Environmental and Molecular Mutagenesis最新文献

{"title":"Review of Transcriptomic Biomarkers That Predict In Vitro Genotoxicity in Human Cell Lines.","authors":"Heng-Hong Li, Jiri Aubrecht, Tatyana Y Doktorova, Danyel Jennen, J Christopher Corton, Roland Froetschl, Roman Mezencev, Carole L Yauk","doi":"10.1002/em.70004","DOIUrl":"10.1002/em.70004","url":null,"abstract":"<p><p>The current genotoxicity testing paradigm provides little mechanistic information, has poor specificity in predicting carcinogenicity in humans, and is not suited to assessing a large number of chemicals. Genomic technologies enable the characterization of genome-wide transcriptional changes in response to chemical treatments that can inform mechanisms or modes of action. These technologies provided an impetus to develop transcriptomic biomarkers that could transform genotoxicity hazard assessment for drugs, cosmetics, and environmental and industrial chemicals. In August 2022, the International Workshops on Genotoxicity Testing (IWGT) held a workshop to critically review progress in the development and application of transcriptomic biomarkers in genotoxicity testing. Here, we describe the findings of this workshop's subgroup that conducted a systematized review and analysis of in vitro transcriptomic biomarkers for evaluating genotoxicity. Although there is a multitude of published reports exploring transcriptomics in genetic toxicology, the working group identified only five in vitro transcriptomic biomarker candidates, of which three (GENOMARK, TGx-DDI, and MU2012) were independently developed with sufficiently defined context of use, validation data, and supporting case studies that warranted inclusion in the review. Although these in vitro biomarkers were developed independently and for different classes of chemicals (TGx-DDI for pharmaceuticals, GENOMARK for cosmetics, and MU2012 for medical and environmental chemicals), they all address the same shortfall of the standard in vitro genotoxicity testing battery, that is, lack of specificity by genotoxicity-induced stress response at the transcriptomic level. In this review, we discuss the development of these in vitro biomarkers, including challenges and progress toward achieving regulatory acceptance.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12353356/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143540637","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":"Tong-man Ong (June 9, 1935–January 5, 2025)","authors":"Gopala Krishna","doi":"10.1002/em.70001","DOIUrl":"10.1002/em.70001","url":null,"abstract":"","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 1-2","pages":"4-5"},"PeriodicalIF":2.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143531300","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":"Characterizing the Pulmonary Toxicity and Potential Mutagenicity of Formaldehyde Fumes in a Human Bronchial Epithelial Tissue Model","authors":"Yuan Le,&nbsp;Baiping Ren,&nbsp;Levan Muskhelishvili,&nbsp;Kelly Davis,&nbsp;Yiying Wang,&nbsp;William Gwinn,&nbsp;Diego Rua,&nbsp;Robert H. Heflich,&nbsp;Xuefei Cao","doi":"10.1002/em.70000","DOIUrl":"10.1002/em.70000","url":null,"abstract":"<div>\u0000 \u0000 <p>Formaldehyde (FA) is a highly reactive aldehyde that is regarded as an inhalation hazard and human carcinogen. Herein, we report a follow-up study evaluating the effects of exposure duration on the toxicity and mutagenicity of FA using a human in vitro air-liquid-interface (ALI) airway tissue model. Previously we exposed ALI cultures to 7.5, 15 and 30-ppm FA fumes 4 h/day for 5 days; currently, we have increased the exposure duration of cultures exposed to 7.5 and 15 ppm FA to 5 days/week for 4 weeks, followed by a 28-day recovery. Due to its toxicity, cultures exposed to 30 ppm FA were treated for 5 days, followed by the recovery. Tissue responses were evaluated following the treatment and recovery. DNA damage was measured using the Comet-Chip assay after 3 days of exposure, and mutagenesis was evaluated by duplex sequencing following the recovery. The toxicity detected following the 4-week exposure was similar to that seen previously with the 5-day exposures: both 7.5 and 15 ppm FA induced moderate decreases in tissue integrity, FANCD2 DNA-repair enzyme expression and IL-6 release, and moderate increases in IL-1RA release. Effects on cell proliferation, ciliary function and tissue structure were minimal. Additionally, neither the 4-week exposure to 7.5 and 15 ppm FA nor the 5-day exposure to 30 ppm FA induced DNA damage or mutations. Using this experimental design, exposure of human ALI airway cultures to FA fumes does not produce genotoxicity or mutagenicity, even when exposures are conducted over a 28-day period.</p>\u0000 </div>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 1-2","pages":"6-21"},"PeriodicalIF":2.