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Mathematical modeling and analysis of insulin clearance in vivo

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Koschorreck,  M.
Systems Biology, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Gilles,  E. D.
Integrated Navigation Systems, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Systems Biology, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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eDoc_366452_2008.pdf
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Citation

Koschorreck, M., & Gilles, E. D. (2008). Mathematical modeling and analysis of insulin clearance in vivo. BMC Systems Biology, 2, 43. doi:10.1186/1752-0509-2-43.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-9641-4
Abstract
Background: Analyzing the dynamics of insulin concentration in the blood is necessary for a comprehensive understanding of the effects of insulin in vivo. Insulin removal from the blood has been addressed in many studies. The results are highly variable with respect to insulin clearance and the relative contributions of hepatic and renal insulin degradation. Results: We present a dynamic mathematical model of insulin concentration in the blood and of insulin receptor activation in hepatocytes. The model describes renal and hepatic insulin degradation, pancreatic insulin secretion and nonspecific insulin binding in the liver. Hepatic insulin receptor activation by insulin binding, receptor internalization and autophosphorylation is explicitly included in the model. We present a detailed mathematical analysis of insulin degradation and insulin clearance. Stationary model analysis shows that degradation rates, relative contributions of the different tissues to total insulin degradation and insulin clearance highly depend on the insulin concentration. Conclusions: This study provides a detailed dynamic model of insulin concentration in the blood and of insulin receptor activation in hepatocytes. Experimental data sets from literature are used for the model validation. We show that essential dynamic and stationary characteristics of insulin degradation are nonlinear and depend on the actual insulin concentration. © 2008 Koschorreck and Gilles; licensee BioMed Central Ltd. [accessed July 4, 2008]