1. Amino Acid Profiling Study of Psidium guajava L. Leaves as an Effective Treatment for Type 2 Diabetic Rats
- Author
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Lushuang Li, Chang Xu, Xi Xie, Makoto Tsunoda, Ying Liu, Rong Wang, Yingxia Zhang, Xin Li, Yuhang Gao, Shiming Deng, Debin Zeng, and Yanting Song
- Subjects
chemistry.chemical_classification ,0303 health sciences ,Article Subject ,030309 nutrition & dietetics ,010401 analytical chemistry ,Metabolic disorder ,Type 2 Diabetes Mellitus ,Phenylalanine ,Pharmacology ,medicine.disease ,Streptozotocin ,01 natural sciences ,0104 chemical sciences ,Amino acid ,03 medical and health sciences ,Other systems of medicine ,Complementary and alternative medicine ,chemistry ,Valine ,Diabetes mellitus ,medicine ,Leucine ,RZ201-999 ,medicine.drug - Abstract
Type 2 diabetes mellitus (T2DM) has become a major disease threatening human health worldwide. At present, the treatment of T2DM cannot cure diabetes and is prone to many side effects. Psidium guajava L. leaves have been reported to possess hypoglycemic activity, and they have been widely used in diabetes treatment in the folk. However, the antidiabetic mechanism has not been clearly explained. Also, the change in amino acid profile can reflect a metabolic disorder and provide insights into system-wide changes in response to physiological challenges or disease processes. The study found that P. guajava L. leaves can decrease fasting blood glucose and lipid levels in type 2 diabetic rats induced by streptozotocin. Through the analysis of amino acid profiling following 20 days of gavage administration, the concentration data were modeled by principal component analysis and orthogonal partial least squares discriminant analysis to find the different metabolites and related metabolic pathways (including cysteine and methionine metabolism, valine, leucine, and isoleucine biosynthesis, phenylalanine, tyrosine, and tryptophan biosynthesis) for the explanation of the hypoglycemic mechanism of P. guajava L., which provides an experimental and theoretical basis for diabetes prediction and for the development of new drugs for the treatment of diabetes.
- Published
- 2020