Interstitial Glucose Concentrations Research Articles

114 Effects of greater levels of soy protein and methionine on periparturient health of sows

Abstract Sow prolificacy in the U.S. continues to trend greater, as does sow mortality. Replacement of soy protein (SBM) in sow diets with corn and purified amino acids (AA), may impact the health of highly prolific sows. In 2015, Denmark increased recommendations for SID methionine (MET) to SID lysine (LYS), MET:LYS to 32%, NRC (2012) recommend 27%. The primary objective of this research was to evaluate SBM and MET at greater levels for their effects on markers of health in the peripartum and lactation periods. A total of 38 parity 1 to 3 females (PIC 1050) were utilized with a starting body weight (BW) of 223.4kg ± 13.0 SD. On d 85 of gestation, sows were allocated by BW and parity to one of four treatments: 1 - 30% SBM (30% of diet), 36% MET:LYS; 2 - 15% SBM, 36% MET:LYS; 3 - 30% SBM, 27% MET:LYS; 4 - 15% SBM, 27% MET:LYS. Sows were fed dietary treatments 28 d pre-farrow, according to BW, and ad libitum throughout lactation. Body condition by caliper (BCS), BW, and backfat (BF) were measured on d 0, 21, 2 d post-farrow, and weaning. Sows were assigned a farrowing ease score of 1 to 4 (1-easy to 4-difficult) based on duration, restless activity, savaging, and assistance required. Continuous glucose monitors (CGM) were placed on a subset of sows (n = 12) on d 113 of gestation through 3 d post-farrow. Data were analyzed using the GLM procedure in SAS with sow serving as the experimental unit. A planned t-test was performed on CGM glucose data. Two sows were removed during lactation. The combined effect of 30% SBM and 36% MET:LYS produced an average lactation BW loss of 0.3 kg, while the 15% SBM and 27% MET:LYS treatment, diets similar to NRC, lost an average of 18.1kg. Sows fed the 30% SBM diets had less lactation BW loss than 15% SBM (Table 1; P < 0.10). Sows fed 36% MET:LYS lost less BW than those fed 27% MET:LYS (P < 0.05). The 36% MET:LYS group also lost less backfat during lactation and had lower pre- and post-farrow body temperatures than 27% MET:LYS (P < 0.01 and P < 0.05, respectively). While no differences in blood glucose were observed, in sows with CGM, greater levels of SBM decreased interstitial glucose concentrations (P = 0.055). In conclusion, greater inclusion of SBM and increasing the MET:LYS ratio in sow diets may improve periparturient changes in body condition and health outcomes.

Exercise-induced increase in muscle insulin sensitivity in men is amplified when assessed using a meal test.

Exercise has a profound effect on insulin sensitivity in skeletal muscle. The euglycaemic-hyperinsulinaemic clamp (EHC) is the gold standard for assessment of insulin sensitivity but it does not reflect the hyperglycaemia that occurs after eating a meal. In previous EHC investigations, it has been shown that the interstitial glucose concentration in muscle is decreased to a larger extent in previously exercised muscle than in rested muscle. This suggests that previously exercised muscle may increase its glucose uptake more than rested muscle if glucose supply is increased by hyperglycaemia. Therefore, we hypothesised that the exercise-induced increase in muscle insulin sensitivitywould appear greater after eating a meal than previously observed with the EHC. Ten recreationally active men performed dynamic one-legged knee extensor exercise for 1 h. Following this, both femoral veins and one femoral artery were cannulated. Subsequently, 4 h after exercise, a solid meal followed by two liquid meals were ingested over 1 h and glucose uptake in the two legs was measured for 3 h. Muscle biopsies from both legs were obtained before the meal test and 90 min after the meal test was initiated. Data obtained in previous studies using the EHC (n=106 participants from 13 EHC studies) were used for comparison with the meal-test data obtained in this study. Plasma glucose and insulin peaked 45 min after initiation of the meal test. Following the meal test, leg glucose uptake and glucose clearance increased twice as much in the exercised leg than in the rested leg; this difference is twice as big as that observed in previous investigations using EHCs. Glucose uptake in the rested leg plateaued after 15 min, alongside elevated muscle glucose 6-phosphate levels, suggestive of compromised muscle glucose metabolism. In contrast, glucose uptake in the exercised leg plateaued 45 min after initiation of the meal test and there were no signs of compromised glucose metabolism. Phosphorylation of the TBC1 domain family member 4 (TBC1D4; p-TBC1D4Ser704) and glycogen synthase activity were greater in the exercised leg compared with the rested leg. Muscle interstitial glucose concentration increased with ingestion of meals, although it was 16% lower in the exercised leg than in the rested leg. Hyperglycaemia after meal ingestion results in larger differences in muscle glucose uptake between rested and exercised muscle than previously observed during EHCs. These findings indicate that the ability of exercise to increase insulin-stimulated muscle glucose uptake is even greater when evaluated with a meal test than has previously been shown with EHCs.

