Classification of diabetic retinopathy: Past, present and future

Hsa_circ_0004776 regulates the retina neovascularization in progression of diabetic retinopathy via hsa-miR-382-5p/BDNF axis

The aim of this work was to identify the regulatory function of hsa_circ_0004776 in the progression of diabetic retinopathy (DR). The direct interactions between hsa_circ_0004776 and hsa-miR-382-5p and between hsa-miR-382-5p and BDNF, were confirmed via dual-luciferase reporter assays. Quantitative Real-Time PCR analysis indicated that hsa_circ_0004776 was highly expressed in aqueous humour samples of DR patients and human retinal microvascular epithelial cells (hRECs) under a high-glucose environment, whereas hsa-miR-382-5p showed the opposite trend. Overexpressed hsa_circ_0004776 significantly enhanced DNA synthesis, proliferation, migration, and tube formation in hRECs in hyperglycaemia, while hsa-miR-382-5p mimics reversed these changes. Additionally, in a streptozotocin-induced Sprague-Dawley rat model of DR, vitreous microinjection of rno-miR-382-5p agomir reversed the pathologic features in the progression of DR, including retinal vascular leakage, capillary decellularization, loss of pericytes, fibrosis, and gliosis. Our results indicated that under hyperglycaemic conditions, hsa_circ_0004776 influences the progression of DR via hsa-miR-382-5p and thus represents a potential therapeutic target.

Association of blood trihalomethane concentrations with diabetes mellitus in older adults in the US: a cross-sectional study of NHANES 2013-2018

Background

Previous studies have demonstrated that there is a correlation between trihalomethanes and disease progression, such as allergic diseases. As we know, only few studies focused on the relationship between trihalomethanes and metabolic diseases, such as diabetes mellitus.

Objective

The aim of this study was to further explore the associations between blood trihalomethane concentrations and diabetes mellitus in older adults in the US.

Methods

Data were collected from the National Health and Nutrition Examination Study (NHANES) database in the survey cycle during 2013 to 2018, including 2,511 older adults in the US whose blood trihalomethane concentrations were measured, involving chloroform (TCM) and brominated trihalomethanes (Br-THMs). Br-THMs include bromodichloromethane (BDCM), dibromochloromethane (DBCM), and bromoform (TBM). Meanwhile, the concentration of total trihalomethanes (TTHMs) was also measured later. A multivariate logistic regression and restricted cubic spline were used to examine the relationship between blood THMs and diabetes mellitus. Meanwhile, we performed a subgroup analysis, which aims to explore the stability of this relationship in different subgroups. In order to further consider the impact of various disinfection by-products on diabetes, we also used weighted quantile sum (WQS). To explore the correlation in trihalomethanes, we plot a correlation heatmap.

Results

Adjusting for potential confounders, we found that there was a significant negative association between chloroform and diabetes mellitus [Model 1 (adjusted for covariates including age, sex, and race, OR = 0.71; 95% CI: 0.50-1.02; p = 0.068; p for trend = 0.094); Model 2 (adjusted for all covariates, OR = 0.68; 95% CI: 0.48-0.96; p = 0.029; p for trend = 0.061)]. In the bromodichloromethane, we reached a conclusion that is similar to TCM [Model 1 (adjusted for covariates including age, sex, and race, OR = 0.54; 95% CI: 0.35-0.82; p = 0.005; p for trend = 0.002); Model 2 (adjusted for all covariates, OR = 0.54; 95% CI: 0.35-0.82; p = 0.003; p for trend = 0.002)]. Meanwhile, the restricted cubic spline curve also further confirms this result (p overall = 0.0027; p overall< 0.001). Based on the analysis in the subgroups, we found that the value p for interaction in the majority of subgroups is higher than 0.1. Trihalomethanes and diabetes were inversely associated, and in the WQS, chloroform and bromodichloromethane were found to be the major contributors to this relationship. In the correlation analysis, we found that most trihalomethanes have a weak correlation, except for TBM and TCM with a strong correlation.

Conclusion

Our results in this study showed that blood chloroform, bromodichloromethane concentrations, and diabetes mellitus in older adults in the US are negatively correlated, suggesting that chloroform and bromodichloromethane can be protective factors for diabetes.