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143482441","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":"Epigenetic Modifications Associated With Wildland–Urban Interface (WUI) Firefighting","authors":"Jaclyn M. Goodrich,&nbsp;Melissa A. Furlong,&nbsp;Derek J. Urwin,&nbsp;Jamie Gabriel,&nbsp;Jeff Hughes,&nbsp;Alesia M. Jung,&nbsp;Miriam M. Calkins,&nbsp;Kathleen N. DuBose,&nbsp;Alberto J. Caban-Martinez,&nbsp;Natasha Schaefer Solle,&nbsp;Shawn C. Beitel,&nbsp;Jefferey L. Burgess","doi":"10.1002/em.70002","DOIUrl":"10.1002/em.70002","url":null,"abstract":"<p>Wildland–urban interface (WUI) firefighting involves exposure to burning vegetation, structures, and other human-made hazards, often without respiratory protection. Response activities can last for long periods of time, spanning multiple days or weeks. Epigenetic modifications, including microRNA (miRNA) expression and DNA methylation, are responsive to toxicant exposures and are part of the development of cancers and other diseases. Epigenetic modifications have not been studied in relation to WUI fires. Firefighters (<i>n</i> = 99) from southern California, including 79 firefighters who responded to at least one WUI fire, provided blood samples at baseline and approximately 10 months later. We quantified the relative abundance of 800 miRNAs in blood samples using the nCounter Human v3 miRNA expression panel and blood leukocyte DNA methylation throughout the genome via the Infinium EPIC array. We used linear mixed models to compare the expression of each miRNA across time and DNA methylation at each locus, adjusting for potential confounders. In the miRNA analysis among all firefighters, 65 miRNAs were significantly different at follow-up compared to baseline at a false discovery rate of 5%. Results were similar when restricted to firefighters with a recorded WUI fire exposure during the interim period, although only 50 were significant. Expression of miRNA hsa-miR-518c-3p, a tumor suppressor, was significantly associated with WUI fire response (fold change 0.77, 95% CI = [0.69, 0.87]). In the DNA methylation analysis, no statistically significant changes over time were identified. In summary, WUI fire exposures over a wildfire season altered miRNA expression but did not substantially impact DNA methylation.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 1-2","pages":"22-33"},"PeriodicalIF":2.3,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/em.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143448588","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":"Review and meta-analysis of gene expression biomarkers predictive of chemical-induced genotoxicity in vivo.","authors":"J Christopher Corton, Scott S Auerbach, Naoki Koyama, Roman Mezencev, Carole L Yauk, Takayoshi Suzuki","doi":"10.1002/em.22646","DOIUrl":"https://doi.org/10.1002/em.22646","url":null,"abstract":"<p><p>There is growing recognition across broad sectors of the toxicology community that gene expression biomarkers have the potential to identify genotoxic and nongenotoxic carcinogens through a weight-of-evidence approach, providing opportunities to reduce reliance on the 2-year bioassay to identify carcinogens. In August 2022, a workshop within the International Workshops on Genotoxicity Testing (IWGT) was held to critically review current methods to identify genotoxicants using various 'omics profiling methods. Here, we describe the findings of a workshop subgroup focused on the state of the science regarding the use of biomarkers to identify chemicals that act as genotoxicants in vivo. A total of 1341 papers were screened to identify those that were most relevant. While six published biomarkers with characterized accuracy were initially examined, four of the six were not considered further, because they had not been tested for classification accuracy using additional sets of chemicals or other transcript profiling platforms. Two independently derived biomarkers used in conjunction with standard computational techniques can identify genotoxic chemicals in vivo (rat liver or both rat and mouse liver) on different gene expression profiling platforms. The biomarkers have predictive accuracies of ≥92%. These biomarkers have the potential to be used in conjunction with other biomarkers in integrated test strategies using short-term rodent exposures to identify genotoxic and nongenotoxic chemicals that cause cancer.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143002242","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":"Assessing the impact of different solvents in the bacterial reverse mutation test","authors":"Satyam N. Patel,&nbsp;Chetan K. Kajavadara,&nbsp;Rushikesh M. Shukla,&nbsp;Darshan T. Valani,&nbsp;Laxit K. Bhatt,&nbsp;Rajesh Sundar,&nbsp;Mukul R. Jain","doi":"10.1002/em.22649","DOIUrl":"10.1002/em.22649","url":null,"abstract":"<p>The bacterial reverse mutation test is essential for identifying the mutagenic potential of chemicals. The solubility of the test substance is vital for achieving the recommended assay concentration. Preferred solvents like dimethyl sulfoxide and water are chosen for their compatibility and historical data. Selecting a compatible solvent with <i>Salmonella typhimurium</i> and <i>Escherichia coli</i> WP2 uvrA strains, considering a maximum cytotoxic concentration or the limit of 5 mg/plate, can be challenging. This study assessed various solvents, including N,N-dimethylformamide, acetone, acetonitrile, ethyl acetate, 95% ethanol, diethylene glycol monomethyl ether, methanol, P-dioxane, tetrahydrofuran, and dimethylacetamide, as alternative solvents in the AMES test. Results showed all solvents, except tetrahydrofuran, were compatible at concentrations up to 100 μL/plate or more, as they did not inhibit S9 enzymes, bacterial growth, or alter bacterial revertant colony counts, making them suitable for the bacterial reverse mutation test.