Background: Primary Sjögren’s syndrome (pSS) related dry eye disease (DED) is severe and treatment-resistant. Beyond lacrimal gland involvement, whether pSS as a systemic autoimmune disease affects other parts maintaining ocular surface homeostasis, including the meibomian gland and conjunctiva is not yet clear. Methods: Fresh eyelids from the pSS model and control mice were prepared for single-cell RNA sequencing. Immunofluorescence and multiplex immunohistochemistry were applied to detect expression of selected proteins in specific areas. MGD signs were evaluated via gland imaging, Oil Red O and LipidTox staining. Findings: The pSS model presented DED and MGD phenotypes, including corneal defects, meibomian gland atrophy and abnormal lipid metabolism and secretion. Upregulation of Wnt/β-catenin signaling was a key trait in clusters with high genetic risks of SS, with differentiating meibocytes and ductal suprabasal epithelia mainly involved. Hair follicle matrix served as the major source of Wnt ligands. Specifically, Wnt/β-catenin signaling was associated with upregulation of lipid catabolic process in the acini and epidermis development in the duct driven by Tcf7l1 and Tcf7l2 respectively. Inhibiting Wnt/β-catenin signaling with LGK974 reversed these pathologies and alleviated MGD and DED in pSS mice Interpretation: In pSS mice eyelids, hair follicle-initiated Wnt/β-catenin signaling drives abnormal acinar lipid metabolism and ductal keratinization through Tcf7l1 and Tcf7l2 mediated network. Blockage of Wnt/β-catenin signaling through LGK974 successfully alleviates these abnormalities and serves as a potent therapeutic approach.

Dry eye disease is a prevalent ocular surface disorder primarily driven by oxidative stress and inflammation, remains a therapeutic challenge due to the limitations of current treatments. In this study, we developed a multifunctional nanoparticle system, using a layer-by-layer self-assembly strategy to enhance the delivery and efficacy of a natural antioxidant, proanthocyanidin (PC). The nanocomplex consists of a caseinate-proanthocyanidin core, further modified with chitosan-triphenylphosphonium (CS-TPP) for mitochondrial targeting and coated with hyaluronic acid (HA) to prolong ocular surface retention. In vitro and in vivo studies demonstrated that PC-Casein/CS-TPP/HA (CCH@PC) effectively scavenges reactive oxygen species with an elimination efficiency of up to 70%, protects mitochondrial function, and significantly extends corneal residence time compared to conventional eye drops. Moreover, in a murine model of dry eye, CCH@PC markedly alleviated clinical symptoms, effectively promotes the tear secretion of the dry eye model mice, increasing from 2.20 mm to 5.06 mm, suppressed inflammatory responses, and promoted corneal epithelial repair. These findings highlight the potential of CCH@PC as a targeted, sustained, and multifunctional nanotherapeutic platform for treating dry eye disease and other oxidative stress-related ocular pathologies.

To evaluate changes in ocular, psychological, and opticortical parameters following VR/AR movie exposure. Observational cohort study. Fifty-five healthy adults (17 males, 38 females; age range 19–39 years; mean age 26.1 ± 4.2 years) watched VR/AR movies for 30 min. Visual function assessments included best-corrected visual acuity (BCVA), intraocular pressure (IOP), tear film breakup time (BUT), contrast sensitivity function (CSF), stereopsis, eye position, and the accommodative convergence to accommodation (AC/A) ratio. Electroencephalography (EEG) was recorded during both resting and task states. Psychological assessments included measures of visual fatigue, arousal, affective state (PANAS), emotion, and anxiety. No significant changes were observed in IOP, BUT, phoria at 3–40 cm, accommodative response, AC/A ratio, AULCSF, or stereopsis. Both VR and AR exposure led to increased visual fatigue, decreased shyness, and elevated anxiety. EEG recordings showed significant reductions in resting-state alpha wave activity. Increases in visual fatigue were positively correlated with P300 peak latency shifts, which were also associated with increased anxiety. Shyness score reductions were negatively correlated with alpha wave changes. A visual health model was developed. However, its variables were not significantly associated with visual health outcomes (P > 0.05), indicating a lack of independent predictive value. A 30-minute exposure to VR/AR movies does not significantly impair tear film stability, accommodation, or stereopsis. However, it induces measurable changes in EEG, including altered alpha-wave activity and P300 latency, which are associated with visual fatigue. The visual impact of VR/AR may depend on content features and system design. An integrative visual health model that combines subjective symptoms, ocular metrics, and EEG features was established, providing a preliminary framework for comprehensive visual health assessment. Trial registration: Registered at https://clinicaltrials.gov/ NCT04530773; on August 2, 2022.