Optical coherence tomography angiography in diabetic retinopathy: A major review

Diabetic retinopathy (DR) is characterized by retinal vasculopathy and is a leading cause of visual impairment. Optical coherence tomography angiography (OCTA) is an innovative imaging technology that can detect various pathologies and quantifiable changes in retinal microvasculature. We briefly describe its functional principles and advantages over fluorescein angiography and perform a comprehensive review on its clinical applications in the screening or management of people with prediabetes, diabetes without clinical retinopathy (NDR), nonproliferative DR (NPDR), proliferative DR (PDR), and diabetic macular edema (DME). OCTA reveals early microvascular alterations in prediabetic and NDR eyes, which may coexist with sub-clinical neuroretinal dysfunction. Its applications in NPDR include measuring ischemia, detecting retinal neovascularization, and timing of early treatment through predicting the risk of retinopathy worsening or development of DME. In PDR, OCTA helps characterize the flow within neovascular complexes and evaluate their progression or regression in response to treatment. In eyes with DME, OCTA perfusion parameters may be of predictive value regarding the visual and anatomical gains associated with treatment. We further discussed the limitations of OCTA and the benefits of its incorporation into an updated DR severity scale.

Source-free active domain adaptation for diabetic retinopathy grading based on ultra-wide-field fundus images

Domain adaptation (DA) is commonly employed in diabetic retinopathy (DR) grading using unannotated fundus images, allowing knowledge transfer from labeled color fundus images. Existing DAs often struggle with domain disparities, hindering DR grading performance compared to clinical diagnosis. A source-free active domain adaptation method (SFADA), which generates features of color fundus images by noise, selects valuable ultra-wide-field (UWF) fundus images through local representation matching, and adapts models using DR lesion prototypes, is proposed to upgrade DR diagnostic accuracy. Importantly, SFADA enhances data security and patient privacy by excluding source domain data. It reduces image resolution and boosts model training speed by modeling DR grade relationships directly. Experiments show SFADA significantly improves DR grading performance, increasing accuracy by 20.90% and quadratic weighted kappa by 18.63% over baseline, reaching 85.36% and 92.38%, respectively. This suggests SFADA's promise for real clinical applications.

No causal association between serum vitamin D levels and diabetes retinopathy: A Mendelian randomization analysis

BACKGROUND AND AIM

Diabetes retinopathy (DR) is a common microvascular complication of diabetes, and it is the main cause of global vision loss. The current observational research results show that the causal relationship between Vitamin D and DR is still controversial. Therefore, we conducted a Mendelian randomization study to determine the potential causal relationship between serum 25-hydroxyvitamin D 25(OH)D and DR.

METHODS AND RESULTS

In this study, we selected aggregated data on serum 25(OH)D levels (GWAS ID: ebi-a-GCST90000615) and DR (GWAS ID: finn-b-DM_RETINOPATHY) from a large-scale GWAS database. Then use MR analysis to evaluate the possible causal relationship between them. We mainly use inverse variance weighted (IVW), supplemented by MR Egger and weighted median methods. Sensitivity analysis is also used to ensure the stability of the results, such as Cochran's Q-test, MR-PRESSO, MR-Egger interception test, and retention method. The MR analysis results showed that there was no significant causal relationship between 25(OH)D and DR (OR = 1.0128, 95%CI=(0.9593,1.0693), P = 0.6447); Similarly, there was no significant causal relationship between DR and serum 25 (OH) D levels (OR = 0.9900, 95% CI=(0.9758,1.0045), P = 0.1771).

CONCLUSION

Our study found no significant causal relationship between serum 25(OH)D levels and DR, and vice versa. A larger sample size randomized controlled trial is needed to further reveal its potential causal relationship.

Causal relationships between blood metabolites and diabetic retinopathy: a two-sample Mendelian randomization study

Background

Diabetic retinopathy (DR) is a microvascular complication of diabetes, severely affecting patients' vision and even leading to blindness. The development of DR is influenced by metabolic disturbance and genetic factors, including gene polymorphisms. The research aimed to uncover the causal relationships between blood metabolites and DR.

Methods

The two-sample mendelian randomization (MR) analysis was employed to estimate the causality of blood metabolites on DR. The genetic variables for exposure were obtained from the genome-wide association study (GWAS) dataset of 486 blood metabolites, while the genetic predictors for outcomes including all-stage DR (All DR), non-proliferative DR (NPDR) and proliferative DR (PDR) were derived from the FinnGen database. The primary analysis employed inverse variance weighted (IVW) method, and supplementary analyses were performed using MR-Egger, weighted median (WM), simple mode and weighted mode methods. Additionally, MR-Egger intercept test, Cochran's Q test, and leave-one-out analysis were also conducted to guarantee the accuracy and robustness of the results. Subsequently, we replicated the MR analysis using three additional datasets from the FinnGen database and conducted a meta-analysis to determine blood metabolites associated with DR. Finally, reverse MR analysis and metabolic pathway analysis were performed.

Results

The study identified 13 blood metabolites associated with All DR, 9 blood metabolites associated with NPDR and 12 blood metabolites associated with PDR. In summary, a total of 21 blood metabolites were identified as having potential causal relationships with DR. Additionally, we identified 4 metabolic pathways that are related to DR.

Conclusion

The research revealed a number of blood metabolites and metabolic pathways that are causally associated with DR, which holds significant importance for screening and prevention of DR. However, it is noteworthy that these causal relationships should be validated in larger cohorts and experiments.

Recognition of diabetic retinopathy and macular edema using deep learning

Diabetic retinopathy (DR) and diabetic macular edema (DME) are both serious eye conditions associated with diabetes and if left untreated, and they can lead to permanent blindness. Traditional methods for screening these conditions rely on manual image analysis by experts, which can be time-consuming and costly due to the scarcity of such experts. To overcome the aforementioned challenges, we present the Modified CornerNet approach with DenseNet-100. This system aims to localize and classify lesions associated with DR and DME. To train our model, we first generate annotations for input samples. These annotations likely include information about the location and type of lesions within the retinal images. DenseNet-100 is a deep CNN used for feature extraction, and CornerNet is a one-stage object detection model. CornerNet is known for its ability to accurately localize small objects, which makes it suitable for detecting lesions in retinal images. We assessed our technique on two challenging datasets, EyePACS and IDRiD. These datasets contain a diverse range of retinal images, which is important to estimate the performance of our model. Further, the proposed model is also tested in the cross-corpus scenario on two challenging datasets named APTOS-2019 and Diaretdb1 to assess the generalizability of our system. According to the accomplished analysis, our method outperformed the latest approaches in terms of both qualitative and quantitative results. The ability to effectively localize small abnormalities and handle over-fitted challenges is highlighted as a key strength of the suggested framework which can assist the practitioners in the timely recognition of such eye ailments.

Targeting autophagy with natural products as a potential therapeutic approach for diabetic microangiopathy

As the quality of life improves, the incidence of diabetes mellitus and its microvascular complications (DMC) continues to increase, posing a threat to people's health and wellbeing. Given the limitations of existing treatment, there is an urgent need for novel approaches to prevent and treat DMC. Autophagy, a pivotal mechanism governing metabolic regulation in organisms, facilitates the removal of dysfunctional proteins and organelles, thereby sustaining cellular homeostasis and energy generation. Anomalous states in pancreatic β-cells, podocytes, Müller cells, cardiomyocytes, and Schwann cells in DMC are closely linked to autophagic dysregulation. Natural products have the property of being multi-targeted and can affect autophagy and hence DMC progression in terms of nutrient perception, oxidative stress, endoplasmic reticulum stress, inflammation, and apoptosis. This review consolidates recent advancements in understanding DMC pathogenesis via autophagy and proposes novel perspectives on treating DMC by either stimulating or inhibiting autophagy using natural products.

Emerging role of ferroptosis in diabetic retinopathy: a review

BACKGROUND

Diabetic retinopathy (DR) is a significant complication of diabetes and the primary cause of blindness among working age adults globally. The development of DR is accompanied by oxidative stress, characterised by an overproduction of reactive oxygen species (ROS) and a compromised antioxidant system. Clinical interventions aimed at mitigating oxidative stress through ROS scavenging or elimination are currently available. Nevertheless, these treatments merely provide limited management over the advanced stage of the illness. Ferroptosis is a distinctive form of cell death induced by oxidative stress, which is characterised by irondependent phospholipid peroxidation.

PURPOSE

This review aims to synthesise recent experimental evidence to examine the involvement of ferroptosis in the pathological processes of DR, as well as to explicate the regulatory pathways governing oxidative stress and ferroptosis in retina.

METHODS

We systematically reviewed literature available up to 2023.

RESULTS

This review included 12 studies investigating the involvement of ferroptosis in DR.

DISCOVER: 2-D multiview summarization of Optical Coherence Tomography Angiography for automatic diabetic retinopathy diagnosis