Leveraging continuous glucose monitoring for personalized modeling of insulin-regulated glucose metabolism

Continuous glucose monitoring (CGM) is a promising, minimally invasive alternative to plasma glucose measurements for calibrating physiology-based mathematical models of insulin-regulated glucose metabolism, reducing the reliance on in-clinic measurements. However, the use of CGM glucose, particularly in combination with insulin measurements, to develop personalized models of glucose regulation remains unexplored. Here, we simultaneously measured interstitial glucose concentrations using CGM as well as plasma glucose and insulin concentrations during an oral glucose tolerance test (OGTT) in individuals with overweight or obesity to calibrate personalized models of glucose-insulin dynamics. We compared the use of interstitial glucose with plasma glucose in model calibration, and evaluated the effects on model fit, identifiability, and model parameters’ association with clinically relevant metabolic indicators. Models calibrated on both plasma and interstitial glucose resulted in good model fit, and the parameter estimates associated with metabolic indicators such as insulin sensitivity measures in both cases. Moreover, practical identifiability of model parameters was improved in models estimated on CGM glucose compared to plasma glucose. Together these results suggest that CGM glucose may be considered as a minimally invasive alternative to plasma glucose measurements in model calibration to quantify the dynamics of glucose regulation.

Improved glycaemic control induced by evening activity breaks does not persist overnight amongst healthy adults: A randomized crossover trial.

To compare the effects of 4 hours of laboratory-based regular activity breaks (RABs) and prolonged sitting (SIT) on subsequent 48-h free-living interstitial glucose levels in a group of healthy adults. In this randomized crossover trial, participants completed two 4-h laboratory-based interventions commencing at ~5:00 pm: (1) SIT and (2) SIT interrupted with 3 min of body weight resistance exercise activity breaks every 30 min (RABs). Continuous glucose monitoring was performed during the intervention and for 48-h after, during which time participants returned to a free-living setting. Twenty-eight adults (female n = 20, mean ± SD age 25.5 ± 5.6 years, body mass index 29.2 ± 6.9 kg/m2) provided data for this analysis. During the intervention period, RABs lowered mean interstitial glucose by 8.3% (-0.47 mmol/L/4 h, 95% confidence interval [CI] -0.74 to -0.20; p = 0.001) and area under the curve (AUC) by 8.9% (-2.01 mmol/L/4 h, 95% CI -3.05 to -0.97; p < 0.001) compared to SIT. Measures of glycaemic variability were not significantly different during the intervention. There were no significant differences in mean glucose and AUC between conditions during the first nocturnal period and 24-h post intervention. When compared to SIT, RABs increased continuous overall net action of glucose at 1 h and SD glucose by 22% (0.18 mmol/L, 95% CI 0.03 to 0.29; p = 0.018) and 26% (95% CI 4.9 to 42.7; p = 0.019) in the first nocturnal period and by 10% (0.09 mmol/L, 95% CI 0.01, 0.17; p = 0.025) and 15% (95% CI 6.6 to 22.4; p = 0.001) in the 24-h post intervention period, respectively. Performing activity breaks in the evening results in acute reductions in interstitial glucose concentrations; however, the magnitude of these changes is not maintained overnight or into the following 48 hours.

Effect of sodium-glucose cotransporter 2 inhibitor canagliflozin on interstitial glucose concentration in insulin-treated diabetic dogs.