PURPOSE:To develop and evaluate a machine learning (ML) model to predict postoperative vault and residual refractive error following Implantable Collamer Lens (ICL) implantation by incorporating corneal functional parameters, and to investigate their influence on prediction accuracy. METHODS:This study included 282 eyes implanted with ICLs from 142 patients. A Marine Predators Algorithm combined with a support vector machine (MPA-SVM) for feature selection and optimal modeling was trained to predict postoperative vault residual refractive error using preoperative ocular parameters, with and without corneal functional parameters, including tear film quality and corneal endothelium metrics. Model performance was compared using mean absolute error (MAE), median absolute error (MedAE), R-squared (R2), and Wilcoxon signed-rank tests. RESULTS:Corneal endothelium metrics significantly improved MPA-SVM performance in vault prediction (P < .05), achieving lower MAE (138.55) and MedAE (110.41) and higher R2 (0.26) and prediction accuracy. For refractive error prediction, combining tear film quality, endothelium metrics, and other ocular parameters yielded the best results for cylinder (MAE = 0.38; MedAE = 0.32; R2 = 0.19), significantly outperforming models using only ocular parameters (P < .05). Endothelium metrics also improved sphere prediction, with numerically lower MedAE and a higher percentage of prediction errors within ±0.25, ±0.50, and ±0.75 diopters. CONCLUSIONS:In the MPA-SVM ICL prediction model, corneal endothelium metrics significantly improves vault prediction and, when combined with tear film quality parameters, enhances cylinder prediction after ICL implantation. This enhanced model offers ophthalmologists a valuable tool for improving the safety and planning of ICL procedures.

Purpose:The purpose of this study was to delineate retinal vessel hemodynamics across myopia severity using high-resolution adaptive optics scanning laser ophthalmoscopy (AOSLO) and investigate their correlation with fundus structure. Methods:In this cross-section study, hemodynamics in intraocular branches of the central retinal artery and vein from 124 participants, including flow velocity, volumetric flow, wall shear stress (WSS), and the wall to lumen ratio (WLR) were derived from AOSLO. Associations of axial length (AL) with these parameters were evaluated, with adjustment for vessel diameter (VD) and other confounders. Partial correlation analysis assessed relationships between hemodynamics and fundus structures, including capillary density and fundus thickness. Results:Arterial flow velocity and WSS demonstrated a biphasic relationship with longer AL: velocity increased up to 25.13 mm (β = 1.66) and then decreased (β = -2.17), whereas WSS increased up to 24.98 mm (β = 7.53) before declining (β = -17.15). Conversely, venous flow velocity (β = -0.95) and WSS (β = -7.78) progressively declined with increasing AL. After adjustment for confounders, longer AL was associated with increasing WLR in arteries (β = 0.83) and veins (β = 0.58), alongside decreased volumetric flow (artery: β = -0.14 and vein: β = -0.09). Increased WLR showed the strongest correlation with fundus structural changes, including reduced nasal retinal capillary density (ρ = -0.36) and choroid thinning (ρ = -0.44). Conclusions:This study conducted a detailed assessment of the hemodynamics of retinal vessels at different levels of myopia with AOSLO, revealing severity-dependent alterations characterized by elevated vascular resistance, reduced retinal perfusion, and biphasic arterial response. These hemodynamic alterations were closely correlated with fundus structural changes, suggesting vascular dysregulation may be a contributing factor to the pathophysiological changes associated with increasing severity of myopia.

