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 Postdoc Neuromathematics - Paris
web ( 26 de Febrero del 2010 )

Environment SISYPHE (SIgnals and SYstems in PHysiology and Engineering) deals with questions raised by some complex dynamical systems issued from Physiology and Engineering: modeling; identification and observation from signals; control. We consider multi-scale or networked dynamical systems involving exchanges of energy or control information among scales and subsystems. Most studies are motivated by the cardiovascular and reproductive systems or by energy conversion systems for low-emission vehicles. REGATE (REgulation of the GonAdoTropE axis) is interested in the multi-level and multi-scale modeling, simulation and control of the gonadotrope axis (also called hypothalamo-hypophyso-gonadal axis). The project articulates on the coupling between different mathematical (mainly: conservation laws and dynamical systems) and computing (mainly: temporal logic and model checking) formalisms with biological knowledge and data. Missions The neuroendocrine axes play a major part in controlling the main physiological functions (metabolism, growth, development and reproduction). The connection between the central nervous system and the endocrine system takes place on the level of the hypothalamus, where endocrine neurons are able to secrete hormones that target the pituitary gland. The reproductive axis is under the control of the gonadotropin-releasing hormone (GnRH), which is secreted in pulses from specific hypothalamic areas. GnRH effects on its target cells depend critically on pulse frequency and ultimately results in the differential secretion patterns of the luteinizing hormone (LH) and follicle-stimulating hormone (FSH). Recent papers have focused on different steps in the GnRH signaling cascade to try and explain frequency dependence: autocrine/paracrine actions of pituitary polypeptides [1], competition between different MAPK cascades [2] or Ca2+/NFAT signaling pathway [3]. No comprehensive mechanism for frequency decoding has yet emerged and genuine frequency effects can still not be distinguished from exposure to different cumulative GnRH levels. The post-doc work will first consist in building and analyzing a minimalist model allowing for frequency decoding in the framework of dynamical systems, and based on adequate generalization of the well-known Integrate and Fire model. The second step will be dedicated to make the bridge between this phenomenological model and the key biochemical nodes of the GnRH signaling network. [1] R Bertram and X-Y Li. A mathematical model for the actions of activin, inhibin and follistatin on pituitary gonadotrophs. Bull. Math. Biol., 2008, 70: 2211-2228. [2] S Lim et al. Negative feedback governs gonadotrope frequency-decoding of gonadotropin releasing hormone pulse-frequency. PLoS one, 2009, 4 : e7244. [3] SP Armstrong et al. Pulsatile and sustained gonadotropin-releasing hormone (GnRH) receptor signaling: Does the Ca2+/NFAT signaling pathway decode GnRH pulse frequency? J. Biol. Chem., 2009, 284:35746-57. Skills and Profile Applied Mathematics (dynamical systems), Computational neurosciences

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