Integrating Multi-Omics Data Using Machine Learning to Explore New Therapeutic Targets for Acute Kidney Injury.

ABSTRACT: Renal ischemia-reperfusion (I/R) injury is an unavoidable complication associated with renal transplantation, and currently, there are no targeted therapeutic interventions. The objective of this study was to explore the molecular mechanisms that contribute to I/R-induced acute kidney injury (I/R-AKI) and to discover potential targets for effective renal safeguarding. Bioinformatics techniques were employed to analyse critical genes regulating I/R-AKI at the single-cell level and to develop diagnostic models. Additionally, key pharmacological agents that inhibit the expression of target genes were identified for subsequent experimental validation. Pathological changes in the kidneys of I/R mice and patients with AKI were observed using immunofluorescence, western blotting, immunohistochemi

SUBMITTER: Gong Q 

PROVIDER: S-EPMC12385122 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature