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Background Global myopia prevalence poses a substantial public health burden with vision-threatening complications, necessitating effective prevention and control strategies. Precise prediction of spherical equivalent (SE), myopia, and high myopia onset is vital for proactive clinical interventions. Methods We reviewed electronic medical records of pediatric and adolescent patients who underwent cycloplegic refraction measurements at the Eye & Ear, Nose, and Throat Hospital of Fudan University between January 2005 and December 2019. Patients aged 3–18 years who met the inclusion criteria were enrolled in this study. To predict the SE and onset of myopia and high myopia in a specific year, two distinct models, random forest (RF) and the gradient boosted tree algorithm (XGBoost), were trained and validated based on variables such as age at baseline, and SE at various intervals. Outputs included SE, the onset of myopia, and high myopia up to 15 years post-initial examination. Age-stratified analyses and feature importance assessments were conducted to augment the clinical significance of the models. Results The study enrolled 88,250 individuals with 408,255 refraction records. The XGBoost-based SE prediction model consistently demonstrated robust and better performance than RF over 15 years, maintaining an R 2 exceeding 0.729, and a Mean Absolute Error ranging from 0.078 to 1.802 in the test set. Myopia onset prediction exhibited strong area under the curve (AUC) values between 0.845 and 0.953 over 15 years, and high myopia onset prediction showed robust AUC values (0.807–0.997 over 13 years, with the 14th year at 0.765), emphasizing the models' effectiveness across age groups and temporal dimensions on the test set. Additionally, our classification models exhibited excellent calibration, as evidenced by consistently low brier score values, all falling below 0.25. Moreover, our findings underscore the importance of commencing regular examinations at an early age to predict high myopia. Conclusions The XGBoost predictive models exhibited high accuracy in predicting SE, onset of myopia, and high myopia among children and adolescents aged 3–18 years. Our findings emphasize the importance of early and regular examinations at a young age for predicting high myopia, thereby providing valuable insights for clinical practice.

Background Retinal detachment (RD) is a vision-threatening disorder of significant severity. Individuals with high myopia (HM) face a 2 to 6 times higher risk of developing RD compared to non-myopes. The timely identification of high myopia-related retinal detachment (HMRD) is crucial for effective treatment and prevention of additional vision impairment. Consequently, our objective was to streamline and validate a machine-learning model based on clinical laboratory omics (clinlabomics) for the early detection of RD in HM patients. Methods We extracted clinlabomics data from the electronic health records for 24,440 HM and 5607 HMRD between 2015 and 2022. Lasso regression analysis assessed fifty-nine variables, excluding collinear variables (variance inflation factor > 10). Four models based on random forest, gradient boosting machine (GBM), generalized linear model, and Deep Learning Model were trained for HMRD diagnosis and employed for internal validation. An external test of the models was done. Three random data sets were further processed to validate the performance of the diagnostic model. The primary outcomes were the area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUCPR) to diagnose HMRD. Results Nine variables were selected by all models. Given the AUC and AUCPR values across the different sets, the GBM model was chosen as the final diagnostic model. The GBM model had an AUC of 0.8550 (95%CI = 0.8322–0.8967) and an AUCPR of 0.5584 (95%CI = 0.5250–0.5879) in the training set. The AUC and AUCPR in the internal validation were 0.8405 (95%CI = 0.8060–0.8966) and 0.5355 (95%CI = 0.4988–0.5732). During the external test evaluation, it reached an AUC of 0.7579 (95%CI = 0.7340–0.7840) and an AUCPR of 0.5587 (95%CI = 0.5345–0.5880). A similar discriminative capacity was observed in the three random data sets. The GBM model was well-calibrated across all the sets. The GBM-RD model was implemented into a web application that provides risk prediction for HM individuals. Conclusion GBM algorithms based on nine features successfully predicted the diagnosis of RD in patients with HM, which will help ophthalmologists to establish a preliminary diagnosis and to improve diagnostic accuracy in the clinic.

