Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.2
3.9
Journals
Biomedicines
Special Issues
Emerging Issues in Retinal Degeneration
share announcement

Emerging Issues in Retinal Degeneration

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cell Biology and Pathology".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 1468

Special Issue Editor

Dr. Ponarulselvam Sekar

E-Mail Website
Guest Editor
Department of Ophthalmology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany
Interests: neuroretina pathologies; ocular oncology; purinergic signaling; mitochondrial dynamics in retina

Special Issue Information

Dear Colleagues,

Retinal degeneration includes a spectrum of progressive eye diseases such as age-related macular degeneration (AMD), retinitis pigmentosa (RP) and diabetic retinopathy, all of which can result in significant vision loss or blindness. As the global population ages and diabetes becomes more prevalent, these conditions are emerging as critical public health challenges. This Special Issue is dedicated to showcasing the latest advancements and addressing new challenges in the study of retinal degeneration.

We encourage researchers and clinicians to submit original research papers, reviews and case reports that delve into innovative diagnostic techniques, cutting-edge therapeutic strategies and the fundamental molecular pathways involved in retinal degeneration. The areas of interest encompass gene therapy, stem cell therapy, retinal implants and new pharmacological treatments. We also welcome contributions that examine the effects of lifestyle and environmental factors on disease progression, the identification of predictive biomarkers and enhancements in imaging technology.

The aim of this Special Issue is to present a thorough overview of contemporary trends and future directions in retinal degeneration research. By promoting interdisciplinary collaboration and the exchange of knowledge, we strive to enhance our understanding and treatment of these debilitating diseases, thereby improving the outcomes and quality of life for patients.

Dr. Ponarulselvam Sekar
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • retinal degeneration
  • age-related macular degeneration (AMD)
  • retinitis pigmentosa (RP)
  • diabetic retinopathy
  • gene therapy
  • stem cell therapy
  • retinal implants
  • pharmacological treatments
  • diagnostic methods
  • molecular mechanisms
  • predictive biomarkers
  • imaging technologies
  • signaling pathways
  • oxidative stress
  • neuroprotection

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

10 pages, 719 KiB  
Article
Investigation of UCHL3 and HNMT Gene Polymorphisms in Greek Patients with Type 2 Diabetes Mellitus and Diabetic Retinopathy
by Konstantinos Flindris, Vivian Lagkada, Aikaterini Christodoulou, Maria Gazouli, Marilita Moschos, Georgios Markozannes and George Kitsos
Biomedicines 2025, 13(2), 341; https://doi.org/10.3390/biomedicines13020341 - 3 Feb 2025
Viewed by 78
Abstract
Background and Objectives: Recent studies have shed light on the association between genetic factors and diabetic retinopathy (DR) onset and progression. The purpose of our study was to investigate the association between rs4885322 single-nucleotide polymorphism (SNP) of the UCHL3 gene and rs11558538 SNP [...] Read more.
Background and Objectives: Recent studies have shed light on the association between genetic factors and diabetic retinopathy (DR) onset and progression. The purpose of our study was to investigate the association between rs4885322 single-nucleotide polymorphism (SNP) of the UCHL3 gene and rs11558538 SNP of the HNMT gene with the risk of DR in Greek patients with type 2 diabetes mellitus (T2DM). Materials and Methods: In our case–control study, we included 85 T2DM patients with DR and 71 T2DM patients without DR (NDR), matched by ethnicity and gender. Demographic and clinical data of all patients were collected, and then patients went through a complete ophthalmological examination and were genotyped for rs4885322 SNP of UCHL3 gene and for the rs11558538 SNP of HNMT gene. Statistical analysis was implemented by STATA v.16.1. Results: No significant differences in demographic and clinical data were observed between the DR and the NDR group (p-value ≥ 0.05), except for the lower mean of age, longer duration of DM, more frequent use of insulin therapy, and higher levels of hemoglobin A1c (HbA1c) in the DR group. The allelic effect of rs488532 increases the risk of DR by 2.04 times, and in the dominant genetic model, the risk of DR is elevated by 123%, while both associations are statistically significant (p-value < 0.05). Moreover, the allelic effect of rs11558538 is associated with a 3.27 times increased DR risk and, in the dominant genetic model, reveals an augmented risk of DR by 231%, while both associations are also statistically significant (p-value < 0.05). Conclusions: The rs4885322 SNP of the UCHL3 gene and the rs11558538 SNP of the HNMT gene are associated with DR risk in Greek patients with T2DM. However, further studies with larger samples and different ethnicities should be implemented to clarify the exact association of these SNPs and DR onset. Full article
(This article belongs to the Special Issue Emerging Issues in Retinal Degeneration)
►▼ Show Figures

Figure 1

15 pages, 8206 KiB  
Article
Fundus Image Deep Learning Study to Explore the Association of Retinal Morphology with Age-Related Macular Degeneration Polygenic Risk Score
by Adam Sendecki, Daniel Ledwoń, Aleksandra Tuszy, Julia Nycz, Anna Wąsowska, Anna Boguszewska-Chachulska, Andrzej W. Mitas, Edward Wylęgała and Sławomir Teper
Biomedicines 2024, 12(9), 2092; https://doi.org/10.3390/biomedicines12092092 - 13 Sep 2024
Viewed by 1134
Abstract
Background: Age-related macular degeneration (AMD) is a complex eye disorder with an environmental and genetic origin, affecting millions worldwide. The study aims to explore the association between retinal morphology and the polygenic risk score (PRS) for AMD using fundus images and deep learning [...] Read more.
Background: Age-related macular degeneration (AMD) is a complex eye disorder with an environmental and genetic origin, affecting millions worldwide. The study aims to explore the association between retinal morphology and the polygenic risk score (PRS) for AMD using fundus images and deep learning techniques. Methods: The study used and pre-processed 23,654 fundus images from 332 subjects (235 patients with AMD and 97 controls), ultimately selecting 558 high-quality images for analysis. The fine-tuned DenseNet121 deep learning model was employed to estimate PRS from single fundus images. After training, deep features were extracted, fused, and used in machine learning regression models to estimate PRS for each subject. The Grad-CAM technique was applied to examine the relationship between areas of increased model activity and the retina’s morphological features specific to AMD. Results: Using the hybrid approach improved the results obtained by DenseNet121 in 5-fold cross-validation. The final evaluation metrics for all predictions from the best model from each fold are MAE = 0.74, MSE = 0.85, RMSE = 0.92, R2 = 0.18, MAPE = 2.41. Grad-CAM heatmap evaluation showed that the model decisions rely on lesion area, focusing mostly on the presence of drusen. The proposed approach was also shown to be sensitive to artifacts present in the image. Conclusions: The findings indicate an association between fundus images and AMD PRS, suggesting that deep learning models may effectively estimate genetic risk for AMD from retinal images, potentially aiding in early detection and personalized treatment strategies. Full article
(This article belongs to the Special Issue Emerging Issues in Retinal Degeneration)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop