Eye Disorders Research Articles

Automated Non-Supervised Eye Disorder Screening System Using Virtual Reality.

Neglecting eye disorders can lead to visual impairment or even vision loss, making early diagnosis and medical treatment crucial. This paper presents the development of an automated non-supervised eye disorder screening system that utilises Virtual Reality (VR) to provide a preliminary screening for common eye disorders. The system integrates advanced pupil-tracking techniques, image-processing methods, and eye disorder screening algorithms into one package for comprehensive eye disorder monitoring, including a strabismus test, a pupil test, and a contrast sensitivity test. Patients can wear a VR headset and use a joystick to interact with the VR scenario. The system is validated through experiments conducted on both healthy subjects and patients in hospitals, demonstrating an agreement rate exceeding 90% when compared to diagnoses by doctors. The test results highlight its potential for real-world applications, ultimately improving the accessibility of early screening for eye disorders and remote healthcare.

Detecting Conjunctival Hyperemia Using an Effective Machine Learning based Method

Among the many complex sensory organs, the human eye stands out. Prevention of eye illnesses is of the utmost importance since irreversible vision loss might result from postponed treatment. Therefore, to manage the continuous course of eye illnesses, early identification and monitoring are vital. Hyperemia, or redness, from increased blood flow, is one sign of conjunctivitis, an eye disorder defined by inflammation of the conjunctiva. Many illnesses and problems are often curable or significantly reducible with the help of the greatest medicines, sophisticated procedures, and early, accurate diagnosis by medical experts. Because there is a severe lack of diagnostic specialists, patients with vision difficulties are often not given the care they need because their conditions are not properly diagnosed. Segmentation approaches are crucial for detecting and quantifying hyperemic areas, which are necessary for diagnosing and evaluating conjunctivitis. This paper presents a very efficient machine learning framework for the detection of eye problems. The system does this by integrating segmentation approaches with feature extraction techniques. The use of the discrete cosine transform (DCT) generates feature vectors from the segmented regions of interest. Random forests and neural networks are two machine learning classifiers that are learned using feature vectors. This approach has a 96% success rate and has potential to assist ophthalmologists in assessing the severity of illnesses in objective and accurate manner. This strategy might be advantageous for adopting ICT-based solutions in public health systems in remote regions.

Optideneffnet: Deep Learning Framework For Retinal Diseases Prediction

The eye is the primary sensory organ involved in vision. Since some eye conditions might result in blindness, it is important to diagnose and treat them as soon as possible. In ophthalmic diagnostics, it is essential to identify various ocular illnesses from fundus images. On the other hand, subjectivity and mistake arise when ophthalmologists manually detect images. As a result, several automation techniques are developed, however they need to improve in terms of classification accuracy. This work proposes a novel multi-label automated Deep Learning (DL) prediction system called OptiDenEffNet, which can identify various retinal illnesses, as a solution for such challenges. The study begins with an extensive pre-processing step includes label encoding, data cleaning and normalization. The proposed OptiDenEffNet model, which combines many DL blocks, and the Attention Block, which act as feature descriptors, are then used to extract discriminative deep feature representations. Finally, a Discriminative Gated Recurrent Unit (DGRU), a highly developed prediction model is used. This DGRU can provide a probability distribution that precisely predict eye disorders on particular age by incorporating a Softmax layer to its architecture. Extensive tests are conducted on the challenging Ocular Disease Recognition Dataset using Python platform. The proposed model achieves the maximum accuracy of 98.269% and 99.691% in the 70:30 and 80:20 data splits respectively. The results specify that the proposed OptiDenEffNet model works better than state-of-the-art for predict retinal diseases.

Transformer-Enhanced Retinal Vessel Segmentation for Diabetic Retinopathy Detection Using Attention Mechanisms and Multi-Scale Fusion

Eye health has become a significant concern in recent years, given the rising prevalence of visual impairment resulting from various eye disorders and related factors. Global surveys suggest that approximately 2.2 billion individuals are visually impaired, with at least 1 billion affected by treatable diseases or ailments. Early detection, treatment, and screening for fundus diseases are crucial in addressing these challenges. In this study, we propose a novel segmentation model for retinal vascular delineation aimed at diagnosing diabetic retinopathy. The model integrates CBAM (Channel-Attention and Spatial-Attention) for enhanced feature representation, JPU (Joint Pyramid Upsampling) for multi-scale feature fusion, and transformer blocks for contextual understanding. Leveraging deep-learning techniques, our proposed model outperforms existing approaches in retinal vascular segmentation, like achieving a Mean IOU of 0.8047, Recall of 0.7254, Precision of 0.8492, F1 Score of 0.7824, and Specificity of 0.9892 for CHASEDB1 dataset. Extensive evaluations on benchmark datasets demonstrate its efficacy, highlighting its potential for automated diabetic retinopathy screening.

Ophthalmic Formulations for the Treatment of Allergic Conjunctivitis and Their Effect on the Ocular Surface: A Review of Safety and Tolerability Assessments in Clinical Trials.

Allergic conjunctivitis (AC) is the most common allergic eye disorder. Antiallergic eyedrops are the first line of pharmacological treatment. However, the application of antiallergic eyedrops can potentially alter tear homeostasis and affect the ocular surface, which may result in iatrogenic diseases such as dye eye disease (DED). Long-term treatment of AC with eyedrops containing preservatives and other components may increase the risk of DED and ocular surface damage. Here, we examined 20 clinical trials published during the past ten years with antihistamine ophthalmic formulations in the treatment of AC, to evaluate the extent of evidence about their safety and tolerability. Remarkably, we find that most trials lack an evaluation of the critical ocular surface parameters, such as tear film break-up time, tear volume, corneal and conjunctival damage, and inflammation, to properly assess the state of the ocular surface state after prolonged treatment. There is a need to increase awareness of the use of specific formulations that do not increase the risk of iatrogenic DED.

Emerging Ocular Side Effects of Immune Checkpoint Inhibitors: A Comprehensive Review.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, offering significant improvements in patient survival across various malignancies. However, their use is associated with a broad spectrum of immune-related adverse events (irAEs), including those affecting the eye and its surrounding structures, collectively termed ocular irAEs (OirAEs). Although rare, OirAEs (e.g., keratitis, uveitis, retinal vasculitis, etc.) can significantly impact a patient's quality of life, leading to ocular complications if left untreated. This review provides a comprehensive overview of OirAEs associated with ICIs, including their clinical manifestations, underlying mechanisms, and current management strategies. We delve into the anterior and posterior segment adverse events, highlighting conditions such as dry eye, uveitis, and retinal disorders, as well as neuro-ophthalmic and orbital complications. Furthermore, we discuss the challenges in diagnosing and treating these conditions, particularly given the overlap with other autoimmune and paraneoplastic syndromes. Finally, we identify key knowledge gaps and suggest future research directions aimed at optimizing the management of OirAEs while maintaining the efficacy of cancer therapy. This review underscores the need for increased awareness among clinicians to prevent irreversible ocular damage and enhance patient outcomes.

Sarvatantra Swatantra Kaikulangara Rama Varier - An illustrious polymath who enriched the Ayurveda literature

Abstract Kaikulangara Rama Varier (1832–1897) was one of the greatest Sanskrit scholars, Kerala had ever seen. He had a profound knowledge of Sanskrit, Ayurveda, Astrology, Vedanta, Yogabhyasa, Tarka, Vyakarana, and Music. With his extraordinary writing skills, even the toughest Sanskrit slokas were translated into Malayalam and made reader-friendly. His keen interest in popularizing Sanskrit language paved the way for translational works of Ayurveda. In the present study, the life profile of Kaikulangara Rama Varier is documented with the data collected through direct interviews with relatives, historians, and other published works. In Ayurveda, the literary works of Kaikulangara Rama Varier, which are commendable are Arogyaraksha-Kalpadruma, Bhavaprakasha and Sararthadarpana vyakhyana of Ashtanga Hridaya, Vaidya granthamala, and Vaidyamrita tarangini. The areas of panchakarma and management of eye disorders from his Ashtanga Hridaya commentaries were compiled and published separately as Panchakarma chikitsa and Netra chikitsa. Arogyaraksha-Kalpadruma expounds on various areas of pediatric practice right from birth, including the prevention and management of age-specific illness with many unique drug formulations that are successfully in practice even now. His recommendations on pediatric practices remain unparalleled and have made him more famous in Ayurveda. Over time, much of his works of literature got decayed. It is the need of the hour to preserve and explore these invaluable works, especially those related to Ayurveda, to sustain the knowledge and essence of this traditional science.

Parental Ability to Detect Visual or Ocular Anomalies in Their Children

INTRODUCTION: Children typically depend on their parents to seek eyecare. Visual and ocular disorders can be challenging for parents to identify with the absence of apparent symptoms. This may hinder timely clinical diagnosis for children who need treatment. Parental awareness regarding common paediatric eye and vision anomalies along with eye care seeking behaviour has been reported, but there is a lack of studies that demonstrate parental ability to identify a presenting eye or vision disorder in their own children. AIM: This study aimed to determine parental ability to recognise a significant eye problem in their children. METHODS: The study population consisted of beneficiaries of Jaber Al Ahmad Armed Forces Hospital in Kuwait. Structured history and symptoms were taken from parents and comprehensive eye examinations were conducted for their children. Parental responses were compared to the eye test results to attain the study purpose. RESULTS: A total of 188 parental interviews and 188 eye test results data were collected from 137 parents and their children. Only a few parents (18.1%) were able to detect significant visual or ocular anomalies in their children. One-third of the parents (33%) were under the assumption that the visual or ocular status of their children was within the norm, while the eye test results showed that the children had clinically significant issues. Overall, 41.5% of the entire group of parents were wrong in their assumption about the children’s visual or ocular status. CONCLUSION: The findings suggest that a large proportion of parents may not be able to identify a presenting eye disorder in their children. This emphasises the significance of routine eye examinations at an early age.

Reactive Oxygen Species Responsive Supramolecular Prodrug Eyedrops for the Treatment of Choroidal Neovascularization.

Choroidal neovascularization (CNV) represents a hallmark of neovascular fundus diseases, including age-related macular degeneration and diabetic retinopathy. Traditional eyedrops have encountered formidable challenges in treating CNV, primarily due to their extremely poor intraocular bioavailability and potential adverse off-target effects. Herein, an ocular-permeable supramolecular prodrug eyedrop (Di-DAS/P-PCD) has been developed for the on-demand delivery of antiangiogenic agents in the oxidative microenvironment of CNV. The eyedrop nanoformulation is composed of cell-penetrating peptide-modified PEGylated cyclodextrin (P-PCD) and reactive oxygen species (ROS)-sensitive antiangiogenic dasatinib prodrug Di-DAS. In a laser-induced CNV mouse model, daily instillation of Di-DAS/P-PCD has achieved remarkable penetration into the choroid and significantly suppressed CNV growth while exhibiting a good biocompatibility profile. Our results highlight the potential of the supramolecular prodrug eyedrops as a versatile approach for the targeted treatment of CNV and other neovascular eye disorders.

Deletion upstream of MAB21L2 highlights the importance of evolutionarily conserved non-coding sequences for eye development

Anophthalmia, microphthalmia and coloboma (AMC) comprise a spectrum of developmental eye disorders, accounting for approximately 20% of childhood visual impairment. While non-coding regulatory sequences are increasingly recognised as contributing to disease burden, characterising their impact on gene function and phenotype remains challenging. Furthermore, little is known of the nature and extent of their contribution to AMC phenotypes. We report two families with variants in or near MAB21L2, a gene where genetic variants are known to cause AMC in humans and animal models. The first proband, presenting with microphthalmia and coloboma, has a likely pathogenic missense variant (c.338 G > C; p.[Trp113Ser]), segregating within the family. The second individual, presenting with microphthalmia, carries an ~ 113.5 kb homozygous deletion 19.38 kb upstream of MAB21L2. Modelling of the deletion results in transient small lens and coloboma as well as midbrain anomalies in zebrafish, and microphthalmia and coloboma in Xenopus tropicalis. Using conservation analysis, we identify 15 non-coding conserved elements (CEs) within the deleted region, while ChIP-seq data from mouse embryonic stem cells demonstrates that two of these (CE13 and 14) bind Otx2, a protein with an established role in eye development. Targeted disruption of CE14 in Xenopus tropicalis recapitulates an ocular coloboma phenotype, supporting its role in eye development. Together, our data provides insights into regulatory mechanisms underlying eye development and highlights the importance of non-coding sequences as a source of genetic diagnoses in AMC.

Adverse events associated with parenteral nutrition support therapy: A pharmacovigilance study.

Parenteral nutrition (PN) plays a crucial role in nutrition support therapy, yet data on related adverse events (AEs) in practical settings are scarce. To address this, we analyzed AE signals associated with PN treatment from the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database. We extracted data from the FAERS database, covering the period from the first quarter (Q1) of 2004 to Q1 of 2024. Drug names and AEs were standardized. We then conducted disproportionality analyses using four different algorithms to evaluate the association between PN and its associated AEs. We collected a total of 48,890,925 reports from the FAERS database, of which 1642 involved PN-related AEs. After categorization, we identified 21 system organ classes (SOCs), and hepatobiliary disorders were the only significant SOC across all four algorithms. At the preferred term (PT) level, we identified 99 PTs that showed significant disproportionality in all four algorithms. Fat overload syndrome, fatty acid deficiency, parenteral nutrition-associated liver disease (PNALD), Malassezia infection, and Pantoea agglomerans infection were the most prominent PTs. In addition, several potential new AE signals included nervous, cardiac, immune, psychiatric, blood, renal, urinary, and eye disorders. Our study identified several common and rare PN-related AEs reported in the FAERS database. Patients and healthcare providers should remain vigilant about these AEs. Understanding the risks of PN therapy and establishing practical procedures can help reduce AEs.

Keratoconus.

Keratoconus is a progressive eye disorder primarily affecting individuals in adolescence and early adulthood. The ectatic changes in the cornea cause thinning and cone-like steepening leading to irregular astigmatism and reduced vision. Keratoconus is a complex disorder with a multifaceted aetiology and pathogenesis, including genetic, environmental, biomechanical and cellular factors. Environmental factors, such as eye rubbing, UV light exposure and contact lens wearing, are associated with disease progression. On the cellular level, a complex interplay of hormonal changes, alterations in enzymatic activity that modify extracellular membrane stiffness, and changes in biochemical and biomechanical signalling pathways disrupt collagen cross-linking within the stroma, contributing to structural integrity loss and distortion of normal corneal anatomy. Clinically, keratoconus is diagnosed through clinical examination and corneal imaging. Advanced imaging platforms have improved the detection of keratoconus, facilitating early diagnosis and monitoring of disease progression. Treatment strategies for keratoconus are tailored to disease severity and progression. In early stages, vision correction with glasses or soft contact lenses may suffice. As the condition advances, rigid gas-permeable contact lenses or scleral lenses are prescribed. Corneal cross-linking has emerged as a pivotal treatment aimed at halting the progression of corneal ectasia. In patients with keratoconus with scarring or contact lens intolerance, surgical interventions are performed.

Uncovering genetic loci and biological pathways associated with age-related cataracts through GWAS meta-analysis

Age-related cataracts is a highly prevalent eye disorder that results in the clouding of the crystalline lens and is one of the leading causes of visual impairment and blindness. The disease is influenced by multiple factors including genetics, prolonged exposure to ultraviolet radiation, and a history of diabetes. However, the extent to which each of these factors contributes to the development of cataracts remains unclear. Our study identified 101 independent genome-wide significant loci, 57 of which are novel. We identified multiple genes and biological pathways associated with the cataracts, including four drug-gene interactions. Our results suggest a causal association between type 1 diabetes and cataracts. Also, we highlighted a surrogate measure of UV light exposure as a marker of cataract risk in adults.

Effect of Honey in Eye Disease

Honey is regarded as a therapeutical agent due to its antibacterial and inflammatory remedial or medicational characteristics; its successful use in the treatment of non-healing infected wounds has pushed its wider clinical employment for treating different ailments, including eye disorders. The honey is commonly used to treat bullous keratopathy, postoperative corneal edema, and dry eye illness. It can be used as an anti-inflammatory and antibacterial medication to treat eye problems. The role and Impact of honey in eye disease are clarified in this review.

“You Should Get That Checked Out”: An Exploratory Analysis of Health-Related Discussions on Reddit

Abstract Introduction/Objective Social media has become a widely-used way for people to share opinions about healthcare and medical topics. Social media data can be leveraged to understand patient concerns and provide insight into why patients may turn to an internet forum, rather than the healthcare system, for health advice. Data collected on users’ questions and discussions can be used to better manage healthcare resources, including laboratory tests. We aimed to investigate Reddit posts discussing medical conditions and characterize their implications. Methods/Case Report We collected one year of Reddit posts containing the phrases “get tested” and “get checked.” An initial selection of posts was manually read by the authors to categorize the issues discussed in the posts into conditions. An automated script was then developed to assign additional posts to conditions, based on keywords. Condition assignment was performed on the entire one-year Reddit dataset. Related conditions were grouped into broader medical topics. Analysis of the condition assignments was then performed to assess condition and medical topic frequencies in medical condition-focused subreddits and general (non-medical-focused) subreddits. Results (if a Case Study enter NA) Among all conditions, STIs, eye disorders, anxiety, and pregnancy had the highest post frequency. Of the broader medical topics, the most frequent were psychiatry and mental health; genitourinary and reproductive health; infectious disease; and endocrinology, nutrition, and metabolism. Overall, conditions that appeared most frequently as a top-five condition in general subreddits included addiction and drug use, ADHD, abuse, and STIs. These conditions may be associated with fear of stigmatization. Conclusion Overall, we find that health discussions center on certain topics on Reddit. These topics may represent areas where people feel more comfortable discussing their health online, and where the healthcare system could focus additional outreach and resources. They may also shed light on how laboratory tests can be best managed.

Advancements in Ocular Therapy: A Review of Emerging Drug Delivery Approaches and Pharmaceutical Technologies

Eye disorders affect a substantial portion of the global population, yet the availability of efficacious ophthalmic drug products remains limited. This can be partly ascribed to a number of factors: (1) inadequate understanding of physiological barriers, treatment strategies, drug and polymer properties, and delivery systems; (2) challenges in effectively delivering drugs to the anterior and posterior segments of the eye due to anatomical and physiological constraints; and (3) manufacturing and regulatory hurdles in ocular drug product development. The present review discusses innovative ocular delivery and treatments, encompassing implants, liposomes, nanoparticles, nanomicelles, microparticles, iontophoresis, in situ gels, contact lenses, microneedles, hydrogels, bispecific antibodies, and gene delivery strategies. Furthermore, this review also introduces advanced manufacturing technologies such as 3D printing and hot-melt extrusion (HME), aimed at improving bioavailability, reducing therapeutic dosages and side effects, facilitating the design of personalized ophthalmic dosage forms, as well as enhancing patient compliance. This comprehensive review lastly offers insights into digital healthcare, market trends, and industry and regulatory perspectives pertaining to ocular product development.

TdCoxSNN: Time-dependent Cox survival neural network for continuous-time dynamic prediction

Abstract The aim of dynamic prediction is to provide individualized risk predictions over time, which are updated as new data become available. In pursuit of constructing a dynamic prediction model for a progressive eye disorder, age-related macular degeneration (AMD), we propose a time-dependent Cox survival neural network (tdCoxSNN) to predict its progression using longitudinal fundus images. tdCoxSNN builds upon the time-dependent Cox model by utilizing a neural network to capture the nonlinear effect of time-dependent covariates on the survival outcome. Moreover, by concurrently integrating a convolutional neural network with the survival network, tdCoxSNN can directly take longitudinal images as input. We evaluate and compare our proposed method with joint modelling and landmarking approaches through extensive simulations. We applied the proposed approach to two real datasets. One is a large AMD study, the Age-Related Eye Disease Study, in which more than 50,000 fundus images were captured over a period of 12 years for more than 4,000 participants. Another is a public dataset of the primary biliary cirrhosis disease, where multiple laboratory tests were longitudinally collected to predict the time-to-liver transplant. Our approach demonstrates commendable predictive performance in both simulation studies and the analysis of the two real datasets.

Safety Profiles Related to Dosing Errors of Rapid-Acting Insulin Analogs: A Comparative Analysis Using the EudraVigilance Database.

Diabetes is a widespread condition that can lead to multiple and severe complications. Rapid-acting insulin analogs (RAIAs) and long-acting insulin analogs are prescribed for the effective management of diabetes. RAIAs are expected to be associated with a higher number of dosing errors because of their rapid onset, short duration of action, and the need for frequent dosing, compared to other insulin analogs. There are three approved RAIAs on the market: insulin lispro (LIS), insulin aspart (ASP), and insulin glulisine (GLU). The aim of this study is to evaluate the real-world evidence on dosing errors reported for RAIAs in EudraVigilance (EV), an established pharmacovigilance database, in comparison to other insulin analogs and human insulins. A descriptive analysis and a disproportionality analysis were conducted. ASP and LIS were associated with high percentages of adverse drug reactions (ADRs) (22% and 17%, respectively), with over 70% of the reports involving serious ADRs. A higher frequency of cardiac and eye disorder ADRs was observed for LIS compared with ASP and GLU. GLU showed a higher frequency of ADRs in the skin and subcutaneous tissue disorders category. LIS dosing errors accounted for 5% of the total number of cases, while dosing errors for ASP and GLU were less than 3%. The most frequently reported dosing errors involved improper dosing (49%). Although there were fewer dosing errors of RAIAs in comparison to other insulins, the severity of the potential outcome highlights the importance of precise dosing and timing. Improved the monitoring and reporting of these dosing errors could enhance diabetes patient care. Additionally, smart medical devices could improve therapeutic outcomes.

Studies on identification of Garudapacha - An unfamiliar raw material used in Ayurveda formulations

Introduction: The raw drugs of mineral and metallic origin are exclusively classified into different groups. There are around 70 minerals and metals described in Rasashastra. There is a rare mineral called Garudapacha used in Kerala state of India, the details of which are scarce or rather not available. It is called as veluthagarudapacha, Palgarudapacha in Malayalam language and palgarudakallu, palgaruda and garudakallu in Tamil. A brief account of shodhana and marana is also mentioned for this mineral drug. The bhasma of Garudapacha is indicated in the conditions like asthisrava (leucorrhea), netraroga (Eye disorders), asthishosha (osteoporosis) and mutrakrichra (dysuria). Materials and methods: An attempt was made in this work to collect the samples of Garudapacha from different districts of Kerala. Collected sample was examined through selected physical properties of minerals. The sample was also analysed using Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM EDS). Results: Two samples of Garudapacha could be collected one each from Palakkad and Thiruvananthapuram districts of Kerala state. On examination the sample was massive, compact, brittle, translucent to opaque, white stone, with white streak, Pearly to dull luster, flat to conchoidal fracture, 2.5 to 3.5 Hardness and 2.9 to 3 specific gravity. SEM EDS analysis showed presence of magnesium, carbon, calcium and silica. Discussion and conclusion: From the physical appearance and other mineralogical features the collected sample was identified as Magnesite a carbonate of magnesium with a chemical composition of MgCO3. It was further affirmed while the sample was subjected to instrumental analysis. There was presence of magnesium, carbon and silica among which 28.74% magnesium and 6.89 % was carbon.

Emc1 is essential for vision and zebrafish photoreceptor outer segment morphogenesis.

Inherited retinal diseases (IRDs) are a rare group of eye disorders characterized by progressive dysfunction and degeneration of retinal cells. In this study, we characterized the raifteirí (raf) zebrafish, a novel model of inherited blindness, identified through an unbiased ENU mutagenesis screen. A mutation in the largest subunit of the endoplasmic reticulum membrane protein complex, emc1 was subsequently identified as the causative raf mutation. We sought to elucidate the cellular and molecular phenotypes in the emc1-/- knockout model and explore the association of emc1 with retinal degeneration. Visual behavior and retinal electrophysiology assays demonstrated that emc1-/- mutants had severe visual impairments. Retinal histology and morphometric analysis revealed extensive abnormalities, including thinning of the photoreceptor layer, in addition to large gaps surrounding the lens. Notably, photoreceptor outer segments were drastically smaller, outer segment protein expression was altered and hyaloid vasculature development was disrupted. Transcriptomic profiling identified cone and rod-specific phototransduction genes significantly downregulated by loss of emc1. These data shed light on why emc1 is a causative gene in inherited retinal disease and how outer segment morphogenesis is regulated.