Recent Developments in Rodent Models of High-Fructose Diet-Induced Metabolic Syndrome: A Systematic Review

Metabolic syndrome (MetS) is the physiological clustering of hypertension, hyperglycemia, hyperinsulinemia, dyslipidemia, and insulin resistance. The MetS-related chronic illnesses encompass obesity, the cardiovascular system, renal operation, hepatic function, oncology, and mortality. To perform pr...

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Veröffentlicht in:Nutrients 2021-07, Vol.13 (8), p.2497, Article 2497
Hauptverfasser: Chan, Alvin Man Lung, Ng, Angela Min Hwei, Mohd Yunus, Mohd Heikal, Idrus, Ruszymah Bt Hj, Law, Jia Xian, Yazid, Muhammad Dain, Chin, Kok-Yong, Shamsuddin, Sharen Aini, Lokanathan, Yogeswaran
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Sprache:eng
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Zusammenfassung:Metabolic syndrome (MetS) is the physiological clustering of hypertension, hyperglycemia, hyperinsulinemia, dyslipidemia, and insulin resistance. The MetS-related chronic illnesses encompass obesity, the cardiovascular system, renal operation, hepatic function, oncology, and mortality. To perform pre-clinical research, it is imperative that these symptoms be successfully induced and optimized in lower taxonomy. Therefore, novel and future applications for a disease model, if proven valid, can be extrapolated to humans. MetS model establishment is evaluated based on the significance of selected test parameters, paradigm shifts from new discoveries, and the accessibility of the latest technology or advanced methodologies. Ultimately, the outcome of animal studies should be advantageous for human clinical trials and solidify their position in advanced medicine for clinicians to treat and adapt to serious or specific medical situations. Rodents (Rattus norvegicus and Mus musculus) have been ideal models for mammalian studies since the 18th century and have been mapped extensively. This review compiles and compares studies published in the past five years between the multitude of rodent comparative models. The response factors, niche parameters, and replicability of diet protocols are also compiled and analyzed to offer insight into MetS-related disease-specific modelling.
ISSN:2072-6643
2072-6643
DOI:10.3390/nu13082497