persons exposed to high levels of road traffic noise [ 64 ]. The studies on road traffic noise and MI/IHD were generally based on estimated noise levels at the most exposed façade (L den Max). Only one study investigated risks of MI and IHD in relation to estimated noise levels at the least exposed façade (L den Min) [ 8 ]. This study was based on a nationwide Danish cohort, using information from registries. The HR for IHD was 1.05 (95 % CI: 1.04; 1.06) per 10 dB 10-year mean road L den Min. Corresponding risk estimates for MI and angina pectoris were 1.03 (95 % CI: 1.02; 1.05) and 1.11 (95 % CI: 1.08; 1.14), respectively. The risk estimates for road L den Max were similar to those for L den Min, and the exposure-response relation indicated a threshold of around 50 dB ( Fig. 5 ). Few studies have addressed risks of MI/IHD concerning exposure to railway or aircraft noise, probably because these exposures affect a relatively small proportion of the general population, making risk estimates uncertain. In three large studies, risk estimates for MI related to railway noise were 1.02 (95 % CI: 1.01; 1.04) [ 65 ], 0.97 (95 % CI: 0.95; 0.99) [ 8 ] and 1.04 (95 % CI: 0.99; 1.08) [ 63 ] per 10 dB L den , respectively. These three studies also investigated effects of aircraft noise, suggesting an increased risk of MI. In a small fourth study no association with aircraft noise was observed [ 54 ]. Two studies indicated that combined exposure to all three kinds of transportation noise (road traffic, railway and aircraft) may bring a risk of IHD [ 8 , 66 ]. In conclusion, there is strong evidence that long-term exposure to road traffic noise is associated with an increased risk of incident IHD, including MI. However, the excess risk appears lower in recent studies compared to the estimate calculated for the WHO report, which may be ascribed to relatively fewer individuals exposed to high noise levels and thresholds in the exposure-response function. An increased risk probably also exists in persons exposed to railway and aircraft noise, but the data is too limited for precise risk estimation. Heart failure incidence Heart failure is one of the leading causes of morbidity and mortality worldwide. It is characterized by symptoms such as shortness of breath, structural or functional cardiac abnormalities and by reduced cardiac output caused by either impaired systolic or diastolic function (in general, the heart's inability to pump blood efficiently). One consequence of chronic noise exposure is activation of the SNS, leading to an increase in blood pressure and elevated heart rate, which can induce structural vascular changes and over time result in heart damage [ 67 , 68 ]. To date, only a handful of studies have investigated the association between transportation noise and heart failure, and heart failure was not evaluated by WHO in 2018 [ 69 ]. Currently, six longitudinal studies have investigated the association between transportation noise and the incidence of heart failure [ 8 , 55 , [70] , [71] , [72] , [73] ]. Studies yield consistent positive associations between road traffic noise and heart failure, ranging from 2 to 9 % higher risk per 10 dB [ 8 , 55 , [70] , [71] , [72] , [73] ]. While the two studies on railway noise and heart failure both indicated positive associations [ 8 , 71 ], the two studies on aircraft noise and heart failure were contradictory: a Danish nationwide study reported a positive association [ 8 ] while a large German study found no overall association [ 71 ]. The most recent of the aforementioned studies was a nationwide cohort from Denmark with a study base of around 2.5 million persons above 50 years of age and 79,358 incident cases of heart failure. The study reported an association with a 4 % higher risk of heart failure per 10 dB road traffic noise [ 8 ]. A novel aspect and important strength of this study was the inclusion of noise at the least exposed façade (L den Min), which was associated with a higher risk for heart failure compared to noise at the most exposed façade (L den Max). This was the case for both road and railway noise (e.g., for road traffic noise the HRs per 10 dB were 1.04 (95 % CI: 1.03; 1.05) for L den Max and 1.09 (95 % CI: 1.07; 1.10) for L den Min). Thacher and colleagues also reported that combined exposure to multiple noise sources (road, rail, or aircraft) was particularly harmful, with a HR of 1.27 (95 % CI: 1.17; 1.37) in people exposed to all three noise sources. Few studies have investigated the shape of the exposure-response function for transportation noise and heart failure. In the Danish nationwide study, a clear exposure-dependent association was seen for road traffic noise, with elevated risk for heart failure evident already at around 50 dB for L den Max and 45 dB for L den Min ( Fig. 5 ) [ 8 ]. Lastly, Thacher et al. found that road and railway noise models were robust to adjustment for PM 2.5 . Taken together, the studies published to date consistently point towards transportation noise as a risk factor for incident heart failure, particularly for road traffic noise. However, further well-designed longitudinal studies are still needed, especially to elucidate to what extent railway and aircraft noise affects the risk of developing heart failure. Stroke incidence Stroke is one of the leading causes of death and disability worldwide [ 74 ]. When the evidence was compiled for the 2018 WHO noise guidelines, only one cohort study on the effects of noise on stroke incidence was available [ 69 ]. The Danish study found an HR of 1.14 (95 % CI: 1.03; 1.25) per 10 dB L den increase in road traffic noise [ 75 ] and the WHO rated the evidence as being of moderate quality. At that time there were only a few ecological and cross-sectional studies that addressed the impact of railway and aircraft noise, and the evidence was rated as very low quality for both. The number of studies on road traffic noise and incident stroke has increased substantially in recent years. In five of the new studies, confounder adjustment has been thorough (i.e., lifestyle factors and/or individual level socioeconomic status as well as air pollution have been accounted for). Two of the studies, based on data from nine pooled Scandinavian cohorts and the entire Danish population, respectively, found road traffic noise to be associated with a higher risk of stroke [ 4 , 5 ]. Studies based on cohorts in London [ 72 ], Norway and Oxford [ 76 ], and the United Kingdom as a whole [ 77 ] found no associations in the fully adjusted models. However, it should be noted that simplified noise exposure assessment approaches were applied in the studies which found no association. In studies with less complete confounder adjustment, two studies reported an association with stroke [ 56 , 78 ], whereas three other studies did not [ 54 , 58 , 79 ]. There have been only a few new longitudinal studies on railway and aircraft noise. Two studies reported no association between railway noise and stroke [ 4 , 5 ], whereas one study with less complete confounder adjustment did [ 78 ]. The same study did not find any association between daily mean aircraft noise level and stroke, but there were indications that nighttime noise events might be harmful. One study on aircraft noise had only five cases [ 54 ], rendering the results uninformative, and another study found an association at moderate but not high noise levels [ 4 ]. A pooled study of nine cohorts in Denmark and Sweden is a recent example of a study applying both valid noise exposure assessment, sufficient observations, and extensive adjustment for confounders [ 4 ]. This study included over 135,000 participants and 11,000 stroke cases and adjusted for individual and area-level confounders. It assessed exposure using the Nordic prediction method accounting for full residential history at address-level precision. The study found road traffic noise to be associated with a higher risk of stroke, with an HR of 1.06 (95 % CI 1.03; 1.08) for each 10 dB increase in L den , and the association remained after adjustment for air pollution. There was no difference between the effect estimates for two stroke subtypes (i.e., ischemic and hemorrhagic). Railway noise was not associated with stroke, and the results for aircraft noise were inconclusive. The exposure-response function for road traffic noise in the pooled Scandinavian study was approximately linear from 40 dB to 80 dB ( Fig. 4 ). Similarly, a large nationwide Danish study found that the association was seemingly linear at lower levels of noise (from 40 dB), although the effect seemed to level off at higher levels (roughly above 62 dB) [ 5 ]. HR in the study was 1.04 (95 % CI: 1.03; 1.05) per 10 dB road L den Max. The effect estimate for road L den Min was comparable. In summary, the number of studies on road traffic noise and stroke incidence has substantially increased in recent years. Although large studies of high quality regarding exposure, confounders, and outcome assessment reported adverse effects, the inconsistent findings relating to road traffic noise and stroke call for more research based on high-quality prospective cohort studies. For railway and aircraft noise there are too few studies to draw conclusions. Of note, a cumulative effect on risk for stroke by noise, air pollution and lack of green space was recently published [ 80 ]. Cardiovascular mortality Chronic exposure to transportation noise and its effects on the body can influence the progression of CVD and ultimately lead to death. Reflecting the available body of evidence at the time, mortality studies in the 2018 WHO review [ 69 ] related only to IHD and stroke, in relation to road traffic [ [81] , [82] , [83] , [84] ] or aircraft noise [ [85] , [86] , [87] ]. No studies were available on railway noise. For IHD mortality, the pooled estimates per 10 dB L den were 1.04 (95 % CI: 0.97; 1.12) for aircraft noise and 1.05 (95 % CI: 0.97; 1.13) for road traffic noise. Only aircraft noise exposure showed a trend towards an association with stroke mortality: 1.07 (95 % CI: 0.98; 1.17). Overall, the number of studies was limited in number and scope with studies mainly from Europe. For aircraft noise, the majority were ecological studies and later judged to have ‘low-quality evidence’. For road traffic noise, however, the judgment was deemed ‘moderate-quality evidence’. Newer mortality studies have included a broader range of specific CVDs. Those showing an association of incident CVD with noise were mainly the larger cohort studies (predominantly from Denmark and Switzerland), which not only followed participants for decades, but had the highest quality exposure assessment at the home's façade [ 6 , [88] , [89] , [90] ]. This has been demonstrated to be essential for minimizing exposure measurement error [ 91 ]. In these studies, the associations between noise and CVD mortality were also robust to air pollution adjustment [ 6 , 8 , 92 , 93 ]. Unique features of the Danish studies included: the long address record allowing exposure to be explored over different long-term averaging periods (e.g. as 1, 5, 10 and 23-year means depending on the study) [ 88 , 90 ] and exposure for both the most and least exposed façades [ 90 , 91 ]. Similarly, the Swiss studies offer unique insights into the timing of noise exposure over the 24-h day [ 52 ] and the influence of other noise characteristics such as intermittency [ 6 , 89 ]. A Danish cohort study, including roughly 53,000 individuals, reported the risk of all CVDs and stroke mortality to be 1.13 (1.06; 1.19) and 1.11 (0.99; 1.25), respectively, per IQR 10-year mean road L den Max and 1.10 (1.01; 1.21) for IHD for L den Min, after considering important lifestyle factors not often available in all large cohorts [ 90 ]. The Swiss National Cohort, effectively including all adults in Switzerland but lacking lifestyle factors, studied these relationships plus mortality from blood pressure-related disease, MI, and heart failure, finding small (2–4%) increased risks for each condition in relation road traffic noise (e.g., 1.03 (1.02–1.03) per 10 dB L den Max for CVD mortality) [ 6 ]. Railway noise was also associated with all CVDs, blood pressure-related, IHD, MI, and stroke mortality but not with heart failure. Higher levels of intermittency at night were independently associated with mortality. Another Danish study with detailed lifestyle data on ≈25,000 female nurses did not find significant associations between road traffic noise and all CVD, stroke or IHD (e.g., 1.10 (0.91–1.31) per 10 dB road traffic noise for stroke mortality) [ 88 ]. Two small studies on road traffic noise and all CVD mortality exclusively in men were conducted in Caerphilly, South Wales, UK (n = 2398) and Gothenburg, Sweden (n = 6304) and did not find any associations [ 94 , 95 ]. In addition, two large studies from the UK (n ≈ 340,000) and the Netherlands (n ≈ 340,000) found no associations with road traffic noise [ 77 , 96 ]. In the UK study, the association between road traffic noise and CVD mortality attenuated to null after adjusting for air pollution, and the Dutch study found no association with either road traffic noise, railway noise, or air pollution. The latter observation suggests that the study suffered some methodological constraints, as the link with air pollution and CVD is well-established. Few newer studies have investigated CVD mortality in relation to aircraft noise; only two based on cohorts with individual-level data investigated CVD mortality in relation to aircraft noise: the US nurses cohort [ 97 ] and the Swiss National Cohort study [ 6 ]. Neither found an association with all CVD mortality, though the Swiss study did show increased risk for mortality specifically from MI and ischemic stroke (1.04 (1.02–1.06) and 1.07 (1.02–1.11) per 10 dB L den , respectively after co-exposure adjustment). Exposures were generally low in the US study, and the exposure contrast was small. Interestingly, in Switzerland, the association between aircraft noise exposure and CVD mortality were stronger and exhibited a linear increase from as low as 30 dB when focusing on the populations in the immediate vicinity of airports: 1.02 (1.01–1.03) and 1.06 (1.02–1.09) per 10 dB L den for CVD and MI mortality, respectively [ 98 ]. In conclusion, road traffic noise shows associations with all CVD and IHD/MI mortality and is judged to be of moderate-high quality. Studies on railway and aircraft noise are still too few to judge, though indicate only a small increased risk for all CVD mortality, if any, based on moderate quality evidence. Short-term cardiovascular health effects of noise in a population setting Investigating short-term or acute health effects of transportation noise on any health outcome in epidemiological studies is notoriously difficult due to a variety of methodological challenges. First, to study short-term effects, fine resolution time information on both the exposure and the outcome are necessary. Concerning MI, for example, exposures in the 2 h preceding the event are usually considered as possible triggers [ 99 ]. This means that to study transportation noise as a possible trigger for MI, hourly resolution noise exposure data and the exact time of the outcome event are required. Second, in many settings, noise follows regular patterns with variations in the exposure levels, primarily due to external factors influencing traffic activity, such as the time of the day, day of the week, and holidays. Since these factors also influence people's behavior and, therefore, are associated with the onset of many acute adverse health outcomes, disentangling possible acute health effects from such time trends is difficult. This mainly applies to road traffic noise, railway noise, and industry noise. Other sources, like wind turbine and aircraft noise, show a higher temporal variability, which offers opportunities to study acute health effects. Multiple epidemiological approaches suited to studying the acute effects of exposure on transient risk changes for immediate onset outcomes exist. Time series analyses are commonly conducted in environmental epidemiology for aggregated data [ 100 ]. For data on individual level, self-matched designs, such as the case-crossover design or the more recently developed case time series design, are well-suited [ 101 , 102 ]. These designs have the additional benefit of adjusting for time-constant, individual-level covariates by design. So far, they have been predominantly applied to study health risks due to temperature or air pollution [ 103 , 104 ]. Only few methodologically robust studies on acute effects of transportation noise have been conducted and, therefore, we in this section also evaluate studies investigating acute effects of other noise-sources. In a Danish study, hospitalizations and deaths from stroke (16,913 cases) and AMI (17,559 cases) among Danes exposed to wind turbine noise between 1982 and 2013 were analyzed using a time-stratified case-crossover design [ 105 ]. Mean nighttime outdoor (10 Hz–10 kHz) and low frequency (10–160 Hz) indoor wind turbine noise was predicted for the four days preceding diagnosis and reference days. For outdoor wind turbine noise above 36 dB, there were indications of an association with stroke but not with MI. For low-frequency indoor noise between 10 and 15 dB and above 15 dB, odds ratios (ORs) (95 % CI) for MI were 1.27 (0.97; 1.67) and 1.62 (0.76; 3.45), respectively, when compared to indoor low-frequency wind turbine noise below 5 dB. For stroke, corresponding ORs (95 % CI) were 1.27 (0.95; 1.69) and 2.30 (0.96; 5.50). One case-crossover study found evidence for short-term associations between aircraft noise exposure and CVD mortality based on an analysis of all cardiovascular deaths that occurred around the Zurich airport between 2000 and 2015 [ 106 ]. Nighttime noise 2 h preceding death among people exposed to 40–50 dB and >50 dB was associated with ORs (95 % CI) of respectively 1.33 (1.05; 1.67) and 1.44 (1.03; 2.04) compared to the reference of <20 dB with a significant exposure-response trend. No associations were observed for daytime deaths. This suggests that nighttime aircraft noise can trigger deaths by CVD. Among specific outcomes, associations indicated an increased risk for IHD, MI, heart failure, and arrhythmias. A study around Heathrow Airport applied the same crossover approach on hospital admissions and deaths due to CVD [ 107 ]. Since only the date, and not time, of death was available, however, they could not investigate exposures directly before the events. The study found slight associations between emergency hospital admissions due to CVD and aircraft noise exposure on the previous late evening (22:00–23:00h, OR per 10 dB = 1.007 [95 % CI: 1.000; 1.013]) or in the early morning (04:30–06:00h, OR per 10 dB = 1.012 [95 % CI: 1.002; 1.021]) of the same day. No associations with cardiovascular deaths were observed. This is an example of the challenges when investigating the acute effects of noise in a population setting, and how important it is to have fine temporal resolution exposure and outcome data to do so successfully. In conclusion, more high-quality studies on the acute health effects of transportation noise are needed. In light of the available methods and increasing availability of high-quality, fine temporal and spatial resolution noise models, the necessary tools to conduct such studies are available. Incidence of type 2 diabetes Global diabetes prevalence has been on a steady rise for decades, surging from 108 million in 1980 to 422 million in 2014 [ 108 ]. Key risk factors include obesity, a sedentary lifestyle, and an unhealthy diet, and recent studies have suggested that also transportation noise may be a risk factor for type 2 diabetes [ 54 , [109] , [110] , [111] , [112] , [113] , [114] , [115] ]. In 2018, the expert group appointed by WHO identified only one high-quality study on transportation noise and diabetes [ 116 ], based on which they concluded moderate-quality evidence for an association [ 69 ]. Since then, nine cohort studies investigating the effects of transportation noise on the risk of incident diabetes have been published, consistently showing that noise, especially from roads, was associated with a higher risk of type 2 diabetes [ 54 , [109] , [110] , [111] , [112] , [113] , [114] , [115] ]. Based on these cohort studies, a 2023 meta-analysis found a joint risk estimate per 10 dB of 1.06 (1.03; 1.09) for road traffic noise (7 studies), 1.01 (1.00; 1.01) for aircraft noise (3 studies), and 1.02 (1.01; 1.03) for railway noise (2 studies) [ 3 ]. The study that added most weight into the meta-analysis on noise and diabetes [ 3 ], was a nationwide study in Denmark, with the inclusion of 3.56 million participants ≥35 years old and 233,912 incident cases of type 2 diabetes [ 115 ]. The study investigated the effects of long-term noise exposure (10-year mean) to road, railway, and aircraft noise, calculated based on detailed information on the moving history of all participants at address-level precision. For roads and railways, the study included both L den Max and L den Min. Lastly, the analyses adjusted for various individual- and area-level sociodemographic covariates, such as education, income, and occupation, and air pollution. The study found that road traffic and railway noise were associated with a higher diabetes risk. For road traffic noise, the association was strongest for L den Min, with HRs per 10 dB of 1.08 (1.07; 1.09) for L den Min and 1.03 (1.03; 1.04) for L den Max in fully adjusted models, indicating that effects of noise on sleep is an essential pathway in the development of noise-induced diabetes. The exposure-response curves for road L den Max and L den Min indicated the lack of lower “safe” noise level, as the risk increased throughout the exposure range from 35 to 40 dB and up ( Fig. 6 ). If confirmed in future studies, this will add substantially to the estimated disease burden, as current health impact studies