BioModelsapplication/xmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=curation_notes.txthttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=BIOMD0000000356.pdfhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=BIOMD0000000356-biopax2.owlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=BIOMD0000000356-biopax3.owlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=BIOMD0000000356_url.xmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=manifest.xmlhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=metadata.rdfhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=BIOMD0000000356.pnghttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=BIOMD0000000356.mhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=BIOMD0000000356-matlab.mhttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=BIOMD0000000356.odehttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=curation_image.jpeghttps://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000356?filename=BIOMD0000000356_url.sedmlprimaryOK200Ishan AjmeraManually curatedordinary differential equation modelDiabetes MellitusL2V4https://www.ebi.ac.uk/biomodels/BIOMD000000035621572040falseBioModelsBIOMD0000000343 biomodels.db BIOMD0000000379 biomodels.db BIOMD0000000137 biomodels.dbModelsSBMLNyman2011 M3Hierarachical InsulinGlucosedynamics2011MODEL1108190000E Nyman, Cecilia Brännmark, Robert Palmér, Jan Brugård, Fredrik H Nyström, Peter Strålfors, Gunnar CedersundE Nyman21572040, Type 2 diabetes is a metabolic disease that profoundly affects energy homeostasis. The disease involves failure at several levels and subsystems and is characterized by insulin resistance in target cells and tissues (i.e. by impaired intracellular insulin signaling). We have previously used an iterative experimental-theoretical approach to unravel the early insulin signaling events in primary human adipocytes. That study, like most insulin signaling studies, is based on in vitro experimental examination of cells, and the in vivo relevance of such studies for human beings has not been systematically examined. Herein, we develop a hierarchical model of the adipose tissue, which links intracellular insulin control of glucose transport in human primary adipocytes with whole-body glucose homeostasis. An iterative approach between experiments and minimal modeling allowed us to conclude that it is not possible to scale up the experimentally determined glucose uptake by the isolated adipocytes to match the glucose uptake profile of the adipose tissue in vivo. However, a model that additionally includes insulin effects on blood flow in the adipose tissue and GLUT4 translocation due to cell handling can explain all data, but neither of these additions is sufficient independently. We also extend the minimal model to include hierarchical dynamic links to more detailed models (both to our own models and to those by others), which act as submodules that can be turned on or off. The resulting multilevel hierarchical model can merge detailed results on different subsystems into a coherent understanding of whole-body glucose homeostasis. This hierarchical modeling can potentially create bridges between other experimental model systems and the in vivo human situation and offers a framework for systematic evaluation of the physiological relevance of in vitro obtained molecular/cellular experimental data.. 29, 286. Department of Clinical and Experimental Medicine, Diabetes and Integrative Systems Biology, Linköping University, SE58185 Linköping, Sweden.ajmera@ebi.ac.ukEMBL-EBIBIOMD0000000356Type 2 diabetes is a metabolic disease that profoundly affects energy homeostasis. The disease involves failure at several levels and subsystems and is characterized by insulin resistance in target cells and tissues (i.e. by impaired intracellular insulin signaling). We have previously used an iterative experimental-theoretical approach to unravel the early insulin signaling events in primary human adipocytes. That study, like most insulin signaling studies, is based on in vitro experimental examination of cells, and the in vivo relevance of such studies for human beings has not been systematically examined. Herein, we develop a hierarchical model of the adipose tissue, which links intracellular insulin control of glucose transport in human primary adipocytes with whole-body glucose homeostasis. An iterative approach between experiments and minimal modeling allowed us to conclude that it is not possible to scale up the experimentally determined glucose uptake by the isolated adipocytes to match the glucose uptake profile of the adipose tissue in vivo. However, a model that additionally includes insulin effects on blood flow in the adipose tissue and GLUT4 translocation due to cell handling can explain all data, but neither of these additions is sufficient independently. We also extend the minimal model to include hierarchical dynamic links to more detailed models (both to our own models