Diabetic Retinopathy (DR), an ocular complication of diabetes, is a leading cause of blindness worldwide. Traditionally, DR is monitored using Color Fundus Photography (CFP), a widespread 2-D imaging modality. However, DR classifications based on CFP have poor predictive power, resulting in suboptimal DR management. Optical Coherence Tomography Angiography (OCTA) is a recent 3-D imaging modality offering enhanced structural and functional information (blood flow) with a wider field of view. This paper investigates automatic DR severity assessment using 3-D OCTA. A straightforward solution to this task is a 3-D neural network classifier. However, 3-D architectures have numerous parameters and typically require many training samples. A lighter solution consists in using 2-D neural network classifiers processing 2-D en-face (or frontal) projections and/or 2-D cross-sectional slices. Such an approach mimics the way ophthalmologists analyze OCTA acquisitions: (1) en-face flow maps are often used to detect avascular zones and neovascularization, and (2) cross-sectional slices are commonly analyzed to detect macular edemas, for instance. However, arbitrary data reduction or selection might result in information loss. Two complementary strategies are thus proposed to optimally summarize OCTA volumes with 2-D images: (1) a parametric en-face projection optimized through deep learning and (2) a cross-sectional slice selection process controlled through gradient-based attribution. The full summarization and DR classification pipeline is trained from end to end. The automatic 2-D summary can be displayed in a viewer or printed in a report to support the decision. We show that the proposed 2-D summarization and classification pipeline outperforms direct 3-D classification with the advantage of improved interpretability.

Serum α-Klotho and fibroblast growth factor 23 levels are not associated with non-proliferative diabetic retinopathy in type 1 diabetes mellitus

Diabetic retinopathy is a commonly observed cause of blindness and is a common problem in individuals with diabetes. Recent investigations have showed the capability of serum α-Klotho and FGF 23 in mitigating the effects of diabetic retinopathy. This study aimed to discover the correlation between FGF 23, α-Klotho, and diabetic retinopathy in type 1 diabetics. This case-control study included 63 diabetic patients and 66 healthy controls. Following an overnight duration of fasting, morning blood samples were taken from both the patient and the control groups. The serum concentrations of α-Klotho and FGF 23 were quantified. An experienced ophthalmologist inspected the retinopathy. All participants in this study have moderate non-proliferative retinopathy. A p value under 0.05 was considered statistically significant. The mean α-Klotho level for retinopathic diabetic patients was 501.7 ± 172.2 pg/mL and 579.6 ± 312.1 pg/mL for non-retinopathic diabetic patients. In comparison, α-Klotho level of the control group was 523.2 ± 265.4 pg/mL (p = 0.531). The mean of FGF 23 level did not demonstrate a significant difference (p = 0.259). The mean FGF 23 level were 75.7 ± 14.0 pg/mL, 74.0 ± 14.8 pg/mL and 79.3 ± 14.4 pg/mL in groups, respectively. In conclusion, there was no significant difference in FGF 23 and α-Klotho levels between type 1 diabetics with and without retinopathy when compared to the control group.

A single cell atlas of circulating immune cells involved in diabetic retinopathy

This study focused on examining the exact role of circulating immune cells in the development of diabetic retinopathy (DR). In vitro co-culture experiments showed that peripheral blood mononuclear cells (PBMCs) from patients with type 1 DR crucially modulated the biological functions of human retinal microvascular endothelial cells (HRMECs), consequently disrupting their normal functionality. Single-cell RNA sequencing (scRNA-seq) study revealed unique differentially expressed genes and pathways in circulating immune cells among healthy controls, non-diabetic retinopathy (NDR) patients, and DR patients. Of significance was the observed upregulation of JUND in each subset of PBMCs in patients with type 1 DR. Further studies showed that downregulating JUND in DR patient-derived PBMCs led to the amelioration of HRMEC dysfunction. These findings highlighted the notable alterations in the transcriptomic patterns of circulating immune cells in type 1 DR patients and underscored the significance of JUND as a key factor for PBMCs in participating in the pathogenesis of DR.

The association between the severity of diabetic retinopathy and cognitive impairment: a cross-sectional study

PURPOSE

To assess the correlation among cognitive impairment (CI) and the degree of diabetic retinopathy (DR).

METHODS

The current analytic cross-sectional study has been carried out on two hundred ten individuals having diabetes mellitus type 2. Individuals were split into 7 groups in order of severity of DR in the worse eye with 30 cases in each group. Cognition function has been determined utilizing mini-mental state examination (MMSE) and montreal cognitive assessment (MoCA) tests.

RESULTS

Comparing the severity of CI using both MMSE and MoCA tests, statistically substantial differences have been discovered among individuals without DR, those having non-proliferative diabetic retinopathy (NPDR), and proliferative diabetic retinopathy (PDR) (p < 0.001). The greatest percentage of severe and moderate CI was seen in the PDR group. Regarding the severity of CI, there has been a statistically substantial difference among NPDR and PDR groups, as well as among no-DR and PDR groups (p < 0.001). Moreover, the severity of CI in the MMSE and MoCA tests had a negative connection with the grades of DR (r = - 0.522, P < 0.001 and r = - 0.540, P < 0.001, respectively).

