Effect of restraint stress on 2,3,7,8 tetrachloro dibenzo-p-dioxin induced testicular and epididymal toxicity in rats

Dioxins like 2,3,7,8 tetrachlorodibenzo-p—dioxin (TCDD) impair male reproductive system by increasing the generation of reactive oxygen species (ROS). Glucocorticoids have been found to suppress male reproductive function and also influence TCDD pathway. As stress is characterized by an increase in the level and activity of glucocorticoids, the present experiments were conducted to evaluate the effect of restraint stress on TCDDinduced testicular and epididymal toxicity. Adult male Wistar rats were subjected to either restraint stress (5 hours/day) or TCDD treatment (100 ng/kg b.w./day) or both for 15 days. Restraint stress or TCDD treatment raised the serum level of corticosterone and suppressed the testicular level of steroidogenic acute regulatory (StAR) protein and serum level of testosterone significantly. In the testis and epididymis, restraint stress or TCDD treatment raised the levels of lipid peroxidation and hydrogen peroxide and suppressed the activities of antioxidant enzymes significantly. In rats subjected to both restraint stress and TCDD treatment, a significant increase in the serum level of corticosterone and a significant decrease in the testicular level of StAR protein and serum level of testosterone were observed as compared to rats treated with TCDD alone. A significant increase in the levels of lipid peroxidation and hydrogen peroxide and a significant decrease in the activities of antioxidant enzymes were observed in the testis and epididymis of rats subjected to both restraint stress and TCDD treatment as compared to TCDD alone treated rats. Thus, restraint stress potentiates the adverse effects of TCDD on male reproductive organs.

Drug Repositioning Using Computer-aided Drug Design (CADD)

Drug repositioning is a method of using authorized drugs for other unusually complex diseases. Compared to new drug development, this method is fast, low in cost, and effective. Through the use of outstanding bioinformatics tools, such as computer-aided drug design (CADD), computer strategies play a vital role in the re-transformation of drugs. The use of CADD's special strategy for target-based drug reuse is the most promising method, and its realization rate is high. In this review article, we have particularly focused on understanding the various technologies of CADD and the use of computer-aided drug design for target-based drug reuse, taking COVID-19 and cancer as examples. Finally, it is concluded that CADD technology is accelerating the development of repurposed drugs due to its many advantages, and there are many facts to prove that the new ligand-targeting strategy is a beneficial method and that it will gain momentum with the development of technology.

Application of ANFIS for the Selection of Optimal Wire-EDM Parameters While Machining Ti-6Al-4V Alloy and Multi-Parametric Optimization Using GRA Method

The applications of artificial intelligence (AI) are becoming more popular and relevant research have been conducted in every field of engineering and science by using these AI techniques. Therefore, this research aims to examine the influence of wire electric-discharge machining (WEDM) parameters on performance parameters to improve the productivity with a higher surface finish of titanium alloy (Ti-6Al-4V) by using the artificial intelligent technique. In this experimental analysis, the Adaptive Network Based fuzzy Inference System (ANFIS) model has been highly-developed and the multi-parametric optimization has been done to find the optimal solution for the machining of the titanium superalloy. The peak current (Ip), taper angle, pulse on time (Ton), pulse of time (Toff) and the dielectric fluid flow rate were selected as operation constraints to conduct experimental trials. The surface roughness (SR) and MRR were considered as output responses. The influence on machining performance has been analyzed by an ANFIS model and the developed model was validated with the full factorial regression models. The developed models showed the minimum mean percentage error and the optimized parameters by the GRA method showed the considerable improvement in the process.