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Non-metallic iodine single-atom catalysts with optimized electronic structures for efficient Fenton-like reactions.
Nat Commun
January 2025
State Environmental Protection Key Laboratory of Environmental Health Impact Assessment of Emerging Contaminants, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China.
In this study, we introduce a highly effective non-metallic iodine single-atom catalyst (SAC), referred to as I-NC, which is strategically confined within a nitrogen-doped carbon (NC) scaffold. This configuration features a distinctive C-I coordination that optimizes the electronic structure of the nitrogen-adjacent carbon sites. As a result, this arrangement enhances electron transfer from peroxymonosulfate (PMS) to the active sites, particularly the electron-deficient carbon.
View Article and Find Full Text PDFPrepartum supplementation of Ascophyllum nodosum meal or ethylenediamine dihydroiodide: Effects on colostrum yield and growth and health of dairy calves.
J Dairy Sci
January 2025
Department of Agriculture, Nutrition, and Food Systems, University of New Hampshire, Durham, NH 03824. Electronic address:
We aimed to evaluate the effects of prepartum supplementation of different I sources (Ascophyllum nodosum [ASCO] meal and ethylenediamine dihydroiodide [EDDI]) on colostrum yield of cows, and blood concentrations of glucose, BHB, and thyroid hormones and growth of dairy calves. Forty multiparous Holstein cows were blocked by lactation number and expected calving date and assigned to 1 of 4 treatments 28 d before parturition: (1) EDDI supplemented (11 mg/d) to a basal diet to meet the NRC (2001) I concentration of 0.5 mg of I/kg of DMI (control = CON [0 g/d of ASCO meal]; actual I concentration = 0.
View Article and Find Full Text PDFQuaternary Ammonium Compounds: A New Driver and Hidden Threat for Prevalence in Hospital Wastewater and Human Feces.
Environ Sci Technol
January 2025
National Key Laboratory of Veterinary Public Health and Safety, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
The emergence of mobile colistin resistance gene has attracted global attention. The prevalence of -positive (MCRPEC) in humans largely decreased following the ban of colistin as an animal growth promoter in China. However, the prevalence of MCRPEC in the hospital environment and the relationship between disinfectants and remain unclear.
View Article and Find Full Text PDFIodoform in Surgical Practice: A Comprehensive Review of Its Historical Evolution, Clinical Applications, and Safety Profiles.
Cureus
December 2024
Department of Neurosurgery, Hurley Medical Center, Flint, USA.
Iodoform, a halogenated organic compound, has been a cornerstone in surgical practice due to its potent antiseptic and antimicrobial properties. This comprehensive review examines the historical evolution, mechanism of action, clinical applications, and safety profile of iodoform across various surgical disciplines. Historically significant formulations like Whitehead's varnish and bismuth iodoform paraffin paste (BIPP) demonstrated remarkable efficacy in wound healing during the late 19th and early 20th centuries.
View Article and Find Full Text PDFEnd-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.
Open Heart
January 2025
Department of Molecular and Clinical Medicine, University of Gothenburg Institute of Medicine, Gothenburg, Sweden.
Purpose: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ECG-gated coronary CT angiography (CCTA) scans.
Methods: From a database of 6293 CCTA scans, we used pre-existing curved multiplanar reformations (CMR) images of the LAD, RCA and LCX arteries to create end-to-end deep-learning models for the detection of moderate or severe stenoses. We preprocessed the images by exploiting domain knowledge and employed a transfer learning approach using EfficientNet, ResNet, DenseNet and Inception-ResNet, with a class-weighted strategy optimised through cross-validation.
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