clobetasol (DFD06 / DFD06 Cream / DFD 06)

Structural and Angiographic Assessment of the Nerve Fiber Layer in Age-Related Macular Degeneration and Diabetic Retinopathy.

Hua Xiaohui X, Hormel Tristan T TT, Wang Jie J, Flaxel Christina J CJ et al.

The purpose of this study was to evaluate structural and microvascular alterations in the nerve fiber layer (NFL) in age-related macular degeneration (AMD) and diabetic retinopathy (DR). A total of 74 healthy controls, 101 patients with AMD, and 117 patients with DR were included. One eye per participant was imaged using a Solix OCTA device centered on the optic disc to measure NFL thickness and nerve fiber layer plexus (NFLP) vessel density (VD). For both parameters, we analyzed the independent associations of age, AMD, and DR; compared age-matched healthy controls with the AMD groups and with the DR groups; and evaluated correlations with age in healthy controls. Multivariate analyses demonstrated that age was independently associated with both NFL thickness and NFLP VD, whereas AMD was not associated with either parameter and DR was associated only with NFLP VD. The associations of AMD and DR with these two parameters were also confirmed in age-matched analyses. Additionally, NFLP VD decreased significantly with increasing DR severity (P < 0.001). In healthy controls, age was significantly correlated with both NFL thickness (Spearman's ρ = -0.26, P = 0.026) and NFLP VD (ρ = -0.32, P = 0.006). NFL thickness was associated with age, but not with AMD or DR. In contrast, DR was independently associated with reduced NFLP VD, which also significantly correlated with DR severity. These findings provide evidence supporting further investigation of NFLP VD in relation to DR, while accounting for age.

Redistribution of Aquaporin Proteins in Retinal Blood Vessels in Human Diabetic Retinopathy.

Britten-Jones Alexis Ceecee AC, Petrova Rosica R, Green Colin R CR, Grey Angus C AC et al.

Diabetic macular edema, the primary cause of vision loss in non-proliferative diabetic retinopathy (NPDR), is traditionally attributed to microvascular leakage but may also involve structural and caliber change in large retinal vessels. This study investigated the spatial distributions of key aquaporins from the aquaporin family mediating water transport or membrane stability in donor human retinas with diabetic retinopathy (DR). Human donor retinas were fixed, sectioned and labeled for immunohistochemistry using antibodies against Aquaporin 0 (AQP0), Aquaporin 1 (AQP1) and Aquaporin 4 (AQP4). Labeling was performed in combination with vascular and cellular markers including calbindin, A kinase anchor protein-2 (AKAP-2), vimentin, glial fibrillary acidic protein (GFAP), Kir4.1, and collagen IV. Images were acquired using high-resolution laser scanning confocal microscopy and analyzed using ImageJ. AQP0 distribution in the inner retina remained unchanged in DR. In contrast, both AQP1 and AQP4 exhibited marked redistribution within and around large retinal vessels. Specifically, AQP1, typically confined to the endothelium of superficial vessels, was detected in the middle layer of vessel walls in DR. AQP4, normally localized to the ganglion cell layer and associated with vimentin-positive Müller glia processes, was observed in the outer vessel layers, even in the absence of significant GFAP upregulation. The novel localization of AQP1 within the vessel wall may reflect altered spatial organization of water transport pathways within retinal vessel walls, contributing to impaired contractile function. These findings indicate that alterations in aquaporin distribution may be associated with vascular remodeling observed in DR.

ARTNet: Adaptive channel-wise and Region-aware Transformer Network for diabetic retinopathy segmentation and classification.

Kumar Annuj A, Shruthi Munjam M, Sujeeth Thiruppathy T, Mohideen Abubacker Kaja AK et al.

Early and accurate detection of diabetic retinopathy (DR) is essential to prevent irreversible vision loss; however, manual screening is labor-intensive and subject to inter-observer variability. To address these limitations, we propose ARTNet, an Adaptive channel-wise and Region-aware Transformer Network for automated DR classification and segmentation from retinal fundus images. ARTNet integrates three sub-network mechanisms. The Adaptive Channel-wise Feature Network (ACFNet) performs channel recalibration using dual pooling and shared multilayer perceptrons to enhance discriminative retinal representations while suppressing irrelevant responses. The Ophthalmic Region-Aware Attention Network (ORAANet) applies spatial attention to highlight clinically significant regions, including lesions and abnormal vasculature. The Retinal Patch Aggregation Encoder Network (RPAENet), built on multi-head self-attention, captures long-range dependencies and global retinal context for hierarchical feature modeling. Convolutional refinement and global average pooling enable robust five-class DR classification, while a class-balanced focal loss mitigates data imbalance and improves minority-class sensitivity. Extensive experiments on benchmark datasets demonstrate the superiority of ARTNet over intermediate and state-of-the-art models. On the Diabetic Retinopathy Detection dataset, ARTNet achieves 96.45% accuracy, 96.85% precision, 96.34% recall, and 96.60% F1-score. The model is further validated on the APTOS-2019 Blindness Detection and IDRiD datasets. Classification performance is evaluated using image-level DR grading metrics, whereas lesion segmentation performance is evaluated using the pixel-level lesion annotations available only in the IDRiD dataset. Results show that dual attention with transformer-based global reasoning improves feature representation and classification reliability. Its efficiency and stability support real-time ophthalmic screening and a clinical decision system.

Reply to Dr. Zhang's Letter to the Editor re: R.M. Bernardino, L.B. Yin, K. Lajkosz, et al. Intraductal Carcinoma Predicts Poor Response to Neoadjuvant Therapy in High-risk Prostate Cancer: A Retrospective Analysis of a Prospective Trial. Eur Urol Open Sci 2025;82:52-8.

Bernardino Rui M RM, Yin Leyi B LB, Lajkosz Katherine K, Winqust Eric E et al.