Environmental and Molecular Mutagenesis最新文献

{"title":"Identifying Gene Predictors of Chemicals Linked With Breast Cancer: A Machine Learning Analysis of MCF7 Cellular Transcriptomic Screening Data.","authors":"Lauren E Koval, Richard Judson, Julia E Rager","doi":"10.1002/em.70034","DOIUrl":"https://doi.org/10.1002/em.70034","url":null,"abstract":"<p><p>Breast cancer is the most prevalent cancer in women and has been linked to exposure to environmental chemicals. However, many chemicals have not been evaluated for relationships with this outcome. In this study, we analyzed RNA sequencing data from human breast cancer-derived MCF7 cells exposed to hundreds of individual chemicals. These chemicals were binned into three categories: (1) chemicals with known associations to breast cancer (BCs); (2) chemicals with a lack of relationship to breast cancer (NBCs); and (3) chemicals that remain understudied for breast cancer risk (UCs). Machine learning models were trained to discriminate between BCs and NBCs based on transcriptomic and physicochemical property data. The best model yielded a balanced accuracy of 80% and was applied to the UCs. A total of 170 genes were found to contribute to model performance, including Claspin (CLSPN), Runt-related Transcription Factor 2 (RUNX2), and Ubinuclein 2 (UBN2). These genes further informed enriched pathways relevant to inflammation, ferroptosis signaling, and cell proliferation. Additionally, 97 UCs were predicted to be more analogous to BCs, including select biocides and dyes. To ground results in human population data, expression profiles for the 170 genes were assessed in tumor samples from The Cancer Genome Atlas, yielding overlap in human cancer-relevant alterations and in vitro chemical-induced alterations. Collectively, this study addresses a gap related to understanding which chemicals may be of interest for further characterization of breast cancer risk by prioritizing chemicals and underlying mechanisms using high-throughput transcriptomic screening data.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145039493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adverse Outcome Pathways Applied to Space Radiation Research.","authors":"Vinita Chauhan, Veronica S Grybas, Devyn Hoopfer, Casey Higginson, Elizabeth A Ainsbury, Omid Azimzadeh, Afshin Beheshti, Steve Blattnig, Marjan Boerma, Sylvain V Costes, Stephen Doty, Christelle Adam-Guillermin, Nobuyuki Hamada, Patricia Hinton, Janice L Huff, Robert Reynolds, Ruth C Wilkins, Scott Wood, Carole L Yauk","doi":"10.1002/em.70031","DOIUrl":"https://doi.org/10.1002/em.70031","url":null,"abstract":"<p><p>Long-duration spaceflight exposes astronauts to various stressors that can alter human physiology, potentially causing immediate and long-term health effects. These stressors can damage biomolecules, cells, tissues, and organs, leading to adverse outcomes. Developing adverse outcome pathways (AOPs) relevant to radiation exposure can guide research priorities and inform risk assessments of future space exploration activities. Through expert consultation, we developed an AOP network linking 18 key events (KEs) to four non-cancer outcomes: learning and memory impairment, bone loss, abnormal vascular remodeling, and cataract development. A novel scoping review methodology informed the evidence evaluation and supported causal linkages between two KEs. The AOP network begins with the molecular initiating event (MIE) of energy deposition onto cells, which may trigger oxidative stress and DNA damage. If DNA damage is misrepaired, it could lead to gene mutations or chromosomal aberrations. In cases where these occur in critical cell cycle genes, there is a possibility of uncontrolled cellular proliferation. Persistent KEs may contribute to the activation of tissue-resident cells, suppression of anti-inflammatory processes, and promotion of chronic inflammation. This inflammatory cycle, potentially driven by mitochondrial dysfunction and immune cell activation, could lead to cell death and tissue damage. Over time, this accumulation of damage might contribute to organ-specific adverse outcomes associated with radiation exposure. This AOP network consolidates knowledge across biological levels and identifies gaps in understanding causal relationships. It aims to guide research for space traveler risk models and can also apply to other radiation exposure scenarios, such as in medical or occupational settings.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145023046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstracts From the 56th Annual Meeting of the Environmental Mutagenesis and Genomics Society, Genomic Health Innovations, Perspectives, and Progress Bloom in the Flower City, September 6 – 10, 2025 - Rochester, NY","authors":"","doi":"10.1002/em.70032","DOIUrl":"https://doi.org/10.1002/em.70032","url":null,"abstract":"","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 S1","pages":"6-106"},"PeriodicalIF":2.