are based mainly on noise levels ≥55 dB L den . A limitation of administrative studies, such as the above-described Danish study, is the lack of information on lifestyle factors. The degree of residual confounding from lifestyle in studies with access to only sociodemographic covariates was recently investigated in a Danish cohort study of 286,151 persons of whom 7574 developed diabetes during follow-up [ 117 ]. This study found a HR of 1.07 (95 % CI: 1.04; 1.10) per 10 dB L den Max in a crude model adjusted for age, sex, and year. Following adjustment for individual- and area-level sociodemographic covariates, the HR was reduced to 1.05 (95 % CI: 1.02; 1.08), indicating the importance of considering socioeconomic differences in noise studies. After further adjustment for lifestyle, more specifically smoking, consumption of fruit, vegetables and red meat, and physical activity, the HR was 1.04 (95 % CI: 1.01; 1.07). This suggests that residual confounding due to lifestyle covariates is not a major concern in registry-based studies with adjustment for key sociodemographic covariates, although these results need confirmation in future studies on other populations, both in relation to diabetes and other outcomes. In support of noise as a risk factor for type 2 diabetes, four longitudinal cohort studies have indicated that transportation noise increases the risk of developing overweight [ [118] , [119] , [120] , [121] ], which is a major risk factor for diabetes. Although the indicators of obesity investigated displayed some variation across the studies (body mass index (BMI), waist circumference, and weight gain), associations were generally observed between road traffic noise and markers of obesity. Interestingly, results on changes in waist circumference and central obesity were more consistent than results on changes in BMI [ 118 , 119 ]. This observation aligns with a noise-induced activation of the stress-response, as high concentrations of cortisol have primarily been associated with central obesity. In conclusion, exposure to road traffic noise has consistently been shown associated with diabetes, whereas evidence is still lacking for railway and aircraft noise. Recent studies suggest that L den Min may be more relevant than L den Max in the development of diabetes and therefore future studies should include this measure. Importantly, a cumulative effect on risk for diabetes by noise, air pollution and lack of green space was recently published [ 122 ]. Incidence and mortality from neurodegenerative diseases As described above, substantial evidence linking transportation noise and cardiometabolic diseases has emerged in recent years. However, our understanding of the detrimental health effects of noise on the brain remains limited. Degenerative diseases of the brain and nervous system (e.g., Alzheimer's disease, and Parkinson's disease) affect millions of persons worldwide and are a public health priority due to their economic and societal burden [ 123 , 124 ]. Among well-known risk factors for neurodegenerative diseases, such as education and unhealthy lifestyle, environmental exposures like air pollution and noise have been suggested to affect the central nervous system [ [123] , [124] , [125] , [126] ]. The number of studies investigating associations between transportation noise and dementia and cognition in adults is, however, limited. In the WHO guidelines from 2018, dementia was not evaluated due to lack of studies [ 2 ]. A systematic review from 2020 concluded that there was no clear evidence supporting an association between transportation noise and dementia or cognitive decline, given the few studies with high variation in outcome definition and study design [ 127 ]. Among the five studies included in this review, only two investigated transportation noise and incidence of dementia. Both studies, one from Sweden [ 128 ] and one from the UK [ 129 ], found that noise was not associated with a risk of dementia. Two cross-sectional studies included in this review, however, suggested that transportation noise can affect cognitive function in adults [ 130 , 131 ]. Since this review, four new studies on transportation noise and dementia have been published [ 88 , [132] , [133] , [134] ]. One was an American cohort study including 1612 participants, which found positive associations between road traffic noise and Alzheimer's disease, with a HR of 1.3 (95 % CI: 1.0; 1.6) per 11.6 dB (interquartile range, IQR) [ 133 ]. In a Canadian study investigating neurodegenerative diseases (i.e., non-Alzheimer's dementia, Alzheimer's disease, Parkinson's disease, and multiple sclerosis), traffic-related community noise was not associated with any of the outcomes [ 134 ]. Another study conducted in Denmark looked specifically at dementia-related mortality and found a HR of 1.12 (95 % CI: 0.90; 1.38) per 10 dB increase in 5-year mean L den Max [ 88 ]. The fourth and largest of these recent studies was a Danish nationwide cohort study including almost two million elderly [ 132 ]. Besides its large study population and long follow-up, this study presented some unique strengths compared to most studies on the topic. First, the exposure assessment was based on the exact address location and considered the complete address history before and throughout the entire follow-up period, which differs from other studies that estimated noise levels at postal code levels [ 129 , 134 ], and/or only assessed noise at one point in time [ 128 , 129 , 133 ]. Second, noise exposure was estimated at the most and least exposed façades, which allows for possible interpretations on noise exposure during sleep. The nationwide Danish study found transportation noise from road traffic and railway to be associated with an increased risk for all-cause dementia and dementia subtypes. For Alzheimer's disease, the authors found a HR of 1.16 (95 % CI: 1.11; 1.22) for road L den Max ≥65 dB compared with <45 dB; and 1.27 (95 % CI: 1.22; 1.34) for road L den Min ≥55 dB compared with <40 dB. Road traffic noise, but not railway noise, was associated with vascular dementia. For all-cause dementia, exposure-response functions showed linear associations starting from 35 dB, with leveling-off or even small declines at high noise exposures. Despite the limited number of studies investigating associations between transportation noise and neurodegenerative diseases, a growing body of evidence has demonstrated that transportation noise may also be detrimental to the brain and nervous system. Therefore, future studies investigating associations between transportation noise and these diseases are strongly recommended. Cancer incidence and mortality Exposure to transportation noise has been associated with various risk factors for cancer, including oxidative stress, inflammation, disruption of the circadian rhythm, and change in lifestyle habits, such as smoking and alcohol intake ( Fig. 1 , Fig. 2 ) [ 14 , 67 , 135 , 136 ]. However, the effects of transportation noise on cancer have received only a little attention, with a total of 10–15 epidemiological studies to cover this highly diverse and prevalent disease outcome, including studies on breast and colon cancer [ 9 , 10 , [137] , [138] , [139] , [140] ] and cancer mortality [ 7 , 88 , 90 ]. The most studied cancer outcome concerning transportation noise is breast cancer, which has been investigated in three Danish [ 9 , 10 , 137 ] and one German study [ 141 ]. While the three Danish studies investigated effects of long-term exposure to noise (10-year mean in two studies [ 10 , 137 ] and 24-year mean in one study [ 9 ], the German study only had information on noise exposure at time of cancer diagnosis. The results on breast cancer are inconsistent. A Danish cohort study of 29,875 women found both road traffic and railway noise to be associated with a higher risk of estrogen-receptor negative but not with estrogen-receptor positive breast cancer [ 137 ], which was partly supported by a large German case-control study (≈478,000 women) that indicated associations between exposure to high levels of aircraft noise only among women with estrogen-receptor negative breast cancer [ 141 ]. However, the German study found only weak indications of associations between road traffic and railway noise and the risk of breast cancer. Furthermore, a Danish cohort of 22,466 nurses found associations between road traffic noise and breast cancer only among women with estrogen-receptor-positive breast cancer [ 9 ]. The largest study of noise and breast cancer is a nationwide Danish cohort study of 1.8 million women, of whom over 66,000 developed breast cancer during follow-up [ 10 ]. The study had access to residential address history for all participants, with address-specific estimation of road traffic and railway noise at the most and least exposed façades. The authors reported that a 10 dB increase in road L den Min (10-year mean) was associated with an HR of 1.032 (95 % CI: 1.019; 1.046), whereas for road L den Max, only a slightly higher risk was observed (HR: 1.012; 95 % CI: 1.002; 1.022) in fully adjusted models, including socioeconomic status and use of hormone replacement therapy. This indicates that the effects of noise during sleep may be significant in developing breast cancer, potentially disturbing the circadian rhythm [ 136 ], which is a suspected risk factor for breast cancer [ 142 ]. The study also found railway noise associated with a slightly higher risk of breast cancer with HRs of 1.02 for both L den Max and L den Min. In contrast to previous studies, the nationwide Danish study found similar size HR among women with estrogen-receptor positive and estrogen-receptor negative breast cancer subtypes. Another type of cancer that has received some attention in relation to transportation noise is colon cancer [ [138] , [139] , [140] ]. The studies conducted indicated that long-term exposure to road traffic noise (5- or 10-year time-weighted means) might be associated with a slightly higher risk of colon cancer with a HR per 10 dB increase of 1.011 (95 % CI: 0.997; 1.025) in a nationwide Danish cohort of 3.5 million participants and 36,000 incident cases [ 140 ] and a HR of 1.06 (95 % CI: 1.00; 1.12) in a population of 11 pooled Nordic cohorts totaling ≈155,000 persons and 2757 cases [ 139 ]. Long-term effects of road traffic noise on the risk of prostate cancer, non-Hodgkin's lymphoma (NHL), and childhood cancer have been investigated in only one study each, which suggested that high exposure to road traffic noise may be a risk factor for NHL [ 143 ], but not for prostate [ 144 ] or childhood cancer [ 145 ]. Lastly, a few studies have investigated associations between noise and overall cancer mortality, indicating associations between long-term exposure to road traffic noise (10- or 23-year time-weighted means) and overall cancer mortality with HRs ranging from 1.02 to 1.08 [ 7 , 88 , 90 ]. Interestingly, one of these studies investigated associations between L den Max and L den Min and found stronger associations with road L den Min (HR: 1.06; 95 % CI: 1.05; 1.07) compared to L den Max (HR: 1.03; 95 % CI: 1.02; 1.03), suggesting that effects of noise on sleep are especially relevant concerning overall cancer mortality [ 7 ]. In conclusion, much more research is needed to elucidate whether transportation noise is a risk factor for cancer. So far, focus has been on only a few cancer types, mainly breast and colon cancer. However, transportation noise may also increase the risk of other cancer types, given the suggested mechanisms behind noise-associated pathologies (section 2 ). Hearing loss and tinnitus incidence Noise exposure can affect hearing through increased ROS that have effects on outer hair cells of the cochlea, especially in the 3–6 kHz region, resulting in sensorineural noise-induced hearing loss (NIHL) [ [146] , [147] , [148] , [149] , [150] , [151] ]. The risk of NIHL increases if noise exposure exceeds the equivalent A-weighted sound pressure level (LA eq ) of 85 dB(A) as repeated exposures for an extended period ( Fig. 1 ) [ 147 ]. This is frequently seen following high occupational noise exposure and recreational noise [ 147 , 152 ]. Furthermore, there is a high risk of NIHL with frequent exposure to transient impulse-like sounds, such as shooting and explosions from military activities [ 151 ]. These sudden and transient sound exposures can be > 140 dB SPL and result in blast injuries of the sense of hearing immediately [ 153 ]. It is well-known that loud sound exposures above 85 dB(A) can result in temporary threshold shifts, where the hearing thresholds return to the pre-exposure threshold levels after some time [ 154 ]. Recurrent sound exposures can lead to permanent threshold shifts with permanent damage of the outer hair cells in the cochlea [ 155 ]. Rodent experiments have shown that sound exposure resulting in a temporary threshold shifts can lead to synaptopathy (damaged synapses between inner hair cells of the cochlea and the spiral ganglion neuron) [ 156 , 157 ]. This is referred to as hidden hearing loss because synaptopathy occurs even though the cochlea's outer hair cells are not damaged and, thereby, do not affect hearing thresholds [ 157 , 158 ]. Tinnitus is perceived by the affected individual as a phantom sensation of noise. There is a high risk of tinnitus in patients with NIHL and other types of hearing loss [ [159] , [160] , [161] ]. It has also been suggested that tinnitus can result from spiral ganglion neuron fiber loss due to synaptopathy [ 158 , 162 ]. While noise exposure at levels above 85 dB(A) can harm hearing and lead to tinnitus, much less is known about whether exposures below that level can affect the auditory system, such as transportation noise. The general understanding is that noise exposure below 80 dB(A) cannot harm hearing. However, a recent nationwide study from Denmark found that exposure to road traffic noise was associated with higher risk of tinnitus with adjusted HR of 1.06 (95 % CI: 1.04; 1.08) and 1.02 (95 % CI: 1.01; 1.03) per 10-dB increase in 10-year exposure to L den Min and L den Max, respectively [ 11 ]. The highest HRs were found among people without hearing loss and among those who had never been in a blue-collar job. This demonstrates that the cause leading to tinnitus may differ fundamentally from the well-known associations between hearing loss in general, particularly NIHL and tinnitus related to distress. Transportation noise is a known stressor and stress can increase the loudness of tinnitus and the distress caused by the condition [ 163 ]. Tinnitus symptoms are likely enhanced in stressful periods, where stress hormones can affect the limbic, reticular, and auditory systems, as negative thoughts towards tinnitus affect the ability to habituate to the symptoms [ 164 , 165 ]. Cantuaria et al. demonstrated the highest HRs for L den Min, a potential proxy for nighttime noise exposure [ 11 , 166 ]. Stress and tinnitus may form a vicious circle as sleep deprivation increases stress, which has negative impact on tinnitus [ 167 ]. Tinnitus can itself affect sleep initiation and the resumption of sleep if awakening occurs during night [ 168 ]. Of note, also the indirect noise pathway can induce auditory effects. The mechanism regarding how environmental noise affects the auditory system is not well understood and requires further research. It is, however, unlikely that the mechanism is identical to the tinnitus associated with hearing loss in general. All-cause mortality With increasing evidence that transportation noise has a systemic impact on the body and may thus affect additional fatal outcomes beyond CVD, several cohort studies on all-cause mortality have recently been published using long-term exposure assessment based on established prediction models and accounting for most relevant confounding factors, such as age, sex and socioeconomic variables ( Table 2 ) [ 7 , 77 , 90 , 93 , 95 , 97 ]. Seven studies addressed associations with road traffic noise ( Fig. 7 ). Thereof, four studies reported significant associations ranging between 4.5 and 8 % increase in mortality per 10 dB increase in road traffic noise and one study reported a significant association with railway noise [ 169 ]. One smaller study from Sweden did not observe any association with transportation noise. According to a random effect meta-analysis, the five European cohort studies addressing road traffic noise yielded a pooled relative risk of 1.06 (95 % CI. 1.03; 1.08) per 10 dB. Sørensen et al. reported separate estimates for road and railway noise and observed no significant associations between railway noise and mortality if expressed as risk increase per 10 dB [ 7 ]. However, in this study, an increased relative risk for all 5-dB noise exposure categories above an L den of 35 dB was observed compared to the reference category (<35 dB). However, the exposure-response function did follow a continuously increasing pattern and thus linearization of the curve resulted in absence of association. Grady et al. addressed only aircraft noise and did not observe any significant association [ 97 ]. In the U.S. study on aircraft noise [ 97 ], only 7 % of the population was exposed to >50 dB L dn . Consequently, a substantial part of the study population is expected to be exposed to considerably higher levels of road traffic noise than aircraft noise, which thus may have masked the association with aircraft noise. Vienneau et al. provided a relative risk for road traffic as well as for the energetic sum of railway, aircraft and road traffic noise on all-natural cause mortality [ 93 ]. The latter relative risk was very similar to the one for road traffic noise. The lowest effect threshold was presented in some of the papers either by non-parametric splines or by categorical analysis. In terms of L den , significant associations were observed in Sørensen et al. above 35 dB for railway noise and above 45 dB for road traffic noise [ 7 ], and in Thacher et al. above 55 dB [ 90 ]. Vienneau et al. showed non-parametric splines for cardiovascular mortality [ 6 ], where associations were observed to become significant above 30 dB (railway), 38 dB (road) and 50 dB (aircraft noise). This indicates that new studies with large sample sizes and high-quality noise exposure modeling are able to demonstrate detrimental effects from noise even below the WHO guideline values. This conclusion is supported by studies on the incidence of other outcomes that also found low effect thresholds such as for IHD [ 63 ], stroke [ 5 ], heart failure [ 8 ] or diabetes [ 170 ]. Burden of disease To transfer scientific knowledge on noise and health to preventive and regulatory measures, it is important to quantify the attributable health impacts on the population. A key quantitative health impact assessment metric is Disability-Adjusted Life Years (DALYs), which includes both morbidity and mortality. The growing use of DALYs is primarily driven by WHO and the Global Burden of Disease (GBD) study [ 171 ], as they use this metric when estimating burden of disease (BoD) attributable to several risk factors in addition to a wide range of physical and mental disorder and disabilities. In 2011, WHO estimated DALYs attributable to transportation noise in Western Europe for the first time [ 172 ], using noise exposure data assessed according to the Environmental Noise Directive, 2002/49/EC (END). High noise annoyance, high degree of sleep disturbance, IHD, cognitive impairment, and tinnitus were included as health outcomes in this BoD assessment by WHO. Since then, the European Environmental Agency has estimated environmental noise to be the second most important environmental risk factor, after air pollution, in driving disease burden in the EU [ 173 ]. Noise was associated with 22 million DALYs due to high annoyance, 6.5 million DALYs due to high sleep disturbance, 48,000 DALYs due to IHD, and 12,000 premature deaths (due to IHD) per year. As described above, the knowledge in the field of noise and health has grown rapidly since the WHO systematic review was published in 2018 [ 2 ]. Updated knowledge of the causal association between noise and various health outcomes from high-quality studies is an important pillar in health impact assessment. Only a limited number of studies have estimated the disease burden due to environmental noise [ [174] , [175] , [176] , [177] , [178] , [179] , [180] ], and these studies often differ in methodological aspects, which makes comparison across areas and studies difficult. To estimate DALYs, several input parameters are required. In addition to selecting health outcomes with associated exposure-response functions, noise exposure distribution and health data are needed for the population for which the calculations will be performed. A recent BoD study in the Nordic countries, Denmark, Finland, Norway, and Sweden, aimed at using a harmonized approach and comparable input data to estimate DALYs attributable to road traffic and railway noise [ 179 ]. This study also addressed the influence of methodological choices in the estimation of BoD. Noise exposure assessment according to END was used as the primary source of exposure. In addition, nationwide noise models were available for Denmark and Norway. Transportation noise contributed with a considerable disease burden in the Nordic capitals, between 300 and 500 DALYs/100,000 for road traffic noise and 40–150 DALYs/100,000 for railway noise. The estimated BoD attributable to road traffic noise was found to be in the same order of magnitude as for PM 2.5 air pollution, as reported by GBD. Furthermore, the DALY estimates for road traffic noise were increased with up to 17 % when stroke and diabetes were included in addition to the high annoyance (HA), high sleep disturbance (HSD), and IHD. In addition, several important methodological findings were uncovered. First, the assessment based on noise exposure data according to END considerably underestimated the burden due to transportation