Omics A Journal of Integrative Biology最新文献

{"title":"Characterization of Lipid Alterations by Oncogenic <i>PIK3CA</i> Mutations Using Untargeted Lipidomics in Breast Cancer.","authors":"Jae Hun Jung, Da-Qing Yang, Hongming Song, Xiangyu Wang, Xinyan Wu, Kwang Pyo Kim, Akhilesh Pandey, Seul Kee Byeon","doi":"10.1089/omi.2023.0076","DOIUrl":"10.1089/omi.2023.0076","url":null,"abstract":"<p><p>Lipids play crucial biological roles in health and disease, including in cancers. The phosphatidylinositol 3-kinase (PI3K) signaling pathway is a pivotal promoter of cell growth and proliferation in various types of cancer. The somatic mutations in <i>PIK3CA</i>, the gene coding for the catalytic subunit p110α of PI3K, are frequently present in cancer cells, including breast cancer. Although the most prominent mutants, represented by single amino acid substitutions in the helical domain in exon 9 (E545K) and the kinase domain in exon 20 (H1047R) are known to cause a gain of PI3K function, activate AKT signaling and induce oncogenic transformation, the effect of these mutations on cellular lipid profiles has not been studied. We carried out untargeted lipidomics using liquid chromatography-tandem mass spectrometry to detect the lipid alterations in mammary gland epithelial MCF10A cells with isogenic knockin of these mutations. A total of 536 species of lipids were analyzed. We found that the levels of monosialogangliosides, signaling molecules known to enhance cell motility through PI3K/AKT pathway, were significantly higher in both mutants. In addition, triglycerides and ceramides, lipid molecules known to be involved in promoting lipid droplet production, cancer cell migration and invasion, were increased, whereas lysophosphatidylcholines and phosphatidylcholines that are known to inhibit cancer cell motility were decreased in both mutants. Our results provide novel insights into a potential link between altered lipid profile and carcinogenesis caused by the <i>PIK3CA</i> hotspot mutations. In addition, we suggest untargeted lipidomics offers prospects for precision/personalized medicine by unpacking new molecular substrates of cancer biology.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366275/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9864993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Versatility of Plectin in Cancer: A Pan-Cancer Analysis on Potential Diagnostic and Prognostic Impacts of Plectin Isoforms.","authors":"Hulya Gundesli,&nbsp;Medi Kori,&nbsp;Kazim Yalcin Arga","doi":"10.1089/omi.2023.0053","DOIUrl":"https://doi.org/10.1089/omi.2023.0053","url":null,"abstract":"<p><p>Plectin, encoded by <i>PLEC</i>, is a cytoskeletal and scaffold protein with a number of unique isoforms that act on various cellular functions such as cell adhesion, signal transduction, cancer cell invasion, and migration. While plectin has been shown to display high expression and mislocalization in tumor cells, our knowledge of the biological significance of plectin and its isoforms in tumorigenesis remain limited. In this study, we first performed pathway enrichment analysis to identify cancer hallmark proteins associated with plectin. Then, a pan-cancer analysis was performed using RNA-seq data collected from the Cancer Genome Atlas (TCGA) to detect the mRNA expression levels of <i>PLEC</i> and its transcript isoforms, and the prognostic as well as diagnostic significance of the transcript isoforms was evaluated considering cancer stages. We show here that several tissue specific <i>PLEC</i> isoforms are dysregulated in different cancer types and stages but not the expression of <i>PLEC</i>. Among them, <i>PLEC 1d</i> and <i>PLEC 1f</i> are potential biomarker candidates and call for further translational and personalized medicine research. This study makes a contribution as a stride to unravel the molecular mechanisms underpinning plectin isoforms in cancer development and progression by revealing the potent plectin isoforms in different stages of cancer as potential early cancer detection biomarkers. Importantly, uncovering how plectin isoforms guide malignancy and particular cancer types by comprehensive functional studies might open new avenues toward novel cancer therapeutics.