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5G-enabled ultra-sensitive fluorescence sensor for proactive prognosis of COVID-19.
Guo, Jiuchuan; Chen, Shuqin; Tian, Shulin; Liu, Ke; Ni, Jian; Zhao, Ming; Kang, Yuejun; Ma, Xing; Guo, Jinhong.
  • Guo J; School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China.
  • Chen S; School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, PR China.
  • Tian S; School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China.
  • Liu K; School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China.
  • Ni J; State Key Lab of Advanced Welding and Joining, Harbin Insititude of Technology (Shenzhen), Shenzhen, 518055, PR China.
  • Zhao M; State Key Lab of Advanced Welding and Joining, Harbin Insititude of Technology (Shenzhen), Shenzhen, 518055, PR China.
  • Kang Y; School of Materials and Energy, Southwest University, Chongqing, 400715, PR China.
  • Ma X; School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, PR China; Shenzhen Bay Laboratory, No.9 Duxue Road, Shenzhen, 518055, PR China. Electronic address: maxing@hit.edu.cn.
  • Guo J; School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China. Electronic address: guojinhong@uestc.edu.cn.
Biosens Bioelectron ; 181: 113160, 2021 Jun 01.
Article in English | MEDLINE | ID: covidwho-1128905
ABSTRACT
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading around the globe since December 2019. There is an urgent need to develop sensitive and online methods for on-site diagnosing and monitoring of suspected COVID-19 patients. With the huge development of Internet of Things (IoT), the impact of Internet of Medical Things (IoMT) provides an impressive solution to this problem. In this paper, we proposed a 5G-enabled fluorescence sensor for quantitative detection of spike protein and nucleocapsid protein of SARS-CoV-2 by using mesoporous silica encapsulated up-conversion nanoparticles (UCNPs@mSiO2) labeled lateral flow immunoassay (LFIA). The sensor can detect spike protein (SP) with a detection of limit (LOD) 1.6 ng/mL and nucleocapsid protein (NP) with an LOD of 2.2 ng/mL. The feasibility of the sensor in clinical use was further demonstrated by utilizing virus culture as real clinical samples. Moreover, the proposed fluorescence sensor is IoMT enabled, which is accessible to edge hardware devices (personal computers, 5G smartphones, IPTV, etc.) through Bluetooth. Medical data can be transmitted to the fog layer of the network and 5G cloud server with ultra-low latency and high reliably for edge computing and big data analysis. Furthermore, a COVID-19 monitoring module working with the proposed the system is developed on a smartphone application (App), which endows patients and their families to record their medical data and daily conditions remotely, releasing the burdens of going to central hospitals. We believe that the proposed system will be highly practical in the future treatment and prevention of COVID-19 and other mass infectious diseases.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Systems / Immunoassay / Biosensing Techniques / COVID-19 Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Biosens Bioelectron Journal subject: Biotechnology Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Systems / Immunoassay / Biosensing Techniques / COVID-19 Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Biosens Bioelectron Journal subject: Biotechnology Year: 2021 Document Type: Article