Identification and validation of a pyroptosis-related signature in identifying active tuberculosis via a deep learning algorithm.

Journal: Frontiers in cellular and infection microbiology
PMID: 38029270

Abstract

INTRODUCTION: Active tuberculosis (ATB), instigated by Mycobacterium tuberculosis (M.tb), rises as a primary instigator of morbidity and mortality within the realm of infectious illnesses. A significant portion of M.tb infections maintain an asymptomatic nature, recognizably termed as latent tuberculosis infections (LTBI). The complexities inherent to its diagnosis significantly hamper the initiatives aimed at its control and eventual eradication.

Authors

  • Yuchen Liu
    Department of Internal Medicine, Peking Union Medical College Hospital, Beijing, China.
  • Lifan Zhang
    Division of Infectious Diseases, Department of Internal Medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Fengying Wu
    Division of Infectious Diseases, Department of Internal Medicine, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Ye Liu
    Department of Cell Biology, Van Andel Research Institute, 333 Bostwick Ave NE, Grand Rapids, MI, 49503, USA.
  • Yuanchun Li
    Department of Control Science and Engineering, Jilin University, Changchun, Jilin, China; Department of Control Engineering, Changchun University of Technology, Changchun, Jilin, China.
  • Yan Chen
    Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.

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