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 1-2","pages":"69-76"},"PeriodicalIF":2.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142970184","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":"Consensus findings of an International Workshops on Genotoxicity Testing workshop on using transcriptomic biomarkers to predict genotoxicity.","authors":"Roland Froetschl, J Christopher Corton, Henghong Li, Jiri Aubrecht, Scott S Auerbach, Florian Caiment, Tatyana Y Doktorova, Yurika Fujita, Danyel Jennen, Naoki Koyama, Matthew J Meier, Roman Mezencev, Leslie Recio, Takayoshi Suzuki, Carole L Yauk","doi":"10.1002/em.22645","DOIUrl":"https://doi.org/10.1002/em.22645","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Gene expression biomarkers have the potential to identify genotoxic and non-genotoxic carcinogens, providing opportunities for integrated testing and reducing animal use. In August 2022, an International Workshops on Genotoxicity Testing (IWGT) workshop was held to critically review current methods to identify genotoxicants using transcriptomic profiling. Here, we summarize the findings of the workgroup on the state of the science regarding the use of transcriptomic biomarkers to identify genotoxic chemicals in vitro and in vivo. A total of 1341 papers were examined to identify the biomarkers that show the most promise for identifying genotoxicants. This analysis revealed two independently derived in vivo biomarkers and three in vitro biomarkers that, when used in conjunction with standard computational techniques, can identify genotoxic chemicals in vivo (rat or mouse liver) or in human cells in culture using different gene expression profiling platforms, with predictive accuracies of ≥92%. These biomarkers have been validated to differing degrees but typically show high reproducibility across transcriptomic platforms and model systems. They offer several advantages for applications in different contexts of use in genotoxicity testing including: early signal detection, moderate-to-high-throughput screening capacity, adaptability to different cell types and tissues, and insights on mechanistic information on DNA-damage response. Workshop participants agreed on consensus statements to advance the regulatory adoption of transcriptomic biomarkers for genotoxicity. The participants agreed that transcriptomic biomarkers have the potential to be used in conjunction with other biomarkers in integrated test strategies in vitro and using short-term rodent exposures to identify genotoxic and non-genotoxic chemicals that may cause cancer and heritable genetic effects. Following are the consensus statements from the workgroup. Transcriptomic biomarkers for genotoxicity can be used in Weight of Evidence (WoE) evaluation to: determine potential genotoxic mechanisms and hazards; identify misleading positives from in vitro genotoxicity assays; serve as new approach methodologies (NAMs) integrated into the standard battery of genotoxicity tests. Several transcriptomic biomarkers have been developed from sufficiently robust training data sets, validated with external test sets, and have demonstrated performance in multiple laboratories. These transcriptomic biomarkers can be used following established study designs and models designated through existing validation exercises in WoE evaluation. Bridging studies using a selection of training and test chemicals are needed to deviate from the established protocols to confirm performance when a transcriptomic biomarker is being applied in other: tissues, cell models, or gene expression platforms. Top dose selection and time of gene expression analysis are critical and should be established during transcriptomic bi","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142931001","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":"Machine learning enhances genotoxicity assessment using MultiFlow® DNA damage assay","authors":"Panuwat Trairatphisan,&nbsp;Lena Dorsheimer,&nbsp;Peter Monecke,&nbsp;Jan Wenzel,&nbsp;Rubin James,&nbsp;Andreas Czich,&nbsp;Yasmin Dietz-Baum,&nbsp;Friedemann Schmidt","doi":"10.1002/em.22648","DOIUrl":"10.1002/em.22648","url":null,"abstract":"<p>Genotoxicity is a critical determinant for assessing the safety of pharmaceutical drugs, their metabolites, and impurities. Among genotoxicity tests, mechanistic assays such as the MultiFlow® DNA damage assay (MFA) allows the investigations on mode of action (MoA) of DNA damage through four mechanistic markers recorded at two time points. Previous studies have shown that machine learning (ML) can enhance precision on classifying the MoA of genotoxicants. Nevertheless, these approaches need to be tailored to specific chemical spaces and lab conditions for accurate risk assessment. In this study, we applied various state-of-the-art ML algorithms available in an open-source R package (caret) to build MFA-ML models using data from Bryce et al. (2016). The best model achieved 95% accuracy on the training dataset and correctly predicted genotoxicity in 16 out of 17 cases in the test dataset. Incorporating molecular descriptors properties from established in silico models demonstrated further improved performance of the approach to cover challenging examples of pharmaceuticals exhibiting a pharmacological mode of action that could interfere with the biomarker response. Further model validation on an external test set with 49 non-overlapped compounds showed a high model accuracy at 92%. Additionally, a tailored graphical user interface was developed using a freely available R package (shiny) to support visual analysis of MFA data including MoA predictions, facilitating broad usage by laboratory scientists. Lastly, a perspective on the integration of MoA predictions as additional evidence into a genotoxicity assessment workflow is proposed.