BMC Medical Genomics最新文献

{"title":"Construction of a molecular diagnostic system for neurogenic rosacea by combining transcriptome sequencing and machine learning","authors":"Rui Mao, Ji Li","doi":"10.1186/s12920-024-02008-0","DOIUrl":"https://doi.org/10.1186/s12920-024-02008-0","url":null,"abstract":"Patients with neurogenic rosacea (NR) frequently demonstrate pronounced neurological manifestations, often unresponsive to conventional therapeutic approaches. A molecular-level understanding and diagnosis of this patient cohort could significantly guide clinical interventions. In this study, we amalgamated our sequencing data (n = 46) with a publicly accessible database (n = 38) to perform an unsupervised cluster analysis of the integrated dataset. The eighty-four rosacea patients were partitioned into two distinct clusters. Neurovascular biomarkers were found to be elevated in cluster 1 compared to cluster 2. Pathways in cluster 1 were predominantly involved in neurotransmitter synthesis, transmission, and functionality, whereas cluster 2 pathways were centered on inflammation-related processes. Differential gene expression analysis and WGCNA were employed to delineate the characteristic gene sets of the two clusters. Subsequently, a diagnostic model was constructed from the identified gene sets using linear regression methodologies. The model's C index, comprising genes PNPLA3, CUX2, PLIN2, and HMGCR, achieved a remarkable value of 0.9683, with an area under the curve (AUC) for the training cohort's nomogram of 0.9376. Clinical characteristics from our dataset (n = 46) were assessed by three seasoned dermatologists, forming the NR validation cohort (NR, n = 18; non-neurogenic rosacea, n = 28). Upon application of our model to NR diagnosis, the model's AUC value reached 0.9023. Finally, potential therapeutic candidates for both patient groups were predicted via the Connectivity Map. In summation, this study unveiled two clusters with unique molecular phenotypes within rosacea, leading to the development of a precise diagnostic model instrumental in NR diagnosis.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182005","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":"Identification of autophagy-related genes as potential biomarkers correlated with immune infiltration in bipolar disorder: a bioinformatics analysis","authors":"Dong Cao, Yafang Liu, Jinghong Mei, Shuailong Yu, Cong Zeng, Jing Zhang, Yujuan Li","doi":"10.1186/s12920-024-02003-5","DOIUrl":"https://doi.org/10.1186/s12920-024-02003-5","url":null,"abstract":"Bipolar disorder (BPD) is a kind of manic and depressive phase alternate episodes of serious mental illness, and it is correlated with well-documented cortical brain abnormalities. Emerging evidence supports that autophagy dysfunction in neuronal system contributes to pathophysiological changes in neurological disease. However, the role of autophagy in bipolar disorder has rarely been elucidated. This study aimed to identify the autophagy-related gene as a potential biomarker Correlated to immune infiltration in BPD. The microarray dataset GSE23848 and autophagy-related genes (ARGs) were downloaded. Differentially expressed genes (DEGs) between normal and BPD samples were screened using the R software. Machine learning algorithms were performed to screen the significant candidate biomarker from autophagy-related differentially expressed genes (ARDEGs). The correlation between the screened ARDEGs and infiltrating immune cells was explored through correlation analysis. In this study, the autophagy pathway was abundantly enriched and activated in BPD, as indicated by Pathway enrichment analysis. We identified 16 ARDEGs in BPD compared to the normal group. A signature of 4 ARDEGs (ERN1, ATG3, CTSB, and EIF2AK3) was screened. ROC analysis showed that the above genes have good diagnostic performance. In addition, immune correlation analysis considered that the above four genes significantly correlated with immune cells in BPD. Autophagy - immune cell axis mediates pathophysiological changes in BPD. Four important ARDEGs are prospective to be potential biomarkers associated with immune infiltration in BPD and helpful for the prediction or diagnosis of BPD.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182007","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":"Whole exome sequencing analysis of 167 men with primary infertility","authors":"Haiyan Zhou, Zhaochu Yin, Bin Ni, Jiwu Lin, Shuwei Luo, Wanqin Xie","doi":"10.1186/s12920-024-02005-3","DOIUrl":"https://doi.org/10.1186/s12920-024-02005-3","url":null,"abstract":"Spermatogenic failure is one of the leading causes of male infertility and its genetic etiology has not yet been fully understood. The study screened a cohort of patients (n = 167) with primary male infertility in contrast to 210 normally fertile men using whole exome sequencing (WES). The expression analysis of the candidate genes based on public single cell sequencing data was performed using the R language Seurat package. No pathogenic copy number variations (CNVs) related to male infertility were identified using the the