Associations of Diabetic Retinopathy with Retinal Neurodegeneration on the Background of Diabetes Mellitus. Overview of Recent Medical Studies with an Assessment of the Impact on Healthcare systems

Nanoformulations of flavonoids for diabetes and microvascular diabetic complications

Diabetes is a chronic metabolic disease characterized by an excess of glucose in the blood. If the constant sugar level is not managed correctly in diabetic patients, it may lead to microvascular complications such as diabetic retinopathy, neuropathy, and nephropathy. There are several synthetic drugs for the management of diabetes; however, these drugs produce immense adverse effects in long-term use. Flavonoids are naturally occurring substances categorized in various classes. They are known for their diverse pharmacological actions, and one of them is prominent antihyperglycemic action and their activities in diabetic complications. In the last few decades, many research studies emphasized the potential of flavonoids in diabetes management. Nevertheless, most flavonoids are insoluble in water and cannot produce desired therapeutic action when administered in conventional dosage forms. To overcome this issue, flavonoids were formulated into different nanoformulations to enhance solubility, absorption, and therapeutic efficacy. This review article focuses on flavonoid nanoformulations and in vitro and in vivo studies reported to overcome diabetes mellitus and its complications.

Relationship Between Glycosylated Hemoglobin Levels and Contrast Sensitivity in People with Type 2 Diabetes Mellitus Without Diabetic Retinopathy

Objectives

This study aimed to investigate the relationship between glycosylated hemoglobin (HbA1c) value and contrast sensitivity (CS) in people with Type 2 diabetes mellitus (T2DM) and no diabetic retinopathy (DR) changes.

Materials and Methods

This cross-sectional study was conducted in the endocrinology department of a tertiary hospital and included 120 participants aged 30-40 years with T2DM without DR and with visual acuity of 6/6 in both eyes. Lea CS charts with one symbol size (10M) were used to measure CS. The relationship between HbA1c value and CS was calculated using linear regression analysis.

Results

Of 120 participants with T2DM without DR, 83 (69.2%) were female. Sixty-four participants (53.3%) were in the 36-40 years age group. Mean known duration of diabetes was 3.3±1.65 years. Mean HbA1c value was 10.46±1.48%, with three-fourths of participants having an HbA1c value greater than 8%. Mean CS measured at distances of 1 meter, 2 meters, 3 meters and 4 meters were 164.75±21.12, 122.0±45.08, 93.0±45.37, and 58.67±20.04, respectively. Most participants (n=113, 94.2%) had normal CS (170 at 0.6% contrast) tested at 1 meter. More than half (53.3%) of the participants had reduced CS (40 at 2.5% contrast) at 4 meters. CS measured at 3 meters showed a strong negative correlation with duration of diabetes (r=-0.855, p<0.001; R²=0.731) and HbA1c values (r=-0.865; p<0.001; R²=0.747).

Conclusion

CS was inversely associated with diabetes duration and HbA1c values in people with T2DM before any defect in visual acuity or clinical evidence of DR.

An active learning method for diabetic retinopathy classification with uncertainty quantification

In recent years, deep learning (DL) techniques have provided state-of-the-art performance in medical imaging. However, good quality (annotated) medical data is in general hard to find due to the usually high cost of medical images, limited availability of expert annotators (e.g., radiologists), and the amount of time required for annotation. In addition, DL is data-hungry and its training requires extensive computational resources. Furthermore, DL being a black-box method lacks transparency on its inner working and lacks fundamental understanding behind decisions made by the model and consequently, this notion enhances the uncertainty on its predictions. To this end, we address these challenges by proposing a hybrid model, which uses a Bayesian convolutional neural network (BCNN) for uncertainty quantification, and an active learning approach for annotating the unlabeled data. The BCNN is used as a feature descriptor and these features are then used for training a model, in an active learning setting. We evaluate the proposed framework for diabetic retinopathy classification problem and demonstrate state-of-the-art performance in terms of different metrics.

[Modern concepts of pathogenesis of diabetic retinopathy]

This literature review presents modern view on the pathogenesis of diabetic retinopathy (DR) paying particular attention to the molecular mechanisms leading to its development, as well as the manifestations of retinal neurodegeneration in such patients. Assessment of this condition and its clinical manifestations makes it possible to diagnose DR at the stage of absent initial vascular changes. Investigating the neurodegeneration mechanisms could supplement the existing understanding of the disease pathogenesis and could possibly help find new ways of treatment and prevention of DR.

Antidiabetic Effects and Mechanisms of Rosemary (Rosmarinus officinalis L.) and its Phenolic Components

Diabetes mellitus is a chronic endocrine disease result from absolute or relative insulin secretion deficiency, insulin resistance, or both, and has become a major and growing public healthy menace worldwide. Currently, clinical antidiabetic drugs still have some limitations in efficacy and safety such as gastrointestinal side effects, hypoglycemia, or weight gain. Rosmarinus officinalis is an aromatic evergreen shrub used as a food additive and medicine, which has been extensively used to treat hyperglycemia, atherosclerosis, hypertension, and diabetic wounds. A great deal of pharmacological research showed that rosemary extract and its phenolic constituents, especially carnosic acid, rosmarinic acid, and carnosol, could significantly improve diabetes mellitus by regulating glucose metabolism, lipid metabolism, anti-inflammation, and anti-oxidation, exhibiting extremely high research value. Therefore, this review summarizes the pharmacological effects and underlying mechanisms of rosemary extract and its primary phenolic constituents on diabetes and relative complications both in vitro and in vivo studies from 2000 to 2020, to provide some scientific evidence and research ideas for its clinical application.

Fushiming Capsule Attenuates Diabetic Rat Retina Damage via Antioxidation and Anti-Inflammation

Aims

Diabetic retinopathy (DR) remains one of the leading causes of acquired blindness. Fushiming capsule (FSM), a compound traditional Chinese medicine, is clinically used for DR treatment in China. The present study was to investigate the effect of FSM on retinal alterations, inflammatory response, and oxidative stress triggered by diabetes.

Main Methods

Diabetic rat model was induced by 6-week high-fat and high-sugar diet combined with 35 mg/kg streptozotocin (STZ). 30 days after successful establishment of diabetic rat model, full field electroretinography (ffERG) and optical coherence tomography (OCT) were performed to detect retinal pathological alterations. Then, FSM was administered to diabetic rats at different dosages for 42-day treatment and diabetic rats treated with Calcium dobesilate (CaD) capsule served as the positive group. Retinal function and structure were observed, and retinal vascular endothelial growth factor-α (VEGF-α), glial fibrillary acidic (GFAP), and vascular cell adhesion protein-1 (VCAM-1) expressions were measured both on mRNA and protein levels, and a series of blood metabolic indicators were also assessed.

Key Findings

In DR rats, FSM (1.0 g/kg and 0.5 g/kg) treatment significantly restored retinal function (a higher amplitude of b-wave in dark-adaptation 3.0 and OPs2 wave) and prevented the decrease of retinal thickness including inner nuclear layer (INL), outer nuclear layer (ONL), and entire retina. Additionally, FSM dramatically decreased VEGF-α, GFAP, and VCAM-1 expressions in retinal tissues. Moreover, FSM notably improved serum antioxidative enzymes glutathione peroxidase, superoxide dismutase, and catalase activities, whereas it reduced serum advanced glycation end products, methane dicarboxylic aldehyde, nitric oxide, and total cholesterol and triglycerides levels.

Significance

FSM could ameliorate diabetic rat retina damage possibly via inhibiting inflammation and improving antioxidation.