Objective: To determine whether IARC's 2001 decision to downgrade the classification of insulation glass wool from Group 2B to Group 3 remains valid in light of epidemiological evidence reported after 2001.
Methods: We performed a systematic review of epidemiological evidence regarding respiratory cancer risks in relation to man-made vitreous fiber (MMVF) exposure before and after the 2001 IARC re-evaluation with focus on glass wool exposure and respiratory system cancer.
Results: Since 2001, three new community-based, case-control studies, two detailed analyses of existing cohort studies and two reviews/meta-analyses were published. These studies revealed no consistent evidence of an increased respiratory system cancer risk in relation to glass wool exposure.
Conclusions: From our evaluation of the epidemiological evidence published since 2001, we conclude that IARC's 2001 decision to downgrade insulation glass wool from Group 2B to Group 3 remains valid.
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http://dx.doi.org/10.1016/j.yrtph.2011.02.009 | DOI Listing |
Int J Mol Sci
December 2024
Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555, Japan.
Phosphate invert glasses (PIGs) have been attracting attention as materials for bone repair. PIGs have a high flexibility in chemical composition because they are composed of orthophosphate and pyrophosphate and can easily incorporate various ions in their glass networks. In our previous work, incorporation of niobium (Nb) into melt-quench-derived PIGs was effective in terms of controlling their ion release, and Nb ions promoted the activity of osteoblast-like cells.
View Article and Find Full Text PDFJ Pathol Inform
January 2025
U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging, Diagnostics, and Software Reliability, Silver Spring, MD, United States of America.
Objective: With the increasing energy surrounding the development of artificial intelligence and machine learning (AI/ML) models, the use of the same external validation dataset by various developers allows for a direct comparison of model performance. Through our High Throughput Truthing project, we are creating a validation dataset for AI/ML models trained in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple negative breast cancer (TNBC).
Materials And Methods: We obtained clinical metadata for hematoxylin and eosin-stained glass slides and corresponding scanned whole slide images (WSIs) of TNBC core biopsies from two US academic medical centers.
J Occup Environ Hyg
November 2024
Stantec, Cincinnati, Ohio.
A limited number of published studies have evaluated concentrations of airborne fibers in outdoor air, with even fewer assessing typical air concentrations in the ambient air near fiberglass wool manufacturing facilities. Building upon the assessment by Switala et al. (1994), area samples for airborne fiber concentrations (diameters of less than 3 µm, lengths greater than 5 µm, and aspect ratios equal to or greater than 5 to 1) were collected at fixed locations along the fence lines of three fiberglass wool manufacturing facilities in the United States.
View Article and Find Full Text PDFAnn Work Expo Health
November 2024
Center for Primary Care and Public Health Lausanne, Lausanne University, Route de la Corniche 2, 1066, Épalinges, Switzerland.
When comparing the particle emissivity for different materials and/or mechanical activities, a serious methodological issue emerges due to the dynamic nature of solid aerosols. Particle size distribution and concentration depend on initial particle emission that constantly evolves due to aerodynamic collisions. In this context, we propose a methodological approach and an experimental setup that enables to assess the release of fine/ultra-fine particles maintaining a steady-state inhalable mass concentration, here chosen at the Swiss occupational exposure level value for biopersistent granular particles (OEL: 10 mg/m3) in a controlled ventilation chamber.
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