Human Genomics最新文献

{"title":"Decoding the lactylation-immune link in calcific aortic valve disease: a comprehensive bioinformatics approach.","authors":"Gaofeng Li, Jinchi Zhang, Xiang Qiu, Fuqiang Tong, Xiuqi Hu, Wenyi Wan, Zongqi Han, Weihua Qiao, Nianguo Dong","doi":"10.1186/s40246-025-00823-9","DOIUrl":"10.1186/s40246-025-00823-9","url":null,"abstract":"","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"107"},"PeriodicalIF":4.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12481745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145191756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-based transcriptomic analysis identifies candidate genes in sepsis-induced coagulopathy and explores the immunomodulatory potential of baicalein.","authors":"Lifang Mu, Yuxue Zhang, Tingting Yuan, Dingshun Zhang, Zhifeng Liu, Ming Wu, Li Zhong","doi":"10.1186/s40246-025-00818-6","DOIUrl":"https://doi.org/10.1186/s40246-025-00818-6","url":null,"abstract":"<p><strong>Background: </strong>Sepsis is a major contributor to high morbidity and mortality, often leading to coagulation disorders (CD) in affected individuals. Baicalein, a natural compound with well-established anti-inflammatory properties, shows promise as a potential treatment for sepsis. However, its molecular mechanisms in sepsis-associated CD remain poorly understood. This study investigated the therapeutic effects of baicalein in sepsis and identified candidate genes involved in its mechanism of action.</p><p><strong>Methods: </strong>Transcriptomic data, baicalein-related targets from public databases, and CD-related genes from the literature were analyzed to identify potential candidate genes. Machine learning algorithms and expression validation techniques were employed to screen initial candidate genes from the candidates. A nomogram was then constructed based on these candidate genes. Functional enrichment and immune infiltration analyses were conducted to explore the underlying mechanisms, while molecular docking was used to assess interactions between baicalein and the candidate genes. Gene expression was further validated by reverse transcription-quantitative PCR (RT-qPCR).</p><p><strong>Results: </strong>Seven initial candidate genes were identified. Machine learning and expression validation confirmed MMP9, ARG1, and FYN as the final candidate genes involved in sepsis. A highly accurate nomogram, constructed using these candidate genes, demonstrated strong predictive value for sepsis diagnosis. Functional enrichment analysis revealed their pivotal roles in sepsis pathogenesis, while immune infiltration analysis indicated immune dysregulation in sepsis. Additionally, molecular docking revealed strong binding interactions between baicalein and proteins encoded by these candidate genes, supporting further investigation of its therapeutic potential in sepsis. However, these in silico findings are preliminary and require validation through in vitro and in vivo experiments to confirm biological activity. RT-qPCR further validated differential expression of these genes in patients with sepsis compared to healthy controls, confirming the results.</p><p><strong>Conclusion: </strong>This study identified MMP9, ARG1, and FYN as candidate genes in sepsis involved in immune regulation. Additionally, molecular docking revealed strong binding interactions between baicalein and the proteins encoded by these candidate genes, supporting further investigation of its therapeutic potential in sepsis.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"102"},"PeriodicalIF":4.3,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12398980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RENOVO-NF1 accurately predicts NF1 missense variant pathogenicity.","authors":"Emanuele Bonetti, Serena Pellegatta, Nayma Rosati, Marica Eoli, Luca Mazzarella","doi":"10.1186/s40246-025-00803-z","DOIUrl":"https://doi.org/10.1186/s40246-025-00803-z","url":null,"abstract":"<p><p>Identification of a pathogenic variant in NF1 is diagnostic for neurofibromatosis, but is often impossible at the moment of variant detection due to many factors including allelic heterogeneity, sequence homology, and the lack of functional assays. Computational tools may aid in interpretation but are not established for NF1. Here, we optimized our random forest-based predictor RENOVO for NF1 variant interpretation. RENOVO was developed using an approach of \"database archaeology\": by comparing versions of ClinVar over the years, we defined \"stable\" variants that maintained the same pathogenic/likely pathogenic/benign/likely benign (P/LP/B/LB) classification over time (n = 3579, the training set), and \"unstable\" variants that were initially classified as Variants of Unknown Significance (VUS) but were subsequently reclassified as P/LP/B/LB (n = 57, the test set). This approach allows to retrospectively measure accuracy on prediction with insufficient information, reproducing the scenario of maximal clinical utility. We further validated performance on: (i) validation set 1: 100 NF1 variants classified as VUS at the time of RENOVO development and subsequently reclassified as P/LP/B/LB in ClinVar; (ii) validation set 2: 15 de novo variants discovered in a prospective clinical cohort and subsequently reclassified per ACMG criteria. RENOVO obtained consistently high accuracy on all datasets: 98.6% on the training test, 96.5% in the test set, 82% in validation set 1 (but 96.2% for missense variants) and 93.7% on validation set 2. In conclusion, RENOVO-NF1 accurately interprets NF1 variants for which information at the time of detection is insufficient for ACMG classification and may overcome diagnostic challenges in neurofibromatosis.