Dynamic of Glucose Homeostasis in Virtual Patients: A Comparison between Different Behaviors

This work presents a mathematical model of homeostasis dynamics in healthy individuals, focusing on the generation of conductive data on glucose homeostasis throughout the day under dietary and physical activity factors. Two case studies on glucose dynamics for populations under conditions of physical activity and sedentary lifestyle were developed. For this purpose, two types of virtual populations were generated, the first population was developed according to the data of a total of 89 physical persons between 20 and 75 years old and the second was developed using the Monte Carlo approach, obtaining a total of 200 virtual patients. In both populations, each participant was classified as an active or sedentary person depending on the physical activity performed. The results obtained demonstrate the capacity of virtual populations in the generation of in-silico approximations similar to those obtained from in-vivo studies. Obtaining information that is only achievable through specific in-vivo experiments. Being a tool that generates information for the approach of alternatives in the prevention of the development of type 2 Diabetes.

Characterization of Individualized Glycemic Excursions during a Standardized Bout of Hypoglycemia-Inducing Exercise and Subsequent Hypoglycemia Treatment—A Pilot Study

The glycemic response to ingested glucose for the treatment of hypoglycemia following exercise in type 1 diabetes patients has never been studied. Therefore, we aimed to characterize glucose dynamics during a standardized bout of hypoglycemia-inducing exercise and the subsequent hypoglycemia treatment with the oral ingestion of glucose. Ten male patients with type 1 diabetes performed a standardized bout of cycling exercise using an electrically braked ergometer at a target heart rate (THR) of 50% of the individual heart rate reserve, determined using the Karvonen equation. Exercise was terminated when hypoglycemia was reached, followed by immediate hypoglycemia treatment with the oral ingestion of 20 g of glucose. Arterialized blood glucose (ABG) levels were monitored at 5 min intervals during exercise and for 60 min during recovery. During exercise, ABG decreased at a mean rate of 0.11 ± 0.03 mmol/L·min−1 (minimum: 0.07, maximum: 0.17 mmol/L·min−1). During recovery, ABG increased at a mean rate of 0.13 ± 0.05 mmol/L·min−1 (minimum: 0.06, maximum: 0.19 mmol/L·min−1). Moreover, 20 g of glucose maintained recovery from hypoglycemia throughout the 60 min postexercise observation window.

PSXV-16 Blood glucose dynamics after feeding in the Orlov trotter horses in the conditions of the training center in preparation for trotter-racing

It is necessary to consider the factors affecting the dynamics and blood glucose (BG) level to maintain a horse’s high performance and health during intensive training. The study aimed to research the influence of the feeding regime on the change in BG level in the Orlov trotter horses during the period of intensive training (summer) in the conditions of the stud farm’s training center in the Kaluga region (Russia). Horses aged 2 to 4 years, stallions (n = 7), and mares (n = 5) received commercial mixed feed three times a day and grass hay in free access. Four times a week after lunch, horses are released into the paddock with cut grass. Blood was collected from the jugular vein. Blood was collected before morning feeding and then every hour until four h after morning and afternoon feeding. The dynamics of BG changes depending on the presence or absence of the grass paddock after feeding were evaluated. If horses remained in the stall after feeding, the BG level gradually increased, reaching a maximum (4.95 ± 0.21 mmol/L) 3 hours after feeding and was significantly higher (P ≤ 0.05) than when they were immediately moved to the paddock with grass. The maximum BG concentration in horses in the paddock was observed 1 hour after feeding (4.55 ± 0.21 mmol/L); it didn’t have significant differences with the BG level after 1 hour in “stall horses” (4.5 ± 0.14 mmol/L). Then the BG level of the “paddock horses” gradually decreased, and in the “stall horses” increased. No significant difference in BG levels was observed 4 hours after feeding. When horses can walk in a paddock after feeding concentrates and eat grass, blood glucose levels do not rise and tend to decrease.

Glucose levels between the anterior chamber of the eye and blood are correlated based on blood glucose dynamics

Glycemic control is essential to manage metabolic diseases such as diabetes. Frequent measurements of systemic glucose levels with prompt managements can prevent organ damages. The eye is a glucose highly demanding organ in our body, and the anterior chamber (AC) in the eye has been suggested for a noninvasive blood glucose monitoring site. However, calculating blood glucose levels from measuring glucose levels in AC has been difficult and unclear. In this study, we aimed to examine glucose levels from AC and find a correlation with blood glucose levels. A total of 30 patients with cataracts (men and women, study 1; 7 and 3, study 2; 9 and 11) who visited Keio University Hospital from 2015 to 2018 and agreed to participate in this study were recruited. Glucose levels from AC and the blood were examined by a UV-hexokinase or H2O2-electrode method before/during the cataract surgery. These values were analyzed with regression analyses depending on the groups (blood glucose-ascending and descending groups). In the blood glucose-descending group, glucose levels from AC were strongly correlated with blood glucose levels (a high R2 value, 0.8636). However, the relatively moderate correlation was seen in the blood glucose-ascending group (a low R2 value, 0.5228). Taken together, we showed different correlation ratios on glucose levels between AC and the blood, based on blood glucose dynamics. Stacking data regarding this issue would enable establishing noninvasive blood glucose monitoring from measuring glucose levels in AC more correctly, which will be helpful for proper and prompt managements for glucose-mediated complications.

