The Glucose–Insulin Control System

Hallgreen, Christine Erikstrup; Korsgaard, Thomas Vagn; Hansen, René Normann; Colding‐Jørgensen, Morten

doi:10.1002/9783527622672.ch6

Cited by 6 publications

(10 citation statements)

References 97 publications

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“…Obviously, this is still a much simplified, exploratory model; the actual mechanism of glucose-induced insulin secretion in β-cells is complex and involves various molecular-level events [ 1 , 2 , 36 , 37 , 39 , 70 , 96 , 97 ]. The present model gives an adequate quantitative description of the main distinctive features of insulin release, but, at this stage, does not account for interspecies differences and does not incorporate a number of effects known to affect glucose-induced insulin release including, e.g., amplifiers such as glucagon-like peptide-1 (GLP-1) as well as time-dependent effects (i.e., both time-dependent inhibition and potentiation; e.g., the "glucose priming" effect) [ 98 ].…”

Section: Resultsmentioning

confidence: 99%

“…In healthy humans, blood glucose levels have to be maintained in a relatively narrow range: typically 4-5 mM and usually within 3.5-7.0 mM (60-125 mg/dL) in fasting subjects [ 1 , 2 ]. This is mainly achieved via the finely-tuned glucose-insulin control system whereby β-cells located in pancreatic islets act as glucose sensors and adjust their insulin output as a function of the blood glucose level.…”

Section: Introductionmentioning

confidence: 99%

“…Human islets have diameters ranging up to about 500 μm with a size distribution that is well described by a Weibull distribution function, and islets with diameters of 100-150 μm are the most representative [ 3 ]. Because abnormalities in β-cell function are the main culprit behind elevated glucose levels, quantitative models describing the dynamics of glucose-stimulated insulin release (GSIR) are of obvious interest [ 1 ] for both type 1 (insulin-dependent or juvenile-onset) and type 2 (non-insulin dependent or adult-onset) diabetes mellitus. They could help not only to better understand the process, but also to more accurately assess β-cell function and insulin resistance.…”

Section: Introductionmentioning

confidence: 99%

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A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

Buchwald

2011

Theor Biol Med Model

114

148

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BackgroundBecause insulin is the main regulator of glucose homeostasis, quantitative models describing the dynamics of glucose-induced insulin secretion are of obvious interest. Here, a computational model is introduced that focuses not on organism-level concentrations, but on the quantitative modeling of local, cellular-level glucose-insulin dynamics by incorporating the detailed spatial distribution of the concentrations of interest within isolated avascular pancreatic islets.MethodsAll nutrient consumption and hormone release rates were assumed to follow Hill-type sigmoid dependences on local concentrations. Insulin secretion rates depend on both the glucose concentration and its time-gradient, resulting in second-and first-phase responses, respectively. Since hypoxia may also be an important limiting factor in avascular islets, oxygen and cell viability considerations were also built in by incorporating and extending our previous islet cell oxygen consumption model. A finite element method (FEM) framework is used to combine reactive rates with mass transport by convection and diffusion as well as fluid-mechanics.ResultsThe model was calibrated using experimental results from dynamic glucose-stimulated insulin release (GSIR) perifusion studies with isolated islets. Further optimization is still needed, but calculated insulin responses to stepwise increments in the incoming glucose concentration are in good agreement with existing experimental insulin release data characterizing glucose and oxygen dependence. The model makes possible the detailed description of the intraislet spatial distributions of insulin, glucose, and oxygen levels. In agreement with recent observations, modeling also suggests that smaller islets perform better when transplanted and/or encapsulated.ConclusionsAn insulin secretion model was implemented by coupling local consumption and release rates to calculations of the spatial distributions of all species of interest. The resulting glucose-insulin control system fits in the general framework of a sigmoid proportional-integral-derivative controller, a generalized PID controller, more suitable for biological systems, which are always nonlinear due to the maximum response being limited. Because of the general framework of the implementation, simulations can be carried out for arbitrary geometries including cultured, perifused, transplanted, and encapsulated islets.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

