期刊
APPLIED PHYSICS LETTERS
卷 121, 期 6, 页码 -出版社
AIP Publishing
DOI: 10.1063/5.0104527
关键词
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资金
- Wuhan frontier project for applied foundational research [2019020701011452]
- innovation team fund of the National Ethnic Affairs Commission [MZR20002]
- South-Central Minzu University [KTZ20039, CZP 18003, 2020-519]
The analysis and detection of nucleic acid and specific antigens and antibodies are fundamental for virus monitoring. However, current technologies have limited applicability in early monitoring and control of unknown viruses transmitted via aerosols. In this study, a weak light spectral imaging technology based on Tesla discharge (T-DAI) is reported, which enables real-time monitoring of viruses in simulated aerosols with high sensitivity and specificity. This technology could provide an important means for predicting, screening, and monitoring unknown or pandemic pathogenic viruses in the air or exhaled breath.
The analysis and detection of nucleic acid and specific antigens and antibodies are the most basic technologies for virus monitoring. However, the potential window for applying these technologies exists within a late specific period in the early monitoring and control of unknown viruses, especially human and animal pathogenic viruses transmitted via aerosols, e.g., SARS-CoV-2 and its variants. This is because early, real-time, and convenient monitoring of unknown viruses in the air or exhaled gas cannot be directly achieved through existing technologies. Herein, we report a weak light spectral imaging technology based on Tesla discharge (termed T-DAI) that can quickly monitor for viruses in real time in simulated aerosols with 71% sensitivity and 76% specificity for aerosol virus concentrations exceeding approximately 2800 vp/mu l. This technology realizes the rapid detection of low concentrations of viruses in aerosols and could provide an important means for predicting, screening, and monitoring unknown or pandemic pathogenic viruses in the air or exhaled breath of humans and animals. (C) 2022 Author(s).
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