Chlorogenic acid modulates glucose and lipid metabolisms via AMPK activation in HepG2 cells and shows its anti-hyperglycemic effect on streptozocin-induced diabetic mice

Objective:In this study,we focus on the hypoglycemic effects of chlorogenic acid(CGA)in vitro and in vivo and its mechanism base on regulate glucose and lipid metabolism via AMPK activation.Methods:The cytotoxicity,glucose consumption and intracellular triglyceride assay were been detected by commercial kits.The western blots were used to detection the associated protein levels after CGA treatment,and the inhibiter blocking experiments were also be done.In vivo experiment,the fasting blood-glucose,lipid metabolism,liver function,insulin resistance,glucose tolerance,and pathological change were assessed on streptozocin induced diabetic mice.Results:We found that CGA exhibited no cytotoxicity at concentrations of 100μM,it caused a significant increasing of glucose consumption and reducing of the PA-BSA induced intracellular TG level on HepG2 cells at 50μM and 100μM treatment,CGA exhibited up-regulating the level of p-AMPK(Thr172)and p-ACC(Ser79)in dose-dependent manners in vitro and in vivo.The stimulating activities of CGA on AMPK were completely blocked by compound c(CC)on HepG2 cells.And the efficacies of CGA on glucose consumption and intracellular TG accumulation were also completely blocked by CC pretreatment.The CGA also exhibited potent anti-diabetic effects with hypoglycemic activity,improve insulin resistance and glucose tolerance,regulate glucose and lipid metabolism and protect the liver function in vivo.Conclusion:Our results suggested that CGA can regulate glucose and lipid metabolism by AMPK activation,and exhibit potent anti-hyperglycemic effect in streptozocin induced diabetes mice,and may be used as a potential effective anti-diabetes drug.

金融大脑:当金融遇见AI 2.0（英文）

人工智能(AI)是技术革命和产业转型的核心技术。金融智能作为AI 2.0时代新需求之一,引起学术界和工业界广泛关注。在当前充满活力的资本市场中,金融智能展示了快速准确的机器学习能力,可处理复杂数据,并有潜力逐渐成为'金融大脑'。我们对现有金融智能进行总结和综述:首先,论述金融智能概念,阐述其在金融技术领域的地位。其次,介绍金融智能的细分领域,回顾财富管理、风险管理、金融安全、金融智能客服和区块链等领域的最新技术。最后,提出一个称作'金融大脑'(FinBrain)的研究框架,总结了4个开放性问题,即可解释的金融代理和因果关系、不确定性下的感知和预测、风险敏感和稳健决策以及多智能体博弈和机制设计。相信这些研究方向可为AI 2.0在金融领域的发展奠定基础。