Blood glucose dynamics during sleep in patients with obstructive sleep apnea and normal glucose tolerance: effects of CPAP therapy

Purpose Glycemic variability (GV) and hypoglycemia during nighttime are presumed to be associated with fatal bradycardia. The aim of this prospective study was to evaluate blood glucose dynamics during sleep in patients with obstructive sleep apnea syndrome (OSA) and normal glucose tolerance. Methods Patients with OSA and no diabetes who underwent type 1 overnight polysomnography from December 2018 to May 2020 participated in this study. GV was evaluated in all participants for 14 days using a flash glucose monitoring device. Correlations were examined between GV indexes and indexes related to sleep breathing disorders, the effects of treatment with continuous positive airway pressure (CPAP) on these GV indexes, and the characteristics of glucose dynamics in different OSA subtypes classified by sleep stage. Results Among 42 patients with OSA and no diabetes, the standard deviation of GV during sleep correlated significantly with sleep time spent with oxygen saturation <90% (r=0.591, p=0.008). High blood glucose index during sleep correlated significantly with stage N1% (r=0.491, p=0.032) and negatively with stage N2% (r=−0.479, p=0.038). High blood glucose index correlated significantly with sleep time spent with oxygen saturation <90% (r=0.640, p=0.003). The rapid eye movement–related OSA group had a higher incidence of hypoglycemia. One-week with CPAP treatment significantly improved GV during sleep, standard deviation of GV (from 12.1 to 9.0 mg/dL, p<0.001), and high blood glucose index (from 0.7 to 0.4, p=0.006). Conclusions To evaluate GV during sleep in patients with OSA may be useful for clinical risk management. CPAP treatment for 1 week may have an improving GV and high blood glucose index. Clinical trial registration UMIN000038489 2019/11/04, UMIN 000025433 2016/12/27

A Glucose-Only Model to Extract Physiological Information from Postprandial Glucose Profiles in Subjects with Normal Glucose Tolerance

Background: Current mathematical models of postprandial glucose metabolism in people with normal and impaired glucose tolerance rely on insulin measurements and are therefore not applicable in clinical practice. This research aims to develop a model that only requires glucose data for parameter estimation while also providing useful information on insulin sensitivity, insulin dynamics and the meal-related glucose appearance (GA). Methods: The proposed glucose-only model (GOM) is based on the oral minimal model (OMM) of glucose dynamics and substitutes the insulin dynamics with a novel function dependant on glucose levels and GA. A Bayesian method and glucose data from 22 subjects with normal glucose tolerance are utilised for parameter estimation. To validate the results of the GOM, a comparison to the results of the OMM, obtained by using glucose and insulin data from the same subjects is carried out. Results: The proposed GOM describes the glucose dynamics with comparable precision to the OMM with an RMSE of 5.1 ± 2.3 mg/dL and 5.3 ± 2.4 mg/dL, respectively and contains a parameter that is significantly correlated to the insulin sensitivity estimated by the OMM ( r = 0.7) Furthermore, the dynamic properties of the time profiles of GA and insulin dynamics inferred by the GOM show high similarity to the corresponding results of the OMM. Conclusions: The proposed GOM can be used to extract useful physiological information on glucose metabolism in subjects with normal glucose tolerance. The model can be further developed for clinical applications to patients with impaired glucose tolerance under the use of continuous glucose monitoring data.

A Comprehensive Model of Glucose-Insulin Regulation Including Acute and Prolonged Effects of Physical Activity in Type 1 Diabetes

Objective: For type 1 diabetic patients, accurate adjustment of insulin treatment to physical activity (PA) is a challenging open problem. Glucose uptake by the exercising muscles increases acutely, causing increased hepatic glucose production to maintain glucose homeostasis. Meanwhile, insulin sensitivity is elevated for a prolonged period to drive glycogen repletion during recovery. These processes strongly depend on PA duration and intensity, making their combined effects difficult to predict accurately. In this work, we develop a model of glucose-insulin regulation that captures PA from low to high intensity including acute and prolonged effects on glucose metabolism. Methods: We extended an existing minimal model of glucose-insulin regulation to capture PA-driven changes in glucose metabolism. We incorporated the insulin-independent increase in glucose uptake and production, including the effects of glycogen depletion and of high-intensity PA on production. The model also captures the prolonged increase in insulin sensitivity. Results: The model accurately predicts glucose dynamics of published data during short and prolonged PA of moderate to high intensity and during subsequent recovery. In-silico full-day studies elucidate the effects of timing, duration and intensity of PA and of insulin bolus reduction on glucose levels during and after the activity. Conclusion: The proposed model captures the blood glucose dynamics during all main PA regimes. Significance: Mathematical models of glucose-insulin regulation are critical components of closed-loop insulin delivery and clinical decision support systems for achieving good glycemic control. The presented model shows potential for the development and assessment of algorithms targeting treatment adjustment to PA.