1.The effects of aerobic exercise on endothelial nitric oxide synthase uncoupling in the myocardium of spontaneously hypertensive rats
Guan KOU ; Zhen WAN ; Xiaozhe LIU ; Xiaoyang NIU
Chinese Journal of Physical Medicine and Rehabilitation 2024;46(3):193-198
Objective:To observe any effect of regular aerobic exercise on cardiac remodeling in spontaneously hypertensive rats (SHR) and explore the mechanism of endothelial nitric oxide synthase (eNOS) uncoupling.Methods:Thirty 6-week-old healthy male SHR were divided into a sedentary group and an exercise group, each of 15. Another ten age- and sex-matched Wistar-Kyoto rats were set as a normal control group. The animals in the normal control and sedentary groups were fed quietly in their cages, and those in the exercise group performed moderate intensity treadmill exercise for 8 weeks (5 times per week). Forty-eight hours after the last training, echocardiography was applied to document cardiac structure and function in both groups. Wheat germ agglutinin staining and Picrosirius Red staining were used to obtain the cardiomyocyte cross sectional areas (CSAs) and interstitial collagen volume fractions (CVFs) of all of the mice. The rates of cardiomyocyte apoptosis were measured using TUNEL staining, and myocardial tetrahydrobiopterin (BH4) content was measured using high-performance liquid chromatography. Total eNOS, eNOS dimer and eNOS monomer protein expression in the myocardia were detected using western blotting.Results:Compared with the normal control group, the left ventricular wall thickness (LVWT), myocardial CSA, CVF, apoptosis of cardiomyocytes and eNOS monomer levels were significantly higher in the sedentary group, on average. But the end-diastolic diameter (LVEDD) and ejection fraction (LVEF) of the left ventricle and the levels of eNOS dimer and myocardial BH4 and the eNOS dimer/monomer ratio tended to be lower. Comparing the exercise group with the sedentary group, the average LVEDD, LVEF, eNOS dimer, eNOS dimer/monomer ratio and myocardial BH4 content were significantly higher in the exercise group, but the myocardial CVF, cardiomyocyte apoptosis and eNOS monomer levels were significantly lower. LVWT and CSA were not significantly different. There were no significant differences in the total eNOS protein levels among the three groups.Conclusion:Regular aerobic exercise might improve cardiac remodeling in cases of spontaneous hypertension regulating eNOS uncoupling, at least in rats.
2.Drug target inference by mining transcriptional data using a novel graph convolutional network framework.
Feisheng ZHONG ; Xiaolong WU ; Ruirui YANG ; Xutong LI ; Dingyan WANG ; Zunyun FU ; Xiaohong LIU ; XiaoZhe WAN ; Tianbiao YANG ; Zisheng FAN ; Yinghui ZHANG ; Xiaomin LUO ; Kaixian CHEN ; Sulin ZHANG ; Hualiang JIANG ; Mingyue ZHENG
Protein & Cell 2022;13(4):281-301
A fundamental challenge that arises in biomedicine is the need to characterize compounds in a relevant cellular context in order to reveal potential on-target or off-target effects. Recently, the fast accumulation of gene transcriptional profiling data provides us an unprecedented opportunity to explore the protein targets of chemical compounds from the perspective of cell transcriptomics and RNA biology. Here, we propose a novel Siamese spectral-based graph convolutional network (SSGCN) model for inferring the protein targets of chemical compounds from gene transcriptional profiles. Although the gene signature of a compound perturbation only provides indirect clues of the interacting targets, and the biological networks under different experiment conditions further complicate the situation, the SSGCN model was successfully trained to learn from known compound-target pairs by uncovering the hidden correlations between compound perturbation profiles and gene knockdown profiles. On a benchmark set and a large time-split validation dataset, the model achieved higher target inference accuracy as compared to previous methods such as Connectivity Map. Further experimental validations of prediction results highlight the practical usefulness of SSGCN in either inferring the interacting targets of compound, or reversely, in finding novel inhibitors of a given target of interest.
Drug Delivery Systems
;
Proteins
;
Transcriptome