Search Results (2,208)

Fyn is widely involved in diverse cellular physiological processes, including cell growth and survival, and has been implicated in the regulation of energy metabolism and the pathogenesis of diabetes mellitus through multiple pathways. Fyn plays a role in increasing fat accumulation and promoting insulin resistance, and it also contributes to the development of diabetic complications such as diabetic kidney disease and diabetic retinopathy. The primary mechanism by which Fyn modulates lipid metabolism is that it inhibits AMP-activated protein kinase (AMPK). Additionally, it affects energy homeostasis through regulating specific signal pathways affecting lipid metabolism including pathways related to CD36, through enhancement of adipocyte differentiation, and through modulating insulin signal transduction. Inflammatory stress is one of the fundamental mechanisms in diabetes mellitus and its complications. Fyn also plays a role in inflammatory stress-related signaling cascades such as the Akt/GSK-3β/Fyn/Nrf2 pathway, exacerbating inflammation in diabetes mellitus. Therefore, Fyn emerges as a promising therapeutic target for regulating glucolipid metabolism and alleviating type 2 diabetes mellitus. This review synthesizes research on the role of Fyn in the regulation of energy metabolism and the development of diabetes mellitus, while exploring its specific regulatory mechanisms. Full article

Background/Objectives: Diabetic retinopathy is a leading cause of vision impairment worldwide, and the development of reliable automated classification systems is crucial for early diagnosis and clinical decision-making. This study presents a comprehensive comparative evaluation of two state-of-the-art deep learning families for the task of classifying diabetic retinopathy using retinal fundus images. Methods: The models were trained and tested in both binary and multi-class settings. The experimental design involved partitioning the data into training (70%), validation (20%), and testing (10%) sets. Model performance was assessed using standard metrics, including precision, sensitivity, specificity, F1-score, and the area under the receiver operating characteristic curve. Results: In binary classification, the ResNeXt101-64x4d model and RegNetY32GT model demonstrated outstanding performance, each achieving high sensitivity and precision. For multi-class classification, ResNeXt101-32x8d exhibited strong performance in early stages, while RegNetY16GT showed better balance across all stages, particularly in advanced diabetic retinopathy cases. To enhance transparency, SHapley Additive exPlanations were employed to visualize the pixel-level contributions for each model’s predictions. Conclusions: The findings suggest that while ResNeXt models are effective in detecting early signs, RegNet models offer more consistent performance in distinguishing between multiple stages of diabetic retinopathy severity. This dual approach combining quantitative evaluation and model interpretability supports the development of more robust and clinically trustworthy decision support systems for diabetic retinopathy screening. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly recognized as a significant comorbidity in individuals with type 1 diabetes (T1D), despite its historical association with type 2 diabetes. This review focuses on summarizing current findings regarding the role of insulin resistance in the development of MASLD in T1D, as well as examining the relationship between MASLD and diabetes-related complications. We will also briefly discuss the prevalence, diagnostic challenges, associated complications, and potential mechanisms underlying MASLD in T1D. Although insulin resistance is well established in MASLD among those with type 2 diabetes, its role in T1D requires further clarification. Emerging markers, such as the estimated glucose disposal rate, offer early insight into this relationship. MASLD in T1D is linked to both microvascular and macrovascular complications, including nephropathy, retinopathy, neuropathy, and cardiovascular disease. Variability in prevalence estimates reflects inconsistencies among imaging modalities, emphasizing the need for standardized, non-invasive diagnostic approaches. Recognizing and addressing MASLD and its links to insulin resistance and diabetes complications in T1D is vital for mitigating long-term complications and enhancing clinical outcomes. Full article