CONCLUSION

We discovered a negative connection between the grades of DR and the severity of CI that persisted as a significant finding, showing that patients with more severe DR tended to have higher levels of CI. These results might offer retinal examination or retinal photography as a promising strategy for mass screening of CI in diabetic patients, especially if it is combined with artificial intelligence and telemedicine.

Emerging role of extracellular vesicles in diabetic retinopathy

Diabetic retinopathy (DR), a complex complication of diabetes mellitus (DM), is a leading cause of adult blindness. Hyperglycemia triggers DR, resulting in microvascular damage, glial apoptosis, and neuronal degeneration. Inflammation and oxidative stress play crucial roles during this process. Current clinical treatments for DR primarily target the advanced retinal disorder but offer limited benefits with inevitable side effects. Extracellular vesicles (EVs) exhibit unique morphological features, contents, and biological properties and can be found in cell culture supernatants, various body fluids, and tissues. In DR, EVs with specific cargo composition would induce the reaction of receptor cell once internalized, mediating cellular communication and disease progression. Increasing evidence indicates that monitoring changes in EV quantity and content in DR can aid in disease diagnosis and prognosis. Furthermore, extensive research is investigating the potential of these nanoparticles as effective therapeutic agents in preclinical models of DR. This review explores the current understanding of the pathological effects of EVs in DR development, discusses their potential as biomarkers and therapeutic strategies, and paves the way for further research and therapeutic advancements.

Present and future screening programs for diabetic retinopathy: a narrative review

Diabetes is a prevalent global concern, with an estimated 12% of the global adult population affected by 2045. Diabetic retinopathy (DR), a sight-threatening complication, has spurred diverse screening approaches worldwide due to advances in DR knowledge, rapid technological developments in retinal imaging and variations in healthcare resources.Many high income countries have fully implemented or are on the verge of completing a national Diabetic Eye Screening Programme (DESP). Although there have been some improvements in DR screening in Africa, Asia, and American countries further progress is needed. In low-income countries, only one out of 29, partially implemented a DESP, while 21 out of 50 lower-middle-income countries have started the DR policy cycle. Among upper-middle-income countries, a third of 59 nations have advanced in DR agenda-setting, with five having a comprehensive national DESP and 11 in the early stages of implementation.Many nations use 2-4 fields fundus images, proven effective with 80-98% sensitivity and 86-100% specificity compared to the traditional seven-field evaluation for DR. A cell phone based screening with a hand held retinal camera presents a potential low-cost alternative as imaging device. While this method in low-resource settings may not entirely match the sensitivity and specificity of seven-field stereoscopic photography, positive outcomes are observed.Individualized DR screening intervals are the standard in many high-resource nations. In countries that lacks a national DESP and resources, screening are more sporadic, i.e. screening intervals are not evidence-based and often less frequently, which can lead to late recognition of treatment required DR.The rising global prevalence of DR poses an economic challenge to nationwide screening programs AI-algorithms have showed high sensitivity and specificity for detection of DR and could provide a promising solution for the future screening burden.In summary, this narrative review enlightens on the epidemiology of DR and the necessity for effective DR screening programs. Worldwide evolution in existing approaches for DR screening has showed promising results but has also revealed limitations. Technological advancements, such as handheld imaging devices, tele ophthalmology and artificial intelligence enhance cost-effectiveness, but also the accessibility of DR screening in countries with low resources or where distance to or a shortage of ophthalmologists exists.

A deep learning system for predicting time to progression of diabetic retinopathy

Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images. First, we used 717,308 fundus images from 179,327 participants with diabetes to pretrain the system. Subsequently, we trained and validated the system with a multiethnic dataset comprising 118,868 images from 29,868 participants with diabetes. For predicting time to DR progression, the system achieved concordance indexes of 0.754-0.846 and integrated Brier scores of 0.153-0.241 for all times up to 5 years. Furthermore, we validated the system in real-world cohorts of participants with diabetes. The integration with clinical workflow could potentially extend the mean screening interval from 12 months to 31.97 months, and the percentage of participants recommended to be screened at 1-5 years was 30.62%, 20.00%, 19.63%, 11.85% and 17.89%, respectively, while delayed detection of progression to vision-threatening DR was 0.18%. Altogether, the DeepDR Plus system could predict individualized risk and time to DR progression over 5 years, potentially allowing personalized screening intervals.

[Objective functional monitoring of retinoprotective treatment in diabetic retinopathy]

In recent years, there has been a growing interest in the contribution of neuroretinal degeneration to the pathogenesis of diabetic retinopathy (DR).

PURPOSE

This study assesses the effect of the drug Retinalamin on the functional state of the retina in patients with DR using the Diopsys NOVA Vision Testing System that utilizes electrophysiological (EP) technology.

