Blood Glucose Regulation In Type Research Articles

Effect of structured individual and combined education on blood glucose regulation in type 2 diabetes mellitus

Abstract Although various approaches have been used in diabetes self-management education (DSME) programs, the effect of DSME programs on glycemic control is controversial. This study aimed to compare the effects of structured individual education and combined education on glycemic regulation in type 2 diabetes mellitus (T2DM). This study included T2DM patients who applied to the Ust Kaynarca Diabetes Center between 1 January 2018 and 11 March 2020. All data were retrospectively evaluated from hospital information systems. Patients who received only individual education were defined as the individual education group (IEG), and patients who received both individual and group education were defined as the combined education group (CEG). A total of 496 T2DM patients, with 248 (50.0%) in the IEG and 248 (50.0%) in the CEG, were included in the study. The change in HbA1c (ΔHbA1c) value for the IEG was 1.0% (2.5%), while the ΔHbA1c value for the CEG was 1.9% (2.8%) (P < 0.001). When factors affecting the glycemic control were evaluated, it was determined that the type of education [odds ratio (OR) = 2.295, P < 0.001], gender (OR = 1.799, P = 0.007), presence of hyperlipidemia (OR = 0.559, P = 0.032) and presence of medications added to treatment (OR = 1.558, P = 0.041) were effective on glycemic control. Combined education, in which individual and group education are conducted together, is more effective than individual education in glucose regulation.

The spleen assumes a major role in blood glucose regulation in type 1 diabetes patients treated with BCG

The Bacillus Calmette-Guérin (BCG) vaccine, which has been used for > 100 years to prevent tuberculosis, is well-established for bladder cancer treatment, and under study for neurological and autoimmune diseases. In patients with type 1 diabetes (T1D), BCG vaccinations have been shown in randomized clinical trials to gradually lower blood sugar to near normal levels. This effect appears to be driven by a BCG-induced shift in lymphoid cells’ glucose metabolism from oxidative phosphorylation to aerobic glycolysis. The latter is a state of high glucose utilization that draws more glucose from the blood. Apart from blood, it is unknown whether BCG establishes residence in any organs and alters their glucose metabolism. In this two-year-long clinical trial in type 1 diabetics, we use positron emission tomography (PET) and x-ray computed tomography (CT) to map organs that increase their uptake of the glucose analogue 18F-fluorodeoxyglucose (18F-FDG) before versus after BCG vaccinations. We also injected BALB/c mice with BCG to test for the presence of BCG in various organs. Results from both studies point to the spleen as the dominant site for glucose uptake and BCG residence. The human spleen is significant because its 47% increase in 18F-FDG uptake by a large population of lymphocytes and monocytes might help to explain BCG’s systemic lowering of blood glucose to near normal levels. Findings suggest that the spleen, triggered by BCG, assumes a critical role in systemic glucose regulation in the absence of a functional pancreas.

Optimizing Blood Glucose Regulation in Type 1 Diabetes Patients via Genetic Algorithm-Based Fuzzy Logic Controller Considering Substantial Meal Protocol

Effective management of blood glucose levels in individuals with type 1 diabetes, especially after meals, is crucial for diabetes care. Artificial pancreas systems (APS) perform automated insulin delivery in subjects with type 1 diabetes mellitus (T1DM). In this study, an optimized fuzzy logic controller was designed to achieve a euglycemic range after a substantial meal intake. All in silico simulations were performed using the MATLAB/Simulink environment, leveraging control variability grid analysis (CVGA), and the performance of the controller was evaluated. The proposed controller is based on a fuzzy-logic control law designed in three stages. First, a nonlinear framework of the glucose-insulin regulatory system was identified based on the heavy meal protocol of three patients given as follows: for subject ID 117-1, a total of 295 gCHO; for subject ID 126-1, 236 gCHO; and subject ID 128-1, 394 gCHO over a day. Then, an iterative tree structure was employed to establish a stabilizing control rule for insulin delivery, integrating inputs from two Mamdani Fuzzy Inference System (FIS) objects. Finally, a genetic algorithm refines the control system by fine-tuning the uncertainty of the fuzzy membership functions. Two scenarios were considered for three patients to assess the performance of the proposed controller. The results indicated its effectiveness under various conditions, achieving a time in the range of 61.25%, 71% and 61.10% respectively for the three subjects. The obtained results are analyzed and compared with IMC and multi-objective output feedback controllers. The findings of the study reveal that the proposed controller shows promising advancements in tailored strategies for type 1 diabetes patients, outperforming the other controllers in terms of blood glucose regulation.

