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A researcher at the University of Illinois Chicago discusses the implementation of artificial intelligence in the care of retinopathy of prematurity (ROP). The study highlights the challenges and opportunities of using AI systems for diagnosing ROP, emphasizing the importance of a stable telemedicine infrastructure for successful implementation. The research suggests the need for further validation of AI systems with diverse populations and low-cost imaging devices to prevent childhood blindness effectively. [Extracted from the article]

Researchers at Bharati Vidyapeeth (Deemed to be University) Medical College and Hospital in Maharashtra, India, conducted a study on retinopathy of prematurity (ROP), a vaso-proliferative retinal disease that can lead to blindness if not diagnosed early. The study found that factors such as low birth weight, prematurity, respiratory distress syndrome, and mechanical ventilation were significantly associated with ROP. Prompt screening and early diagnosis of ROP are crucial in reducing complications and preventing blindness. The study was published in the Al Ameen Journal of Medical Sciences. [Extracted from the article]

Researchers at Johns Hopkins University conducted a study to compare different methods for identifying diabetic retinopathy (DR) and related conditions using natural language processing (NLP) techniques. The study included 91,097 patients and 692,486 office visits, with the Text-and-ICD NLP System showing the highest performance in identifying clinical conditions. The prevalence of DR and related conditions varied depending on the identification methodology, with the Text-and-ICD NLP System being the most effective. The study was supported by Research To Prevent Blindness and the National Eye Institute. [Extracted from the article]

Researchers at the University of Malaya in Kuala Lumpur, Malaysia, have developed a privacy-preserving approach using deep learning models for diagnosing diabetic retinopathy (DR). Diabetic retinopathy is a common complication of diabetes that can lead to blindness if not detected early. The study explores the use of artificial intelligence (AI) to predict DR risks while addressing privacy concerns related to healthcare data. The findings suggest that privacy-preserving methods, such as encryption, do not significantly impact the performance of the AI models in predicting DR risks. [Extracted from the article]

Researchers at the Second Xiangya Hospital of Central South University in China have detailed the progress and prospects of using artificial intelligence (AI) in diagnosing and treating diabetic retinopathy (DR). The integration of AI, particularly deep learning models, has significantly improved early DR detection and may soon be used in telemedicine to address medical resource shortages and health inequities. The study highlights key AI models for DR diagnosis and treatment, addressing challenges such as bias, transparency, and ethics, and offers a prospective outlook on future developments in this field. [Extracted from the article]

Researchers from the University of Medicine and Pharmacy Timisoara in Romania conducted a study on 377 patients with type 2 diabetes mellitus to assess cardiovascular risk factors as independent predictors of diabetic retinopathy (DR) progression. The study found that systolic blood pressure, LDL cholesterol, and body mass index (BMI) were significant predictors of DR progression. Machine learning models, particularly XGBoost, showed moderate accuracy in identifying DR stages, suggesting that integrating these risk factors into clinical practice may improve early detection and intervention strategies for DR. The study was published in Medicina and can be accessed for free online. [Extracted from the article]

University of California researchers conducted a study comparing the use of a rule-based natural language processing (NLP) algorithm with International Classification of Diseases (ICD) codes for classifying diabetic retinopathy severity. The study found that the NLP algorithm performed better in classifying proliferative diabetic retinopathy (PDR) compared to ICD codes, with higher sensitivity and similar positive predictive value. The research highlights the potential of NLP algorithms in improving the efficiency and accuracy of cohort selection for research on diabetic retinopathy. [Extracted from the article]

A study conducted at Anhui University of Chinese Medicine focused on developing puerarin-loaded poly(lactic acid) microspheres for sustained ocular delivery to treat diabetic retinopathy, a common complication of diabetes leading to blindness. The research optimized the preparation of these microspheres and found that intravitreal injection of the microspheres significantly prolonged the half-life of puerarin in eye tissues, achieving sustained drug release. The study suggests that this method has positive implications for the treatment of diabetic retinopathy. [Extracted from the article]

A study conducted at Nitte (Deemed to be University) introduced a new Modified Regularisation Long Short-term Memory (MR-LSTM) framework for the diagnosis of Diabetic Retinopathy (DR). This framework utilizes deep learning to provide an accurate and efficient solution for early detection of DR, achieving an accuracy of 97.12 percent and an F1 Score of 98.49. The research aims to revolutionize DR diagnosis by offering timely and accessible solutions to combat vision-threatening conditions. [Extracted from the article]

