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Excessive anthropogenic phosphorus (P) emissions put constant pressure on aquatic ecosystems. This pressure can be quantified as the freshwater eutrophication potential (FEP) by linking P emissions, P fate in environmental compartments, and the potentially disappeared fraction of species due to increase of P concentrations in freshwater. However, previous fate modeling on global and regional scales is mainly based on the eight-direction algorithm without distinguishing pollution sources. The algorithm fails to characterize the fate paths of point-source emissions via subsurface pipelines and wastewater treatment infrastructure, and exhibits suboptimal performance in accounting for multidirectional paths caused by river bifurcations, especially in flat terrains. Here we aim to improve the fate modeling by incorporating various fate paths and addressing multidirectional scenarios. We also update the P estimates by complementing potential untreated point-source emissions (PSu). The improved method is examined in a rapidly urbanizing area in Taihu Lake Basin, China in 2017 at a spatial resolution of 100 m × 100 m. Results show that the contribution of PSu on FEP (62.6%) is greater than that on P emissions (58.5%). The FEP is more spatially widely distributed with the improved fate modeling, facilitating targeted regulatory strategies tailored to local conditions.
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http://dx.doi.org/10.1021/acs.est.4c01205 | DOI Listing |
Food Res Int
November 2025
Department of Food Science and Technology, College of Agricultural and Environmental Sciences, University of Georgia, Griffin, GA 30223, USA. Electronic address:
Turmeric-derived curcumin offers various health benefits but has poor bioavailability due to low water solubility and rapid gastrointestinal degradation. A recently proposed raw-to-nano strategy enables the direct formulation of turmeric nanoparticles from raw turmeric, using inherent biopolymers to encapsulate and protect curcumin. However, it remains unclear how these nanoparticles enhance gastrointestinal bioavailability and how food matrices influence this process.
View Article and Find Full Text PDFComp Biochem Physiol C Toxicol Pharmacol
September 2025
Department of Biological Sciences, Clemson University, Clemson, SC, USA; Clemson University Center for Human Genetics, Greenwood, SC, USA. Electronic address:
Tetrabromobisphenol A (TBBPA), a widely used flame retardant in textiles and electronics, poses toxicological risks through both environmental and indoor exposures. Biomonitoring studies have detected significant TBBPA levels in prenatal environments, including cord blood, raising concerns about developmental impacts. Using zebrafish as a model, this study addresses critical gaps in understanding how developmental TBBPA exposures perturb regulatory pathways that govern dorsoventral patterning.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
United States Environmental Protection Agency, Center for Computational Toxicology and Exposure, 109 TW Alexander Dr., Research Triangle Park, North Carolina 27711, United States.
To assess environmental fate, transport, and exposure for PFAS (per- and polyfluoroalkyl substances), predictive models are needed to fill experimental data gaps for physicochemical properties. In this work, quantitative structure-property relationship (QSPR) models for octanol-water partition coefficient, water solubility, vapor pressure, boiling point, melting point, and Henry's law constant are presented. Over 200,000 experimental property value records were extracted from publicly available data sources.
View Article and Find Full Text PDFBlood
September 2025
The University of Chicago, Chicago, Illinois, United States.
Long-term maintenance of somatic stem cells relies on precise regulation of self-renewal and differentiation. Understanding the molecular framework for these homeostatic processes is essential for improved cellular therapies and treatment of myeloid neoplasms. CUX1 is a widely expressed, dosage-sensitive transcription factor crucial in development and frequently deleted in myeloid neoplasia in the context of -7/(del7q).
View Article and Find Full Text PDFBiosaf Health
August 2025
Faculty of Innovation Engineering, Macau University of Science and Technology, 999078, Macao Special Administrative Region of China.
Understanding human-virus protein-protein interactions is critical for studying molecular mechanisms driving viral infection, immune evasion, and propagation, thereby informing strategies for public health. Here, we introduce a novel multimodal deep learning framework that integrates high-confidence experimental datasets to systematically predict putative interactions between human and viral proteins. Our approach incorporates two complementary tasks: binary classification for interaction prediction and conditional sequence generation to identify interacting protein partners.
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