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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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