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9661142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Transformation, Omics and Society: Industry 4.0 and Industry 5.0.","authors":"Vural Özdemir","doi":"10.1089/omi.2023.0067","DOIUrl":"10.1089/omi.2023.0067","url":null,"abstract":"","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9622106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging Pathogens in Planetary Health and Lessons from Comparative Genome Analyses of Three <i>Clostridia</i> Species.","authors":"Ankit Singh Tanwar,&nbsp;Padival Shruptha,&nbsp;Apoorva Jnana,&nbsp;Angela Brand,&nbsp;Mamatha Ballal,&nbsp;Kapaettu Satyamoorthy,&nbsp;Thokur Sreepathy Murali","doi":"10.1089/omi.2023.0034","DOIUrl":"https://doi.org/10.1089/omi.2023.0034","url":null,"abstract":"<p><p><i>Clostridioides difficile</i> (CD) is a major planetary health burden. A Gram-positive opportunistic pathogen, CD, colonizes the large intestine and is implicated in sepsis, pseudomembranous colitis, and colorectal cancer. <i>C. difficile</i> infection typically following antibiotic exposure results in dysbiosis of the gut microbiome, and is one of the leading causes of diarrhea in the elderly population. While several studies have focused on the toxigenic strains of CD, gut commensals such as <i>Clostridium butyricum</i> (CB) and <i>Clostridium tertium</i> (CT) could harbor toxin/virulence genes, and thus pose a threat to human health. In this study, we sequenced and characterized three isolates, namely, CT (MALS001), CB (MALS002), and CD (MALS003) for their antimicrobial, cytotoxic, antiproliferative, genomic, and proteomic profiles. Although <i>in vitro</i> cytotoxic and antiproliferative potential were observed predominantly in CD MALS003, genome analysis revealed pathogenic potential of CB MALS002 and CT MALS001. Pangenome analysis revealed the presence of several accessory genes typically involved in fitness, virulence, and resistance characteristics in the core genomes of sequenced strains. The presence of an array of virulence and antimicrobial resistance genes in CB MALS002 and CT MALS001 suggests their potential role as emerging pathogens with significant impact on planetary health.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9651581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breast Cancer Therapeutics and Hippo Signaling Pathway: Novel MicroRNA-Gene-Protein Interaction Networks.","authors":"Shradheya R R Gupta,&nbsp;Garima Nagar,&nbsp;Pooja Mittal,&nbsp;Shweta Rana,&nbsp;Harpreet Singh,&nbsp;Rajeev Singh,&nbsp;Archana Singh,&nbsp;Indrakant K Singh","doi":"10.1089/omi.2023.0047","DOIUrl":"https://doi.org/10.1089/omi.2023.0047","url":null,"abstract":"<p><p>The Hippo signaling pathway is a master regulator of development, cell proliferation, and apoptosis in particular, and it plays an important role in tissue regeneration, controlling organ size, and cancer suppression. Dysregulation of the Hippo signaling pathway has been implicated in breast cancer, a highly prevalent cancer affecting 1 out of every 15 women worldwide. While the Hippo signaling pathway inhibitors are available, they are suboptimal, for example, due to chemoresistance, mutation, and signal leakage. Inadequate knowledge about the Hippo pathway connections and their regulators limits our ability to uncover novel molecular targets for drug development. We report here novel microRNA (miRNA)-gene and protein-protein interaction networks in the Hippo signaling pathway. We employed the GSE miRNA dataset for the present study. The GSE57897 dataset was normalized and searched for differentially expressed miRNAs, and their targets were searched using the miRWalk2.0 tool. From the upregulated miRNAs, we observed that the <i>hsa-miR-205-5p</i> forms the biggest cluster and targets four genes involved in the Hippo signaling pathway. Interestingly, we found a novel connection between two Hippo signaling pathway proteins, <i>angiomotin (AMOT)</i> and <i>mothers against decapentaplegic homolog 4 (SMAD4).</i> From the downregulated miRNAs, <i>hsa-miR-16-5p</i>, <i>hsa-miR-7g-5p</i>, <i>hsa-miR-141-3p</i>, <i>hsa-miR-103a-3p</i>, <i>hsa-miR-21-5p</i>, and <i>hsa-miR-200c-3p</i>, target genes were present in the pathway. We found that <i>PTEN</i>, <i>EP300</i>, and <i>BTRC</i> were important cancer-inhibiting proteins, form hubs, and their genes interact with downregulating miRNAs. We suggest that targeting proteins from these newly unraveled networks in the Hippo signaling pathway and further research on the interaction of hub-forming cancer-inhibiting proteins can open up new avenues for next-generation breast cancer therapeutics.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10016909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gastric Cancer Biomarker Candidates Identified by Machine Learning and Integrative Bioinformatics: Toward Personalized Medicine.","authors":"Vigneshwar Suriya Prakash Sinnarasan,&nbsp;Dahrii Paul,&nbsp;Rajesh Das,&nbsp;Amouda Venkatesan","doi":"10.1089/omi.2023.0015","DOIUrl":"https://doi.org/10.1089/omi.2023.0015","url":null,"abstract":"<p><p>Gastric cancer (GC) is among the leading causes of cancer-related deaths worldwide. The discovery of robust diagnostic biomarkers for GC remains a challenge. This study sought to identify biomarker candidates for GC by integrating machine learning (ML) and bioinformatics approaches. Transcriptome profiles of patients with GC were analyzed to identify differentially expressed genes between the tumor and adjacent normal