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"106"},"PeriodicalIF":4.3,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12400616/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel splice-altering frameshift variant in the COL1A1 gene underlies osteogenesis imperfecta type I: molecular characterization of a four-generation Chinese pedigree and literature review.","authors":"Dongye He, Yanan Luo, Shuoshuo Wei, Yumeng Wang, Chuanpeng Zhang, Shuxiong Chen, Bo Ban, Mei Zhang, Yanying Li","doi":"10.1186/s40246-025-00816-8","DOIUrl":"10.1186/s40246-025-00816-8","url":null,"abstract":"<p><strong>Backgroud: </strong>Osteogenesis imperfecta (OI) is a phenotypically and genetically heterogeneous group of inherited connective tissue disorder. This investigation aims to elucidate the molecular etiology underlying a four-generation Chinese family affected by OI.</p><p><strong>Methods: </strong>Whole-exome sequencing was employed to identify pathogenic variants in the proband, with subsequent Sanger sequencing performed for familial co-segregation analysis. A minigene assay was conducted to investigate the effect of variant on splicing patterns. The pathogenic potential of variant was evaluated through protein structural modeling and HEK293 cell-based functional studies. COL1A1 splicing variants were further collated to analyze its occurrence frequency across geographically diverse OI cohorts, intronic distribution patterns and potential hotpots for mild versus severe subtypes.</p><p><strong>Results: </strong>Multiple affected members within an non-consanguineous Chinese pedigree exhibited clinical manifestations fitting OI-associated phenotypic spectrum. A novel heterozygous COL1A1 splicing variant (c.370-2A > C) inherited from the mother was identified in the proband. The splicing variant altered the canonical acceptor site (AG) at the intron 4-exon 5 junction, activating a adjacent cryptic splicing site in exon 5. This abberrant splicing event introduced a frameshift variant (c.370_379delGGACCCGCAG), and generated a premature termination codon that truncates the COL1A1 protein (p.Gly124Alafs*138). AlphaFold3-based protein structural modeling revealed the loss of the triple-helical domain in this truncated protein. In vitro functional assays showed that mRNA and protein expression levels of mutant COL1A1 were significantly increased than wild-type COL1A1 (p < 0.05). Comprehensive literature analysis indicated that COL1A1 splicing variants account for < 10% of variants in OI cohorts from the vast majority of regions. The acceptor site of intron 9 and the donor sites of intron 35 are hotspots for COL1A1 splicing variant occurrence. Moreover, the majority of COL1A1 splicing variants, expecially those proximal to the 5' and 3' terminal regions, result in mild manifestations of OI type I, whereas variants at donor sites of introns 14, 20, and 46, may be candidate hotspots for lethal OI type II.</p><p><strong>Conclusions: </strong>Our study revealed the pathogenic mechanism of a novel COL1A1 splicing variant in a four-generation Chinese family with OI, and provided updated data on COL1A1 splicing variants and its potential hotpots for mild versus severe OI subtypes.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"103"},"PeriodicalIF":4.3,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12398993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic and transcriptomic data reveal molecular differences between homologous recombination deficiency subgroups in Chinese ovarian cancer patients.","authors":"Hongxia Wang, Wenhong Zhao, Wenhao Zhou, Na Wang, Yijie Li, Kaiyun Qin, Jingde Jia, Jiaqian Wang, Congcong Song, Yu Yu, Fenghua Zhang, Xu Cui, Lanlan Zhao, Haitao Luo, Zhengmao Zhang","doi":"10.1186/s40246-025-00806-w","DOIUrl":"https://doi.org/10.1186/s40246-025-00806-w","url":null,"abstract":"<p><strong>Background: </strong>Ovarian cancer (OV) has the highest mortality rate among gynecological cancers and shows varied responses to chemotherapy combined with PARP inhibitors based on homologous recombination deficiency (HRD) subtypes.</p><p><strong>Methods: </strong>This study enrolled 143 Chinese OV patients to determine the HRD score grouping threshold using genomic features, dividing patients into HRD-high and HRD-low groups. Multi-omics sequencing was conducted on 70 patients receiving adjuvant chemotherapy with PARP inhibitors.