The utility of sodium-glucose cotransporter 2 inhibitors (SGLT2i) has not been reported in insulin-treated diabetic dogs. Canagliflozin, a PO-administered SGLT2i, decreases interstitial glucose concentration (IG) in insulin-treated diabetic dogs. Five insulin-treated diabetic dogs. Uncontrolled open label longitudinal study. Canagliflozin (2-4 mg/kg/day PO) was added to an unchanged insulin dose for 7 days. Fractional excretion of glucose was calculated by dividing the product of urine glucose and serum creatinine concentrations by the product of serum glucose and urine creatinine concentrations. Hypoglycemia was defined as IG <60 mg/dL. Median IG in 2869 measurements obtained while dogs were treated with insulin and canagliflozin was 87 mg/dL (range, 40-500 mg/dL) and was significantly lower than median IG in 1426 measurements obtained while dogs were treated with insulin alone (212 mg/dL; range, 41-500 mg/dL; P < .001). Median fractional excretion of glucose when dogs were treated with insulin and canagliflozin was 1.1% (range, 0.9%-2.0%), significantly higher than when dogs were treated with insulin alone (0.3%; range, 0.01%-1.0%; P = .04). The frequency of hypoglycemia was higher in dogs treated with insulin and canagliflozin (544 of 2869 IG measurements, 19%) compared with the frequency of hypoglycemia in dogs treated with insulin alone (52 of 1426 IG measurements, 4%; P < .001). Canagliflozin may have a role in improving glycemic control in insulin-treated diabetic dogs, but the dose of insulin should be decreased when adding canagliflozin to insulin treatment.

Performance of an interstitial glucose monitoring in patients with type 1 diabetes during haemodialysis

Abstract Background The use of interstitial glucose monitoring devices such as Flash Glucose Monitoring has been shown to be beneficial in patients with type 1 diabetes (T1DM). However, these devices have been little studied in patients with diabetes treated by chronic haemodialysis (HD). Methods The goal of this prospective, observational, multicentric, study was to evaluate the analytical performance of the FreeStyle Libre® 2 (FSL2) sensor in T1DM patients during HD sessions. During three HD sessions, interstitial glucose concentrations (ISFG) given by the FSL2 were compared, every 15 minutes, with blood glucose concentration (BG) obtained simultaneously. BG concentrations were measured by two different glucometers: the Accu-Chek Guide® and the StatStrip® meter. Results Twelve hemodialysis patients were included. Mean age was 54 ± 11 years. Mean diabetes duration was 36.5 ± 11.6 years and dialysis vintage was 35 ± 22 months. A total of 565 pairs of ISFG/BG values were available for analysis. The mean absolute relative difference, defined as the mean of the absolute relative differences between the ISFG and BG measurements, was 17.4% and 20.9% when the ISFG were compared to the StatStrip glucometer or Accu-Chek Guide, respectively. Interstitial results tend to underestimate blood results but all values were classified as having clinically acceptable error. The differences observed remained stable during the dialysis session and were not associated with the ultrafiltration rate. Conclusion The use of the FSL2 interstitial glucose monitoring device in HD patients with T1DM is clinically acceptable, even though the accuracy of the device is generally poorer than in studies including non-dialysis patients.

Functionalized Microwires‐Based Bundle Electrodes for Detection of Multiplexed Metabolites in Interstitial Space

Metabolic substances play a pivotal role in maintaining the body's regular physiological functions. When these processes are disrupted, it can lead to metabolic disorders which may cause severe damage to various organs. Diabetes mellitus, a prevalent metabolic disorder, arises from disturbances in sugar metabolism among other substances. Consequently, there's a pressing need to monitor metabolite levels for early diagnosis. To address this, in this study, a semi‐implantable metabolite sensing system developed around functionalized microwires‐based bundle electrodes (FMBE) is introduced. This FMBE device tracks glucose, hydrogen peroxide (H2O2), and uric acid (UA) levels in vivo in real time, sensitively, and continuously. The FMBE is coated with Au nanoclusters and carbon nanotube–2D carbides and nitride (MXene) nanocomposites to enhance sensing surface area. In vitro characterizations affirm the FMBE's linear responsivity, detection sensitivity, and selectivity toward glucose, H2O2, and UA sensing. In addition, in in vivo testing in healthy and diabetic rats, it is demonstrated that FMBE is able to continuously monitor interstitial glucose, H2O2, and UA concentrations after implantation. The FMBE system, thus, stands out as a promising platform for real‐time, in situ monitoring of metabolite concentrations, potentially assisting in the diagnosis of diabetes and associated complications.

Continuous Monitoring of Interstitial Fluid Glucose Responses to Endurance Exercise with Different Levels of Carbohydrate Intake.

