The global incidence of autoimmune diseases is on the rise, leading to a corresponding increase in ocular complications associated with these conditions. Autoimmune pathologies can directly target ocular tissues via inflammatory mediators or induce endothelial dysfunction and microvascular alterations that compromise ocular integrity. These mechanisms give rise to a broad spectrum of ocular manifestations. In this review, optical coherence tomography angiography (OCTA)-detected changes in the eye are examined in the context of systemic autoimmune and inflammatory diseases. These imaging biomarkers show promise as novel indicators for identifying relapse risk and subclinical inflammatory stages in systemic autoimmune disorders.

Repeated low-level red-light therapy (RLRL) has recently emerged as a new type of treatment to control myopia. In our study, we aim to compare the effects of RLRL and peripheral defocus modifying spectacle (PDMSL) in Medium-High myopia. This study is a randomized controlled trial. The participants were 25 children with ≥ −4.00 diopters (D) of myopia. Groups of intervention (RLRL) and control (PDMSL) were assigned 1:1. In the RLRL group, the participant would use the device and wore single-vision spectacles daily. In the control group, the participant wore PDMSL daily. The axial length, spherical equivalent refractions, and other ophthalmic examinations were measured at baseline, one, three, six, nine, and 12 months. There were 13 children in the RLRL group, and 12 children in the PDMSL group. Spherical equivalent refraction change was 0.28 ± 0.50D and −0.79 ± 0.48D at 12 months, in both groups, respectively. There was significant difference (<italic>p</italic> &lt; 0.001). Axial length change was −0.18 ± 0.17 mm and 0.34 ± 0.13 mm at 12 months in both groups, respectively. There was significant difference (<italic>p</italic> &lt; 0.001). There were no adverse events reported that were related to the treatment. RLRL was more effective in myopia control. RLRL could be well tolerated, with few adverse effects related to the treatment.

Retinal degenerative diseases refer to a group of disorders characterized by the gradual degradation of retinal tissue structure and function. With their incidence on the rise, there is an urgent need to develop new therapeutic strategies. Retinal organoids, as an emerging technology with promising potential for the treatment of retinal degenerative diseases, play a crucial role in constructing a disease model and drug screening. Here, we review recent developments in retinal organoid research, focusing particularly on their application in transplantation methodologies. We aimed to optimize the implantation process of retinal organoids while qualitatively and quantitatively assessing the degree of visual function recovery. This evaluation intended to determine their potential and effectiveness in treating retinal diseases, thereby advancing the clinical application of organoid transplantation technologies. Although animal experiments have demonstrated that retinal organoids hold significant potential in improving retinal structure and function, there remains a lack of sufficient clinical evidence to support their application efficacy in humans. Therefore, future studies should further optimize implantation protocols for retinal organoids and refine the associated evaluation strategies, with the goal of integrating more clinical data. This will, in turn, provide a more robust evidence base for the application of retinal organoids in human subjects.

Glaucoma is a common ocular disease characterized by elevated intraocular pressure (IOP). Despite the efforts to manage IOP, it still cannot prevent the development of glaucomatous neurodegeneration in the retina. Microglia, the principal resident immune components in the eyes, serve as the concertmaster in the progression of glaucoma. They are activated and polarized in response to the stimuli, including increased IOP attack and advancing neurodegeneration. In previous studies, microglia not only target retinal ganglion cells, which are the victims of glaucomatous neurodegeneration, but also interplay with the other cells in the retina, including Müller cells and astrocytes. These interactions can either accelerate or decelerate the glaucomatous progression. In these complex interactions, directly targeting or inhibiting part of them may become a focal point for future therapies. Therefore, microglial activation and their mutual regulation with the other retinal cells have become a breakthrough point. This review explores the role of microglia in glaucoma pathogenesis and concentrates on the microglial activation and immune regulatory functions. The current study focuses on the immune network orchestrated by microglia and their interactions, to shed light on potential avenues for developing novel neuroprotective therapies that target microglia.

The application of artificial intelligence (AI) in ophthalmological clinical education has attracted widespread attention. This systematic review followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and searched three electronic databases (PubMed, Google Scholar, and Web of Science) for literature published between 1 January 2019 and 31 May 2025. In total, 38 studies were included to evaluate the role of AI in ophthalmological education. The results indicate that AI enhances the screening and diagnostic capabilities for ophthalmic diseases through big data and deep learning algorithms, while also diversifying educational approaches. Technologies such as virtual reality (VR), augmented reality (AR), and intelligent tutoring systems create immersive learning environments that support surgical simulation, real-time feedback, and personalized learning pathways, significantly improving students' engagement and skill acquisition. Furthermore, AI-assisted image analysis and automated annotation tools optimize educational resources, shorten the duration of learning, and improve diagnostic accuracy. Nevertheless, challenges remain in the promotion of AI, including issues related to data quality, privacy protection, and ethical considerations.

