Multiplex metal-detection based assay (MMDA) for COVID-19 diagnosis and identification of disease severity biomarkers

Author:

Zhou Ying1,Yuan Shuofeng234ORCID,To Kelvin Kai-Wang2345ORCID,Xu Xiaohan1,Li Hongyan1,Cai Jian-Piao23,Luo Cuiting2,Hung Ivan Fan-Ngai36ORCID,Chan Kwok-Hung234,Yuen Kwok-Yung23457ORCID,Li Yu-Feng89ORCID,Chan Jasper Fuk-Woo23457ORCID,Sun Hongzhe1ORCID

Affiliation:

1. Department of Chemistry, State Key Laboratory of Synthetic Chemistry, CAS-HKU Joint Laboratory of Metallomics on Health and Environment, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China

2. State Key Laboratory of Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China

3. Department of Clinical Microbiology, and Infection Control, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong Province, China

4. Centre for Virology, Vaccinology and Therapeutics, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China

5. Department of Microbiology, Queen Mary Hospital, Pokfulam, Hong Kong Special Administrative Region, China

6. Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China

7. Academician Workstation of Hainan Province, Hainan Medical University, Haikou, Hainan, China

8. CAS-HKU Joint Laboratory of Metallomics on Health and Environment, CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, Beijing Metallomics Facility, National Consortium for Excellence in Metallomics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China

9. University of Chinese Academy of Sciences, Beijing, China

Abstract

A MMDA platform is developed by using metal-tagged antibodies as reporting probes combined with machine learning algorithms, as a general strategy for highly multiplexed biofluid assay.

Funder

Innovation and Technology Commission

Sanming Project of Medicine in Shenzhen

University of Hong Kong

Health and Medical Research Fund

Research Grants Council, University Grants Committee

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

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