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Cited by 630

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Evaluation of Nucleocapsid and Spike Protein-Based Enzyme-Linked Immunosorbent Assays for Detecting Antibodies against SARS-CoV-2

Open access
Liu, Wanbing, Liu, Lei, Kou, Guomei, Zheng, Yaqiong, Ding, Yinjuan, Ni, Wenxu, Wang, Qiongshu, Tan, Li, Wu, Wanlei, Tang, Shi, Xiong, Zhou, Zheng, Shangen·2020·Journal of Clinical Microbiology

Abstract

At present, PCR-based nucleic acid detection cannot meet the demands for coronavirus infectious disease (COVID-19) diagnosis. Two hundred fourteen confirmed COVID-19 patients who were hospitalized in the General Hospital of Central Theater Command of the People’s Liberation Army between 18 January and 26 February 2020 were recruited. Two enzyme-linked immunosorbent assay (ELISA) kits based on recombinant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid protein (rN) and spike protein (rS) were used for detecting IgM and IgG antibodies, and their diagnostic feasibility was evaluated.

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Crossref · 10.1128/jcm.00461-20

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Metadata

Authors
Liu, W., Liu, L., Kou, G., Zheng, Y., Ding, Y., Ni, W., Wang, Q., Tan, L., Wu, W., Tang, S., Xiong, Z., & Zheng, S.
Venue
Journal of Clinical Microbiology
Published
2020-05-26
Volume
58
Issue
6
ISSN
  • 0095-1137 (ISSN-L)
  • 1098-660X
OpenAlex
W3013213522
Cited by
630
References
3
FWCI
17.56
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Evaluation of Nucleocapsid and Spike Protein-Based Enzyme-Linked Immunosorbent Assays for Detecting Antibodies against SARS-CoV-2. https://app.cochat.ai/papers/10.1128/jcm.00461-20
The paper
Liu, W., Liu, L., Kou, G., Zheng, Y., Ding, Y., Ni, W., Wang, Q., Tan, L., Wu, W., Tang, S., Xiong, Z., & Zheng, S. (2020). Evaluation of Nucleocapsid and Spike Protein-Based Enzyme-Linked Immunosorbent Assays for Detecting Antibodies against SARS-CoV-2. Journal of Clinical Microbiology. https://doi.org/10.1128/jcm.00461-20

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

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