This a model from the article: Modeling robust oscillatory behavior of the hypothalamic-pituitary-adrenal axis. Kyrylov V, Severyanova LA, Vieira A. IEEE Trans Biomed Eng. 2005 Dec;52(12):1977-83. 16366221 , Abstract: A mathematical model of the hypothalamic-pituitary-adrenal (HPA) axis of the human endocrine system is proposed. This new model provides an improvement over previous models by introducing two nonlinear factors with physiological relevance: 1) a limit to gland size; 2) rejection of negative hormone concentrations. The result is that the new model is by far the most robust; e.g., it can tolerate at least -50% and +100% perturbations to any of its parameters. This high degree of robustness allows one, for the first time, to model features of the system such as circadian rhythm and response to hormone injections. In addition, relative to its closest predecessor, the model is simpler; it contains only about half of the parameters, and yet achieves more functions. The new model provides opportunities for teaching endocrinology within a biological or medical school context; it may also have applications in modeling and studying HPA axis disorders, for example, related to gland size dynamics, abnormal hormone levels, or stress influences. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Kyrylov V, Severyanova LA, Vieira A. (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.