GATK-gCNV tool. Accordingly, variants of 17 known causative (five X-linked and twelve autosomal) genes, including ACTRT1, ADAD2, AR, BCORL1, CFAP47, CFAP54, DNAH17, DNAH6, DNAH7, DNAH8, DNAH9, FSIP2, MSH4, SLC9C1, TDRD9, TTC21A, and WNK3, were identified in 23 patients. Variants of 12 candidate (seven X-linked and five autosomal) genes were identified, among which CHTF18, DDB1, DNAH12, FANCB, GALNT3, OPHN1, SCML2, UPF3A, and ZMYM3 had altered fertility and semen characteristics in previously described knockout mouse models, whereas MAGEC1,RBMXL3, and ZNF185 were recurrently detected in patients with male factor infertility. The human testis single cell-sequencing database reveals that CHTF18, DDB1 and MAGEC1 are preferentially expressed in spermatogonial stem cells. DNAH12 and GALNT3 are found primarily in spermatocytes and early spermatids. UPF3A is present at a high level throughout spermatogenesis except in elongating spermatids. The testicular expression profiles of these candidate genes underlie their potential roles in spermatogenesis and the pathogenesis of male infertility. WES is an effective tool in the genetic diagnosis of primary male infertility. Our findings provide useful information on precise treatment, genetic counseling, and birth defect prevention for male factor infertility.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182111","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":"Transcriptomic analysis reveals key molecular signatures across recovery phases of hemorrhagic fever with renal syndrome","authors":"Yuanyuan Hu, Chao Wu, Tuohang Li, Yang Wu, Kun Yao, Mengtian Zhang, Pan Li, Xuzhao Bian","doi":"10.1186/s12920-024-02004-4","DOIUrl":"https://doi.org/10.1186/s12920-024-02004-4","url":null,"abstract":"Hemorrhagic fever with renal syndrome (HFRS), a life-threatening zoonosis caused by hantavirus, poses significant mortality risks and lacks specific treatments. This study aimed to delineate the transcriptomic alterations during the recovery phases of HFRS. RNA sequencing was employed to analyze the transcriptomic alterations in peripheral blood mononuclear cells from HFRS patients across the oliguric phase (OP), diuretic phase (DP), and convalescent phase (CP). Twelve differentially expressed genes (DEGs) were validated using quantitative real-time PCR in larger sample sets. Our analysis revealed pronounced transcriptomic differences between DP and OP, with 38 DEGs showing consistent expression changes across all three phases. Notably, immune checkpoint genes like CD83 and NR4A1 demonstrated a monotonic increase, in contrast to a monotonic decrease observed in antiviral and immunomodulatory genes, including IFI27 and RNASE2. Furthermore, this research elucidates a sustained attenuation of immune responses across three phases, alongside an upregulation of pathways related to tissue repair and regeneration. Our research reveals the transcriptomic shifts during the recovery phases of HFRS, illuminating key genes and pathways that may serve as biomarkers for disease progression and recovery.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182112","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":"Shared etiology of Mendelian and complex disease supports drug discovery","authors":"Panagiotis N. Lalagkas, Rachel D. Melamed","doi":"10.1186/s12920-024-01988-3","DOIUrl":"https://doi.org/10.1186/s12920-024-01988-3","url":null,"abstract":"Drugs targeting disease causal genes are more likely to succeed for that disease. However, complex disease causal genes are not always clear. In contrast, Mendelian disease causal genes are well-known and druggable. Here, we seek an approach to exploit the well characterized biology of Mendelian diseases for complex disease drug discovery, by exploiting evidence of pathogenic processes shared between monogenic and complex disease. One way to find shared disease etiology is clinical association: some Mendelian diseases are known to predispose patients to specific complex diseases (comorbidity). Previous studies link this comorbidity to pleiotropic effects of the Mendelian disease causal genes on the complex disease. In previous work studying incidence of 90 Mendelian and 65 complex diseases, we found 2,908 pairs of clinically associated (comorbid) diseases. Using this clinical signal, we can match each complex disease to a set of Mendelian disease causal genes. We hypothesize that the drugs targeting these genes are potential candidate drugs for the complex disease. We evaluate our candidate drugs using information of current drug indications or investigations. Our analysis shows that the candidate drugs are enriched among currently investigated or indicated drugs for the relevant complex diseases (odds ratio = 1.84, p = 5.98e-22). Additionally, the candidate drugs are more likely to be in advanced stages of the drug development pipeline. We also present an approach to prioritize Mendelian diseases with particular promise for drug repurposing. Finally, we find that the combination of comorbidity and genetic similarity for a Mendelian disease and cancer pair leads to recommendation of candidate drugs that are enriched for those investigated or indicated. Our findings suggest a novel way to take advantage of the rich knowledge about Mendelian disease biology to improve treatment of complex diseases.