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular Impacts of Occupational Exposure to Waste Anesthetic Gases","authors":"Mariane A. P. Silva,&nbsp;Mónica Cappetta,&nbsp;Tony F. Grassi,&nbsp;Leandro G. Braz,&nbsp;Mariana G. Braz","doi":"10.1002/em.70029","DOIUrl":"10.1002/em.70029","url":null,"abstract":"<p>Millions of healthcare professionals are occupationally exposed to waste anesthetic gases (WAGs) worldwide; however, their effect on DNA methylation is unknown. Thus, for the first time, global DNA methylation analysis was performed in addition to the comet assay and gene expression analysis in this case–control study to reveal possible molecular alterations associated with WAG exposure. A total of 86 participants were included (43 healthcare professionals exposed to WAGs and 43 matched-controls). Mononuclear cells were isolated for the comet assay, and DNA was extracted from whole blood for global DNA methylation analysis. RNA was isolated for the gene expression of <i>NRF2</i>, <i>SIRT1</i>, and <i>HO1</i>. Increased DNA damage was observed in the exposed group (<i>p</i> = 0.02). No differences in global DNA methylation or <i>HO1</i> expression were observed (<i>p</i> &gt; 0.05), but <i>SIRT1</i> (<i>p</i> = 0.01) and <i>NRF2</i> (<i>p</i> = 0.02) upregulation were observed in the exposed group. These findings highlight the molecular effects of WAG exposure.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 6-7","pages":"397-402"},"PeriodicalIF":2.3,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/em.70029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144947256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Origin Story of IARC's 10 Key Characteristics of Carcinogens.","authors":"David M DeMarini","doi":"10.1002/em.70028","DOIUrl":"https://doi.org/10.1002/em.70028","url":null,"abstract":"<p><p>The 10 Key Characteristics of Carcinogens (KCs) were developed by the International Agency for Research on Cancer (IARC) as a framework for organizing mechanistic data for evaluating agents as potential human carcinogens. They emerged from more than half a century of insight into the mechanisms of carcinogenesis. In particular, the Hallmarks of Cancer described by D. Hannahan and R.A. Weinberg in 2000 and 2011 stimulated thinking about how carcinogens resulted in the features of cancer cells. A Workshop at the Environmental Mutagen Society meeting in 2007 produced a list of 15 Key Events Associated with Carcinogenesis (Guyton et al. Mutat Res 681:230, 2009). Also in 2007, IARC organized an Advisory Meeting to update the literature on the approximately 100 IARC Group 1 (known) human carcinogens, resulting in IARC Monograph Vol. 100 in 2012. IARC then recognized the need to identify the mechanistic events associated with human carcinogens, addressing these in a Workshop in April and November 2012, during which the KCs were developed. Along with IARC, other agencies began incorporating the KCs into cancer evaluations, and the KCs were soon modified for evaluating agents for a variety of toxicological endpoints beyond cancer. After experience using the KCs for cancer evaluations, IARC convened a workshop in 2023 to assess the KCs, publishing a summary of the workshop and a technical report in 2025. The concept underlying the KCs has provided a universal framework for organizing the mechanistic literature of agents for their potential as human carcinogens and many other toxicological endpoints.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144858993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Colemanite Attenuates Metaflumizone-Mediated Hematic/Hepatic Inflammation and DNA Damage in Oncorhynchus mykiss.","authors":"Muhammed Atamanalp, Adem Karaman, Arzu Ucar, Gonca Alak, Veysel Parlak, Fatma Betul Ozgeris, Aslı Cilingir Yeltekin, Hasan Turkez","doi":"10.1002/em.70026","DOIUrl":"https://doi.org/10.1002/em.70026","url":null,"abstract":"<p><p>This study was arranged to assign the LC₅₀ value and effects of metaflumizone (MFZ) in Oncorhynchus mykiss blood/liver tissue with a multibiomarker approach. In addition, the positive/negative responses of the colemanite (COL) substance for integrating therapeutic agents into aquaculture were also discussed. Hematology profile revealed that red blood cell (RBC), hemoglobin (Hgb), and hematocrit (Hct) decreased temporally as a result of MFZ application compared to the control group. When cortisol results were evaluated, it was determined that MFZ induced cortisol levels at 48th and 96th hours. It was noted that antioxidant enzyme activities were significantly inhibited in blood/liver tissue taken at 48th/96th hour samples of MFZ application. After MFZ exposure, malondialdehyde (MDA) and myeloperoxidase (MPO) values increased, and this situation was interpreted as statistically meaningful. Nuclear factor erythroid 2 level (Nrf-2) was inhibited depending on time when the administration and control groups were compared. In the MFZ + COL group, inhibition was found to be alleviated. In the 48th and 96th hour analyses of blood/liver tissue, it was determined that interleukin-6 (IL-6) and tumor necrosis factor alfa (TNF-α) values were induced in MFZ applied groups, and COL tried to inhibit this situation. MFZ application showed a significant increase in 8-OHdG content and caspase 3 level, which was statistically significant (p < 0.05) over time. COL (single and/or MFZ) suppressed the accumulation of 8-hidroksi-2'-deoksiguanozin (8-OHdG) and caspase-3 levels as treatment, resulting in similar results to the control group. However, COL administration showed attenuation of all parameters with respect to these MFZ-induced toxicities, possibly because of its free radical scavenging and anti-inflammatory features.