Optical coherence tomography (OCT) has revolutionized retinal disease diagnosis with its high-resolution and three-dimensional imaging nature, yet its full diagnostic automation in clinical practices remains constrained by multi-stage workflows and conventional single-slice, single-task AI models. We present Full-process OCT-based Clinical Utility System (FOCUS), a foundation model-driven framework enabling end-to-end automation of 3D OCT retinal disease diagnosis. FOCUS sequentially performs image quality assessment with EfficientNetV2-S, followed by abnormality detection and multi-disease classification using a fine-tuned Vision Foundation Model. Crucially, FOCUS leverages a unified adaptive aggregation method to intelligently integrate 2D slice-level predictions into comprehensive 3D patient-level diagnosis. Trained and tested on 3300 patients (40,672 slices), and externally validated on 1345 patients (18,498 slices) across four different-tier centers and diverse OCT devices, FOCUS achieved high F1-scores for quality assessment (99.01%), abnormally detection (97.46%), and patient-level diagnosis (94.39%). Real-world validation across centers also showed stable performance (F1: 90.22–95.24%). In human-machine comparisons, FOCUS matched expert performance in abnormality detection (F1: 95.47% vs 90.91%) and multi-disease diagnosis (F1: 93.49% vs 91.35%), while demonstrating better efficiency. FOCUS automates the image-to-diagnosis pipeline, representing a critical advance towards unmanned ophthalmology with a validated blueprint for autonomous screening to enhance population scale retinal care accessibility and efficiency.

AIMS:Vascular endothelial growth factor (VEGF) drives corneal neovascularization (CorNV), yet no anti-VEGF eye drops are clinically available. We report phase I/IIa trials of KH906, a novel topical anti-VEGF agent. METHODS:Trial 1 was a phase I, open-label, dose-escalation study in healthy adults receiving KH906 at 0.1, 0.5, or 1.0 mg/mL. Trial 2 was a phase I, multicentre, open-label, dose-escalation study in patients with CorNV at the same doses. Trial 3 was a phase IIa, randomized, double-masked, placebo-controlled study assigning patients 1:1:1 to 0.5 mg/mL KH906, 1.0 mg/mL KH906, or placebo. Primary endpoints were safety, tolerability and pharmacokinetics (Trials 1 and 2) and safety, tolerability and efficacy (Trial 3). RESULTS:From 10 December 2018 to 16 June 2021, 18 healthy participants and 39 patients with CorNV were enrolled. One treatment-related adverse event occurred: a mild corneal epithelial defect in the 1.0-mg/mL group in Trial 3. No serious or other drug-related adverse events were observed. In Trial 2, KH906 reduced the CorNV area and vessel length. In Trial 3, at Day 28, mean changes in CorNV area were -1.2 (0.8), -1.6 (1.1) and -0.7 (1.1), and mean changes in CorNV length were -8.0 (7.3), -6.6 (5.9) and -1.7 (7.9), in the 0.5-mg/mL KH906, 1.0-mg/mL KH906 and placebo groups, respectively. The 1.0-mg/mL dose produced greater reduction of the CorNV area than lower doses, indicating a dose-response effect. CONCLUSIONS:KH906 appears safe and well tolerated and demonstrates preliminary efficacy in reducing CorNV, with higher doses showing greater effect, supporting further clinical development.

Choroidal melanoma is a prevalent intraocular malignant tumor with high mortality rate and liver metastases, related to the lack of sensitive and noninvasive therapeutic modalities. To address the imaging diagnostics and therapeutic predicaments for choroidal melanoma, a novel nanoplatform is developed through the integration of an aggregation-induced emission photosensitizer with two-dimensional MXene nanosheets (MX@PEG-MeoTTPy). This nanoplatform simultaneously exhibits distinctive properties and multiple functions including exceptional biocompatibility, efficient type I reactive oxygen species generation, high-quality fluorescence bioimaging, mild near-infrared (NIR) photothermal performance and superior cellular uptake. Furthermore, a thermosensitive hydrogel composite is engineered to encapsulate the nanosheets, enabling controlled and sustained release over 72 h via NIR irradiation and tumor microenvironment-induced gel–sol transition. The nanoplatform leverages synergistic mild photothermal therapy and photodynamic therapy, leading to precise and sustained tumor ablation through pyroptosis-mediated cell death. Both in vitro and in vivo studies validate that the nanosystem serves as an effective theranostic agent for dual-modal imaging-guided synergistic therapy, offering a multifaceted therapeutic strategy for intraocular tumors and showing significant potential for clinical application in choroidal melanoma therapy.