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182113","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":"Identifying inversions with breakpoints in the Dystrophin gene through long-read sequencing: report of two cases","authors":"Liqing Chen, Xiaoping Luo, Hongling Wang, Yu Tian, Yan Liu","doi":"10.1186/s12920-024-01997-2","DOIUrl":"https://doi.org/10.1186/s12920-024-01997-2","url":null,"abstract":"Duchenne Muscular Dystrophy (DMD) is an X-linked disorder caused by mutations in the DMD gene, with large deletions being the most common type of mutation. Inversions involving the DMD gene are a less frequent cause of the disorder, largely because they often evade detection by standard diagnostic methods such as multiplex ligation probe amplification (MLPA) and whole exome sequencing (WES). : Our research identified two intrachromosomal inversions involving the dystrophin gene in two unrelated families through Long-read sequencing (LRS). These variants were subsequently confirmed via Sanger sequencing. The first case involved a pericentric inversion extending from DMD intron 47 to Xq27.3. The second case featured a paracentric inversion between DMD intron 42 and Xp21.1, inherited from the mother. In both cases, simple repeat sequences (SRS) were present at the breakpoints of these inversions. Our findings demonstrate that LRS is an effective tool for detecting atypical mutations. The identification of SRS at the breakpoints in DMD patients enhances our understanding of the mechanisms underlying structural variations, thereby facilitating the exploration of potential treatments.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182114","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":"Dual diagnosis of achondroplasia and mandibulofacial dysostosis with microcephaly.","authors":"Ekaterina Lyulcheva-Bennett, Christopher Kershaw, Eleanor Baker, Stuart Gillies, Emma McCarthy, Jenny Higgs, Natalie Canham, Dawn Hennigan, Chris Parks, Daimark Bennett","doi":"10.1186/s12920-024-01999-0","DOIUrl":"10.1186/s12920-024-01999-0","url":null,"abstract":"<p><strong>Background: </strong>Achondroplasia and mandibulofacial dysostosis with microcephaly (MFDM) are rare monogenic, dominant disorders, caused by gain-of-function fibroblast growth factor receptor 3 (FGFR3) gene variants and loss-of-function elongation factor Tu GTP binding domain-containing 2 (EFTUD2) gene variants, respectively. The coexistence of two distinct Mendelian disorders in a single individual is uncommon and challenges the traditional paradigm of a single genetic disorder explaining a patient's symptoms, opening new avenues for diagnosis and management.</p><p><strong>Case presentation: </strong>We present a case of a female patient initially diagnosed with achondroplasia due to a maternally inherited pathogenic FGFR3 variant. She was referred to our genetic department due to her unusually small head circumference and short stature, which were both significantly below the expected range for achondroplasia. Additional features included distinctive facial characteristics, significant speech delay, conductive hearing loss, and epilepsy. Given the complexity of her phenotype, she was recruited to the DDD (Deciphering Developmental Disorders) study and the 100,000 Genomes project for further investigation. Subsequent identification of a complex EFTUD2 intragenic rearrangement confirmed an additional diagnosis of mandibulofacial dysostosis with microcephaly (MFDM).</p><p><strong>Conclusion: </strong>This report presents the first case of a dual molecular diagnosis of achondroplasia and mandibulofacial dysostosis with microcephaly in the same patient. This case underscores the complexity of genetic diagnoses and the potential for coexistence of multiple genetic syndromes in a single patient. This case expands our understanding of the molecular basis of dual Mendelian disorders and highlights the importance of considering the possibility of dual molecular diagnoses in patients with phenotypic features that are not fully accounted for by their primary diagnosis.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11378366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142145032","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":"Exploring novel MYH7 gene variants using in silico analyses in Korean patients with cardiomyopathy.","authors":"Oc-Hee Kim, Jihyun Kim, Youngjun Kim, Soyoung Lee, Beom Hee Lee, Bong-Jo Kim, Hyun-Young Park, Mi-Hyun Park","doi":"10.1186/s12920-024-02000-8","DOIUrl":"10.1186/s12920-024-02000-8","url":null,"abstract":"<p><strong>Background: </strong>Pathogenic variants of MYH7, which encodes the beta-myosin heavy chain protein, are major causes of dilated and hypertrophic cardiomyopathy.</p><p><strong>Methods: </strong>In this study, we used whole-genome sequencing data to identify MYH7 variants in 397 patients with various cardiomyopathy subtypes who were participating in the National Project of Bio Big Data pilot study in Korea. We also performed in silico analyses to predict the pathogenicity of the novel variants, comparing them to known pathogenic missense variants.