Deep Learning-Enhanced Hand-Driven Spatial Encoding Microfluidics for Multiplexed Molecular Testing at Home.

Journal: ACS nano
Published Date:

Abstract

The frequent global outbreaks of viral infectious diseases have significantly heightened the urgent demand for molecular testing at home. However, the labor-intensive sample preparation and nucleic acid amplification steps, along with the complexity and bulkiness of detection equipment, have limited the large-scale application of molecular testing at home. Here, we propose artificial intelligence-enhanced hand-driven microfluidic system (MACRO) based on RPA and CRISPR technologies for home diagnosis of multiple types of infectious diseases. Leveraging a multidimensional space hourglass structure design, precise spatiotemporal control of fluids can be achieved simply by flipping the chip. Through dual chemical reactions, the system eliminates the need for nucleic acid extraction and purification, simplifying sample preparation and obviating the reliance on heating equipment. The MACRO achieves attomolar sensitivity within 60 min from sample input to result, and 100% specificity for 27 HPV subtypes. Clinical validation using 140 cervical swab specimens demonstrated 98.57% accuracy with 100% specificity. Further, we validated MACRO through multiplex detection of three clinically critical respiratory pathogens (SARS-CoV-2, Influenza A, and Influenza B) in 70 samples, achieving 100% diagnostic concordance. To circumvent subjective errors and enable real-time data collection, we further developed a mobile health platform based on the YoLov8 image recognition algorithm to ensure rapid and precise result output. With the performance of cost-effectiveness ($1.34 per target), and independence from instrument support, MACRO provides a comprehensive solution for molecular testing at home, offering significant implications for enhancing early warning systems for major epidemics and improving public health emergency response capabilities.

Authors

  • Ying Zhang
    Department of Nephrology, Nanchong Central Hospital Affiliated to North Sichuan Medical College, Nanchong, China.
  • Dongjuan Chen
    Department of Laboratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430074, China.
  • Xin Tang
    School of Science, Huazhong Agricultural University, Wuhan, Hubei province, China.
  • Tao Xu
    Department of Urology, Peking University People's Hospital, Beijing, China.
  • Shunji Li
    The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
  • Xudong Zhao
  • Zeyu Miao
    The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
  • Yufei Zhang
    School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China.
  • Hu Zhou
    Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
  • Ying Li
    School of Information Engineering, Chang'an University, Xi'an 710010, China.
  • Yiwei Li
    New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China.
  • Peng Chen
  • Bi-Feng Liu
    The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics and Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.