Glucose-induced pancreatic insulin release is the fundamental mechanism responsible for glucose homeostasis, its failure determining the clinical picture of Diabetes Mellitus. The details of the feedback loop controlling glycemia through insulin secretion have been an important subject of investigation and modeling for decades. In this note, a recently published population model is considered, whose purpose is to replicate in silico different observed phenomena such as low frequency glycemia-insulinemia oscillations, as well as concordant induction of high-frequency insulin oscillations. The basic idea underlying this model is that the pancreas behaves like a population of independent controllers (each consisting of a fundamental secreting unit, a pancreatic islet), all reacting to the same glucose stimulus, but with varying perfomance characteristics. This idea has been supported by a relatively wide range of simulations, aiming to replicate most important in vivo experiments concerning pancreatic insulin release. It will be shown in this note that the same mathematical structure can also replicate a set of in vitro experiments, provided that the model context is adapted to the structure of the different experiments to be simulated. More in details, the model will be shown to reproduce the double phase of insulin release during a prolonged glucose stimulus: A first phase of impulsive insulin release, immediately upon glucose administration, and a second phase of more gradual release, dependent on the potentiation effect of the secretory units. ©2013 IEEE.

An islet population model of pancreatic insulin production / A., De Gaetano; GAZ, CLAUDIO ROBERTO; GORI GIORGI, Claudio; P., Palumbo. - ELETTRONICO. - (2013), pp. 3355-3360. (Intervento presentato al convegno IEEE 52 annual conference on decision and control tenutosi a Florence; Italy nel 10-13 dicembre 2013) [10.1109/CDC.2013.6760396].

An islet population model of pancreatic insulin production

GAZ, CLAUDIO ROBERTO;GORI GIORGI, Claudio;
2013

Abstract

Glucose-induced pancreatic insulin release is the fundamental mechanism responsible for glucose homeostasis, its failure determining the clinical picture of Diabetes Mellitus. The details of the feedback loop controlling glycemia through insulin secretion have been an important subject of investigation and modeling for decades. In this note, a recently published population model is considered, whose purpose is to replicate in silico different observed phenomena such as low frequency glycemia-insulinemia oscillations, as well as concordant induction of high-frequency insulin oscillations. The basic idea underlying this model is that the pancreas behaves like a population of independent controllers (each consisting of a fundamental secreting unit, a pancreatic islet), all reacting to the same glucose stimulus, but with varying perfomance characteristics. This idea has been supported by a relatively wide range of simulations, aiming to replicate most important in vivo experiments concerning pancreatic insulin release. It will be shown in this note that the same mathematical structure can also replicate a set of in vitro experiments, provided that the model context is adapted to the structure of the different experiments to be simulated. More in details, the model will be shown to reproduce the double phase of insulin release during a prolonged glucose stimulus: A first phase of impulsive insulin release, immediately upon glucose administration, and a second phase of more gradual release, dependent on the potentiation effect of the secretory units. ©2013 IEEE.
2013
IEEE 52 annual conference on decision and control
pancreas; insuline; glucose
Pubblicazione in atti di convegno::04b Atto di convegno in volume
An islet population model of pancreatic insulin production / A., De Gaetano; GAZ, CLAUDIO ROBERTO; GORI GIORGI, Claudio; P., Palumbo. - ELETTRONICO. - (2013), pp. 3355-3360. (Intervento presentato al convegno IEEE 52 annual conference on decision and control tenutosi a Florence; Italy nel 10-13 dicembre 2013) [10.1109/CDC.2013.6760396].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/745401
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