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author:

Dong, Hui (Dong, Hui.) [1] | Mo, Jin (Mo, Jin.) [2] | Yu, Yongjian (Yu, Yongjian.) [3] | Xie, Wantao (Xie, Wantao.) [4] | Zheng, Jianping (Zheng, Jianping.) [5] | Jia, Chao (Jia, Chao.) [6]

Indexed by:

EI

Abstract:

Introduction: Regular and rapid large-scale screening for pathogens is crucial for controlling pandemics like Coronavirus Disease 2019 (COVID-19). In this study, we present the development of a digital point-of-care testing (POCT) system utilizing microfluidic paper-based analytical devices (μPADs) for the detection of SARS-CoV-2 gene fragments. The system incorporates temperature tuning and fluorescent detection components, along with intelligent and autonomous image acquisition and self-recognition programs. Methods: The developed POCT system is based on the nucleic acid amplification test (NAAT), a well-established molecular biology technique for detecting and amplifying nucleic acids. We successfully detected artificially synthesized SARS-CoV-2 gene fragments, namely ORF1ab gene, N gene, and E gene, with minimal reagent consumption of only 2.2μL per readout, representing a mere 11% of the requirements of conventional in-tube methods. The power dissipation of the system was low, at 6.4W. Results: Our testing results demonstrated that the proposed approach achieved a limit of detection of 1000 copies/mL, which is equivalent to detecting 1 copy or a single RNA template per reaction. By employing standard curve analysis, the quantity of the target templates can be accurately determined. Conclusion: The developed digital POCT system shows great promise for rapid and reliable detection of SARS-CoV-2 gene fragments, offering a cost-effective and efficient solution for controlling pandemics. Its compatibility with other diagnostic techniques and low reagent consumption make it a viable option to enhance healthcare in resource-limited areas. Copyright © 2023 Dong, Mo, Yu, Xie, Zheng and Jia.

Keyword:

Analytic equipment Biomolecules Coronavirus Cost effectiveness Diagnosis Digital devices Digital microfluidics Diseases Genes Image processing

Community:

  • [ 1 ] [Dong, Hui]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 2 ] [Dong, Hui]Fujian Provincial Collaborative Innovation Center of High-End Equipment Manufacturing, Fuzhou, China
  • [ 3 ] [Mo, Jin]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 4 ] [Mo, Jin]Fujian Provincial Collaborative Innovation Center of High-End Equipment Manufacturing, Fuzhou, China
  • [ 5 ] [Yu, Yongjian]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 6 ] [Yu, Yongjian]Fujian Provincial Collaborative Innovation Center of High-End Equipment Manufacturing, Fuzhou, China
  • [ 7 ] [Xie, Wantao]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 8 ] [Xie, Wantao]Fujian Provincial Collaborative Innovation Center of High-End Equipment Manufacturing, Fuzhou, China
  • [ 9 ] [Zheng, Jianping]Fujian Provincial Hospital, Fujian, Fuzhou, China
  • [ 10 ] [Jia, Chao]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 11 ] [Jia, Chao]Fujian Provincial Collaborative Innovation Center of High-End Equipment Manufacturing, Fuzhou, China

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Source :

Frontiers in Bioengineering and Biotechnology

Year: 2023

Volume: 11

4 . 3

JCR@2023

4 . 3 0 0

JCR@2023

ESI HC Threshold:42

JCR Journal Grade:1

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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