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What about the Workers? An Update.
J Radiol Prot
January 2025
The University of Manchester, Manchester, M13 9PL, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
Epidemiological studies of nuclear industry workers are of substantial importance to understanding the risk of cancer consequent to low-level exposure to radiation, and these studies should provide vital evidence for the construction of the international system of radiological protection. Recent studies involve large numbers of workers and include health outcomes for workers who accumulated moderate (and even high) doses over prolonged periods while employed during the earlier years of the nuclear industry. The interpretation of the findings of these recent studies has proved to be disappointingly difficult.
View Article and Find Full Text PDFEffect of konjac glucomannan aerogel-immobilized Chlorella vulgaris LH-1 on oil-contaminated seawater remediation and endogenous bacterial community diversity.
Water Environ Res
January 2025
Zhejiang Key Laboratory of Petrochemical Environmental Pollution Control, Zhejiang Ocean University, Zhoushan, P. R. China.
Ocean oil spills can severely impact ecosystems and disrupt marine biodiversity and habitats. Microbial remediation is an effective method for removing thin oil slick contamination. In this study, the adsorption and degradation of low-concentration oil spills by Chlorella vulgaris LH-1 immobilized in konjac glucomannan (KGM) aerogel were investigated.
View Article and Find Full Text PDFConfined growth by self-combustion of a Cu-based nanophase into mesostructured acid supports for DME production from CO2.
Chempluschem
January 2025
Universita degli Studi Di Cagliari, Chemical and Geological Science, S.S. 554 bivio per Sestu, 09042, Monserrato, ITALY.
This work deals with the design of nanocomposite hydrogenation-dehydration bifunctional catalysts for the one-pot conversion of CO2 to dimethyl ether (DME), focusing on obtaining a high and homogeneous dispersion of a Cu-based CO2 hydrogenation phase into the pores of mesostructured supports. Particularly, three aluminosilicate mesostructured acid catalysts with catalytic activity towards methanol dehydration and featuring different porous structures (Al-MCM-41, Al-SBA-15, Al-SBA-16) were synthesized and used as supports to host a CuO/ZnO/ZrO2 (CZZ) CO2 hydrogenation catalyst for methanol synthesis. The use of a mesostructured support allows to maximize the exposed surface of the CO2 reduction function by nanostructuring it through its confinement within the mesochannels, thus obtaining nanocomposite bifunctional catalysts with an ultra-small hydrogenation nanophase.
View Article and Find Full Text PDFScanner-based real-time three-dimensional brain + body slice-to-volume reconstruction for T2-weighted 0.55-T low-field fetal magnetic resonance imaging.
Pediatr Radiol
January 2025
Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, SE1 7EH, UK.
Background: Motion correction methods based on slice-to-volume registration (SVR) for fetal magnetic resonance imaging (MRI) allow reconstruction of three-dimensional (3-D) isotropic images of the fetal brain and body. However, all existing SVR methods are confined to research settings, which limits clinical integration. Furthermore, there have been no reported SVR solutions for low-field 0.
View Article and Find Full Text PDFIdentify potential drug candidates within a high-quality compound search space.
Brief Bioinform
November 2024
The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, No. 100, Minjiang Avenue, Smart New Town, Quzhou, Zhejiang Province, 324000, China.
The identification of potential effective drug candidates is a fundamental step in new drug discovery, with profound implications for pharmaceutical research and the healthcare sector. While many computational methods have been developed for such predictions and have yielded promising results, two challenges persist: (i) The cold start problem of new drugs, which increases the difficulty of prediction due to lack of historical data or prior knowledge. (ii) The vastness of the compound search space for potential drug candidates.
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