Many patients with wet age-related macular degeneration do not respond well to anti- vascular endothelial growth factor A (VEGFA) therapy for choroidal neovascularization (CNV), and the efficacy of anti-VEGFA decreases over time. We investigated the hypothesis that fibrotic changes, in particular via endothelial-to-mesenchymal transition (EndoMT), play a role in CNV and alter the therapeutic effects of VEGFA pathway blockage. Induction of EndoMT of primary human retinal endothelial cells led to a significantly reduced response to VEGFA at the level of gene expression, cellular proliferation, migration, and tube formation. Suppression of EndoMT restored cell responsiveness to VEGFA. In a mouse model of spontaneous CNV, fibrotic changes and EndoMT persisted as the CNV lesions became more established over time. VEGFA receptor-2 (VEGFR2) antagonism further induced fibrosis and EndoMT in the CNV. The combination of VEGFR2 antagonism and fibrosis/EndoMT inhibition was more effective than either individual treatment in reducing CNV. Our data indicate that fibrosis and EndoMT are involved in the progression of CNV, are exacerbated by VEGFR2 inhibition, and could provide an explanation for the reduced efficacy of anti-VEGFA treatment over time.

Purpose To develop a Vision Transformer model to detect different stages of diabetic maculopathy (DM) based on optical coherence tomography (OCT) images. Methods After removing images with poor quality, a total of 3319 OCT images were extracted from the Eye Center of the Renmin Hospital of Wuhan University and randomly split the images into training and validation sets in a 7:3 ratio. All macular cross-sectional scan OCT images were collected retrospectively from the eyes of DM patients from 2016 to 2022. One of the OCT stages of DM, including early diabetic macular oedema (DME), advanced DME, severe DME and atrophic maculopathy, was labelled on the collected images, respectively. A deep learning (DL) model based on Vision Transformer was trained to detect four OCT grading of DM. Results The model proposed in our paper can provide an impressive detection performance. We achieved an accuracy of 82.00%, an F1 score of 83.11%, an area under the receiver operating characteristic curve (AUC) of 0.96. The AUC for the detection of four OCT grading (ie, early DME, advanced DME, severe DME and atrophic maculopathy) was 0.96, 0.95, 0.87 and 0.98, respectively, with an accuracy of 90.87%, 89.96%, 94.42% and 95.13%, respectively, a precision of 88.46%, 80.31%, 89.42% and 87.74%, respectively, a sensitivity of 87.03%, 88.18%, 63.39% and 89.42%, respectively, a specificity of 93.02%, 90.72%, 98.40% and 96.66%, respectively and an F1 score of 87.74%, 84.06%, 88.18% and 88.57%, respectively. Conclusion Our DL model based on Vision Transformer demonstrated a relatively high accuracy in the detection of OCT grading of DM, which can help with patients in a preliminary screening to identify groups with serious conditions. These patients need a further test for an accurate diagnosis, and a timely treatment to obtain a good visual prognosis. These results emphasised the potential of artificial intelligence in assisting clinicians in developing therapeutic strategies with DM in the future.

To investigate the effects of partial sleep deprivation (PSD) on the retinal microvasculature in individuals with myopia, using optical coherence tomography angiography (OCTA). In total, 87 right eyes were categorized by axial length (AL) into three groups: A (AL < 24 mm, n = 20), B (24 ≤ AL < 26 mm, n = 41), and C (AL ≥ 26 mm, n = 26). Participants underwent macular (6 mm × 6 mm) and optic disc (4.5 mm × 4.5 mm) OCTA scans. Vessel density (VD) parameters-including superficial capillary plexus VD (SCP-VD), deep capillary plexus VD (DCP-VD), radial peripapillary capillary VD (RPC-VD), inside disc RPC VD (iVD), and peripapillary RPC VD (ppVD)-were compared at baseline, before and after PSD, and following 3 days of regular sleep. Compared with group A, groups B and C had lower baseline DCP-VD in all subregions (P < 0.05), except for the perifovea-inferior area, where only groups C and A showed significant differences (P = 0.001). After PSD, group C showed a decrease in SCP-VD in certain subregions of the parafovea (P = 0.013 and P = 0.022 for parafovea-temporal and parafovea-inferior, respectively), along with an increase in ppVD (P = 0.012). All VD parameters recovered after 3 days of regular sleep (P < 0.05). The retinal microvasculature of myopic eyes with an AL of ≥26 mm show greater susceptibility to PSD than those with an AL of <26 mm. However, short-term PSD effects can be restored by setting a regular sleep schedule.

