The aim of the present ring trial was to test whether two new methodological approaches for the in vitro classification of eye irritating chemicals can be reliably transferred from the developers' laboratories to other sites. Both test methods are based on the well-established open source reconstructed 3D hemicornea models. In the first approach, the initial depth of injury after chemical treatment in the hemicornea model is derived from the quantitative analysis of histological sections. In the second approach, tissue viability, as a measure for corneal damage after chemical treatment, is analyzed separately for epithelium and stroma of the hemicornea model. The three independent laboratories that participated in the ring trial produced their own hemicornea models according to the test producer's instructions, thus supporting the open source concept. A total of 9 chemicals with different physicochemical and eye-irritating properties were tested to assess the between-laboratory reproducibility (BLR), the predictive performance, as well as possible limitations of the test systems. The BLR was 62.5% for the first and 100% for the second method. Both methods enabled to discriminate Cat. 1 chemicals from all non-Cat. 1 substances, which qualifies them to be used in a top-down approach. However, the selectivity between No Cat. and Cat. 2 chemicals still needs optimization.
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http://dx.doi.org/10.14573/altex.1610311 | DOI Listing |
Arch Dermatol Res
January 2025
Department of Dermatology, Drexel University College of Medicine, 860 1St Avenue, Suite 8B, Philadelphia, PA, 19406, USA.
UV-A exposure is a major risk factor for melanoma, nonmelanoma skin cancer, photoaging, and exacerbation of photodermatoses. Since people spend considerable time in cars daily, inadequate UV-A attenuation by car windows can significantly contribute to the onset or exacerbation of these skin diseases. Given recent market trends in the automobile industry and known impact of car windows on cumulative lifelong UV damage to the skin, there is a need to comparatively evaluate UV transmission across windows in electric vehicles (EV), hybrid vehicles (HV), and gas vehicles (GV) as well as variability based on year of manufacture and mileage to inform car manufacturers and consumers of the potential for UV exposure to the skin based on vehicle.
View Article and Find Full Text PDFAm J Sports Med
January 2025
American Hip Institute Research Foundation, Des Plaines, Illinois, USA.
Background: Sex has been associated with different pathologic characteristics in painful hips undergoing hip arthroscopic surgery.
Purpose: To compare minimum 10-year patient-reported outcomes (PROs) and survivorship in patients who underwent primary hip arthroscopic surgery for femoroacetabular impingement syndrome and labral tears according to sex.
Study Design: Cohort study; Level of evidence, 3.
BMC Public Health
January 2025
Epidemiology Program, Institute of Health Sciences, Istanbul Medipol University, Istanbul, Türkiye.
Introduction: This study aims to investigate the knowledge, attitudes, and behaviors of Syrian migrant women regarding breast and cervical cancer screenings in the Sultanbeyli district of Istanbul.
Methods: The women were recruited from Extended Migrant Health Centre, which is a primary health care institution in Istanbul. In August 2024, face-to-face interviews were conducted using an open-ended, semi-structured question form administered by a nurse experienced in qualitative research.
BMC Med Res Methodol
January 2025
Biostatistics Research Group, Department of Population Health Sciences, University of Leicester, Leicester, UK.
Background: Since 2015, the Complex Reviews Synthesis Unit (CRSU) has developed a suite of web-based applications (apps) that conduct complex evidence synthesis meta-analyses through point-and-click interfaces. This has been achieved in the R programming language by combining existing R packages that conduct meta-analysis with the shiny web-application package. The CRSU apps have evolved from two short-term student projects into a suite of eight apps that are used for more than 3,000 h per month.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
School of Mechanical Engineering, Shandong University, Jinan, China.
Extensive research on retinal layer segmentation (RLS) using deep learning (DL) is mostly approaching a performance plateau, primarily due to reliance on structural information alone. To address the present situation, we conduct the first study on the impact of multi-spectral information (MSI) on RLS. Our experimental results show that incorporating MSI significantly improves segmentation accuracy for retinal layer optical coherence tomography (OCT) images.
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