LILRA5⁺ macrophages drive early oxidative stress surge in sepsis: a single-cell transcriptomic landscape with therapeutic implications.

ABSTRACT:

Background

In sepsis, oxidative stress (OS) triggers essential adaptive responses and emerging OS-related biomarkers show potential for enhancing sepsis diagnosis and therapy.

Methodology

In this study, we used single-cell datasets and the OS gene set to identify immune cell types with the highest oxidative activity across different sepsis states. Differential expression genes (DEG) between "high state" cells and "low state" cells were screened. High-dimensional weighted gene co-expression network analysis (hdWGCNA), combined with multiple machine learning methods, was used for the selection of hub genes. Expressions of hub genes were then validated. Cell-cell communication and transcription factor analysis were performed later. Real-time quantitative reverse transcription (

SUBMITTER: Xu P 

PROVIDER: S-EPMC12336265 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature