Literature DB >> 34032128

Minimal and Maximal Models to Quantitate Glucose Metabolism: Tools to Measure, to Simulate and to Run in Silico Clinical Trials.

Claudio Cobelli1, Chiara Dalla Man2.   

Abstract

Several models have been proposed to describe the glucose system at whole-body, organ/tissue and cellular level, designed to measure non-accessible parameters (minimal models), to simulate system behavior and run in silico clinical trials (maximal models). Here, we will review the authors' work, by putting it into a concise historical background. We will discuss first the parametric portrait provided by the oral minimal models-building on the classical intravenous glucose tolerance test minimal models-to measure otherwise non-accessible key parameters like insulin sensitivity and beta-cell responsivity from a physiological oral test, the mixed meal or the oral glucose tolerance tests, and what can be gained by adding a tracer to the oral glucose dose. These models were used in various pathophysiological studies, which we will briefly review. A deeper understanding of insulin sensitivity can be gained by measuring insulin action in the skeletal muscle. This requires the use of isotopic tracers: both the classical multiple-tracer dilution and the positron emission tomography techniques are discussed, which quantitate the effect of insulin on the individual steps of glucose metabolism, that is, bidirectional transport plasma-interstitium, and phosphorylation. Finally, we will present a cellular model of insulin secretion that, using a multiscale modeling approach, highlights the relations between minimal model indices and subcellular secretory events. In terms of maximal models, we will move from a parametric to a flux portrait of the system by discussing the triple tracer meal protocol implemented with the tracer-to-tracee clamp technique. This allows to arrive at quasi-model independent measurement of glucose rate of appearance (Ra), endogenous glucose production (EGP), and glucose rate of disappearance (Rd). Both the fast absorbing simple carbs and the slow absorbing complex carbs are discussed. This rich data base has allowed us to build the UVA/Padova Type 1 diabetes and the Padova Type 2 diabetes large scale simulators. In particular, the UVA/Padova Type 1 simulator proved to be a very useful tool to safely and effectively test in silico closed-loop control algorithms for an artificial pancreas (AP). This was the first and unique simulator of the glucose system accepted by the U.S. Food and Drug Administration as a substitute to animal trials for in silico testing AP algorithms. Recent uses of the simulator have looked at glucose sensors for non-adjunctive use and new insulin molecules.

Entities:  

Keywords:  diabetes; in silico simulation; insulin action; insulin secretion; multiscale modeling; stabilized tracers

Mesh:

Substances:

Year:  2021        PMID: 34032128      PMCID: PMC9445339          DOI: 10.1177/19322968211015268

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  148 in total

1.  Oral glucose tolerance test minimal model indexes of beta-cell function and insulin sensitivity.

Authors:  E Breda; M K Cavaghan; G Toffolo; K S Polonsky; C Cobelli
Journal:  Diabetes       Date:  2001-01       Impact factor: 9.461

2.  Inducing remission of Type 2 diabetes in the Caribbean: findings from a mixed methods feasibility study of a low-calorie liquid diet-based intervention in Barbados.

Authors:  K Bynoe; N Unwin; C Taylor; M M Murphy; L Bartholomew; A Greenidge; M Abed; S Jeyaseelan; C Cobelli; C Dalla Man; R Taylor
Journal:  Diabet Med       Date:  2019-08-12       Impact factor: 4.359

3.  Toward a Run-to-Run Adaptive Artificial Pancreas: In Silico Results.

Authors:  Chiara Toffanin; Roberto Visentin; Mirko Messori; Federico Di Palma; Lalo Magni; Claudio Cobelli
Journal:  IEEE Trans Biomed Eng       Date:  2017-01-11       Impact factor: 4.538

4.  Kinetic modeling of [(18)F]FDG in skeletal muscle by PET: a four-compartment five-rate-constant model.

Authors:  A Bertoldo; P Peltoniemi; V Oikonen; J Knuuti; P Nuutila; C Cobelli
Journal:  Am J Physiol Endocrinol Metab       Date:  2001-09       Impact factor: 4.310

5.  Effects of dipeptidyl peptidase-4 inhibition on gastrointestinal function, meal appearance, and glucose metabolism in type 2 diabetes.

Authors:  Adrian Vella; Gerlies Bock; Paula D Giesler; Duane B Burton; Denise B Serra; Monica Ligueros Saylan; Beth E Dunning; James E Foley; Robert A Rizza; Michael Camilleri
Journal:  Diabetes       Date:  2007-02-15       Impact factor: 9.461

6.  Roles of glucose transport and glucose phosphorylation in muscle insulin resistance of NIDDM.

Authors:  R C Bonadonna; S Del Prato; E Bonora; M P Saccomani; G Gulli; A Natali; S Frascerra; N Pecori; E Ferrannini; D Bier; C Cobelli; R A DeFronzo
Journal:  Diabetes       Date:  1996-07       Impact factor: 9.461

7.  Modeling error and apparent isotope discrimination confound estimation of endogenous glucose production during euglycemic glucose clamps.

Authors:  D T Finegood; R N Bergman; M Vranic
Journal:  Diabetes       Date:  1988-08       Impact factor: 9.461

8.  A compartmental model to quantitate in vivo glucose transport in the human forearm.

Authors:  C Cobelli; M P Saccomani; E Ferrannini; R A Defronzo; R Gelfand; R Bonadonna
Journal:  Am J Physiol       Date:  1989-12

9.  Prehepatic insulin production in man: kinetic analysis using peripheral connecting peptide behavior.

Authors:  R P Eaton; R C Allen; D S Schade; K M Erickson; J Standefer
Journal:  J Clin Endocrinol Metab       Date:  1980-09       Impact factor: 5.958

10.  The effect of vagal nerve blockade using electrical impulses on glucose metabolism in nondiabetic subjects.

Authors:  Matheni Sathananthan; Sayeed Ikramuddin; James M Swain; Meera Shah; Francesca Piccinini; Chiara Dalla Man; Claudio Cobelli; Robert A Rizza; Michael Camilleri; Adrian Vella
Journal:  Diabetes Metab Syndr Obes       Date:  2014-07-11       Impact factor: 3.168

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  1 in total

1.  Comment on "Minimal and Maximal Models to Quantitate Glucose Metabolism: Tools to Measure, to Simulate and to Run in Silico Clinical Trials".

Authors:  Manuel Eichenlaub; M P Saccomani; John G Hattersley; Natasha A Khovanova
Journal:  J Diabetes Sci Technol       Date:  2021-10-25
  1 in total

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