Repairing corneal stromal defects remains a significant clinical challenge. While hydrogels have been explored for corneal injury repair, their structural and compositional dissimilarity to natural corneal tissue has limited their potential as a viable alternative to corneal transplantation. In this study, a decellularized corneal hydrogel system (HCSL) was developed to address these limitations. The HCSL integrates decellularized corneal stromal lenticules, gelatin methacrylate (GelMA), and oxidized dextran (Odex) to create a composite decellularized corneal hydrogel with superior mechanical strength, adhesion, and biocompatibility. This hydrogel offers exceptional optical transparency and mechanical properties tailored for tissue repair. The fabrication process involves decellularizing corneal lenticules and embedding them within a hydrogel matrix composed of GelMA and Odex, which is then photo-cross-linked under visible blue light. The resulting hydrogel exhibits robust enzymatic resistance, minimal swelling, and high adhesion strength. In vitro studies demonstrated that the HCSL hydrogel promotes cell proliferation and preserves the phenotype of corneal stromal cells, confirming its biocompatibility. Additionally, the hydrogel effectively reduces scar formation during the healing process. In vivo experiments using rabbit models of corneal injury revealed that HCSL significantly accelerated epithelialization, enhanced corneal transparency, and minimized scar formation compared to control treatments. Histological analysis confirmed the successful repair of corneal defects, with well-organized epithelial and stromal layers and no significant inflammatory response or neovascularization. These findings underscore the potential of the HCSL hydrogel as a promising alternative to corneal transplantation for treating corneal injuries. Its unique combination of structural mimicry, mechanical properties, and biological activity positions it as a strong candidate for clinical application in corneal repair and regeneration.

PURPOSE. Dry eye disease (DED) is characterized by progressive corneal epithelial damage and chronic inflammation, yet the specific cell death mechanisms underlying epithelial loss remain unclear. This study investigated the role of RIPK3-mediated necroptosis in corneal epithelial injury and inflammation in DED. METHODS. A DED murine model was established using scopolamine hydrobromide and desiccative stress. Corneal damage was assessed via fluorescein staining, SEM, and TEM. Molecular mechanisms were explored through RNA-sequencing, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis. The pathogenic role of RIPK3 and NLRP3 was validated using knockout (RIPK3-/-, NLRP3-/-), AAV-mediated overexpression, and siRNA knockdown. The therapeutic potential of the necroptosis inhibitor Necrostatin-1 was evaluated in vivo. RESULTS. RNA-sequencing and KEGG analysis identified the TNF signaling pathway and necroptosis markers (RIPK3, MLKL) were significantly upregulated in DED corneal epithelium. RIPK3 knockdown markedly alleviated corneal epithelial damage and cell death, whereas localized RIPK3 overexpression exacerbated epithelial injury and inflammatory responses. Mechanistically, SQSTM1 act as a critical downstream mediator of RIPK3, promoting MLKL activation and necroptosis independently of canonical autophagic flux. Further analyses demonstrated that the RIPK3-SQSTM1 axis directly amplified NLRP3 inflammasome activation, thereby linking epithelial cell death to sustained inflammatory signaling. Consistently, desiccative stress induced rapid and persistent RIPK3-MLKL activation in human corneal epithelial cells, whereas Necrostatin-1 preserved corneal epithelial integrity and suppressed inflammasome activation in vivo. CONCLUSIONS. This study identifies a RIPK3-SQSTM1-NLRP3 signaling axis as a key driver of corneal epithelial damage and inflammation in DED. These findings provide mechanistic insight into ocular surface epithelial loss and highlight necroptosis as a promising therapeutic target for DED.

