Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Liver Diseases and Con ditions - Non-Alcoholic Fatty Liver Diseaseis the subject of a report. Accordin g to news originating from Zhejiang, People’s Republic of China, byNewsRx corre spondents, research stated, “Concrete epidemiological evidence has suggested the mutuallycontributingeffect respectively between nonalcoholic fatty liver dise ase (NAFLD), type 2 diabetes mellitus(T2DM), and periodontitis (PD); however, t heir shared crosstalk mechanism remains an open issue. TheNAFLD, PD, and T2DM-r elated datasets were obtained from the NCBI GEO repository.”Our news journalists obtained a quote from the research from Zhejiang University , “Their commondifferentially expressed genes (DEGs) were identified and the fu nctional enrichment analysis performed bythe DAVID platform determined relevant biological processes and pathways. Then, the STRING databaseestablished a PPI network of such DEGs and topological analysis through Cytoscape 3.7.1 software along with the machine-learning analysis by the least absolute shrinkage and sele ction operator (LASSO)algorithm screened out hub characteristic genes. Their ef ficacy was validated by external datasets using thereceiver operating character istic (ROC) curve, and gene expression and location of the most robust one wasd etermined using single-cell sequencing and immunohistochemical staining. Finally , the promising drugswere predicted through the CTD database, and the CB-DOCK 2 and Pymol platform mimicked moleculardocking. Intersection of differentially e xpressed genes from three datasets identified 25 shared DEGs ofthe three diseas es, which were enriched in MHC II-mediated antigen presenting process. PPI netwo rkand LASSO machine-learning analysis determined 4 feature genes, of which the MS4A6A gene mainlyexpressed by macrophages was the hub gene and key immune cell type. Molecular docking simulationchosen fenretinide as the most promising med icant for MS4A6A macrophages.”
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