MATERIAL AND METHODS

The study included patients with type 1 and 2 diabetes mellitus (DM) with DR of any stage without macular edema. Patients underwent standard ophthalmological examination and objective functional examination of the retina using the Diopsys NOVA Vision Testing System. The control group consisted of patients with type 1 and 2 DM with DR who did not receive Retinalamin.

RESULTS

Significant changes in pattern electroretinography and flash electroretinography parameters were recorded in patients who received a course of Retinalamin. Two clinical examples are presented, which can be designated as the first experience of objective functional monitoring of treatment of patients with DR with Retinalamin.

CONCLUSION

Retinoprotective therapy is necessary already at the early stages of DR. Electroretinography is an objective tool for functional analysis of the earliest changes in retinal cells in DR. It is necessary to use the identified "therapeutic" window for the appointment of retinoprotective agents.

Oxidative Stress Mediates Epigenetic Modifications and the Expression of miRNAs and Genes Related to Apoptosis in Diabetic Retinopathy Patients

Knowledge on the underlying mechanisms and molecular targets for managing the ocular complications of type 2 diabetes mellitus (T2DM) remains incomplete. Diabetic retinopathy (DR) is a major cause of irreversible visual disability worldwide. By using ophthalmological and molecular-genetic approaches, we gathered specific information to build a data network for deciphering the crosslink of oxidative stress (OS) and apoptosis (AP) processes, as well as to identify potential epigenetic modifications related to noncoding RNAs in the eyes of patients with T2DM. A total of 120 participants were recruited, being classified into two groups: individuals with T2MD (T2MDG, n = 67), divided into a group of individuals with (+DR, n = 49) and without (-DR, n = 18) DR, and a control group (CG, n = 53). Analyses of compiled data reflected significantly higher plasma levels of malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPx) and significantly lower total antioxidant capacity (TAC) in the +DR patients compared with the -DR and the CG groups. Furthermore, the plasma caspase-3 (CAS3), highly involved in apoptosis (AP), showed significantly higher values in the +DR group than in the -DR patients. The microRNAs (miR) hsa-miR 10a-5p and hsa-miR 15b-5p, as well as the genes BCL2L2 and TP53 involved in these pathways, were identified in relation to DR clinical changes. Our data suggest an interaction between OS and the above players in DR pathogenesis. Furthermore, potential miRNA-regulated target genes were identified in relation to DR. In this concern, we may raise new diagnostic and therapeutic challenges that hold the potential to significantly improve managing the diabetic eye.

Progression of insulin resistance in individuals with type 1 diabetes: A retrospective longitudinal study on individuals from Thailand

AIMS

To investigate temporal changes in glycaemic control and weight contributing to insulin resistance (IR), in Thai individuals with type 1 diabetes (T1D).

METHODS

Longitudinal data of 69 individuals with T1D were retrospectively collected over a median follow-up of 7.2 years. The estimated glucose disposal rate (eGDR), a marker of IR, was calculated using an established formula. Individuals were assigned as insulin-sensitive T1D (the latest eGDR≥8 mg/kg/min), or insulin-resistant T1D/double diabetes (the latest eGDR<8 mg/kg/min). Generalised linear mixed model was employed to compare the temporal patterns of HbA1c, BMI, and eGDR between the two groups.

RESULTS

26 insulin-resistant T1D had a gradual decline in eGDR, corresponding with increased weight and HbA1c. In contrast, 43 insulin-sensitive T1D had stable insulin sensitivity with an improvement in HbA1c over time, associated with a modest weight gain. Fluctuations of glucose levels were observed during the early diabetes course leading to unstable eGDR, thus limiting the use of eGDR to classify insulin-resistant T1D.

CONCLUSION

T1D individuals who eventually develop IR are likely to experience early increasing IR over time. In contrast, those who ultimately do not have IR, maintain their insulin sensitivity throughout their course at least in the medium term.

Lesion-aware attention network for diabetic nephropathy diagnosis with optical coherence tomography images

Purpose

For early screening of diabetic nephropathy patients, we propose a deep learning algorithm to screen high-risk patients with diabetic nephropathy from retinal images of diabetic patients.

Methods

We propose the use of attentional mechanisms to improve the model's focus on lesion-prone regions of retinal OCT images. First, the data is trained using the base network and the Grad-CAM algorithm locates image regions that have a large impact on the model output and generates a rough mask localization map. The mask is used as a auxiliary region to realize the auxiliary attention module. We then inserted the region-guided attention module into the baseline model and trained the CNN model to guide the model to better focus on relevant lesion features. The proposed model improves the recognition of the lesion region.

