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Cited by 904

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Turning 'sweet' on immunity: galectin–glycan interactions in immune tolerance and inflammation

Open access
Rabinovich, Gabriel A., Toscano, Marta A.·2009·Nature Reviews Immunology

Abstract

The function of deciphering the biological information encoded by the glycome, which is the entire repertoire of complex sugar structures expressed by cells and tissues, is assigned in part to endogenous glycan-binding proteins or lectins. Galectins, a family of animal lectins that bind N-acetyllactosamine-containing glycans, have many roles in diverse immune cell processes, including those relevant to pathogen recognition, shaping the course of adaptive immune responses and fine-tuning the inflammatory response. How do galectins translate glycan-encoded information into tolerogenic or inflammatory cell programmes? An improved understanding of the mechanisms underlying these functions will provide further opportunities for developing new therapies based on the immunoregulatory properties of this multifaceted protein family.

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Crossref · 10.1038/nri2536

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Metadata

Authors
Rabinovich, G. A., & Toscano, M. A.
Venue
Nature Reviews Immunology
Published
2009-05
Volume
9
Issue
5
Pages
338-352
ISSN
  • 1474-1733 (ISSN-L)
  • 1474-1741
OpenAlex
W2088373848
Cited by
904
References
7
FWCI
2.90
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Turning 'sweet' on immunity: galectin–glycan interactions in immune tolerance and inflammation. https://app.cochat.ai/papers/10.1038/nri2536
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Rabinovich, G. A., & Toscano, M. A. (2009). Turning 'sweet' on immunity: galectin–glycan interactions in immune tolerance and inflammation. Nature Reviews Immunology. https://doi.org/10.1038/nri2536

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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.