We compared the 24 h changes in interstitial fluid glucose concentration (IGC) following a simulated soccer match between subjects consuming a high-carbohydrate (HCHO; 8 g/kg BW/day) diet and those consuming a moderate-carbohydrate (MCHO; 4 g/kg BW/day) diet. Eight active healthy males participated in two different trials. The subjects were provided with the prescribed diets from days 1 to 3. On day 3, the subjects performed 90 min (2 bouts × 45 min) of exercise simulating a soccer match. The IGC of the upper arm was continuously monitored from days 1 to 4. No significant difference in the IGC was observed between trials during exercise. The total area under the curve (t-AUC) value during exercise did not significantly differ between the HCHO (9719 ± 305 mg/dL·90 min) and MCHO (9991 ± 140 mg/dL·90 min). Serum total ketone body and beta-hydroxybutyrate concentrations were significantly higher in the MCHO than in the HCHO after a second bout of exercise. No significant differences in the IGC were observed between trials at any time point during the night after exercise (0:00-7:00). In addition, t-AUC value during the night did not significantly differ between the HCHO (32,378 ± 873 mg/dL·420 min) and MCHO (31,749 ± 633 mg/dL·420 min). In conclusion, two days of consuming different carbohydrate intake levels did not significantly affect the IGC during a 90 min simulated soccer match. Moreover, the IGC during the night following the exercise did not significantly differ between the two trials despite the different carbohydrate intake levels (8 vs. 4 g/kg BW/day).

Effects Of Different Carbohydrate Intake Levels On Interstitial Fluid Glucose Concentration During High-intensity Intermittent Exercise

Effects Of Different Carbohydrate Intake Levels On Interstitial Fluid Glucose Concentration During High-intensity Intermittent Exercise

Glycemic variability and hypoglycemia before and after Roux-en-Y Gastric Bypass and Sleeve Gastrectomy – A cohort study of females without diabetes

BackgroundRoux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) lead to lower fasting glucose concentrations, but might cause higher glycemic variability (GV) and increased risk of hypoglycemia. However, it has been sparsely studied in patients without preoperative diabetes under normal living conditions. ObjectivesTo study 24-hour interstitial glucose (IG) concentrations, GV, the occurrence of hypoglycemia and dietary intake before and after laparoscopic RYGB and SG in females without diabetes. SettingOutpatient bariatric units at a community and a university hospital. MethodsContinuous glucose monitoring and open-ended food recording over 4 days in 4 study periods: at baseline, during the preoperative low-energy diet (LED) regimen, and at 6 and 12 months postoperatively. ResultsOf 47 patients included at baseline, 83%, 81%, and 79% completed the remaining 3 study periods. The mean 24-hour IG concentration was similar during the preoperative LED regimen and after surgery and significantly lower compared to baseline in both surgical groups. GV was significantly increased 6 and 12 months after surgery compared to baseline. The self-reported carbohydrate intake was positively associated with GV after surgery. IG concentrations below 3.9 mmol/L were observed in 14/25 (56%) of RYGB- and 9/12 (75%) of SG-treated patients 12 months after surgery. About 70% of patients with low IG concentrations also reported hypoglycemic symptoms. ConclusionsThe lower IG concentration in combination with the higher GV after surgery, might create a lower margin to hypoglycemia. This could help explain the increased occurrence of hypoglycemic episodes after RYGB and SG.

Assessment of the FreeStyle Libre 2 interstitial glucose monitor in hypo- and euglycemic cats.

Continuous glucose monitoring systems have been validated for eu- and hyperglycemic cats. The FreeStyle Libre 2 (FSL2) is sufficiently accurate in people during hypoglycemia to guide critical treatment decisions without confirmation of blood glucose concentration (BG). Assess FSL2 accuracy in cats with hypoglycemia. Nine healthy, purpose-bred cats. Hyperinsulinemic-hypoglycemic clamps were performed by IV infusion of regular insulin (constant rate) and glucose (variable rate). Interstitial glucose concentration (IG), measured by FSL2, was compared to BG measured by AlphaTrak2. Data were analyzed for all paired measurements (n = 364) and separately during stable BG (≤1 mg/dL/min change over 10 minutes). Pearson's r test, Bland-Altman test, and Parkes Error Grid analysis respectively were used to determine correlation, bias, and clinical accuracy (P < .05 considered significant). Overall, BG and IG correlated strongly (r = 0.83, P < .0001) in stable glycemia and moderately at all rates of change (r = 0.69, P < .0001). Interstitial glucose concentration underestimated BG in euglycemia, but the BG-IG difference was progressively smaller as BG decreased (12.9 ± 12.2, 8.8 ± 11.2, -3.2 ± 7.4, and -7.8 ± 5.2 mg/dL in the ranges of 80-120 [n = 64], 60-79 [n = 29], 50-59 [n = 71], and 29-49 mg/dL [n = 53], respectively). Although IG underestimates BG throughout most of the hypo-euglycemic range, IG generally overestimates BG in marked hypoglycemia (<60 mg/dL). It is therefore imperative to evaluate FSL2 results in this critical range with caution.

