Current Diabetes Reviews - Volume 11, Issue 3, 2015

Type 1 diabetes (T1D) is caused by the chronic autoimmune destruction of insulin producing beta cells. Beta cell replacement therapy through whole pancreas or islet transplantation is a therapeutic option for patients in which a stable glucose control is not achievable with exogenous insulin therapy. Long-term insulin independence is, however, hampered by the recipient immune response that includes activation of inflammatory pathways and specific allo- and autoimmunity. The identification and monitoring of soluble and cellular biomarkers are of critical relevance for the prediction of graft damage, for the evaluation of responses to immune-modulating therapy, and for target pathways identification to generate novel drugs or therapeutic approaches. The final objective of immune monitoring is to find ways to improve the outcome of pancreas and islet transplantation. In this review, we discuss the available tools to monitor the innate, humoral and cellular responses after islet and pancreas transplantation, and the most relevant findings generated by these measurements.

Background: Post-transplant diabetes mellitus is a significant risk factor for cardiovascular disease in solid organ transplantation. The main underlying pathophysiological mechanism of PTDM is pancreatic beta cell dysfunction in the context of insulin resistance, but the relative importance of each of these important components of glycemic metabolism is under intense debate. Methods: We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials to January 15, 2015. We selected systematic reviews and meta-analyses and randomized clinical trials. When no such reports were found for a given topic or drug, observational studies were included in the assessment. Results: There are agents with known diabetogenic effects: corticosteroids, calcineurin inhibitors including tacrolimus and cyclosporine, as well as the mammalian target of rapamycin inhibitors (sirolimus and everolimus). The association between the use of induction agents and PTDM is very scarce. No diabetogenic effects have been found with the use of azathioprine, mycophenolate mofetil and its derivatives. Conclusion: Immunosuppression is the major modifiable risk factor for development of PTDM but risk versus benefit analysis is required to balance risk of developing PTDM versus rejection. Caution is advisable in immunosuppressant adjustments in the event that PTDM develops based on current evidence. Physicians should choose and use immunosuppression regimens shown to have the best outcome for patient and graft survival, irrespective of PTDM risk.

Treatment options for management of post-transplantation diabetes mellitus (PTDM) are limited with regards to the availability of strong clinical evidence base. This is a concern as PTDM is common after solid organ transplantation and associated with poor clinical outcomes. PTDM and type 2 diabetes mellitus are distinct pathophysiological entities that have important differences with regards to aetiology, clinical course and management. Therefore, any clinical evidence of treatment benefit from the general population with type 2 diabetes mellitus may not be directly translated to the solid organ transplant recipient. In addition, the potential risk and benefit of using many of these therapeutic agents must take account of the complicated post-transplantation milieu of immunosuppression. While there is reasonable evidence base for treatment of diabetes mellitus in the general population, the same is not true in a post-transplantation setting. In this article the treatment options available for PTDM will be discussed, with a transplant-specific focus on the pros and cons of each particular component of the glucose lowering therapy armoury.

A closed-loop system that provides both the sensing of glucose and the appropriate dosage of insulin could dramatically improve treatment options for insulin-dependent diabetics. The intrahepatic implantation of allogeneic islets has the potential to provide this intimate control, by transplanting the very cells that have this inherent sensing and secretion capacity. Limiting islet transplantation, however, is the significant loss and dysfunction of islets following implantation, due to the poor engraftment environment and significant immunological attack. In this review, we outline approaches that seek to address these challenges via engineering biomimetic materials. These materials can serve to mimic natural processes that work toward improving engraftment, minimizing inflammation, and directing immunological responses. Biomimetic materials can serve to house cells, recapitulate native microenvironments, release therapeutic agents in a physiological manner, and/or present agents to direct cells towards desired responses. By integrating these approaches, superior platforms capable of improving long-term engraftment and acceptance of transplanted islets are on the horizon.

The identification of at-risk individuals prior to transplantation may enable implementation of measures to prevent or delay PTDM development, while early detection facilitates prompt management and may prevent acute and chronic complications. Thus, in this review, we examine proposed tools for the prediction of PTDM for use prior to and following solid organ transplantation. This includes PTDM prediction models based on biochemical assessments of glycaemia and other indices, in addition to those solely based on clinical parameters. We also examine the available methods for diagnosis of PTDM early and late post-transplant, including the advantages and limitations of fasting plasma glucose (FPG), OGTT, random plasma glucose and HbA1c assessment. Key findings are that OGTT should remain the gold standard diagnostic method for PTDM, however, there is emerging data to support a role for HbA1c beyond 3 months posttransplant. FPG has low sensitivity during the first year post-transplant. Improved prediction and diagnosis of PTDM may lead to improvements in patient survival, quality of life and health care costs in future.

