Citations

Background: Several clinical trials have been performed to assess safety and efficacy of closed-loop control. Some included physical activity (PA), with the goal of challenging the control algorithms with a rapid change in insulin sensitivity while reducing the risk of hypoglycemia. However, the question remains as to the necessity to inform the control algorithm on the imminent PA. The aim here is to assess in silico (i) if it is necessary to announce upcoming PA and (ii) if this is the case, what is the safest strategy of basal insulin reduction in the context of the closed-loop control. Methods: We modified the University of Virginia/Padova type 1 diabetes simulator to incorporate the effect of PA based on a study in healthy subjects that demonstrated an almost doubling of insulin sensitivity during PA versus rest. Two in silico experiments, including a PA session, have been simulated on the virtual adult population: One in the absence of and one with different degrees of reductions and durations of basal insulin infusion rates. Results: Most in silico subjects experienced hypoglycemia in the absence of basal insulin adjustment. We show that, in the absence of patient-specific information, a safe and effective strategy is to reduce basal insulin by 50% starting 90 min before exercise and by 30% during exercise. Conclusions: Our results suggest that control algorithms could benefit by knowing an upcoming PA. Ideally, the control algorithm should be informed about the patient-specific basal insulin reduction pattern. An alternative strategy that has been proposed here has been deemed safe and effective in in silico experiments.

Background: Glucose sensors measure glucose concentration in the interstitial fluid (ISF), remote from blood. ISF glucose is well known to be “delayed” with respect to blood glucose (BG). However, ISF glucose is not simply a shifted-in-time version of BG but exhibits a more complex pattern. Methods: To gain insight into this problem, one can use linear systems theory. However, this may lose a more clinical readership, thus we use simulation and two case studies to convey our thinking in an easier way. In particular, we consider BG concentration measured after meal and exercise in 12 healthy volunteers, whereas ISF glucose is simulated using a well-accepted model of blood–ISF glucose kinetics, which permits calculation of the equilibration time, a parameter characterizing the system. Two metrics are defined: blood and ISF glucose difference at each time point and time to reach the same glucose value in blood and ISF. Results: The simulation performed and the two metrics show that the relationship between blood–ISF glucose profiles is more complex than a pure shift in time and that the pattern depends on both equilibration time and BG. Conclusions: In this in silico study, we have illustrated, with simple case studies, the meaning of the of ISF glucose with respect to BG. Understanding that ISF glucose is not just a shifted-in-time version but a distorted mirror of BG is important for a correct use of continuous glucose monitoring for diabetes management.

Our recent study defined the chemokine-induced human monocyte signaling under normoglycemic condition. To explore the hyperglycemia-induced monocyte signaling, we performed adhesion, migration, and transmigration assays on human monocytes obtained from THP-1 cell line in the presence of normal (5 mM) and high (10 and 20 mM) glucose concentrations without chemokines. We observed augmented ( P < 0.01) monocyte adhesion to human umbilical vein endothelial cell monolayer at 10 than 5 mM glucose with no further increase at 20-mM glucose concentration ( P < 0.07 vs 10 mM; P < 0.01 vs 5 mM). But incremental increases in monocyte migration ( P < 0.01), transmigration ( P < 0.01), and stress fiber response ( P < 0.01) were observed at 10- and 20-mM glucose concentrations in comparison to 5-mM glucose concentrations. We found gradational increase ( P < 0.01) in phosphorylation of Akt S473 and glycogen synthase kinase (GSK3β S9 ) in hyperglycemia (10 and 20 mM) when compared with 5 mM glucose. Furthermore, hyperglycemia (both 10 and 20 mM)-treated monocyte showed up-regulated phosphorylation of p101 and p110γ subunits of PI-3 kinase in comparison to 5 mM glucose. Hyperglycemia-induced monocyte migration was restored to basal levels in the presence of PI-3 kinase inhibitor, LY. These observations imply that modest hyperglycemia per se, as is commonly observed in diabetic individuals, is a potent stimulator of monocyte activity even without chemokines.

