Identification and validation of NETs-related biomarkers in active tuberculosis through bioinformatics analysis and machine learning algorithms

Identification and validation of NETs-related biomarkers in active tuberculosis through bioinformatics analysis and machine learning algorithms

IntroductionDiagnostic delays in tuberculosis (TB) threaten global control efforts, necessitating early detection of active TB (ATB). This study explores neutrophil extracellular traps (NETs) as key mediators of TB immunopathology to identify NETs-related biomarkers for differentiating ATB from late...

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Bibliographic Details
Main Authors: Shengfang Xia, Qi An, Rui Lin, Yalan Tu, Zhu Chen, Dongmei Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Immunology
Subjects:
active tuberculosis (ATB)
latent tuberculosis infection (LTBI)
diagnosis
neutrophil extracellular traps (NETs)
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2025.1599667/full
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https://www.frontiersin.org/articles/10.3389/fimmu.2025.1599667/full

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