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Cited by 257

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Inducing Mucosal IgA: A Challenge for Vaccine Adjuvants and Delivery Systems

Open access
Boyaka, Prosper N·2017·The Journal of Immunology

Abstract

Mucosal IgA or secretory IgA (SIgA) are structurally equipped to resist chemical degradation in the harsh environment of mucosal surfaces and enzymes of host or microbial origin. Production of SIgA is finely regulated, and distinct T-independent and T-dependent mechanisms orchestrate Ig α class switching and SIgA responses against commensal and pathogenic microbes. Most infectious pathogens enter the host via mucosal surfaces. To provide a first line of protection at these entry ports, vaccines are being developed to induce pathogen-specific SIgA in addition to systemic immunity achieved by injected vaccines. Mucosal or epicutaneous delivery of vaccines helps target the inductive sites for SIgA responses. The efficacy of such vaccines relies on the identification and/or engineering of vaccine adjuvants capable of supporting the development of SIgA alongside systemic immunity and delivery systems that improve vaccine delivery to the targeted anatomic sites and immune cells.

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Metadata

Authors
Boyaka, P. N.
Venue
The Journal of Immunology
Published
2017-07-01
Volume
199
Issue
1
Pages
9-16
ISSN
  • 0022-1767 (ISSN-L)
  • 1550-6606
OpenAlex
W2723539103
Cited by
257
References
6
FWCI
7.33
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Inducing Mucosal IgA: A Challenge for Vaccine Adjuvants and Delivery Systems. https://app.cochat.ai/papers/10.4049/jimmunol.1601775
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Boyaka, P. N. (2017). Inducing Mucosal IgA: A Challenge for Vaccine Adjuvants and Delivery Systems. The Journal of Immunology. https://doi.org/10.4049/jimmunol.1601775

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.