Optimizing blood glucose regulation in type 1 diabetes: A fractional order controller approach

This study presents the design and implementation of a Fractional Order Proportional, Integral, and Derivative (FOPID) controller intended for the regulation of blood glucose levels in individuals with type 1 diabetes mellitus (T1DM). The efficacy of this controller is evaluated through its application to a nonlinear Stolwijk–Hardy model simulating T1DM patients, accounting for a range of physiological conditions. Utilizing a genetic algorithm, the parameters of the FOPID controller are fine-tuned. By conducting a comparative analysis with previously established control algorithms, the performance of the proposed controller is validated, demonstrating its superior performance. The results underscore the significant improvements achieved by the proposed controller in maintaining blood glucose concentrations within safe thresholds, particularly in scenarios involving disruptions due to meals.

Internal model control based module for the elimination of meal and exercise announcements in hybrid artificial pancreas systems

Background and ObjectivesHybrid artificial pancreas systems outperform current insulin pump therapies in blood glucose regulation in type 1 diabetes. However, subjects still have to inform the system about meals intake and exercise to achieve reasonable control. These patient announcements may result in overburden and compromise controller performance if not provided timely and accurately. Here, a hybrid artificial pancreas is extended with an add-on module that releases subjects from meals and exercise announcements. MethodsThe add-on module consists of an internal-model controller that generates a “virtual” control action to compensate for disturbances. This “virtual” action is converted into insulin delivery, rescue carbohydrates suggestions, or insulin-on-board limitations, depending on a switching logic based on glucose measurements and predictions. The controller parameters are tuned by optimization and then related to standard parameters from the open-loop therapy. This module is implemented in a hybrid artificial pancreas system proposed by our research group for validation. This hybrid system extended with the add-on module is compared with the hybrid controller with carbohydrate counting errors (hybrid) and the hybrid controller with an alternative unannounced meal compensation module based on a meal detection algorithm (meal detector). The validation used the educational version of the UVa/Padova simulator to simulate the three controllers under two scenarios: one with only meals and another with meals and exercise. The exercise was modeled as a temporal increase of the insulin sensitivity resulting in the glucose drop usually related to an aerobic exercise. ResultsFor the scenario with only meals, the three controllers achieved similar time in range (proposed: 85.1 [77.9,88.1]%, hybrid: 84.0 [75.9,86.4]%, meal detector: 81.9 [79.3,83.8]%, median [interquartile range]) with low time in moderate hypoglycemia. Under the scenario with meals and exercise, the proposed module reduces 4.61% the time in hypoglycemia achieved with the other controllers, suggesting an acceptable amount of rescues (27.2 [23.7, 31.0] g). ConclusionsThe proposed add-on module achieved promising results: it outperformed the meal-detector-based controller, even achieving a postprandial performance as good as the hybrid controller (with carbohydrate counting errors). Also, the rescue suggestion feature of the module mitigated exercise-induced hypoglycemia with admissible rescue amounts.

Association of Neutrophil to Lymphocyte and Platelet To Lymphocyte ratio with Blood Glucose Regulation in Type 2 Diabetes Patients

INTRODUCTION: 
 Diabetes is characterized by chronic hyperglycemia with disturbances of carbohydrate, protein and lipid metabolism. Disorders of lipid metabolism are common in diabetes causing greater cardiovascular risks. Leukocytosis is a major marker of metabolic syndrome. Both neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) are related to subclinical inflammation worsening the glycemic control. HbA1c is used as a marker of blood glucose regulation.
 OBJECTIVE:
 To investigate the association of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio with blood glucose regulation in patients with type 2 diabetes mellitus.
 
 METHODS:
 This comparative analytical study was conducted in Shifa International Hospital on diabetic patients. Sample size was calculated as 62 by WHO sample size calculator . Non randomized convenient sampling was used. Patients were divided into two groups according to HbA1c level taking 7% as cut off point. Full blood count, lipid profile and liver profile were carried out. Data was analyzed by SPSS version 21. Descriptive statistics were calculated for categorical variables. For quantitative normal and dispersed variables, independent student t and Mann Whitney U test were applied respectively. P Value less than 0.05 was considered significant.
 
