Location: Lenbury, Pacheenburawana, 1991 @ 3ece2f89daab / lenbury_pacheenburawana_1991.cellml

Author:
Catherine Lloyd <c.lloyd@auckland.ac.nz>
Date:
2010-07-01 03:22:35+12:00
Desc:
Removed xml:base="" from the model.
Permanent Source URI:
https://models.cellml.org/workspace/lenbury_pacheenburawana_1991/rawfile/3ece2f89daabcdeab34824f5833fd2bc270b308c/lenbury_pacheenburawana_1991.cellml

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This CellML file was generated on 20/04/2010 at 2:07:39 at p.m. using:

COR (0.9.31.1371)
Copyright 2002-2010 Dr Alan Garny
http://cor.physiol.ox.ac.uk/ - cor@physiol.ox.ac.uk

CellML 1.0 was used to generate this model
http://www.cellml.org/
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				<title>Modelling fluctuation phenomena in the plasma cortisol secretion system in normal man</title>
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					<firstname>Catherine</firstname>
					<surname>Lloyd</surname>
					<affiliation>
						<shortaffil>Auckland Bioengineering Institute, The University of Auckland</shortaffil>
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				This CellML model runs in OpenCell and COR, and the units are consistent. The model is an accurate representation of the published model (equations 1a-1c), and runs to recreate the published results (figure 4). Parameter values were taken from the legend of figure 4.			 
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				<title>Model Structure</title>
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ABSTRACT: A system of three non-linear differential equations with exponential feedback terms is proposed to model the self-regulating cortisol secretion system and explain the fluctuation patterns observed in clinical data. It is shown that the model exhibits bifurcation and chaos patterns for a certain range of parametric values. This helps us to explain clinical observations and characterize different dynamic behaviors of the self-regulative system.
</para>
				<para>
The original paper reference is cited below:
</para>
				<para>
Modelling fluctuation phenomena in the plasma cortisol secretion system in normal man, Yongwimon Lenbury and Pariwatana Pacheenburawana, 1991, <emphasis>BioSystems</emphasis>
, 26, 117-125.  <ulink url="http://www.ncbi.nlm.nih.gov/pubmed/1668715">PubMed ID: 1668715</ulink>
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					<caption>Schematic diagram of the self-regulatory system for corticol secretion.  CRH represents corticotropin-releasing hormone, ACTH is adrenocorticotropic hormone, and F represents cortisol.  The red lines represent positive feedback pathways, while the blue lines represent negative feedback loops.</caption>
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			<rdf:value>I've checked the model in COR and I've made all the units (except time) dimensionless to be true to the paper.  I've also replaced the stimulus equation with a cosine function.  This is the original stimulus.  The equation I'd included in the previous model was taken from a theoretical study.  I think the CellML model can recreate the original model's results.  I can't be 100% sure though as the figures published in the paper are based on altering the model in a matrix form...  and I can't set those initial conditions because they're not mentioned in the core model.</rdf:value>
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			<rdf:value>I've checked the model in COR and I've made all the units (except time) dimensionless to be true to the paper.  I've also replaced the stimulus equation with a cosine function.  This is the original stimulus.  The equation I'd included in the previous model was taken from a theoretical study.  I think the CellML model can recreate the original model's results.  I can't be 100% sure though as the figures published in the paper are based on altering the model in a matrix form...  and I can't set those initial conditions because they're not mentioned in the core model.</rdf:value>
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      <map_components component_1="z" component_2="y"/>
      <map_variables variable_1="y" variable_2="y"/>
      <map_variables variable_1="z" variable_2="z"/>
   </connection>
   <connection>
      <map_components component_1="z" component_2="x"/>
      <map_variables variable_1="z" variable_2="z"/>
   </connection>
   <connection>
      <map_components component_1="x" component_2="model_constants"/>
      <map_variables variable_1="b" variable_2="b"/>
   </connection>
   <connection>
      <map_components component_1="y" component_2="model_constants"/>
      <map_variables variable_1="b" variable_2="b"/>
   </connection>
</model>