Visually navigating environmental terrain on foot requires the human cerebral cortex to process multisensory information. To study the effects of gait speed and visual environment on human electrocortical spectral power dynamics during visually guided treadmill locomotion, we recorded high-density mobile electroencephalography (EEG) signals from 11 healthy subjects at a range of treadmill walking speeds (0.6, 0.8, 1.0, and 1.5 m/s) in three contrasting virtual reality scenes: (1) a stationary three-dimensional (3D) grid, (2) a moving forest trail, and (3) a moving city street that matched the treadmill's gait speed. Sensorimotor and parietal cortical regions showed greater theta band spectral power (4−8 Hz) and reduced the alpha (8−13 Hz), beta (13−30 Hz), and gamma band (&gt; 30 Hz) power at faster walking speeds, indicative of greater cortical processing. In contrast, visual and parietal cortical processing increased while walking along a virtual forest trail and city street compared with a stationary 3D grid, but sensorimotor cortical processing increased in the absence of a moving visual environment. Differential responses among cortical structures while navigating contrasting environments at different speeds provide insight into sensory reweighting that can improve our understanding of cortical processing during gait and help identify biomarkers for predicting locomotor deficits and the risk of falls due to competing sensory demands.

Diabetic macular edema (DME), a leading cause of vision impairment in diabetes, is primarily treated with intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections. However, variable treatment response rates often lead to persistent edema and irreversible vision loss. Accurate prediction of treatment response is therefore critical for optimizing treatment strategies and preserving visual function. This review examines the application of artificial intelligence (AI) to predict anti-VEGF treatment outcomes in DME. While optical coherence tomography (OCT) imaging has shown significant progress, the potential of optical coherence tomography angiography (OCTA) and fluorescein angiography (FA) remains under-exploited. AI holds considerable promise for enhancing predictive accuracy. Future research should focus on multimodal imaging approaches integrating structural, ischemic, and vascular information to develop more accurate and reliable predictive models for personalized DME treatment.

Aging causes impairment of contrast sensitivity and chromatic discrimination, leading to changes in the perceptual interactions between color and luminance information. We aimed to investigate the influence of chromatic noise on luminance contrast thresholds in young and older adults. Forty participants were divided equally into Young (29.6±6.3-year-old) and Elderly Groups (57.8±6.6-year-old). They performed a luminance contrast discrimination task in the presence of chromatic noise maskers using a mosaic stimulus in a mosaic background. Four chromatic noise masking protocols were applied (protan, deutan, tritan, and no-noise protocols). We found that luminance contrast thresholds were significantly elevated by the addition of chromatic noise in both age groups (P<0.05). In the Elderly group, but not the younger group, thresholds obtained in the tritan protocol were lower than those obtained from protan and deutan protocols (P<0.05). For all protocols, the luminance contrast thresholds of elderly participants were higher than in young people (P<0.01). Tritan chromatic noise was less effective in inhibiting luminance discrimination in elderly participants.

Recently, a detailed catalog of 32 retinal ganglion cell (RGC) visual response patterns in mouse has emerged. However, the 10,000 samples required for this catalog-based on fluorescent signals from a calcium indicator dye-are much harder to acquire from the extracellular spike train recordings underlying our bionic vision research. Therefore, we sought to convert spike trains into pseudocalcium signals so that our data could be directly matched to the 32 predefined, calcium signal-based groups. A microelectrode array (MEA) was used to record spike trains from mouse RGCs of 29 retinas. Visual stimuli were adapted from the Baden et al. study; including moving bars, full-field contrast and temporal frequency chirps, and black-white and UV-green color flashes. Spike train histograms were converted into pseudocalcium traces with an OGB-1 convolution kernel. Response features were extracted using sparse principal components analysis to match each RGC to one of the 32 RGC groups. These responses mapped onto of the 32 previously described groups; however, some of the groups remained unmatched. Thus, adaptation of the Baden et al. methodology for MEA recordings of spike trains instead of calcium recordings was partially successful. Different classification methods, however, will be needed to define clear RGC groups from MEA data for our bionic vision research. Nevertheless, others may pursue a pseudocalcium approach to reconcile spike trains with calcium signals. This work will help to guide them on the limitations and potential pitfalls of such an approach.