 RESULTS:
 Out of total 93 patients,33 (35.4 %) were males and 60(64.5%) were females. The mean duration of disease was 8.26 ± 5.8 years. NLR and PLR were elevated in patients having poor glucose control but that difference was not significant. Significant difference between the groups was found with random blood glucose. LDL, triglycerides , cholesterol ratio, ALT and AST were raised in patients having poor glycemic control.
 
 CONCLUSION:
 Patients having poor blood glucose regulation have increased levels of haematological and serological parameters posing greater cardiovascular health risks to patients with type 2 diabetes

An adaptive back-stepping control for blood glucose regulation in type 1 diabetes

In this paper, an adaptive back-stepping controller is designed to regulate the blood glucose in type 1 diabetics. Bergman’s minimal model (BMM) is employed to mathematically model Type 1 diabetes mellitus (T1DM). Firstly, an adaptive virtual controller is designed to bring back the blood glucose level to its safe range. Then, a second adaptive controller is designed to determine the insulin intake. Controller performance and asymptotic stability of the adaptive back-stepping method is proved using Lyapunov stability theory. To verify the effectiveness of the proposed approach in tracking the desired blood glucose, simulation results have been performed. Meal disturbance to diabetes patient is also definitely described and is presented in simulation results. The results show the advantages of the proposed controller such as proper convergence time, robustness in the presence of external disturbances and uncertainties in human body parameters.

Novel algebraic meal disturbance estimation based adaptive robust control design for blood glucose regulation in type 1 diabetes patients.

This study designs a robust closed-loop control algorithm for elevated blood glucose level stabilisation in type 1 diabetic patients. The control algorithm is based on a novel control action resulting from integrating algebraic meal disturbance estimator with back-stepping integral sliding mode control (BISMC) technique. The estimator shows finite time convergence leading to accurate and fast estimation of meal disturbance. Moreover, compensation of the estimated disturbance in controller provides significant reduction in chattering phenomenon, which is inherent drawback of sliding mode control (SMC). The controller is applied to one of the most reliable models of type 1 diabetic patients, named Bergman's minimal model. The effectiveness and superiority of the designed controller is shown by comparing it to classical SMC and super-twisting sliding mode control. The designed controller is subject to three different cases for detailed analysis of the controller's robustness against meal disturbance. The three cases considered are hyperglycaemia, hyperglycaemia combined with meal disturbance and three meal disturbance. The simulation results confirm superior performance of algebraic disturbance estimator based BISMC controller for all the cases mentioned above.

Association of Retinol Binding Protein-4 and Microalbuminuria and Blood Glucose Regulation in Type 2 Diabetic Iraqi Patients

Retinol binding protein 4 (RBP-4) has long been known as the carriers for vitamin A, in the plasma it is banded to transthyretin to form too large complex for glomerulus filtration. Discovered as adipokine involved in the pathogenesis of type 2 diabetes induced insulin resistant and linked to obesity. Diabetic nephropathy one of serious microvascular complication that impact large numbers of the patient however, association with RBP-4 is not fully known. The present study tested this hypothesis by measuring serum RBP4 in samples of Iraqi type 2 diabetic (n=120) with normal albumin excretion (n=57) and microalbuminuria (n=63) of either sex. and Also apparently health subjects (n=30) were involved to serve as control. Concentrations of the RBP4 were significantly elevated in serum of microalbuminuric diabetic patients as compare with normoalbuminuric patients, (p=0.000<0.05). also glycemic index parameters significantly higher (for all p<0.05). In conclusion, the study suggested that serum level of RBP4 are affected by microalbuminuria and the assessment of RBP-4 as controller for insulin resistant in type 2 diabetic in further studies must take into consideration other renal problems.

Design of backstepping LQG controller for blood glucose regulation in type I diabetes patient

Design of backstepping LQG controller for blood glucose regulation in type I diabetes patient

Design of backstepping LQG controller for blood glucose regulation in type I diabetes patient

The mechanisation of the insulin infusion regulation through the artificial pancreas (AP) is needed to design with an objective to control the blood glucose (BG) level in type 1 diabetes mellitus (T1DM) patients. However, to make it applicable in real time, major components needed are availability of proper sensor augmented pumps, glucose monitoring systems, and control techniques. Recent times many researchers suggest robust control techniques for designing a robust controller for computing the required insulin dose for a highly nonlinear human metabolism system. This paper proposes a simulation model of glucose metabolism process and design of a backstepping linear quadratic Gaussian controller (BLQGC) to control the BG level in TIDM patients. The simulations are carried out through MATLAB/SIMULINK environment and the results indicate comparatively better control ability of the proposed algorithm to control the BG concentration within the range of normoglycaemia in terms of accuracy, stability, quick damping and robustness.

Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control-based approach.

Here, a direct adaptive control strategy with parametric compensation is adopted for an uncertain non‐linear model representing blood glucose regulation in type 1 diabetes mellitus patients. The uncertain parameters of the model are updated by appropriate design of adaptation laws using the Lyapunov method. The closed‐loop response of the plasma glucose concentration as well as external insulin infusion rate is analysed for a wide range of variation of the model parameters through extensive simulation studies. The result indicates that the proposed adaptive control scheme avoids severe hypoglycaemia and gives satisfactory performance under parametric uncertainty highlighting its ability to address the issue of inter‐patient variability.

An adaptive backstepping based non-linear controller for artificial pancreas in type 1 diabetes patients

Abstract Artificial pancreas enables closed loop automated control for blood glucose regulation in type 1 diabetic patients. Simple backstepping controller for regulation of blood glucose level has recently been proposed in the literature. In this research work, we have proposed backstepping based adaptive controller for integration in artificial pancreas. Controller design has been based on Bergman's minimal model which represents the dynamics of blood glucose-insulin system of human body. Glucose effectiveness factor has been treated as an unknown parameter and its value has been adapted using Lyapunov based adaptive backstepping control approach. Effects of meal disturbance, physical non-linearities and sensor noise have also been considered in the controller design. A complete mathematical derivation of the proposed nonlinear controller has been described and simulation results have been presented using Matlab/Simulink environment. Results indicate improvement in tracking response and overshoot/undershoot characteristics as compared to some recently developed techniques in literature. Proposed controller assures dynamic stability against disturbances and deviations in human body parameters. Practical implementation of the proposed controller can result in better artificial pancreas.

Fuzzy type-2 fractional Backstepping blood glucose control based on sliding mode observer

A new combination of fractional order (FO) nonlinear control and sliding mode observer (SMO) for blood glucose regulation in type 1 diabetes mellitus is proposed in this paper. An observer estimates the difficult-to-measure process variables that are significant to control law design and to prevent failures. A SMO is proposed to estimate non-measurable states variables of Bergman minimal model by data acquired from a continuous glucose monitoring sensor. At first based on Backstepping method with FO sliding surface a control signal is proposed, and then interval type 2 fuzzy logic is utilized to reduce the chattering phenomenon in control signal. The FO sliding mode control provides robust performance and the Backstepping algorithm protects the controller in front of mismatched and matched uncertainties. Simulation results of the proposed controller are compared with its integer counterpart.

Simultaneous model predictive control and moving horizon estimation for blood glucose regulation in Type 1 diabetes

SummaryA new estimation and control approach for the feedback control of an artificial pancreas to treat Type 1 diabetes mellitus is proposed. In particular, we present a new output‐feedback predictive control approach that simultaneously solves the state estimation and control objectives by means of a single min‐max optimization problem. This involves optimizing a cost function with both finite forward and backward horizons with respect to the unknown initial state, unmeasured disturbances and noise, and future control inputs and is similar to simultaneously solving a model predictive control (MPC) problem and a moving horizon estimation (MHE) problem. We incorporate a novel asymmetric output cost to penalize dangerous low blood glucose values more severely than less harmful high blood glucose values. We compare this combined MPC/MHE approach to a control strategy that uses state‐feedback MPC preceded by a Luenberger observer for state estimation. In‐silico results showcase several advantages of this new simultaneous MPC/MHE approach, including fewer hypoglycemic events without increasing the number of hyperglycemic events, faster insulin delivery in response to a meal consumption, and shorter insulin pump suspensions, resulting in smoother blood glucose trajectories.

