Objective This study aim to investigate the potential targets involving the effect of ginsenoside on osteoporosis using a network pharmacology approach. Methods Ginsenoside and its drug targets associated to osteoporosis (OP) were identified by using network analysis. First, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), DrugBank database, Pharmmapper database and Cytoscape software were used to mine information relevant to Ginsenoside ingredients and Ginsenoside -related targets. Second, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of ginsenoside-target gene and ginsenoside-OP target gene were performed in String, Phenopedia, DisGeNET database and Metascape software. Eventually, the protein to protein interaction (PPI) of key ginsenoside-OP targets were created by String database and Cytoscape software. The validation of the binding of ginsenoside to target proteins was plotted by utilizing SwissDock tool, UCSF Chimera and Pymol software. Results A total of 8 important active ingredients of ginsenosides were obtained in the TCMSP. Eighty potential targets of ginsenoside and 1304 related targets involved in OP were subjected to network analysis, and the 17 intersection targets were indicated to be linked to ginsenoside treating OP. GO and KEGG analysis showed the top 10 items of biological processes, cellular components, molecular functions and signaling pathways in the 80 targets of ginsenoside. Then, 14 key targets were determined to be the most crucial genes by protein to protein interaction (PPI) analysis. In the 14 intersection potential targets, 10 signaling pathways were defined by Metascape software. Validation plots of four target proteins IL1B, TNF, IFNG, NFKBIA binding to ginsenoside rh2 was drew, lastly. Conclusion This study investigated the potential targets and signaling pathways of ginsenoside during the treatment of OP, which might be beneficial to elucidate the mechanism concerned to the action of ginsenoside and might supply a better understanding of its anti-OP effects.

Heart failure (HF) is the final stage of many cardiovascular illnesses and the leading cause of death worldwide. At the same time, ischemic cardiomyopathy has replaced valvular heart disease and hypertension as the primary causes of heart failure. Cellular senescence in heart failure is currently receiving more attention. In this paper, we investigated the correlation between the immunological properties of myocardial tissue and the pathological mechanisms of cellular senescence during ischemic cardiomyopathy leading to heart failure (ICM-HF) using bioinformatics and machine learning methodologies. Our goals were to clarify the pathogenic causes of heart failure and find new treatment options. First, after obtaining GSE5406 from the Gene Expression Omnibus (GEO) database and doing limma analysis, differential genes (DEGs) among the ICM-HF and control groups were identified. We intersected these differential genes with cellular senescence-associated genes (CSAG) via the CellAge database to obtain 39 cellular senescence-associated DEGs (CSA-DEGs). Then, a functional enrichment analysis was performed to elucidate the precise biological processes by which the hub genes control cellular senescence and immunological pathways. Then, the respective key genes were identified by Random Forest (RF) method, LASSO (Least Absolute Shrinkage and Selection Operator) algorithms, and Cytoscape’s MCODE plug-in. Three sets of key genes were taken to intersect to obtain three CSA-signature genes (including MYC, MAP2K1, and STAT3), and these three CSA-signature genes were validated in the test gene set (GSE57345), and Nomogram analysis was done. In addition, we assessed the relationship between these three CSA- signature genes and the immunological landscape of heart failure encompassing immunological infiltration expression profiles. This work implies that cellular senescence may have a crucial role in the pathogenesis of ICM-HF, which may be closely tied to its effect on the immune microenvironment. Exploring the molecular underpinnings of cellular senescence during ICM-HF is anticipated to yield significant advances in the disease’s diagnosis and therapy.