The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Little Fish, Big Data: Zebrafish as a Model for Cardiovascular and Metabolic Disease
Open accessAbstract
The burden of cardiovascular and metabolic diseases worldwide is staggering. The emergence of systems approaches in biology promises new therapies, faster and cheaper diagnostics, and personalized medicine. However, a profound understanding of pathogenic mechanisms at the cellular and molecular levels remains a fundamental requirement for discovery and therapeutics. Animal models of human disease are cornerstones of drug discovery as they allow identification of novel pharmacological targets by linking gene function with pathogenesis. The zebrafish model has been used for decades to study development and pathophysiology. More than ever, the specific strengths of the zebrafish model make it a prime partner in an age of discovery transformed by big-data approaches to genomics and disease. Zebrafish share a largely conserved physiology and anatomy with mammals. They allow a wide range of genetic manipulations, including the latest genome engineering approaches. They can be bred and studied with remarkable speed, enabling a range of large-scale phenotypic screens. Finally, zebrafish demonstrate an impressive regenerative capacity scientists hope to unlock in humans. Here, we provide a comprehensive guide on applications of zebrafish to investigate cardiovascular and metabolic diseases. We delineate advantages and limitations of zebrafish models of human disease and summarize their most significant contributions to understanding disease progression to date.
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Sex determination, gonadal sex differentiation, and plasticity in vertebrate species
Nagahama, Y., Chakraborty, T., Paul-Prasanth, B., Ohta, K., & Nakamura, M. (2021) · Physiological Reviews · doi:10.1152/physrev.00044.2019 · Cited by 346
Gut, P., Matilainen, S., Meyer, J. G., Pällijeff, P., Richard, J., Carroll, C. J., Euro, L., Jackson, C. B., Isohanni, P., Minassian, B. A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19743-4 · Cited by 83
Self-citationPre-clinical Models of Metastasis in Pancreatic Cancer
Miquel, M., Zhang, S., & Pilarsky, C. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.748631 · Cited by 53
Xiao, Y., Hu, L., Duan, J., Che, H., Wang, W., Yuan, Y., Xu, J., Chen, D., & Zhao, S. (2024) · Environmental Pollution · doi:10.1016/j.envpol.2024.124022 · Cited by 49
Metadata
- Authors
- Gut, P., Reischauer, S., Stainier, D. Y. R., & Arnaout, R.
- Venue
- Physiological Reviews
- Publisher
- American Physiological Society
- Published
- 2017-07-01
- Volume
- 97
- Issue
- 3
- Pages
- 889-938
- ISSN
- 0031-9333 (ISSN-L)
- 1522-1210
- OpenAlex
- W2611783013
- Cited by
- 333
- References
- 33
- FWCI
- 2.83
- Type
- journal article
- Language
- en
- Open access
- green
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