Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to purine metabolism-associated genes.

ABSTRACT: Sepsis, characterized as a systemic inflammatory response triggered by pathogen invasion, represents a continuum that may progress from mild systemic infection to severe sepsis, potentially culminating in septic shock and multiple organ dysfunction syndrome. A pivotal element in the pathogenesis and progression of sepsis involves the significant disruption of oncological metabolic networks, where cells within the pathological milieu exhibit metabolic functions that diverge from their healthy counterparts. Among these, purine metabolism plays a crucial role in nucleic acid synthesis. However, the contribution of Purine Metabolism Genes (PMGs) to the defense mechanisms against sepsis remains inadequately explored. Leveraging bioinformatics, this study aimed to identify and substantiate poten

SUBMITTER: Liang F 

PROVIDER: S-EPMC11696736 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature