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Statement Of Problem: Clinical studies evaluating the levels of interleukin-1 beta (IL-1β) in tears and conjunctival secretions of patients with ocular defects after using ocular prostheses are lacking. Therefore, a comparative evaluation of IL-1β levels in the defective eye before and after placement of an ocular prosthesis is needed.
Purpose: The purpose of this clinical study was to compare the microbiota and IL-1β in tears and conjunctival secretions of patients with an ocular defect after using an ocular prosthesis.
Material And Methods: Patients visiting the prosthodontic department for the rehabilitation of an eye defect that could be restored with an ocular prosthesis were screened with predetermined inclusion and exclusion criteria. Twenty participants were enrolled in the study, and written informed consent was obtained. An ocular prosthesis was provided for each participant to manage anophthalmia. Tear samples for the evaluation of microbiota and IL-1β levels were collected from each participant from the healthy and the defective eye before and after using the ocular prosthesis. The culture method was used to identify microbiotas, and the IL-1β was quantified using an enzyme-linked immunosorbent assay sandwich kit. The obtained data of all parameters were tabulated and compared by using a statistical software program (α=.05).
Results: A statistically significant difference was observed on comparing microbiota and the levels of IL-1β, with a significant increase in the levels after the ocular prosthesis was provided (P<.05).
Conclusions: Levels of IL-1 β in the test group increased as compared with the control group. The increase might be attributed to the inflammatory changes as a result of change in microbiota.
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http://dx.doi.org/10.1016/j.prosdent.2024.12.009 | DOI Listing |
Alzheimers Dement
September 2025
Department of Neurology, Beijing TianTan Hospital, Capital Medical University, Beijing, China.
Cognitive impairment and dementia, including Alzheimer's disease (AD), pose a global health crisis, necessitating non-invasive biomarkers for early detection. This review highlights the retina, an accessible extension of the central nervous system (CNS), as a window to cerebral pathology through structural, functional, and molecular alterations. By synthesizing interdisciplinary evidence, we identify retinal biomarkers as promising tools for early diagnosis and risk stratification.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
Global Health Economics Centre, Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Background: Artificial intelligence (AI) algorithms offer an effective solution to alleviate the burden of diabetic retinopathy (DR) screening in public health settings. However, there are challenges in translating diagnostic performance and its application when deployed in real-world conditions.
Objective: This study aimed to assess the technical feasibility of integration and diagnostic performance of validated DR screening (DRS) AI algorithms in real-world outpatient public health settings.
AJNR Am J Neuroradiol
September 2025
From the Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America (J.S.S., B.M., S.H., A.H., J.S.), and Department of Aerospace Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (H.S.).
Background And Purpose: The choroid of the eye is a rare site for metastatic tumor spread, and as small lesions on the periphery of brain MRI studies, these choroidal metastases are often missed. To improve their detection, we aimed to use artificial intelligence to distinguish between brain MRI scans containing normal orbits and choroidal metastases.
Materials And Methods: We present a novel hierarchical deep learning framework for sequential cropping and classification on brain MRI images to detect choroidal metastases.
Retina
September 2025
Department of Ophthalmology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 15, CH-3010.
Purpose: To evaluate inter-grader variability in posterior vitreous detachment (PVD) classification in patients with epiretinal membrane (ERM) and macular hole (MH) on spectral-domain optical coherence tomography (SD-OCT) and identify challenges in defining a reliable ground truth for artificial intelligence (AI)-based tools.
Methods: A total of 437 horizontal SD-OCT B-scans were retrospectively selected and independently annotated by six experienced ophthalmologists adopting four categories: 'full PVD', 'partial PVD', 'no PVD', and 'ungradable'. Inter-grader agreement was assessed using pairwise Cohen's kappa scores.