noise at the national level. The study revealed considerably higher DALY rates attributable to road traffic noise when based on the nationwide models compared to END. Thus, the degree of coverage contributes considerably to the higher estimates for the nationwide models. Secondly, the study revealed different interpretations across the Nordic countries of the geographical areas to be included in the END noise mapping and the noise exposure assessment method. Thus, no comparable DALYs attributable to noise could be assessed for the Nordic countries, only for the capital cities using additional noise exposure data beyond what was reported to the European Commission according to END. Differences in definitions of agglomerations according to END across geographical areas and time have also previously been reported for European countries [ 181 ]. Lastly, by using lower cut-offs of L den and L night the DALY rates for HA and HSD increased by up to 40 % compared to the estimates based on the END mapping thresholds (L den 55 dB and L night 50 dB). Another recent BoD study estimated DALYs from HA, HSD, IHD, stroke, and diabetes attributable to long-term transportation noise exposures in England for the adult population in 2018. It was concluded that ∼97,000 DALYs are lost due to road traffic, ∼13,000 due to railway, and ∼17,000 due to aircraft noise [ 180 ]. It is important to further update the scientific evidence and to develop harmonized methods to reliably quantify the BoD of environmental noise. Previous BoD studies have selected a few specific outcomes but none of them have considered new studies on e.g., all-cause mortality as discussed in the previous chapter (1.3.10). Thus, current BoD estimates are expected to substantially underestimate the impact of transportation noise. As transportation noise contributes considerably to the environmental BoD, inclusion of noise as an environmental risk factor in the GBD is strongly encouraged. Pathophysiological mechanisms of noise exposure General pathophysiological mechanisms Decades of research investigating the detrimental health outcomes of noise exposure have identified ‘direct’ and ‘indirect’ pathways that contribute. The direct pathway describes the manner in which high-intensity noise produces mechanical damage in the inner ear and the downstream physiological responses to such an exposure ( Fig. 8 ). The indirect pathway, on the other hand, was suggested by Babisch in 2002 [ 182 ], and describes how noise exposure at “sub-hazardous” intensities for the cochlea is able to elicit cognitive, emotional, and physiological responses. Both pathways contribute to stress responses, which lead to elevated levels of catecholamine, adrenocorticotropic hormone (ACTH), and cortisol secretion via SNS and HPA activation. Sound is perceived by the auditory cortex and the stress response is thought to be activated in hypothalamus but the exact sequence of signaling events, interplay between different brain regions and identity of activated neurons remains to be fully elucidated and are the subjects of ongoing investigations [ 183 ]. Chronic activation of stress systems contributes to peripheral and central adverse health effects [ 29 ]. Exposure to loud or unwanted noise can interrupt sleep, cause emotional stress, or disrupt daily activities. Reduced sleep quantity and quality, and chronic stressors can mimic many of the effects that are observed following noise exposure, including decreased melatonin production which result in disruption of the circadian and endocrine systems and an increased allostatic load [ 184 ]. Impaired sleep also increases leptin and ghrelin levels as well as appetite, coinciding with reduced insulin sensitivity [ 184 ]. Chronic activation of the HPA axis leads to high cortisol levels, which can heighten risk factors for CVDs, including increased blood pressure, vascular reactivity, and anxiety [ 185 ]. In concert, sympathetic activation can increase blood pressure as well as proinflammatory and procoagulant responses [ 186 ]. Overall, noise triggers neuroinflammation and cerebral oxidative stress, blood pressure increases, endothelial dysfunction, cardiovascular and systemic oxidative stress, inflammation and myelomonocytic infiltration of peripheral tissues, and dysregulation of circadian rhythms ( Fig. 8 ) [ 13 ]. Mechanistically, these noise-induced disruptions activate the endothelin-1 (ET-1) pathway and RAAS, leading to vasoconstriction and a rise in circulating inflammatory markers including tumor necrosis factor-alpha (TNFα), interleukins IL-1 and IL-6, and C-reactive protein (CRP), and oxidative stress biomarkers [ 184 ]. In addition, ET-1 and RAAS activation contribute to medial thickening, structural remodeling and hypertrophy (as mentioned in section 1.2 ) promoting the onset of heart failure by noise exposure [ 37 , 38 ]. The original concept of “oxidative stress” was formulated in 1985 as “ imbalance of prooxidants and antioxidants in favor of the prooxidants ” [ 188 ]. In subsequent years, progress in redox research on the role of oxidants in redox signaling and redox regulation called for an update of the concept [ 189 ], which led to the updated definition of oxidative stress as “ an imbalance between oxidants and antioxidants in favor of the oxidants, leading to a disruption of redox signaling and control and/or molecular damage ” (reviewed in Ref. [ 190 ]). In order to account for the beneficial versus detrimental nature of oxidative stress, different subforms of oxidative stress were classified, ranging from physiological oxidative stress (eustress) to excessive and toxic oxidative burden (distress) [ [190] , [191] , [192] ]. Hydrogen peroxide is a central redox signaling agent in physiological oxidative stress (eustress) [ 193 ]. In the context of noise exposure, one could ask whether a physiological low level of noise is required, especially when in view of a comfortable social environment, to contribute to health-promoting eustress, such as the documented positive psychosocial effects of music. In contrast, high levels of (annoying) noise initiate detrimental distress. Whether prolonged absolute silence is beneficial or harmful needs to be examined. Oxidative stress from any source, including NOX2-derived or mitochondrial H 2 O 2 /O 2 •− [ 194 ], can trigger ET-1 expression [ 195 , 196 ], which can then lead to a vicious circle that contributes significantly to the cardiovascular oxidative stress and damage [ 197 ]. In hypertensive rats, plasma angiotensin II (one product of RAAS) and ET-1 levels are positively correlated with blood pressure [ 198 ], and both are decreased following treatment with bosentan (ET A/B receptor blocker), implying crosstalk between the two systems [ 199 ]. The connection between these two pathways has a potent physiological influence and triggering either pathway can produce a strong vasoconstrictive stimulus. Bulk RNA sequencing of heart, kidney, and aorta in a translational murine model of noise exposure indicated downregulation of antioxidant enzymes (superoxide dismutase 1, glutathione peroxidase 1) as well as the transcription factor Forkhead box protein O (FOXO). This implies that noise activates systems leading to oxidative stress (i.e., activation of inflammatory myeloid cells) at the same time as downregulating expression of the antioxidant enzymes [ 14 , 16 ]. Fig. 9 summarizes some of the oxidative stress-driven pathomechanisms linked to noise exposure that results in an increased susceptibility to various diseases [ 29 ]. Understanding the crosstalk between the stress response, oxidative stress and vasoconstrictor mechanisms has been vital in understanding how noise elicits detrimental health effects. Pre-clinical models using approaches that directly and indirectly study stress as a key component support the association [ 13 , 22 , 67 , 200 ]. Critically, glutamatergic signaling in the amygdala of rats [ 201 ] and heightened amygdala activity in humans [ 47 , [202] , [203] , [204] ], are indicative of stress-induced arousal, and appear to be enhanced following noise exposure. Corticosterone is increased in the plasma of noise-exposed rats and mice [ 29 ], implying activation of the HPA axis. Increases in plasma and kidney adrenaline and noradrenaline indicate sympathetic activation in noise-exposed mice [ 14 ] and rats [ 205 , 206 ]. Activation of these stress response systems corresponds with detrimental cardiovascular readouts in murine models of noise exposure, including hypertension [ 207 , 208 ], increased myocardial fibrosis [ 209 ], and atrial interstitial fibrosis [ 210 ]. Of note, enhanced stress hormone signaling has also been associated with a higher risk of cancer [ 211 ], and increased amygdala metabolic activity was reported to correlate with adiposity [ 202 , 212 ] and diabetes [ 213 ], in relation to noise exposure. The clinical correlates of this noise-induced stress response are summarized in Textbox 2 . The subsequent sections shed light on the downstream molecular mechanisms. Noise-dependent adverse effects on the cardiovascular system Investigation of the cardiovascular health effects of noise in humans dates back to the 1960s. An early study revealed that noise exposure led to the narrowing of peripheral blood vessels in individuals engaged in exercise [ 224 ] . Another study claimed that exposure to noise or music elicited variable cardiac output and minute flow and concluded that it was the stimulus' intensity rather than the nature of the sound caused the responses [ 225 ]. A study supporting this conclusion included 1005 German industrial workers, showing that workers in noisy industries were more likely to have problems of the peripheral circulation and heart as well as disturbed balance [ 226 ]. These studies describe the ‘direct’ pathway of the noise reaction scheme, but only account for noise exposure during waking hours. Also, factory workers exposed to high noise levels (L Aeq > 80 dB(A)) were found to have significantly higher glutathione peroxidase levels, systolic and diastolic blood pressure, and DNA damage than office workers (L Aeq 40–50 dB(A)) [ 227 ]. Exposure to one night of transportation noise in humans was sufficient to increase blood pressure the following day [ 228 , 229 ]. This is likely due to interference with blood pressure dipping by repeated nighttime autonomic arousal [ 230 ]. Another human field study found that one night of aircraft noise exposure (L eq 46.3 dB (A) , peak level 60 dB (A) ) reduced sleep quality, increased stress hormone levels, caused endothelial dysfunction, and decreased pulse transit time (reflecting SNS activation) in healthy individuals ( Fig. 10 ) [ 30 ]. Notably, when exposed to noise while awake, feelings of “annoyance” appear to be linked to conditions such as anxiety and depression [ 231 , 232 ] as well as atrial fibrillation [ 24 , 233 ]. In two additional small human field studies, vitamin C was shown to alleviate endothelial dysfunction associated with one night of aircraft noise exposure or railway noise ( Fig. 10 ) [ 30 , 234 ], suggesting that oxidative stress plays a key role in the underlying pathophysiology [ 235 ]. Healthy individuals subjected to either 30 or 60 train noise events during the night (average SPL of 52 and 54 dB(A)) resulted in reduced sleep quality and impaired flow-mediated dilatation (FMD) of the brachial artery compared to control individuals exposed to background noise (average SPL 33 dB(A)) [ 234 ]. Furthermore, the plasma proteome of these subjects appeared to shift toward a pro-thrombotic and pro-inflammatory state. Additionally, the SAPALDIA consortium reported that chronic exposure to nocturnal intermittent train or road traffic noise correlated with arterial stiffness, measured as pulse wave velocity [ 236 ]. These investigations and others underline the importance of sleep disruption as a cardiovascular risk factor. Importantly, these studies also indicated that noise can impact health even when subjects are apparently unaware. These human studies, pointing to the involvement of inflammation, oxidative stress or adverse redox signaling in noise-related CVD, are further supported by mechanistic animal studies described in the preceding sections, building upon previous reviews [ 13 , 22 , 67 , 200 ]. Given the high incidence of CVD and the fact that IHD was the first disease directly linked to noise exposure, it is important to investigate how noise can affect the risk and severity of CVDs. It should also be kept in mind that epidemiological studies have linked noise exposure with a higher risk of other major diseases, including diabetes, cancer, and dementia (see section 1 ). One of the few human studies investigating the impact of noise on CVD-associated pathways reported that one night of aircraft noise was enough to increase serum levels of 3-nitrotyrosine-modified proteins in patients with established coronary artery disease [ 16 , 237 ]. This is strong evidence for an increased oxidative stress. Endothelial dysfunction was also pronounced in these patients, suggesting that a compromised endothelium or pre-activated oxidative milieu could predispose to the harmful effects of noise. The exposure of healthy volunteers to one-night of noise (L eq 45 dB(A)) also impaired diastolic heart function, as assessed through sequential echocardiography, compared with a control group (L eq 37 dB(A)) [ 238 ]. Importantly, endothelial dysfunction is also an early marker of diabetes [ 239 ] and this relationship could partially explain the link between higher amygdala activity and the cardiometabolic effects of transportation noise [ 240 ]. High-intensity industrial noise during longer periods was also found to induce hypertension in rhesus monkeys [ 207 ] and in rats [ 242 ]. Furthermore, rats exposed to very high levels of white noise (100 dB(A)) had impaired endothelium-dependent relaxation of the thoracic aorta, higher sensitivity to the vasoconstrictor agonist serotonin, and increased systolic blood pressure [ 243 , 244 ]. The latter studies used very high SPL levels that could incur physical damage, however, studies of “sub-hazardous” levels of noise exposure (<80 dB(A)) are rare. More recent studies investigated the effects of aircraft noise on cardiovascular biomarkers by exposing mice to around the clock lower SPL (e.g., aircraft noise with a L eq of 72 dB(A) and peak level of 85 dB(A) for 24 h for 1, 2 and 4 days) [ 14 , 16 ]. These identified a significant noise-induced increase in stress hormone levels, blood pressure, and vascular and cerebral oxidative stress, all associated with impaired endothelial function and diminished vascular nitric oxide levels ( Fig. 11 ). While the protocol of noise exposure in experiments with animals has differed quite markedly between studies, the physiological consequences have been consistent and comparable to the results reported in humans. In animal studies, RNA-sequencing has revealed noise-induced dysregulation of gene networks associated with endothelial and vascular signaling and even potential risk marker genes [ 14 ]. Importantly, mice exposed to white noise (similar exposure time and mean SPL as to aircraft noise) did not show these cardiovascular effects, implying that noise characteristics (such as frequency or pattern) rather than the SPL determine the extent of cardiovascular damage [ 14 ]. Since white noise represents a continuous “swoosh” including a broad range of frequencies, it may be even the pattern of aircraft noise based on the intermittent irregular crescendo and decrescendo sound levels of the starting and landing events. Aircraft noise exposure during sleep was substantially more detrimental to the cardiovascular system than exposure during the awake phase, and cardiovascular damage was almost entirely prevented by Nox2 deletion, pointing to the crucial role of inflammatory cells in mediating noise-induced cardiovascular effects [ 16 ]. In mice, endothelial dysfunction and blood pressure increases were established very rapidly i.e., on the first day of noise exposure, and persisted over 4 weeks of continuous noise exposure, indicating no apparent adaptation [ 245 ]. However, when noise exposure ceased, vascular dysfunction and oxidative stress in conductance vessels returned to normal within 4 days, whereas the damage to microvessels of the brain, envisaged by ROS formation and impaired relaxation persisted [ 246 ]. Importantly, noise exacerbated blood pressure increases and endothelial dysfunction in mice with pre-existing hypertension (induced by angiotensin-II infusion) [ 247 ] and aggravated cardiovascular damage in three models of diabetes (unpublished data, Mihalikova et al.). Moreover, exposure to aircraft noise for 4 days primed the cardiovascular system in favor of an inflammatory phenotype with enhanced H 2 O 2 /O 2 •− formation and infiltration of pro-inflammatory immune cells. The latter resulted in exacerbated damage of the heart and impaired cardiac function in mice subjected to MI by ligation of the left anterior descending artery [ 248 ]. Exposure of animals to noise prior to MI also increased cardiac mitochondrial O 2 •− formation, impaired mitochondrial respiration and increased pro-inflammatory cytokines in the heart. In addition, noise pre-exposure also caused endothelial dysfunction, and more pronounced increases in vascular ROS levels. This correlates well with observations from the population-based Gutenberg Health Cohort Study as subjects with incident MI at follow up revealed elevated CRP at baseline and worse left ventricular ejection fraction (LVEF) when they had a history of high noise exposure and subsequent annoyance at enrolment [ 248 ]. The most studied effects of noise on the development of CVD and death due to CVD in humans are summarized in sections 1.3.1 , 1.3.2 , 1.3.3 , 1.3.4 . For more mechanistic insight and human studies on adverse cardiovascular effects of noise please refer to Refs. [ 13 , 22 , 200 ]. Noise-dependent adverse effects on the brain Noise can elicit a variety of responses that ultimately culminate in neuropsychiatric disorders ( Fig. 12 ), including neuroanatomical changes [ 249 , 250 ]. In animal studies, very high-intensity noise pulses (≈200 dB) were found to increase the expression of the proto-oncogenes c-Fos and c-Myc. This happened in the cortex, thalamus, and hippocampus as rapidly as 2 h after exposure. While c-Myc levels returned to control levels after seven days, c-Fos remained elevated for at least 21 days. Additionally, β-amyloid precursor protein (APP) levels increased, creating a phenotype indicative of human traumatic brain injury and Alzheimer's disease [ 251 ]. While this study provided early evidence of noise-provoked damage in the brain, the intensity of noise was very high and not representative of average noise exposure in everyday life. Other studies using lower-intensity noise have, however, generally supported that noise produces damage within the brain [ 125 ]. Cheng et al. used a murine noise exposure model of 80 dB SPL, 2 h/day for 1–3 weeks, and found that noise could cause structural and functional changes in the auditory cortex and hippocampus [ 252 ]. They additionally suggested that while the auditory cortex was affected by a realistic level of noise, it appeared that the hippocampus (a non-auditory brain structure) was more vulnerable, meaning that there are aspects to how noise ‘propagates’ within the brain that are poorly understood. It is becoming evident, however, that nonauditory symptoms do arise, and noise-induced stress has been found to impair cognition and motor coordination and to cause changes in feeding behavior, fear, and anxiety, possibly arising due to metabolic and anatomical changes in neurons [ 253 , 254 ]. Feeding behavior seems to be particularly susceptible to change following stress. Indeed, humans [ [255] , [256] , [257] ] and animals [ [258] , [259] , [260] ] prefer more pleasurable food following exposure to stress, and noise is reported to impair eating and lactation behavior [ 255 , 261 ]. Chronic stress may elicit depressive disorders, and recent epidemiological studies have indicated that transportation noise may be associated with depression and other mental disorders [ 127 , 262 , 263 ], which was also supported by preclinical mechanistic data [ 249 ]. It has previously been mentioned that β-APP levels increased because of high-intensity noise exposure [ 251 ], indicating a potential link between noise exposure, stress, and neurodegenerative disease. There are standard mechanistic links between these diseases. Alzheimer's disease and dementia are both exacerbated by chronic inflammation and oxidative stress [ 265 ], likely through activation of protein kinase C (PKC) and protein kinase A [ 115 ], which can then hyperphosphorylate tau and lead to the aggregation of amyloid plaques [ 266 ]. APP, the protein from which amyloid beta (Aβ) is cleaved, is a transmembrane protein with a cholesterol-binding domain and is sensitive to oxidation by ROS [ 267 ], leading to alterations in membrane fluidity and lipid composition [ 268 ], and consequently, the growth of insoluble amyloid plaques that prevent or disrupt neuronal signaling and pruning [ 269 ]. There is an essential overlap in pathophysiological mechanisms between Alzheimer's and dementia with those of noise-elicited stress. Oxidative imbalance is a hallmark feature of noise exposure models in both humans and rodents, though neuroinflammation and oxidative stress have only been recorded in the brains of rodents [ 16 ]. Wistar rats subjected to 4 weeks of white noise (100 dB(A)) accumulated Aβ 40 and Aβ 42 in the hippocampus, which persisted for up to two weeks after noise cessation. These rats also manifested persistent elevations in glial fibrillary acidic protein (GFAP) staining, which indicates astrocyte activation, as well as increases in TNFα and the receptor for advanced glycation end (RAGE) products, indicating that both inflammatory and oxidative processes were likely taking