Objective: To investigate the effects of polydatin on a high-fat diet-induced non-alcoholic fatty liver disease(NAFLD) mouse model and hepatoma G2(HepG2) cell model, and to reveal its potential molecular mechanisms. Methods: Thirty 6-week-old male SPF C57BL/6J mice were randomly divided into a normal diet group and a high-fat diet group. After the NAFLD mouse model was established in the high-fat diet group, they were further divided into a model group and a polydatin treatment group. The polydatin treatment group was administered polydatin by gavage at a dose of 250 mg/(kg·d) for 10 weeks, during which body weight was monitored and oral glucose and insulin tolerance tests were performed. At the end of the experiment, a series of tests to evaluate the effects of polydatin on mouse liver weight, blood lipids, liver lipid accumulation, and liver injury markers were performed. The expression of G0/G1 switch gene 2(G0S2) and adipose triglyceride lipase(ATGL) was measured by qRT-PCR and Western blot, and gene expression was further verified using immunohistochemical staining. The effects of polydatin on HepG2 cell activity was assessed by CCK-8 assay, lipid accumulation was observed by oil red O staining, and the expression of G0S2 and ATGL was detected by qRT-PCR and Western blot. Results: Polydatin significantly reduced the body weight, liver weight, and serum and liver tissue levels of aspartate aminotransferase(AST), alanine aminotransferase(ALT), triglyceride(TG), and total cholesterol (TC) in mice (P < 0. 05) , al⁃leviated pathological liver damage , decreased G0S2 expression (P < 0. 05) , and increased ATGL expression (P <0. 05) . At the cellular level , polydatin reduced lipid droplet accumulation , improved lipid metabolism , decreased G0S2 expression ( P < 0. 05 ) , and increased ATGL expression ( P < 0. 05 ) . Even in cells with knockdown of G0S2 , polydatin still promoted fat decomposition (P < 0. 01) . Conclusion Polydatin promotes hepatic fat break⁃down by regulating the expression of G0S2 and ATGL , helping to alleviate metabolic disorders and liver damage in the NAFLD mouse model caused by a high⁃fat diet , offering a new strategy for treating NAFLD.

Modern TCM understands the pathogenesis of blood glucose fluctuation mainly from the viscera (spleen, kidney, liver, bile, small intestine), middle energizer, "yin fire theory", "Xuanfu depression" and "qi transformation". In clinic, blood glucose fluctuation is mainly divided into four syndrome types: qi-yin deficiency syndrome, yin-yang deficiency syndrome, exuberance of fire and heat syndrome, and heat stagnation in liver-stomach syndrome. TCM compounds can improve blood glucose fluctuation by improving insulin resistance, regulating intestinal microflora, promoting the secretion of glucagon-like peptide-1, and fighting oxidative stress.

Objective:To compare the performances of different time series models in predicting COVID-19 in different countries.Methods:We collected the daily confirmed case numbers of COVID-19 in the USA, India, and Brazil from April 1 to September 30, 2020, and then constructed an autoregressive integrated moving average (ARIMA) model and a recurrent neural network (RNN) model, respectively. We applied the mean absolute percentage error (MAPE) and root mean square error (RMSE) to compare the performances of the two models in predicting the case numbers from September 21 to September 30, 2020.Results:For the ARIMA models applied in the USA, India, and Brazil, the MAPEs were 13.18%, 9.18%, and 17.30%, respectively, and the RMSEs were 6 542.32, 8 069.50, and 3 954.59, respectively. For the RNN models applied in the USA, India, and Brazil, the MAPEs were 15.27%, 7.23% and 26.02%, respectively, and the RMSEs were 6 877.71, 6 457.07, and 5 950.88, respectively.Conclusions:The performance of the prediction models varied with country. The ARIMA model had a better prediction performance for COVID-19 in the USA and Brazil, while the RNN model was more suitable in India.