Endothelin-1 (ET-1) overactivity has been implicated as a factor contributing to glaucomatous neuropathy, and it has been utilized in animal models of retinal ischemia. The functional effects of long-term ET-1 exposure and possible compensatory mechanisms have, however, not been investigated. This was therefore the purpose of our study. ET-1 was delivered into rat eyes via a single intravitreal injection of 500 µM or via transgene delivery using an adeno-associated viral (AAV) vector. Retinal function was assessed using electroretinography (ERG) and the retinal expression of potentially compensatory genes was evaluated by means of qRT-PCR. Acute ET-1 delivery led to vasoconstriction and a significant reduction in the ERG response. AAV-ET-1 resulted in substantial transgene expression and ERG results similar to the acute ET-1 injections and comparable to other models of retinal ischemia. Compensatory changes were observed, including an increase in calcitonin gene-related peptide (CGRP) gene expression, which may both counterbalance the vasoconstrictive effects of ET-1 and provide neuroprotection. This chronic ET-1 ischemia model might be especially relevant to glaucoma research, mimicking the mild and repeated ischemic events in patients with long-term vascular dysfunction. The compensatory mechanisms, and particularly the role of vasodilatory CGRP in mitigating the retinal damage, warrant further investigation with the aim of evaluating new therapeutic strategies.
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http://dx.doi.org/10.3390/cells12151987 | DOI Listing |
Sci Rep
January 2025
Department of Ophthalmology, Konyang University College of Medicine, Daejeon, Republic of Korea.
To determine longitudinal changes in the peripapillary retinal nerve fiber layer (pRNFL) thickness in type 2 diabetes mellitus (T2DM) patients with hypertension (HTN). Participants were divided into three groups: normal controls (Group 1), patients with T2DM (Group 2), and patients with both T2DM and HTN (Group 3). Following the initial examination, patients underwent three additional examinations at 1-year intervals.
View Article and Find Full Text PDFBiomed Tech (Berl)
January 2025
Department of Computer Science, 72937 Centre for Machine Learning and Intelligence (CMLI), Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, India.
Objectives: Diabetic retinopathy (DR) is associated with long-term diabetes and is a leading cause of blindness if it is not diagnosed early. The rapid growth of deep learning eases the clinicians' DR diagnosing procedure. It automatically extracts the features and performs the grading.
View Article and Find Full Text PDFBr J Ophthalmol
January 2025
Department of Neurosciences, Imaging and Clinical Sciences, University "G. d'Annunzio" Chieti-Pescara, Chieti, Italy.
Purpose: To quantitatively explore preretinal abnormal tissue (PAT) in macula-on rhegmatogenous retinal detachment (RRD) before and after surgery.
Methods: In this case-series study, PAT was detected by en-face optical coherence tomography images with custom slabs in eyes that underwent pars plana vitrectomy and SF6 for macula-on RRD.Main outcome measures were PAT area at baseline, 3-month and 6-month follow-up, and its relative change.
Stem Cell Reports
December 2024
Department of Cardio Metabolic Diseases Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany. Electronic address:
Complement factor H (CFH) common genetic variants have been associated with age-related macular degeneration (AMD). While most previous in vitro RPE studies focused on the common p.His402Tyr CFH variant, we characterized rare CFH variants that are highly penetrant for AMD using induced pluripotent stem-cell-derived retinal pigment epithelium (iPSC-RPE).
View Article and Find Full Text PDFPLoS One
January 2025
School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China.
Optical Coherence Tomography (OCT) offers high-resolution images of the eye's fundus. This enables thorough analysis of retinal health by doctors, providing a solid basis for diagnosis and treatment. With the development of deep learning, deep learning-based methods are becoming more popular for fundus OCT image segmentation.
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