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144844977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding the Impact of Genetic Polymorphisms in Xenobiotic Metabolizing Enzymes and Ovarian Cancer: A Comprehensive Review.","authors":"Harshavardhani Canchi Sistla, Srikanth Talluri, Sivaramakrishnan Venkatabalasubramanian, Nageswara Rao Dunna","doi":"10.1002/em.70030","DOIUrl":"https://doi.org/10.1002/em.70030","url":null,"abstract":"<p><p>Ovarian cancer (OC), the third most common and fatal gynecological malignancy, is a heterogeneous disease characterized by genomic instability. The interaction between genetic and environmental factors, including xenobiotics, plays a crucial role in OC initiation, progression, and treatment resistance. Xenobiotic metabolism (XM) is a key process for metabolizing and detoxifying environmental carcinogens, drugs, and other xenobiotics. Variations in XM genes (XMGs), such as those encoding cytochrome P450s (CYPs), UDP-glucuronosyltransferases (UGTs), sulfotransferases (SULTs), N-acetyltransferases, and glutathione S-transferases (GSTs), can alter enzyme activity, thereby affecting detoxification, hormone metabolism, and clinical outcomes. Previous research has shown the effects of genetic variants on XM in OC, underscoring the importance of pharmacogenomics in tailoring personalized treatments. However, challenges persist, including individual variability, study inconsistencies, and insufficient ovarian-specific data on XM. This review provides a comprehensive overview of XM in OC. It emphasizes the importance of phase I and II enzymes in detoxification and biotransformation, and ABC transporters in drug metabolism and chemoresistance. This review provides insights into the emerging roles of CYPs, GSTs, glutathione peroxidases, myeloperoxidase, catalase, superoxide dismutase, SULTs, and UGTs, and addresses the need for further research to understand their influence on OC risk and prognosis. By addressing the gaps in ovarian-specific XM research, including their role in susceptibility and treatment response, these insights have the potential to advance targeted therapeutic strategies and overcome the challenges of chemoresistance in OC.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144834437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tissue and Sex-Specific Performance of a Cancer Driver Based Biomarker in rasH2-Tg Mice.","authors":"Kelly L Harris, Jennifer B Faske, Binsheng Gong, Barbara L Parsons","doi":"10.1002/em.70027","DOIUrl":"10.1002/em.70027","url":null,"abstract":"<p><p>The ability to predict rodent lifetime tumor responses from short-term exposures and a scientific basis for rodent to human extrapolation are unmet needs in cancer risk assessment. To address these needs, quantitation of cancer driver mutations (CDMs) was integrated with an error-corrected, next generation sequencing (NGS) approach. The method developed, CarcSeq, involves performing multiple, high-fidelity PCR reactions to amplify hotspot CDM-containing target sequences, tagging amplicons with 9 base unique identifier sequences, and constructing libraries from the pooled amplicons. Single-strand consensus sequences were constructed for error correction. A metric of variability in CDM levels, median absolute deviation in mutant fraction (MAD), is being developed as a biomarker of clonal expansion. This study leveraged the sex-related difference in spontaneous lung tumor development in the rasH2-Tg mouse model to validate and refine the CarcSeq approach for assessing clonal expansion. Significantly greater MAD was observed in male as compared to female rasH2-Tg mice, along with more recurrent mutations and a higher proportion of mutations conferring a potentially selectable phenotype in males, consistent with the greater propensity for spontaneous lung tumorigenesis in males. In the analysis of MAD, use of a sex-specific median and classification of lung-specific drivers based on a COSMIC-reported mutation frequency ≥ 5% performed better than use of the overall median MF and classification based on COSMIC's top ranked lung neoplasia genes. Thus, this study provides further validation of the CarcSeq/MAD biomarker approach and technical insight into best practices in evaluating clonal expansion based on measurement of cancer driver gene mutations.