Ursolic Acid Florotriazole Treatment Causes Inhibition of Squamous Cell Carcinoma through Fas Signaling Pathway

Purpose: To investigate the effect of ursolic acid florotriazole (UFT), on SCC-15 oral squamous cancer cells.Methods: Confocal laser microscope with a 490 nm argon laser was used to record the fluorescence of the cells and capture the images. Flow cytometry and Cell Quest program were used to analyze the DNA content of the stained cells. Apoptosis was characterized by YO-PRO-1 staining.Results: Treatment of SCC-15 cells with UFT for 48 h significantly reduced cell viability in a dosedependent manner. At 20 μg/mL concentration of UFT, SCC-15, cell viability was reduced to 19 % compared to 100 % in the untreated cells (p = 0.0002). UFT treatment enhanced the proportion of apoptotic cells which was evident from YO-PRO-1 staining. In UFT-treated cultures, the population of cells in sub-G1 phase increased to 38.54 % compared to 7.32 % for control after 48 h. Expression of Fas in UFT-treated cells was also higher (p = 0.0002) than in untreated cells. In C3H/HeJ mice, administration of UFT daily for 14 days caused a significant (p = 0.0002) reduction in tumor volume and weight after 30 days of SCC-15 carcinoma cell administration.Conclusion: UFT treatment inhibits viability and induces apoptosis in squamous cell carcinoma cells through suppression of Fas expression. Therefore, UFT may be useful for the treatment of squamous cell cancer.Keywords: Ursolic acid florotriazole, Squamous cell cancer, Fas expression, Tumor volume, Cell viability, Apoptosi

SCOPE: Scalable Composite Optimization for Learning on Spark

Many machine learning models, such as logistic regression~(LR) and support vector machine~(SVM), can be formulated as composite optimization problems. Recently, many distributed stochastic optimization~(DSO) methods have been proposed to solve the large-scale composite optimization problems, which have shown better performance than traditional batch methods. However, most of these DSO methods are not scalable enough. In this paper, we propose a novel DSO method, called \underline{s}calable \underline{c}omposite \underline{op}timization for l\underline{e}arning~({SCOPE}), and implement it on the fault-tolerant distributed platform \mbox{Spark}. SCOPE is both computation-efficient and communication-efficient. Theoretical analysis shows that SCOPE is convergent with linear convergence rate when the objective function is convex. Furthermore, empirical results on real datasets show that SCOPE can outperform other state-of-the-art distributed learning methods on Spark, including both batch learning methods and DSO methods

Effects of Phosphorus Accumulation in Soil with the Utilization Ages of the Vegetable Greenhouses in the Suburb of Shenyang

AbstractThe accumulation of phosphorus in different utilization age (0, 1, 2, 3, 5, 13-year) vegetable greenhouses soil with multi-point mixed samples was examined in Damintun Town of Shenyang. The results showed that the content of P of all samples was increased with the utilization ages of the vegetable greenhouses. For all the samples, the concentration of TP and Olsen-P in the 0-40cm layer was higher than that in the 40-120cm. Compared with other samples, the content of TP and Olsen-P of 13 years of vegetable greenhouse soil is the highest throughout the 0-120cm. In the 0-20cm layer, the TP concentrations in 13-year vegetable greenhouse soil is 4 times higher than that in the open vegetable land, and the concentration of Olsen-P range from 23.87mg kg-1 in bare land soil to 102.13mg kg-1 in 13-year vegetable greenhouse soil. These results demonstrated that long-term continuous P input from chemical fertilizers and manure can cause P accumulation in soils and enrich in topsoil