Population biomonitoring data sets such as the Canadian Health Measures Survey (CHMS) and the United States National Health and Nutrition Examination Survey (NHANES) collect and analyze spot urine samples for analysis for biomarkers of exposure to non-persistent chemicals. Estimation of population intakes using such data sets in a risk-assessment context requires consideration of intra- and inter-individual variability to understand the relationship between variation in the biomarker concentrations and variation in the underlying daily and longer-term intakes. Two intensive data sets with a total of 16 individuals with collection and measurement of serial urine voids over multiple days were used to examine these relationships using methyl paraben, triclosan, bisphenol A (BPA), monoethyl phthalate (MEP), and mono-2-ethylhexyl hydroxyl phthalate (MEHHP) as example compounds. Composited 24 h voids were constructed mathematically from the individual collected voids, and concentrations for each 24 h period and average multiday concentrations were calculated for each individual in the data sets. Geometric mean and 95th percentiles were compared to assess the relationship between distributions in spot sample concentrations and the 24 h and multiday collection averages. In these data sets, spot sample concentrations at the 95th percentile were similar to or slightly higher than the 95th percentile of the distribution of all 24 h composite void concentrations, but tended to overestimate the maximum of the multiday concentration averages for most analytes (usually by less than a factor of 2). These observations can assist in the interpretation of population distributions of spot samples for frequently detected analytes with relatively short elimination half-lives.
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http://dx.doi.org/10.1038/jes.2016.54 | DOI Listing |
Nutrients
January 2025
Department of Nutrition, School of Public Health, Sun Yat-sen University, 74 Zhong Shan Road 2, Guangzhou 510080, China.
Background: Evidence regarding the individual and combined impact of dietary flavonoids on the risk of metabolic dysfunction associated with steatotic liver disease (MASLD) remains scarce. Our objective is to evaluate the association between individual and multiple dietary flavonoids with MASLD in adults.
Methods: Data sets were obtained from the National Health and Nutrition Examination Survey (NHANES), 2017-2018.
Materials (Basel)
January 2025
College of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China.
Due to the uncertainty of material properties of plate-like structures, many traditional methods are unable to locate the impact source on their surface in real time. It is important to study the impact source-localization problem for plate structures. In this paper, a data-driven machine learning method is proposed to detect impact sources in plate-like structures and its effectiveness is tested on three plate-like structures with different material properties.
View Article and Find Full Text PDFMedicina (Kaunas)
January 2025
Department of Internal Medicine (Nephrology), Faculty of Medicine, Ufuk University, 06510 Ankara, Turkey.
Immunoglobulin G4-related disease (IgG4-RD) is an immune-mediated, fibroinflammatory, multiorgan disease with an obscure pathogenesis. Findings indicating excessive platelet activation have been reported in systemic sclerosis, which is another autoimmune, multisystemic fibrotic disorder. The immune-mediated, inflammatory, and fibrosing intersections of IgG4-RD and systemic sclerosis raised a question about platelets' role in IgG4-RD.
View Article and Find Full Text PDFCancers (Basel)
January 2025
Department of Biostatistics, Data Science, and Epidemiology, School of Public Health, Georgia Cancer Center at Augusta University, Augusta, GA 30912, USA.
: Recent growth in the number and applications of high-throughput "omics" technologies has created a need for better methods to integrate multiomics data. Much progress has been made in developing unsupervised methods, but supervised methods have lagged behind. : Here we present the first algorithm, PLASMA, that can learn to predict time-to-event outcomes from multiomics data sets, even when some samples have only been assayed on a subset of the omics data sets.
View Article and Find Full Text PDFInt J Environ Res Public Health
January 2025
Department of Psychology, Springfield College, 263 Alden Street, Springfield, MA 01109, USA.
Changes in athletic identity have been documented after injury and other sport transitions in nomothetic investigations. Patterns of change in athletic identity after injury have not been examined systematically at the individual level. In the current study, secondary analyses were performed on two data sets ( = 43 and = 80) in which athletic identity values were available for before and at least six months after anterior cruciate ligament (ACL) reconstruction.
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