</p><p><strong>Results: </strong>In this study, TP53 mutations enriched in the HRD-high group, while ARID1A, PIK3CA, and PTEN mutations were more common in the HRD-low group. HRD-high patients exhibited stronger immune activation, including elevated STAT1 expression, HLA signatures, and increased M1 macrophage infiltration, correlating with better prognosis. Additionally, peripheral blood analysis revealed higher bMSI and maxVAF levels in HRD-low patients compared to HRD-high patients, suggesting ctDNA as a potential tool for dynamic monitoring post-treatment.</p><p><strong>Conclusions: </strong>This study identified distinct molecular and immune profiles between HRD subgroups in Chinese ovarian cancer patients. Patients with HRD-high and STAT1 expression ≥ 74 suggests PARPi benefit.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"104"},"PeriodicalIF":4.3,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12398958/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carrying APOL1 G1 allele is associated with cardiovascular complications during COVID-19 in an admixed population.","authors":"Nathan A Cadore, Bibiana S de O Fam, Giovanna C Giudicelli, Thayne W Kowalski, Renan C Sbruzzi, Marcos A Castro E Silva, Marilea F Feira, Célia Mariana B de Souza, Dirceu R da Silva, Osvaldo Artigalás, Renan B Lemes, Maíra R Rodrigues, Kelly Nunes, Alexandre C Pereira, Lygia V Pereira, Tábita Hünemeier, Fernanda S L Vianna","doi":"10.1186/s40246-025-00790-1","DOIUrl":"https://doi.org/10.1186/s40246-025-00790-1","url":null,"abstract":"","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"105"},"PeriodicalIF":4.3,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12398974/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-omics signature of healthy versus unhealthy lifestyles reveals associations with diseases.","authors":"Grace Fu, Blake R Rushing, Lee Graves, David C Nieman, Matteo Pellegrini, Matthew Soldano, Michael J Thompson, Camila A Sakaguchi, Wimal Pathmasiri, Susan J Sumner","doi":"10.1186/s40246-025-00817-7","DOIUrl":"https://doi.org/10.1186/s40246-025-00817-7","url":null,"abstract":"<p><p>This multi-omics cross-sectional study investigated differences in metabolomics, proteomics, and epigenomics profiles between two groups of adults matched for age but differing in lifestyle factors such as body composition, diet, and physical activity patterns. Data from prior studies were utilized for a comprehensive integrative analysis. The study included 52 participants in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females). Using multi-omics integration software (OmicsNet and Pathview), 96 significantly (p < 0.05) enriched pathways were identified that differentiated the LIFE and CON groups. Top pathways significantly (p < 2.63 × 10^-5) influenced by group status included fatty acid degradation, fatty acid elongation, glutathione metabolism, Parkinson disease, and central carbon metabolism in cancer. This study identified a distinct metabolic signature comprised of metabolites, proteins, and gene methylation sites associated with a healthy lifestyle. These findings provide unique, but complementary, results to previous single-omics analyses using metabolomics and proteomics procedures which showed that the LIFE group exhibited lower plasma bile acid levels, higher levels of beneficial fatty acids, reduced innate immune activation, enhanced lipoprotein metabolism, and increased HDL remodeling. The current multi-omics analysis builds on these previous results by providing a more holistic view of how metabolites, proteins, and methylation sites associated with a healthy lifestyle, providing a larger, more comprehensive list of altered pathways. Additionally, the integrated analysis revealed connections between lifestyle factors and conditions such as cancer and insulin resistance beyond what identified in the single-omics approaches, highlighting the broader metabolic impact of lifestyle on health. Overall, the signatures identified by this multi-omics approach provide a basis for developing more translational biomarkers, such as those that defined the cancer and insulin resistance pathways that can be used to assess one's state of health and provide guidance on behavior modifications that should be taken to lower disease risk.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"101"},"PeriodicalIF":4.3,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12398164/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DNA methylation in adaptation to high-altitude environments and pathogenesis of related diseases.","authors":"Xingkai Zhang, Yuxi Yang, Qinghai Shi","doi":"10.1186/s40246-025-00794-x","DOIUrl":"https://doi.org/10.1186/s40246-025-00794-x","url":null,"abstract":"<p><p>High-altitude environments, characterized by hypoxia, low temperatures, and intense ultraviolet radiation, pose significant challenges to human physiology and health. DNA methylation, as a key epigenetic regulatory mechanism, plays a central role in human adaptation to high-altitude environments and in disease pathogenesis. Current research