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Articles by C. Cobelli
Total Records ( 7 ) for C. Cobelli
  M Campioni , G Toffolo , R Basu , R. A Rizza and C. Cobelli
 

In this article, a first aim was to develop a minimal modeling approach to noninvasively assess hepatic insulin extraction in 204 healthy subjects studied with a standard meal by coupling the already available meal C-peptide minimal model with a new insulin model. The ingredients of this model are posthepatic IDR, which in turn is described in terms of pancreatic ISR and hepatic insulin extraction HE, and a linear monocompartmental model of insulin kinetics. Even if ISR is provided by the C-peptide minimal model, the simultaneous assessment of HE and insulin kinetics is critical, since compensations may arise between parameters describing these two processes. Therefore, as a second aim of this study, a method was developed to predict standard values of insulin kinetic parameters in an individual on the basis of the individual's anthropometric characteristics. The statistical analysis, based on linear regression of insulin kinetic parameters estimated from IM-IVGTT data performed on the same subjects, demonstrated that insulin kinetic parameters can be accurately predicted from age and body surface area. Once kinetic parameters of the new insulin model were fixed to these values, HE profile and indexes during a meal were reliably estimated in each individual, indicating a significant suppression during the meal since the overall index of HE, equal to 60 ± 1% in the basal state, is reduced to 40 ± 1% during a meal. However, standard parameters provide an approximation of the individual one; thus, the third aim was to define the impact on estimated indexes of using standard instead of individually estimated values. Our results showed that the 25% uncertainty affecting as an average insulin kinetic parameters of an individual, when they are predicted from age and body surface area, translates into a similar relative uncertainty in the individual's hepatic insulin extraction indexes.

  G Pillonetto , A Caumo and C. Cobelli
 

The classical minimal model (MM) index of insulin sensitivity, SI, does not account for how fast or slow insulin action takes place. In a recent work, we proposed a new dynamic insulin sensitivity index, SID, which is able to take into account the dynamics of insulin action as well. The new index is a function of two MM parameters, namely SI and p2, the latter parameter governing the speed of rise and decay of insulin action. We have previously shown that in normal glucose tolerant subjects SID provides a more comprehensive picture of insulin action on glucose metabolism than SI. The aim of this study is to show that resorting to SID rather SI is even more appropriate when studying diabetic patients who have a low and slow insulin action. We analyzed insulin-modified intravenous glucose tolerance test studies performed in 10 diabetic subjects and mixed meal glucose tolerance test studies exploiting the triple tracer technique in 14 diabetic subjects. We derived both SI and SID resorting to Bayesian and Fisherian identification strategies. The results show that SID is estimated more precisely than SI when using the Bayesian approach. In addition, the less labor-intensive Fisherian approach can still be used to obtain reliable point estimates of SID but not of SI. These results suggest that SID yields a comprehensive, precise, and cost-effective assessment of insulin sensitivity in subjects with impaired insulin action like impaired glucose tolerant subjects or diabetic patients.

  M. G Pedersen , G. M Toffolo and C. Cobelli
 

The oral glucose tolerance test and meal tolerance test are common clinical tests of the glucose-insulin system. Several mathematical models have been suggested as means to extract information about β-cell function from data from oral tolerance tests. Any such model needs to be fairly simple but should at the same time be linked to the underlying biology of the insulin-secreting β-cells. The scope of the present work is to present a way to make such a connection using a recent model describing intracellular mechanisms. We show how the three main components of oral minimal secretion models, derivative control, proportional control, and delay, are related to subcellular events, thus providing mechanistic underpinning of the assumptions of the minimal models.

  P Denti , A Bertoldo , P Vicini and C. Cobelli
 

Population approaches, traditionally employed in pharmacokinetic-pharmacodynamic studies, have shown value also in the context of glucose-insulin metabolism models by providing more accurate individual parameters estimates and a compelling statistical framework for the analysis of between-subject variability (BSV). In this work, the advantages of population techniques are further explored by proposing integration of covariates in the intravenous glucose tolerance test (IVGTT) glucose minimal model analysis. A previously published dataset of 204 healthy subjects, who underwent insulin-modified IVGTTs, was analyzed in NONMEM, and relevant demographic information about each subject was employed to explain part of the BSV observed in parameter values. Demographic data included height, weight, sex, and age, but also basal glycemia and insulinemia, and information about amount and distribution of body fat. On the basis of nonlinear mixed-effects modeling, age, visceral abdominal fat, and basal insulinemia were significant predictors for SI (insulin sensitivity), whereas only age and basal insulinemia were significant for P2 (insulin action). The volume of distribution correlated with sex, age, percentage of total body fat, and basal glycemia, whereas no significant covariate was detected to explain variability in SG (glucose effectiveness). The introduction of covariates resulted in a significant shrinking of the unexplained BSV, especially for SI and P2 and considerably improved the model fit. These results offer a starting point for speculation about the physiological meaning of the relationships detected and pave the way for the design of less invasive and less expensive protocols for epidemiological studies of glucose-insulin metabolism.