Background Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. This study aimed to develop and evaluate an OCT-omics prediction model for assessing anti-vascular endothelial growth factor (VEGF) treatment response in patients with DME. Methods A retrospective analysis of 113 eyes from 82 patients with DME was conducted. Comprehensive feature engineering was applied to clinical and optical coherence tomography (OCT) data. Logistic regression, support vector machine (SVM), and backpropagation neural network (BPNN) classifiers were trained using a training set of 79 eyes, and evaluated on a test set of 34 eyes. Clinical implications of the OCT-omics prediction model were assessed by decision curve analysis. Performance metrics (sensitivity, specificity, F1 score, and AUC) were calculated. Results The logistic, SVM, and BPNN classifiers demonstrated robust discriminative abilities in both the training and test sets. In the training set, the logistic classifier achieved a sensitivity of 0.904, specificity of 0.741, F1 score of 0.887, and AUC of 0.910. The SVM classifier showed a sensitivity of 0.923, specificity of 0.667, F1 score of 0.881, and AUC of 0.897. The BPNN classifier exhibited a sensitivity of 0.962, specificity of 0.926, F1 score of 0.962, and AUC of 0.982. Similar discriminative capabilities were maintained in the test set. The OCT-omics scores were significantly higher in the non-persistent DME group than in the persistent DME group ( p  < 0.001). OCT-omics scores were also positively correlated with the rate of decline in central subfield thickness after treatment (Pearson’s R  = 0.44, p  < 0.001). Conclusion The developed OCT-omics model accurately assesses anti-VEGF treatment response in DME patients. The model’s robust performance and clinical implications highlight its utility as a non-invasive tool for personalized treatment prediction and retinal pathology assessment.

Corneal alkali burns are severe ocular injuries characterized by extensive tissue damage, inflammation, oxidative stress, and neovascularization, which often lead to long-term visual impairment and corneal fibrosis. This review comprehensively examines the mechanisms underlying alkali burn injuries, including the roles of inflammatory mediators, oxidative stress, and cellular responses, while highlighting current and emerging therapeutic approaches. Traditional treatments, such as corticosteroids and surgical interventions, often have limited efficacy and significant side effects. Recent advances in innovative therapies, including stem cell-derived exosomes, hydrogel-based drug delivery systems, and herbal components, demonstrate significant potential for improving corneal healing and reducing complications. These novel approaches aim to mitigate inflammation, enhance epithelial repair, and prevent neovascularization, offering promising pathways for scar-free healing and the restoration of corneal transparency. Future research should focus on integrating these therapies into multifunctional treatment strategies to optimize clinical outcomes and improve quality of life for patients suffering from corneal alkali burns.

Diabetic retinopathy (DR), a well-known microvascular complication of diabetes mellitus, remains the main cause of vision loss in working-age adults worldwide. Up to now, there is a shortage of information in the study regarding the contributing factors of DR in diabetes. Accumulating evidence has identified glycemic variability (GV), referred to fluctuations of blood glucose levels, as a risk factor for diabetes-related complications. Recent reports demonstrate that GV plays an important role in accounting for the susceptibility to DR development. However, its exact role in the pathogenesis of DR is still not fully understood. In this review, we highlight the current landscape and relevant mechanisms of GV in DR, as well as address the mechanism-based therapeutic strategies, aiming at better improving the quality of DR management in clinical practice.

