ArticleDisease markers2023
Identification of Inflammatory Gene in the Congenital Heart Surgery Patients following Cardiopulmonary Bypass via the Way of WGCNA and Machine Learning Algorithms.
Article in Disease markers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Corrections and comments
- Retracted
Authors and funding
2 authors.
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Abstract
Performing cardiopulmonary bypass (CPB) to reduce ischemic injury during surgery is a common approach to cardiac surgery. However, this procedure can lead to systemic inflammation and multiorgan dysfunction. Therefore, elucidating the molecular mechanisms of CPB-induced inflammatory cytokine release is essential as a critical first step in identifying new targets for therapeutic intervention. The GSE143780 dataset which is mRNA sequencing from total circulating leukocytes of the neonatorum was downloaded from the Gene Expression Omnibus (GEO) database. A total of 21 key module genes were obtained by analyzing the intersection of differentially expressed gene (DEG) and gene coexpression network analysis (WGCNA), and then, 4 genes (TRAF3IP2-AS1, PPARGC1B, CD4, and PDLIM5) were further confirmed after the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) screening and were used as hub genes for CPB-induced inflammatory cytokine release in patients with congenital heart defects. The enrichment analysis revealed 21 key module genes mainly related to the functions of developmental cell growth, regulation of monocyte differentiation, regulation of myeloid leukocyte differentiation, ERK1 and ERK2 cascade, volume-sensitive anion channel activity, and estrogen receptor binding. The result of gene set enrichment analysis (GSEA) showed that the hub genes were related to different physiological functions of cells. The ceRNA network established for hub genes includes 3 hub genes (PPARGC1B, CD4, and PDLIM5), 55 lncRNAs, and 34 miRNAs. In addition, 4 hub genes have 215 potential therapeutic agents. Finally, expression validation of the four hub genes revealed that they were all significantly low expressed in the surgical samples than before.
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