On-Site Detection of SARS-CoV-2 Antigen by Deep Learning-Based Surface-Enhanced Raman Spectroscopy and Its Biochemical Foundations.
Jinglin Huang,Wen Jiaxing,Wen Jiaxing,Minjie Zhou,Ni Shuang,Wei Le,Chen Guo,Lai Wei,Yong Zeng,Daojian Qi,Ming Pan,Jianan Xu,Yan Wu,Li Zeyu,Yuliang Feng,Zongqing Zhao,Zhibing He,Li Bo,Zhao Songnan,Baohan Zhang,Peili Xue,Shusen He,Kun Fang,Yuanyu Zhao,Kai Du +24 more
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TLDR
In this article, a deep learning-based surface-enhanced Raman spectroscopy technique was developed for the sensitive, rapid, and on-site detection of the SARS-CoV-2 antigen in the throat swabs or sputum from 30 confirmed COVID-19 patients.Abstract:
A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have developed a deep learning-based surface-enhanced Raman spectroscopy technique for the sensitive, rapid, and on-site detection of the SARS-CoV-2 antigen in the throat swabs or sputum from 30 confirmed COVID-19 patients. A Raman database based on the spike protein of SARS-CoV-2 was established from experiments and theoretical calculations. The corresponding biochemical foundation for this method is also discussed. The deep learning model could predict the SARS-CoV-2 antigen with an identification accuracy of 87.7%. These results suggested that this method has great potential for the diagnosis, monitoring, and control of SARS-CoV-2 worldwide.read more
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Integrated System for On-Site Rapid and Safe Screening of COVID-19
Dongheyu Zhang,Yuntao Guo,Liyang Zhang,Yao Wang,Siqi Peng,Simeng Duan,Lin Geng,Xiao Zhang,Wei Wang,Mengjie Yang,Guizhen Wu,Jiayi Chen,Zihao Feng,Xinyuan Wang,Yue Wu,Haotian Jiang,Qikang Zhang,Jing-ying Sun,Shenwei Li,Yuping He,Meng Xiao,Yingchun Xu,Hong Wang,Peipei Liu,Qun Zhou,Haiyun Luo +25 more
TL;DR: An integrated system, which incorporates a machine-learning-based Fourier transform infrared spectroscopy technique for rapid COVID-19 screening and air-plasma-based disinfection modules to prevent potential secondary infections, is established.
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Counter-propagating Gaussian beam enhanced Raman spectroscopy for rapid reagentless detection of respiratory pathogens in nasal swab samples
Gregory W. Auner,S. Kiran Koya,Chang-Yeng Huang,C. Shanley,Micaela Trexler,Sally Yurgelevic,Jake DeMeulemeester,Krista Bui,Kristen Amyx-Sherer,Michelle Brusatori +9 more
TL;DR: In this article , a point-of-need Raman spectroscopy-based platform is described for rapid detection of multiple respiratory pathogens in nasal swab samples with high sensitivity and specificity.
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Spectroscopic Methods for the Detection of Microbial Pathogens and Diagnostics of Infectious Diseases—An Updated Overview
Subramani Pandian,Selvaraj Alagu Lakshmi,Arumugam Priya,Boopathi Balasubramaniam,John-Lewis Zinia Zaukuu,Ravindran Durgadevi,Soo-In Sohn +6 more
TL;DR: In this paper , the authors reviewed the most reliable tools that are prerequisites for the rapid detection of microbes and discussed the remarkable roles of surface-enhanced Raman scattering, Fourier transform infrared, electrochemical impedance, near-infrared, and MALDI-TOF/TOF in the identification and characterization of pathogenic microbes.
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Recent development of surface-enhanced Raman scattering for biosensing
Chenglong Lin,Yanyan Li,Yusi Peng,Shuaichang Zhao,Meimei Xu,Lingxia Zhang,Zhengren Huang,Jianlin Shi,Yong-Huang Yang +8 more
TL;DR: In this paper , the challenges and perspectives of SERS biosensing in the future are presented, and the important strategies (extending from nanomaterials with tunable shapes and nanostructures to surface bio-functionalization by modifying affinity groups or specific biomolecules) for improving SERS sensing performance are comprehensively discussed.
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Label-Free Saliva Test for Rapid Detection of Coronavirus Using Nanosensor-Enabled SERS
TL;DR: In this article , a surface-enhanced Raman scattering (SERS) based test was designed to rapidly diagnose SARS-CoV-2 from saliva, which significantly increased the detection specificity and sensitivity.
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