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Cited by 190

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Review: IFN- α / β Receptor Interactions to Biologic Outcomes: Understanding the Circuitry

Brierley, Melissa M., Fish, Eleanor N.·2002·Journal of Interferon & Cytokine Research

Abstract

Type I interferons (IFNs), which include the IFN-alphas, IFN-beta, IFN-omega, IFN-kappa, and IFN-tau, are an evolutionarily conserved group of secreted cytokines that serve as potent extracellular mediators of host defense and homeostasis. Binding of IFNs to specific cell surface receptors results in the activation of multiple intracellular signaling cascades, leadingto the synthesis of proteins that mediate antiviral, growth inhibitory and immunomodulatory responses. In the past decade, considerable information has accumulated pertaining to the different signalingpathways that are activated by the type I IFNs. Although many of the literature findings are specific to defined cell systems or are tissue restricted, the intent of this review is to place these signaling cascades and their effectors in the context of distinct biologic outcomes.

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Metadata

Authors
Brierley, M. M., & Fish, E. N.
Venue
Journal of Interferon & Cytokine Research
Published
2002-08
Volume
22
Issue
8
Pages
835-845
ISSN
  • 1079-9907 (ISSN-L)
  • 1557-7465
OpenAlex
W2048767389
Cited by
190
References
5
FWCI
3.69
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Review: IFN- α / β Receptor Interactions to Biologic Outcomes: Understanding the Circuitry. https://app.cochat.ai/papers/10.1089/107999002760274845
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Brierley, M. M., & Fish, E. N. (2002). Review: IFN- α / β Receptor Interactions to Biologic Outcomes: Understanding the Circuitry. Journal of Interferon & Cytokine Research. https://doi.org/10.1089/107999002760274845

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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.