Buchwald

2011

Theor Biol Med Model

114

148

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“…Assuming that

α_{2}

would be within a reasonable range of this value, we constrained

α_{2}

to be within

{[10}^{- 6}, 5 \times 0.8 \times V_{L}^{F}]

mmol/L/min. The uptake rate of fatty acids,

α_{3}

, was estimated to be a maximum of 0.6 mmol/min, 21 similarly a wide including this value was confined:

{[10}^{- 6}, 2 \times 0.6 / V_{L}^{F}]

mmol/L/min. The basal source term for plasma TGs,

α_{4}

was estimated from the estimate for clearance

σ_{2}

(estimated from the fructose DNL experiment 9 ), and reported values for plasma TG concentrations (1.2 mmol/L).…”

Section: Parameter Estimatesmentioning

confidence: 99%

Modeling fructose-load-induced hepatic de-novo lipogenesis by model simplification

Musante

2017

Gene�Regul Syst Bio

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Hepatic de-novo lipogenesis is a metabolic process implemented in the pathogenesis of type 2 diabetes. Clinically, the rate of this process can be ascertained by use of labeled acetate and stimulation by fructose administration. A systems pharmacology model of this process is desirable because it facilitates the description, analysis, and prediction of this experiment. Due to the multiple enzymes involved in de-novo lipogenesis, and the limited data, it is desirable to use single functional expressions to encapsulate the flux between multiple enzymes. To accomplish this we developed a novel simplification technique which uses the available information about the properties of the individual enzymes to bound the parameters of a single governing ‘transfer function’. This method should be applicable to any model with linear chains of enzymes that are well stimulated. We validated this approach with computational simulations and analytical justification in a limiting case. Using this technique we generated a simple model of hepatic de-novo lipogenesis in these experimental conditions that matched prior data. This model can be used to assess pharmacological intervention at specific points on this pathway. We have demonstrated this with prospective simulation of acetyl-CoA carboxylase inhibition. This simplification technique suggests how the constituent properties of an enzymatic chain of reactions gives rise to the sensitivity (to substrate) of the pathway as a whole.

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“…Quantitative models describing the dynamics of glucosestimulated insulin secretion are of obvious interest [1] for both type 1 (insulin-dependent or juvenile-onset) [2] and type 2 (non-insulin dependent or adult-onset) diabetes mellitus. Maintenance of glucose levels within the normal range (typically within 3.5 -7.0 mM = 60 -125 mg/ dL in healthy humans) is achieved via the finely-tuned glucose-insulin control system.…”

Section: Introductionmentioning

confidence: 99%

Glucose-stimulated insulin secretion in isolated pancreatic islets: Multiphysics FEM model calculations compared to results of perifusion experiments with human islets

Buchwald¹,

Cechin²

2013

JBiSE

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Because insulin released by the β-cells of pancreatic islets is the main regulator of glucose levels, the quantitative modeling of their glucose-stimulated insulin secretion is of obvious interest not only to improve our understanding of the processes involved, but also to allow better assessment of β -cell function in diabetic patients or islet transplant recipients as well as the development of improved artificial or bioartificial pancreas devices. We have recently developed a general, local concentrations-based multiphysics computational model of insulin secretion in avascular pancreatic islets that can be used to calculate insulin secretion for arbitrary geometries of cultured, perifused, transplanted, or encapsulated islets in response to various glucose profiles. Here, experimental results obtained from two different dynamic glucose-stimulated insulin release (GSIR) perifusion studies performed by us following standard procedures are compared to those calculated by the model. Such perifusion studies allow the quantitative assessment of insulin release kinetics under fully controllable experimental conditions of varying external concentrations of glucose, oxygen, or other compounds of interest, and can provide an informative assessment of islet quality and function. The time-profile of the insulin secretion calculated by the model was in good agree- ment with the experimental results obtained with isolated human islets. Detailed spatial distributions of glucose, oxygen, and insulin were calculated and are presented to provide a quantitative visualization of various important aspects of the insulin secretion dynamics in perifused islets.

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The Glucose–Insulin Control System

Cited by 6 publications

References 97 publications

A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

Modeling fructose-load-induced hepatic de-novo lipogenesis by model simplification

Glucose-stimulated insulin secretion in isolated pancreatic islets: Multiphysics FEM model calculations compared to results of perifusion experiments with human islets

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