Endothelin receptor antagonists influence cardiovascular morphology in uremic rats

Endothelin receptor antagonists influence cardiovascular morphology in uremic rats.BackgroundIt is generally held that renal failure results in blood pressure (BP)-independent structural changes of the myocardium and the vasculature. The contribution, if any, of endothelin (ET) to these changes has been unknown.MethodsWe morphometrically studied random samples of the left ventricle myocardium and small intramyocardial arteries in subtotally (5/6) nephrectomized (SNx) male Sprague-Dawley rats treated with either the selective ETA receptor antagonist BMS182874 (30mg/kg/day) or the nonselective ETA/ETB receptor antagonist Ro46-2005 (30mg/kg/day) in comparison with either sham-operated rats, untreated SNx, or SNx rats treated with the angiotensin-converting enzyme inhibitor trandolapril (0.1mg/kg/day).ResultsEight weeks later, systolic BP was lower in trandolapril-treated SNx compared with untreated SNx animals. No decrease in BP was seen following either ET receptor antagonist at the dose used. A significantly increased volume density of the myocardial interstitium was found in untreated SNx rats as compared with sham-operated controls. Such interstitial expansion was prevented by trandolapril and either ET receptor antagonist. SNx caused a substantial increase in the wall thickness of small intramyocardial arteries. The increase was prevented by trandolapril or BMS182874 treatment. The arteriolar wall:lumen ratio was significantly lower in all treated groups when compared with untreated SNx. In contrast, only trandolapril, but not the ET receptor antagonists, attenuated thickening of the aortic media in SNx animals.ConclusionsThe ETA-selective and ETA/ETB-nonselective receptor antagonists appear to prevent development of myocardial fibrosis and structural changes of small intramyocardial arteries in experimental chronic renal failure. This effect is independent of systemic BP

Classical Cosmological Tests for Galaxies of the Hubble Ultra Deep Field

Images of the Hubble Ultra Deep Field are analyzed to obtain a catalog of galaxies for which the angular sizes, surface brightness, photometric redshifts, and absolute magnitudes are found. The catalog contains a total of about 4000 galaxies identified at a high signal-to-noise ratio, which allows the cosmological relations angular size{redshift and surface brightness-redshift to be analyzed. The parameters of the evolution of linear sizes and surface brightness of distant galaxies in the redshift interval 0.5-6.5 are estimated in terms of a grid of cosmological models with different density parameters. The distribution of photometric redshifts of galaxies is analyzed and possible superlarge inhomogeneities in the radial distribution of galaxies are found with scale lengths as large as 2000 Mpc.Comment: 23 pages, 9 figures, 1 tabl

Downloading articles by Russian researchers using the SCI-hub resource

On the basis of the 28 million downloaded articles posted by J. Bohannon and A. Elbakyan on the Internet on the Sci-Hub resource for the period from September 1, 2015 to February 29, 2016, about 1.5 million articles downloaded by Russian researchers were identifie

The density of robotization of agriculture in Russia and its regions

According to the Rosstat data a share of agricultural organizations which introduce technological innovations is low (2.7%). The study aims to determine the density of agricultural robotization in Russia and its regions. The density of agricultural robotization is influenced by the average annual number of employees in the industry, which was 5802 thousand people in 2013-2019 and decreased by 22% over the studied period. The data show that 435 units of robotics were introduced in agricultural organizations in the Russian Federation in 2006-2019. The vast majority of robotics used in agriculture in Russia is milking robots mainly by European manufacturers. Robotics is used in the agricultural sector in the Central (185 units), Volga (95 units), NorthWest (66 units) and Ural (68 units) federal districts. The introduction of robotics in agriculture in the Southern, Siberian and North Caucasian federal districts is practically not carried out. The highest density of agricultural robotization is observed in the Kaluga (42.67 robots per 10 thousand employees in the industry), the Ryazan (14.8), the Sverdlovsk (6.32) and the Vologda Region (6.21). The results of the study will allow development of a mechanism that promotes priority robotization of rural areas where robotization is slow or is not carried out to prevent their technological lagging behind and the further development of a stagnation processes. The scientific significance of the research results will contribute to the development of theoretical aspects of robotics application in agriculture and the spatial aspects of robotization. © 2020, World Scientific and Engineering Academy and Society. All rights reserved.The study was funded by RFBR, a project number is 20-010-00636 А «Spatial development of agricultural robotization in Russia: trends, factors, mechanisms

The density of robotization of agriculture in Russia and its regions

According to the Rosstat data a share of agricultural organizations which introduce technological innovations is low (2.7%). The study aims to determine the density of agricultural robotization in Russia and its regions. The density of agricultural robotization is influenced by the average annual number of employees in the industry, which was 5802 thousand people in 2013-2019 and decreased by 22% over the studied period. The data show that 435 units of robotics were introduced in agricultural organizations in the Russian Federation in 2006-2019. The vast majority of robotics used in agriculture in Russia is milking robots mainly by European manufacturers. Robotics is used in the agricultural sector in the Central (185 units), Volga (95 units), NorthWest (66 units) and Ural (68 units) federal districts. The introduction of robotics in agriculture in the Southern, Siberian and North Caucasian federal districts is practically not carried out. The highest density of agricultural robotization is observed in the Kaluga (42.67 robots per 10 thousand employees in the industry), the Ryazan (14.8), the Sverdlovsk (6.32) and the Vologda Region (6.21). The results of the study will allow development of a mechanism that promotes priority robotization of rural areas where robotization is slow or is not carried out to prevent their technological lagging behind and the further development of a stagnation processes. The scientific significance of the research results will contribute to the development of theoretical aspects of robotics application in agriculture and the spatial aspects of robotization. © 2020, World Scientific and Engineering Academy and Society. All rights reserved.The study was funded by RFBR, a project number is 20-010-00636 А «Spatial development of agricultural robotization in Russia: trends, factors, mechanisms