Predictive Glucose Monitoring for People with Diabetes Using Wearable Sensors

Diabetes is a chronic non-communicable disease resulting from pancreatic inability to produce the hormone insulin, or a physiological cellular inability to use this hormone effectively. This leads to unregulated blood glucose levels, which can cause significant and often irreversible physiological damage. Current means of glucose level monitoring range from infrequent capillary blood glucose sampling to continuous interstitial fluid glucose monitoring. However, the accuracy of these methods is limited by numerous factors. A potential solution to this shortcoming involves the use of wearable sensors that record an individual’s physiological responses to a range of daily activities, which are subsequently fused and processed with machine learning (ML) algorithms to provide a prediction of an individual’s glucose level and can provide an artificial intelligence-driven glucose monitoring platform. In this paper, we conduct a comparison case study using quadratic discriminant analysis (QDA) and support vector machine (SVM) algorithms for the classification of glucose levels with data acquired from the wearable sensors of a type 1 diabetic individual. Preliminary results demonstrate predicted glucose levels with >70% accuracy, indicating potential for this approach to be used in the design of an ergonomic glucose prediction platform utilizing wearable sensors. Further work will involve the exploration of additional datasets from affordable wearables to enhance and improve the prediction power of the ML algorithms.

A Case Report of Dual Infection of Rhino-Orbital Mucormycosis and Scabies in a Diabetic Patient

Diabetes mellitus is an immunosuppressed condition and patients with this condition are more prone to bacterial, viral, fungal, and parasitic infections and infestations. Mucormycosis is one of the acute opportunistic infections seen in diabetic individuals which are the third most common angioinvasive disease. Scabies is an acute form of skin disease seen in immune-compromised patients like diabetic individuals and is caused by Sarcoptes scabiei. Early identification, successful management, and prompt medical/surgical intervention reduce the morbidity and mortality associated with them. ​Hereby we report a case of dual infection of mucormycosis and scabies in a diabetic individual. Key words: Knowledge and practice, child survival strategies, mothers, south Nigeria.

A comparison among three maximal mathematical models of the glucose-insulin system

The most well-known and widely used mathematical representations of the physiology of a diabetic individual are the Sorensen and Hovorka models as well as the UVAPadova Simulator. While the Hovorka model and the UVAPadova Simulator only describe the glucose metabolism of a subject with type 1 diabetes, the Sorensen model was formulated to simulate the behaviour of both normal and diabetic individuals. The UVAPadova model is the most known model, accepted by the FDA, with a high level of complexity. The Hovorka model is the simplest of the three models, well documented and used primarily for the development of control algorithms. The Sorensen model is the most complete, even though some modifications were required both to the model equations (adding useful compartments for modelling subcutaneous insulin delivery) and to the parameter values. In the present work several simulated experiments, such as IVGTTs and OGTTs, were used as tools to compare the three formulations in order to establish to what extent increasing complexity translates into richer and more correct physiological behaviour. All the equations and parameters used for carrying out the simulations are provided.

Cerebrovascular Complications of Diabetes: SGLT-2 Inhibitors as a Promising Future Therapeutics

Sodium-Glucose co-transporter inhibitors are a novel class of drugs that are widely used in the treatment of type 2 diabetes mellitus medical management. This class of drugs has a simple mechanism of action by which they decrease blood glucose levels. They prevent the uptake or re-absorption of glucose in the blood by inhibiting the SGLT2 co-transport channels located in the renal proximal convoluted tubule. Since, SGLT2 is the low affinity, high capacity glucose transporter, it allows the co-transport of sodium and glucose through it. SGLT2s are accountable for around 90% of the renal glucose reuptake. Cerebrovascular complications or accidents (CVAs) are the world's leading cause of mortality, resulting in around 6 million deaths annually. Diabetics are prone to develop mitochondrian dysfunction and neurodegeneration due to hyperglycemia and oxidative stress end products. Due to hyperglycemic condition in diabetes, it’s always an elevated risk of cerebrovascular dysfunction due to hyperglycemia as it includes endothelial dysfunction, atherosclerosis, hypercoagulability, oxidative stress, renal reperfusion injury which may lead to neuronal degeneration and cognitive impairment. A diabetic individual is more prone to develop risk factors for transient ischemic attacks than non-diabetic patient. These inhibitors reduce hyperglycemia by blocking renal glucose reabsorption, therefore promoting an increase in renal glucose excretion. This review discusses the potential role of SGLT2 inhibitors in treating CVAs associated with T2DM.

Control of Hyperglycemia Using Differentiated and Undifferentiated Mesenchymal Stem Cells in Rats with Type 1 Diabetes

Due to their ability in self-renewing and differentiation into a wide variety of tissues, mesenchymal stem cells (MSCs) exhibit outstanding potential for regenerative medicine. This study was aimed at investigating different aspects of MSC therapy in controlling hyperglycemia in streptozotocin-induced diabetes rats. Using an islet cell differentiation protocol, bone marrow (BM) MSCs were differentiated into insulin-producing cells (IPCs). The differentiation process was evaluated by immunocytochemistry, reverse transcriptase PCR, and dithizone staining. Diabetic animals in 4 diabetic individual groups received normal saline, BM-MSCs, coadministration of BM-MSCs with supernatant, and IPCs. Blood glucose and insulin levels were monitored during the experiment. Immunohistochemical analysis of the pancreas was performed at the end of the experiment. Administration of BM-MSCs could not reverse glucose and insulin levels in experimental animals as efficiently as cotransplantation of BM-MSCs with supernatant. The effect of coadministration of BM-MSCs with supernatant and transplantation of IPCs on controlling hyperglycemia is comparable. Immunohistochemical analysis showed that number and size of islets per section were significantly increased in groups receiving IPCs and BM-MSC-supernatant compared to the MSC group of animals. In conclusion, coadministration of BM-MSCs with supernatant could be used as efficiently as IPC transplantation in controlling hyperglycemia in diabetic rats.