The DOI matches its Crossref record; 121 of the 121 references it cites were found in a registry or an index.
Animal models of metabolic syndrome: a review
Open accessAbstract
Metabolic syndrome (MetS) consists of several medical conditions that collectively predict the risk for cardiovascular disease better than the sum of individual conditions. The risk of developing MetS in human depends on synergy of both genetic and environmental factors. Being a multifactorial condition with alarming rate of prevalence nowadays, establishment of appropriate experimental animal models mimicking the disease state in humans is crucial in order to solve the difficulties in evaluating the pathophysiology of MetS in human. This review aims to summarize the underlying mechanisms involved in the pathophysiology of dietary, genetic, and pharmacological models of MetS. Furthermore, we will discuss the usefulness, suitability, pros and cons of these animal models. Even though numerous animal models of MetS have been established, further investigations on the invention of new animal model and clarification of plausible mechanisms are still necessary to confer a better understanding to researchers on the selection of animal models for their studies.
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Cites
1 retracted
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Cited by
Mzhelskaya, K. V., Shipelin, V. A., Shumakova, A. A., Musaeva, A. D., Soto, J. S., Riger, N. A., Trusov, N. V., Kirbaeva, N. V., Apryatin, S. A., & Gmoshinski, I. V. (2020) · Behavioural Brain Research · doi:10.1016/j.bbr.2019.112270 · Cited by 24
Metadata
- Authors
- Wong, S. K., Chin, K.-Y., Suhaimi, F. H., Fairus, A., & Ima-Nirwana, S.
- Venue
- Nutrition & Metabolism
- Published
- 2016-10-04
- Volume
- 13
- Issue
- 1
- Pages
- 65-65
- ISSN
- 1743-7075 (ISSN-L)
- OpenAlex
- W2528626298
- Cited by
- 371
- References
- 121
- FWCI
- 28.29
- Type
- journal article
- Language
- en
- Open access
- gold
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- Wong, S. K., Chin, K.-Y., Suhaimi, F. H., Fairus, A., & Ima-Nirwana, S. (2016). Animal models of metabolic syndrome: a review. Nutrition & Metabolism. https://doi.org/10.1186/s12986-016-0123-9
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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