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 1-2","pages":"45-57"},"PeriodicalIF":2.3,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142909408","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":"Genetic instability of a single exposure to sevoflurane at different concentrations in monitored mice","authors":"Maria Vitória Destro,&nbsp;Mariane A. P. Silva,&nbsp;Tony F. Grassi,&nbsp;Lídia R. de Carvalho,&nbsp;Daisy M. F. Salvadori,&nbsp;Leandro G. Braz,&nbsp;Mariana G. Braz","doi":"10.1002/em.22647","DOIUrl":"10.1002/em.22647","url":null,"abstract":"<p>Sevoflurane is an inhalation anesthetic widely used for general anesthesia, but its genotoxic potential is controversial in clinical studies. It is unknown whether the effects are due to surgery or the anesthetic. Thus, for the first time, the present study investigated genotoxicity in peripheral blood cells and in target organs (liver, lung, and kidney) and micronucleus (MN) in the bone marrow of a single exposure to sevoflurane at three different concentrations in monitored mice. Ninety Swiss mice were distributed into the following groups: exposure to sevoflurane at 3.3% (low), 4.5% (intermediate), and 6.0% (high) in 40% oxygen (O₂) for 2 h; negative control (no exposure); negative control with O₂; and positive control. The exposed animals were heated, monitored for vital signs (temperature, O₂ saturation, heart rate/pulse, and respiratory rate), and anesthetized via a modern low-flow digital system. Mice were euthanized 2 and 24 h after exposure for evaluation by the comet assay and MN test, respectively. No DNA damage occurred in the 3.3% group for any of the organs evaluated, and no genotoxic or mutagenic effects were observed at any sevoflurane concentration in the peripheral blood or liver cells. However, a significant increase in DNA damage was observed at higher concentrations in kidney (4.5%) and lung cells (6.0%) and in the MN frequency (groups 4.5% and 6.0%). No cytotoxicity or histological alterations were observed. In conclusion, high concentrations of sevoflurane induce DNA damage, but concentrations equivalent to those used in clinical practice do not demonstrate genotoxic or mutagenic effects.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":"66 1-2","pages":"58-68"},"PeriodicalIF":2.3,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142893059","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":"Outcome of IWGT workshop on transcriptomic biomarkers for genotoxicity: Key considerations for bioinformatics.","authors":"Matthew J Meier, Florian Caiment, J Christopher Corton, Roland Frötschl, Yurika Fujita, Danyel Jennen, Roman Mezencev, Carole Yauk","doi":"10.1002/em.22644","DOIUrl":"https://doi.org/10.1002/em.22644","url":null,"abstract":"<p><p>As a part of the International Workshop on Genotoxicity Testing (IWGT) in 2022, a workgroup was formed to evaluate the level of validation and regulatory acceptance of transcriptomic biomarkers that identify genotoxic substances. Several such biomarkers have been developed using various molecular techniques and computational approaches. Within the IWGT workgroup on transcriptomic biomarkers, bioinformatics was a central topic of discussion, focusing on the current approaches used to process the underlying molecular data to distill a reliable predictive signal; that is, a gene set that is indicative of genotoxicity and can then be used in later studies to predict potential DNA damaging properties for uncharacterized chemicals. While early studies used microarray data, a technological shift occurred in the past decade to incorporate modern transcriptome measuring techniques such as high-throughput transcriptomics, which in turn is based on high-throughput sequencing. Herein, we present the workgroup's review of the current bioinformatic approaches to identify genes comprising transcriptomic biomarkers. Within the context of regulatory toxicology, the reproducibility of a given analysis is critical. Therefore, the workgroup provides consensus recommendations on how to facilitate sufficient reporting of experimental parameters for the analytical procedures used in a transcriptomic biomarker study, including the recommendation to develop a biomarker-specific reporting module within the OECD Omics Reporting Framework.</p>","PeriodicalId":11791,"journal":{"name":"Environmental and Molecular Mutagenesis","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827734","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}