Although, metformin is a drug of the first choice in the treatment of type 2 diabetes mellitus, its molecular action is not fully determined. It is widely accepted that the antihyperglycemic effect of metformin is a result of a decrease in hepatic glucose production, and several cellular targets of the drug have been proposed. The reduction of gluconeogenesis evoked by metformin may be a result of an energy deficit evoked through the inhibition of mitochondrial respiratory chain complex I and/or increased cytosolic redox state and decreased mitochondrial redox state elicited by the inhibition of mitochondrial glycerophosphate dehydrogenase (mGPD). Metformin mediated reduction of hepatic gluconeogenesis was found to be AMP-activated protein kinase (AMPK) dependent and independent, including the inhibition of gluconeogenesis gene expression and allosteric regulation of key gluconeogenesis enzymes. Recently, it was reported that inhibition of mGPD by metformin decreases the level of dihydroxyacetone phosphate and reduces the conversion of lactate to pyruvate, that in consequence diminishes the utilization of glycerol and lactate for gluconeogenesis. The purpose of this paper is to discus molecular mechanisms responsible for the metabolic action of metformin.

Diabetic Retinopathy (DR) is an eye disease, which may cause blindness by the upsurge of insulin in blood. The major cause of visual loss in diabetic patient is macular edema. To diagnose and follow up Diabetic Macular Edema (DME), a powerful Optical Coherence Tomography (OCT) technique is used for the clinical assessment. Many existing methods found out the DME affected patients by estimating the fovea thickness. These methods have the issues of lower accuracy and higher time complexity. In order to overwhelm the above limitations, a hybrid approaches based DR detection is introduced in the proposed work. At first, the input image is preprocessed using green channel extraction and median filter. Subsequently, the features are extracted by gradient-based features like Histogram of Oriented Gradient (HOG) with Complete Local Binary Pattern (CLBP). The texture features are concentrated with various rotations to calculate the edges. We present a hybrid feature selection that combines the Particle Swarm Optimization (PSO) and Differential Evolution Feature Selection (DEFS) for minimizing the time complexity. A binary Support Vector Machine (SVM) classifier categorizes the 13 normal and 75 abnormal images from 60 patients. Finally, the patients affected by DR are further classified by Multi-Layer Perceptron (MLP). The experimental results exhibit better performance of accuracy, sensitivity, and specificity than the existing methods.

Chronic hyperglycemia and its associated metabolic products are key factors responsible for the development and progression of diabetic chronic kidney disease (CKD). Endocrinologists are tasked with detection and management of early CKD before patients need referral to a nephrologist for advanced CKD or dialysis evaluation. Primary care physicians are increasingly becoming aware of the importance of managing hyperglycemia to prevent or delay progression of CKD. Glycemic control is an integral part of preventing or slowing the advancement of CKD in patients with diabetes; however, not all glucose-lowering agents are suitable for this patient population. The availability of the latest information on treatment options may enable physicians to thwart advancement of serious renal complication in patients suffering from diabetes. This review presents clinical data that shed light on the risk/benefit profiles of three relatively new antidiabetes drug classes, the dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 analogs, and sodium glucose co-transporter 2 inhibitors, particularly for patients with diabetic CKD, and summarizes the effects of these therapies on renal outcomes and glycemic control for endocrinologists and primary care physicians. Current recommendations for screening and diagnosis of CKD in patients with diabetes are also discussed.

In modern society, combatting cardiovascular and metabolic diseases has been highlighted as an urgent global challenge. In recent decades, the scientific literature has identified that behavioral variables (e.g. smoking, unhealthy diet and physical inactivity) are related to the development of these outcomes and, therefore, preventive actions should focus on the promotion of physical exercise practice and a healthy diet, as well as combatting the smoking habit from an early age. The promotion of physical exercise in the general population has been suggested as a relevant goal by significant health organizations around the world. On the other hand, recent literature has indicated that physical exercise performed in early life prevents the development of diabetes mellitus, dyslipidemia and arterial hypertension during adulthood, although this protective effect seems to be independent of the physical activity performed during adulthood. Apparently, the interaction between physical exercise and human growth in early life constitutes an issue which is not completely understood by sports medicine. The aim of the present review was therefore to discuss recent evidence on the effects of physical exercise performed during childhood and adolescence on cardiovascular and metabolic outcomes in adulthood.