Evaluation of Cardioprotective Effects of Genistein against Diabetes-induced Cardiac Dysfunction in Rats

Purpose: To investigate the possible cardioprotective effects and potential pharmacological mechanism of genistein.Methods: Six-week old ZDF and lean rats were randomized into 4 groups (8 rats/group), including group 1 (control lean rats); group 2 (lean rats treated with genistein, 2.5 mg/kg); group 3 (control ZDF rats); and group 4 (ZDF treated with genistein). Two groups (2 and 4) were treated with genistein for 12 weeks, and cardiac functions and metabolic alterations were determined. Macrophage/monocyte chemo-attractant protein-1 (MCP-1), vascular cellular adhesion molecule-1 (VCAM-1) and intracellular adhesion molecule-1 (ICAM-1) secretion and their messenger RNA transcription level also were observed.Results: Genistein attenuated diabetes-induced cardiac dysfunction and pathological alterations, by improving glucose tolerance and insulin resistance; facilitating Akt activation and glucose utilization, and attenuating oxidative stress and interrelated MAP kinase and NF-κB signalling pathways. In addition, genistein treatment markedly reduced diabetic-induced MCP-1 (83.33 %), VCAM-1 (74.66 %) and ICAM-1 (71.42 %) secretion and mRNA transcription in ZDF rats.Conclusion: The results demonstrate the putative effects of genistein against cardiovascular dysfunction by improving glucose homeostasis, attenuating oxidative stress and reduced diabeticinduced endothelial dysfunction in ZDF rats. Thus, genistein is a potential candidate for the prevention of cardiovascular diseases.Keywords: Cardiac dysfunction, Genistein, Oxidative stress, Inflammatory response, Insulin resistance, Glucose toleranc

Flow and heat transfer in metal foam filled pipes under two extended Darcy models

The flow and heat transfer in pipes filled with metal foams were studied numerically.In this study,the two-equation model based on LNTE (Local Non-Thermal equilibrium) was employed as energy equations,furthermore the flow models extended by Brinkman and Brinkman-Forchheimer were employed as momentum equations respectively,and a comparison between these two models was made and analysed.The numerical results indicate that the velocity profiles under two models are different,but their temperature profiles are almost the same as each other,consequently,there are barely differences between the Nu numbers under two models.According to numerical results,the Nu number of metal-foam filled pipes is of the order of magnitude of 102～103,which is much bigger than that of bare pipes and conventional heat exchangers.The metal-foam filled pipes exhibit excellent heat transfer performance,however high pressure drop is produced at the same time.By using the program for heat transfer calculation of metal foam that is developed by us,someone can make optimization of heat transfer and pressure drop in practical applications

Knowledge-driven Meta-learning for CSI Feedback

Accurate and effective channel state information (CSI) feedback is a key technology for massive multiple-input and multiple-output systems. Recently, deep learning (DL) has been introduced for CSI feedback enhancement through massive collected training data and lengthy training time, which is quite costly and impractical for realistic deployment. In this article, a knowledge-driven meta-learning approach is proposed, where the DL model initialized by the meta model obtained from meta training phase is able to achieve rapid convergence when facing a new scenario during target retraining phase. Specifically, instead of training with massive data collected from various scenarios, the meta task environment is constructed based on the intrinsic knowledge of spatial-frequency characteristics of CSI for meta training. Moreover, the target task dataset is also augmented by exploiting the knowledge of statistical characteristics of wireless channel, so that the DL model can achieve higher performance with small actually collected dataset and short training time. In addition, we provide analyses of rationale for the improvement yielded by the knowledge in both phases. Simulation results demonstrate the superiority of the proposed approach from the perspective of feedback performance and convergence speed.Comment: arXiv admin note: text overlap with arXiv:2301.1347