Background: The thyroid gland is a potential target organ for radiation-related damage. The aim of this analysis was to investigate the association between occupational exposure to ionizing radiation and the risk of autoimmune thyroid disease as well as thyroid nodules and dysfunction in workers of a former nuclear power station.
Methods: Seventy-one male power station workers 38 to 57 years of age who had been exposed to a lifetime dose in the upper allowed range (accumulated lifetime dose 70 to 400 mSv) were compared to a population-based sample of 670 males who were not exposed to occupational radiation. Thyroid ultrasound was performed by the same observers. Laboratory parameters were analyzed in a central laboratory.
Results: After controlling analyses for age and further relevant confounders no significant differences with respect to thyroid nodules and markers of autoimmune thyroid disease were detected between exposed and nonexposed individuals. However, nuclear power plant employees had higher odds for elevated serum thyrotropin (TSH) levels than the reference group (odds ratio 4.54; 95% confidence interval 1.43; 13.91).
Conclusions: Workers of a nuclear power plant with occupational exposure to ionizing radiation within the upper allowed dose range have an increased risk of elevated serum TSH levels. Further studies are required to confirm possible effects of occupational exposure to radiation on thyroid function.
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http://dx.doi.org/10.1089/thy.2006.16.1009 | DOI Listing |
Neuroradiol J
January 2025
Calgary Stroke Program, Department of Clinical Neurosciences and Radiology, University of Calgary, Canada.
Background And Purpose: Successful and complete reperfusion should be the aim of every endovascular thrombectomy (EVT) procedure. However, the effect of time delays on successful reperfusion in late window stroke patients presenting 6-to-24 h from onset has not been investigated.
Materials And Methods: We pooled individual patient-level data from seven trials and registries for anterior circulation stroke patients treated with EVT between 6 and 24 h from onset.
J Environ Radioact
January 2025
Institute of Nature and Environmental Technology, Kanazawa University, Kakuma, 920-1192, Kanazawa, Ishikawa, Japan.
Radionuclides, including I, were released into the atmosphere by the Fukushima nuclear power plant accident. We measured the dissolved I concentration in 11 rivers in eastern Fukushima from 2016 to 2020 to clarify the I concentration level in river water under base-flow conditions. During the study period, the maximum I concentration in the river water was 1.
View Article and Find Full Text PDFEur J Radiol Open
June 2025
Department of Nuclear Medicine, Medical Faculty and University Hospital Duesseldorf, Heinrich Heine University Duesseldorf, Düsseldorf 40225, Germany.
Objective: [F]FDG imaging is an integral part of patient management in CAR-T-cell therapy for recurrent or therapy-refractory DLBCL. The calculation methods of predictive power of specific imaging parameters still remains elusive. With this retrospective study, we sought to evaluate the predictive power of the baseline metabolic parameters and tumor burden calculated with automated segmentation via different thresholding methods for early therapy failure and mortality risk in DLBCL patients.
View Article and Find Full Text PDFMalting quality of barley is a complex characteristic, which is influenced by a combination of interacting traits that are regulated by various genetic and environmental factors. The activities of various enzymes play pivotal roles in determining the malting quality, as they drive the biochemical processes responsible for converting barley saccharides and proteins into fermentable sugars and amino acids during the malting process. In this study, 14 malting barley cultivars were used to investigate the relationship between enzyme activities and malting quality traits.
View Article and Find Full Text PDFNeurocomputing (Amst)
January 2025
Department of Electrical and Computer Engineering, University of Maryland at College Park, 8223 Paint Branch Dr, College Park, MD, 20740, USA.
Inference using deep neural networks on mobile devices has been an active area of research in recent years. The design of a deep learning inference framework targeted for mobile devices needs to consider various factors, such as the limited computational capacity of the devices, low power budget, varied memory access methods, and I/O bus bandwidth governed by the underlying processor's architecture. Furthermore, integrating an inference framework with time-sensitive applications - such as games and video-based software to perform tasks like ray tracing denoising and video processing - introduces the need to minimize data movement between processors and increase data locality in the target processor.
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