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Cited by 283

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

Lymph Node Macrophages

Open access
Gray, Elizabeth E., Cyster, Jason G.·2012·Journal of Innate Immunity

Abstract

Lymph node (LN) macrophages have long been known for their efficient uptake of lymph-borne antigens. A convergence of studies on innate and adaptive immune responses has led to exciting recent advances in understanding their more specialized properties: presenting antigens to B cells, dendritic cells and T cells, producing trophic factors and cytokines, and, remarkably, being permissive for viral infection, a property critical for mounting anti-viral responses. LN macrophages have been traditionally divided into subsets based on their subcapsular sinus and medullary locations. Here, we classify LN macrophages into three subsets: subcapsular sinus macrophages, medullary sinus macrophages and medullary cord macrophages. We review the literature regarding the roles of these cells in innate and adaptive immune responses and requirements for their development. We also discuss challenges associated with their purification as well as the existence of additional heterogeneity among LN macrophages.

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Crossref · 10.1159/000337007

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Metadata

Authors
Gray, E. E., & Cyster, J. G.
Venue
Journal of Innate Immunity
Publisher
S. Karger AG
Published
2012
Volume
4
Issue
5-6
Pages
424-436
ISSN
  • 1662-811X (ISSN-L)
  • 1662-8128
OpenAlex
W2067170256
Cited by
283
References
6
FWCI
5.30
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Lymph Node Macrophages. https://app.cochat.ai/papers/10.1159/000337007
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Gray, E. E., & Cyster, J. G. (2012). Lymph Node Macrophages. Journal of Innate Immunity. https://doi.org/10.1159/000337007

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.