11 research outputs found

    NPY Neuron-Specific Y2 Receptors Regulate Adipose Tissue and Trabecular Bone but Not Cortical Bone Homeostasis in Mice

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    BACKGROUND: Y2 receptor signalling is known to be important in neuropeptide Y (NPY)-mediated effects on energy homeostasis and bone physiology. Y2 receptors are located post-synaptically as well as acting as auto receptors on NPY-expressing neurons, and the different roles of these two populations of Y2 receptors in the regulation of energy homeostasis and body composition are unclear. METHODOLOGY/PRINCIPAL FINDINGS: We thus generated two conditional knockout mouse models, Y2(lox/lox) and NPYCre/+;Y2(lox/lox), in which Y2 receptors can be selectively ablated either in the hypothalamus or specifically in hypothalamic NPY-producing neurons of adult mice. Specific deletion of hypothalamic Y2 receptors increases food intake and body weight compared to controls. Importantly, specific ablation of hypothalamic Y2 receptors on NPY-containing neurons results in a significantly greater adiposity in female but not male mice, accompanied by increased hepatic triglyceride levels, decreased expression of liver carnitine palmitoyltransferase (CPT1) and increased expression of muscle phosphorylated acetyl-CoA carboxylase (ACC). While food intake, body weight, femur length, bone mineral content, density and cortical bone volume and thickness are not significantly altered, trabecular bone volume and number were significantly increased by hypothalamic Y2 deletion on NPY-expressing neurons. Interestingly, in situ hybridisation reveals increased NPY and decreased proopiomelanocortin (POMC) mRNA expression in the arcuate nucleus of mice with hypothalamus-specific deletion of Y2 receptors in NPY neurons, consistent with a negative feedback mechanism between NPY expression and Y2 receptors on NPY-ergic neurons. CONCLUSIONS/SIGNIFICANCE: Taken together these data demonstrate the anti-obesogenic role of Y2 receptors in the brain, notably on NPY-ergic neurons, possibly via inhibition of NPY neurons and concomitant stimulation of POMC-expressing neurons in the arcuate nucleus of the hypothalamus, reducing lipogenic pathways in liver and/or skeletal muscle in females. These data also reveal as an anti-osteogenic effect of Y2 receptors on hypothalamic NPY-expressing neurons on trabecular but not on cortical bone

    Balancing a Mixed-Model Assembly System in the Footwear Industry

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    Part 7: Operations Planning, Scheduling and ControlInternational audiencePortuguese footwear industry has improved dramatically to become one of the main world players. This work is part of a project in cooperation with a large footwear company, operating a new automated assembly equipment, integrating various lines. Balancing such lines implies going from an almost manual preparation executed by experienced operators, to a planning supported by optimisation systems. These complex mixed-model lines have distinctive characteristics, which make balancing a unique problem. The paper proposes the ASBsm – Assembly System Balancing Solution Method, a new method that integrates a constructive heuristic and an improvement heuristic, which takes inspiration from Tabu Search. The solutions obtained, based on real instances, are quite encouraging when compared with other effected factory solutions. Consequently, the balances obtained by ASBsm are now being implemented and articulated with sequencing methods

    Generalized net models of basic genetic algorithm operators

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    © Springer International Publishing Switzerland 2016. Generalized nets (GN) are applied here to describe some basic operators of genetic algorithms, namely selection, crossover and mutation and different functions for selection (roulette wheel selection method and stochastic universal sampling), different crossover techniques (one-point crossover, two-point crossover, and “cut and splice” technique), as well as mutation operator (mutation operator of the Breeder genetic algorithm). The resulting GN models can be considered as separate modules, but they can also be accumulated into a single GN model to describe a whole genetic algorithm
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