15 research outputs found
Proportional Insulin Infusion in Closed-Loop Control of Blood Glucose
<div><p>A differential equation model is formulated that describes the dynamics of glucose concentration in blood circulation. The model accounts for the intake of food, expenditure of calories and the control of glucose levels by insulin and glucagon. These and other hormones affect the blood glucose level in various ways. In this study only main effects are taken into consideration. Moreover, by making a quasi-steady state approximation the model is reduced to a single nonlinear differential equation of which parameters are fit to data from healthy subjects. Feedback provided by insulin plays a key role in the control of the blood glucose level. Reduced β-cell function and insulin resistance may hamper this process. With the present model it is shown how by closed-loop control these defects, in an organic way, can be compensated with continuous infusion of exogenous insulin.</p></div
Peak value <i>x</i><sub>max</sub> as a function of the size <i>w</i> of the carbohydrate component of the meal and the parameter Ď.
<p>(a) Parameter <i>w</i> is varied while the other parameters are fixed (solid line). The peak value that corresponds with the meal (<i>w</i> = 280.3) is given by (â). A linear regression (dashed line) is made after deleting the values <i>w</i> ⼠500: <i>x</i><sub>max</sub> = 4.7 + 0.01 <i>w</i>. (b) Dependence of <i>x</i><sub>max</sub> upon Ď. The value of <i>x</i><sub>max</sub> for (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169135#pone.0169135.e009" target="_blank">9</a>) is given by (â). For Ď = 2 the peak value is 12.8 (â ); this can be brought down to 9.7 by doubling Ď (âĄ), see the section on closed-loop blood glucose control.</p
Fitting the solution of differential Eq (7).
<p>The data (o) is from a meal which has rice as the main component (Fig 5 of [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169135#pone.0169135.ref007" target="_blank">7</a>], â Meal 1) with <i>w</i> = 280.3 mmol. The parameter estimates are given in (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169135#pone.0169135.e009" target="_blank">9</a>).</p
Subject characteristics (Nâ=â12).
<p>Values are mean Âą standard deviation. HR â=â heart rate, BMI â=â body mass index, VO2MAX â=â maximum oxygen uptake, VO2Peak â=â peak oxygen uptake, Wmax â=â maximum work load.</p
Changes in metabolic parameters in plasma of lean subjects (nâ=â18), obese subjects (nâ=â18) and obese diabetic subjects (nâ=â6) at 2 h and 4 h after high fat shake consumption.
<p>Values are expressed as mean Âą SD. Saturated fatty acid (SFA), monounsaturated fatty acid (MUFA), polyunsaturated fatty acid (PUFA), Free fatty acids (FFA), Triglycerides (TAG).</p
Induction of transcription factor pathways by exercise.
<p>Transcription factor pathways related to growth, stress response, cAMP signalling and hypoxia were induced by exercise. Transcription factor pathways were identified for the exercising leg using IPA and are displayed in a bar diagram. Genes induced by exercise for the different transcription factors can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051066#pone.0051066.s005" target="_blank">table S1</a>. Transcription factors with a z-score above 1.5 (or under â1.5) are considered as biologically relevant.</p
ClueGO network analysis.
<p>Analysis shows significant regulation of several GO categories involved in skeletal muscle development, angiogenesis, inflammation and MAPK cascade in the exercising leg (A; Nâ=â9) and basal metabolism and signalling in the non-exercising leg (B; Nâ=â7). The nodes represent significantly changed GO categories. Lines represent the overlap between different categories. All nodes with a large overlap have a similar colour.</p
Changes in plasma metabolic parameters at 2 h and 4 h after high-fat shake consumption.
<p>Mean (Âą SEM) changes in plasma triglyceride (A), free fatty acid (B), insulin (C) and glucose (D) concentrations of lean subjects (nâ=â18), obese subjects (nâ=â18) and obese diabetic subjects (nâ=â6) after consumption of 3 different shakes, enriched in saturated fatty acids (SFA, line with squares), monounsaturated fatty acids (MUFA, dotted line with triangles) or n-3 polyunsaturated fatty acids (n-3 PUFA, dashed line with circles). Different letters indicate significant differences (p<0.05) between shakes at a given time.</p
Baseline characteristics of the participants.
<p>Values are expressed as mean Âą standard deviation. Abbreviations: Free fatty acids (FFA), Triglycerides (TAG), Subcutaneous Adipose Tissue (SAT), Visceral adipose tissue (VAT).</p>1<p>Significantly different (p<0.05) from lean subjects.</p>2<p>For VAT, SAT en VAT/SAT ratio nâ=â17 for lean subjects, nâ=â18 for obese subjects and nâ=â4 for obese diabetic subjects.</p