Hand grip strength is inversely associated with total daily insulin dose requirement in patients with type 2 diabetes mellitus: a cross-sectional study.

Short-term (2 weeks to 3 months) insulin intensive therapy using continuous subcutaneous insulin infusion (CSII) can improve islet beta cell function and prolong glycemic remission in patients with newly diagnosed type 2 diabetes mellitus (T2DM). However, the total daily insulin dose (TDD, IU/kg/d) required to achieve near-normoglycemic control with CSII still needs to be frequently adjusted based on blood glucose monitoring. Although real-time continuous glucose monitoring (rtCGM), which measures the interstitial fluid glucose concentration continuously without much difficulty, facilitates the adjustment of insulin dosage, its adoption in the T2DM population is strictly limited by insurance coverage and lack of awareness of rtCGM among clinicians. Thus, it is of clinical significance to identify easy-to-use parameters that may allow a more rapid and accurate prediction of TDD requirement. This study aimed to explore the association between hand grip strength (HGS) and TDD requirement in patients with T2DM receiving CSII therapy. A total of 180 eligible patients with T2DM were enrolled in the study and divided into three groups based on their HGS: low (L), medium (M), and high (H). The TDD requirement was calculated on day 7 or 8 of CSII treatment. Anthropometric parameters, including HGS, skeletal muscle mass, skeletal muscle index (SMI) and 6-m gait speed, and laboratory data, were collected on the morning of the second day after admission, within the first 24 h of CSII therapy. These parameters were used to identify significant predictors of TDD requirement using Pearson or Spearman correlation test, and stepwise multiple regression analysis. There were no significant differences in age, duration of T2DM, waist-to-hip ratio (WHR), body mass index (BMI), blood pressure, liver function, estimated glomerular filtration rate, triglyceride, total cholesterol, glycosylated hemoglobin A1c (HbA1c), homeostatic model assessment of insulin resistance (HOMA-IR), and homeostasis model assessment of beta cell function (HOMA-β) among the groups. The H group had higher body muscle mass-to-fat ratio (BMFR), skeletal muscle mass-to-fat ratio (SMFR), SMI, 6-m gait speed, and lower TDD requirement than the M and L groups. The HGS negatively correlated with TDD requirement (r = -0.33, p < 0.001) after adjusting for sex, age, BMI, WHR, HbA1c, Ln (HOMA-β), Ln (HOMA-IR), Ln (BMFR), Ln (SMFR), SMI, and 6-m gait speed. Multivariate stepwise regression analysis indicated that HGS was an independent predictor of TDD requirement in patients with T2DM (β = -0.45, p < 0 001). Lower HGS is associated with an increased TDD requirement in T2DM patients. HGS may facilitate the prediction of TDD requirement in T2DM patients receiving CSII therapy.

A Markov Model of Gap Occurrence in Continuous Glucose Monitoring Data for Realistic in Silico Clinical Trials

Background and objectiveContinuous glucose monitoring (CGM) sensors measure interstitial glucose concentration every 1-5 min for days or weeks. New CGM-based diabetes therapies are often tested in in silico clinical trials (ISCTs) using diabetes simulators. Accurate models of CGM sensor inaccuracies and failures could help improve the realism of ISCTs. However, the modeling of CGM failures has not yet been fully addressed in the literature. This work aims to develop a mathematical model of CGM gaps, i.e., occasional portions of missing data generated by temporary sensor errors (e.g., excessive noise or artifacts). MethodsTwo datasets containing CGM traces collected in 167 adults and 205 children, respectively, using the Dexcom G6 sensor (Dexcom Inc., San Diego, CA) were used. Four Markov models, of increasing complexity, were designed to describe three main characteristics: number of gaps for each sensor, gap distribution in the monitoring days, and gap duration. Each model was identified on a portion of each dataset (training set). The remaining portion of each dataset (real test set) was used to evaluate model performance through a Monte Carlo simulation approach. Each model was used to generate 100 simulated test sets with the same size as the real test set. The distributions of gap characteristics on the simulated test sets were compared with those observed on the real test set, using the two-sample Kolmogorov-Smirnov test and the Jensen-Shannon divergence. ResultsA six-state Markov model, having two states to describe normal sensor operation and four states to describe gap occurrence, achieved the best results. For this model, the Kolmogorov-Smirnov test found no significant differences between the distribution of simulated and real gap characteristics. Moreover, this model obtained significantly lower Jensen-Shannon divergence values than the other models. ConclusionsA Markov model describing CGM gaps was developed and validated on two real datasets. The model describes well the number of gaps for each sensor, the gap distribution over monitoring days, and the gap durations. Such a model can be integrated into existing diabetes simulators to realistically simulate CGM gaps in ISCTs and thus enable the development of more effective and robust diabetes management strategies.