Objective Inadequate vascular remodeling is contributory to increased cardiovascular events in people with type 2 diabetes mellitus (DM) and impaired fasting glucose (IFG). Vascular endothelial growth factor (VEGF) and its regulatory molecule soluble Flt-1(sFlt-1) play important roles in atherogenesis. Research Design We measured fasting plasma concentrations of VEGF and sFlt-1 in 11 nondiabetic (ND) (aged 46.1 ± 2.1 years; body mass index [BMI], 26.1 ± 0.9 kg/m 2 ; glucose, 5.0 ± 0.1 mM), 15 IFG (aged 52.9 ± 1.8 years; BMI, 32.7 ± 1.3 kg/m 2 ; glucose, 6.4 ± 0.1 mM), and 8 DM (aged 55.8 ± 3.2 years; BMI, 30.0 ± 1.0 kg/m 2 ; glucose, 9.3 ± 0.5 mM) subjects. Results Plasma VEGF (42.1 ± 4.0 vs 24.2 ± 0.9 vs 29.4 ± 3.8 pg/mL, respectively) and sFlt-1 (119.4 ± 4.9 vs 58.9 ± 3.2 vs 56.7 ± 1.2 pg/mL, respectively) concentrations were higher ( P < 0.04) in DM than IFG and ND subjects. Whereas VEGF concentrations were significantly lower ( P < 0.05) in IFG than in ND subjects, sFlt-1 concentrations did not differ between the IFG and ND subjects. Conclusions Although plasma VEGF concentrations were higher (35%) in DM than in ND subjects, VEGF action on vascular remodeling was likely attenuated by higher sFlt-1 concentrations in DM. In contrast, IFG subjects did not have major perturbations in either VEGF or sFlt-1 levels. Further studies defining the roles of these mediators in DM and IFG are necessary to extend these observations.

Background: The relationship between daily psychological stress and BG fluctuations in type 1 diabetes (T1DM) is unclear. More research is needed to determine if stress-related BG changes should be considered in glucose control algorithms. This study in the usual free-living environment examined relationships among routine daily stressors and BG profile measures generated from CGM readings. Methods: A total of 33 participants with T1DM on insulin pumps wore a CGM device for 1 week and recorded daily ratings of psychological stress, carbohydrates, and insulin boluses. Results: Within-subjects ANCOVAs found a significant relationship between daily stress and indices of BG variability/instability ( r = .172 to .185, P = .011 to .018, r 2 = 2.97% to 3.43%), increased % time in hypoglycemia ( r = .153, P = .036, r 2 = 2.33%) and decreased carbohydrate consumption ( r = –.157, P = .031, r 2 = 2.47%). Models accounted for more variance for individuals reporting the highest daily stress. There was no relationship between stress and mean daily glucose or low/high glucose risk indices. Conclusions: These preliminary findings suggest that naturally occurring daily stressors can be associated with increased glucose instability and hypoglycemia, as well as decreased food consumption. In addition, findings support the hypothesis that some individuals are more metabolically reactive to stress. More rigorous studies using CGM technology are needed to understand whether the impact of daily stress on BG is clinically meaningful and if it is a behavioral factor that should be considered in glucose control systems for some individuals.

Abstract Context: Early postprandial hyperglycemia and delayed hypoglycemia remain major problems in current management of type 1 diabetes (T1D). Objective: Our objective was to investigate the effects of pramlintide, known to suppress glucagon and delay gastric emptying, on postprandial glucose fluxes in T1D. Design: This was a single-center, inpatient, randomized, crossover study. Patients: Twelve patients with T1D who completed the study were analyzed. Interventions: Subjects were studied on two occasions with or without pramlintide. Triple tracer mixed-meal method and oral minimal model were used to estimate postprandial glucose turnover and insulin sensitivity (SI). Integrated liver insulin sensitivity was calculated based on glucose turnover. Plasma glucagon and insulin were measured. Main Outcome Measure: Glucose turnover and SI were the main outcome measures. Results: With pramlintide, 2-hour postprandial glucose, insulin, glucagon, glucose turnover, and SI indices showed: plasma glucose excursions were reduced (difference in incremental area under the curve [iAUC], 444.0 mMmin, P = .0003); plasma insulin concentrations were lower (difference in iAUC, 7642.0 pMmin; P = .0099); plasma glucagon excursions were lower (difference in iAUC, 1730.6 pg/mlmin; P = .0147); meal rate of glucose appearance was lower (difference in iAUC: 1196.2 μM/kg fat free mass [FFM]; P = .0316), endogenous glucose production was not different (difference in iAUC: −105.5 μM/kg FFM; P = .5842), rate of glucose disappearance was lower (difference in iAUC: 1494.2 μM/kg FFM; P = .0083). SI and liver insulin sensitivity were not different between study visits (P &gt; .05). Conclusions: Inhibition of glucagon and gastric emptying delaying reduced 2-hour prandial glucose excursions in T1D by delaying meal rate of glucose appearance.

