Mathematical Modelling and Simulation of &amp;lt;i&amp;gt;β&amp;lt;/i&amp;gt;-Cell Mass, Insulin and Glucose Dynamics: Effect of Genetic Predisposition to Diabetes

Boutayeb, Wiam; Lamlili, Mohamed E. N.; Boutayeb, Abdesslam; Derouich, Mohamed

doi:10.4236/jbise.2014.76035

Cited by 20 publications

(14 citation statements)

References 25 publications

(29 reference statements)

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“…These parameters were applied to the mathematical model for the pancreas–muscle–liver MPS, and the glucose and insulin concentration were predicted. When the glucose production rate of the liver (Pr glu ) of 10 mM/hr, and an insulin clearance rate (Cl ins ) of 200 mU/hr were applied to the model, which was determined by fitting to the concentration profiles from the literature, the predicted concentration profile of glucose in the blood compartment matched the glucose concentration profile in the blood the human reported in the literature (Figure c‐i, S1; Bergman et al, ; Boutayeb et al, ). These results suggest that the addition of the liver compartment enabled more physiologically relevant description of glucose dynamics than the model having the pancreas and the muscle only.…”

Section: Resultsmentioning

confidence: 92%

“…An insulin secretion model of the pancreas was based on the literature (Boutayeb, Lamlili, Boutayeb, & Derouich, ), and the equation for the model was expressed as follows:

V_{blood in pancreas} ∙ \frac{italicdI}{italicdt} = V_{pancreas} ∙ \frac{R_{ins} ∙ G}{K_{ins} + G},

where V blood in pancreas is the volume of blood in pancreas, I is the concentration of insulin, t is time, V pancreas is volume of pancreas, G is concentration of glucose, R ins is maximum rate of insulin secretion, and K ins is constant of insulin secretion model.…”

Section: Methodsmentioning

confidence: 99%

“…The glucose uptake model of muscle was based on the literature (Boutayeb et al, ), and the equation was expressed as follows:

V_{blood in normal muscle} ∙ \frac{italicdG}{italicdt} = - V_{muscle} ∙ C_{glu} ∙ G - V_{muscle} ∙ \frac{R_{glu} ∙ I}{K_{glu} + I} ∙ G,

where V blood in muscle is volume of blood in muscle, G is concentration of glucose, t is time, V muscle is the volume of the muscle, C glu is rate of glucose uptake independent of insulin, R glu is maximum rate of glucose uptake dependent of insulin, and K glu is constant of glucose uptake model dependent of insulin.…”

Section: Methodsmentioning

confidence: 99%

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Construction of pancreas–muscle–liver microphysiological system (MPS) for reproducing glucose metabolism

Lee

Choi

et al. 2019

Biotech & Bioengineering

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Although in vitro models are widely accepted experimental platforms, their physiological relevance is often severely limited. The limitation of current in vitro models is strongly manifested in case of diseases where multiple organs are involved, such as diabetes and metabolic syndrome. Microphysiological systems (MPS), also known as organ-on-a-chip technology, enable a closer approximation of the human organs and tissues, by recreating the tissue microenvironment. Multiorgan MPS, also known as multiorgan-on-a-chip or body-on-a-chip, offer the possibility of reproducing interactions between organs by connecting different organ modules. Here, we designed a three-organ MPS consisting of pancreas, muscle, and liver, to recapitulate glucose metabolism and homeostasis by constructing a mathematical model of glucose metabolism, based on experimental measurement of glucose uptake by muscle cells and insulin secretion by pancreas cells. A mathematical model was used to modify the MPS to improve the physiological relevance, and by adding the liver model in the mathematical model, physiological realistic glucose and insulin profiles were obtained. Our study may provide a methodological framework for developing multiorgan MPS for recapitulating the complex interaction between multiple organs. K E Y W O R D Sglucose metabolism, mathematical model, multiorgan MPS, multiorgan-on-a-chip (MOC), pancreas-muscle-liver MPS

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Section: Resultsmentioning

confidence: 92%

“…An insulin secretion model of the pancreas was based on the literature (Boutayeb, Lamlili, Boutayeb, & Derouich, ), and the equation for the model was expressed as follows:

V_{blood in pancreas} ∙ \frac{italicdI}{italicdt} = V_{pancreas} ∙ \frac{R_{ins} ∙ G}{K_{ins} + G},

Section: Methodsmentioning

confidence: 99%

“…The glucose uptake model of muscle was based on the literature (Boutayeb et al, ), and the equation was expressed as follows:

V_{blood in normal muscle} ∙ \frac{italicdG}{italicdt} = - V_{muscle} ∙ C_{glu} ∙ G - V_{muscle} ∙ \frac{R_{glu} ∙ I}{K_{glu} + I} ∙ G,

Section: Methodsmentioning

confidence: 99%

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Construction of pancreas–muscle–liver microphysiological system (MPS) for reproducing glucose metabolism

Lee

Choi

et al. 2019

Biotech & Bioengineering

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“…Hernandez et al proposed an extension of the Topp model by adding the surface insulin receptor dynamics [10]. Boutayeb et al extended Topps model by stressing the effect of genetic predisposition to diabetes [11].…”

Section: Introductionmentioning

confidence: 99%

“…Our model is based on mathematical models published by Boutayeb et al [11], Roy et al [8] and Hernandez et al [10].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Obesity on Predisposed People to Type 2 Diabetes: Mathematical Model

Boutayeb¹,

Derouich²,

Boutayeb³

et al. 2015

Bioinformatics and Biomedical Engineering

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Abstract. Several mathematical models have been developed to simulate, analyse and understand the dynamics of β-cells, insulin and glucose. In this paper we study the effect of obesity on type 2 diabetes in people with genetic predisposition to diabetes. Equilibrium analysis and stability analysis are studied and the model shows three equilibrium points: a stable trivial pathological equilibrium point P0, a stable physiological equilibrium point P1 and a saddle point P2. A simulation is carried out to understand the models behaviour.

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Introduction

2020

Control in Bioprocessing

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Mathematical Modelling and Simulation of <i>β</i>-Cell Mass, Insulin and Glucose Dynamics: Effect of Genetic Predisposition to Diabetes

Cited by 20 publications

References 25 publications

Construction of pancreas–muscle–liver microphysiological system (MPS) for reproducing glucose metabolism

Construction of pancreas–muscle–liver microphysiological system (MPS) for reproducing glucose metabolism

The Impact of Obesity on Predisposed People to Type 2 Diabetes: Mathematical Model

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