The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Cytoplasmic Signaling Pathways That Regulate Cardiac Hypertrophy
Abstract
▪ Abstract This review discusses the rapidly progressing field of cardiomyocyte signal transduction and the regulation of the hypertrophic response. When stimulated by a wide array of neurohumoral factors or when faced with an increase in ventricular-wall tension, individual cardiomyocytes undergo hypertrophic growth as an adaptive response. However, sustained cardiac hypertrophy is a leading predictor of future heart failure. A growing number of intracellular signaling pathways have been characterized as important transducers of the hypertrophic response, including specific G protein isoforms, low-molecular-weight GTPases (Ras, RhoA, and Rac), mitogen-activated protein kinase cascades, protein kinase C, calcineurin, gp130-signal transducer and activator of transcription, insulin-like growth factor I receptor pathway, fibroblast growth factor and transforming growth factor β receptor pathways, and many others. Each of these signaling pathways has been implicated as a hypertrophic transducer, which collectively suggests an emerging paradigm whereby multiple pathways operate in concert to orchestrate a hypertrophic response
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Metadata
- Authors
- Molkentin, J. D., & Dorn II, G. W.
- Venue
- Annual Review of Physiology
- Publisher
- Annual Reviews
- Published
- 2001-03
- Volume
- 63
- Issue
- 1
- Pages
- 391-426
- ISSN
- 0066-4278 (ISSN-L)
- 1545-1585
- OpenAlex
- W2130678592
- Cited by
- 689
- References
- 11
- FWCI
- 3.76
- Type
- journal article
- Language
- en
- Open access
- closed
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- Molkentin, J. D., & Dorn II, G. W. (2001). Cytoplasmic Signaling Pathways That Regulate Cardiac Hypertrophy. Annual Review of Physiology. https://doi.org/10.1146/annurev.physiol.63.1.391
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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.
