retinal disorders
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2022 ◽  
Vol 12 ◽  
Author(s):  
Etelka Pöstyéni ◽  
Alma Ganczer ◽  
Andrea Kovács-Valasek ◽  
Robert Gabriel

The mammalian retina contains approximately 30 neuropeptides that are synthetized by different neuronal cell populations, glia, and the pigmented epithelium. The presence of these neuropeptides leaves a mark on normal retinal molecular processes and physiology, and they are also crucial in fighting various pathologies (e.g., diabetic retinopathy, ischemia, age-related pathologies, glaucoma) because of their protective abilities. Retinal pathologies of different origin (metabolic, genetic) are extensively investigated by genetically manipulated in vivo mouse models that help us gain a better understanding of the molecular background of these pathomechanisms. These models offer opportunities to manipulate gene expression in different cell types to help reveal their roles in the preservation of retinal health or identify malfunction during diseases. In order to assess the current status of transgenic technologies available, we have conducted a literature survey focused on retinal disorders of metabolic origin, zooming in on the role of retinal neuropeptides in diabetic retinopathy and ischemia. First, we identified those neuropeptides that are most relevant to retinal pathologies in humans and the two clinically most relevant models, mice and rats. Then we continued our analysis with metabolic disorders, examining neuropeptide-related pathways leading to systemic or cellular damage and rescue. Last but not least, we reviewed the available literature on genetically modified mouse strains to understand how the manipulation of a single element of any given pathway (e.g., signal molecules, receptors, intracellular signaling pathways) could lead either to the worsening of disease conditions or, more frequently, to substantial improvements in retinal health. Most attention was given to studies which reported successful intervention against specific disorders. For these experiments, a detailed evaluation will be given and the possible role of converging intracellular pathways will be discussed. Using these converging intracellular pathways, curative effects of peptides could potentially be utilized in fighting metabolic retinal disorders.


PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0261897
Author(s):  
Marlene Glatz ◽  
Regina Riedl ◽  
Wilfried Glatz ◽  
Mona Schneider ◽  
Andreas Wedrich ◽  
...  

Purpose To assess the prevalence and causes of visual impairment and blindness in a Central European country. The findings may have implications for the planning of further research and development of therapies in order to prevent blindness. Setting Department of Ophthalmology, Medical University of Graz, Austria. Design Retrospective, epidemiological study. Methods The database of the Main Confederation of Austrian Social Insurances was searched for patients with visual impairment, legal blindness or deaf-blindness. This database gathers data from patients of all insurance providers in the country who receive care due to visual impairment and blindness. To determine the prevalence of these conditions, the number of all entries recorded in February 2019 was evaluated. Additionally, all new entries between (January 1st,) 2017, and (December 31st,) 2018, were analysed for distinct characteristics, such as sex, the cause of blindness/visual impairment, and age. Since health care allowances can provide a considerable source of income (459.90€-936.90€ per month), good coverage of practically all patients who are blind and visually impaired in the country can be assumed. Results On February 2nd, 2019, 17,730 patients with visual impairments, blindness or deaf-blindness were registered in Austria, resulting in a prevalence of these diagnoses of 0.2% in the country. During the observational period from 2017 to 2018, 4040 persons met the inclusion criteria. Of these, 2877 were female (65.3%), and 1527 were male (34.7%). The mean age was 75.7 ± 18.0 years (median 82). Most patients (n = 3675, 83.4%) were of retirement age, while 729 (16.6%) were working-age adults or minors. In total, an incidence of 25.0 (95% confidence limit (CL) 24.3–25.8) per 100,000 person-years was observed from 2017 to 2018. A higher incidence was observed for females (32.2, 95% CL 31.0–33.3) than for males (17.7, 95% CL 16.8–18.5). Incidences where higher for males in lower age groups (e.g. 10–14 years: rate ratio RR = 2.7, 95% CL 1.1–6.8), and higher for females in higher age groups (e.g. 70–74 years: RR = 0.6, 95% CL 0.5–0.8). In total, the most frequent diagnoses were macular degeneration (1075 persons, 24.4%), other retinal disorders (493 persons, 11.2%) and inherited retinal and choroidal diseases (IRDs) (186 persons, 4.2%). Persons with IRDs were significantly younger compared to persons with macular degeneration or retinal disorders (IRDs: median 57, range 2–96 vs 83, 5–98 and 82, 1–98 years, p<0.001). For persons of retirement age, macular degeneration, other retinal disorders and glaucoma were the three most frequent diagnoses. In contrast, among working-aged adults and children, IRDs were the leading cause of visual impairment and blindness (103 persons, 14.1%). Conclusion These data show that IRDs are the leading cause of blindness and visual impairment in working-aged persons and children in Austria. Thus, these findings suggest to draw attention to enhance further research in the fields of emerging therapies for IRDs.