Results

To evaluate the lesion-aware attention network, we trained and tested it using OCT volumetric data collected from 66 patients with diabetic retinal microangiopathy (89 eyes, male = 43, female = 23). There were 45 patients (60 eyes, male=27, female = 18) in DR group and 21 patients (29 eyes, male = 16, female = 5) in DN group. Our proposed model performs even better in disease classification, specifically, the accuracy of the proposed model was 91.68%, the sensitivity was 89.99%, and the specificity was 92.18%.

Conclusion

The proposed lesion-aware attention model can provide reliable screening of high-risk patients with diabetic nephropathy.

Liraglutide intervention improves high-glucose-induced reactive gliosis of Müller cells and ECM dysregulation

Reactive gliosis of Müller cells plays an important role in the pathogenesis of diabetic retinopathy (DR). Liraglutide, a glucagon-like peptide-1 receptor (GLP-1R) agonist, has been shown to improve DR by inhibiting reactive gliosis. However, the mechanism of inhibition has yet to be elucidated. This study investigated the effects of liraglutide on Müller glia reactivity in the early stages of DR and the underlying mechanisms. Proteomics combined with bioinformatics analysis, HE staining, and immunofluorescence staining revealed ganglion cell loss, reactive gliosis of Müller cells, and extracellular matrix (ECM) imbalance in rats with early stages of DR. High glucose (HG) exposure up-regulated GFAP and TNF-α expression and down-regulated ITGB1 expression and FN1 content in extracellular fluid in rMC1 cells, thereby promoting reactive gliosis. GLP-1R knockdown and HG+DAPT inhibition experiments show that liraglutide balances ECM levels by inhibiting activation of the Notch1/Hes1 pathway and ameliorates high-glucose-induced Müller glia reactivity. Thus, the study provides new targets and ideas for improvement of DR in early stages.

Recent advances in the study of circadian rhythm disorders that induce diabetic retinopathy

Diabetic retinopathy (DR) is a severe microvascular complication of diabetes mellitus and a major cause of blindness in young adults. Multiple potential factors influence DR; however, the exact mechanisms are poorly understood. Advanced treatments for DR, including laser therapy, vitrectomy, and intraocular drug injections, slow the disease's progression but fail to cure or reverse visual impairment. Therefore, additional effective methods to prevent and treat DR are required. The biological clock plays a crucial role in maintaining balance in the circadian rhythm of the body. Poor lifestyle habits, such as irregular routines and high-fat diets, may disrupt central and limbic circadian rhythms. Disrupted circadian rhythms can result in altered glucose metabolism and obesity. Misaligned central and peripheral clocks lead to a disorder of the rhythm of glucose metabolism, and chronically high sugar levels lead to the development of DR. We observed a disturbance in clock function in patients with diabetes, and a misaligned clock could accelerate the development of DR. In the current study, we examine the relationship between circadian rhythm disorders, diabetes, and DR. We conclude that: 1) abnormal function of the central clock and peripheral clock leads to abnormal glucose metabolism, further causing DR and 2) diabetes causes abnormal circadian rhythms, further exacerbating DR. Thus, our study presents new insights into the prevention and treatment of DR.

Research progress in artificial intelligence assisted diabetic retinopathy diagnosis

Diabetic retinopathy (DR) is one of the most common retinal vascular diseases and one of the main causes of blindness worldwide. Early detection and treatment can effectively delay vision decline and even blindness in patients with DR. In recent years, artificial intelligence (AI) models constructed by machine learning and deep learning (DL) algorithms have been widely used in ophthalmology research, especially in diagnosing and treating ophthalmic diseases, particularly DR. Regarding DR, AI has mainly been used in its diagnosis, grading, and lesion recognition and segmentation, and good research and application results have been achieved. This study summarizes the research progress in AI models based on machine learning and DL algorithms for DR diagnosis and discusses some limitations and challenges in AI research.

Rapid Reduction of HbA1c and Early Worsening of Diabetic Retinopathy: A Real-world Population-Based Study in Subjects With Type 2 Diabetes

OBJECTIVE

Early worsening of diabetic retinopathy (EWDR) due to the rapid decrease of blood glucose levels is a concern in diabetes treatment. The aim of the current study is to evaluate whether this is an important issue in subjects with type 2 diabetes with mild or moderate nonproliferative DR (NPDR), who represent the vast majority of subjects with DR attended in primary care.

