A composite computational model of liver glucose homeostasis. II. Exploring system behaviour

Journal of the Royal Society Interface

Volumn 9, Issue 69, 2012, Pages 701-706

  Sumner, T ^a,c   Hetherington, J ^a   Seymour, R M ^a   Li, L ^a,d   Varela Rey, M ^a,e   Yamaji, S ^a,f   Saffrey, P ^a,b,g   Margoninski, O ^a,b,h   Bogle, I D L ^a   Finkelstein, A ^a,b   Warner, A ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

^c INSTITUTE FOR ANIMAL HEALTH   (United Kingdom)

^d INSTITUTE FOR ENERGY TECHNOLOGY   (Norway)

^e INSTITUTO DE SALUD CARLOS III   (Spain)

^f BURNHAM INSTITUTE   (United States)

^g WESTERN INFIRMARY   (United Kingdom)

^h Verisign   (Switzerland)

Author keywords

Bifurcation analysis; Computational modelling; Glucose homeostasis; Liver

Indexed keywords

BIFURCATION (MATHEMATICS); INSULIN; LIVER; PHYSIOLOGY; SENSITIVITY ANALYSIS;

BIFURCATION ANALYSIS; COMPOSITE MODELS; COMPUTATIONAL MODEL; COMPUTATIONAL MODELLING; GLUCOSE HOMEOSTASIS; HOMEOSTATIC CONTROL; INSULIN SENSITIVITY; MODEL PARAMETERS; STABLE LIMIT CYCLE; SUBMODELS;

GLUCOSE;

GLUCOSE; INSULIN;

BLOOD GLUCOSE MONITORING; CHEMICAL BINDING; COMPOSITE MATERIAL; GLUCOSE BLOOD LEVEL; GLUCOSE HOMEOSTASIS; GLUCOSE INTAKE; INSULIN DEPENDENT DIABETES MELLITUS; INSULIN RELEASE; INSULIN RESISTANCE; INSULIN SENSITIVITY; LIFESTYLE MODIFICATION; LIVER; MATHEMATICAL MODEL; MOLECULAR DYNAMICS; NON INSULIN DEPENDENT DIABETES MELLITUS; OSCILLATION; QUALITATIVE ANALYSIS; QUANTITATIVE ANALYSIS; REVIEW;

EID: 84859413292     PISSN: 17425689     EISSN: 17425662     Source Type: Journal    
DOI: 10.1098/rsif.2011.0783     Document Type: Review

References (15)

1. Hetherington, J. et al. 2012 A composite computational model of liver glucose homeostasis. II. Building the composite model. J. R. Soc Interface 9, 689-700. (doi:10.1098/rsif.2011.0141)
2. Margoninski, O., Saffrey, P., Hetherington, J., Li, L., Finkelstein, A. & Warner, A. 2006 A specification language and a framework for the execution of composite models in systems biology. LNCS Trans. Comput. Syst. Biol. 4230, 163-184. (Pubitemid 351150629)
3. Noble, D. 2002 Modeling the heart: from genes to cells to the whole organ. Science 295, 1678-1682. (doi:10.1126/science.1069881)
4. Lockton, J. A. & Poucher, S. M. 2007 Single dose glucagon (0.5 mg iv bolus) administration in healthy human volunteers is a robust model for assessment of glycogenolysis: characterisation of the glucose excursion after glucagon challenge. J. Pharmacol. Toxicol. Methods 55, 86-90. (doi:10.1016/j.vascn.2006.03.009)
5. Simon, C., Brandenberger, G. & Follenius, M. 1987 Ultradian oscillations of plasma glucose, insulin and C-peptidein man during continuous enteral nutrition. J. Clin. Endocrinol. Metab. 64, 669-674. (doi:10.1210/jcem- 64-4-669)
6. Simon, C. & Brandenberger, G. 2002 Ultradian oscillations of insulin secretion in humans. Diabetes 51(Suppl. 1), S258-S261. (doi:10.2337/diabetes.51. 2007.S258)
7. Sturis, J., Polonsky, K. S., Mosekilde, E. & Cauter, E. V. 1991 Computer model for mechanisms underlying ultradian oscillations of insulin and glucose. Am. J. Physiol. Endocrinol. Metab. 260, E801-E809.
8. Zimmet, P., Alberti, K. G. M. M. & Shaw, J. 2001 Global and societal implications of the diabetes epidemic. Nature 414, 782-787. (doi:10.1038/ 414782a)
9. Weyer, C., Hanson, R., Tataranni, P. A., Bogardus, C. & Pratley, R. E. 2000 A high fasting plasma insulin concentration predicts type 2 diabetes independent of insulin resistance. Diabetes 49, 2094-2101. (doi:10.2337/ diabetes.49.12.2094)
10. Doedel, E. 2007 AUTO-07p: software for continuation and bifurcation problems in ordinary differential equations. Montreal, Canada: Concordia University. See http://indy.cs.concordia.ca/auto/.
11. Svendsen, P. T., Lauritzen, L., Søegaard, U. & Nerup, J. 1982 Glycosylated haemoglobin and steady-state mean blood glucose concentration in type 1 (insulin-dependent) diabetes. Diabetoligica 23, 403-405. (Pubitemid 12037379)
12. De Bodo, R. C. & Altszuler, N. 1958 Insulin hypersensitivity and physiological insulin antagonists. Physiol. Rev. 38, 389-445.
13. Weng, W. & Breslow, J. L. 1996 Dramatically decreased high density lipoprotein cholesterol, increased remnant clearance, and insulin hypersensitivity in apolipoprotein A-II knockout mice suggest a complex role for apolipoprotein A-II in atherosclerosis susceptibility. Proc. Natl Acad Sci. USA 93, 14 788-14 794.
14. Fujiwara, Y., Hiroyama, M., Sanbe, A., Aoyagi, T., Birumachi, J., Yamauchi, J., Tsujimoto, G. & Tanoue, A. 2007 Insulin hypersensitivity in mice lacking the V1b vasopressin receptor. J. Physiol. 584, 235-244. (doi:10.1113/jphysiol.2007.136481)
15. Hetherington, J., Warner, A. & Seymour, R. M. 2006 Simplification and its consequences in biological modelling: conclusions from a study of calcium oscillations in hepatocytes. J. R. Soc. Interface 10, 319-331. (doi:10.1098/rsif.2005.0101)