2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Yang Yu ◽  
Licheng Li ◽  
Shu Lin ◽  
Jianmin Hu

AbstractAge-related macular degeneration, diabetic retinopathy, retinitis pigmentosa and other retinal disorders are the main causes of visual impairment worldwide. In the past, these retinal diseases, especially dry age-related macular degeneration, proliferative diabetic retinopathy and retinitis pigmentosa, were treated with traditional surgery and drugs. However, the effect was moderate. In recent years, researchers have used embryonic stem cells, induced pluripotent stem cells, mesenchymal stem cells, olfactory ensheathing cells and other stem cells to conduct experiments and found that stem cells can inhibit inflammation, regulate immune response, secrete neurotrophic factors, and differentiate into retinal cells to replace and promote restoration of the damaged parts. These stem cells have the potential to treat retinal diseases. Whether it is in animal experiments or clinical trials, the increase in the number of retinal cells, maintenance of function and improvement of visual function all reflect the advanced of stem cells to treat retinal diseases, but its risk preserves the donor’s hidden pathogenic genes, immune rejection and tumorigenicity. With the development of exosomes study, researchers have discovered that exosomes come from a wide range of sources and can be secreted by almost all types of cells. Using exosomes with stem cell to treat retinal diseases is more effective than using stem cells alone. This review article summarizes the recent advances in the application of olfactory ensheathing cells and stem cells/exosomes in the treatment of retinal disorders.


Cells ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 60
Author(s):  
Manuela Santo ◽  
Ivan Conte

Lysosomes are membrane-bound cell organelles that respond to nutrient changes and are implicated in cell homeostasis and clearance mechanisms, allowing effective adaptation to specific cellular needs. The relevance of the lysosome has been elucidated in a number of different contexts. Of these, the retina represents an interesting scenario to appreciate the various functions of this organelle in both physiological and pathological conditions. Growing evidence suggests a role for lysosome-related mechanisms in retinal degeneration. Abnormal lysosomal activation or inhibition has dramatic consequences on photoreceptor cell homeostasis and impacts extensive cellular function, which in turn affects vision. Based on these findings, a series of therapeutic methods targeting lysosomal processes could offer treatment for blindness conditions. Here, we review the recent findings on membrane trafficking, subcellular organization, mechanisms by which lysosome/autophagy pathway impairment affects photoreceptor cell homeostasis and the recent advances on developing efficient lysosomal-based therapies for retinal disorders.


2021 ◽  
Vol 12 (1) ◽  
pp. 7
Author(s):  
Muhammad Arsalan ◽  
Adnan Haider ◽  
Jiho Choi ◽  
Kang Ryoung Park

Retinal blood vessels are considered valuable biomarkers for the detection of diabetic retinopathy, hypertensive retinopathy, and other retinal disorders. Ophthalmologists analyze retinal vasculature by manual segmentation, which is a tedious task. Numerous studies have focused on automatic retinal vasculature segmentation using different methods for ophthalmic disease analysis. However, most of these methods are computationally expensive and lack robustness. This paper proposes two new shallow deep learning architectures: dual-stream fusion network (DSF-Net) and dual-stream aggregation network (DSA-Net) to accurately detect retinal vasculature. The proposed method uses semantic segmentation in raw color fundus images for the screening of diabetic and hypertensive retinopathies. The proposed method’s performance is assessed using three publicly available fundus image datasets: Digital Retinal Images for Vessel Extraction (DRIVE), Structured Analysis of Retina (STARE), and Children Heart Health Study in England Database (CHASE-DB1). The experimental results revealed that the proposed method provided superior segmentation performance with accuracy (Acc), sensitivity (SE), specificity (SP), and area under the curve (AUC) of 96.93%, 82.68%, 98.30%, and 98.42% for DRIVE, 97.25%, 82.22%, 98.38%, and 98.15% for CHASE-DB1, and 97.00%, 86.07%, 98.00%, and 98.65% for STARE datasets, respectively. The experimental results also show that the proposed DSA-Net provides higher SE compared to the existing approaches. It means that the proposed method detected the minor vessels and provided the least false negatives, which is extremely important for diagnosis. The proposed method provides an automatic and accurate segmentation mask that can be used to highlight the vessel pixels. This detected vasculature can be utilized to compute the ratio between the vessel and the non-vessel pixels and distinguish between diabetic and hypertensive retinopathies, and morphology can be analyzed for related retinal disorders.


2021 ◽  
Author(s):  
Muhammad Zubair Khan ◽  
Yugyung Lee ◽  
Arslan Munir ◽  
Muazzam Ali Khan

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1651
Author(s):  
Prabal Datta Barua ◽  
Wai Yee Chan ◽  
Sengul Dogan ◽  
Mehmet Baygin ◽  
Turker Tuncer ◽  
...  

Optical coherence tomography (OCT) images coupled with many learning techniques have been developed to diagnose retinal disorders. This work aims to develop a novel framework for extracting deep features from 18 pre-trained convolutional neural networks (CNN) and to attain high performance using OCT images. In this work, we have developed a new framework for automated detection of retinal disorders using transfer learning. This model consists of three phases: deep fused and multilevel feature extraction, using 18 pre-trained networks and tent maximal pooling, feature selection with ReliefF, and classification using the optimized classifier. The novelty of this proposed framework is the feature generation using widely used CNNs and to select the most suitable features for classification. The extracted features using our proposed intelligent feature extractor are fed to iterative ReliefF (IRF) to automatically select the best feature vector. The quadratic support vector machine (QSVM) is utilized as a classifier in this work. We have developed our model using two public OCT image datasets, and they are named database 1 (DB1) and database 2 (DB2). The proposed framework can attain 97.40% and 100% classification accuracies using the two OCT datasets, DB1 and DB2, respectively. These results illustrate the success of our model.


2021 ◽  
Vol Volume 15 ◽  
pp. 4591-4605
Author(s):  
Francesca Simonelli ◽  
Andrea Sodi ◽  
Benedetto Falsini ◽  
Giacomo Bacci ◽  
Giancarlo Iarossi ◽  
...  

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