Artificial Intelligence-Assisted Digital Immunoassay Based on a Programmable-Particle-Decoding Technique for Multitarget Ultrasensitive Detection.

Journal: Analytical chemistry
PMID:

Abstract

The development of a multitarget ultrasensitive immunoassay is significant to fields such as medical research, clinical diagnosis, and food safety inspection. In this study, an artificial intelligence (AI)-assisted programmable-particle-decoding technique (APT)-based digital immunoassay system was developed to perform multitarget ultrasensitive detection. Multitarget was encoded by programmable polystyrene (PS) microspheres with different characteristics (particle size and number), and subsequent visible signals were recorded under an optical microscope after the immune reaction. The resultant images were further analyzed using a customized, AI-based computer vision technique to decode the intrinsic properties of polystyrene microspheres and to reveal the types and concentrations of targets. Our strategy has successfully detected multiple inflammatory markers in clinical serum and antibiotics with a broad detection range from pg/mL to μg/mL without extra signal amplification and conversion. An AI-based digital immunoassay system exhibits great potential to be used for the next generation of multitarget detection in disease screening for candidate patients.

Authors

  • Yang Zhou
    State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou, China.
  • Weiqi Zhao
    College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
  • Yaoze Feng
    College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
  • Xiaohu Niu
    College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
  • Yongzhen Dong
    College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
  • Yiping Chen
    Beijing Engineering Research Center for BioNanotechnology & CAS Key Laboratory for Biological Effects of Nanomaterials and Nanosafety, National Center for Nanoscience and Technology, Beijing 100190, PR China. Electronic address: chenyp@nanoctr.cn.