The psychological impact of vision loss due to diabetic retinopathy is compounded by the loss of diabetes self-management skills. The appropriate role and timing for rehabilitative intervention has not been determined. Twenty-nine individuals with diabetes mellitus, 16 with stable visual impairment and 13 with fluctuating and transitional visual impairment, underwent psychological assessment before and after entering into a specially designed rehabilitation program. Low levels of performance were rehabilitation program. Low levels of performance were demonstrated by the Rosenberg Self-Esteem Scale and the Diabetes Self-Reliance Test in both groups. The Minnesota Multiphasic Personality Inventory, the Zung Self-Rating Depression Scale, and the Rand Mental Health Index suggested that subjects with stable vision impairment were moderately compensated relative to the transitional group, although the former group may have been totally blind. Both groups demonstrated significant improvements in psychological profiles after the program. It is suggested that a rehabilitation program may be of clinical benefit early in the course of vision loss associated with diabetic retinopathy.
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http://dx.doi.org/10.2337/diacare.11.7.551 | DOI Listing |
West Afr J Med
September 2024
Department of Ophthalmology, University of Calabar, Calabar, Cross River State, Nigeria.
Background: Strabismus is a potential cause of ocular morbidity.
Objective: The aim of this study was to determine the frequency, types of manifest strabismus and co-morbidities among patients attending a referral paediatric ophthalmology and strabismus clinic in Calabar, Nigeria.
Methods: A retrospective review of case-notes of patients attending the paediatric ophthalmology and strabismus clinic from January 1, 2017 to December 31, 2019 was done.
Viruses
December 2024
Beijing Youcare Kechuang Pharmaceutical Technology Co., Ltd., Beijing 100176, China.
Human respiratory syncytial virus (RSV) remains a significant global health threat, particularly for vulnerable populations. Despite extensive research, effective antiviral therapies are still limited. To address this urgent need, we present AVP-GPT2, a deep-learning model that significantly outperforms its predecessor, AVP-GPT, in designing and screening antiviral peptides.
View Article and Find Full Text PDFPharmaceutics
January 2025
Centre for Public Health, Institute of Clinical Sciences, School of Medicine, Queen's University Belfast, Belfast BT7 1NN, UK.
Background/objectives: The visual acuity (VA) outcomes after the first and second years of anti-vascular endothelial growth factor (anti-VEGF) treatment in patients with diabetic macular oedema (DMO) were evaluated, and the factors associated with treatment success were investigated.
Methods: Using Medisoft electronic medical records (UK), this retrospective cohort study analysed VA outcomes, changes, and determinants in DMO patients at year 1 and year 2 after initial anti-VEGF injection. Descriptive analysis examined baseline demographics and clinical characteristics, while regression models were used to assess associations between these factors and changes in VA.
Pharmaceuticals (Basel)
January 2025
Department of Pharmacy Sciences, School of Pharmacy and Health Professions, Creighton University, Omaha, NE 68178, USA.
Inherited retinal disorders (IRDs) represent a group of challenging genetic conditions that often lead to severe visual impairment or blindness. The complexity of these disorders, arising from their diverse genetic causes and the unique structural and functional aspects of retinal cells, has made developing effective treatments particularly challenging. Recent advancements in gene therapy, especially non-viral nucleic acid delivery systems like liposomes, solid lipid nanoparticles, dendrimers, and polymersomes, offer promising solutions.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Key Laboratory of Modern Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Nanjing Institute of Agricultural Mechanization, Nanjing 210014, China.
To address several challenges, including low efficiency, significant damage, and high costs, associated with the manual harvesting of , in this study, a machine vision-based intelligent harvesting device was designed according to its agronomic characteristics and morphological features. This device mainly comprised a frame, camera, truss-type robotic arm, flexible manipulator, and control system. The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate .
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