Papaverine-induced and endothelium-dependent relaxation in the isolated rat aortic strip

PubMedID: 10488403In the present study, we aimed to obtain further evidence in favour of the hypothesis that nitric oxide (NO) is a major mediator of endothelium-dependent vasorelaxation and to clarify whether NO plays a role in papaverine-induced vasorelaxation. The relaxant effects of acetylcholine (Ach), acidified NaNO2 or papaverine were investigated on isolated helical strips of the rat thoracic aorta precontracted with phenylephrine in an organ bath containing Krebs solution aerated with 95% O2 and 5% CO2. The relaxation was quantified as % peak reduction of phenylephrine contracture. Saponin abolished the relaxant effects of Ach completely whereas it had no effect on the responses to acidified NaNO2 or papaverine. NG-nitro-L-arginine (L-NOARG) reduced the effects of Ach significantly, but it was ineffective on the relaxation induced by acidified NaNO2. The inhibitory action of L-NOARG was partly restored by L-arginine, but not by D-arginine. Hemoglobin, hydroxocobalamin and hydroquinone exhibited significant inhibition on the relaxation evoked by Ach and acidified NaNO2. L-NOARG, hydroxocobalamin and hydroquinone caused only limited but significant decrease in the relaxation due to papaverine. This phenomenon was also observed by increasing phenylephrine concentration leading to an enhancement in the contraction. Our findings strongly support the view that Ach-induced relaxation of rat aorta strips is mediated by free NO released from the endothelium and the results suggest that NO may indirectly contribute to papaverine-induced relaxation

Smart4RES: Next generation solutions for renewable energy forecasting and applications with focus on distribution grids

This paper presents the solutions on renewable energy forecasting proposed by the Horizon2020 Project Smart4RES. The ambition of the project is twofold: (1) increase substantially the performance of short-term forecasting models of Renewable Energy Sources (RES) production and associated weather forecasting and (2) optimize decisions subject to RES uncertainty in power systems and electricity markets. Developments are based on latest advances in meteorology and original use of data science (combination of multiple data sources, data-driven approaches for trading and grid management). Finally, solutions such as flexibility forecast of distributed resources and data markets are oriented towards value for power system stakeholders. Although the project covers a broad scope, in this paper we focus on a selection of use cases that concern the integration of renewables in distribution grids