Background: Recent advances in accuracy and reliability of continuous glucose monitoring (CGM) devices have focused renewed interest on the use of such technology for therapeutic dosing of insulin without the need for independent confirmatory blood glucose meter measurements. An important issue that remains is the susceptibility of CGM devices to erroneous readings in the presence of common pharmacologic interferences. We report on a new method of assessing CGM sensor error to pharmacologic interferences using the example of oral administration of acetaminophen. Materials and Methods: We examined the responses of several different Food and Drug Administration–approved and commercially available CGM systems (Dexcom [San Diego, CA] Seven ® Plus™, Medtronic Diabetes [Northridge, CA] Guardian ® , and Dexcom G4 ® Platinum) to oral acetaminophen in 10 healthy volunteers without diabetes. Microdialysis catheters were placed in the abdominal subcutaneous tissue. Blood and microdialysate samples were collected periodically and analyzed for glucose and acetaminophen concentrations before and after oral ingestion of 1 g of acetaminophen. We compared the response of CGM sensors with the measured acetaminophen concentrations in the blood and interstitial fluid. Results: Although plasma glucose concentrations remained constant at approximately 90 mg/dL (approximately 5 m M ) throughout the study, CGM glucose measurements varied between approximately 85 to 400 mg/dL (from approximately 5 to 22 m M ) due to interference from the acetaminophen. The temporal profile of CGM interference followed acetaminophen concentrations measured in interstitial fluid (ISF). Conclusions: This is the first direct measurement of ISF concentrations of putative CGM interferences with simultaneous measurements of CGM performance in the presence of the interferences. The observed interference with glucose measurements in the tested CGM devices coincided temporally with appearance of acetaminophen in the ISF. The method applied here can be used to determine the susceptibility of current and future CGM systems to interference from acetaminophen or other exogenous pharmacologic agents.

Background: Quantitative assessment of the dynamic relationship between plasma and interstitial fluid (ISF) glucose and the estimation of the plasma-to-ISF delay are of major importance to determine the accuracy of subcutaneous glucose sensors, an essential component of open- and closed-loop therapeutic systems for type 1 diabetes mellitus (T1DM). The goal of this work is to develop a model of plasma-to-ISF glucose kinetics from multitracer plasma and interstitium data, obtained by microdialysis, in healthy and T1DM subjects, under fasting conditions. Materials and Methods: A specific experimental design, combining administration of multiple tracers with the microdialysis technique, was used to simultaneously frequently collect plasma and ISF data. Linear time-invariant compartmental modeling was used to describe glucose kinetics from the tracer data because the system is in steady state. Results: A two-compartment model was shown accurate and was identified from both plasma and ISF data. An “equilibration time” between plasma and ISF of 9.1 and 11.0 min (median) in healthy and T1DM subjects, respectively, was calculated. Conclusions: We have demonstrated that, in steady-state condition, the glucose plasma-to-ISF kinetics can be modeled with a linear two-compartment model and that the “equilibration time” between the two compartments can be estimated with precision. Future studies will assess plasma-to-interstitium glucose kinetics during glucose and insulin perturbations in both healthy and T1DM subjects.

Background: Understanding the effect size, variability, and underlying physiology of the dawn phenomenon is important for next-generation closed-loop control algorithms for type 1 diabetes (T1D). Subjects and Methods: We used an iterative protocol design to study 16 subjects with T1D on individualized insulin pump therapy for two successive nights. Endogenous glucose production (EGP) rates at 3 a.m. and 7 a.m. were measured with [6,6- 2 H 2 ]glucose as a single tracer, infused from midnight to 7 a.m. in all subjects. To explore possibility of tracer recycling due to prolonged [6,6- 2 H 2 ]glucose infusion, which was highly probable after preplanned interim data analyses, we infused a second tracer, [6- 3 H]glucose, from 4 a.m. to 7 a.m. in the last seven subjects to measure EGP at 7 a.m. Results: Cortisol concentrations increased during both nights, but changes in glucagon and insulin concentration were inconsistent. Although the plasma glucose concentrations rose from midnight to 7 a.m. during both nights, EGP measured with [6,6- 2 H 2 ]glucose between 3 a.m. and 7 a.m. did not differ during Night 1 but fell in Night 2. However, EGP measured with [6- 3 H]glucose at 7 a.m. was higher than that measured with [6,6- 2 H 2 ]glucose during both nights, thereby suggesting tracer recycling probably underestimating EGP calculated at 7 a.m. with [6,6- 2 H 2 ]glucose. Likewise, EGP was higher at 7 a.m. with [6- 3 H]glucose than at 3 a.m. with [6,6- 2 H 2 ]glucose during both nights. Conclusions: The data demonstrate a consistent overnight rise in glucose concentrations through increased EGP, mediated likely by rising cortisol concentrations. The observations with the dual tracer approach imply significant tracer recycling leading to underestimation of EGP measured by longer-duration tracer infusion.