University of Michigan researchers conducted a study on diabetic retinopathy, focusing on proliferative diabetic retinopathy (PDR) and its inflammatory pathways. The research involved single-cell transcriptomics of vitreous cells from patients with PDR, revealing a predominance of T cells and distinct immune cell proportions compared to peripheral blood. This study highlights the potential of liquid vitreous biopsies to provide insights into vitreoretinal diseases. [Extracted from the article]

The research conducted at the Indian Institute of Science in Karnataka, India, focuses on automated grading of Diabetic Retinopathy using Ultra-wide Optical Coherence Tomography Angiography scans. The study aims to develop a method for accurately grading the severity of Diabetic Retinopathy by analyzing vascular abnormalities on retinal images. The research findings suggest that radiomics analysis could be used for multimodal grading and further analysis of Diabetic Retinopathy, indicating its potential scope in this area. The study was funded by various organizations including the Wellcome Trust and the Science and Engineering Research Board in India. [Extracted from the article]

A patent application by inventors Dewi Harjanto and Wei Hsi Yeh focuses on prime editing methods and compositions for correcting mutations associated with USH2A-retinopathy, including non-syndromic retinitis pigmentosa and Usher syndrome. The application aims to address genetic disorders that lead to visual impairment and deaf-blindness by targeting mutations in the USH2A gene. The disclosed prime editing guide RNAs (PEgRNAs) and systems offer potential treatments for these conditions by correcting genetic alterations in the target gene. [Extracted from the article]

A patent has been issued for dendrimer compositions and methods for drug delivery to the eye by Ashvattha Therapeutics Inc. The invention aims to provide effective therapies for inflammatory and angiogenic diseases of the eye, such as age-related macular degeneration, diabetic retinopathy, and macular edema. The compositions deliver therapeutic agents selectively to activated microglial cells in the retina and choroid, targeting the underlying causes of retinal degenerative diseases. The method involves administering a composition comprising a dendrimer conjugated to receptor tyrosine kinase inhibitors to reduce the number or activity of activated microglia and macrophages in the eye. [Extracted from the article]

Researchers have submitted a patent application for methods to diagnose and treat ischemic eye disease, specifically focusing on proliferative diabetic retinopathy (PDR). The application includes a range of biomarkers that can be used for diagnosis, prognosis, and monitoring treatment of PDR. The methods involve obtaining vitreous samples from patients and measuring the expression levels of specific biomarkers to diagnose and treat PDR effectively. The patent application aims to provide innovative approaches to address the challenges associated with diabetic retinopathy, a leading cause of vision loss in adults. [Extracted from the article]

A recent study conducted by researchers from the University of Lisbon focused on retinopathy of prematurity (ROP), a retinal neovascular disease affecting preterm infants. The study analyzed the incidence of ROP and identified key risk factors for its development and progression, such as low gestational age and the number of red blood cell transfusions. The findings emphasize the importance of addressing these risk factors in ROP risk management and suggest further research is needed to explore preventive interventions. For more information, the full article can be accessed for free at the Children journal website. [Extracted from the article]

The article discusses a clinical trial, NCT06662448, focusing on the efficacy and feasibility of home-based repetitive transorbital alternating current stimulation (rtACS) for treating visual impairment in individuals with optic neuropathy. The study aims to assess the impact of rtACS on vision loss and functional independence. The trial involves various outcome measures, including changes in retinal nerve fiber layer thickness, visual field analyzer scores, and visual acuity scores, among others. The study is not yet recruiting participants and is set to be completed by May 18, 2029. [Extracted from the article]

The article discusses a clinical trial, NCT06664502, known as EYE-TIE-201, which aims to investigate the safety and effectiveness of a new drug called EYE201. The study consists of two parts: a multiple ascending dose safety study in participants with macular edema following branch retinal vein occlusion and a dose-finding safety and preliminary efficacy study in participants with either diabetic macular edema or neovascular age-related macular degeneration. The trial involves a total of 92 participants and is currently recruiting, with a completion date set for May 2026. [Extracted from the article]

Researchers at the University of Sherbrooke have focused on retinopathy of prematurity (ROP), a severe condition affecting premature infants. The study examines traditional treatments like cryotherapy and laser photocoagulation, as well as emerging nanotherapeutic strategies to improve ROP management. Nanotherapies show promise in offering targeted drug delivery with reduced side effects, potentially enhancing outcomes for premature infants with ROP. Further research is needed to confirm the efficacy and safety of these innovative approaches. [Extracted from the article]

A study conducted at Tianjin Medical University in China focused on the impact of intravitreal injections on controlling oxygen-induced retinopathy in mouse models. The research highlighted the importance of using specific needle sizes and timing intervals for injections to effectively manage retinopathy. The study emphasized the need for careful consideration of these factors to ensure successful outcomes in the model. The findings were published in the journal Experimental Eye Research and were peer-reviewed. [Extracted from the article]

A case report from Renmin Hospital of Wuhan University discusses a rare instance of Purtscher-like retinopathy (PLR) and paracentral acute middle maculopathy (PAMM) possibly linked to improper use of antihypertensive drugs in a 49-year-old male. The patient experienced vision loss and scotomas in one eye, with fundus examination revealing characteristic retinal abnormalities. After discontinuing the antihypertensive medication and receiving alternative treatments, the patient's vision improved, emphasizing the importance of proper medication use in clinical practice. This study contributes to understanding the etiology and pathophysiology of PLR and PAMM. [Extracted from the article]

A recent study conducted at Wenzhou Medical University in China compared the effectiveness of single-field versus multi-field fundus photography for screening and monitoring diabetic retinopathy in community settings. The research found that single-field fundus photography showed substantial agreement with multi-field grading in classifying diabetic retinopathy severity, with reduced sensitivity but reasonable effectiveness for detection. This study supports the use of single-field fundus photography to improve access to diabetic retinopathy detection in community care, although acknowledging its limitations compared to multi-field imaging. [Extracted from the article]

A study conducted at Hebrew University of Jerusalem examined the effects of glucagon-like-peptide-1 receptor agonists (GLP1-RAs) on diabetic retinopathy (DR) progression, visual acuity, central subfield thickness, and response to intravitreal injections (IVIs) in a cohort of patients. The study found that patients treated with GLP1-RA did not show significant differences in DR progression, visual acuity, or central subfield thickness compared to the control group. However, GLP1-RA therapy was not significantly associated with improved IVI response, with ocular parameters acting as confounding factors. [Extracted from the article]

A recent study conducted in Varna, Bulgaria, aimed to update data on the prevalence of Diabetic Retinopathy (DR) among diabetic patients in Northeastern Bulgaria. The study found that the overall prevalence of any DR was 39.9%, with higher rates in Type 1 diabetes patients compared to Type 2. The research highlights the importance of comprehensive national DR screening programs and proactive measures to prevent visual impairment and blindness. The findings provide valuable epidemiological insights for future research and emphasize the need for widespread screening, even in rural areas. [Extracted from the article]

Researchers from Symbiosis International (Deemed University) in Pune, India, have developed a new approach called Dunnock-Scheduler optimization-based Light GBM (DkSO-Light GBM) for the detection of Diabetic Retinopathy (DR) using multimodal image fusion. This method combines Optical Coherence Tomography Angiography (OCTA) images with fundus images to classify normal and abnormal retinas with high accuracy. The experimental outcomes show that the DkSO-Light GBM model outperforms conventional techniques in terms of accuracy, sensitivity, specificity, and other metrics, making it a promising tool for automated DR diagnosis. [Extracted from the article]

Researchers at the University of Johannesburg have developed a transparent diagnosis model for diabetic retinopathy using Explainable AI (XAI) to address the challenges of diverse symptoms and diagnostic difficulties associated with the disease. The XAI approach enhances interpretability of models, allowing clinicians to understand the reasoning behind decisions and improve diagnostic accuracy. The proposed model achieved a 94% better diagnostic accuracy than traditional methods, indicating potential for improved healthcare settings. The study was supported by the Research Fund from the University of Johannesburg and involved researchers from diverse backgrounds. [Extracted from the article]

A recent study conducted at Government Medical College focused on assessing the quality of life in patients with diabetic retinopathy after treatment with Anti-VEGF and laser photocoagulation. The study found that patients treated with Anti-VEGF therapy experienced better outcomes in certain quality of life domains compared to those treated with photocoagulation therapy. The research suggests that Anti-VEGF therapy may be a preferred treatment option for patients with diabetic retinopathy, especially those with diabetic macular edema requiring intervention. For more information, readers can refer to the International Journal of Scientific Research. [Extracted from the article]

