Aptamer-functionalized graphene quantum dots combined with artificial intelligence detect bacteria for urinary tract infections.

Journal: Frontiers in cellular and infection microbiology
PMID: 40308970

Abstract

OBJECTIVES: Urinary tract infection is one of the most prevalent forms of bacterial infection, and prompt and efficient identification of pathogenic bacteria plays a pivotal role in the management of urinary tract infections. In this study, we propose a novel approach utilizing aptamer-functionalized graphene quantum dots integrated with an artificial intelligence detection system (AG-AI detection system) for rapid and highly sensitive detection of ().

Authors

  • Kun Li
    State Key Laboratory of Veterinary Etiological Biology National Foot-and-Mouth Disease Reference Laboratory Lanzhou Veterinary Research Institute Chinese Academy of Agricultural Sciences, Lanzhou, Gansu, China.
  • Shiqiang Fang
    Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Tangwei Wu
    Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Chao Zheng
    School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong 510515 People's Republic of China.
  • Yi Zeng
    Department of Geriatrics, Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, China.
  • Jinrong He
    Cancer Research Institute of Wuhan, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yingmiao Zhang
    Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Zhongxin Lu
    Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

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