Diabetic retinopathy (DR) is a progressive, multifactorial complication of diabetes and one of the major global causes of visual impairment. Its pathogenesis involves chronic hyperglycaemia-induced oxidative stress, inflammation, mitochondrial dysfunction, neurodegeneration, and pathological angiogenesis, as well as emerging systemic contributors such as gut microbiota dysregulation. While current treatments, including anti-vascular endothelial growth factor (anti-VEGF) agents, corticosteroids, and laser photocoagulation, have shown clinical efficacy, they are largely limited to advanced stages of DR, require repeated invasive procedures, and do not adequately address early neurovascular and metabolic abnormalities. Resveratrol (RSV), a naturally occurring polyphenol, has emerged as a promising candidate due to its potent antioxidant, anti-inflammatory, neuroprotective, and anti-angiogenic properties. This review provides a comprehensive analysis of the molecular mechanisms by which RSV exerts protective effects in DR, including modulation of oxidative stress pathways, suppression of inflammatory cytokines, enhancement of mitochondrial function, promotion of autophagy, and inhibition of pathological neovascularisation. Despite its promising pharmacological profile, the clinical application of RSV is limited by poor aqueous solubility, rapid systemic metabolism, and low ocular bioavailability. Various routes of administration, including intravitreal injection, topical instillation, and oral and sublingual delivery, have been investigated to enhance its therapeutic potential. Recent advances in drug delivery systems, including nanoformulations, liposomal carriers, and sustained-release intravitreal implants, offer potential strategies to address these challenges. This review also explores RSV’s role in combination therapies, its potential as a disease-modifying agent in early-stage DR, and the relevance of personalised medicine approaches guided by metabolic and genetic factors. Overall, the review highlights the therapeutic potential and the key translational challenges in positioning RSV as a multi-targeted treatment strategy for DR. Full article

Diabetes mellitus poses a significant global health challenge, primarily due to its chronic metabolic dysregulation, leading to widespread tissue and organ damage. This systemic impact results in a range of complications that markedly reduce patients’ quality of life. Therefore it is critical to understand the mechanisms underlying these complications. DJ-1 (also known as PARK7) is a highly conserved multifunctional protein involved in antioxidative defense, metabolic equilibrium, and cellular survival. Recent studies have highlighted that DJ-1 is critically involved in the pathogenesis and progression of diabetic complications, including macrovascular issues like cardiovascular disease and microvascular conditions such as diabetic nephropathy, retinopathy, and neuropathy, suggesting that it may serve as a promising therapeutic target. Importantly, drugs targeting DJ-1 have shown therapeutic effects. This review provides a comprehensive overview of the current under-standing of DJ-1’s role in diabetes-related complications, emphasizing recent research advances. Full article

The retina offers a unique window into both ocular and systemic health, motivating the development of AI-based tools for disease screening and risk assessment. In this study, we present a comprehensive evaluation of six state-of-the-art deep neural networks, including convolutional neural networks and vision transformer architectures, on the Brazilian Multilabel Ophthalmological Dataset (BRSET), comprising 16,266 fundus images annotated for multiple clinical and demographic labels. We explored seven classification tasks: Diabetes, Diabetic Retinopathy (2-class), Diabetic Retinopathy (3-class), Hypertension, Hypertensive Retinopathy, Drusen, and Sex classification. Models were evaluated using precision, recall, F1-score, accuracy, and AUC. Among all models, the Swin-L generally delivered the best performance across scenarios for Diabetes (AUC = 0.88, weighted F1-score = 0.86), Diabetic Retinopathy (2-class) (AUC = 0.98, weighted F1-score = 0.95), Diabetic Retinopathy (3-class) (macro AUC = 0.98, weighted F1-score = 0.95), Hypertension (AUC = 0.85, weighted F1-score = 0.79), Hypertensive Retinopathy (AUC = 0.81, weighted F1-score = 0.97), Drusen detection (AUC = 0.93, weighted F1-score = 0.90), and Sex classification (AUC = 0.87, weighted F1-score = 0.80). These results reflect excellent to outstanding diagnostic performance. We also employed gradient-based saliency maps to enhance explainability and visualize decision-relevant retinal features. Our findings underscore the potential of deep learning, particularly vision transformer models, to deliver accurate, interpretable, and clinically meaningful screening tools for retinal and systemic disease detection. Full article