The cornea is the outermost layer of the eye and plays an essential role in our visual system. Limbal epithelial stem cells (LESCs), which are localized to a highly regulated limbal niche, are the master conductors of corneal epithelial regeneration. Damage to LESCs and their niche may result in limbal stem cell deficiency (LSCD), a disease confused ophthalmologists so many years and can lead to corneal conjunctivalization, neovascularization, and even blindness. How to restore the LESCs function is the hot topic for ocular scientists and clinicians around the world. This review introduced LESCs and the niche microenvironment, outlined various techniques for isolating and culturing LESCs used in LSCD research, presented common diseases that cause LSCD, and provided a comprehensive overview of both the diagnosis and multiple treatments for LSCD from basic research to clinical therapies, especially the emerging cell therapies based on various stem cell sources. In addition, we also innovatively concluded the latest strategies in recent years, including exogenous drugs, tissue engineering, nanotechnology, exosome and gene therapy, as well as the ongoing clinical trials for treating LSCD in recent five years. Finally, we highlighted challenges from bench to bedside in LSCD and discussed cutting-edge areas in LSCD therapeutic research. We hope that this review could pave the way for future research and translation on treating LSCD, a crucial step in the field of ocular health. Graphical Abstract

Background Myopia has emerged as a major public health concern globally, which is tightly associated with scleral extracellular matrix (ECM) remodeling and choroidal vasculopathy. Choroidal vasculopathy has gradually been recognized as a critical trigger of myopic pathology. However, the precise mechanism controlling choroidal vasculopathy remains unclear. Transfer RNA-derived fragments (tRFs) are known as a novel class of small non-coding RNAs that plays important roles in several biological and pathological processes. In this study, we investigated the role of tRF-22-8BWS72092 (tRF-22) in choroidal vasculopathy and myopia progression. Methods The tRF-22 expression pattern under myopia-related stresses was detected by qRT-PCR. MTT assays, EdU incorporation assays, Transwell migration assays, and Matrigel assays were conducted to detect the role of tRF-22 in choroidal endothelial cell function in vitro. Isolectin B4 staining and choroidal sprouting assay ex vivo were conducted to detect the role of tRF-22 in choroidal vascular dysfunction in vivo. Immunofluorescent staining, western blot assays and ocular biometric parameters measurement were performed to examine whether altering tRF-22 expression in choroid affects scleral hypoxia and ECM remodeling and myopia progression in vivo. Bioinformatics analysis and luciferase activity assays were conducted to identify the downstream targets of tRF-22. RNA-sequencing combined with m6A-qPCR assays were used to identify the m6A modified targets of METTL3. Gain-of-function and Loss-of-function analysis were performed to reveal the mechanism of tRF-22/METTL3-mediated choroidal vascular dysfunction. Results The results revealed that tRF-22 expression was significantly down-regulated in myopic choroid. tRF-22 overexpression alleviated choroidal vasculopathy and retarded the progression of myopia in vivo. tRF-22 regulated choroidal endothelial cell viability, proliferation, migration, and tube formation ability in vitro. Mechanistically, tRF-22 interacted with METTL3 and blocked m 6 A methylation of Axin1 and Arid1b mRNA transcripts, which led to increased expression of Axin1 and Arid1b. Conclusions Our study reveals that the intervention of choroidal vasculopathy via tRF-22-METTL3- Axin1/Arid1b axis is a promising strategy for the treatment of patients with myopic pathology. Graphical Abstract

Background Corneal neovascularization (CorNV) is a vision-threatening complication arising from various pathological conditions. While persistent inflammation has been established as the core driver, its underlying mechanisms have not been fully elucidated. Current first-line anti-vascular endothelial growth factor (anti-VEGF) therapies are limited by non-responsiveness and recurrence, often associated with ongoing inflammatory activity. The flavonoid compound icariin (ICA) reportedly exhibits potent anti-inflammatory properties and has been widely used to manage systemic inflammatory conditions. However, its specific role in CorNV has not been fully elucidated. Methods This study established two models of corneal neovascularization using alkali burn and suture techniques, followed by treatment with ICA. Next, the area of neovascularization and the degree of corneal inflammatory edema were quantified. Using immunofluorescence, flow cytometry, and ELISA techniques, the expression levels of M1 macrophage markers, proinflammatory cytokines (IL-1β, IL-6, TNF-α), and VEGF were assessed both in vivo (following corneal injury) and in vitro (in RAW264.7 macrophages). NF-κB pathway activity was assessed using western blot and immunofluorescence techniques. Results ICA significantly reduced the area of CorNV and attenuated inflammatory cell infiltration. These effects were associated with down-regulation of M1 macrophage markers in both corneal tissue and cultured macrophages. Mechanistically, ICA inhibited phosphorylation of IκBα and NF-κB, thereby reducing NF-κB translocation to the nucleus and reducing expression levels of IL-1β, IL-6, TNF-α, and VEGF. Conclusion Our study findings suggest that by inhibiting NF-κB signaling and M1 macrophage polarization, ICA effectively mitigates CorNV, offering a novel therapeutic strategy for this patient population.