tissues. Subsequently, we constructed protein-protein interaction networks so as to find the significant hub genes. Along with the bioinformatics integration of ML methods such as support vector machine, the recursive feature elimination was used to select the most informative genes. The analysis unraveled 160 significant genes, with 88 upregulated and 72 downregulated, 10 hub genes, and 12 features from the variable selection method. The integrated analyses found that <i>EXO1</i>, <i>DTL</i>, <i>KIF14</i>, and <i>TRIP13</i> genes are significant and poised as potential diagnostic biomarkers in relation to GC. The receiver operating characteristic curve analysis found <i>KIF14</i> and <i>TRIP13</i> are strongly associated with diagnosis of GC. We suggest <i>KIF14</i> and <i>TRIP13</i> are considered as biomarker candidates that might potentially inform future research on diagnosis, prognosis, or therapeutic targets for GC. These findings collectively offer new future possibilities for precision/personalized medicine research and development for patients with GC.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9661124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gene Set Based Integrated Methylome and Transcriptome Analysis Reveals Potential Molecular Mechanisms Linking Cigarette Smoking and Related Diseases.","authors":"Pashupati P Mishra,&nbsp;Binisha H Mishra,&nbsp;Emma Raitoharju,&nbsp;Nina Mononen,&nbsp;Jorma Viikari,&nbsp;Markus Juonala,&nbsp;Nina Hutri-Kähönen,&nbsp;Mika Kähönen,&nbsp;Olli T Raitakari,&nbsp;Terho Lehtimäki","doi":"10.1089/omi.2023.0028","DOIUrl":"https://doi.org/10.1089/omi.2023.0028","url":null,"abstract":"<p><p>Advanced integrative analysis of DNA methylation and transcriptomics data may provide deeper insights into smoke-induced epigenetic alterations, their effects on gene expression and related biological processes, linking cigarette smoking and related diseases. We hypothesize that accumulation of DNA methylation changes in CpG sites across genomic locations of different genes might have biological significance. We tested the hypothesis by performing gene set based integrative analysis of blood DNA methylation and transcriptomics data to identify potential transcriptomic consequences of smoking via changes in DNA methylation in the Young Finns Study (YFS) participants (<i>n</i> = 1114, aged 34-49 years, women: 54%, men: 46%). First, we performed epigenome-wide association study (EWAS) of smoking. We then defined sets of genes based on DNA methylation status within their genomic regions, for example, sets of genes containing hyper- or hypomethylated CpG sites in their body or promoter regions. Gene set analysis was performed using transcriptomics data from the same participants. Two sets of genes, one containing 49 genes with hypomethylated CpG sites in their body region and the other containing 33 genes with hypomethylated CpG sites in their promoter region, were differentially expressed among the smokers. Genes in the two gene sets are involved in bone formation, metal ion transport, cell death, peptidyl-serine phosphorylation, and cerebral cortex development process, revealing epigenetic-transcriptomic pathways to smoking-related diseases such as osteoporosis, atherosclerosis, and cognitive impairment. These findings contribute to a deeper understanding of the pathophysiology of smoking-related diseases and may provide potential therapeutic targets.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10254975/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10015811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"miR-433 Inhibits Glioblastoma Progression by Suppressing the PI3K/Akt Signaling Pathway Through Direct Targeting of <i>ERBB4</i>.","authors":"Huawei Jiang,&nbsp;Zhiwei Su,&nbsp;Wangxiong Hu,&nbsp;Xianggui Yuan,&nbsp;Teng Yu,&nbsp;Jing Yang,&nbsp;Xibin Xiao,&nbsp;Shu Zheng,&nbsp;Biaoyang Lin","doi":"10.1089/omi.2023.0046","DOIUrl":"https://doi.org/10.1089/omi.2023.0046","url":null,"abstract":"<p><p>Glioblastoma multiforme (GBM) is a highly malignant brain tumor where new biomarkers and drug targets are much needed in the oncology clinic. miR-433 was identified as a tumor-suppressing miRNA in several different types of human cancer. However, the integrative biology of miR-433 in GBM is still largely unknown. By analyzing the expression profiles of miR-433 in 198 patients with glioma at The Cancer Genome Atlas, we found that the miR-433 expression was decreased in glioma whereas the low expression of miR-433 was significantly associated with shorter overall survival. We then conducted <i>in vitro</i> studies and demonstrated that increased expression of miR-433 suppressed the proliferation, migration, and invasion of LN229 and T98G cells, two representative glioma cell lines. Further, using <i>in vivo</i> mouse model, we found that upregulation of miR-433 inhibited the tumor growth of glioma cells. To situate the integrative biology understanding of the action of miR-433 in glioma, we identified <i>ERBB4</i> as a gene targeted directly by miR-433 in LN229 and T98G cells. Overexpressed <i>ERBB4</i> rescued the phenotype caused by overexpression of miR-433. Finally, we showed that miR-433 suppressed the PI3K/Akt pathway in glioma cells. In conclusion, our study demonstrated that miR-433 could potentially act as a tumor suppressor for GBM and may serve as a potential therapeutic target for GBM. Further integrative biology and clinical translational research are warranted to evaluate miR-433 in GBM.