0003 Sleep and Circadian Disruption Induced by Simulated Night Shift Work Impair Cardiometabolic Outcomes in Healthy Adults

Abstract Introduction People who work evening, night or rotating shifts make up 20% of the US workforce and have a heightened risk for Type 2 diabetes (T2D) and cardiovascular disease (CVD) compared to people who work days, possibly due to repeated bouts of sleep and circadian disruption. However, the mechanism(s) by which sleep and circadian disruption impair cardiometabolic health are unclear. We therefore investigated the impact of acute circadian misalignment on factors related to cardiometabolic health including interstitial glucose concentration, glucose tolerance, resting systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR). Methods Ten healthy adults (6F, 25.0±4.5y, BMI: 22.0±2.2kg/m2; mean±SD) participated in an ongoing 6d inpatient simulated night shift protocol to induce sleep and circadian disruption. Participants lived at the Sleep and Metabolism Laboratory for 2d to simulate day shift work followed by 2d of simulated night shift work. Continuous interstitial glucose monitoring was conducted throughout the study (FreeStyle Libre Pro; Abbott, Alameda, CA, USA). BP and HR were assessed 30 minutes after waketime (Omron HEM-FL31; Omron Healthcare, Kyoto, JP) followed by an oral glucose tolerance tests (OGTT) conducted 1.5h after waketime in both conditions. Results Simulated night shift work was associated with significantly higher interstitial glucose area under the curve (AUC) in response to an identical first meal after waking (18,299±1412 v 14,606±2035 [mg/dl]*min; p=0.009; mean±SEM) as well as plasma glucose AUC during the OGTT (23,239±2574 v 18,776±1832; p=0.002) compared to simulated day work. Furthermore, simulated night shift work was associated with a significant increase in resting DBP (75±3 v 66±2; p=0.017) compared to day work. No changes were observed in resting SBP (p=0.40) or HR (p=0.11) between conditions. Conclusion Sleep and circadian disruption induced by simulated night shift work appear to impair markers of cardiometabolic health, even in healthy, lean adults. Night shift work is largely unavoidable in modern society, thus is it critical to identify strategies or countermeasures to prevent the impact of circadian misalignment on T2D and CVD risk in a large portion of the population. Support (if any) This project was supported in part by R01DK125653 &amp; F31HL165883.

Spectro-spatial features in distributed human intracranial activity proactively encode peripheral metabolic activity

Mounting evidence demonstrates that the central nervous system (CNS) orchestrates glucose homeostasis by sensing glucose and modulating peripheral metabolism. Glucose responsive neuronal populations have been identified in the hypothalamus and several corticolimbic regions. However, how these CNS gluco-regulatory regions modulate peripheral glucose levels is not well understood. To better understand this process, we simultaneously measured interstitial glucose concentrations and local field potentials in 3 human subjects from cortical and subcortical regions, including the hypothalamus in one subject. Correlations between high frequency activity (HFA, 70–170 Hz) and peripheral glucose levels are found across multiple brain regions, notably in the hypothalamus, with correlation magnitude modulated by sleep-wake cycles, circadian coupling, and hypothalamic connectivity. Correlations are further present between non-circadian (ultradian) HFA and glucose levels which are higher during awake periods. Spectro-spatial features of neural activity enable decoding of peripheral glucose levels both in the present and up to hours in the future. Our findings demonstrate proactive encoding of homeostatic glucose dynamics by the CNS.

Performance of the FreeStyle Libre Flash Glucose Monitoring System during an Oral Glucose Tolerance Test and Exercise in Healthy Adolescents.

