首页|Affiliated Hospital of Kunming University of Science and Technology Reports Find ings in Bioinformatics (Mitophagy related diagnostic biomarkers for coronary in- stent restenosis identified using machine learning and bioinformatics)
Affiliated Hospital of Kunming University of Science and Technology Reports Find ings in Bioinformatics (Mitophagy related diagnostic biomarkers for coronary in- stent restenosis identified using machine learning and bioinformatics)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Biotechnology - Bioinf ormatics is the subject of a report. According to news originating from Yunnan, People's Republic of China, by NewsRx correspondents, research stated, "Percutan eous coronary intervention (PCI) combined with stent implantation is currently o ne of the most effective treatments for coronary artery disease (CAD). However, in-stent restenosis (ISR) significantly compromises its long-term efficacy." Our news journalists obtained a quote from the research from the Affiliated Hosp ital of Kunming University of Science and Technology, "Mitophagy plays a crucial role in vascular homeostasis, yet its role in ISR remains unclear. This study a ims to identify mitophagy-related biomarkers for ISR and explore their underlyin g molecular mechanisms. Through differential gene expression analysis between IS R and Control samples in the combined dataset, 169 differentially expressed gene s (DEGs) were identified. Twenty-three differentially expressed mitophagy-relate d genes (DEMRGs) were identified by intersecting with mitophagyrelated genes (M RGs) from the GeneCards, and functional enrichment analysis indicated their sign ificant involvement in mitophagy-related biological processes. Using Weighted Ge ne Co-expression Network Analysis (WGCNA) and three machine learning algorithms (Logistic-LASSO, RF, and SVM-RFE), LRRK2, and ANKRD13A were identified as mitoph agy-related biomarkers for ISR. The nomogram based on these two genes also exhib ited promising diagnostic performance for ISR. Gene Set Enrichment Analysis (GSE A) as well as immune infiltration analyses showed that these two genes were clos ely associated with immune and inflammatory responses in ISR. Furthermore, poten tial small molecule compounds with therapeutic implications for ISR were predict ed using the connectivity Map (cMAP) database."
YunnanPeople's Republic of ChinaAsiaBioinformaticsBiomarkersBiotechnologyCardiologyCardiovascularCyborgsDiagnostics and ScreeningEmerging TechnologiesGeneticsHealth and Medicin eInformation TechnologyMachine LearningRestenosis
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