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This study focuses on the synthesis of a novel Cerium-Magnesium (CeO-MgO) binary oxide nanomaterials by a simple co-precipitation process and used to remove harmful pollutants such as Cr(VI), Cu(II), and F. The morphology, phase, crystallite size, thermal stability, functional groups, surface area, and porosity of the synthesized nanomaterial were determined by using XRD, SEM, FTIR, TGA/DTA, and BET studies. The prepared nanomaterials showed adsorption selectivity of Cu(II) ≈ F> Cr(VI) with a high adsorption capacity of 84.

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Objectives: The high incidence of coronary artery heart disease (CHD) poses a significant burden and challenge to public health systems globally. Effective prevention and early diagnosis of CHD have become key strategies to alleviate this burden. This study aims to explore the application of advanced machine learning techniques to enhance the accuracy of early screening and risk assessment for CHD.

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Background: Traditionally, urine analysis of calcium (Ca), magnesium (Mg) and phosphate (Phos) requires acidification of the sample. This study aims to assess the need for acidification and evaluate preanalytical factors that influence the accurate measurement of these analytes in urine.

Results: A total of 107 spot urine samples from patients with a median age of 9 years (95 % ≤ 21 years of age, range 5 days to 46 years) were analyzed for Ca (n = 94), Mg (n = 97), and Phos (n = 102) with and without acidification.

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Background: Kidney stone disease is a common surgical disease and significant public health issue, may be influenced by environmental factors such as domestic water hardness and its related minerals. Previous studies have shown inconsistent and controversial results regarding the impact of domestic water hardness on kidney stone formation.

Methods: This prospective cohort study analyzed data from 288,041 participants in the UK Biobank with no prior history of kidney stones from 2006-2024.

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