Background:Dry eye disease (DED) is a common chronic eye disease with a high prevalence, and the imbalance of the tear film is a core characteristic of its pathogenesis. The time that is required for the tear film to break and form a dry spot after eye opening is known as the fluorescein breakup time (FBUT). FBUT is a standard clinical test for DED diagnosis. Currently, most DED diagnoses rely on FBUT test image acquisition devices and manual timing judgments, which are subjective, complex, and difficult. Additionally, computer-aided detection techniques face challenges in feature recognition, accuracy (ACC), and real-time, fully automated detection. Therefore, the automated recognition of dry eye based on deep learning analysis of fluorescein tear film breakup videos has become an important research direction. The objective of this study was to develop a system using a deep learning model to automatically detect DED from fluorescein tear film breakup videos. Methods:We constructed a fluorescein tear film video dataset with 148 DED cases and 100 non-DED cases based on clinical evaluations, and a segment dataset included 2,543 video frames with annotated tear film regions. Based on this, we proposed a fully automated method for DED detection with multidimensional temporal features of tear film as input. First, we used the multi-attention segmentation network (MASN) to segment the tear film region. Then, the tear film percentage curve in the video was used to calculate the fully open eye threshold, which determines the consecutive frames for further analysis. Subsequently, we constructed an efficient network to compress the morphological features in the tear film region and used PyRadiomics to extract the texture features from the tear film region. Finally, the cross-attention transformer classification network (CATCN) was used to detect the DED, which fused the temporal and spatial features from two different perspectives. Results:The segmentation results of the tear film region achieved an ACC of 0.97, a sensitivity (SE) of 0.82, and an area under the curve (AUC) of 0.98. The DED detection method was then tested on our datasets, achieving an ACC of 0.92, an SE of 0.86, and an AUC of 0.96. Conclusions:The fully automated dry eye detection system achieves excellent detection performance through precise tear film segmentation and multi-view tear film feature fusion recognition. It offers a convenient new method for large-scale screening of DED.

Intermittent fasting (IF) has emerged as a promising immunometabolic intervention, yet its therapeutic value in Sjögren's syndrome (SS)-related dry eye remains unclear. In this study, IF robustly improved tear secretion and corneal integrity in SS mice and markedly reshaped the gut ecosystem. Integrated 16S rRNA sequencing and fecal metabolomics identified Akkermansia muciniphila and bile acids as key responders to IF, and oral supplementation with either Akkermansia or ursodeoxycholic acid effectively recapitulated IF's therapeutic benefits. Single-cell and bulk transcriptomic profiling, together with flow cytometry, revealed extensive remodeling of the lacrimal gland immune microenvironment, characterized by reduced pro-inflammatory Th17 infiltration and the emergence of anti-inflammatory CD8+ effector populations. These findings demonstrate that IF alleviates SS-related dry eye through coordinated regulation of gut microbiota, gut metabolism, and local autoimmune responses. By establishing a healthier gut milieu and rebalancing lacrimal gland immunity, IF represents a safe, system-level strategy with translational potential for long-term management of SS-associated dry eye.

PURPOSE:To compare associations of BMI, total body fat percentage, and fat distribution with dry eye disease (DED) and assess metabolites mediation. DESIGN:Retrospective cross-sectional study. METHODS:This retrospective cross-sectional study included 483,115 UK Biobank participants (14,570 with DED and 468,545 without DED). Adiposity was assessed by baseline anthropometry and bioelectrical impedance, and DED was identified using primary care Read codes, self-reports, and medication records. Multivariable logistic regression adjusted for demographic, metabolic, medication, and lifestyle factors. Sex-specific exploratory mediation analyses evaluated baseline NMR metabolites between adiposity and incident DED. RESULTS:In women, after full adjustment including total body fat percentage, each 1% increase in trunk fat percentage was associated with 2.8% higher odds of DED (OR = 1.028, 95% CI 1.015-1.040; P < 0.001), whereas each 1% increase in arm and leg fat percentages was associated with 1.7% (OR = 0.983, 95% CI 0.975-0.990; P < 0.001) and 2.0% lower odds of DED (OR = 0.980, 95% CI 0.971-0.990; P < 0.001), respectively. Mediation analyses implicated GlycA-related inflammation, HDL remodeling, and energy metabolism. In men, BMI≥40 kg/m² was associated with 46.1% higher odds of DED (OR = 1.461, 95% CI 1.172-1.821; P < 0.001), and body fat >35% was associated with 22.4% higher odds (OR = 1.224, 95% CI 1.070-1.399; P = 0.003). Metabolites related to lipid and lipoprotein metabolism were identified as candidate intermediary metabolites in men. CONCLUSION:Adiposity showed sex-specific associations with DED, characterized by central obesity in women and higher overall body fat percentage in men. These retrospective cross-sectional findings do not establish causation.

