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Inducible NO synthase: role in cellular signalling
Abstract
The discovery of endothelium-derived relaxing factor and its identification as nitric oxide (NO) was one of the most exciting discoveries of biomedical research in the 1980s. Besides its potent vasodilatory effects, NO was found under certain circumstances to be responsible for the killing of microorganisms and tumour cells by activated macrophages and to act as a novel, unconventional type of neurotransmitter. In 1992, Science picked NO as the ‘Molecule of the Year’, and over the past years NO has become established as a universal intercellular messenger that acutely affects important signalling pathways and, on a more long-term scale, modulates gene expression in target cells. These actions will form the focus of the present review.
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Guo, F.-Q., Okamoto, M., & Crawford, N. M. (2003) · Science · doi:10.1126/science.1086770 · Cited by 889
Sturrock, A., Cahill, B., Norman, K., Huecksteadt, T. P., Hill, K., Sanders, K., Karwande, S. V., Stringham, J. C., Bull, D. A., Gleich, M., et al. (2006) · American Journal of Physiology-Lung Cellular and Molecular Physiology · doi:10.1152/ajplung.00269.2005 · Cited by 402
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Metadata
- Authors
- Beck, K.-F., Eberhardt, W., Frank, S., Huwiler, A., Meßmer, U. K., Mühl, H., & Pfeilschifter, J.
- Venue
- Journal of Experimental Biology
- Publisher
- The Company of Biologists
- Published
- 1999-03-15
- Volume
- 202
- Issue
- 6
- Pages
- 645-653
- ISSN
- 0022-0949 (ISSN-L)
- 1477-9145
- OpenAlex
- W2146159955
- Cited by
- 164
- References
- 0
- FWCI
- 7.61
- Type
- journal article
- Language
- en
- Open access
- closed
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- Beck, K.-F., Eberhardt, W., Frank, S., Huwiler, A., Meßmer, U. K., Mühl, H., & Pfeilschifter, J. (1999). Inducible NO synthase: role in cellular signalling. Journal of Experimental Biology. https://doi.org/10.1242/jeb.202.6.645
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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.