Diabetic retinopathy (DR) is a major cause of blindness in adult, and the accumulation of advanced glycation end products (AGEs) is a major pathologic event in DR. Methylglyoxal (MGO), a highly reactive dicarbonyl compound, is a precursor of AGEs. Although the therapeutic potential of metformin for retinopathy disorders has recently been elucidated, possibly through AMPK activation, it remains unknown how metformin directly affects the MGO-induced stress response in retinal pigment epithelial cells. Therefore, in this study, we compared the effects of metformin and the AMPK activator A769662 on MGO-induced DR in mice, as well as evaluated cytotoxicity, mitochondrial dynamic changes and dysfunction in ARPE-19 cells. We found MGO can induce mitochondrial ROS production and mitochondrial membrane potential loss, but reduce cytosolic ROS level in ARPE-19 cells. Although these effects of MGO can be reversed by both metformin and A769662, we demonstrated that reduction of mitochondrial ROS production rather than restoration of cytosolic ROS level contributes to cell protective effects of metformin and A769662. Moreover, MGO inhibits AMPK activity, reduces LC3II accumulation, and suppresses protein and gene expressions of MFN1, PGC-1α and TFAM, leading to mitochondrial fission, inhibition of mitochondrial biogenesis and autophagy. In contrast, these events of MGO were reversed by metformin in an AMPK-dependent manner as evidenced by the effects of compound C and AMPK silencing. In addition, we observed an AMPK-dependent upregulation of glyoxalase 1, a ubiquitous cellular enzyme that participates in the detoxification of MGO. In intravitreal drug-treated mice, we found that AMPK activators can reverse the MGO-induced cotton wool spots, macular edema and retinal damage. Functional, histological and optical coherence tomography analysis support the protective actions of both agents against MGO-elicited retinal damage. Metformin and A769662 via AMPK activation exert a strong protection against MGO-induced retinal pigment epithelial cell death and retinopathy. Therefore, metformin and AMPK activator can be therapeutic agents for DR.

Ultraviolet radiation, especially UVA, can penetrate the lens, reach the retina, and induce oxidative stress to retinal pigment epithelial (RPE) cells. Even though it is weakly absorbed by protein and DNA, it may trigger the production of reactive oxygen species (ROS) and generate oxidative injury; oxidative injury to the retinal pigment epithelium has been implicated to play a contributory role in age-related macular degeneration (AMD). Studies showed that resveratrol, an abundant and active component of red grapes, can protect several cell types from oxidative stress. In this study, adult RPE cells being treated with different concentrations of resveratrol were used to evaluate the protective effect of resveratrol on RPE cells against UVA-induced damage. Cell viability assay showed that resveratrol reduced the UVA-induced decrease in RPE cell viability. Through flow cytometry analysis, we found that the generation of intracellular H₂O₂ induced by UVA irradiation in RPE cells could be suppressed by resveratrol in a concentration-dependent manner. Results of Western blot analysis demonstrated that resveratrol lowered the activation of UVA-induced extracellular signal-regulated kinase, c-jun-NH₂ terminal kinase and p38 kinase in RPE cells. In addition, there was also a reduction in UVA-induced cyclooxygenase-2 (COX-2) expression in RPE cells pretreated with resveratrol. Our observations suggest that resveratrol is effective in preventing RPE cells from being damaged by UVA radiation, and is worth considering for further development as a chemoprotective agent for the prevention of early AMD.

Purpose: Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss, and its prevalence is expected to rise with aging populations. Early prediction of AMD progression is critical for effective management. This systematic review and meta-analysis evaluate the accuracy, sensitivity, and specificity of artificial intelligence (AI) algorithms in in detecting and predicting progression of AMD. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review and meta-analysis were conducted from inception to February 7th, 2025. We included five studies that assessed the performance of AI algorithms in predicting AMD progression using multimodal imaging. Data on accuracy, sensitivity, and specificity were extracted, and meta-analysis was performed using Comprehensive Meta-Analysis software version 3.7. Heterogeneity was assessed using the I² statistic. Results: Of the five studies, AI models demonstrated superior accuracy (mean difference: 0.07, 95% CI: 0.07, 0.07; p < 0.00001) and sensitivity (mean difference: 0.08, 95% CI: 0.08, 0.08; p < 0.00001) compared to retinal specialists. Specificity also showed a minimal but significant advantage for AI (mean difference: 0.01, 95% CI: 0.01, 0.01; p < 0.00001). Importantly, heterogeneity was minimal to absent across all analyses (I² = 0–0.42%), supporting the reliability and consistency of pooled findings. Conclusion: AI algorithms outperform retinal specialists in predicting AMD progression, particularly in accuracy and sensitivity. These findings support the potential of AI in AMD prediction; however, given the limited number of included studies, the results should be interpreted as exploratory and in need of validation through future large-scale, prospective studies.