place in the brain of exposed rats [ 270 ]. Thirty days of noise exposure has also been reported to cause tau phosphorylation in the hippocampus [ 271 ] and increased CRH. These studies are meaningful proofs-of-concept that noise can interact with critical pathways for the pathogenesis of Alzheimer's disease. It should also be noted that these experiments typically studied quite young animals (∼8 weeks). The ability to clear amyloid plaques is reduced with age [ 272 ], suggesting that a more severe phenotype could be observed in older populations. Associations between transportation noise and the risk of Alzheimer's disease have only been investigated in a few studies (e.g., Ref. [ 132 ]), suggesting transportation noise as a significant risk factor for neurodegenerative diseases (described in detail in section 1.3.7 .). There are also studies indicating that noise exposure can impair cognition [ 273 ]. This is likely to occur through the stress hormone-dependent mechanism previously described, as plasma corticosterone was significantly increased in rats following 1, 15 or 30 days of 4-h of 100 dB noise exposure [ 274 ]. The latter effects were coincident with increases in superoxide dismutase expression and lipid peroxidation. These rats also had changes in dendritic spines count in the hippocampus and prefrontal cortex and deficiencies in their working and reference memory [ 275 , 276 ]. Other studies have produced similar results by demonstrating a reduction in dendritic processes in the hippocampus of noise-exposed rodents, leading to impairment in memory as well as oxidative stress [ 270 , 277 ]. Increased dopamine levels in the brain following noise stress [ [278] , [279] , [280] ] also point to an oxidative influence in these symptoms, as dopamine can be metabolized by monoamine oxidase (MAO) to generate H 2 O 2 . Hydrogen peroxide can activate further ROS sources, which perpetuates the production of other oxidative species and leads to ROS-mediated changes in the morphology of cerebellar Purkinje cells [ 280 ]. A neuroinflammatory phenotype involving astrocyte and microglial activation and subsequent oxidative stress was reported in mice following moderate-intensity noise exposure for four days ( Fig. 9 ) [ 281 ]. These symptoms were more severe in mice with pre-existing hypertension and primarily associated with noise exposure during sleep [ 16 , 247 ]. Nox2 knockout mice were protected from these effects, underlining the important role of ROS (H 2 O 2 /O 2 •− ) and phagocyte dysregulation in perpetuating the damage in the brain following noise exposure [ 16 , 187 ]. Accordingly, it is not surprising that noise has been associated with a higher risk of stroke, especially ischemic stroke (see section 1.3.3 ). Since stroke is a vascular disease, the same pathophysiological mechanisms are active as described for vascular/endothelial damage in the preceding section, with a central role of inflammation and oxidative stress, both key determinants of stroke development and pathophysiology [ 282 , 283 ]. Concerning the permeability of the blood-brain barrier, there is some mechanistic evidence indicating that noise exposure results in its disruption, and substantial peripheral immune infiltration in the brains of noise exposed mice was recently observed [ 281 ]. For example, the exposure of pigs to low-frequency but high-intensity noise (140 dB(A)) increased permeability of the blood-brain barrier due to leaky tight junctions [ 284 ]. The most important human correlates for noise effects on the brain are reported in Textbox 3 , and more mechanistic insights and human studies on neuropsychiatric effects of noise were summarized previously [ 125 , 285 ]. Impaired sleep Another significant health impact of nighttime noise is sleep disturbance [ 200 , 292 ]. It is well established that insufficient sleep profoundly impacts upon mental health [ 293 , 294 ]. Furthermore, sleep fragmentation and deprivation in general, and in response to nocturnal noise, are established cardiovascular risk factors [ 295 , 296 ]. Several studies have found nighttime aircraft noise to be associated with hypertension in people living near airports [ 228 , 297 , 298 ], other studies, however, failed to confirm this [ 299 ]. The underlying pathomechanisms may be related to circadian dysregulation of metabolic, endocrine [ 300 ], and immune pathways [ 301 ]. Sleep restriction [ 302 ] and fragmentation [ 303 ] also induce endothelial dysfunction and potentiate cerebral oxidative stress [ 304 ], likely due to increased NADPH oxidase (mainly NOX-2) activation. Similarly, chronic aircraft noise has also been associated with learning and memory impairment in children [ 286 ], possibly due to inappropriate activation of NOX-2 [ 305 ]. There is also translational evidence that this enzyme is a critical component of noise-induced adverse cerebral and cardiovascular complications; mice with a genetic deletion of NOX-2 (gp91phox-) were almost completely protected from noise [ 16 ]. NOX-5 could be another candidate for noise-induced ROS formation in humans but was so far not studied. The overlap in the pathophysiological mechanisms of noise and impaired sleep is supported by several human studies. For example, a field study of 75 healthy adults subjected to overnight aircraft noise demonstrated that noise impaired sleep quality, increased adrenaline, and subsequently worsened endothelial function - as determined by FMD [ 30 ]. Further, these effects were noise exposure-dependent, clearly linked to the “indirect pathway”. Human studies have been supplemented by translational work, including a study in mice by Carreras et al. that demonstrated endothelial dysfunction and arterial hypertension following 20 weeks of sleep deprivation/fragmentation [ 303 ]. Furthermore, the vascular walls showed structural alterations, with disturbed elastic fiber arrangement and aggregated foam cells and macrophages, and the sleep-deprived mice expressed lower levels of mRNA encoding the senescence markers telomerase reverse transcriptase (TERT) and cyclin A, the tumor suppressor p16 INK4 as well as higher levels of IL-6 [ 303 ]. In other animal studies, sleep fragmentation was linked with insulin resistance, NADPH oxidase activation [ 306 ], and increased oxidative stress [ 307 ], which mirror pathomechanistic elements of noise exposure. Similarly, links between sleep deprivation, increased oxidative stress, manic-like behavior, and memory impairment have also been made in mice [ [308] , [309] , [310] ], all triggered by HPA and SNS activation. Sleep was also shown to protect against atherosclerosis [ 311 ]. Overall, there is a remarkable overlap in symptoms and readouts of oxidative homeostasis and inflammatory activation between sleep fragmentation/deprivation and noise exposure, as highlighted by mechanistic mouse studies of noise-induced cerebral and cardiovascular damage (reviewed in Refs. [ 13 , 22 ]). Significantly, in mice, noise exposure during the sleep phase contributed to the bulk of the cardiovascular and cerebral damage, with only minor contributions from exposure during the waking phase [ 16 ]. RNA sequencing of noise-exposed mouse kidney, heart, and aorta homogenates also revealed that FOXO3 signaling could be the molecular crux of circadian disruption following poor sleep quality, as the transcriptional trigger for noise-induced vascular damage via oxidative stress and inflammation. The role of the impaired circadian clock for noise-induced adverse health effects is explained in more detail in section 2.3.3 . Infrasound refers to frequencies below 20 Hz, while low-frequency sound covers 20–200 Hz. These types of sound come from many environmental sources, including machinery like compressors and ventilation systems, as well as traffic noise. Research shows that wind turbines can generate low-frequency noise exceeding 20 dB inside nearby homes [ 312 ], and emerging evidence has linked low-frequency sound with health effects. This is important given the future shift towards renewable energy and its implications for population health. Wind turbine noise has been associated with some negative health effects, particularly annoyance and sleep disturbance, in those living close to wind farms [ 313 , 314 ]. The noise level for wind turbines is associated with multiple factors apart from proximity e.g., wind speed (and its variations) and other meteorologic factors (e.g., wet weather, fog). Overall, evidence indicates that the level of audible noise from wind turbines increases annoyance in nearby residents [ 315 , 316 ] with some studies reporting that annoyance to wind turbine noise is higher than that for traffic-related noise [ 314 , 317 ]. Self-reported sleep disturbance also appears to increase with proximity to wind turbines. One study from Canada has shown that the aggregate annoyance from wind turbines is linked with multiple factors beyond noise, including vibrations, visual impact and shadow flicker, blinking warning lights, and those factors (in addition to noise) explained two thirds of the reported annoyance variability [ 318 ]. However, studies using objective measures of sleep have not consistently detected any effect of wind turbine noise on sleep quality or duration. The evidence for impacts on cardiovascular health, mental health, cognitive function and metabolic processes is limited and inconsistent. A sham-controlled trial of infrasound exposure did not pick up any relationship between infrasound and the health factors examined such as somatic and psychiatric symptoms, sound-sensitivity, sleep quality, cognitive performance, and structural MRI [ 319 ]. Research on health impact of infrasound is challenging given the ubiquitous nature of infrasound (e.g., from wind, ocean waves, and earth vibrations), and the difficulty in differentiating the actual effects of infrasound from just sensing its presence. Noise-dependent adverse effects on the intestine via the gut microbiome It is now widely accepted that the gut microbiome influences critical biological processes. Disruption therein can influence inflammation and redox signaling in the gastrointestinal tract and, thereby, impact cardiometabolic health ( Fig. 13 ) [ 320 , 321 ]. Gut health appears to influence mood and behavior via a gut-brain axis that can also affect the development of psychiatric disorders and intestinal inflammatory disease [ 322 , 323 ]. Few studies have directly addressed the interaction between noise and the gut microbiome. One study, however, reported that exposure to noise for 4 h during the sleep phase of mice over a period of 30 days, caused alterations in the gut-brain axis (e.g., intestinal tight junction proteins and neurotransmitters) [ 324 ]. This study used a mouse model for Alzheimer's disease and reported both cognitive impairment and the accumulation of Aβ, supporting previous studies (see section 2.1.2 ) linking noise with neuropsychiatric disease. However, the authors also reported decreased levels of the neurotransmitters serotonin and gamma-aminobutyric acid (GABA), increased readouts of inflammation, and impaired tight junction protein expression (claudins, occludin) coupled with changes in the balance of intestinal flora by 16S ribosomal RNA sequencing [ 324 ]. Additionally, feces from the noise-exposed mice resulted in an Alzheimer's-like phenotype when transplanted into unexposed mice. Taken together, these results could indicate a mechanism where stress or poor-quality sleep because of noise compromises the intestinal barrier, which then disrupts normal homeostasis in the gut and creates a feedback loop within the gut-brain axis Fig. 13 ). A second study also reported changes in pro-oxidative and antioxidant pathways and inflammation following noise exposure in mice [ 325 ], compounded with similar reports in another rat study that also found evidence that glucose metabolism was disturbed following 30 days of noise exposure [ 326 ]. These stressed rats also exhibited elevated glycogen and triglycerides in the liver and IL1β and TNFα in the intestine, indicating a disturbance in both metabolism and inflammation. Another report described a shift in gut species from health-promoting actinobacteria to health-compromising proteobacteria, that was also accompanied by increases in TNF-α and IL-1β and changes in body weight [ 327 ]. Apart from proinflammatory and metabolic effects, anxiety-like behavior has also been reported in rats exposed to noise in conjunction with increased corticosterone; once again pointing to increased stress as the ignition for these symptoms [ 328 ]. Interestingly, probiotic treatment alleviated these symptoms by restoring the functional interaction of the gut-brain axis ( Fig. 13 ). Treatment of noise-exposed rats with Lactobacillus rhamnosus GG prevented cognitive deficits and systemic inflammation by modulating the gut-brain axis (e.g., restoration of behavior and corticosterone levels) [ 329 ]. Additionally, a recent study found higher gut microbial diversity in sparrows living in a noisy environment, suggesting that urban sparrows have higher bacterial wealth than their rural counterparts, which was also associated with increased corticosterone and decreased food intake [ 330 ]. While studies directly connecting noise, gut health, and disease symptoms are sparse, the results generally agree with mechanisms and symptoms reported in other models, suggesting that the effects of noise are perpetuated throughout the body by nonspecific and broad effects. It also suggests that disturbances in one system (i.e., gut) could exacerbate dysregulation in another system (i.e., vasculature) to promote pathogenesis [ 331 ]. In summary, the gut microbiome plays an important role in immune system (de)activation in response to different noise patterns [ 332 ]. Noise exposure, aging, and age-related diseases Substantial experimental evidence in animals supports the role of noise exposure for accelerated aging, and both experimental and clinical studies clearly show the key role of noise exposure promoting age-related diseases. Indeed, the aging process is greatly modulated by the environment. Accordingly, common pathophysiological mechanisms, including mitochondrial oxidative stress, impaired nitric oxide signaling, endothelial dysfunction, and inflammation, have been found in the context of noise exposure [ 227 , 333 , 334 ] as well as in age-related diseases, such as Alzheimer's and Parkinson's diseases, renal dysfunction, retinopathy, and CVDs [ 45 , 285 , 335 ]. Furthermore, noise exposure can induce cognitive deficit, especially in spatial learning and memory performance [ 265 , 336 , 337 ], and chronic noise was found to lead to overproduction of amyloid β and tau hyperphosphorylation in the hippocampus and prefrontal cortex in senescence-accelerated mouse prone 8 (SAMP8) mice [ 338 ]. The auditory system is the one most affected by noise exposure upon aging. Indeed, synaptopathic noise (100 dB) accelerates cochlear aging [ 339 ]. Noise exposure is considered a major cause of age‐related hearing loss, called presbycusis [ 340 ], mainly by related to cochlear synaptic loss [ 156 , 341 ] and sensory cell degeneration of the outer hair cells at the high frequency end of the cochlea. Presbycusis seems to result from damage to mitochondrial DNA and subsequent mitochondrial dysfunction [ 340 ], and noise enhances the age-related oxidative stress in the cochlea by increasing superoxide production and lipid peroxidation [ 342 ]. Sources of oxidative stress and detection of reactive oxygen species Clinical and epidemiological data also show an association between typical oxidative stress markers, such as lipid peroxidation products, 3-nitrotyrosine or oxidized DNA/RNA bases, with all significant non-communicable diseases of cardiovascular [ [343] , [344] , [345] ], metabolic [ 39 , 40 ] or neurodegenerative origin [ 42 , 346 ] as well as with different forms of cancer [ 41 , 347 ]. Especially ischemic heart disease is tightly linked to mitochondrial H 2 O 2 /O 2 •− formation and oxidative tissue damage [ 348 ]. Since oxidative stress is a hallmark of most non-communicable diseases, it is important to know more about the sources of H 2 O 2 /O 2 •− , and to gain insight into the mechanisms of oxidative damage, thereby providing better understanding of noise-induced diseases described in the first part of this position paper. NADPH oxidases NOX-2 (gp91phox), which was referred to frequently in the previous sections, is the enzymatic weapon used by myeloid phagocytes to combat immune insults. This enzyme allows actors within the innate immune system to produce toxic oxidants to destroy engulfed pathogens-a critically important action in host defense. However the same machinery can also be inappropriately deployed and activated in response to sterile inflammation; a dysregulation that contributes to endothelial dysfunction [ 354 , 355 ], hypertension [ 356 , 357 ], IHD [ 358 ], and atherosclerosis [ 359 ]. Whereas the involvement of different NADPH oxidase isoforms (e.g., NOX-1, NOX-4, NOX-3, and DUOX-2) in noise-induced hearing loss is well established [ [360] , [361] , [362] ], only a few studies have provided information about the role of NADPH oxidases in the non-auditory (indirect) pathology. Upon exposure to noise, NOX-2 protein and Nox2 mRNA levels are consistently upregulated in the murine aorta and heart [ 14 , 248 , 281 ]. Also, a more pronounced activation state of NOX-2 was reported for noise-exposed mice, which was driven by angiotensin-II dependent diacylglycerol-mediated PKC activation with subsequent Ser328 phosphorylation of p47 phox ; the cytosolic regulator of NOX-2 ( Fig. 14 ) [ 16 ]. Accordingly, the oxidative burst in whole blood of noise-exposed mice, which is mainly driven by phagocytic NADPH oxidase in leukocytes, was more pronounced than in unexposed mice [ 16 ]. The latter finding was further supported by slightly higher serum levels of soluble NOX-2-derived peptide (sNox2-dp, an ELISA-based measure of NOX-2 activation) in mice upon noise exposure [ 245 ]. Evidence of oxidative stress is readily detectable in the aorta, heart and brains from mice exposed to noise. Importantly, mice with a genetic deletion of Nox2 are protected from this oxidative stress as well as from the subsequent microvascular dysfunction in the cerebral microvessels and leukocyte-endothelial cell interaction [ 16 ]. Moreover, proteomic analyses demonstrated no noise-induced increase in inflammatory signaling in plasma from Nox2 knockout mice, a situation that was markedly different in samples from Nox2 expressing mice [ 363 ]. The enzyme can be targeted pharmacologically and the NOX-2 inhibitor, GSK2795039, quenched ROS signals in cerebral cryo-sections of noise-exposed mice [ 16 ], which overall points to this enzyme fueling the proverbial oxidative fire that arises. Further support for a central role of NOX-2 in noise-mediated pathophysiology comes from a study showing an additive upregulation of NOX-2 protein in noise-exposed hypertensive mice, mirrored by additive increases of aortic and cardiac superoxide formation [ 247 ]. A similar add-on effect of noise on NOX-2 expression and activity was also reported in mice that had experienced MI before noise exposure [ 248 ]. It was also shown that NOX-2-expressing cells were primarily responsible for noise-induced cardiovascular and cerebrovascular damage through a selective ablation protocol targeting cells expressing lysozyme M (LysM) (e.g., monocytes and macrophages) by overexpression of an inducible diphtheria toxin receptor [ 281 ]. By low dose treatment with diphtheria toxin these inflammatory cell subsets can be specifically killed, thereby removing the most prominent NOX-2 expressing cells. As a result, blood pressure, endothelial function, and oxidative stress parameters were not adversely affected in mice without LysM + cells exposed to noise. In the brains of noise-exposed mice, aggravated NOX-2 activation was observed in the form of phosphorylation of the significant cytosolic regulator of NOX-2, p47 phox , at serine 328, as well as activation of PKC, as measured by phosphorylation of the myristoylated alanine-rich C-kinase substrate (MARCKS) [ 15 , 16 ]. NOX-2 protein expression was also increased in cerebral micro-vessels [ 364 ]. In addition, Nox1 mRNA expression was increased in the brains of noise-exposed mice [ 16 ], an observation mirrored by enhanced 3-nitrotyrosine, ROS formation, and impaired microvascular function in cerebral arterioles [ 363 ]. Nox1 upregulation was also found in isolated lung endothelial cells [ 14 ]. In contrast, no upregulation of vascular NOX-4 in mice exposed to noise with low SPL (<80 dB(A)) was reported, although a tendency of higher NOX-4 levels in the brains of noise-exposed mice was noted [ 16 ]. Studies have also observed that noise-exposed mice had increased ET-1 expression in the aorta and that ET-receptor signaling was exacerbated as envisaged by more pronounced ET-1-dependent vasoconstriction [ 14 , 16 ]. Endothelin-1 exacerbates oxidative burden by directly inducing NOX-2 expression [ 365 , 366 ] and directing ET-receptor-dependent NADPH oxidase-derived O 2 •− formation and subsequently H 2 O 2 by dismutation. This second action can be illustrated by ex vivo ET A -receptor blockade of vascular cells [ 365 , 367 , 368 ] or white blood cells [ 36 ], resulting in reduced NOX-dependent O 2 •− and H 2 O 2 formation, as is also the case in hypertension [ [369] , [370] , [371] ]. Alternatively, catecholamines can activate astrocytes, microglia, and consequently NOX-2 [ 372 ]. Mitochondria Though NOX enzymes are essential generators of O 2 •− , H 2 O 2 and other ROS, they are not their sole source. Mitochondria are well-known producers of O 2 •− and H 2 O 2 and an important pharmacological target for treating IHD [ 373 , 374 ] but may have on impact on development of hypertension as well [ 375 , 376 ]. Interestingly, a study has found that some of the oxidative burden observed after noise exposure