Low vision substantially impairs reading ability, educational participation, and access to information among children and adolescents. Existing assistive technologies primarily focus on visual magnification and often provide limited support for higher-level cognitive processing during reading tasks. This study aimed to develop and evaluate a virtual reality (VR)-based multimodal intelligent reading aid integrating image enhancement, optical character recognition (OCR), text-to-speech (TTS), and large language model (LLM)-assisted semantic summarization for low-vision adolescents. This study consisted of 2 sequential components. First, a prospective ophthalmic safety evaluation was conducted in 22 healthy adults to assess the short-term ocular safety and tolerability of the VR device. Ophthalmic examinations included tear film break-up time (TBUT), phoria, accommodative function, intraocular pressure (IOP), best-corrected visual acuity (BCVA), and simulator sickness scores before and after device exposure. Second, a within-subject controlled functional evaluation was conducted in 36 low-vision adolescents aged 9–17 years. Participants completed standardized reading tasks under 2 conditions: unaided reading and VR-assisted reading. Reading completion time was evaluated as the primary outcome. Secondary outcomes included user satisfaction and system usability assessed using the System Usability Scale (SUS). Paired-sample t tests were used for statistical analyses. In the ophthalmic safety cohort, no significant changes were observed in TBUT, distance phoria, near phoria, accommodative convergence/accommodation ratio, accommodative response, IOP, BCVA, or simulator sickness scores following VR exposure (all P>.05). No device-related adverse events or clinically significant discomfort were reported. In the functional evaluation cohort, the VR-based reading aid significantly improved reading performance compared with unaided reading. Mean reading completion time decreased from 52.11 (SD 8.83) seconds to 26.53 (SD 3.74) seconds (P<.001), representing an approximately 49% reduction in reading time. User satisfaction was significantly higher under the VR-assisted condition than under the unaided condition (85.56 [SD 4.23] vs 36.53 [SD 11.53]; P<.001). The mean SUS score was 71.32 (SD 3.71), exceeding the established benchmark score of 68 and indicating good overall usability and user acceptance. The proposed VR-based multimodal intelligent reading aid demonstrated favorable short-term ocular safety, good usability, and significant improvements in reading efficiency and user satisfaction among low-vision adolescents. By integrating immersive visualization, OCR-based text recognition, auditory feedback, and AI-assisted semantic processing into a unified digital health platform, the system may represent a promising approach for enhancing reading accessibility, educational participation, and independent learning in visually impaired populations. ClinicalTrials.gov 2024LSPJ164

The comprehensive review by Tang et al., titled "Emerging Oligonucleotide Therapeutics for the Treatment of Dry Eye Diseases," is a timely and important contribution to the field of ocular surface medicine. It offers a detailed and insightful overview of a rapidly evolving therapeutic class that includes spanning small interfering RNAs (siRNAs), antisense oligonucleotides, microRNA modulators, and aptamers. These agents hold significant promise for addressing the complex and multifactorial mechanisms underlying dry eye disease (DED). The authors effectively argue that oligonucleotide-based therapies represent a paradigm shift in treatment strategy, transitioning from the current symptomatic and single-pathway approaches toward precise, gene-targeted interventions. However, as we critically evaluate this emerging landscape, it becomes increasingly clear that the success of these therapeutics will not depend solely on molecular innovation. Instead, their clinical impact will hinge on overcoming two major obstacles: the development of efficient, targeted delivery systems and the successful translation of preclinical findings into meaningful clinical outcomes.

PURPOSE:To explore the ability of conjunctival microvasculature in differentiating ocular surface inflammation (OSI) in mild dry eye (DE), and to guide adjunctive anti-inflammatory treatment in mild DE. METHODS:83 mild DE patients and 26 healthy controls were enrolled in a cross-sectional study. Mild DE patients were classified into those with OSI and those without based on Z-score level of tear cytokines. Differences in microvasculature and clinical manifestations were analyzed, alongside correlations with tear cytokines. A logistic regression model was developed for detecting OSI based on microvascular parameters. A secondary analysis of a RCT involved 35 mild DE patients with OSI to compare microvascular and clinical outcomes between treatment groups (adjunctive 0.05% Cyclosporine A vs. artificial tears alone). RESULTS:Elevated blood flow velocity (BFV: 0.37 ± 0.04 mm/s) and wall shear rate (WSR: 170.98 ± 26.96 s-1) were found in mild DE with OSI than those without (BFV: 0.32 ± 0.03 mm/s, WSR: 145.90 ± 18.46 s-1, p < 0.01), while no significant differences were found in clinical manifestations. BFV and WSR were correlated with IL-6 (rBFV = 0.43, rWSR = 0.39, p < 0.05). The AUC - ROC for the mild DE-related OSI detection model based on BFV and WSR was 0.858. In mild DE with OSI treated with 0.05% Cyclosporine A, BFV, WSR, IL-6, clinical manifestations improved significantly at 12 weeks (p < 0.05). CONCLUSIONS:Elevated BFV and WSR can facilitate early detection of mild DE-related OSI before changes in symptoms and signs, allowing timely anti-inflammatory intervention.

