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June 3, 2026Renal Failure0 citationsOpen Access

Combining bioinformatics and machine learning to analyze and validate sepsis-related cell senescence genes and potential drugs

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SPShuaijie PeiDLD Y LiXYXiaoli Yu

Key Points

  • This study aims to analyze sepsis-related cell senescence genes and evaluate potential drug interventions.
  • Utilized bioinformatics and machine learning to identify genes.
  • Validating diagnostic efficacy of eight differentially expressed senescence-related genes (DE-SRGs).
  • Examined the effects of fenofibrate on inflammation and senescence in sepsis-induced acute kidney injury models.
  • Identified eight DE-SRGs associated with sepsis.
  • Fenofibrate demonstrated anti-inflammatory and anti-senescence effects in acute kidney injury models.
  • Validated the diagnostic utility of the identified senescence genes.

Abstract

models of sepsis-induced acute kidney injury (AKI), fenofibrate has been observed to alleviate senescence and inflammation. In conclusion, the present study identified eight DE-SRGs associated with sepsis and validated their diagnostic efficacy. And, fenofibrate might exert anti-inflammatory and anti-senescence effects in sepsis-induced AKI by regulating senescence genes, shedding fresh light on sepsis treatment.

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Cite This Study

Pei et al. (2026) studied this question.

synapsesocial.com/papers/6a1fc40fdee9eb8c0dce5991https://doi.org/10.1080/0886022x.2026.2667584
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1PPARα agonist administration worsens survival and kidney function in a mouse polymicrobial sepsis model2026
  2. 2Unlocking the potential of senescence-related gene signature as a diagnostic and prognostic biomarker in sepsis: insights from meta-analyses, single-cell RNA sequencing, and in vitro experiments2024 · 3 citations
  3. 3Fenofibrate Mitigates Acute Lung Injury in a Rat Model of Feces-Induced Peritonitis2026
  4. 4Identification of senescence-related genes in diagnosing idiopathic pulmonary fibrosis via integrating bioinformatics analysis and machine learning2026
  5. 5Molecular mechanisms of lipid metabolism abnormalities driving sepsis and atrial fibrillation: A Systematic study based on bioinformatics and machine learning2025