may be ascribed to mitochondria: rats exposed to low-frequency noise (≥90 dB(A), <500 Hz) had cardiac fibrosis, enlarged cardiac mitochondria and reduced connexin 43 content, indicating mitochondrial damage [ 377 ]. Mitochondrial connexin 43 content affects ROS formation [ 378 , 379 ]. Mitochondrial swelling, matrix dilution, cristolysis, and DNA damage have been reported in response to very loud noise (100 dB(A)) and linked to high noradrenaline levels, MAO activity, and disturbed mitophagy [ 380 , 381 ], possibly negatively impacting permeability transition (e.g., mPTP) and calcium handling [ 382 ]. Two different isoforms of MAO exist, namely MAO-A and MAO-B, both of which are located at the outer mitochondrial membrane (reviewed in Ref. [ 383 ]). Species- and cell type-dependent expressed MAO isoforms differ. Taking the heart as example, in rats MAO-A predominates at adulthood while in adult mice MAO-B dominates. Interestingly, in rat hearts, MAO-B activity also predominates up to an age of 2–3 weeks, most likely since MAO-B expression increases under mechanical strain as compared to the quiescent situation [ 383 ]. Human hearts contain both MAO isoforms, but with more, albeit moderate, expression for MAO-A in cardiomyocytes. The two MAO isoforms have common substrates, such as dopamine but also specific substrates: MAO-B can metabolize 1-methyl histamine, produced by the histamine-N-methyltransferase, while MAO-A metabolizes serotonin (or 5-hydroxytryptamin, 5-HT) and catecholamines. Interestingly, MAO-A contributes to serotonin- but not norepinephrine-dependent damage of rat ventricular myocytes [ 384 ]. MAO requires flavin adenine dinucleotide as a cofactor that is reduced by the reaction and subsequently re-oxidized by molecular oxygen, generating hydrogen peroxide. MAO can also form reactive aldehydes, such as 4-hydroxynonenal, as byproduct of catecholamine metabolism through cardiolipin peroxidation inside mitochondria in primary cardiomyocytes. Deleterious effects of 4-hydroxynonenal are physiologically prevented by its rapid metabolism [ 385 ], furthermore facilitated by the activation of mitochondrial aldehyde dehydrogenase 2 [ 386 ]. An increased expression/activity of MAO occurs during aging and with different cardiovascular diseases. While the underlying mechanisms of MAO upregulation are still unclear, one potential factor contributing to increased MAO expression/activity might be increased substrate availability. An increased sympathetic tone increases plasma norepinephrine and epinephrine concentrations. Serotonin concentrations are increased during different disease states (for review, see Ref. [ 387 ]) and part of the increase has been attributed to altered platelet function [ 388 ]. Histamine co-localizes with norepinephrine in neurons [ 389 ] and is enclosed in cytoplasmic granules of mast cells, which lie adjacent to blood vessels and between cardiomyocytes [ 390 ], and mast cell degranulation might occur under stress conditions [ 391 ]. Activation of MAO contributed to development of endothelial dysfunction [ 392 ] and irreversible cardiomyocyte injury in vitro [ 393 ] and in vivo [ 394 ], also the latter was restricted to males only. In the cochlea, loud noise (100–120 dB(A)) also activates SHC-transforming protein 1 (SHC1, p66 Shc ), a mitochondrial source of oxidative stress. Cochlear vascular dysfunction and transient noise-induced hearing loss subsequently arose [ 395 ]. p66 Shc is involved in the regulation of vascular tone [ 396 ], also during aging [ 397 ], with little effect on irreversible cardiac damage under stress conditions [ 398 ] (also reviewed in Refs. [ 399 , 400 ]). Some studies have reported that noise exposure <80 dB(A) can lead to mitochondrial ROS formation in the brains of noise-exposed mice [ 16 ] as well as higher superoxide formation rates in cardiac mitochondria [ 247 ]. An additive increase in mitochondrial superoxide levels was also seen in the hearts of noise-exposed mice with MI in conjunction with impaired mitochondrial respiration and oxygen handling [ 248 ]. Of note, whereas cerebral ROS formation (most probably superoxide) upon 1 or 2 days of noise exposure was fully responsive to NOX-2 inhibition or genetic deletion of Nox2, the ROS signal after 4 days of noise was still visible in the absence of NOX-2 activity, suggesting that mitochondrial ROS formation may play a role following chronic noise exposure [ 16 ]. Potential mechanisms of mitochondrial O 2 •− and H 2 O 2 formation in response to noise are summarized in ( Fig. 14 ). Catecholamines released upon noise-induced sympathetic activation could lead to hydrogen peroxide formation by MAO, enzymes that are potent mitochondrial H 2 O 2 sources using noradrenaline or adrenaline as substrates [ 401 ]. Another pathway of noise-induced mitochondrial O 2 •− and H 2 O 2 formation may consist of the PKC-dependent activation of the mitochondrial ATP-sensitive potassium channel (K ATP ) channel by phosphorylation at a threonine residue [ 402 , 403 ] with subsequent depolarization of the mitochondrial membrane potential leading to higher superoxide formation rates from respiratory complexes I, II, and III [ 197 ]. Finally, ROS-induced mPTP opening by thiol oxidation of the significant regulator cyclophilin D [ 353 ] may represent a mechanism for how noise could promote the release of mitochondrial calcium, O 2 •− and H 2 O 2 to the cytosol, activating redox- and calcium-sensitive kinases such as PKC [ 197 , 404 ]. However, it is unclear to what extent this mechanism contributes to noise-mediated pathophysiology. Uncoupled nitric oxide synthases Due to the excessive superoxide formation in noise-exposed animals, endothelial NOS (eNOS) in the aorta (and nNOS in the brain) uncouples, which means that it transforms into a source of O 2 •− and H 2 O 2 rather than, or in addition to • NO source ( Fig. 14 ) [ 45 , 405 ]. NOS uncoupling was previously demonstrated in tissues of noise-exposed mice by dihydroethidium staining in the presence of the eNOS inhibitor N G -nitro- l -arginine methyl ester ( l -NAME) [ 16 , 247 , 281 ]. eNOS is redox-sensitive because of its reliance on a readily oxidizable cofactor, tetrahydrobiopterin (BH 4 ). Without BH 4 , eNOS cannot produce • NO, but instead produces O 2 •− [ 355 ]. The concomitant formation of • NO and O 2 •− by uncoupled eNOS generates peroxynitrite, which in term reacts with proteins to result in their tyrosine nitration i.e. the appearance of 3-nitrotyrosine-positive proteins in the vascular wall of conductance and resistance vessels [ 14 , 248 , 363 ]. eNOS uncoupling diminishes • NO bioavailability in the aortas of noise-exposed mice as determined by the direct quantification of • NO using electron spin resonance spectroscopy [ 14 ] or via plasma nitrite levels [ 245 , 247 ]. eNOS activity is also regulated by the phosphorylation of the enzyme and a reduction in the phosphorylation of an activity promoting site (Ser1177) was also reported in hypertensive mice exposed to 7 days of aircraft noise [ 247 ]. Uncoupling of eNOS by noise at the same time as activating Ser1177 phosphorylation seems contradictory but may represent a futile counter-regulatory process. Increased plasma nitrite levels in noise-exposed rats have also been attributed to the action of inducible NOS [ 206 ], as is common in inflammatory conditions. Taken together, dysregulation or uncoupling of eNOS is a central event in the pathophysiology of CVD and is closely correlated with impaired endothelial function (see section 2.1.1 ). eNOS S-glutathionylation was also increased in the aorta and heart of noise-exposed mice [ 14 ]. The latter effect was not observed in Nox2 –deficient mice [ 16 ] and was aggravated in noise-exposed hypertensive or ischemic/reperfused mouse hearts [ 247 , 248 ]. eNOS activity can be inhibited by its phosphorylation on inhibitory sites that shut down • NO and O 2 •− production completely but no study has yet addressed the impact of noise on these mechanisms. Still, the kinases that phosphorylate the inhibitory sites in eNOS (i.e., PKC, protein tyrosine kinase 2 (PYK-2)) are redox-activated, so an involvement of this mechanism upon noise exposure is highly probable [ 45 ]. As a direct effect of loud noise in the cochlea of guinea pigs, inducible and endothelial NOS levels were upregulated, which likely contribute to nitrosative and oxidative stress [ 406 ]. The NOS enzyme that is preferably expressed in neuronal tissues, nNOS, appears to respond slightly differently to noise exposure than eNOS. Noise-exposed mice presented with downregulation and uncoupling of nNOS, an event that did not occur in Nox2 knockout mice [ 16 ]. Murine cerebral nNOS was also phosphorylated on serine 847 [ 16 ], which is an inhibitory site [ 407 ], possibly indicating an uncoupled nNOS enzyme [ 408 ]. This site is also redox-sensitive via calcium/calmodulin-dependent protein kinase [ 408 ]. Some support for the uncoupling of nNOS in the noise-exposed brain comes in the form of ex vivo inhibition with ARL-17477, which partially blocked the oxidative stress signal in cerebral tissue of noise-exposed mice [ 16 ]. The presence of noise-induced O 2 •− in the tissue may deplete vasodilatory • NO, resulting in a neuroinflammatory phenotype and loss of the protective antioxidant transcription factor Foxo3, exacerbating the oxidative imbalance and potentiating endothelial dysfunction in the brain [ 16 , 281 ]. These initial steps can produce a pro-oxidative/inflammatory phenotype explaining the observed impairment of cognitive development (memory/learning) of school children exposed to high noise levels [ 286 ], similar to the learning and memory impairment reported in adults [ 305 ]. An impact of dysregulated nNOS on impairment of cognitive and memory function seems feasible in light of direct effects of neuronal • NO on these processes or indirectly by the regulatory role of • NO on glutamate signaling Fig. 15 illustrates the mechanisms influencing the NOS coupling status in noise-exposed rodents. Detection of reactive oxygen species Superoxide The most used probe for the in vivo and in vitro detection of superoxide radical anion (O 2 •– ) is dihydroethidium (DHE, also known as hydroethidine, HE) [ 409 , 410 ]. This probe forms an O 2 •– -specific red fluorescent product, 2-hydroxyethidium (2-OH-E + ). It should be noted, however, that 2-OH-E + is not the only fluorescent product of DHE oxidation, and ethidium (E + ) is another fluorescent product that is formed during the oxidation of DHE by other oxidants. Also, heme proteins, including cytochrome c , are known to efficiently oxidize DHE to ethidium (E + ) and several dimeric products [ 411 ]. Therefore, increased red fluorescence is expected during apoptosis and is associated with mobilization of mitochondrial cytochrome c . This implies the need to selectively detect and quantify 2-OH-E + , typically accomplished using chromatographic techniques (HPLC with fluorescence, electrochemical or mass spectrometric detection) allowing separation and detection of different oxidation products [ 412 , 413 ]. Derivatives of DHE targeted to mitochondria (MitoSOX Red, MitoNeoD) or the extracellular space (hydropropidine) have been also reported [ [414] , [415] , [416] ]. The chemistry of those probes resembles the chemistry of DHE, and therefore the same recommendations regarding the detection of the O 2 •– -specific product apply [ 410 , 411 , 417 , 418 ]. Lucigenin has been used for chemiluminescent O 2 •– detection for more than two decades [ 419 ]. While some studies showed a good correlation with the production of 2-OH-E + from DHE [ 420 ] without such a parallel assay, the lucigenin-derived chemiluminescence may be difficult to interpret, as the probe reacts very slowly with O 2 •– . It may act as a redox cycler in the presence of flavoproteins, resulting in O 2 •– production [ 421 ]. Nitroblue tetrazolium and more recently water-soluble tetrazolium (WST-1) probes are being used as colorimetric stains for superoxide, as they form formazan-type reduced products, easily detectable by spectrophotometry [ 422 , 423 ]. This type of probes is typically used for cellular and cell-free assays in vitro . The major limitation is the possibility of superoxide independent reduction of tetrazolium salts to formazans, requiring further studies on the involvement of superoxide in the reduction of the probes [ 424 ]. Also, the redox cycling activity of nitroblue tetrazolium to produce superoxide has been reported and should be considered when using the probe [ 425 ]. While still awaiting a complete chemical characterization and biological validation, additional promising chemical probes for O 2 •– , including triflate-, phosphonate- and more recently tetrazine-based sensors, have been developed [ [426] , [427] , [428] ]. A further method to measure superoxide is by electron spin resonance [ 429 ]. Superoxide is able to form a characteristic spin adduct with 5,5-dimethyl-1-pyrroline-N-oxide (DMPO) forming DMPO-OOH, which is easily detectable by electron spin resonance. Problems of this method are the slow reaction of superoxide with DMPO, the low concentrations of the spin adduct formed (also due to its degradation by biological antioxidants such as vitamin C or glutathione) and the relatively complicated analytical equipment required. Hydrogen peroxide Detection of H 2 O 2 is typically accomplished using peroxidase-dependent probes, including reduced fluorescein and rhodamine probes (DCFH, DHR), and Amplex Red [ 427 , 430 ]. Peroxidase-dependent assays may be used to analyze extracellular H 2 O 2 or in cell-free systems, including isolated mitochondria, and Amplex Red is the recommended probe [ 431 ]. The use of DCFH and DHR probes should be avoided, as those probes do not react directly with H 2 O 2 , can be oxidized by cytochrome c mobilized during apoptosis [ 432 ], and may produce O 2 •– during their conversion to the fluorescent product [ 421 , 433 ]. Using boronate-based probes may allow the detection of H 2 O 2 , ONOO − or other boronate-reactive oxidants [ [434] , [435] , [436] ]. With proper experimental design and/or detailed profiling of the oxidation/nitration products, the oxidants involved may be identified [ 437 , 438 ]. The advantages of boronate probes include direct reaction with the oxidants, resistance to peroxidatic oxidation, and a wide range of detection modalities, including bioluminescence and other in vivo -compatible techniques [ 439 , 440 ]. Other ROS Other probes typically used for general assessment of oxidative stress and burst include luminol and analogs, such as L-012 probe [ 441 ]. Although initially assumed to be specific for superoxide, such probes are prone to peroxidase-catalyzed oxidation, and may produce superoxide in such systems [ 442 ]. As inflammation may lead to increased expression of peroxidases (e.g., myeloperoxidase), increased oxidation of such probes should not be used as a sole indication of increased ROS level but should be accompanied by additional assays to determine the role of peroxidases and preferably the identity of the oxidant(s) involved. The constant development of new redox probes and assays opens an exciting opportunity to decipher the role of specific ROS in traffic noise-induced pathologies. An overview on recommended methods of ROS detection can be found in Refs. [ 443 , 444 ]. Redox-related pathophysiological mechanisms Stress response As described in section 2.1 , a primary general mechanism that noise operates through is the activation of a stress response with subsequent induction of vascular and cerebral inflammation and oxidative stress by the upstream pathophysiological mechanisms shown in Fig. 2 , Fig. 9 , Fig. 16 (reviewed previously [ 28 , 29 ]). The response to noise is immediate, not requiring long duration of exposure to elicit a physiological response (e.g., exposure for 30 min (85 dB(A)) has been found to increase ACTH and corticosterone in a dose-dependent manner) [ 445 , 446 ]. Furthermore, noise-induced activation of the stress response in rats (80–100 dB(A), 8 h/day in 20 days) involved increased levels of plasma corticosterone, adrenaline, noradrenaline, and ET-1, coinciding with elevated levels of malondialdehyde, a readout of oxidative stress, and increased heart rate and arterial blood pressure [ 206 ]. Rats exposed to moderate noise (70 or 85 dB(A), 6 h/day for 3 months) were found to have a dose-dependent increase in corticosterone levels and lipid peroxidation accompanied by morphological changes in the heart and inflamed areas of the pericardium and dilated veins (70 dB(A)), with even greater changes in the 85 dB(A) group [ 205 ]. Additionally, rats chronically exposed to noise had upregulated Crh and Crhr1 (corticotropin-releasing hormone and its receptor) mRNA levels in the amygdala [ 447 ]. The interplay between stress hormones and vasoconstrictors offers a rationale for the disruption of vascular tone triggered by noise exposure ( Fig. 16 ). When noise exposure occurs during sleep, it leads to sleep fragmentation and excessively short sleep intervals [ 448 ], culminating in psychological stress. The increased level of stress hormones and disruption of the circadian rhythm ignites cerebral oxidative stress, involving heightened angiotensin II signaling and activation of NOX-2 [ 310 ]. Such factors collectively contribute to the inflammation of the brain's microvasculature. Animals subjected to noise exposure exhibit elevated levels of circulating angiotensin II as well [ 14 , 449 ]. SNS activation driven by NOX-2-induced oxidative stress proceeds to activate both HPA and RAAS [ 450 , 451 ] and, in turn, catecholamines initiate oxidative stress through pathways such as the promotion of MAO activity [ 401 ] or activation of astrocytes, microglia, and NOX-2 [ 372 ]. In supporting the concept of a RAAS–ROS– SNS axis concept, administrating of a NOX inhibitor reduced blood pressure, angiotensin II, and noradrenaline levels in hypertensive mice [ 452 ]. In contrast, inhibition of type 1 angiotensin II receptor and blockade of angiotensin-converting enzyme decreased oxidative stress within the heart and vasculature [ 453 , 454 ]. In mice, exposure to aircraft noise (72 dB(A) over 4 days) increased the expression of ET-1 in the aorta, a potent vasoconstrictor that triggers NOX-2 activity [ 14 , 16 , 365 ], which is, in part, dependent on RAAS [ 198 ]. These findings supply molecular and pathophysiological insights that address the appearance of endothelial dysfunction and hypertension observed in animal models exposed to (aircraft) noise. Central to this process is NOX-2-triggered oxidative stress and inflammation, alongside the disruption of circadian rhythm due to sleep fragmentation and deprivation. The robust support from animal data underlines the pivotal role of stress response pathways in the detrimental cardiovascular and cerebral consequences of noise exposure in humans. It offers detailed molecular mechanisms regarding the sequence of events within the brain and the stress response axis. Inflammation Inflammation has been associated with acute stress and sleep disturbance, noise exposure, and injury [ 455 ]. This occurs through the immediate activation of the SNS upon exposure to a stimulus, followed by activation of the HPA axis within minutes [ 455 ]. The subsequent release of stress hormones gives rise to systemic and tissue-specific inflammation, with elevated levels of IL-6, IL-1β, proinflammatory monocytic infiltration into tissues [ 43 , 456 ], and oxidative stress [ 29 ]. Stressors such as noise-induced sleep deprivation can induce cerebral oxidative stress orchestrated through angiotensin-II signaling and NOX-2 activation, producing microvascular and neuronal inflammation [ 310 ], likely from a microglial source. Consequently, it is plausible that noise-induced O 2 •− and H 2 O 2 generation fosters an inflammatory profile in the heart, blood vessels, brain, and other organs. Crucial mediators of inflammatory responses, such as the NLR family pyrin domain containing 3 (NLRP3) inflammasome and high-mobility group box 1 protein (HMGB1) are activated under conditions of oxidative stress through redox switches and redox-sensitive transcription factors like nuclear factor kappa B (NFκB) [ 457 , 458 ], which likely underpins noise-triggered inflammation in exposed mice [ 14 , 16 , 247 , 281 , 363 ]. This oxidatively-fueled inflammation could potentially explain the shift towards a pro-atherothrombotic phenotype in the plasma proteome of healthy human subjects exposed to train noise [ 234 ]. Epigenetic alterations promoting immune cell activation, CRP expression [ 459 , 460 ], and inflammatory coronary atherosclerosis related to heightened stress-associated neural activity involving the amygdala [ 47 , 202 , 203 ], could also stem from this complex interplay. In two studies, noise-induced inflammation was prevented in mice with Nox2 deletion [ 16 , 363 ]. Furthermore, antioxidant pharmacological activation/induction of the nuclear factor E2 related factor-2 (NRF-2)/heme oxygenase 1 (HO-1) axis [ 461 ], probiotic therapy [ 329 ], and treatment with the antibiotic minocycline [ 462 ] all been shown to inhibit noise-induced inflammation. The hypothesized mechanisms behind noise-induced inflammation are presented in Fig. 17 . As previously discussed, noise initiates neuroinflammation and Alzheimer's disease pathology in rodent studies [ 270 ], which is in line with results from rodent studies with exposure to low-level noise (73 dB(A)). This leads to increased levels of circulating cytokines (IL-6, IL-1β), aortic iNOS, monocyte chemotactic protein 1 ( MCP-1 or CCL-2), cluster of differentiation 68 ( CD68 ) mRNA levels, cardiac TNF-α, IL-6, IL-1β, interferon γ ( IFN-γ ) , MCP-1, cell adhesion molecules such as vascular cell adhesion molecule 1 ( Vcam-1 ) , and vascular infiltration of immune cells ( Fig. 17 ) [ 14 , 16 , 248 ]. This was accompanied by neuroinflammation characterized by astrocyte activation and higher cerebral CD68, IL-6 and iNOS levels ( Fig. 9 ) [ 16 ] and upregulated expression of Vcam-1, NFκB ( CD40L , NLRP3 and thioredoxin interacting protein (TXNIP) by trend) [ 245 , 281 ]. Other circulating cytokines and chemokines also seemed upregulated in mice exposed to low-level noise as measured using a cytokine array [ 15 ]. The aggravated systemic inflammation in noise-exposed animals is also reflected by enhanced oxidative burst by whole blood leukocytes [ 16 , 245 , 463 ]. In addition, there is evidence that noise additively increases markers of inflammation in mice with pre-established hypertension [ 247 ], on top of experimental MI [ 248 ], or with particulate matter co-exposure [ 15 ]. In addition, heat stress and noise may synergistically increase inflammation [ 464 ]. Molecular support for a noise-induced vital crosstalk between the brain, the heart, and the vessel was provided through a selective ablation protocol targeting cells expressing lysozyme M (LysM) [ 465 ]. Peripheral mononuclear phagocytes (monocytes and macrophages) are characteristically LysM + , while microglia lack or have minimal LysM. As a result, in the LysMCre iDTR model, administration of diphtheria toxin kills and removes peripheral mononuclear phagocytes but not microglia. LysM + cell-deficient mice were protected from noise-induced rise in blood pressure, endothelial dysfunction, and oxidative stress in non-central tissues ( Fig. 18 ) [ 281 ]. Conversely, mice with ablated monocytes/macrophages exhibited an intensified stress response in the brain, as evidenced by elevated plasma corticosterone levels and a neuroinflammatory phenotype. Flow cytometry of noise-exposed murine brains revealed a significant increase in activation markers for microglia - CD68, CD86, and major histocompatibility complex class II (MHC-II). These markers, however, did not return to baseline even with the genetic ablation of LysM + cells, further substantiating the conclusion that microglia are LysM-negative (illustrated in Fig. 18 ) [ 281 ]. This intriguing contrast implies a potential impact of noise on the blood-brain barrier, a phenomenon also reported in hypertension [ 466 ]. Additionally, the presence of a pro-oxidative and pro-inflammatory environment seemed to influence the activation state of astrocytes within the brains of noise-exposed mice. Loud noise has also been found to induce systemic inflammation (e.g., in the skeletal muscles) [ 467 ]. High levels of noise (100 dB in mice and 120 dB in rats) were shown to activate SHC-transforming protein 1 (SHC1, p66 Shc ), a mitochondrial source of H 2 O 2 , which was associated with higher levels of markers of oxidative stress, inflammation (vascular endothelial growth factor (VEGF), interferon γ (IFN-γ) and IL-1α were upregulated; IL-10 and ciliary neurotrophic factor (CNTF) were downregulated), and ischemia in the cochlea, all of which were prevented by Shc1 deletion [ 395 ]. Moreover, numerous pro-inflammatory cytokines and chemokines were found to be upregulated in an array analysis, which nicely correlates with the central role of inflammation for noise-induced hearing loss [ 468 , 469 ]. Cross-sectional studies have indicated that exposure to traffic noise may lead to elevated levels of IL-12 (a myeloid cytokine) and high-sensitivity C-reactive protein (hsCRP) coupled with reductions in natural killer cell populations and activity [ 460 , 470 ]. However, results are not consistent [ 220 , 471 ]. The SAPALDIA study noted that DNA methylation was enriched in pathways corresponding to inflammation, cellular development, and immune responses following prolonged exposure to source-specific transportation noise and air pollution [ 459 ]. A study from Germany found that extended exposure to nighttime traffic noise was associated with subclinical atherosclerosis, particularly in individuals displaying early arterial calcification [ 472 , 473 ]. These findings indicate a potential link between amplified recruitment and/or activation of immune cells by noise and compromised cardiovascular function. A human study that leveraged clinical 18 F-fluorodeoxyglucose positron emission tomography-computed tomography (PET–CT) imaging in 498 individuals without active malignancy or clinical CVD offered additional insights into the immune consequences of noise exposure that contribute to CVD [ 47 ]. This study extended prior work showing that a neuroimmune pathway involving heightened stress-associated neural activity (as amygdala metabolic activity relative to regulatory cortical activity) linked chronic stress and socioeconomic stressors to CVD to show that noise exposure was also an important and independent driver of this pathway [ 49 , 50 ]. Notably, increased noise exposure associated with heightened metabolic activity of the amygdala (relative to regulatory cortical activity), arterial inflammation, and a greater risk of MACE (HR 1.341, 95 % CI 1.147–1.567, per 5 dB(A) increase). These associations remained robust even after multivariable adjustments for potential confounders including air pollution, socioeconomic status, and CVD risk factors. Further investigation via mediation analysis showed a sequential mechanism through which elevated noise exposure was associated with MACE, involving heightened amygdala activity and arterial inflammation [ 47 , 48 ]. Of note, an additive impact of exposure to increased noise and air pollution on arterial inflammation and MACE risk was reported that seems to synergize at the level of the arteries (noise enters the brain while air pollution activates leukopoietic tissues) [ 474 ]. Moreover, stress-associated neural activity has been further linked to atherosclerosis in several separate cohorts by showing a relationship with coronary artery disease complexity, non-calcified coronary plaque burden, and coronary fat attenuation index and a greater risk for recurrent stroke in patients with prior stroke [ [475] , [476] , [477] , [478] ]. Collectively, these findings identify an important pathway that contributes to the development of CVD as a result of noise exposure. Circadian clock The circadian clock regulates crucial biological functions like sleep, body temperature, appetite, and cognitive processes. It operates cyclically (over the day) releasing hormones, most notably cortisol, melatonin, ACTH, testosterone, renin, aldosterone, angiotensin, and catecholamines [ 479 ]. Disruption to this circadian rhythm can be induced by high (nighttime) noise exposure burden [ 13 , 136 , 200 ] or sleep pattern disturbances like those in shift workers [ [480] , [481] , [482] ]. It is a suspected risk factor for many diseases, including CVD, breast cancer [ 483 , 484 ], and psychiatric disorders [ 485 , 486 ]. The circadian rhythm is generally under redox control; direct redox modifications of circadian components cryptochrome (CRY), period (PER), and F-box/leucine-rich-repeat protein 3 (FBXL3) involve thiol oxidation/reduction and the formation or disruption of zinc-sulfur complexes. Maintenance of the appropriate oxidative status allows the circadian rhythm to govern the proper binding of these components to the essential regulators of circadian control—circadian locomotor output cycles protein kaput (CLOCK) and brain and muscle Arnt-like protein 1 (BMAL1) complex, as depicted in Fig. 19 [ 487 ]. This presents a point of intersection between the effects of noise and regular cellular timekeeping – if noise can efficiently disrupt the oxidative balance, it can potentially disturb the circadian rhythm. Redox-sensitive kinases, histone deacetylases, stress-response proteins, and transcription factors can be influenced by ROS, thereby impacting the clock system [ 207 , 251 ]. On the other side it is the nature of noise, which can disrupt sleep and interfere directly with timekeeping [ 488 ]. A comprehensive overview of the impact of various environmental stressors, including mental/social isolation stress, air pollution, heavy metals, and pesticides, on the circadian clock and its adverse redox regulation has previously been published [ 381 ]. Only a few studies have explicitly addressed noise effects on the circadian rhythm. However, other environmental cues and stressors of the cyclical regulation [ 381 , 489 ] (e.g., light, food intake, and temperature), have been found to interfere with the circadian rhythm. A study in mice subjected to continuous aircraft noise exposure for 4 days (72 dB(A)) showed downregulation of Per1 and REV-ERB-α/β (Nr1d1/2) or RORα , along with the upregulation of Bmal1, Cry1, Cul1, Prkag1/2, poly (ADP-ribose) polymerase ( Parp1 )— in total, more than 30 circadian genes displayed altered expression levels in the aorta and kidney compared to unexposed controls [ 16 ]. Additionally, the downregulation of forkhead-box-protein O3 ( FoxO3 ), a central transcription factor regulating circadian genes in vascular tissue, was noted. Pharmacological activation of FoxO3 using bepridil successfully countered noise-induced oxidative stress in the aorta and the resulting endothelial dysfunction [ 16 ]. In a separate study examining the transcriptomics of neurons within the inferior colliculus, a brain structure vital for sound processing, distinct profiles between day- and nighttime exposure appeared in clock genes [ 490 ]. Furthermore, a phase shift was reported for corticosterone levels in feces of noise-exposed mice, indicating a dysregulated circadian rhythm [ 491 ], which may differ in different mouse strains [ 492 ]. Noise exposure alters clock gene expression ( Per1, Per2, Bmal1, and Rev-Erbα ) in the cochlea and the inferior colliculus, having direct implications for noise-induced hearing loss, but may also be relevant for dysregulated circadian rhythms in other brain regions and remote organs [ 493 ]. A differential effect of daytime versus nighttime noise exposure on several inflammatory cytokines with higher peak levels after daytime noise has also been observed [ 494 ]. Noise-induced changes of epigenetic pathways Gene expression is critically and dynamically controlled by epigenetic changes determining the physiological response to environmental factors. As such, it is no surprise that many such epigenetic alterations have been identified in the development and progression of atherosclerosis and correlate with its severity [ 510 , 511 ]. Importantly, epigenetic changes to the genome are generally redox-regulated [ [512] , [513] , [514] ]. For this reason, it is speculated that noise-induced oxidative imbalance could dysregulate the landscape of gene expression via interruption of these epigenetic regulations. The methylome of CVD and risk is currently an important research topic [ 515 ], which carries over into the noise field. Changes in overall methylation were reported in the brains of noise-exposed rats, demonstrating that noise exposure can interfere with transcriptional signals [ 516 ]. The Swiss SAPALDIA cohort study, based on 1389 participants, reported noise-induced alterations of DNA methylation patterns indicating inflammatory activation and immune response [ 459 ]. Downstream of epigenetic changes, studies have reported alterations in coding gene expression in murine aorta, heart, and kidney in response to noise, as detected by RNA sequencing [ 14 , 16 ]. Studies on hearing loss have reported similar results [ 517 , 518 ]. Noncoding RNA and microRNA expression have also been reported to change in response to noise, an important caveat when considering that these are increasingly recognized as playing a role in health and disease [ 519 , 520 ]. For example, increased expression of miR-134/183 occurred in the central amygdala following acute stress exposure [ 521 ], both of which have been reported to be increased in patients with coronary artery disease and depression. Numerous microRNAs, which regulate/respond to antioxidant defense or pro-oxidative proteins, are reported to be affected by environmental exposures [ 519 , 520 ]. Epigenetic effects observed in human and animal studies on hearing loss and in non-auditory models have also been reviewed [ 522 ]. A new emerging concept promotes early life (fetal) reprogramming by various exposures to explain the large impact of environmental exposures on disease development in later life [ [523] , [524] , [525] , [526] ]. For example, dietary factors during pregnancy, such as overnutrition or malnutrition, severely affect the risk of the offspring developing a metabolic disease or CVD during later life [ [527] , [528] , [529] ]. This also holds true for noise pollution, which affects the risk of disease in human and animal offspring via prenatal epigenetic reprogramming [ 530 ]. Antioxidant interventions Various studies have provided molecular support for the beneficial effects of antioxidant interventions against noise-induced damage, including a reduction of systemic oxidative stress (e.g., aortic superoxide formation as measured by HPLC analysis of 2-hydroxyethidium) by genetic deletion of the Nox2 gene ( Nox2 −/− ) or pharmacological inhibition (GSK2795039) of the NOX-2 protein [ 16 ]. Noise-exposed Nox2 knockout mice also had normal endothelial function. Impaired FOXO3 signaling is likely a key mechanism in animal models with low-level noise exposure [ 245 ] since the activation of FOXO3 by the calcium antagonist bepridil significantly improved several vital parameters, such as endothelial dysfunction and vascular/cerebral oxidative stress [ 16 ]. The adverse effects of noise, including hypertension, endothelial dysfunction, vascular and cerebral oxidative stress, and markers of inflammation were also prevented by induction of the antioxidant principle NRF-2 with dimethyl fumarate or direct stimulation of the antioxidant defense enzyme HO-1 by hemin [ 461 ]. Both drugs substantially increased HO-1 and the potent antioxidant bilirubin in noise-exposed mice as a potential mechanistic explanation of NRF-2-mediated protection. Studies have also found protective effects of NRF-2 activators against mental stress conditions [ 565 ], reflected by the beneficial action of CDDO-imidazole in a model of noise-induced hearing loss [ 566 ]. Of great interest are non-pharmacological mitigation strategies against noise-induced damage (e.g., physical exercise and intermittent fasting), conferring potent antioxidant and anti-inflammatory effects largely mediated by AMPK as shown for noise-exposed mice [ 567 ]. Of note, there is an important connection between NRF-2 and AMPK as the kinase phosphorylates NRF-2 and thereby causes activation of the transcription factor [ 568 ], also with high relevance for the protective effects of physical exercise [ 569 ] and intermittent fasting [ 570 ]. N-acetylcysteine therapy prevented oxidative stress envisaged by lipid peroxides in the brain, depressive phenotype, and anxiety-like behavior in mice exposed to loud noise [ 571 ]. Another study reported that changes in the neurotransmitters noradrenaline and serotonin, lipid peroxides, and antioxidant defense enzyme activities in the brain of rats exposed to loud noise were mostly mitigated by vitamin E treatment [ 572 ]. Also, the neuroprotective effects of sildenafil were observed in mice exposed to severe noise stress, which were characterized by protection against oxidative stress and memory dysfunction [ 573 ]. Rosuvastatin normalized oxidative stress plasma markers in response to loud noise in rats [ 574 ]. Summaries of antioxidant interventions against noise-mediated oxidative damage in brain tissues have previously been reported [ 531 , 575 ]. In addition, numerous antioxidant interventions were reported in models of noise-induced cochlear damage and hearing loss (reviewed in Ref. [ 67 ]), where the NOX-3 isoform seems to play a predominant role for ROS formation and oxidative damage [ 576 , 577 ]. Applying the oxidative stress concept to broader mental stress conditions Transportation noise can act as a psychological (mental) stressor similar to other mental stressor, e.g., job-strain. Epidemiological studies have indicated that transportation noise may increase risk of anxiety and depression, though high-quality prospective studies on this are still needed [ 578 ]. Accordingly, the oxidative stress concept for noise exposure should be discussed in a broader context for all psychological stress conditions to provide a more general perspective applicable to different medical fields. Psychosocial stress is a complex entity, comprised of many factors that can produce an emotionally- and physically-complicated response. Despite this, a series of prospective epidemiological studies have identified two components of this stressor that appear to have an outsized weight in stressful work environments – job strain and effort-reward imbalance. Job strain describes a working situation with high demand and pressure to perform but low control over the task. Employees in these circumstances have higher cardiovascular risk. Another work-related stressor that puts workers at elevated cardiovascular risk is effort-reward imbalance, where individuals expend high effort to achieve rewards (salary, promotion, recognition, security). Examples of occupational groups that suffer significantly from the two scenarios of work stress are nurses and teachers [ 579 ]. Results from >20 cohort studies demonstrate a 1.4-fold increased risk of coronary heart disease for individuals in high-vs. low-stress work [ 580 , 581 ], even after multivariable adjustment for other cardiovascular risks. Accordingly, mental stress is strongly associated with cardiovascular risk and other disease entities, which also holds true for interactions between road traffic and occupational noise exposure, as well as job-strain, in relation to the risk of myocardial infarction [ 582 ]. To bolster the epidemiological claims, these studies included measurement of job strain or effort-reward imbalance and reported associations with elevated autonomic nervous system activity indicators - plasma cortisol and noradrenaline, blood pressure, heart rate, and heart rate variability [ 583 ]. Enhanced autonomic nervous system activity, higher markers of oxidative stress in blood or vascular tissue and increased NFκB and pro-inflammatory activity were also documented [ 584 ]. Urinary 8OHdG and H 2 O 2 , two oxidative stress biomarkers, showed associations in human job stress settings [ 585 ], and anticipatory cortisol reactivity [ 586 ]. This was accompanied by an elevation of NOX-2 in the hypothalamus, mirroring the rat model of psychosocial stress [ 587 ]. These data indicate that oxidative stress represents a major pathomechanism initiated by mental stress. Concluding with the notion that oxidative stress is a well-recognized trigger/promoter of cardiovascular disease provides a rational pathomechanism for higher cardiovascular risk observed under mental stress conditions. There is high-quality research investigating mental stress as a cardiovascular risk in animal studies [ 532 ] and preliminary evidence in studies on humans [ 345 ]. For example, H 2 O 2 -induced vasodilation was impaired in congestive heart disease due to switching potassium channels [ 588 ]. Clinical cardiovascular risk factors are also correlated in numerous CVD epidemiology studies. The current state of knowledge on CVD and oxidative stress has been recently reviewed [ 589 , 590 ], focusing on the major enzymatic sources of oxidants, NADPH oxidases, mitochondria, xanthine oxidase, lipoxygenase, and myeloperoxidase. While the connections have been forged, further research is challenged by the relative difficulty of closely monitoring the oxidative state in human subjects with job strain and psychosocial stress conditions. As one of the coauthors, Helmut Sies summarized, the situation requires enhanced interdisciplinary investigations among human populations applying advanced methods of molecular, biomedical, and epidemiological research [ 192 ]. A crucial future step will be fully elucidating the key role of oxidative stress in the stress-induced cascade of events, which will make preventative and protective measures possible to implement, measures urgently needed as the burden of chronic diseases grows in aging societies. Taken together, the topic of health effects of noise falls with the concept of the exposome, which encompasses the totality of environmental exposures, a concept introduced by C.P. Wild in 2005 [ 17 ]. The main idea of this concept is that detrimental exposures cause biochemical changes and subsequent health or disease outcomes, as discussed above. Evidence supporting the exposome concept was reviewed for CVD [ 591 ], cancer [ 592 ], metabolic disease [ 593 ], pulmonary disease [ 594 ] and, in general, chronic non-communicable diseases [ 595 ]. Linkage of the exposome concept to redox medicine [ 596 ] and tools [ 597 ] are there for application to exposome research [ 190 , 191 , 598 ] (summarized in Fig. 20 ). In addition, preclinical data point towards a central role of adverse redox signaling for exposure-driven health risks, e.g., as shown for noise [ 16 ], air pollution [ 599 ], and metal toxicity [ 600 ]. This warrants a joint effort of health and redox experts and other disciplines for better understanding of environmental health effects [ 601 , 602 ] and overcoming the analytical challenges associated with exposome research [ 603 ]. Financial support M.T.O. is supported in part by 10.13039/100000002 National Institutes of Health K23HL151909 and 10.13039/100000968 American Heart Association 23SCISA1143491. P.W., T.M. and T.G. are Principal Investigators and O.H., M.K. and A.D. are (Young) 10.13039/100010447 Scientists of the German Center for Cardiovascular Research (DZHK) and were supported by 10.13039/100010447 DZHK funding to the partner site Rhine Main (Mainz) and Berlin. R.S. is supported by 10.13039/501100001659 Deutsche Forschungsgemeinschaft (DFG; German Research Foundation) [Project number 268555672—SFB 1213, Project B05]. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability Data will be made available on request.

