Literature DB >> 18374950

Modeling a simplified regulatory system of blood glucose at molecular levels.

Weijiu Liu1, Fusheng Tang.   

Abstract

In this paper, we propose a new mathematical control system for a simplified regulatory system of blood glucose by taking into account the dynamics of glucose and glycogen in liver and the dynamics of insulin and glucagon receptors at the molecular level. Numerical simulations show that the proposed feedback control system agrees approximately with published experimental data. Sensitivity analysis predicts that feedback control gains of insulin receptors and glucagon receptors are robust. Using the model, we develop a new formula to compute the insulin sensitivity. The formula shows that the insulin sensitivity depends on various parameters that determine the insulin influence on insulin-dependent glucose utilization and reflect the efficiency of binding of insulin to its receptors. Using Lyapunov indirect method, we prove that the new control system is input-output stable. The stability result provides theoretical evidence for the phenomenon that the blood glucose fluctuates within a narrow range in response to the exogenous glucose input from food. We also show that the regulatory system is controllable and observable. These structural system properties could explain why the glucose level can be regulated.

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Year:  2008        PMID: 18374950     DOI: 10.1016/j.jtbi.2008.02.021

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  10 in total

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7.  Mathematical modeling of the glucagon challenge test.

Authors:  Saeed Masroor; Marloes G J van Dongen; Ricardo Alvarez-Jimenez; Koos Burggraaf; Lambertus A Peletier; Mark A Peletier
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8.  Positive input observer-based controller design for blood glucose regulation for type 1 diabetic patients: A backstepping approach.

Authors:  Mohamadreza Homayounzade
Journal:  IET Syst Biol       Date:  2022-08-17       Impact factor: 1.468

9.  Linking neuronal brain activity to the glucose metabolism.

Authors:  Britta Göbel; Kerstin M Oltmanns; Matthias Chung
Journal:  Theor Biol Med Model       Date:  2013-08-29       Impact factor: 2.432

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  10 in total

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