ATP-modulated K+ channels sensitive to antidiabetic sulfonylureas are present in adenohypophysis and are involved in growth hormone release.

The adenohypophysis contains high-affinity binding sites for antidiabetic sulfonylureas that are specific blockers of ATP-sensitive K+ channels. The binding protein has a M(r) of 145,000 +/- 5000. The presence of ATP-sensitive K+ channels (26 pS) has been demonstrated by electrophysiological techniques. Intracellular perfusion of adenohypophysis cells with an ATP-free medium to activate ATP-sensitive K+ channels induces a large hyperpolarization (approximately 30 mV) that is antagonized by antidiabetic sulfonylureas. Diazoxide opens ATP-sensitive K+ channels in adenohypophysis cells as it does in pancreatic beta cells and also induces a hyperpolarization (approximately 30 mV) that is also suppressed by antidiabetic sulfonylureas. As in pancreatic beta cells, glucose and antidiabetic sulfonylureas depolarize the adenohypophysis cells and thereby indirectly increase Ca2+ influx through L-type Ca2+ channels. The K+ channel opener diazoxide has an opposite effect. Opening ATP-sensitive K+ channels inhibits growth hormone secretion and this inhibition is eliminated by antidiabetic sulfonylureas

The Impact of New Mobility Modes on a City: A Generic Approach Using ABM

International audienceMobility is a key issue for city planners. Being able to evaluate the impact of its evolution is complex and involves many factors including new technologies like electric cars, autonomous vehicles and also new social habits like vehicle sharing. We need a better understanding of different scenarios to improve the quality of long-term decisions. Computer simulations can be a tool to better understand this evolution, to discuss different solutions and to communicate the implications of different decisions. In this paper, we propose a new generic model that creates an artificial micro-world which allows the modeler to create and modify new mobility scenarios in a quick and easy way. This not only helps to better understand the impact of new mobility modes on a city, but also fosters a better-informed discussion of different futures. Our model is based on the agent-based paradigm using the GAMA Platform. It takes into account different mobility modes, people profiles, congestion and traffic patterns. In this paper, we review an application of the model of the city of Cambridge