and to those by others), which act as submodules that can be turned on or off. The resulting multilevel hierarchical model can merge detailed results on different subsystems into a coherent understanding of whole-body glucose homeostasis. This hierarchical modeling can potentially create bridges between other experimental model systems and the in vivo human situation and offers a framework for systematic evaluation of the physiological relevance of in vitro obtained molecular/cellular experimental data.The insulin and insulin-like growth factor 1 receptors activate overlapping signalling pathways that are critical for growth, metabolism, survival and longevity. Their mechanism of ligand binding and activation displays complex allosteric properties, which no mathematical model has been able to account for. Modelling these receptors' binding and activation in terms of interactions between the molecular components is problematical due to many unknown biochemical and structural details. Moreover, substantial combinatorial complexity originating from multivalent ligand binding further complicates the problem. On the basis of the available structural and biochemical information, we develop a physically plausible model of the receptor binding and activation, which is based on the concept of a harmonic oscillator. Modelling a network of interactions among all possible receptor intermediaries arising in the context of the model (35, for the insulin receptor) accurately reproduces for the first time all the kinetic properties of the receptor, and provides unique and robust estimates of the kinetic parameters. The harmonic oscillator model may be adaptable for many other dimeric/dimerizing receptor tyrosine kinases, cytokine receptors and G-protein-coupled receptors where ligand crosslinking occurs.A hierarchical whole-body modeling approach elucidates the link between in Vitro insulin signaling and in Vivo glucose homeostasis.Harmonic oscillator model of the insulin and IGF1 receptors' allosteric binding and activation.Nyman Elin E, Brännmark Cecilia C, Palmér Robert R, Brugård Jan J, Nyström Fredrik H FH, Strålfors Peter P, Cedersund Gunnar GKiselyov Vladislav V VV, Versteyhe Soetkin S, Gauguin Lisbeth L, De Meyts Pierre PfalseNyman2011_M3Hierarachical_InsulinGlucosedynamics This a model from the article: A Hierarchical Whole-body Modeling Approach Elucidates the Link between in Vitro Insulin Signaling and in Vivo Glucose Homeostasis. Nyman E, Brannmark C, Palmer R, Brugard J, Nystrom FH, Stralfors P, Cedersund G.J Biol Chem.2011 Jul 22;286(29):26028-41. 21572040, Abstract: Type 2 diabetes is a metabolic disease that profoundly affects energy homeostasis. The disease involves failure at several levels and subsystems and is characterized by insulin resistance in target cells and tissues (i.e. by impaired intracellular insulin signaling). We have previously used an iterative experimental-theoretical approach to unravel the early insulin signaling events in primary human adipocytes. That study, like most insulin signaling studies, is based on in vitro experimental examination of cells, and the in vivo relevance of such studies for human beings has not been systematically examined. Herein, we develop a hierarchical model of the adipose tissue, which links intracellular insulin control of glucose transport in human primary adipocytes with whole-body glucose homeostasis. An iterative approach between experiments and minimal modeling allowed us to conclude that it is not possible to scale up the experimentally determined glucose uptake by the isolated adipocytes to match the glucose uptake profile of the adipose tissue in vivo. However, a model that additionally includes insulin effects on blood flow in the adipose tissue and GLUT4 translocation due to cell handling can explain all data, but neither of these additions is sufficient independently. We also extend the minimal model to include hierarchical dynamic links to more detailed models (both to our own models and to those by others), which act as submodules that can be turned on or off. The resulting multilevel hierarchical model can merge detailed results on different subsystems into a coherent understanding of whole-body glucose homeostasis. This hierarchical modeling can potentially create bridges between other experimental model systems and the in vivo human situation and offers a framework for systematic evaluation of the physiological relevance of in vitro obtained molecular/cellular experimental data. 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. 2024-08-212024-09-022011-08-19BIOMD0000000356REACT_3809.1REACT_4836.1REACT_3655.2REACT_3057.1REACT_2507.1REACT_3893.1REACT_4240.1REACT_2603.3REACT_7426.1REACT_342.3REACT_1810.22157204019225456CHEBI:36080MODEL1108190000BIOMD0000000356GO:0061178GO:0006839GO:0043559GO:0031623GO:0016311GO:0038020GO:0016310GO:0006468GO:0006470GO:0005942GO:00072059606BTO:0000443P06213P35568O15530P13678P31749P42345P14672IPR015433