The left ventricular contractility of the rat heart is modulated by changes in flow and a1-adrenoceptor stimulation

Myocardial contractility depends on several mechanisms such as coronary perfusion pressure (CPP) and flow as well as on a1-adrenoceptor stimulation. Both effects occur during the sympathetic stimulation mediated by norepinephrine. Norepinephrine increases force development in the heart and produces vasoconstriction increasing arterial pressure and, in turn, CPP. The contribution of each of these factors to the increase in myocardial performance needs to be clarified. Thus, in the present study we used two protocols: in the first we measured mean arterial pressure, left ventricular pressure and rate of rise of left ventricular pressure development in anesthetized rats (N = 10) submitted to phenylephrine (PE) stimulation before and after propranolol plus atropine treatment. These observations showed that in vivo a1-adrenergic stimulation increases left ventricular-developed pressure (P<0.05) together with arterial blood pressure (P<0.05). In the second protocol, we measured left ventricular isovolumic systolic pressure (ISP) and CPP in Langendorff constant flow-perfused hearts. The hearts (N = 7) were perfused with increasing flow rates under control conditions and PE or PE + nitroprusside (NP). Both CPP and ISP increased (P<0.01) as a function of flow. CPP changes were not affected by drug treatment but ISP increased (P<0.01). The largest ISP increase was obtained with PE + NP treatment (P<0.01). The results suggest that both mechanisms, i.e., direct stimulation of myocardial a1-adrenoceptors and increased flow, increased cardiac performance acting simultaneously and synergistically.

An optical flow-based sensing system for reactive mobile robot navigation

This work discusses the use of optical flow to generate the sensorial information a mobile robot needs to react to the presence of obstacles when navigating in a non-structured environment. A sensing system based on optical flow and time-to-collision calculation is here proposed and experimented, which accomplishes two important paradigms. The first one is that all computations are performed onboard the robot, in spite of the limited computational capability available. The second one is that the algorithms for optical flow and time-to-collision calculations are fast enough to give the mobile robot the capability of reacting to any environmental change in real-time. Results of real experiments in which the sensing system here proposed is used as the only source of sensorial data to guide a mobile robot to avoid obstacles while wandering around are presented, and the analysis of such results allows validating the proposed sensing system.