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12459003/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144834438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing Genotoxicity Assessment by Building a Global AOP Network","authors":"E. Demuynck,&nbsp;T. Vanhaecke,&nbsp;A. Thienpont,&nbsp;D. Cappoen,&nbsp;F. Van Goethem,&nbsp;L. M. T. Winkelman,&nbsp;J. B. Beltman,&nbsp;S. Murugadoss,&nbsp;A.-K. Olsen,&nbsp;F. Marcon,&nbsp;C. Bossa,&nbsp;S. M. Shaikh,&nbsp;D. Nikolopoulou,&nbsp;V. Hatzi,&nbsp;J. Pennings,&nbsp;M. Luijten,&nbsp;C. Adam-Guillermin,&nbsp;M. Paparella,&nbsp;M. Audebert,&nbsp;B. Mertens","doi":"10.1002/em.70022","DOIUrl":"10.1002/em.70022","url":null,"abstract":"<div>\u0000 \u0000 <p>Current genotoxicity testing strategies face several challenges, including a high incidence of misleading positive results that lead to unnecessary animal testing, limited mechanistic insights, insufficient integration of innovative methodologies, and a lack of quantitative assessment. Despite rapid advancements in technology and scientific understanding, genotoxicity testing batteries have remained largely unchanged for years. To modernize genotoxicity assessment and incorporate innovative approaches, the development of Integrated Approaches for Testing and Assessment (IATAs) is essential. These frameworks combine existing knowledge with data from New Approach Methodologies (NAMs) aiming to reduce or eliminate reliance on in vivo testing. Genotoxicity is particularly well-suited for IATA development as numerous cutting-edge, non-animal methods have emerged in recent years, including 3D test systems, Prediscreen, MultiFlow, ToxTracker, and transcriptomic-based biomarkers such as GENOMARK and TGx-DDI. However, the integration of NAMs into IATAs must be systematic and scientifically robust. In this process, the Adverse Outcome Pathway (AOP) framework plays a crucial role by linking molecular-level events to adverse health effects, thereby supporting the structured selection of NAMs. This article explores the key challenges and gaps within the current European regulatory frameworks for chemical compound genotoxicity assessment and discusses how an AOP-based IATA can address these issues. Additionally, we present a global AOP network for permanent DNA damage, designed to guide IATA development and improve regulatory decision-making. This integrated approach has the potential to enhance the accuracy, efficiency, and ethical standards of genotoxicity assessment while reducing reliance on animal testing.</p>\u0000 </div>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 6-7","pages":"341-366"},"PeriodicalIF":2.3,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144816102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Multiplexed Flow Cytometric Assays and Toxicogenomic Signatures for Genotoxicity Prediction: A Model Performance and Case Study Approach","authors":"Tomás Lagunas Jr.,&nbsp;Fjodor Melnikov,&nbsp;Gabby Cole,&nbsp;Steve Niu,&nbsp;Estefania Esparza,&nbsp;John Davies,&nbsp;Catrin Hasselgren,&nbsp;Aaron Fullerton,&nbsp;Yu Zhong","doi":"10.1002/em.70025","DOIUrl":"10.1002/em.70025","url":null,"abstract":"<div>\u0000 \u0000 <p>Genotoxicity assays play a significant role in protecting clinical trial subjects from potential increased risk of genotoxic hazard and cancer during drug development. Traditional genetic toxicology assays typically provide binary outcomes with limited mechanistic insight. This study evaluates machine learning (ML) models based on an in-house implementation of MultiFlow DNA Damage Assay and MicroFlow Assays, and compared these results to previously published Litron assays. Our ML models demonstrated high accuracy, with MultiFlow data achieving 96% balanced accuracy for mode of action (MoA) prediction and 99% for genotoxicity prediction in repeated cross-validation. We collected and interpreted the MicroFlow and MultiFlow data in a dose–response format. The dose–response data enabled us to improve assay inference and model accuracy. In addition, we conducted case studies using toxicogenomic data, including the Toxicogenomic DNA Damage Inducing (TGx-DDI) transcriptomic biomarker and bulk RNA-seq, on a small set of compounds where the MoA is not clearly defined by MultiFlow or MicroFlow. The integration of toxicogenomics provided deeper insights into the molecular mechanisms of genotoxicity, allowing for the identification of specific pathways affected by these compounds. These findings emphasize the importance of careful endpoint selection and data interpretation. Overall, this study enhances the precision of genotoxicity predictions by integrating toxicogenomics, offering a framework for future genotoxicity safety assessments.</p>\u0000 </div>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 6-7","pages":"377-396"},"PeriodicalIF":2.3,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144689648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}