Growth differentiation factor 6 (GDF6) has been reported to be a novel disease gene for age-related macular degeneration (AMD) in Caucasians. This study aimed to investigate whether rs6982567 was associated with neovascular AMD (nAMD) or polypoidal choroidal vasculopathy (PCV) in a Han Chinese cohort. A total of 612 participants (251 PCV patients, 157 nAMD patients and 204 controls) were included in this study. The SNaPshot system was used to genotype the rs6982567. PLINK software was used to evaluate the genotypes and allele frequencies of patients and controls. The allele frequencies of rs6982567 were not significantly associated with nAMD, PCV or PCV and nAMD combined. Subjects with the TT genotype had a 2.42-fold greater risk of PCV (95% confidence interval, 1.07-5.43, p = 0.0290) than subjects with CC genotype. A recessive model of rs6982567 was statistically significantly associated with PCV (odds ratio, 2.29; 95% confidence interval, 1.04-5.05; p = 0.0351). However, the association did not withstand stringent Bonferroni correction. There were no significant differences in genotype distributions or models in nAMD. There was a possible weak association between the rs6982567 near GDF6 and PCV in this replication study with an independent Han Chinese cohort. A complete survey of the GDF6 locus with a larger sample size is needed in future studies.

Purpose. To investigate the impact of denoising on the qualitative and quantitative parameters of optical coherence tomography angiography (OCTA) images of the optic nerve and macular area. Methods. OCTA images of the optic nerve and macular area were obtained using a Canon-HS100 OCT device for 48 participants (48 eyes). Multiple image averaging (MIA) and denoising techniques were used to improve the quality of the OCTA images. The peak signal-to-noise ratio (PSNR) as an image quality parameter and vessel density (VD) as a quantitative parameter were obtained from single-scan, MIA, and denoised OCTA images. The parameters were compared, and the correlation was analyzed between different imaging protocols. Results. In the optic nerve area, there were significant differences in the PSNR and VD in all measured regions between the three groups ( ). The PSNR of the denoised group was significantly higher than that of the other two groups ( ). The VD in the denoised group was significantly lower than that in the single-scan group in all measured regions ( ). In the macular area, there were significant differences in the PSNR and VD in all measured regions among the three groups. The PSNR of the denoised group was significantly higher than that of the other two groups ( ). The VD in the denoised group was significantly lower than that in the single-scan group in all measured regions. The VD around the optic nerve in the denoised group was correlated with that in the single-scan group ( , ), but the VD in the MIA group was not correlated with that in the single-scan group ( , ). The VD around the fovea in the denoised and MIA images was correlated with that in the single-scan group ( , ; , , respectively). Conclusion. Denoising could provide an easy and quick way to improve image quality parameters, such as PSNR. It shows great potential in improving the sensitivity of OCTA images as retinal disease markers.

Purpose. To explore short‐term changes in corneal astigmatism after combined silicone oil removal and cataract (SORC) surgery. Methods. We enrolled 89 patients (43 men and 46 women). Zeiss IOLMaster was used to measure corneal astigmatism status and axial length on the day before and after the SORC surgery. Best‐corrected visual acuity (BCVA) and intraocular pressure (IOP) were recorded. The results were compared to the outcomes at 3 days, 1 week, and 1 month postoperatively. Results. Compared to baseline, K1 decreased significantly at 3 days postoperatively (P = 0.016), 1 week (P = 0.009), and 1 month (P = 0.035), while K2 increased significantly at 3 days postoperatively (P = 0.002), 1 week (P < 0.001), and 1 month (P = 0.001), as well as corneal astigmatism (all P < 0.001). Compared to that at the baseline, BCVA significantly improved at 3 days, 1 week, and 1 month postoperatively (all P < 0.001). Meanwhile, IOP decreased significantly at 3 days postoperatively (P < 0.001), 1 week (P = 0.005), and 1 month (P = 0.007). Similarly, axial length decreased at all follow‐up time points (all P < 0.001). Conclusion. Corneal astigmatism increased in the short term after the SORC operation but gradually decreased at 1 month postoperatively. BCVA improved steadily, and SORC was widely used in the clinic.