Applicability of Isolates and Fractions of Plant Extracts in Murine Models in Type II Diabetes: A Systematic Review. (24th October 2016)

• Record Type: Journal Article
• Authors: Coelho, Gabriela Diniz Pinto; Martins, Vanessa Soares; Amaral, Laura Vieira do; Novaes, Rômulo Dias; Sarandy, Mariáurea Matias; Gonçalves, Reggiani Vilela
• Other Names: Razzaque Mohammed S. Academic Editor.
• Is Part Of: Evidence-based complementary and alternative medicine. Volume 2016(2016)
• Publication Date: 2016-10-24
• Subjects: Alternative medicine -- Periodicals; 615.505
• DOI: 10.1155/2016/3537163
• Languages: English
• ISSNs: 1741-427X

Abstract

Abstract : Type II diabetes mellitus is one of the most common public health problems worldwide. Its increasing prevalence in several countries and the difficult metabolic control of individuals with the disease justify studying strategies for primary prevention. The population has sought alternative and cheaper ways to treat the disease, including the use of plants considered medicinal by the population. In this study, we carried out a systematic review on the applicability of isolates and fractions of plant extracts in animal models in type II diabetes. A literature search was performed in MEDLINE/PubMed and Scopus databases. Studies using other experimental animals (horses, rabbits, and monkeys) and humans as well as articles in Chinese, German, and Russian were excluded. We assessed the quality of the studies included by using the criteria described in the ARRIVE guidelines. In general, the animals that received fractions or isolates presented reduced blood glucose levels, normalization of body weight and plasma insulin levels, and reduced total triglycerides and cholesterol. In addition, we observed wide variation among the analyzed parameters, which hindered comparison between the studies found. In further studies, standardized reports and experimental design would help to establish comparable study groups and advance the overall knowledge, thus facilitating translatability from animal data to human clinical conditions.