</p><p><strong>Results: </strong>We identified 27 MYH7 variants in 41 unrelated patients with cardiomyopathy, consisting of 20 previously known pathogenic/likely pathogenic variants, 2 variants of uncertain significance, and 5 novel variants. Notably, the pathogenic variants predominantly clustered within the myosin motor domain of MYH7. We confirmed that the novel identified variants could be pathogenic, as indicated by high prediction scores in the in silico analyses, including SIFT, Mutation Assessor, PROVEAN, PolyPhen-2, CADD, REVEL, MetaLR, MetaRNN, and MetaSVM. Furthermore, we assessed their damaging effects on protein dynamics and stability using DynaMut2 and Missense3D tools.</p><p><strong>Conclusions: </strong>Overall, our study identified the distribution of MYH7 variants among patients with cardiomyopathy in Korea, offering new insights for improved diagnosis by enriching the data on the pathogenicity of novel variants using in silico tools and evaluating the function and structural stability of the MYH7 protein.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11378590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142139215","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":"A novel variant of biallelic MME gene associated with autosomal recessive late-onset distal hereditary motor neuropathy in Chinese families.","authors":"Bentuo Zhang, Qiang Gang, Lingchao Meng, Zhenyu Li, Xujun Chu, Haohao Wu, Junsu Yang, Baogang Huang, Kang Du","doi":"10.1186/s12920-024-01996-3","DOIUrl":"10.1186/s12920-024-01996-3","url":null,"abstract":"<p><p>Distal hereditary motor neuropathies (dHMN) are a group of heterogeneous diseases and previous studies have reported that the compound heterozygous recessive MME variants cause dHMN. Our study found a novel homozygous MME variant and a reported compound heterozygous MME variant in two Chinese families, respectively. Next-generation sequencing and nerve conduction studies were performed for two probands. The probands in two families presented with the muscle weakness and wasting of both lower limbs and carried a c.2122 A > T (p.K708*) and c.1342 C > T&c.2071_2072delinsTT (p.R448*&p.A691L) variant, respectively. Prominently axonal impairment of motor nerves and slight involvement of sensory nerves were observed in nerve conduction study. Our study reported a \"novel\" nonsense mutation and a missense variant of autosomal recessive late-onset dHMN and reviewed reported MME variants associated with dHMN phenotype.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373294/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142131730","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":"Prediction of metabolic syndrome using machine learning approaches based on genetic and nutritional factors: a 14-year prospective-based cohort study.","authors":"Dayeon Shin","doi":"10.1186/s12920-024-01998-1","DOIUrl":"10.1186/s12920-024-01998-1","url":null,"abstract":"<p><strong>Introduction: </strong>Metabolic syndrome is a chronic disease associated with multiple comorbidities. Over the last few years, machine learning techniques have been used to predict metabolic syndrome. However, studies incorporating demographic, clinical, laboratory, dietary, and genetic factors to predict the incidence of metabolic syndrome in Koreans are limited. In the present study, we propose a genome-wide polygenic risk score for the prediction of metabolic syndrome, along with other factors, to improve the prediction accuracy of metabolic syndrome.</p><p><strong>Methods: </strong>We developed 7 machine learning-based models and used Cox multivariable regression, deep neural network (DNN), support vector machine (SVM), stochastic gradient descent (SGD), random forest (RAF), Naïve Bayes (NBA) classifier, and AdaBoost (ADB) to predict the incidence of metabolic syndrome at year 14 using the dataset from the Korean Genome and Epidemiology Study (KoGES) Ansan and Ansung.</p><p><strong>Results: </strong>Of the 5440 patients, 2,120 were considered to have new-onset metabolic syndrome. The AUC values of model, which included sex, age, alcohol intake, energy intake, marital status, education status, income status, smoking status, dried laver intake, and genome-wide polygenic risk score (gPRS) Z-score based on 344,447 SNPs (p-value < 1.0), were the highest for RAF (0.994 [95% CI 0.985, 1.000]) and ADB (0.994 [95% CI 0.986, 1.000]).</p><p><strong>Conclusions: </strong>Incorporating both gPRS and demographic, clinical, laboratory, and seaweed data led to enhanced metabolic syndrome risk prediction by capturing the distinct etiologies of metabolic syndrome development. The RAF- and ADB-based models predicted metabolic syndrome more accurately than the NBA-based model for the Korean population.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373243/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142131731","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}