This study's aim was to assess FreeStyle Libre Flash glucose monitoring (FGM) performance during an oral glucose tolerance test (OGTT) and treadmill exercise in healthy adolescents. This should advance the feasibility and utility of user-friendly technologies for metabolic assessments in adolescents. Seventeen healthy adolescents (nine girls aged 12.8 ± 0.9 years) performed an OGTT and submaximal and maximal treadmill exercise tests in a laboratory setting. The scanned interstitial fluid glucose concentration ([ISFG]) obtained by FGM was compared against finger-prick capillary plasma glucose concentration ([CPG]) at 0 (pre-OGTT), -15, -30, -60, -120 min post-OGTT, pre-, mid-, post- submaximal exercise, and pre- and post- maximal exercise. Overall mean absolute relative difference (MARD) was 13.1 ± 8.5%, and 68% (n = 113) of the paired glucose data met the ISO 15197:2013 criteria. For clinical accuracy, 84% and 16% of FGM readings were within zones A and B in the Consensus Error Grid (CEG), respectively, which met the ISO 15197:2013 criteria of having at least 99% of results within these zones. Scanned [ISFG] were statistically lower than [CPG] at 15 (-1.16 mmol∙L-1, p < 0.001) and 30 min (-0.74 mmol∙L-1, p = 0.041) post-OGTT. Yet, post-OGTT glycaemic responses assessed by total and incremental areas under the curve (AUCs) were not significantly different, with trivial to small effect sizes (p ≥ 0.084, d = 0.14-0.45). Further, [ISFGs] were not different from [CPGs] during submaximal and maximal exercise tests (interaction p ≥ 0.614). FGM can be a feasible alternative to reflect postprandial glycaemia (AUCs) in healthy adolescents who may not endure repeated finger pricks.

Differences in venous, capillary and interstitial glucose concentrations in individuals without diabetes after glucose load

Abstract Objectives Differences between capillary and venous glucose concentrations have been reported in the past. In continuous glucose monitoring (CGM) system performance studies, comparator measurements are often performed in venous samples, despite CGM systems typically aiming at providing capillary-like values. In this study, differences between venous, capillary and interstitial glucose concentrations, measured with a laboratory analyzer, a self-monitoring of blood glucose (SMBG) system and an intermittent-scanning CGM system were investigated in subjects without diabetes after glucose load. Methods During the study, an oral glucose tolerance test (oGTT) was performed with 41 participants who had no known history of diabetes (mean age 25.5 ± 9.7 years). Venous blood samples for measurement with a laboratory analyzer were collected before drinking the standardized 75 g glucose solution and after 60 and 120 min. In parallel, capillary blood was obtained for measurement with a laboratory analyzer and an SMBG system, and interstitial glucose values were measured with an intermittent-scanning CGM system. Results Glucose concentrations in the fasting state were slightly different for the three different compartments whereas considerable differences (some median differences exceeding 30 %) in glucose concentration were observed 60 and 120 min after the start of the oGTT. Conclusions Marked differences with a high inter-individual variability between venous, capillary, and interstitial fluid glucose concentrations were found especially after glucose load. These differences can affect perceived CGM accuracy in performance studies depending on the specific comparator method used, and they are potentially relevant in clinical practice, like diabetes diagnosis.

Combined effects of exercise and different levels of acute hypoxic severity: A randomized crossover study on glucose regulation in adults with overweight.

Purpose: The aim of this study was to investigate the influence of manipulating hypoxic severity with low-intensity exercise on glucose regulation in healthy overweight adults. Methods: In a randomized crossover design, 14 males with overweight (age: 27 ± 5years; body mass index (BMI) 27.1 ± 1.8kg⋅m2) completed three exercise trials involving 60min aerobic exercise cycling at 90% lactate threshold in normoxia (NM, FiO2 = 20.9%), moderate hypoxia (MH, FiO2 = 16.5%) and high hypoxia (HH, FiO2 = 14.8%). A post-exercise oral glucose tolerance test (OGTT) was performed. Venous blood samples were analyzed for incremental area under the curve (iAUC), plasma glucose and insulin, as well as exerkine concentrations (plasma apelin and fibroblast growth factor 21 [FGF-21]) pre- and post-exercise. A 24-h continuous glucose monitoring (CGM) was used to determine interstitial glucose concentrations. Heart rate, oxygen saturation (SpO2) and perceptual measures were recorded during exercise. Results: Post-exercise OGTT iAUC for plasma glucose and insulin concentrations were lower in MH vs. control (p = 0.02). Post-exercise interstitial glucose iAUC, plasma apelin and FGF-21 were not different between conditions. Heart rate was higher in HH vs. NM and MH, and MH vs. NM (p < 0.001), while SpO2 was lower in HH vs. NM and MH, and MH vs. NM (p < 0.001). Overall perceived discomfort and leg discomfort were higher in HH vs. NM and MH (p < 0.05), while perceived breathing difficulty was higher in HH vs. NM only (p = 0.003). Conclusion: Compared to higher hypoxic conditions, performing acute aerobic-based exercise under moderate hypoxia provided a more effective stimulus for improving post-exercise glucose regulation while concomitantly preventing excessive physiological and perceptual stress in healthy overweight adults.

