Dataset Information

DallaMan2007_MealModel_GlucoseInsulinSystem

ABSTRACT: This a model from the article: Meal simulation model of the glucose-insulin system. Dalla Man C, Rizza RA, Cobelli C.IEEE Trans Biomed Eng.2007 Oct;54(10):1740-9. 17926672, Abstract: A simulation model of the glucose-insulin system in the postprandial state can be useful in several circumstances, including testing of glucose sensors, insulin infusion algorithms and decision support systems for diabetes. Here, we present a new simulation model in normal humans that describes the physiological events that occur after a meal, by employing the quantitative knowledge that has become available in recent years. Model parameters were set to fit the mean data of a large normal subject database that underwent a triple tracer meal protocol which provided quasi-model-independent estimates of major glucose and insulin fluxes, e.g., meal rate of appearance, endogenous glucose production, utilization of glucose, insulin secretion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. Model results are shown in describing both a single meal and normal daily life (breakfast, lunch, dinner) in normal. The same strategy is also applied on a smaller database for extending the model to type 2 diabetes 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. For more information see the terms of use. 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.

DISEASE(S): Diabetes Mellitus

SUBMITTER: Ishan Ajmera

PROVIDER: BIOMD0000000379 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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Dataset's files

Source:

			Action	DRS
	BIOMD0000000379?filename=BIOMD0000000379-biopax2.owl	Owl
	BIOMD0000000379?filename=BIOMD0000000379-biopax3.owl	Owl
	BIOMD0000000379?filename=BIOMD0000000379-matlab.m	Other
	BIOMD0000000379?filename=BIOMD0000000379-octave.m	Other
	BIOMD0000000379?filename=BIOMD0000000379.m	Other

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Publications

Meal simulation model of the glucose-insulin system.

Dalla Man Chiara C Rizza Robert A RA Cobelli Claudio C

IEEE transactions on bio-medical engineering 20071001 10

A simulation model of the glucose-insulin system in the postprandial state can be useful in several circumstances, including testing of glucose sensors, insulin infusion algorithms and decision support systems for diabetes. Here, we present a new simulation model in normal humans that describes the physiological events that occur after a meal, by employing the quantitative knowledge that has become available in recent years. Model parameters were set to fit the mean data of a large normal subjec ...[more]

PMID: 17926672

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Project description:Brännmark2013 - Insulin signalling in human adipocytes (normal condition) The paper describes insulin signalling in human adipocytes under normal and diabetic states using mathematical models based on experimental data. This model corresponds to insulin signalling under normal condtion This model is described in the article: Insulin Signaling in Type 2 Diabetes: EXPERIMENTAL AND MODELING ANALYSES REVEAL MECHANISMS OF INSULIN RESISTANCE IN HUMAN ADIPOCYTES. Brännmark C, Nyman E, Fagerholm S, Bergenholm L, Ekstrand EM, Cedersund G, Strålfors P. J Biol Chem. 2013 Apr 5;288(14):9867-80. Abstract: Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally and in diabetes, we developed a dynamic mathematical model of insulin signaling. The model structure and parameters are identical in the normal and diabetic states of the model, except for three parameters that change in diabetes: (i) reduced concentration of insulin receptor, (ii) reduced concentration of insulin-regulated glucose transporter GLUT4, and (iii) changed feedback from mammalian target of rapamycin in complex with raptor (mTORC1). Modeling reveals that at the core of insulin resistance in human adipocytes is attenuation of a positive feedback from mTORC1 to the insulin receptor substrate-1, which explains reduced sensitivity and signal strength throughout the signaling network. Model simulations with inhibition of mTORC1 are comparable with experimental data on inhibition of mTORC1 using rapamycin in human adipocytes. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling, both at the cellular level and, using a multilevel model, at the whole body level. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis. This model is hosted on BioModels Database and identified by: MODEL1304190000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . 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.