Low Arginine Plasma Levels do not Aggravate Renal Blood Flow after Experimental Renal Ischaemia/reperfusion

AbstractBackground: ischaemic renal dysfunction is present in many clinical settings, including cardiovascular surgery. Renal hypoperfusion seems to be the most important pathophysiologic mechanism. Arginine plasma levels are rate limiting for NO synthesis, and low arginine plasma levels are seen after major vascular surgery. Objective: to establish the effects of low arginine plasma levels on renal blood flow after renal ischaemia/reperfusion. Design: Wistar rats were used in this unilateral renal ischaemia/reperfusion model. After 70 min of ischaemia, the kidney was reperfused for 150 min. Arginase infusion was used to lower arginine plasma levels. Blood flow measurement was performed at the end of the experiment using radiolabelled microspheres. Additional experiments were performed for histopathology. Results: arginase efficiently decreased arginine plasma levels to about 50% of normal. There was a lower blood flow in the ischaemic kidney than the contralateral (non-ischaemic) kidney. Lowering arginine plasma levels did not reduce renal blood flow in the ischaemic kidney. Renal histopathology was not influenced by lowered arginine plasma levels. Conclusions: lowering arginine plasma levels did not affect blood flow or histology following renal ischaemia and reperfusion

An Agent Model for Analysis of Human Performance Quality

A human's performance in a complex task is highly dependent on the demands of the task, in the sense that highly demanding situations will often cause a degradation of performance. To maintain performance quality usually extra effort has to be contributed. However, the resources for such extra effort available to the human are limited. In this paper an agent model is proposed in which different types of relations between effort, task demands and performance quality can be used to analyse the human's performance quality. It is illustrated how a support agent incorporating this model can support a human based on different performance criteria. The agent model thus allows to build agent applications that provide optimal support depending on a specific situation and goal of the task. © 2010 IEEE