Retinal neurovascular unit (NVU) is a multi-cellular structure that consists of the functional coupling between neural tissue and vascular system. Disrupted NVU will result in the occurrence of retinal and choroidal vascular diseases, which are characterized by the development of neovascularization, increased vascular permeability, and inflammation. This pathological entity mainly includes neovascular age-related macular degeneration (neovascular-AMD), diabetic retinopathy (DR) retinal vein occlusion (RVO), and retinopathy of prematurity (ROP). Emerging evidences suggest that the angopoietin/tyrosine kinase with immunoglobulin and epidermal growth factor homology domains (Ang/Tie) signaling pathway is essential for the development of retinal and choroidal vascular. Tie receptors and their downstream pathways play a key role in modulating the vascular development, vascular stability, remodeling and angiogenesis. Angiopoietin 1 (Ang1) is a natural agonist of Tie2 receptor, which can promote vascular stability. On the other hand, angiopoietin 2 (Ang2) is an antagonist of Tie2 receptor that causes vascular instability. Currently, agents targeting the Ang/Tie signaling pathway have been used to inhibit neovascularization and vascular leakage in neovascular-AMD and DR animal models. Particularly, the AKB-9778 and Faricimab have shown promising efficacy in improving visual acuity in patients with neovascular-AMD and DR. These experimental and clinical evidences suggest that activation of Ang/Tie signaling pathway can inhibit the vascular permeability, neovascularization, thereby maintaining the normal function and structure of NVU. This review seeks to introduce the versatile functions and elucidate the modulatory mechanisms of Ang/Tie signaling pathway. Recent pharmacologic therapies targeting this pathway are also elaborated and summarized. Further translation of these findings may afford a new therapeutic strategy from bench to bedside.

Background Dry age-related macular degeneration (AMD) is characterized by progressive degeneration of the retinal pigment epithelium–choroid interface, accompanied by immune dysregulation. However, the cellular interactions and regulatory mechanisms driving macrophage activation in this process remain incompletely understood. Methods We integrated spatial transcriptomics and single-cell RNA sequencing data from a photo-oxidative damage mouse model and human dry AMD samples. A series of bioinformatic analyses, including cell–cell communication analysis, enrichment analysis, and pseudotime trajectory analysis, were performed to characterize cellular features and regulatory pathways. Results In the photo-oxidative damage mouse model, the RPE–choroid region showed marked infiltration of myeloid cells. In human dry AMD samples, SLC16A10-positive macrophages were enriched and exhibited pro-inflammatory features. Further analysis revealed that endothelial cells regulate SLC16A10-positive macrophages through the TNFSF10–TNFRSF10B pathway, with NFKB1 acting as a key regulator to activate NF-κB signaling, thereby promoting the formation of a vascular–immune inflammatory niche. Conclusions This study systematically characterizes immune remodeling in the RPE–choroid region in dry AMD and identifies an endothelial–macrophage TNFSF10–TNFRSF10B–NF-κB signaling pathway that drives disease progression. These findings provide new insights into disease mechanisms and suggest potential therapeutic targets for dry AMD.