  C Dalla Man , F Micheletto , A Sathananthan , R. A Rizza , A Vella and C. Cobelli
 

Glucagon-like peptide-1 (GLP-1)-based therapies for diabetes have aroused interest because of their effects on insulin secretion and glycemic control. However, a mechanistic model enabling quantitation of pancreatic response to GLP-1 has never been developed. To develop such a model we studied 88 healthy individuals (age 26.3 ± 0.6 yr, BMI 24.9 ± 0.4 kg/m2) by use of a hyperglycemic clamp. A variable infusion maintained glucose concentrations at 150 mg/dl for 240 min. At 120 min, an intravenous infusion of GLP-1 was started (0.75 pmol·kg–1·min–1 from 120–180 min, 1.5 pmol·kg–1·min–1 from 181–240 min). Consequently, plasma C-peptide concentration rose from 1,852.0 ± 62.8 pmol/l at 120 min to 4,272.2 ± 176.4 pmol/l at 180 min and to 6,995.8 ± 323.5 pmol/l at 240 min. Four models of GLP-1 action on insulin secretion were considered. All models share the common assumption that insulin secretion is made up of two components, one proportional to glucose rate of change through dynamic responsivity, d, and one proportional to glucose through static responsivity, s, but differing by modality of GLP-1 control. The model that best fit C-peptide data assumes that above-basal insulin secretion depends linearly on GLP-1 concentration and its rate of change. An index () measuring the percentage increase of secretion due to GLP-1 is derived. Before GLP-1 infusion, d = 245.7 ± 15.6 10–9 and s = 25.2 ± 1.4 10–9 min–1. Under GLP-1 stimulus, = 12.6 ± 0.71% per pmol/l, meaning that an increase of 5 pmol/l in peripheral GLP-1 concentrations induces an ~60% increase in over-basal insulin secretion.

  R. Balasubramanian , J. Gerrard , C. Dalla Man , M. J. Firbank , A. Lane , P. T. English , C. Cobelli and R. Taylor
  Aims: Peroxisome proliferator-activated receptor (PPAR)-γ and PPAR-α agonists individually reduce intra-organ triglyceride content and improve insulin sensitivity. However, the precise effects of combined PPAR-γ and PPAR-α therapy on intra-organ triglyceride content and insulin sensitivity in subjects with Type 2 diabetes have not yet been determined.Methods: Diet-controlled Type 2 subjects (n = 9) were studied before and after 16 weeks of combined PPAR-γ [pioglitazone (PIO), 45 mg daily] and PPAR-α [bezafibrate (BEZA), modified release 400 mg daily] agonist therapy. Glucose metabolism and endogenous glucose production were measured following a standard liquid test meal. Liver and muscle triglyceride levels were measured by 1H magnetic resonance spectroscopy.
Results: Combined PIO and BEZA therapy reduced mean fasting (7.5 ± 0.5 vs. 6.5 ± 0.2 mmol/l, P = 0.04) and peak postprandial plasma glucose (15.3 ± 1.1 vs. 11.7 ± 0.6 mmol/l, P = 0.007). No significant change in hepatic or muscle triglyceride content was observed. Postprandial suppression of endogenous glucose production remained similar on both study days. Both subcutaneous and visceral fat content increased following therapy.Conclusions: Combined PIO and BEZA therapy in Type 2 diabetes does not decrease intrahepatic triglyceride content or postprandial endogenous glucose production. This study demonstrates an unexpected adverse interaction of PPAR-α with PPAR-γ agonist therapy.
  S. Dube , I. Errazuriz , C. Cobelli , R. Basu and A. Basu
  Carbohydrate metabolism in humans is regulated by insulin secretion from pancreatic β-cells and glucose disposal by insulin-sensitive tissues. Insulin facilitates glucose utilization in peripheral tissues and suppresses hepatic glucose production. Any defects in insulin action predispose an individual to glucose intolerance and Type 2 diabetes mellitus. Early detection of defects in insulin action could provide opportunities to prevent or delay progression of the disease state. There are different approaches to assess insulin action. Initial methods, such as peripheral insulin concentration and simple indices, have several limitations. Subsequently, researchers developed methodologies using intravenous glucose infusion to determine glucose fluxes. However, these methodologies are limited by being non-physiological. Newer, innovative techniques that have been developed are more sophisticated and physiological. By modelling glucose kinetics using isotope dilution techniques, several robust parameters can be obtained that are physiologically relevant and sound. This brief review summarizes most of the non-physiological and physiological methodologies used to measure the variables of insulin action.
 
 
 
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