BioModelsapplication/xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045.pdfhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045-biopax2.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045-biopax3.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045_url.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045_urn.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045.vcmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045.mhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045.scihttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045.pnghttps://www.ebi.ac.uk/biomodels/model/download/MODEL1006230045?filename=MODEL1006230045.xppprimaryOK200Camille LaibeNon-curatedordinary differential equation modelL2V4https://www.ebi.ac.uk/biomodels/MODEL100623004511035997falseBioModelsSBMLModelsSchlosser2000 GlucoseInsulinFeedback BetaCells2000MODEL1006230045P M Schlosser, J F SelgradeP M Schlosser11035997, Increasing concerns that environmental contaminants may disrupt the endocrine system require development of mathematical tools to predict the potential for such compounds to significantly alter human endocrine function. The endocrine system is largely self-regulating, compensating for moderate changes in dietary phytoestrogens (e.g., in soy products) and normal variations in physiology. However, severe changes in dietary or oral exposures or in health status (e.g., anorexia), can completely disrupt the menstrual cycle in women. Thus, risk assessment tools should account for normal regulation and its limits. We present a mathematical model for the synthesis and release of luteinizing hormone (LH) and follicle-stimulating hormone (FSH) in women as a function of estrogen, progesterone, and inhibin blood levels. The model reproduces the time courses of LH and FSH during the menstrual cycle and correctly predicts observed effects of administered estrogen and progesterone on LH and FSH during clinical studies. The model should be useful for predicting effects of hormonally active substances, both in the pharmaceutical sciences and in toxicology and risk assessment.. null, 108 Suppl 5. Chemical Industry Institute of Technology, Research Triangle Park, North Carolina 27709, USA. schlosser@ciit.orglaibe@ebi.ac.ukEMBL-EBIIncreasing concerns that environmental contaminants may disrupt the endocrine system require development of mathematical tools to predict the potential for such compounds to significantly alter human endocrine function. The endocrine system is largely self-regulating, compensating for moderate changes in dietary phytoestrogens (e.g., in soy products) and normal variations in physiology. However, severe changes in dietary or oral exposures or in health status (e.g., anorexia), can completely disrupt the menstrual cycle in women. Thus, risk assessment tools should account for normal regulation and its limits. We present a mathematical model for the synthesis and release of luteinizing hormone (LH) and follicle-stimulating hormone (FSH) in women as a function of estrogen, progesterone, and inhibin blood levels. The model reproduces the time courses of LH and FSH during the menstrual cycle and correctly predicts observed effects of administered estrogen and progesterone on LH and FSH during clinical studies. The model should be useful for predicting effects of hormonally active substances, both in the pharmaceutical sciences and in toxicology and risk assessment.A model of gonadotropin regulation during the menstrual cycle in women: qualitative features.Schlosser P M PM, Selgrade J F JFfalseSchlosser2000_GlucoseInsulinFeedback_BetaCells This a model from the article: Modeling insulin kinetics: responses to a single oral glucose administration or ambulatory-fed conditions. Lenbury Y, Ruktamatakul S, Amornsamarnkul S. Biosystems 2001 Jan;59(1):15-25 11226623 , Abstract: This paper presents a nonlinear mathematical model of the glucose-insulin feedback system, which has been extended to incorporate the beta-cells' function on maintaining and regulating plasma insulin level in man. Initially, a gastrointestinal absorption term for glucose is utilized to effect the glucose absorption by the intestine and the subsequent release of glucose into the bloodstream, taking place at a given initial rate and falling off exponentially with time. An analysis of the model is carried out by the singular perturbation technique in order to derive boundary conditions on the system parameters which identify, in particular, the existence of limit cycles in our model system consistent with the oscillatory patterns often observed in clinical data. We then utilize a sinusoidal term to incorporate the temporal absorption of glucose in order to study the responses in the patients under ambulatory-fed conditions. A numerical investigation is carried out in this case to construct a bifurcation diagram to identify the ranges of parametric values for which chaotic behavior can be expected, leading to interesting biological interpretations. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Lenbury Y, Ruktamatakul S, Amornsamarnkul S. (2000) - version=1.0 The original CellML model was created by: Catherine Lloyd c.lloyd@auckland.ac.nz The University of Auckland 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. 2010-06-252005-01-012010-06-23MODEL100623004511035997MODEL1006230045GO:00226019606