No abstract

Cancer is a kind of malignant diseases that threatens human health and the research application of anti-tumor drug therapeutics is growingly always been focused on. Many new compounds with great anticancer activity were synthesized but cannot be hard to be developed into clinical use due to its poor water solubility. Deoxypodophyllotoxin (DPT) is just an example. We develop lyophilized Deoxypodophyllotoxin (DPT) loaded polymeric micelles using methoxy polyethylene glycol-block-Poly (D, L-lactide) (mPEG-PLA). DPT-PM freeze-dried powder was successfully prepared using optimized formulation. mPEG-PLA was added to hydration media before hydrating as cryoprotectants. The freeze-dried powder exhibited white pie-solid without collapsing, and the particle size of DPT-PM reconstituted with water was about 20-35 nm. The entrapment efficiency of the reconstituted solution was 98%, which shows no differences with the micelles before lyophilization. In-vitro cytotoxicity and cellular uptake studies showed that DPT-PM has a higher degree of cytotoxicity comparing with DPT and mPEG-PLA micelles and uptake of mPEG-PLA was concentration and time-dependent. In vivo characterization of DPT-PM was done for pharmacokinetics behaviors, antitumor activity and safety. The obtained results showed significant improvement in plasma clearance bioavailability (p <0.05) and prolonged blood circulation time comparing with DPT-HP-b-CD. Moreover, mPEG-PLA micelles had a better degree of anti-tumor efficacy, this was due to better accumulation of mPEG-PLA in tumor cell via enhanced permeability and retention (EPR) effect. Therefore, DPT-PM has great clinical value, and can be expected to be a novel antitumor preparation.

After almost 25 years of expansion since its founding in late 1990, our stock market has expanded to rank second in the world in terms of market capitalisation. However, the stock market's speculative nature, information asymmetry, and extreme volatility can frequently raise serious concerns. The Fama-French five-factor (FF) model is used in this study to determine the variables affecting stock returns. and compares it to the three-factor model to see which model has a stronger ability to explain stock returns in the A-share market in the People’s Republic of China from the standpoint of asset pricing. The monthly data of A-share listed businesses for a total of 264 months between January 2000 and December 2021 are chosen as the sample in this article. Five factors are built using these data. Additionally, descriptive statistics and correlation analysis are carried out for the Chinese A-share market's five-factor model. The returns of the first four variables for regression are used to explain the returns of the fifth component in a five-factor model redundancy test.Finally, the three-factor intercept model and the five-factor intercept model are then obtained by doing a linear regression on the five-factor model. The results of the empirical test allow for the following inferences: All five factors are significant and have more explanatory power than the three factors since the CMA factor is redundant in the five-factor intercept model and is replaced by CMAO.Significant variables in the three-factor intercept model include MKT ,SMB and HML.