CC BY

no

2024-01-16 23:43:48

Redox Biol. 2023 Dec 18; 69:102995

oa_package/97/04/PMC10788624.tar.gz

PMC10788637

38221793

Dear Editor, Physiological lip melanosis is a disorder with a multifactorial aetiology. It varies with ethnicity and is typical of people with darker skin tones. Benign conditions (ephelides, lentigines, labial melanotic macule), malignant instances (pigmented squamous cell carcinoma, malignant melanoma), drug‐induced, post‐inflammatory hyperpigmentation (PIH), endocrine disorders, heavy metals, smoking, amalgam tattoo, Laugier‐Hunziker syndrome and lentiginosis syndromes (Peutz–Jegher's syndrome) are among the factors that can cause lip pigmentation labial melanotic macules are pigmented benign macules with a linear increase in pigment in the basal layer without any melanocyte proliferation and without any vascular component. 1 Although treatment is not needed, it is requested by many patients, who are greatly distressed by this condition. For lip melanosis, there is, unfortunately, no effective treatment. 2 Patients frequently experiment with whitening creams, camouflage lipsticks and lip tattoos without getting the desired outcome. 3 Histological evidence of lip darkening shows abnormal basal layer melanin granule aggregation with a regular number of melanocytes and an excess of dermal melanophages. 4 These are good targets for Q‐switched (QS) lasers because they contain melanin which is the interested chromophore. This way, collateral tissue damage can be reduced. It has been demonstrated that the QS 532‐nm laser works perfectly to treat hyperpigmented lips. Nevertheless, negative effects are more common, last longer and are more intense than with the QS 1064‐nm laser. 5 The QS picosecond lasers emit pulses that are much shorter than the target's thermal relaxation time so they raise the peak temperature without inflicting thermal damage on the nearby tissues. Given this, this study aimed to conduct a preliminary assessment of the application of a picosecond QS 785 nm handpiece (El.En Group, Florence, Italy) for the treatment of lip hyperpigmentation, to minimize blood absorption and maximize the absorption of melanin. A 51‐year‐old male patient with lower lip melanosis is the subject of this case study. The parameters for treatment were spot size 3 mm, fluence 2.8 J/cm 2 , frequency 2 Hz and single pass modality. To get the most out of the technology, a contact sensor was included on the device. The last assessment and follow‐up appointments were conducted 24 h and 14 days following the last laser treatment. Our findings indicate that the patient's mucosa has very quickly almost completely recovered, when compared to the skin (see Figure 1 ). Additionally, the patient was given a visual analogue scale (VAS) with a range of 1 to 10 and the value he reported indicated a high degree (VAS = 9) of satisfaction with complete disappearance of the lip hyperpigmentation. According to Loh et al. (2021), 785 nm may be the preferred wavelength for treating darker lesions and darker skin types. On the other hand, the 730 nm emitting devices may be preferable for treating lightly pigmented lesions because the melanin absorption coefficient at 730 nm is expected to be 30% higher than at 785 nm. 6 Furthermore, due to melanin's preferred absorption over haemoglobin, the 785 nm wavelength may be better compared to 1064 and 532 nm when targeting skin or lip pigment. 7 Indeed, we treated a different and unusual body district such as the internal part of the lower lip. It has unique characteristics being a mucosa and a vascular component‐rich area. Of course, different laser strategies could have been used to target melanin, such as the 675 nm wavelength devices or the 532/1064 nm lasers, that we previously used in other investigations. 8 Nevertheless, in the clinical case presented we decided to have a conservative approach during the treatment, to focus on the melanotic component only and avoid the vascular one. This way, no side effects were registered, and the treatment was almost pain‐free and bearable by the patient. Oral mucosa healing happens way faster than skin healing. Indeed, networks related to wounds of the oral mucosa regulate inflammatory responses and epithelial cell differentiation. 9 In summary, the use of the 785 nm wavelength in our study was warranted to improve melanin absorption when compared to blood absorption. It has been confirmed that the device utilized in this study has a good safety record. The nearly complete elimination of lip hyperpigmentation and the ability to resume normal activities as soon as the laser sessions concluded contributed to the patient's high level of satisfaction following the treatment. The technology also had the benefit of not having any negative long‐term side effects or pain.

