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We characterize cumulative intakes of organophosphorus (OP) pesticides in an agricultural region of California by drawing on human biomonitoring data, California pesticide use reporting (PUR) data, and limited environmental samples together with outputs from the CalTOX multimedia, multipathway, source-to-dose model. The study population is the CHAMACOS cohort of almost 600 pregnant Latina women in the Salinas Valley region. We use model estimates of OP intake and urinary dialkylphosphate (DAP) metabolite excretion to develop premises about relative contributions from different exposure sources and pathways. We evaluate these premises by comparing the magnitude and variation of DAPs in the CHAMACOS cohort with those of the whole U.S. population using data from the National Health and Nutrition Examination Survey (NHANES). This comparison supports the premise that diet is the common and dominant exposure pathway in both populations. Biomarker comparisons and model results support the observation that, relative to NHANES, the CHAMACOS population has a statistically significant (p < 0.001) added intake of OP pesticides with low inter-individual variability. We attribute the magnitude and small variance of this intake to residential nondietary exposures from local agricultural OP uses. These results show that mass-balance models can estimate exposures for OP pesticides within the range measured by biological monitoring.
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http://dx.doi.org/10.1021/es0618447 | DOI Listing |
Biochem Biophys Rep
December 2025
Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.
Brillouin microscopy allows mechanical investigations of biological materials at the subcellular level and can be integrated with Raman spectroscopy for simultaneous chemical mapping, thus enabling a more comprehensive interpretation of biomechanics. The present study investigates different in vitro glioblastoma models using a combination of Brillouin and Raman microspectroscopy. Spheroids of the U87-MG cell line and two patient-derived cell lines as well as patient-derived organoids were used.
View Article and Find Full Text PDFGenome Biol
September 2025
Department of Evolutionary Genetics, Max-Planck Institute for Evolutionary Biology, Plön, Germany.
Background: Most RNA-seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier gene expression to investigate whether they provide insights into the underlying biology.
View Article and Find Full Text PDFExp Neurol
September 2025
CNRS UMR 5536 RMSB, University of Bordeaux, Bordeaux, France; Basic Science Department, Loma Linda University School of Medicine, Loma Linda, CA, USA; CNRS UMR 7372 CEBC, La Rochelle University, Villiers-en-Bois, France.
Introduction: The vulnerability of white matter (WM) in acute and chronic moderate-severe traumatic brain injury (TBI) has been established. In concussion syndromes, including preclinical rodent models, lacking are comprehensive longitudinal studies spanning the mouse lifespan. We previously reported early WM modifications using clinically relevant neuroimaging and histological measures in a model of juvenile concussion at one month post injury (mpi) who then exhibited cognitive deficits at 12mpi.
View Article and Find Full Text PDFSci Total Environ
September 2025
University Hohenheim, Department of Process Analytics and Cereal Science, Stuttgart, 70599, Germany.
Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants with increasing prevalence in agricultural soils, primarily introduced through biosolid application, wastewater irrigation, and atmospheric deposition. This review provides a meta-analysis of terminologies across 145 peer-reviewed studies, identifying inconsistency in the classification of PFAS subgroups-such as "long-chain vs. short-chain," "precursors," and "emerging PFAS"-which hinders regulatory harmonization and model calibration.
View Article and Find Full Text PDFDriven by eutrophication and global warming, the occurrence and frequency of harmful cyanobacteria blooms (CyanoHABs) are increasing worldwide, posing a serious threat to human health and biodiversity. Early warning enables precautional control measures of CyanoHABs within water bodies and in water works, and it becomes operational with high frequency in situ data (HFISD) of water quality and forecasting models by machine learning (ML). However, the acceptance of early warning systems by end-users relies significantly on the interpretability and generalizability of underlying models, and their operability.
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