indicates that high-altitude native populations (such as Tibetans and Andeans) modulate the methylation of hypoxia-responsive genes like EPAS1 and EGLN1 to enhance oxygen transport efficiency and energy metabolism patterns, while simultaneously suppressing excessive erythropoiesis and oxidative stress damage. This epigenetic regulation not only compensates for the lag in genetic adaptation over time but also forms synergistic networks with genetic variations. For instance, the functional SNPs of the EPAS1 gene are co-localized with its differentially methylated regions, revealing a delicate balance between genetic and epigenetic interactions under environmental stress. On the other hand, aberrant methylation patterns may disrupt the homeostasis of the HIF pathway, leading to acute and chronic high-altitude illnesses. This article provides a review of the recent research progress in plateau medicine and DNA methylation (up to 2025), including human clinical studies and animal model research. This includes research on high-altitude adaptation/acclimatization, as well as studies on inadequate adaptation to high altitude in relation to acute and chronic high-altitude-related diseases, cognitive decline, and pregnancy risks. By elucidating the core mechanisms underlying the \"environmen - epigenetics - phenotype\" axis, this work aims to provide a theoretical foundation for precision health interventions in high-altitude regions.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"100"},"PeriodicalIF":4.3,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12398096/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative single-cell and bulk transcriptomic analysis reveals the landscape of T cell mitotic catastrophe associated genes in esophageal squamous cell carcinoma.","authors":"Shuang Li, Zheng Tao, Nan Wang, Yazhou Liu, Kai Xie, Haitao Ma","doi":"10.1186/s40246-025-00815-9","DOIUrl":"https://doi.org/10.1186/s40246-025-00815-9","url":null,"abstract":"<p><strong>Background: </strong>Mitotic catastrophe (MC) is a well-recognized endogenous mechanism of tumor cell death, characterized as a delayed cell death process associated with aberrant mitosis. However, its prognostic significance in the context of intratumoral heterogeneity in esophageal squamous cell carcinoma (ESCC) remains largely unexplored.</p><p><strong>Methods: </strong>We performed an in-depth analysis of single-cell RNA sequencing (scRNA-seq) data from ESCC obtained from the Gene Expression Omnibus (GEO) database. MC scores for individual cells were calculated using the AddModuleScore function, and T cell specific gene modules were identified via the high-dimensional weighted gene co-expression network analysis (hdWGCNA) framework. To further elucidate the developmental trajectories and intercellular interactions of T cells, pseudotime analysis and cell-cell communication inference were conducted. A prognostic risk model was then constructed using three machine learning algorithms combined with multivariate Cox regression analysis. Following risk stratification, we performed immune infiltration profiling, drug sensitivity analysis, and molecular docking to comprehensively assess the functional implications of the risk model in ESCC. Based on preliminary results from quantitative Real-time PCR (qRT-PCR) and Western blotting (WB), we selected the hub gene SLF2 for functional validation using wound healing, Cell Counting Kit-8 (CCK-8) assay, Transwell, and colony formation assays.</p><p><strong>Results: </strong>Based on T cell mitotic catastrophe associated genes (MCAGs) and utilizing machine learning algorithms, we established a robust prognostic risk model for ESCC. The model demonstrated excellent stratification capability in predicting patient outcomes and effectively revealed the heterogeneity of the tumor immune microenvironment (TIME) and drug sensitivity. Furthermore, functional experiments confirmed that knockdown of the hub gene SLF2 significantly inhibited the migration, invasion, and proliferation of ESCC cells.</p><p><strong>Conclusion: </strong>The prognostic model based on MCAGs we developed serves as an effective tool for predicting outcomes in ESCC.T cell-specific MCAGs drive intratumoral heterogeneity in ESCC, serving as potential prognostic biomarkers and therapeutic targets.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"99"},"PeriodicalIF":4.3,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12398072/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative outcome and prognostic factor analysis among MDS/AML patients with TP53 mutations, snps, and wild type.","authors":"Xiaodi Yang, Zeyin Liang, Li Ji, Wei Liu, Bingjie Wang, Yuan Li, Jinping Ou, Xinan Cen, Hanyun Ren, Stefan Wuchty, Ziding Zhang, Yujun Dong","doi":"10.1186/s40246-025-00792-z","DOIUrl":"https://doi.org/10.1186/s40246-025-00792-z","url":null,"abstract":"","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"98"},"PeriodicalIF":4.3,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12395695/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}