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5G 赋能的超高灵敏度荧光传感器,用于主动预测 COVID-19。

5G-enabled ultra-sensitive fluorescence sensor for proactive prognosis of COVID-19.

机构信息

School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China.

School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, PR China.

出版信息

Biosens Bioelectron. 2021 Jun 1;181:113160. doi: 10.1016/j.bios.2021.113160. Epub 2021 Mar 13.

DOI:10.1016/j.bios.2021.113160
PMID:33740542
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7954646/
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@mSiO) 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.

摘要

自 2019 年 12 月以来,严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)在全球范围内传播。迫切需要开发用于现场诊断和监测疑似 COVID-19 患者的敏感和在线方法。随着物联网(IoT)的巨大发展,医疗物联网(IoMT)的影响为解决这一问题提供了令人印象深刻的解决方案。在本文中,我们提出了一种基于 5G 的荧光传感器,用于通过使用介孔硅封装的上转换纳米粒子(UCNPs@mSiO)标记侧向流动免疫分析(LFIA)来定量检测 SARS-CoV-2 的刺突蛋白和核衣壳蛋白。该传感器可以检测刺突蛋白(SP),检测限(LOD)为 1.6ng/mL,核衣壳蛋白(NP)的 LOD 为 2.2ng/mL。通过利用病毒培养作为真实临床样本,进一步证明了传感器在临床应用中的可行性。此外,所提出的荧光传感器是 IoMT 启用的,通过蓝牙可以与边缘硬件设备(个人计算机、5G 智能手机、IPTV 等)连接。医疗数据可以通过超低延迟和高可靠性传输到网络的雾层和 5G 云服务器,以进行边缘计算和大数据分析。此外,还在智能手机应用程序(App)上开发了一个与所提出系统配合使用的 COVID-19 监测模块,使患者及其家属能够远程记录他们的医疗数据和日常情况,减轻前往中心医院的负担。我们相信,所提出的系统将在未来 COVID-19 和其他大规模传染病的治疗和预防中具有很高的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/48d91aeeeb78/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/78c8e7912325/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/54b2e5de215e/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/c1c8f87e85f6/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/1bf79d1d2bdb/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/48d91aeeeb78/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/78c8e7912325/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/54b2e5de215e/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/c1c8f87e85f6/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/1bf79d1d2bdb/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a95/7954646/48d91aeeeb78/gr5_lrg.jpg

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