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9659798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breast Cancer Prognostic Hub Genes Identified by Integrated Transcriptomic and Weighted Network Analysis: A Road Toward Personalized Medicine.","authors":"Prithvi Singh,&nbsp;Aanchal Rathi,&nbsp;Rashmi Minocha,&nbsp;Anuradha Sinha,&nbsp;Mohammad Mahfuzul Haque,&nbsp;Md Imtaiyaz Hassan,&nbsp;Ravins Dohare","doi":"10.1089/omi.2023.0033","DOIUrl":"https://doi.org/10.1089/omi.2023.0033","url":null,"abstract":"<p><p>Breast cancer (BC) is the second-most common type and among the leading causes of worldwide cancer-related deaths. There is marked person-to-person variability in susceptibility to, and phenotypic expression and prognosis of BC, a predicament that calls for personalized medicine and individually tailored therapeutics. In this study, we report new observations on prognostic hub genes and key pathways involved in BC. We used the data set GSE109169, comprising 25 pairs of BC and adjacent normal tissues. Using a high-throughput transcriptomic approach, we selected data on 293 differentially expressed genes to establish a weighted gene coexpression network. We identified three age-linked modules where the light-gray module strongly correlated with BC. Based on the gene significance and module membership features, peptidase inhibitor 15 (<i>PI15</i>) and <i>KRT5</i> were identified as our hub genes from the light-gray module. These genes were further verified at transcriptional and translational levels across 25 pairs of BC and adjacent normal tissues. Their promoter methylation profiles were assessed based on various clinical parameters. In addition, these hub genes were used for Kaplan-Meier survival analysis, and their correlation with tumor-infiltrating immune cells was investigated. We found that PI15 and KRT5 may be potential biomarkers and potential drug targets. These findings call for future research in a larger sample size, which could inform diagnosis and clinical management of BC, thus paving the way toward personalized medicine.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9659778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Common Dysregulated Genes in COVID-19 and Hypersensitivity Pneumonitis: A Systems Biology and Machine Learning Approach.","authors":"Sanjukta Dasgupta,&nbsp;Sankha Subhra Das,&nbsp;Sankalp Patidar,&nbsp;Vaibhav Kajaria,&nbsp;Sushmita Roy Chowdhury,&nbsp;Koel Chaudhury","doi":"10.1089/omi.2022.0171","DOIUrl":"https://doi.org/10.1089/omi.2022.0171","url":null,"abstract":"<p><p>A comprehensive knowledge on systems biology of severe acute respiratory syndrome coronavirus 2 is crucial for differential diagnosis of COVID-19. Interestingly, the radiological and pathological features of COVID-19 mimic that of hypersensitivity pneumonitis (HP), another pulmonary fibrotic phenotype. This motivated us to explore the overlapping pathophysiology of COVID-19 and HP, if any, and using a systems biology approach. Two datasets were obtained from the Gene Expression Omnibus database (GSE147507 and GSE150910) and common differentially expressed genes (DEGs) for both diseases identified. Fourteen common DEGs, significantly altered in both diseases, were found to be implicated in complement activation and growth factor activity. A total of five microRNAs (hsa-miR-1-3p, hsa-miR-20a-5p, hsa-miR-107, hsa-miR-16-5p, and hsa-miR-34b-5p) and five transcription factors (KLF6, ZBTB7A, ELF1, NFIL3, and ZBT33) exhibited highest interaction with these common genes. Next, <i>C3</i>, <i>CFB</i>, <i>MMP-9</i>, and <i>IL1A</i> were identified as common hub genes for both COVID-19 and HP. Finally, these top-ranked genes (hub genes) were evaluated using random forest classifier to discriminate between the disease and control group (coronavirus disease 2019 [COVID-19] vs. controls, and HP vs. controls). This supervised machine learning approach demonstrated 100% and 87.6% accuracy in differentiating COVID-19 from controls, and HP from controls, respectively. These findings provide new molecular leads that inform COVID-19 and HP diagnostics and therapeutics research and innovation.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9663661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}