Hypothalamic K(ATP) channels control hepatic glucose production.
ABSTRACT Obesity is the driving force behind the worldwide increase in the prevalence of type 2 diabetes mellitus. Hyperglycaemia is a hallmark of diabetes and is largely due to increased hepatic gluconeogenesis. The medial hypothalamus is a major integrator of nutritional and hormonal signals, which play pivotal roles not only in the regulation of energy balance but also in the modulation of liver glucose output. Bidirectional changes in hypothalamic insulin signalling therefore result in parallel changes in both energy balance and glucose metabolism. Here we show that activation of ATP-sensitive potassium (K(ATP)) channels in the mediobasal hypothalamus is sufficient to lower blood glucose levels through inhibition of hepatic gluconeogenesis. Finally, the infusion of a K(ATP) blocker within the mediobasal hypothalamus, or the surgical resection of the hepatic branch of the vagus nerve, negates the effects of central insulin and halves the effects of systemic insulin on hepatic glucose production. Consistent with these results, mice lacking the SUR1 subunit of the K(ATP) channel are resistant to the inhibitory action of insulin on gluconeogenesis. These findings suggest that activation of hypothalamic K(ATP) channels normally restrains hepatic gluconeogenesis, and that any alteration within this central nervous system/liver circuit can contribute to diabetic hyperglycaemia.
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ABSTRACT: The cerebellar model articulation controller (CMAC) neural network (NN) is a well-established computational model of the human cerebellum. Nevertheless, there are two major drawbacks associated with the uniform quantization scheme of the CMAC network. They are the following: 1) a constant output resolution associated with the entire input space and 2) the generalization-accuracy dilemma. Moreover, the size of the CMAC network is an exponential function of the number of inputs. Depending on the characteristics of the training data, only a small percentage of the entire set of CMAC memory cells is utilized. Therefore, the efficient utilization of the CMAC memory is a crucial issue. One approach is to quantize the input space nommiformly. For existing nommiformly quantized CMAC systems, there is a tradeoff between memory efficiency and computational complexity. Inspired by the underlying organizational mechanism of the human brain, this paper presents a novel CMAC architecture named hierarchically- clustered adaptive quantization CMAC (HCAQ-CMAC). HCAQ-CMAC employs hierarchical clustering for the nonuniform quantization of the input space to identify significant input segments and subsequently allocating more memory cells to these regions. The stability of the HCAQ-CMAC network is theoretically guaranteed by the proof of its learning convergence. The performance of the proposed network is subsequently benchmarked against the original CMAC network, as well as two other existing CMAC variants on two real-life applications, namely, automated control of car maneuver and modeling of the human blood glucose dynamics. The experimental results have demonstrated that the HCAQ-CMAC network offers an efficient memory allocation scheme and improves the generalization and accuracy of the network output to achieve better or comparable performances with smaller memory usages.IEEE Transactions on Neural Networks 12/2007; 18(6):1658-82. DOI:10.1109/TNN.2007.900810 · 2.95 Impact Factor
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ABSTRACT: Insulin action in the central nervous system regulates energy homeostasis and glucose metabolism. To define the insulin-responsive neurons that mediate these effects, we generated mice with selective inactivation of the insulin receptor (IR) in either pro-opiomelanocortin (POMC)- or agouti-related peptide (AgRP)-expressing neurons of the arcuate nucleus of the hypothalamus. While neither POMC- nor AgRP-restricted IR knockout mice exhibited altered energy homeostasis, insulin failed to normally suppress hepatic glucose production during euglycemic-hyperinsulinemic clamps in AgRP-IR knockout (IR(DeltaAgRP)) mice. These mice also exhibited reduced insulin-stimulated hepatic interleukin-6 expression and increased hepatic expression of glucose-6-phosphatase. These results directly demonstrate that insulin action in POMC and AgRP cells is not required for steady-state regulation of food intake and body weight. However, insulin action specifically in AgRP-expressing neurons does play a critical role in controlling hepatic glucose production and may provide a target for the treatment of insulin resistance in type 2 diabetes.Cell metabolism 07/2007; 5(6):438-49. DOI:10.1016/j.cmet.2007.05.004 · 16.75 Impact Factor
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ABSTRACT: Leptin has pleiotropic effects on glucose homeostasis and feeding behavior. Here, we validate the use of a cell-permeable phosphopeptide that blocks STAT3 activation in vivo. The combination of this biochemical approach with stereotaxic surgical techniques allowed us to pinpoint the contribution of hypothalamic STAT3 to the acute effects of leptin on food intake and glucose homeostasis. Leptin's ability to acutely reduce food intake critically depends on intact STAT3 signaling. Likewise, hypothalamic signaling of leptin through STAT3 is required for the acute effects of leptin on liver glucose fluxes. Lifelong obliteration of STAT3 signaling via the leptin receptor in mice (s/s mice) results in severe hepatic insulin resistance that is comparable to that observed in db/db mice, devoid of leptin receptor signaling. Our results demonstrate that the activation of the hypothalamic STAT3 pathway is an absolute requirement for the effects of leptin on food intake and hepatic glucose metabolism.Cell Metabolism 08/2006; 4(1):49-60. DOI:10.1016/j.cmet.2006.04.014 · 16.75 Impact Factor