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Cited by 552

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Mechanisms of Jak/STAT Signaling in Immunity and Disease

Open access
Villarino, Alejandro V, Kanno, Yuka, Ferdinand, John R, O’Shea, John J·2014·The Journal of Immunology

Abstract

More than two decades ago, experiments on the antiviral mechanisms of IFNs led to the discovery of JAKs and their downstream effectors, the STAT proteins. This pathway has since become a paradigm for membrane-to-nucleus signaling and explains how a broad range of soluble factors, including cytokines and hormones, mediate their diverse functions. Jak/STAT research has not only impacted basic science, particularly in the context of intercellular communication and cell-extrinsic control of gene expression, it also has become a prototype for transition from bench to bedside, culminating in the development and clinical implementation of pathway-specific therapeutics. This brief review synthesizes our current understanding of Jak/STAT biology while taking stock of the lessons learned and the challenges that lie ahead.

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Crossref · 10.4049/jimmunol.1401867

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Metadata

Authors
Villarino, A. V., Kanno, Y., Ferdinand, J. R., & O’Shea, J. J.
Venue
The Journal of Immunology
Published
2014-01-01
Volume
194
Issue
1
Pages
21-27
ISSN
  • 0022-1767 (ISSN-L)
  • 1550-6606
OpenAlex
W1671779243
Cited by
552
References
14
FWCI
14.65
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Mechanisms of Jak/STAT Signaling in Immunity and Disease. https://app.cochat.ai/papers/10.4049/jimmunol.1401867
The paper
Villarino, A. V., Kanno, Y., Ferdinand, J. R., & O’Shea, J. J. (2014). Mechanisms of Jak/STAT Signaling in Immunity and Disease. The Journal of Immunology. https://doi.org/10.4049/jimmunol.1401867

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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.