Obstructive sleep apnea (OSA) is a common condition associated with intermittent hypoxia, systemic inflammation, and vascular dysfunction; mechanisms implicated in retinal disease pathogenesis. This real-world retrospective cohort study used data from the TriNetX Research Network to assess whether continuous positive airway pressure (CPAP) therapy reduces retinal disease incidence among adults with OSA and BMI between 25.0 and 30.0 kg/m². After 1:1 propensity score matching, 101,754 patients were included in the analysis. Retinal outcomes included diabetic retinopathy (DR), age-related macular degeneration (AMD), retinal vein occlusion (RVO), and central serous chorioretinopathy (CSC). CPAP use was associated with a modest but statistically significant reduction in DR (3.2% vs. 3.4%, RR: 0.922, p = 0.016) and AMD (2.1% vs. 2.3%, RR: 0.906, p = 0.018), while no significant differences were found for RVO or CSC. These findings support prior evidence linking CPAP to improved retinal microvascular health and suggest a protective effect against specific retinal complications. Limitations include a lack of data on CPAP adherence, OSA severity, and imaging confirmation. Still, this study highlights the importance of interdisciplinary care between sleep and eye health, and the need for further prospective studies to validate CPAP’s role in preventing retinal disease progression in OSA patients. Full article

Objective: This study aimed to determine the possibility of creating a new animal model in which diabetic retinopathy (DR) progresses due to hypertension caused by salt loading. Methods: Male Spontaneously Diabetic Torii (SDT) fatty rats were divided into two groups: one group received 0.3% saline water starting at 8 weeks of age for a duration of 16 weeks (salt SDT fatty group), while the control group was provided with tap water (SDT fatty group). In addition, Sprague-Dawley (SD) rats receiving tap water served as normal controls. Retinal function was assessed by electroretinography (ERG) at 8 and 24 weeks of age. At 24 weeks, following perfusion with fluorescein dextran, the eyes were enucleated, and retinal flat mounts were prepared for vascular evaluation. Retinal thickness and the number of retinal folds were assessed histologically, and ultrastructural changes in the retina were examined using transmission electron microscopy. Results: Saline administration did not lead to significant changes in food consumption or body weight among the groups. In the salt SDT fatty group, blood pressure was significantly elevated, while blood glucose levels showed a slight reduction. ERG analysis showed that the amplitude of oscillatory potential (OP)1 waves was suppressed, and the latencies of OP3, OP4, and OP5 waves were prolonged. Although no significant changes were noted in retinal thickness or the number of retinal folds, thickening of the retinal capillary basement membrane was evident in the salt SDT fatty group. Conclusions: Hypertension induced by 0.3% saline promotes DR progression in SDT fatty rats. This model may help clarify the role of hypertension in DR. Full article

