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Machine learning-based prediction models for renal impairment in Chinese adults with hyperuricaemia: risk factor analysis.
Sci Rep
March 2025
Department of Endocrinology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, China.
In hyperuricaemic populations, multiple factors may contribute to impaired renal function. This study aimed to establish a machine learning-based model to identify characteristic factors related to renal impairment in hyperuricaemic patients, determine dose‒response relationships, and facilitate early intervention strategies. Data were collected through the big data platform of Nanjing Hospital of Traditional Chinese Medicine, encompassing 2,705 patients with hyperuricaemia (1,577 with renal impairment, 828 without) from June 2019 to June 2022.
View Article and Find Full Text PDFObjectives: We evaluated the intermediate reproducibility imprecision of cystatin C results based on internal quality control (IQC) data.
Methods: Five performance specifications [1/3 total allowable error (TEa), 1/4TEa and three levels performance specifications based on biological variation] were used to calculate the proportion of laboratories with CVs less than or equal to the performance specifications, namely the pass rate. Based on the reference interval of Chinese adult serum cystatin C (0.
Prenatal arsenic exposure alters EZH2/H3K27me3 to induce RKIP/NF-kB/ERK1/2-mediated early-onset kidney disease in mouse offspring.
Environ Sci Pollut Res Int
March 2025
Systems Toxicology Group, FEST Division, CSIR-Indian Institute of Toxicology Research, Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India.
The rising incidences of chronic kidney disease (CKD) and renal failure are a major public health concern. Arsenic, a widespread water contaminant and environmental toxicant, is well-known to contribute to kidney disease in adults. However, its long-term effects on kidney health following early-life exposure remain poorly understood.
View Article and Find Full Text PDFIdentifying and ranking non-traditional risk factors for cardiovascular disease prediction in people with type 2 diabetes.
Commun Med (Lond)
March 2025
Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK.
Background: Cardiovascular disease (CVD) prediction models perform poorly in people with type 2 diabetes (T2DM). We aimed to identify potentially non-traditional CVD predictors for six facets of CVD (including coronary heart disease, ischemic stroke, heart failure, and atrial fibrillation) in people with T2DM.
Methods: We analysed data on 600+ features from the UK Biobank, stratified by history of CVD and T2DM: 459,142 participants without diabetes or CVD, 14,610 with diabetes but without CVD, and 4432 with diabetes and CVD.
Revealing Genomic Traits and Evolutionary Insights of Oryza officinalis from Southern China Through Genome Assembly and Transcriptome Analysis.
Rice (N Y)
March 2025
Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, 530007, China.
Wild rice, as the ancestor of cultivated rice, has accumulated a wide range of beneficial traits through prolonged natural selection and evolution. Oryza officinalis, belonging to the CC genome, differs significantly from the AA genome. In this study, we utilized second- and third-generation sequencing, along with Hi-C technology, to assemble the genome of MT10 (O.
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