A learning automata-based blood glucose regulation mechanism in type 2 diabetes

This paper proposes a learning automata-based mechanism for blood glucose regulation in type 2 diabetics. The proposed mechanism takes into account the past history of the blood glucose level to determine the correct dosage of the insulin. This method uses the learning automata theory to predict the required dosage of insulin and records the patient history in parameters of a Gaussian probability distribution function. The parameters of the distribution function are updated based on the difference between the actual glucose level regulated by the learning automata and the normal range in such a way that the gap between the actual glucose level and the normal one is minimized. As the proposed algorithm proceeds, it can be seen that it converges to the optimal insulin dosage that keeps the glucose level in normal range for a long time. Convergence of the proposed algorithm to the optimal insulin dosage is theoretically proven. A clinical study is conducted to show the performance of the proposed insulin therapy system for regulation of the blood glucose level of type 2 diabetics.

Developments of Glucagon Like Peptide-1 (GLP-1) and Long-acting Analogs in Clinical and Preclinical Studies for Treatment of Type 2 Diabetes

The outstanding physiological functions of glucagon-like peptide-1 make it a promising drug candidate for blood glucose regulation in type 2 diabetes. However, the short half-life of GLP-1 limited its widely clinical utility due to the rapid degradation by dipeptidyl peptidase IV (DPP-IV) and renal clearance. Therefore, stabilisation of glucagon-like peptide-1 is critical for the use of this peptide in drug development. Scientists in pharmaceutical companies have contributed in years to obtain long-acting or sustained GLP-1 derivatives which are reviewed in this report.

Hypoglycemic and antioxidant effects of jaceosidin in streptozotocin-induced diabetic mice

Purpose: In this study, we investigated the effects of jaceosidin on blood glucose regulation in type 1 diabetic mice. Methods: C57BL/6 mice were divided into four groups; normal control (Normal), diabetes control (D-Control), diabetes lowjaceosidin (D-0.005%), and diabetes high-jaceosidin (D-0.02%). Type 1 diabetes was induced by streptozotocin and mice were then fed a diet containing jaceosidin for eight weeks. Fasting blood glucose, oral glucose tolerance test, insulin tolerance test, lipid peroxidation, and antioxidant enzyme activities were assessed. Results: Jaceosidin supplementation for eight weeks had no effect on body weight, organ weight, and blood lipid profiles. However, jaceosidin supplementation significantly lowered fasting blood glucose level and reduced insulin resistance. We also found that jaceosidin supplementation increased antioxidant capacity by enhancement of catalase and GSH-px activities. Conclusion: These results suggest that jaceosidin could be a therapeutic candidate to ameliorate hyperglycemia through increase of antioxidant enzyme activity.

Extended adaptive predictive controller with robust filter to enhance blood glucose regulation in type I diabetic subjects

In this paper, an improved adaptive predictive control with robust filter is developed to be applied in an artificial pancreas. Several problems inherent to endocrine systems for diabetic persons have to be tackled such as nonlinearities, long time delays or daily variations of parameters. Three Finite Impulse Response models for insulin input and the same for meal intake (perturbations) corresponding to normal, hyper-hypoglycaemia levels to implement three zones control are taken into account. The glycaemia reference trajectory is shaped from a healthy person response. A variable weighting factor in the cost function is included to prevent dangerous glycaemia excursions out of the allowed limits. Additionally, a noisy blood glucose subcutaneous sensor model is used. This control strategy is tested on 30 virtual subjects from the UVa – Padova Simulator. Simultaneous meals and physiological disturbances are taken into account and the main conclusions are drawn from Control Variability Grid Analysis.

Knowledge-based Closed-loop Control of Blood Glucose Concentration in Diabetic Patients and Comparison with H∞ Control Technique

In this paper, fuzzy-based closed-loop controller is applied to obtain a robust controller for blood glucose regulation in type I diabetes mellitus patients. The control technique incorporates expert knowledge about treatment of disease by using Mamdani-type fuzzy logic controller to robustly stabilize the blood glucose concentration in normoglycemic level. Controller performance is considered in terms of its ability to reject the multiple meals, on an averaged nonlinear patient model. Robustness of the controller is tested over a group of patients with model parameter varying considerably from the average model. The controller provides the possibility of more accurate control of blood glucose level in the patient in spite of uncertainty in model parameters and measurement noise. The proposed controller has showed superiority over other classical control techniques. A comparative study is presented with well-known conventional H∞ control technique. Simulation results show the superiority of the proposed scheme in terms of reference tracking, disturbance rejection, and measurement noise in comparison with other approaches.