Background: Artificial intelligence (AI) and machine learning (ML) have been reshaping maternal, fetal, neonatal, and reproductive healthcare by enhancing risk prediction, diagnostic accuracy, and operational efficiency across the perinatal continuum. However, no comprehensive synthesis has yet been published. Objective: To conduct a scoping review of reviews of AI/ML applications spanning reproductive, prenatal, postpartum, neonatal, and early child-development care. Methods: We searched PubMed, Embase, the Cochrane Library, Web of Science, and Scopus through April 2025. Two reviewers independently screened records, extracted data, and assessed methodological quality using AMSTAR 2 for systematic reviews, ROBIS for bias assessment, SANRA for narrative reviews, and JBI guidance for scoping reviews. Results: Thirty-nine reviews met our inclusion criteria. In preconception and fertility treatment, convolutional neural network-based platforms can identify viable embryos and key sperm parameters with over 90 percent accuracy, and machine-learning models can personalize follicle-stimulating hormone regimens to boost mature oocyte yield while reducing overall medication use. Digital sexual-health chatbots have enhanced patient education, pre-exposure prophylaxis adherence, and safer sexual behaviors, although data-privacy safeguards and bias mitigation remain priorities. During pregnancy, advanced deep-learning models can segment fetal anatomy on ultrasound images with more than 90 percent overlap compared to expert annotations and can detect anomalies with sensitivity exceeding 93 percent. Predictive biometric tools can estimate gestational age within one week with accuracy and fetal weight within approximately 190 g. In the postpartum period, AI-driven decision-support systems and conversational agents can facilitate early screening for depression and can guide follow-up care. Wearable sensors enable remote monitoring of maternal blood pressure and heart rate to support timely clinical intervention. Within neonatal care, the Heart Rate Observation (HeRO) system has reduced mortality among very low-birth-weight infants by roughly 20 percent, and additional AI models can predict neonatal sepsis, retinopathy of prematurity, and necrotizing enterocolitis with area-under-the-curve values above 0.80. From an operational standpoint, automated ultrasound workflows deliver biometric measurements at about 14 milliseconds per frame, and dynamic scheduling in IVF laboratories lowers staff workload and per-cycle costs. Home-monitoring platforms for pregnant women are associated with 7–11 percent reductions in maternal mortality and preeclampsia incidence. Despite these advances, most evidence derives from retrospective, single-center studies with limited external validation. Low-resource settings, especially in Sub-Saharan Africa, remain under-represented, and few AI solutions are fully embedded in electronic health records. Conclusions: AI holds transformative promise for perinatal care but will require prospective multicenter validation, equity-centered design, robust governance, transparent fairness audits, and seamless electronic health record integration to translate these innovations into routine practice and improve maternal and neonatal outcomes. Full article

Background: Retinal diseases are becoming an important public health issue, with early diagnosis and timely intervention playing a key role in preventing vision loss. Optical coherence tomography (OCT) remains the leading non-invasive imaging technique for identifying retinal conditions. However, distinguishing between diabetic macular edema (DME) and macular edema resulting from retinal vein occlusion (RVO) can be particularly challenging, especially for clinicians without specialized training in retinal disorders, as both conditions manifest through increased retinal thickness. Due to the limited research exploring the application of deep learning methods, particularly for RVO detection using OCT scans, this study proposes a novel diagnostic approach based on stacked convolutional neural networks. This architecture aims to enhance classification accuracy by integrating multiple neural network layers, enabling more robust feature extraction and improved differentiation between retinal pathologies. Methods: The VGG-16, VGG-19, and ResNet50 models were fine-tuned using the Kermany dataset to classify the OCT images and afterwards were trained using a private OCT dataset. Four stacked models were then developed using these models: a model using the VGG-16 and VGG-19 networks, a model using the VGG-16 and ResNet50 networks, a model using the VGG-19 and ResNet50 models, and finally a model using all three networks. The performance metrics of the model includes accuracy, precision, recall, $F_2$-score, and area under of the receiver operating characteristic curve (AUROC). Results: The stacked neural network using all three models achieved the best results, having an accuracy of 90.7%, precision of 99.2%, a recall of 90.7%, and an $F_2$-score of 92.3%. Conclusions: This study presents a novel method for distinguishing retinal disease by using stacked neural networks. This research aims to provide a reliable tool for ophthalmologists to improve diagnosis accuracy and speed. Full article

