Publications of Umberto Picchini

This page shows all publications that appeared in the IASI annual research reports. Authors currently affiliated with the Institute are always listed with the full name.

You can browse through them using either the links of the following line or those associated with author names.

Show all publications of the year  2005, with author Picchini U., in the category IASI Research Reports (or show them all):


IASI Research Report n. 630    

Picchini U., De Gaetano A., Ditlevsen S.

System noise modelization in glucose-insulin dynamics

ABSTRACT
The Euglycemic Hyperinsulinemic Clamp (EHC) is the most widely used experimental procedure for the determination of insulin sensitivity. In the present study, sixteen subjects with BMI between 18.5 and 63.6 kg/m2 have been studied with a long-duration (five hours) EHC. Inorder to explain the oscillations of glycemia occurring in response to the hyperinsulinization and to the continuous glucose infusion at varying speeds, we first hypothesized a system of ordinary differential equations (ODEs), with limited success. We then extended the model and represented the experiment using a system of stochastic differential equations (SDEs). The latter allow for distinction between (i) random variation imputable to observation error and (ii) system noise (intrinsic variability of the metabolic system), due to a variety of influences which change over time. The stochastic model of the EHC was fitted to data and the system noise was estimated by means of a (simulated) maximum likelihood procedure, for a series of different hypothetical measurement error values. We showed that, for the whole range of reasonable measurement error values: (i) the system noise estimates are non-negligible; and (ii) these estimates are robust to changes in the likely value of the measurement error. Explicit expression of system noise is physiologically relevant in this case, since glucose uptake rate is known to be affected by a host of additive influences, usually neglected when modelling metabolism. While in some of the studied subjects system noise appeared to only marginally affect the dynamics, in others the system appeared to be driven more by the erratic oscillations in tissue glucose transport rather than by the overall glucose-insulin control system. It is possible that the quantitative relevance of the unexpressed effects (system noise) should be considered in other physiological situations, represented so far only with deterministic models. Key words: mathematical models, dynamical systems, euglycemic hyperinsulinemic clamp, stochastic differential equations, parameter estimation, Monte Carlo methods, simulated maximum likelihood
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