Oxidative stress is an important pathomechanism found in numerous ocular degenerative diseases. To provide a better understanding of the mechanism and treatment of oxidant/antioxidant imbalance-induced ocular diseases, this article summarizes and provides updates on the relevant research. We review the oxidative damage (e.g., lipid peroxidation, DNA lesions, autophagy, and apoptosis) that occurs in different areas of the eye (e.g., cornea, anterior chamber, lens, retina, and optic nerve). We then introduce the antioxidant mechanisms present in the eye, as well as the ocular diseases that occur as a result of antioxidant imbalances (e.g., keratoconus, cataracts, age-related macular degeneration, and glaucoma), the relevant antioxidant biomarkers, and the potential of predictive diagnostics. Finally, we discuss natural antioxidant therapies for oxidative stress-related ocular diseases.

Atropine is a common treatment used in children with myopia. However, it probably affects intraocular pressure (IOP) under some conditions. Our research aims to analyze clinical data by using machine learning models to evaluate the effect of 19 important factors on intraocular pressure (IOP) in children with myopia treated with topical atropine. The data is collected on 1545 eyes with spherical equivalent (SE) less than −10.0 diopters (D) treated with atropine for myopia control. Four machine learning models, namely multivariate adaptive regression splines (MARS), classification and regression tree (CART), random forest (RF), and eXtreme gradient boosting (XGBoost), were used. Linear regression (LR) was used for benchmarking. The 10-fold cross-validation method was used to estimate the performance of the five methods. The main outcome measure is that the 19 important factors associated with atropine use that may affect IOP are evaluated using machine learning models. Endpoint IOP at the last visit was set as the target variable. The results show that the top five significant variables, including baseline IOP, recruitment duration, age, total duration and previous cumulative dosage, were identified as most significant for evaluating the effect of atropine use for treating myopia on IOP. We can conclude that the use of machine learning methods to evaluate factors that affect IOP in children with myopia treated with topical atropine is promising. XGBoost is the best predictive model, and baseline IOP is the most accurate predictive factor for endpoint IOP among all machine learning approaches.

Background: Hidradenitis suppurativa (HS) is a chronic inflammatory dermatosis primarily affecting women of reproductive age. HS may contribute to an increase of adverse pregnancy outcomes (APOs). Objectives: To investigate the association of HS with APOs. Methods: A systematic review was conducted of observational studies examining the association of maternal HS with APOs. We searched MEDLINE, Embase and CENTRAL from inception to 15 March 2025 for relevant studies. No restrictions were imposed on language or geographical regions. Observational studies, including cohort and case–control designs, which examined the odds or risk of APOs among pregnant patients were considered eligible for inclusion. The risk of bias was assessed using the Newcastle–Ottawa Scale. A random-effects model meta-analysis using the inverse-variance-weighted method was performed. Results: We included four retrospective cohort studies with 15 189 175 pregnancies. The overall risk of bias was low to unclear. The meta-analysis revealed associations of HS with APOs, including gestational diabetes mellitus [odds ratio (OR) 1.46, 95% confidence interval (CI) 1.09–1.96], pre-eclampsia/eclampsia (OR 1.18, 95% CI 1.01–1.38), caesarean section (OR 1.31, 95% CI 1.04–1.64) and postpartum haemorrhage (OR 1.39, 95% CI 1.07–1.82). Regarding adverse fetal outcomes, maternal HS was significantly associated with spontaneous abortion (OR 1.19, 95% CI 1.06–1.34), preterm birth (OR 1.17, 95% CI 1.04–1.31) and birth defects (OR 1.47, 95% CI 1.03–2.11). Conclusions: Pregnant women with HS have an increased risk of APOs, underscoring the need for coordinated care between dermatologists and obstetricians, as well as early diagnosis and intervention to mitigate potential risks to maternal health and fetal development.