RNA-seq analysis of the highly differentiated human retinal pigment epithelial (RPE) cell-line ARPE-19, cultured on transwells for ≥4 months, yielded 44,909 genes showing 83.35% alignment with the human reference genome. These included mRNA transcripts of RPE-specific genes and those involved in retinopathies. Monolayers were fed photoreceptor outer segments (POS), designed to be synchronously internalised, mimicking homeostatic RPE activity. Cells were subsequently fixed at 4, 6, 24 and 48 h when POS were previously shown to maximally co-localise with Rab5, Rab7, LAMP/lysosomes and LC3b/autophagic compartments. A comprehensive analysis of differentially expressed genes involved in proteolysis revealed a pattern of gene orchestration consistent with POS breakdown in the autophagy-lysosomal pathway. At 4 h, these included elevated upstream signalling events promoting early stages of cargo transport and endosome maturation compared to RPE without POS exposure. This transcriptional landscape altered from 6 h, transitioning to promoting cargo degradation in autolysosomes by 24–48 h. Longitudinal scrutiny of mRNA transcripts revealed nuanced differences even within linked gene networks. POS exposure also initiated transcriptional upregulation in ubiquitin proteasome and chaperone-mediated systems within 4–6 h, providing evidence of cross-talk with other proteolytic processes. These findings show detailed evidence of transcriptome-level responses to cargo trafficking and processing in RPE cells. Full article

This study aimed to evaluate the impact of preoperative anti-VEGF injections on pars plana vitrectomy (PPV) outcomes in patients with proliferative diabetic retinopathy (PDR). Material and methods: We analysed 232 eyes with proliferative diabetic vitreoretinopathy treated with posterior vitrectomy. There were 112 women and 120 men. The patients were divided into two groups of 116 eyes each. In 116 eyes (study group), an anti-VEGF injection was administered 3 to 5 days before vitrectomy. The control eyes were not injected with anti-VEGF due to systemic contraindications to anti-VEGF treatment or lack of patient consent. All participants underwent pars plana vitrectomy with silicone oil injection. The oil was removed within 2–3 months after PPV. Results: At 2 years of observation, after removal of silicone oil, visual acuity (VA) was 0.24 ± 0.27 logMAR in the study and 0.37 ± 0.45 logMAR in the control group (p = 0.003). Intraocular pressure was 16.84 ± 6.25 mmHg in the study group and 17.78 ± 6.22 mmHg in the control group (p = 0.04). The mean duration of surgery was 47.62 ± 9.87 and 50.05 ± 9.41 min in the study and control groups, respectively (p = 0.02). The size of intraoperative haemorrhage was 0.97 ± 0.86 dd in the study group and 1.51 ± 1.22 dd in the control group (p = 0.003). The frequency of surgery-induced retinal breaks was 0.34 ± 0.56 in the study group and 0.56 ± 0.76 in the control group (p = 0.003). The recurrence rate of retinal detachment was 0.05 ± 0.22 in the study group and 0.1 ± 0.31 in the control group (p = 0.15). Conclusions: Preoperative anti-VEGF therapy shortens the duration of surgery, reduces complications, and improves long-term outcomes in terms of visual acuity and maintenance of normal eye function. Full article

Background: Although semaglutide (Ozempic^®) is being prescribed off-label to individuals with obesity, some concerns have arisen regarding its use, particularly regarding the risk of thyroid and pancreatic disorders. Therefore, it is crucial to screen patients’ medical and family disease histories, as well as certain clinical parameters, before initiating this treatment for obesity or weight management. However, there is limited research investigating whether pretreatment assessment is adopted in clinical practice. Method: This is a single-center retrospective study involving adults who were prescribed semaglutide for obesity or weight management. Demographic data, comorbid conditions, semaglutide-related lab work, and disease history assessments, including pancreatitis, thyroid abnormalities, oculopathy, neuropathy, and any family history of thyroid cancer, were evaluated and documented prior to treatment initiation. Results: In total, 715 patients were included in the study, with an average age of 40.2 ± 12.0 years, and 49.5% of participants were male. The average weight and BMI prior to using semaglutide were 99.8 ± 18.1 kg and 36.3 ± 8.3 kg/m², respectively, with predominantly overweight and obese individuals (collectively 91.3%). Approximately 69% of patients had 3–5 complications, with a high prevalence of cardiovascular and metabolic diseases before using semaglutide. Although HbA1c, serum creatinine, TSH, T3, T4, triglycerides, HDL, LDL, total cholesterol, and total bilirubin were monitored prior to semaglutide use, none of the patients’ pancreatic lipase, amylase, or calcitonin levels were measured. Although it is important to investigate all personal and family disease histories, including thyroid abnormalities, thyroid cancer, pancreatitis, retinopathy, eye problems, and neuropathy prior to semaglutide initiation, checks were only conducted in 1.8% of patients, despite 98.6% having at least one of the diseases assessed pretreatment. Conclusions: The current pretreatment assessment approach for patients prescribed semaglutide for weight reduction is underdeveloped, particularly with regard to assessing the influence of disease history on semaglutide use. This predisposes patients to a risk of severe clinical outcomes, including thyroid cancer, pancreatitis, and retinopathy. Full article

