Ziyin Bushen Fang improves Diabetic Osteoporosis by Inhibiting Autophagy and Oxidative Stress In vitro and In vivo

Author:

Jiang Bo1,Mou Yan Jie1,Zhang Xian Mei1,Lu Kun1,Xie Ping1,Rao Yan Ling1,Cong Ze Wei1,Sun Qin guo1

Affiliation:

1. Department of Traditional Chinese Medicine, Wuhan Third Hospital, Wuhan, 430060, China

Abstract

Objective:: Diabetic osteoporosis (DOP) belongs to the group of diabetes-induced secondary osteoporosis and is the main cause of bone fragility and fractures in many patients with diabetes. The aim of this study was to determine whether Ziyin Bushen Fang (ZYBSF) can improve DOP by inhibiting autophagy and oxidative stress. background: The aim of this experiment is to study whether Ziyin Bushen Fang (ZYBSF) can treat DOP through autophagy and oxidative stress. Methods:: Type 1 diabetes mellitus (T1DM) was induced in rats using a high-fat high-sugar diet combined with streptozotocin. Micro-CT scanning was used to quantitatively observe changes in the bone microstructure in each group. Changes in the serum metabolites of DOP rats were analyzed using UHPLC-QTOF-MS. The DOP mouse embryonic osteoblast precursor cell model (MC3T3-E1) was induced using high glucose levels. Results:: After ZYBSF treatment, bone microstructure significantly improved. The bone mineral density, trabecular number, and trabecular thickness in the ZYBSF-M and ZYBSF-H groups significantly increased. After ZYBSF treatment, the femur structure of the rats was relatively intact, collagen fibers were significantly increased, and osteoporosis was significantly improved. A total of 1239 metabolites were upregulated and 1527 were downregulated in the serum of T1DM and ZYBSF-treated rats. A total of 20 metabolic pathways were identified. In cellular experiments, ZYBSF reduced ROS levels and inhibited the protein expression of LC3II / I, Beclin-1, and p- ERK. Conclusion:: ZYBSF may improve DOP by inhibiting the ROS/ERK-induced autophagy signaling pathway.

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

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