DATA AVAILABILITY STATEMENT The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

CC BY

no

2024-01-16 23:43:48

Skin Res Technol. 2024 Jan 14; 30(1):e13581

oa_package/c0/7f/PMC10788637.tar.gz

PMC10788638

0

INTRODUCTION Chronic kidney disease (CKD), defined as abnormalities of kidney structure or a glomerular filtration rate (GFR) lower than 60 mL/min/1.73 m 2 for more than 3 months, poses a significant public health burden with a global prevalence of around 13.4%. 1 , 2 Despite the drastic increase in healthcare expenditure for the prevention and treatment of CKD, the number of patients suffering from end‐stage kidney disease (ESKD) is expected to increase by 29%–68% in the United States by 2030. 3 Aside from the detrimental effect on the kidney, CKD is associated with a higher risk of cardiovascular disease (CVD). 4 To delay the development of ESKD and improve CKD prognosis, early detection and management of CKD are crucial, especially for high‐risk populations such as CVD patients. 5 A shared physiological mechanism underlying the pathogenesis of CKD and CVD is the disordered lipid metabolism. 6 Recent studies have suggested that adipokines, such as the fatty acid‐binding protein (FABP) family, are involved in the modulation of lipid metabolism and have the potential to serve as biomarkers or treatment targets for a variety of disorders, such as chronic inflammation, ischemic stroke, metabolic syndrome, atherosclerosis, and CVD. 7 , 8 Among the FABP family, the heart‐type FABP (H‐FABP) or FABP‐3 has been considered a possible biomarker for cardiac and renal injury. FABP‐3 is a small protein expressed in cardiomyocytes and renal distal tubular cells responsible for transporting long‐chain fatty acid, which would be released to the circulation during tissue injuries, such as myocardial infarction, heart failure, and renal tubule injury. 9 , 10 , 11 Also, patients with CKD are reported to have elevated levels of inflammatory and metabolic markers, such as omentin, 12 neuregulin, 13 serum uric acid, 14 kidney injury molecule, 15 prognostic nutritional index, 16 systemic inflammatory index, 17 uric acid/HDL‐cholesterol ratio, 18 and C‐reactive protein, 19 indicating correlations between inflammatory markers and renal disease. Studies have shown that the elevation of serum FABP‐3 concentration is associated with lower estimated GFR (eGFR) in type 2 diabetes mellitus (DM) patients 20 and a higher rate for acute kidney injury after cardiac surgery. 21 However, most of the existing studies are cross‐sectional or retrospective, which makes it difficult to infer the temporal relationship between FABP‐3 and the decline of renal function. Also, the prognostic value of FABP‐3 for kidney injury in high‐risk population such as patients with CVD is unclear. Since the relationship between FABP‐3 and kidney injury in patients with CAD is still unclear, we aimed to examine the correlation between circulating FABP‐3 and renal function decline in patients with chronic coronary syndrome.

METHODS Study design The research is based on the “Development of New Biosignatures for Atherosclerosis Cardiovascular Diseases” study, a multicentre cohort registry that prospectively enrolled a series of patients with the chronic coronary syndrome. This study protocol has been published previously. 22 The patients with stable coronary artery disease (CAD) after successful percutaneous coronary intervention (PCI) were included from nine tertiary referral centers in Taiwan from 2012 to 2017. Patient Subjects who fulfilled the inclusion criteria were enrolled: the presence of a significant CAD history after at least one PCI with coronary ballooning or stenting and remained clinically stable under medical treatment for at least 1 month before this enrolment. Individuals who met any of the following circumstances were excluded: under treatment with a non‐steroid anti‐inflammatory drug, steroid, disease‐modifying antirheumatic drug, or other biological immunosuppressants at enrolment or any time‐point during follow‐up, with underlying autoimmune diseases, had been hospitalized due to acute coronary syndrome in the recent 3 months, anticipated to receive coronary or other cardiac interventions in the following 1 year, undergoing therapy for compelling malignancy, mandatorily hospitalized for other systemic diseases in the following 1 year, with a life expectancy of fewer than 6 months, and failed to cooperate with clinical follow‐up. The study complied with the principles of the Declaration of Helsinki. Approvals from each hospital's independent ethics committees and review boards were obtained (IRB: AS‐IRB01‐19007). Informed consent was obtained from all subjects before participating in this study. Clinical assessment A specially trained nurse documented demographic information following a standardized protocol from the chart or structured questionnaires. After being well‐rested, the blood pressure (BP) values were measured using an electronic BP monitor operated by a trained nurse and recorded as the average of three consecutive measurements at the outpatient clinic ante meridiem . Hypertension was defined as a BP level exceeding 140/90 mmHg or using antihypertensive agents. All subjects were followed on an outpatient basis at the respective institutions. Biomarker measurement Peripheral blood samples (20 cc) were collected for biochemical assessments. The samples were centrifuged before the sera were thawed for assessment. The levels of FABP‐3, as well as baseline serum chemistry, including high‐density lipoprotein‐cholesterol (HDL‐C), low‐density lipoprotein‐cholesterol (LDL‐C), and N‐terminal pro‐brain natriuretic peptide (NT‐pro‐BNP), were assessed at enrolment. Whereas renal function with creatinine was evaluated at the initial visit, every 3 months in the first year, and then at 6‐month intervals. Renal events Renal function, eGFR, was derived from serum creatinine level and demographic parameters based on Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI). 18 Renal events were defined as a decline of over 25% and 50% from the baseline eGFR according to previous studies. 23 , 24 , 25 To explore whether our results were consistent according to different equations for renal function, we further calculated eGFR based on Modification of Diet in Renal Disease (MDRD) and Cockcroft–Gault (CG) equations. 26 , 27 , 28 Statistical analysis Statistical Package for Social Sciences software (Version 21.0, SPSS Inc.) was used for analysis. Continuous variables were presented as mean ± SD, while categorical parameters were presented as numbers with percentages. All patients were divided into three groups (low, middle, and high) according to the FABP‐3 tertile. Parametric continuous data between the three groups were compared using a one‐way analysis of variance. Categorical data between the three groups were compared with a chi‐square test or Fisher's exact test. The Kaplan–Meier curve and log‐rank test were employed to assess the renal event rate based on FABP‐3 levels. Multivariate analysis in conjunction with the Cox proportional hazard regression model was used to evaluate the independent association between FABP‐3 levels and renal function decline. An adjustment was performed for potential confounding factors, including age, sex, BMI, systolic BP, diastolic BP, hypertension, DM, heart failure, use of antihypertensive agents, statins, baseline eGFR, HDL‐C, LDL‐C, NT‐pro‐BNP, and FABP‐3. Each parameter's hazard ratios (HRs) and 95% confidence intervals (CIs) were presented. A two‐sided p value less than .05 was considered statistically significant.

RESULTS Baseline characteristics according to the FABP‐3 level A total of 1606 patients with chronic coronary syndrome were included in this cohort study. The patients were categorized into three groups according to the baseline serum FABP‐3 levels. The patients with the highest FABP‐3 levels were the oldest ( p < .001), having the highest systolic BP ( p = .007), lowest diastolic BP ( p = .047), highest rates of hypertension ( p < .001), DM ( p < .001), and heart failure ( p < .001). They used more calcium channel blockers ( p = .006) and diuretics ( p < .001) but fewer statins ( p = .002). In addition to the lowest LDL‐C levels ( p = .018) and the highest NT‐pro‐BNP levels ( p < .001), patients with the highest FABP‐3 levels had the highest creatinine levels ( p < .001) and the lowest eGFR levels, which were consistent in eGFR values derived from CKD‐EPI ( p < .001), MDRD ( p < .001), and CG equations ( p < .001). Detailed information on the patients is listed in Table 1 . FABP‐3 level and eGFR decline according to CKD‐EPI equation During a mean follow‐up of 35.9 ± 23.2 months, 239 patients had eGFR >25% reduction according to CKD‐EPI equation. There were 60 patients with eGFR >50% reduction according to CKD‐EPI equation. Patients with the highest FABP‐3 levels had the most eGFR >25% reduction ( p < .001) and >50% reduction ( p < .001) (Table 2 ). In the Kaplan–Meier survival curve and log‐rank test, increased levels of FABP‐3 were significantly correlated with eGFR >25% reduction ( p < .001) (Figure 1A ) and >50% reduction ( p < .001) (Figure 1B ). Multivariate analysis with the Cox regression model revealed that subjects with higher FABP‐3 exhibited a greater risk of eGFR >25% reduction (Group 2: HR = 2.328, 95% CI = 1.521–3.562, p < .001; Group 3: HR = 3.054, 95% CI = 1.952–4.776, p < .001) and >50% reduction (Group 3: HR = 4.838, 95% CI = 1.722–13.591, p = .003) according to the CKD‐EPI equation (Table 3 ). FABP‐3 level and eGFR decline according to MDRD and CG equations During a mean follow‐up of 35.9 ± 23.2 months, 274 and 286 patients had eGFR >25% reduction according to MDRD and CG equations, respectively. There were 60 and 58 patients with eGFR >50% reduction according to MDRD and CG equations, respectively. Patients with the highest FABP‐3 levels had the most eGFR >25% reduction ( p < .001 for both equations) and >50% reduction ( p < .001 for both equations) (Table 2 ). In the Kaplan–Meier survival curve and log‐rank test, increased levels of FABP‐3 were significantly correlated with eGFR >25% reduction ( p < .001 for both equations) (Figures S1A and S2A ) and >50% reduction ( p < .001 for both equations) (Figures S1B and S2B ). Multivariate analysis with the Cox regression model revealed that subjects with higher FABP‐3 exhibited a greater risk of eGFR (MDRD) > 25% reduction (Group 2: HR = 1.742, 95% CI = 1.222–2.483, p = .002; Group 3: HR = 2.643, 95% CI = 1.847–3.784, p < .001) and >50% reduction (Group 2: HR = 3.818, 95% CI = 1.261–11.564, p = .018; Group 3: HR = 9.769, 95% CI = 3.291–29.002, p < .001) (Table S1 ). Subjects with higher FABP‐3 exhibited a greater risk of eGFR (CG equation) >25% reduction (Group 2: HR = 1.981, 95% CI = 1.391–2.821, p < .001; Group 3: HR = 2.843, 95% CI = 1.986–4.069, p < .001) and >50% reduction (CG equation)(Group 2: HR = 3.399, 95% CI = 1.112–10.391, p = .032; Group 3: HR = 8.404, 95% CI = 2.815–25.088, p < .001) (Table S2 ).

DISCUSSION Early detection of renal injury in high‐risked populations such as patients with CVD is crucial to prevent CKD or ESRD; however, reliable predictors or biomarkers are lacking. In this prospective cohort study, we investigated the relationship between FABP‐3 and the deterioration of renal function in patients with the chronic coronary syndrome. We found that increased serum FABP‐3 concentration is significantly associated with future eGFR reduction estimated by the three most commonly used formulas. Also known as the heart FABP (H‐FABP), the FABP‐3 is abundantly expressed in the myocardium and is released into circulation after a cardiac injury, such as myocardial infarction. 29 Researchers have suggested the potential of FABP‐3 as a biomarker for CVDs, including heart failure and myocardial infarction. 9 In our cohort, albeit with wide variation, the mean serum concentration of FABP‐3 is slightly higher than that of the normal population. 30 In combination with the fact that FABP‐3 is cleared by the kidney and reports implicating FABP‐3's renal toxicity, 21 , 31 , 32 we hypothesized that the elevation of FABP‐3 in patients after cardiac damage might lead to deterioration of renal function. After correcting the baseline renal function and other potential confounders, the patient groups with higher baseline circulating FABP‐3 have significantly higher risks of the deterioration of renal function, whatever formula is used for deriving the eGFR (Table 3 , S1 and S2 ). Although causality is difficult to infer from a prospective cohort study, our findings met several elements of the Bradford Hill criteria for causality, such as temporality (i.e., high FABP‐3 concentration precedes the renal event), dose–response (i.e., groups with higher FABP‐3 concentration have higher HR for the renal event), and biological plausibility. 33 Hence, one possible mechanistic interpretation of our results is that the FABP‐3 released from the myocardial injury leads to further injury. Further studies must disentangle the relationship between FABP‐3 and cardiovascular and renal dysfunction. From the clinical perspective, the direct implication of this study is that physicians may consider to follow FABP‐3 levels for patient with chronic coronary syndrome to assess the risk of renal damage. Early renal‐protective interventions can be initiated for high risk population to prevent the comorbidities of subsequent CKD. The advantage of this study is the prospective design and rather big population size with detailed characterization. Regarding limitations, first, this is a non‐randomized observational study without intervention; hence the causal relationship between FABP‐3 and renal dysfunction is difficult to infer. Second, creatinine clearance was the only parameter used to assess renal function. We did not include albuminuria into our study. More metrics for renal function, such as urinary albumin excretion, may provide additional information. Third, the dynamic changes in FABP were not documented, compromising the interpretation of the longitudinal effect of the post‐CAD inflammatory burden. An extended follow‐up period is also necessary to observe the eventual prognosis of renal function impairment. Finally, contrast‐induced nephropathy might confound the interrogation of renal dysfunction after PCI. Since the study enrolled only clinically stable patients under medical treatment for at least 1 month and excluded those who anticipated receiving coronary or other cardiac interventions in the following year, such an effect is considered minimized.

CONCLUSIONS We revealed a clear relationship between elevated FABP‐3 levels, inflammatory markers released after myocardial injury, and future decay of renal function in patients with chronic coronary syndrome. The results not only demonstrate that the FABP‐3 might serve as a predictor for the clinician to prevent the progression to CKD for these high‐risked patients but also suggest that FABP‐3 itself may be a pharmacological target for preventing renal damage.

Abstract Background Renal dysfunction is common in patients with coronary artery disease. Due to the shared vascular pathogenesis between the two conditions, novel biomarkers such as the fatty acid‐binding protein‐3 (FABP‐3) have been proposed for diagnosis and prognosis prediction. This multicentre prospective cohort study investigates the association between FABP‐3 and renal dysfunction. Hypothesis We hypothesized that higher FABP‐3 levels are correlated to worse renal outcome. Methods Patients with chronic coronary syndrome were classified into three groups based on the initial serum FABP‐3 levels. The Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI) equation was used to estimate the patient's renal function. Renal events were defined as >25% and >50% decline in estimated glomerular filtration rate (eGFR). Cox multivariable regression was employed to delineate the correlation between FABP‐3 and renal dysfunction. Results A total of 1606 subjects were included. During a mean follow‐up of 35.9 months, there were 239 patients with eGFR >25% reduction and 60 patients with >50% reduction. In the Kaplan–Meier survival curve and log‐rank test, increased levels of FABP‐3 were significantly correlated with eGFR >25% reduction ( p < .001) and >50% reduction ( p < .001). Multivariate Cox regression model revealed that subjects with higher FABP‐3 exhibited a greater risk of eGFR >25% reduction (Group 2: hazard ratio [HR] = 2.328, 95% confidence interval [CI] = 1.521–3.562, p < .001; Group 3: HR = 3.054, 95% CI = 1.952–4.776, p < .001) and >50% reduction (Group 3: HR = 4.838, 95% CI = 1.722–13.591, p = .003). Conclusions Serum FABP‐3 may serve as a novel biomarker to predict eGFR decline in patients with chronic coronary syndrome. For patients with chronic coronary syndrome, early detection and prevention of kidney injury are crucial. We found that a higher serum FABP‐3 level was correlated to an increased risk of estimated glomerular filtration rate (eGFR) decline. Serum FABP‐3 may serve as a novel biomarker to predict eGFR decline in these patients. Yeh J‐T , Huang C‐C , Leu H‐B , et al. Fatty acid‐binding protein‐3 and renal function decline in patients with chronic coronary syndrome . Clin Cardiol . 2024 ; 47 : e24210 . 10.1002/clc.24210

AUTHOR CONTRIBUTIONS Jiunn‐Tyng Yeh and Chin‐Chou Huang conceived the research idea and established the study design. Chin‐Chou Huang, Hsin‐Bang Leu, Wei‐Hsian Yin, Wei‐Kung Tseng, Yen‐Wen Wu, Tsung‐Hsien Lin, Hung‐I Yeh, Kuan‐Cheng Chang, Ji‐Hung Wang, Chau‐Chung Wu, and Jaw‐Wen Chen were responsible for data acquisition. Chin‐Chou Huang analyzed and interpreted the data. Jiunn‐Tyng Yeh drafted the manuscript, which was revised by Chin‐Chou Huang, who offered supervision and mentorship. All authors reviewed and agreed with the final version of the article. CONFLICT OF INTEREST STATEMENT The authors declare no conflict of interest. Supporting information

ACKNOWLEDGMENTS This work was supported by research grants BM10501010039 from Academia Sinica, Taiwan; V112C‐062, V111D63‐002‐MY2‐2, VGHUST112‐G7‐1‐2, V113C‐032, and V113EA‐012 from Taipei Veterans General Hospital, Taipei, Taiwan; and NSTC111‐2314‐B‐A49A‐509‐MY3 from the National Science and Technology Council, Taiwan. The funders played no role in the data collection or preparation of the manuscript. DATA AVAILABILITY STATEMENT Data will be available based on the reasonable request from the corresponding author.

CC BY

no

2024-01-16 23:43:48

Clin Cardiol. 2024 Jan 15; 47(1):e24210

oa_package/17/2c/PMC10788638.tar.gz