Relationships between feeding and glucose concentrations in healthy term infants during the first five days after birth-the Glucose in Well Babies Study (GLOW).

The World Health Organization recommends breastfeeding be commenced as soon as possible after birth. Amongst other benefits, early feeding is expected to support the metabolic transition after birth, but effects on blood glucose concentrations are controversial. We sought to describe the changes in interstitial glucose concentrations after feedings over the first five postnatal days. In healthy singleton term infants, all feeds were recorded using a smart phone app. Glucose concentrations were measured by blinded interstitial monitoring, calibrated by heel-prick capillary samples 2-4 times/d. Feeding sessions were included if a start and end time were recorded, and if the interval between the start of successive feeds was >90 min. The area under the glucose concentration curve (AUC) was calculated by trapezoidal addition from baseline (median of the 3 measurements before the beginning of the session). The maximum deviation (MD) was the greatest change in glucose concentration (positive or negative) from baseline to the next feeding session or 180 min, whichever came first. Data were analyzed using Stata V17 and are presented as mean (95% CI) in mmol/L. Data were available for 62 infants and 1,770 feedings. The glucose response to breastfeeding was not different from zero on day 1 [day 1 AUC 0.05 (-0.00, 0.10), MD 0.06 (-0.05, 0.16)], but increased thereafter (day 3 (AUC 0.23 (0.18, 0.28), MD 0.41 (0.32, 0.50), day 5 AUC 0.11 (0.06, 0.16), MD 0.28 (0.18, 0.37), p < 0.001 for age effect). Glucose response increased with increased duration of breastfeeding (<30 min AUC 0.06 (0.02,0.09), MD 0.12 (0.04,0.19), >30 min AUC 0.20 (0.16, 0.23) MD 0.37 (0.30, 0.44), p < 0.001 for duration effect) and this was observed even in the first 2 days (<30 min AUC-0.02 (-0.06, 0.03), MD -0.06 (-0.15, 0.03), >30 min AUC 0.12 (0.08, 0.16), MD 0.19 (0.11, 0.27), overall p < 0.001 for age x duration interaction). In feeding sessions that were not breastfeeding, the glucose response was greater after formula than after expressed human milk [AUC 0.29 (0.15, 0.29), MD 0.48 (-0.12, 0.61)], and greater after feed volumes >20 ml than <10 ml [20-30 ml AUC 0.19 (0.01, 0.27), MD 0.23 (-0.01, 0.46)]. The glucose response to feeding in the days after birth increases with postnatal age and duration of the feeding episode. Breastfeeding for <30 min has little effect on glucose concentrations in the first two days.

The impact of physical inactivity on glucose homeostasis when diet is adjusted to maintain energy balance in healthy, young males

It is unclear if dietary adjustments to maintain energy balance during reduced physical activity can offset inactivity-induced reductions in insulin sensitivity and glucose disposal to produce normal daily glucose concentrations and meal responses. Therefore, the aim of the present study was to examine the impact of long-term physical inactivity (60 days of bed rest) on daily glycemia when in energy balance. Interstitial glucose concentrations were measured using Continuous Glucose Monitoring Systems (CGMS) for 5 days before and towards the end of bed rest in 20 healthy, young males (Age: 34±8 years; BMI: 23.5±1.8kg/m2). Energy intake was reduced during bed rest to match energy expenditure, but the types of foods and timing of meals was maintained. Fasting venous glucose and insulin concentrations were determined, as well as the change in whole-body glucose disposal using a hyperinsulinemic-euglycemic clamp (HIEC). Following long-term bed rest, fasting plasma insulin concentration increased 40% (p=0.004) and glucose disposal during the HIEC decreased 24% (p<0.001). Interstitial daily glucose total area under the curve (tAUC) from pre-to post-bed rest increased on average by 6% (p=0.041), despite a 20 and 25% reduction in total caloric and carbohydrate intake, respectively. The nocturnal period (00:00-06:00) showed the greatest change to glycemia with glucose tAUC for this period increasing by 9% (p=0.005). CGMS measures of daily glycemic variability (SD, J-Index, M-value and MAG) were not changed during bed rest. Reduced physical activity (bed rest) increases glycemia even when daily energy intake is reduced to maintain energy balance. However, the disturbance to daily glucose homeostasis was much more modest than the reduced capacity to dispose of glucose, and glycemic variability was not negatively affected by bed rest, likely due to positive mitigating effects from the contemporaneous reduction in dietary energy and carbohydrate intake. NCT03594799 (registered July 20, 2018) (https://clinicaltrials.gov/ct2/show/NCT03594799).