Dry eye disease (DED) is highly prevalent in older adults and represents a growing public health burden in aging societies. Although age is a well-recognized risk factor for DED, it is still often treated as a background variable rather than an active biological driver of disease. Emerging evidence indicates that aging itself promotes progressive structural remodeling and functional decline across multiple ocular surface tissues, giving rise to a distinct, aging-driven DED phenotype. In this review, we synthesize current knowledge on how biological aging disrupts ocular surface homeostasis at tissue, cellular, and molecular levels. We describe age-associated changes in the lacrimal gland (LG), meibomian gland (MG), cornea, and conjunctiva, including secretory cell exhaustion, lipid dysregulation, epithelial barrier impairment, neural degeneration, and goblet cell (GC) loss. These structural changes are tightly linked to core aging mechanisms such as cellular senescence, oxidative stress, mitochondrial dysfunction, inflammaging, neuroendocrine imbalance, and stem/progenitor cell decline. Importantly, these processes interact as an integrated network, creating a self-reinforcing cycle of tear film instability, chronic low-grade inflammation, and impaired tissue repair that differs mechanistically from environmentally induced or autoimmune forms of DED. By reframing aging as a central pathogenic driver and considering age-related DED as a distinct subtype, this perspective highlights the need for mechanism-informed therapeutic strategies. Beyond conventional lubrication and anti-inflammatory therapy, interventions targeting oxidative stress, cellular senescence, inflammaging, neurosensory dysfunction, and hormonal alterations may offer more fundamental disease modification in elderly patients.

Importance Virtual reality–based digital defocus vision training (DDVT) may offer a home-based strategy to slow myopia progression in children, but evidence is limited. Objective To evaluate efficacy and safety of a head-mounted virtual reality–based DDVT system on myopia progression. Design, Setting, and Participants This randomized clinical trial was conducted among children aged 6 to 12 years with myopia enrolled in July 2024, with follow-up completed in September 2025. The trial was conducted at a single center in Guangzhou, China. Data were analyzed from September 2025 to October 2025. Intervention Participants were randomized to DDVT plus single-vision spectacles (SVS) or SVS alone. Participants in the DDVT group used a head-mounted virtual reality device at home for 15 minutes per day under parental supervision after an initial in-hospital training session. Main Outcomes and Measures The primary outcome was the between-group difference in axial length (AL) change from baseline to 6 months. The secondary outcome was between-group difference in spherical equivalent refraction (SER) change. Results Of 120 randomized participants, 57 of 60 participants in the DDVT group (95%) and 59 of 60 participants in the SVS group (98%) completed the study. At baseline, mean (SD) ages in the DDVT and SVS groups were 9.42 (1.52) years and 9.31 (1.13) years, respectively, and 53 of 116 participants (45.7%) were female. Mean (SD) AL and spherical equivalent in the DDVT and SVS groups were 24.35 (0.81) mm and 24.40 (0.81) mm and −1.91 (1.11) diopter (D) and −2.04 (1.06) D, respectively. Mean best-corrected visual acuity was −0.04 logMAR (Snellen equivalent, 20/18) and −0.03 logMAR (20/19), respectively. At 6 months, AL increased by 0.15 mm and 0.25 mm in the DDVT and SVS groups, respectively (difference = 0.11 mm; 95% CI, 0.07-0.15 mm; P < .001). SER changed by −0.23 D and −0.46 D (difference = −0.23 D; 95% CI, −0.35 to −0.11 D; P = .003). Visual acuity change at 6 months was −0.02 logMAR (Snellen equivalent, 20/18) and 0.01 logMAR (20/20) in the DDVT and SVS groups, respectively (difference = 0.03 logMAR [Snellen equivalent, 20/21]; 95% CI, 0.02-0.05 [20/21-20/22]; P < .001). No training-related adverse events were observed. Conclusions and Relevance In this randomized clinical trial, the DDVT group had a small absolute reduction in AL and SER myopic progression compared with SVS alone over 6 months in 120 children with myopia aged 6 to 12 years. The clinical relevance of these differences over the short and long term cannot be determined from this trial but support additional studies to assess this intervention as a promising adjunctive approach for pediatric myopia control. Trial Registration ClinicalTrials.gov Identifier: NCT07042022