Researchers from Kuwait University conducted a study on the effects of garlic extract on diabetic retinopathy in rats with streptozotocin-induced diabetes. The study found that rats treated with garlic extract showed improvements in retinal thickness, vascular density, artery diameter, and blood vessel numbers compared to untreated diabetic rats. The research suggests that garlic extract may be a beneficial dietary supplement for diabetic patients to manage and delay the progression of diabetic retinopathy. The study was published in the Journal of Functional Foods in 2024. [Extracted from the article]

The article discusses the impact of diabetes on eye health, specifically diabetic retinopathy, which can lead to blindness. The research highlights the increasing prevalence of diabetic retinopathy globally and the burden it places on medical services due to the long-term care required for affected patients. The study emphasizes the importance of early detection and management of diabetic retinopathy to prevent vision loss. [Extracted from the article]

A recent study conducted at the Second Hospital of Shandong University in China focused on identifying biomarkers related to neutrophil extracellular traps (NETs) in diabetic retinopathy (DR). The research found that five key genes, including CLIC3, GBP2, and P2RY12, were associated with DR, with HOXA1 and PSAP acting as protective factors. These findings offer new insights for clinical diagnosis and potential treatment strategies for DR. For more information, the full article can be accessed in Frontiers in Immunology. [Extracted from the article]

A recent report from the First Affiliated Hospital of Henan University of Science and Technology in China explores the predictive value of combining the serum TyG index, nesfatin-1, and retinol-binding protein 4 for diabetic retinopathy (DR) in patients with type 2 diabetes mellitus. The study found that the TyG index, nesfatin-1, and RBP4 levels were early predictive markers for DR and were associated with the risk and severity of the disease. The combination of these markers showed better predictive performance for DR, indicating their potential utility in early detection and management of DR in diabetic patients. [Extracted from the article]

Researchers at Hainan Medical University conducted a retrospective cohort study to investigate the impact of absolute changes in glycated hemoglobin A1c (HbA1c) on the risk of diabetic retinopathy (DR) in individuals with type 2 diabetes (T2D). The study involved 3,767 people with T2D without DR, and participants were grouped into four categories based on HbA1c absolute changes. The findings suggested that while HbA1c variability is a risk factor for DR, a significant reduction in HbA1c may be protective for individuals with very high baseline HbA1c. The research was funded by the National Natural Science Foundation of China and has been peer-reviewed. [Extracted from the article]

Researchers at Southwest State University conducted a study on the relationship between biological age and diabetic retinopathy in patients with type 2 diabetes mellitus. The study involved 580 patients aged 45-59 years, revealing that an accelerated biological age is a significant risk factor for diabetic retinopathy in this demographic. The findings suggest that biological age should be considered alongside other risk factors for diabetic retinopathy in patients with type 2 diabetes mellitus. [Extracted from the article]

A recent study conducted by researchers at the First Affiliated Hospital in Ningbo, China, explored the relationship between controlling nutritional status (CONUT) score and the risk of developing diabetic retinopathy (DR) in patients with diabetes. The study, which included 5,256 participants, found that higher CONUT scores were associated with an increased risk of DR development and all-cause mortality in patients with DR. While the study suggests that CONUT score may be a useful tool for assessing DR risk and predicting patient outcomes, it is important to note that the study was cross-sectional, and causality cannot be inferred. [Extracted from the article]

Researchers from the Harbin Institute of Technology in Shenzhen, China, have developed a deep convolutional neural network for detecting diabetic retinopathy, a common complication of diabetes that can lead to irreversible blindness. The network incorporates long-range dependence between lesion features in retinal fundus photographs to improve detection accuracy. Experimental results show that this approach outperforms existing models on datasets like Messidor and EyePACS. This study highlights the potential of machine learning and emerging technologies in the field of ophthalmology to enhance healthcare outcomes for individuals with diabetic retinopathy. [Extracted from the article]

Researchers at the University of Electronic Science and Technology of China conducted a study on the anti-ferroptotic effect of resveratrol on retinal Müller cells in the early stages of diabetic retinopathy. The research involved experiments on rats and mice treated with resveratrol, measuring changes in retinal neurofunction and cell viability. The study concluded that resveratrol could be a potential therapeutic option for diabetic retinopathy by regulating the Nrf2/GPx4/PTGS2 pathway. The findings were published in Molecular Neurobiology and have been peer-reviewed. [Extracted from the article]