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MODEL1201140003 - Lenbury2001_InsulinKineticsModel_B


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Reference Publication
Publication ID: 11226623
Lenbury Y, Ruktamatakul S, Amornsamarnkul S.
Modeling insulin kinetics: responses to a single oral glucose administration or ambulatory-fed conditions.
BioSystems 2001 Jan; 59(1): 15-25
Department of Mathematics, Faculty of Science, Mahidol University, Rama 6 Rd., Bangkok 10400, Thailand.  [more]
Original Model: MODEL1201140003.origin
Submitter: Ishan Ajmera
Submission Date: 14 Jan 2012 19:59:58 UTC
Last Modification Date: 14 Jan 2012 20:08:49 UTC
Creation Date: 14 Jan 2012 20:08:49 UTC
bqmodel:isDerivedFrom PubMed 2277508
bqbiol:isVersionOf Gene Ontology glucose homeostasis
Human Disease Ontology diabetes mellitus
bqbiol:hasTaxon Taxonomy Homo sapiens

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 ,
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_ruktamatakul_amornsamarnkul_2001_B
The original CellML model was created by:
Catherine Lloyd
The University of Auckland
The Bioengineering Institute

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