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Cited by 389

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Mucosal Immunity in COVID-19: A Neglected but Critical Aspect of SARS-CoV-2 Infection

Open access
Russell, Michael W., Moldoveanu, Zina, Ogra, Pearay L., Mestecky, Jiri·2020·Frontiers in Immunology

Abstract

The mucosal immune system is the largest component of the entire immune system, having evolved to provide protection at the main sites of infectious threat: the mucosae. As SARS-CoV-2 initially infects the upper respiratory tract, its first interactions with the immune system must occur predominantly at the respiratory mucosal surfaces, during both inductive and effector phases of the response. However, almost all studies of the immune response in COVID-19 have focused exclusively on serum antibodies and systemic cell-mediated immunity including innate responses. This article proposes that there is a significant role for mucosal immunity and for secretory as well as circulating IgA antibodies in COVID-19, and that it is important to elucidate this in order to comprehend especially the asymptomatic and mild states of the infection, which appear to account for the majority of cases. Moreover, it is possible that mucosal immunity can be exploited for beneficial diagnostic, therapeutic, or prophylactic purposes.

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Metadata

Authors
Russell, M. W., Moldoveanu, Z., Ogra, P. L., & Mestecky, J.
Venue
Frontiers in Immunology
Published
2020-11-30
Volume
11
Pages
611337-611337
ISSN
1664-3224 (ISSN-L)
OpenAlex
W3109360305
Cited by
389
References
34
FWCI
8.51
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Mucosal Immunity in COVID-19: A Neglected but Critical Aspect of SARS-CoV-2 Infection. https://app.cochat.ai/papers/10.3389/fimmu.2020.611337
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Russell, M. W., Moldoveanu, Z., Ogra, P. L., & Mestecky, J. (2020). Mucosal Immunity in COVID-19: A Neglected but Critical Aspect of SARS-CoV-2 Infection. Frontiers in Immunology. https://doi.org/10.3389/fimmu.2020.611337

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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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