Dry eye, a common eye disease globally, poses significant challenges to clinical diagnosis and management due to its complex pathogenesis and high incidence rate. The development of artificial intelligence (AI) technology has provided new opportunities for the analysis and auxiliary diagnosis of dry eye imaging. This expert consensus focuses on the classification and annotation methods of dry eye imaging, in line with the application needs of AI technology. It summarizes the scope and tasks of research on the classification and annotation of dry eye imaging and provides detailed standards for the principles and methods of classification and annotation of major imaging modalities, including lipid layer of the tear film, tear meniscus height, tear film breakup time, corneal fluorescein staining, and meibomian gland images. It also clarifies the tools and processes for classification and annotation. The consensus proposes systematic quality control requirements, including annotation consistency assessment, multi-round review, and data cleaning methods. Finally, the consensus summarizes the current challenges and proposes targeted solutions. The launch of this consensus aims to provide high-quality data support for the development of AI in dry eye, enhance the application effects of AI in dry eye diagnosis, disease monitoring, and personalized treatment, and offer scientific references and technical support for clinical and research applications of AI in the field of dry eye.

Background Optical coherence tomography angiography (OCTA) is a novel, non-invasive imaging technique that enables capillary-level visualization of the retinal vasculature, offering critical insights into various ophthalmic diseases. Accurate segmentation and quantitative analysis of microstructures-specifically the retinal vascular network (RVN) and foveal avascular zone (FAZ)-are essential for diagnosis and treatment planning. We aimed to develop an artificial intelligence-based system to automate segmentation and analysis of OCTA microstructures using a deep learning framework. Methods OCTA images were retrospectively collected from January 2020 to December 2022, comprising 2 public datasets (Retinal OCTA vessel Segmentation-1 (ROSE-1) and OCTA_3M) and a newly constructed clinical dataset, named Fully Annotated Retinal OCTA Segmentation dataset (FAROS), acquired at Zhongshan Ophthalmic Center. The FAROS dataset included 40 en face OCTA images from 40 eyes (20 healthy and 20 with retinal diseases such as diabetic retinopathy (DR), age-related macular degeneration, and retinal vein occlusion). Additionally, a separate clinical dataset containing 20 eyes with DR was enrolled to verify the clinical consistency of the observed parameter trends. To accurately segment the RVN and FAZ, we first introduced an innovative OCTA microstructure segmentation network (RS_Unet3+) by combining an encoder-decoder-based architecture with full-scale skip connections and the split-attention-based residual network ResNeSt, paying special attention to OCTA microstructural features while facilitating better model convergence and feature representations. We then performed multi-class segmentation on the FAROS dataset using the proposed RS_Unet3+ and automatically calculated multiple RVN and FAZ parameters from the segmented image for quantitative analysis. Primary quantitative parameters included FAZ area (A), perimeter (P), circularity index (CI), vessel perfusion density (VPD), vessel length density (VLD), fractal dimension (FD), and tortuosity (T). Statistical comparisons between healthy and diseased groups were conducted using the Mann-Whitney U test with a significance threshold of P < 0.05. Results The proposed RS_Unet3+ was verified through systematic experiments to achieve excellent single-task/multi-class performances for RVN or/and FAZ segmentation on 2 publicly available OCTA datasets, respectively. Moreover, the multi-class segmentation task on the FAROS dataset using RS_Unet3+ achieved excellent segmentation performance that could be used as baseline performance as well. In the independent clinical DR dataset, P of FAZ were significantly higher in the DR group compared to the healthy controls (P < 0.01), while the CI was significantly lower (P < 0.001). Vessel parameters including VLD and FD were significantly reduced (P < 0.05, P < 0.01, respectively), and T increased (P < 0.05) in DR eyes, aligning with the previously reported clinical patterns. Conclusion The RS_Unet3+-based deep learning framework enables accurate segmentation and automated quantitative evaluation of retinal microstructures in OCTA images, which is expected to be a potentially reliable and convenient auxiliary tool for clinical disease diagnosis and treatment.