RESEARCH DESIGN AND METHODS

This is a retrospective nested case-control study of subjects with type 2 diabetes and previous mild or moderate NPDR. Using the SIDIAP ("Sistema d'informació pel Desenvolupament de la Recerca a Atenció Primària") database, we selected 1,150 individuals with EWDR and 1,150 matched control subjects (DR without EWDR). The main variable analyzed was the magnitude of the reduction of HbA1c in the previous 12 months. The reduction of HbA1c was categorized as rapid (>1.5% reduction in <12 months) or very rapid (>2% in <6 months).

RESULTS

We did not find any significant difference in HbA1c reduction between case and control subjects (0.13 ± 1.21 vs. 0.21 ± 1.18; P = 0.12). HbA1c reduction did not show significant association with worsening of DR, neither in the unadjusted analyses nor in adjusted statistical models that included the main confounding variables: duration of diabetes, baseline HbA1c, presence of hypertension, and antidiabetic drugs. In addition, when stratification by baseline HbA1c was performed, we did not find that those patients with higher levels of HbA1c presented a higher risk to EWDR.

CONCLUSIONS

Our results suggest that the rapid reduction of HbA1c is not associated with progression of mild or moderate NPDR.

Oxidative Stress and Its Regulation in Diabetic Retinopathy

Diabetic retinopathy is the retinal disease associated with hyperglycemia in patients who suffer from type 1 or type 2 diabetes. It includes maculopathy, involving the central retina and characterized by ischemia and/or edema, and peripheral retinopathy that progresses to a proliferative stage with neovascularization. Approximately 10% of the global population is estimated to suffer from diabetes, and around one in 5 of these individuals have diabetic retinopathy. One of the major effects of hyperglycemia is oxidative stress, the pathological state in which elevated production of reactive oxygen species damages tissues, cells, and macromolecules. The retina is relatively prone to oxidative stress due to its high metabolic activity. This review provides a summary of the role of oxidative stress in diabetic retinopathy, including a description of the retinal cell players and the molecular mechanisms. It discusses pathological processes, including the formation and effects of advanced glycation end-products, the impact of metabolic memory, and involvements of non-coding RNA. The opportunities for the therapeutic blockade of oxidative stress in diabetic retinopathy are also considered.

Porphyromonas gingivalis outer membrane vesicles exacerbate retinal microvascular endothelial cell dysfunction in diabetic retinopathy

Diabetic retinopathy (DR) is one of the leading causes of blindness. Periodontitis is one of the highest oral incidences and has been closely related to various systemic conditions through Porphyromonas gingivalis (P. gingivalis). P. gingivalis OMVs, derived from P. gingivalis, can cause endothelial dysfunction and potentially affect microvascular diseases. Current epidemiological studies provide limited evidence suggesting that periodontitis is associated with DR. However, there is a lack of basic research elucidating how periodontitis affects the severity of DR. This study aimed to explore the potential of P. gingivalis OMVs to contribute to the pathogenesis of DR and explore how it affect the retinal microvascular endothelium. The results demonstrated that P. gingivalis OMVs accelerated the blood-retinal barrier damage in DR mice. In vitro studies showed that the expression of inflammatory factors in human retinal microvascular endothelial cells (HRMECs) was increased after P. gingivalis OMVs stimulation, and the increased reactive oxygen species production, mitochondrial dysfunction, apoptosis, and altered endothelial permeability were observed in HRMECs under P. gingivalis OMVs stimulation. In addition, we found that protease-activated receptor-2 (PAR-2) regulated OMVs-induced TNF-α, MMP-9 mRNA expression, cell death, and endothelial permeability. Overall, we suggested that P. gingivalis OMVs induced mitochondria-related cell death of HRMECs and accelerated endothelial dysfunction, thus aggravating DR, in which PAR-2 plays a potential role. This study is the first research report to delineate the potential molecular mechanism of P. gingivalis OMVs on DR pathogenesis, which uniquely focused on elucidating the possible impact of periodontal pathogen derivatives on DR progression.

Research progress on diagnosing retinal vascular diseases based on artificial intelligence and fundus images

As the only blood vessels that can directly be seen in the whole body, pathological changes in retinal vessels are related to the metabolic state of the whole body and many systems, which seriously affect the vision and quality of life of patients. Timely diagnosis and treatment are key to improving vision prognosis. In recent years, with the rapid development of artificial intelligence, the application of artificial intelligence in ophthalmology has become increasingly extensive and in-depth, especially in the field of retinal vascular diseases. Research study results based on artificial intelligence and fundus images are remarkable and provides a great possibility for early diagnosis and treatment. This paper reviews the recent research progress on artificial intelligence in retinal vascular diseases (including diabetic retinopathy, hypertensive retinopathy, retinal vein occlusion, retinopathy of prematurity, and age-related macular degeneration). The limitations and challenges of the research process are also discussed.