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Recent advances and perspectives of nucleic acid detection for coronavirus

Open access
Shen, Minzhe, Zhou, Ying, Ye, Jiawei, Abdullah AL-maskri, Abdu Ahmed, Kang, Yu, Zeng, Su, Cai, Sheng·2020·Journal of Pharmaceutical Analysis

Abstract

The recent pneumonia outbreak caused by a novel coronavirus (SARS-CoV-2) is posing a great threat to global public health. Therefore, rapid and accurate identification of pathogenic viruses plays a vital role in selecting appropriate treatments, saving people's lives and preventing epidemics. It is important to establish a quick standard diagnostic test for the detection of the infectious disease (COVID-19) to prevent subsequent secondary spread. Polymerase chain reaction (PCR) is regarded as a gold standard test for the molecular diagnosis of viral and bacterial infections with high sensitivity and specificity. Isothermal nucleic acid amplification is considered to be a highly promising candidate method due to its fundamental advantage in quick procedure time at constant temperature without thermocycler operation. A variety of improved or new approaches also have been developed. This review summarizes the currently available detection methods for coronavirus nucleic acid. It is anticipated that this will assist researchers and clinicians in developing better techniques for timely and effective detection of coronavirus infection.

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Metadata

Authors
Shen, M., Zhou, Y., Ye, J., Abdullah AL-maskri, A. A., Kang, Y., Zeng, S., & Cai, S.
Venue
Journal of Pharmaceutical Analysis
Publisher
Elsevier BV
Published
2020-04
Volume
10
Issue
2
Pages
97-101
ISSN
2095-1779 (ISSN-L)
OpenAlex
W3006856666
Cited by
520
References
0
FWCI
13.31
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Recent advances and perspectives of nucleic acid detection for coronavirus. https://app.cochat.ai/papers/10.1016/j.jpha.2020.02.010
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Shen, M., Zhou, Y., Ye, J., Abdullah AL-maskri, A. A., Kang, Y., Zeng, S., & Cai, S. (2020). Recent advances and perspectives of nucleic acid detection for coronavirus. Journal of Pharmaceutical Analysis. https://doi.org/10.1016/j.jpha.2020.02.010

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.