Aims: Adropin (AD), copeptin (CP), neprilysin (NEP) and chitotriosidase (CHIT1) have been associated with the regulation of vascular endothelial function. In this work, we analyzed the plasma concentrations of cytokines (AD, CP, NEP and CHIT1) in type 2 diabetic patients with or without retinopathy (DR) to predict the risk of DR for diabetic patients.
Method: A total of 392 patients diagnosed as type 2 diabetes mellitus (T2DM) and 120 healthy volunteers as a control group were enrolled in this study. T2DM patients were divided into three groups: diabetes without retinopathy (NDR, n = 174) group, non-proliferative diabetic retinopathy (NPDR, n = 118) group and proliferative diabetic retinopathy (PDR, n = 100) group. The serum AD, CP, NEP and CHIT1 levels of subjects were detected by enzyme-linked immunosorbent assay (ELISA).
Results: We reported a significant decrease in AD and a significant increase in CP, NEP and CHIT1 in NDR as well as DR patients when compared with controls (p < 0.05), the lower level of AD and significantly higher levels of CP, NEP and CHIT1 were seen in DR patients compared to NDR group (p < 0.05), at the same time, we observed the lowest level of AD and the highest levels of CP, NEP and CHIT1 in the PDR group. Logistic regression analysis showed that AD was a protective factor for DR, conversely, CP, NEP and CHIT1 were the independent risk factors (p < 0.05). Moreover, receiver operating characteristic curve analyses indicated that CP had greater diagnosis capacity with an AUC (the areas under the ROC curve) of 0.901 than AD, NEP, CHIT1 for DR patients.
Conclusion: The decreased AD level and the elevated CP, NEP and CHIT1 levels involved in vascular endothelial function may be evidence facilitating the presence of DR. Thereby they can be explored to use as promising non-invasive biomarkers for prediction of DR severity, distinguishing DR from diabetic patients.
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http://dx.doi.org/10.1016/j.jdiacomp.2020.107686 | DOI Listing |
Taiwan J Ophthalmol
November 2024
Sirindhorn International Institute of Technology, Thammasat University, Bangkok, Thailand.
Recent advances of artificial intelligence (AI) in retinal imaging found its application in two major categories: discriminative and generative AI. For discriminative tasks, conventional convolutional neural networks (CNNs) are still major AI techniques. Vision transformers (ViT), inspired by the transformer architecture in natural language processing, has emerged as useful techniques for discriminating retinal images.
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December 2024
Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Wide field retinal imaging has emerged as a transformative technology over the last few decades, revolutionizing our ability to visualize the intricate landscape of the retina. By capturing expansive retinal areas, these techniques offer a panoramic view going beyond traditional imaging methods. In this review, we explore the significance of retinal imaging-based biomarkers to help diagnose ocular and systemic conditions.
View Article and Find Full Text PDFTaiwan J Ophthalmol
November 2024
Shri Bhagwan Mahavir Vitreoretinal Services, Sankara Nethralaya, Tamil Nadu, India.
Purpose: This study aimed to evaluate serum cystatin C as a potential biomarker for diabetic retinopathy (DR) in a rural Indian population, addressing the urgent need for effective screening tools amidst rising diabetes prevalence.
Materials And Methods: A cross-sectional study recruited 112 patients with diabetes mellitus from Sambalpur, Odisha, India, categorized into groups with and without DR. Serum cystatin C levels were measured alongside clinical and demographic parameters, using established diagnostic methods.
Taiwan J Ophthalmol
January 2024
Smt. Kanuri Santhamma Center for Vitreoretinal Diseases, Anant Bajaj Retina Institute, LV Prasad Eye Institute, Hyderabad, Telangana, India.
Diabetic retinopathy is one of the most severe forms of retinopathy and a leading cause of blindness all over the world. Of a greater concern is proliferative diabetic retinopathy which leads to vitreous haemorrhage and tractional retinal detachment in such cases. A majority of these cases require a surgical intervention to improve vision and prevent further vision loss.
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June 2025
Assistant Professor, Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Tamil Nadu, 600062, India.
Glaucoma, a severe eye disease leading to irreversible vision loss if untreated, remains a significant challenge in healthcare due to the complexity of its detection. Traditional methods rely on clinical examinations of fundus images, assessing features like optic cup and disc sizes, rim thickness, and other ocular deformities. Recent advancements in artificial intelligence have introduced new opportunities for enhancing glaucoma detection.
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