UCP-3 is expressed in human islets.

<p>A Human UCP-2, UCP-3 and α-tubulin mRNA expression in human islets. B Human islets were cultured at 5.5 or 11 mM glucose, and total protein extracts were analyzed on a western blot using UCP-3 antibodies. The intensities of the protein signal were quantified by scanning of images; blots for UCP-3 and β-actin is shown for one representative experiment. Data are expressed as means±SE, n = 3, * <i>p</i><0.05. C UCP-3 is expressed in human pancreatic islets, where it colocalizes with mitochondria. A representative layer of human pancreata is depicted showing UCP-3, mitochondria and overlay. Images were acquired using confocal microscope and imaged at x63 magnification, bar = 20 µm.</p

UCP3 over expression in human islets increases glucose-stimulated insulin secretion.

<p>A Western blot analysis of UCP-3 expression in transduced islets. B Isolated human pancreatic islets were cultured on extracellular matrix-coated dishes and transduced with adenoviruses expressing control virus (luciferase, Luc), UCP-3 or dnUCP-2. Basal and stimulated insulin secretion indicate the amount secreted during 1-hour incubations at 2.8 (basal) and 16.7 mM (stimulated) glucose following the 2-day culture period after transduction, normalized to whole islet insulin content. C Stimulatory index denotes the amount of stimulated divided by the amount of basal insulin secretion. Data represent results of two different experiments from two different organ donors in quadruplicate. Results are means±SE, *p<0.05 compared to control.</p

Dominant negative UCP-2 enhances insulin secretion in human islets.

<p>A Levels of UCP-2 protein in human islets following adenoviral misexpression of dn-UCP-2 (+) or GFP (−). B DnUCP-2 increases mitochondrial membrane potential. Human islets grown on extracellular-matrix-coated slides were transduced with Ad-dnUCP-2 or Ad-GFP. Mitochondrial membrane potential was detected by live staining with JC-1, and the JC-1 and islet cell area were measured using Image-Pro Plus software. Bar graph shows the percentage of JC-1 (area) divided by total islet area (<i>t</i>-test; *, <i>p</i><0.05 relative to control). C Human islets were transduced with Ad-dnUCP-2 (▪) or Ad-GFP (□, control) and cultured in suspension at 5.5 mM glucose before perifusion. Islets were perifused at 4 mM and 16 mM glucose and insulin concentrations were measured every 4 min. Results are of four independent experiments using four separate human islet donors. Data are presented as means±SE and analyzed by <i>t</i>-test, *, <i>p</i><0.001.</p

Possible Role of Interleukin-1β in Type 2 Diabetes Onset and Implications for Anti-inflammatory Therapy Strategies

<div><p>Increasing evidence of a role of chronic inflammation in type 2 diabetes progression has led to the development of therapies targeting the immune system. We develop a model of interleukin-1β dynamics in order to explain principles of disease onset. The parameters in the model are derived from <i>in vitro</i> experiments and patient data. In the framework of this model, an IL-1β switch is sufficient and necessary to account for type 2 diabetes onset. The model suggests that treatments targeting glucose bear the potential of stopping progression from pre-diabetes to overt type 2 diabetes. However, once in overt type 2 diabetes, these treatments have to be complemented by adjuvant anti-inflammatory therapies in order to stop or decelerate disease progression. Moreover, the model suggests that while glucose-lowering therapy needs to be continued all the way, dose and duration of the anti-inflammatory therapy needs to be specifically controlled. The model proposes a framework for the discussion of clinical trial outcomes.</p></div

Model scheme: IL-1Ra (<i>A</i>) and IL-1β (<i>L</i>) compete for IL-1 receptors giving rise to a fraction of IL-1β bound receptors (<i>F</i>) which determines subsequent signalling in β-cells (<i>B</i>).

<p>These control insulin (<i>I</i>) release and, via the influence of insulin resistance, blood glucose level (<i>G</i>). Arrows: activation effect, line with bar end: inhibition effect. Kinetic terms corresponding to each interaction are labelled. Variables evolving on different time scales are marked by different colours.</p

The dose-effect relationship of IL-1Ra therapy for mild (red circle) and strong T2D (black dot) <i>in silico</i> are shown.

<p>Following the protocol of the clinical trial, glycaemia improvement after 90 days of therapy versus control, is used as a measure. The IL-1Ra threshold predicted by the model is reflected in the jump of the resulting glucose level for both T2D groups. The optimal IL1-Ra dose for strong T2D is substantially larger because of the lower endogenous level of IL-1Ra. The best achieved glucose improvement in response to the therapy is three-fold higher in the case of strong than in mild T2D. The starting glucose level is 11.96 and 18.02 mM for mild and strong T2D, respectively. The final glucose level of the both control groups is 12.21 and 18.82 mM, respectively.</p

A: The bifurcation diagram of the IL-1β-IL-1Ra subsystem as glucose (<i>G</i>) varies.

<p>This subsystem exhibits three stable (full lines) and two unstable (dotted blue lines) steady states. Above a critical glucose level (5.84 mM) the system loses stability of the pre-diabetic state (green line) and progresses to a high IL-1β state (red line), which is stable across the whole physiological glucose range. A third stable state (black line) with even higher IL-1β exists, which, in the hyperglycaemia range, may be associated with advanced T2D. B: A transition from five to three steady states is found that corresponds to the transition from pre-diabetes to overt T2D. Steady states appear as crossing points of the nullclines. The nullclines of IL-1β (red) and IL-1Ra (black) cross in five points at normal glucose level (4.5 mM). When glucose increases, the IL-1β nullcline raises its minimum (inset, transition from red to blue to green curve) such that the low IL-1β and low IL-1Ra steady state vanishes. The system is forced to switch to a high IL-1β state which may be associated with overt T2D. The corresponding glucose level is 4.5, 5.84 and 6.84 mM for the red, blue and green IL-1β nullcline in the inset, respectively.</p

Steady state conditions for the IL-1β/IL-1 Ra subsystem.

<p>Steady state conditions for the IL-1β/IL-1 Ra subsystem.</p

Parameter determined by scanning.

<p>A: Random points are selected in the <i>L</i>_b-<i>A</i>_b plane (normalised with <i>L</i>_c and <i>A</i>_c) and used in the steady state equations (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003798#pcbi.1003798.e002" target="_blank">Eq. (2</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003798#pcbi.1003798.e003" target="_blank">3)</a>) to determine <i>k</i>_1–6. If <i>k</i>_1–6 are non-negative, points either induce an IL-1β switch (red) or do not (blue). B: The IL-1β level <i>L</i>_d/<i>L</i>_c after the switch is shown as a function of IL-1Ra concentration at the bifurcation point.</p

Fitting the model to the fasting glucose history to determine <i>m</i> and <i>τ</i>.

<p>Shown are the best fit results of incident diabetes cases before T2D diagnosis and the data (black line) (red line cross) and non-diabetic controls (red line) (A), interpolated insulin resistance as model input (B), corresponding behaviour of β-cell mass (C) and IL-1β (D).</p