{
"id": "https://doi.org/10.6084/m9.figshare.14338827.v1",
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"url": "https://tandf.figshare.com/articles/journal_contribution/Weighted_gene_co-expression_network_analysis_WGCNA_to_explore_genes_responsive_to_i_Streptococcus_oralis_i_biofilm_and_immune_infiltration_analysis_in_human_gingival_fibroblasts_cells/14338827/1",
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"creators": [
{
"name": "Chen, Xia",
"givenName": "Xia",
"familyName": "Chen"
},
{
"name": "Ma, Jianfeng",
"givenName": "Jianfeng",
"familyName": "Ma"
}
],
"titles": [
{
"title": "Weighted gene co-expression network analysis (WGCNA) to explore genes responsive to Streptococcus oralis biofilm and immune infiltration analysis in human gingival fibroblasts cells"
}
],
"publisher": {
"name": "Taylor & Francis"
},
"container": {},
"subjects": [
{
"subject": "Medicine"
},
{
"subject": "Microbiology"
},
{
"subject": "FOS: Biological sciences",
"schemeUri": "http://www.oecd.org/science/inno/38235147.pdf",
"subjectScheme": "Fields of Science and Technology (FOS)"
},
{
"subject": "Cell Biology"
},
{
"subject": "Genetics"
},
{
"subject": "Molecular Biology"
},
{
"subject": "Immunology"
},
{
"subject": "FOS: Clinical medicine",
"schemeUri": "http://www.oecd.org/science/inno/38235147.pdf",
"subjectScheme": "Fields of Science and Technology (FOS)"
},
{
"subject": "Biological Sciences not elsewhere classified"
},
{
"subject": "Developmental Biology"
},
{
"subject": "Mental Health"
},
{
"subject": "Infectious Diseases"
},
{
"subject": "FOS: Health sciences",
"schemeUri": "http://www.oecd.org/science/inno/38235147.pdf",
"subjectScheme": "Fields of Science and Technology (FOS)"
},
{
"subject": "Computational Biology"
}
],
"contributors": [],
"dates": [
{
"date": "2021-03-30",
"dateType": "Created"
},
{
"date": "2024-02-13",
"dateType": "Updated"
},
{
"date": "2021",
"dateType": "Issued"
}
],
"publicationYear": 2021,
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"34935 Bytes"
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{
"rights": "Creative Commons Attribution 4.0 International",
"rightsUri": "https://creativecommons.org/licenses/by/4.0/legalcode",
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"descriptions": [
{
"description": "The correlation between oral bacteria and dental implants failure has been reported. However, the effect and mechanism of bacteria during dental implants is unclear. In this study, we explored key genes and candidate gene clusters in human gingival fibroblasts (HGF) cells in response to Streptococcus oralis biofilm through weighted gene co-expression network analysis (WGCNA) and differential genes analysis using gene expression matrix, GSE134481, downloaded from the Gene Expression Omnibus (GEO) database. We obtained 325 genes in the module significantly associated with S. oralis infection and 113 differentially expressed genes (DEGs) in the S. oralis biofilm; 62 DEGs indicated significant correlation with S. oralis injury. Multiple immune pathways, such as the tumor necrosis factor (TNF) signaling pathway, were considerably enriched. We obtained a candidate genes cluster containing 12 genes – IL6, JUN, FOS, CSF2, HBEGF, EDN1, CCL2, MYC, NGF, SOCS3, CXCL1, and CXCL2; we observed 5 candidate hub genes associated with S. oralis infection – JUN, IL6, FOS, MYC, and CCL2. The fraction of macrophage M0 cells was significantly increased in biofilm treatment compared with control; expression of FOS and MYC was significantly positively correlated with macrophage M0 cells. Our findings present a fierce inflammation changes in the transcript level of HGF in response to S. oralis.",
"descriptionType": "Abstract"
}
],
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