Dataset Information

MacGregor2005_HypothalamicSystems

ABSTRACT: This a model from the article: Modelling the hypothalamic control of growth hormone secretion. MacGregor DJ, Leng G. J Neuroendocrinol 2005;17(12):788-803 16280026 , Abstract: Here, we construct a mathematical model of the hypothalamic systems that control the secretion of growth hormone (GH). The work extends a recent model of the pituitary GH system, adding representations of the hypothalamic GH-releasing hormone (GHRH) and somatostatin neurones, each modelled as a single synchronised unit. An unpatterned stochastic input drives the GHRH neurones generating pulses of GHRH release that trigger GH pulses. Delayed feedback from GH results in increased somatostatin release, which inhibits both GH secretion and GHRH release, producing an overall pattern of 3-h pulses of GH secretion that is very similar to the secretory profile observed in male rats. Rather than directly stimulating somatostatin release, GH feedback triggers a priming effect, increasing releasable stores of somatostatin. Varying this priming effect to reduce the effect of GH can reproduce the less pulsatile form of GH release observed in the female rat. The model behaviour is tested by comparison with experimental observations with a range of different experimental protocols involving GHRH injections and somatostatin and GH infusion. This model was taken from the CellML repository and automatically converted to SBML. The original model was: MacGregor DJ, Leng G. (2005) - version02 The original CellML model was created by: Lloyd, Catherine, May c.lloyd@aukland.ac.nz The University of Auckland The Bioengineering Institute This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

SUBMITTER: Vijayalakshmi Chelliah

PROVIDER: MODEL9811206584 | BioModels | 2005-01-01

REPOSITORIES: BioModels

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	MODEL9811206584?filename=MODEL9811206584-biopax2.owl	Owl
	MODEL9811206584?filename=MODEL9811206584-biopax3.owl	Owl
	MODEL9811206584?filename=MODEL9811206584.m	Other
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Publications

Modelling the hypothalamic control of growth hormone secretion.

MacGregor D J DJ Leng G G

Journal of neuroendocrinology 20051201 12

Here, we construct a mathematical model of the hypothalamic systems that control the secretion of growth hormone (GH). The work extends a recent model of the pituitary GH system, adding representations of the hypothalamic GH-releasing hormone (GHRH) and somatostatin neurones, each modelled as a single synchronised unit. An unpatterned stochastic input drives the GHRH neurones generating pulses of GHRH release that trigger GH pulses. Delayed feedback from GH results in increased somatostatin rele ...[more]

PMID: 16280026

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Project description:This a model from the article: Model-projected mechanistic bases for sex differences in growth hormone regulation in humans. Farhy LS, Bowers CY, Veldhuis JD. Am J Physiol Regul Integr Comp Physiol 2007 Apr;292(4):R1577-93 17185408 , Abstract: Models of physiological systems facilitate rational experimental design, inference, and prediction. A recent construct of regulated growth hormone (GH) secretion interlinks the actions of GH-releasing hormone (GHRH), somatostatin (SRIF), and GH secretagogues (GHS) with GH feedback in the rat (Farhy LS, Veldhuis JD. Am J Physiol Regul Integr Comp Physiol 288: R1649-R1663, 2005). In contrast, no comparable formalism exists to explicate GH dynamics in any other species. The present analyses explore whether a unifying model structure can represent species- and sex-defined distinctions in the human and rodent. The consensus principle that GHRH and GHS synergize in vivo but not in vitro was explicable by assuming that GHS 1) evokes GHRH release from the brain, 2) opposes inhibition by SRIF both in the hypothalamus and on the pituitary gland, and 3) stimulates pituitary GH release directly and additively with GHRH. The gender-selective principle that GH pulses are larger and more irregular in women than men was conferrable by way of 4) higher GHRH potency and 5) greater GHS efficacy. The overall construct predicts GHRH/GHS synergy in the human only in the presence of SRIF when the brain-pituitary nexus is intact, larger and more irregular GH pulses in women, and observed gender differences in feedback by GH and the single and paired actions of GHRH, GHS, and SRIF. The proposed model platform should enhance the framing and interpretation of novel clinical hypotheses and create a basis for interspecies generalization of GH-axis regulation. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Farhy LS, Bowers CY, Veldhuis JD. (2007) - version03 The original CellML model was created by: Lloyd, Catherine, May c.lloyd@aukland.ac.nz The University of Auckland The Bioengineering Institute This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

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