Background/Objectives: Diabetic macular edema (DME) is the primary cause of vision loss in people with diabetes, and if untreated, it can result in irreversible macular damage. Both fluorescein angiography (FA), the gold standard, and optical coherence tomography angiography (OCTA) are used for evaluation of this disease. The objective of this study was to compare the diagnostic value of both. Methods: We conducted a comparative analysis of 98 patients aged 18–80 years with significant DME and best-corrected visual acuity ≥0.1 according to the Snellen chart. Participants underwent glycated hemoglobin blood test (HbA1c) and ophthalmological examinations, including OCTA and FA. OCTA 3 × 3 mm scans of superficial (SCP) and deep capillary plexus (DCP) along with FA scans were exported to the Gimp computer program. Size of the foveal avascular zone (FAZ), the number of visible microaneurysms (MAs), and ETDRS report number 11 classification of the images were assessed. Results: FAZ size differed significantly in superficial plexus (0.41 mm²), deep plexus (0.43 mm²) OCTA, and FA (0.38 mm²) (p < 0.001). FAZ size in DCP OCTA closely correlated with that of FA (τ = 0.79, p < 0.001). The total number of MAs visualized in the OCTA was significantly lower than in FA (p < 0.001). ETDRS classification of scans revealed that the level of consistency between the examinations was moderate to very strong. Conclusions: OCTA may be useful in evaluating macular ischemia. It is less sensitive in detecting MAs in DME eyes. FAZ has sharper boundaries and is larger when measured in OCTA. Poor glycemic control results in higher incidence of MAs in macula. Full article

Visual field (VF) testing remains a cornerstone in assessing retinal function by measuring how well different parts of the retina detect light. It is essential for early detection, monitoring, and management of many retinal diseases. By mapping retinal sensitivity, VF exams can reveal functional loss before structural changes become visible. This review summarizes how VF testing is applied across key conditions: hydroxychloroquine (HCQ) retinopathy, age-related macular degeneration (AMD), diabetic retinopathy (DR) and macular edema (DME), and inherited disorders including inherited dystrophies such as retinitis pigmentosa (RP). Traditional methods like the Goldmann kinetic perimetry and simple tools such as the Amsler grid help identify large or central VF defects. Automated perimetry (e.g., Humphrey Field Analyzer) provides detailed, quantitative data critical for detecting subtle paracentral scotomas in HCQ retinopathy and central vision loss in AMD. Frequency-doubling technology (FDT) reveals early neural deficits in DR before blood vessel changes appear. Microperimetry offers precise, localized sensitivity maps for macular diseases. Despite its value, VF testing faces challenges including patient fatigue, variability in responses, and interpretation of unreliable results. Recent advances in artificial intelligence, virtual reality perimetry, and home-based perimetry systems are improving test accuracy, accessibility, and patient engagement. Integrating VF exams with these emerging technologies promises more personalized care, earlier intervention, and better long-term outcomes for patients with retinal disease. Full article