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Cited by 772

The DOI matches its Crossref record; 163 of the 163 references it cites were found in a registry or an index.

NOD-Like Receptors: Role in Innate Immunity and Inflammatory Disease

Chen, Grace, Shaw, Michael H., Kim, Yun-Gi, Nuñez, Gabriel·2009·Annual Review of Pathology: Mechanisms of Disease

Abstract

The NOD-like receptors (NLRs) are a specialized group of intracellular receptors that represent a key component of the host innate immune system. Since the discovery of the first NLR almost 10 years ago, the study of this special class of microbial sensors has burgeoned; consequently, a better understanding of the mechanism by which these receptors recognize microbes and other danger signals and of how they activate inflammatory signaling pathways has emerged. Moreover, in addition to their primary role in host defense against invading pathogens, their ability to regulate nuclear factor–kappa B (NF-κB) signaling, interleukin-1-beta (IL-1β) production, and cell death indicates that they are crucial to the pathogenesis of a variety of inflammatory human diseases.

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Crossref · 10.1146/annurev.pathol.4.110807.092239

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Metadata

Authors
Chen, G., Shaw, M. H., Kim, Y.-G., & Nuñez, G.
Venue
Annual Review of Pathology: Mechanisms of Disease
Published
2009-02-01
Volume
4
Issue
1
Pages
365-398
ISSN
  • 1553-4006 (ISSN-L)
  • 1553-4014
OpenAlex
W2151713498
Cited by
772
References
163
FWCI
1.69
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: NOD-Like Receptors: Role in Innate Immunity and Inflammatory Disease. https://app.cochat.ai/papers/10.1146/annurev.pathol.4.110807.092239
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Chen, G., Shaw, M. H., Kim, Y.-G., & Nuñez, G. (2009). NOD-Like Receptors: Role in Innate Immunity and Inflammatory Disease. Annual Review of Pathology: Mechanisms of Disease. https://doi.org/10.1146/annurev.pathol.4.110807.092239

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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.