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Urine test may detect uranium buildup before irreversible injury.
Urine test may detect uranium buildup before irreversible injury.

Urine Test May Detect Uranium Build Up Before Irreversible Injury (Columbia University SRP Center): Scientists revealed a new method to detect kidney damage from uranium exposure early using simple urine tests.

Nanoparticles Help Plants Clean Up Forever Chemicals (Yale University): Researchers developed a novel nanomaterial that enhances the ability of plants to remove PFAS from soil and water. Their approach could expand sustainable, cost-effective cleanup options for PFAS.

Dioxin-Like Compounds Shift the Balance of White Blood Cells (Michigan State University SRP Center): Researchers showed that dioxin-like compounds can alter how white blood cells develop and do so in ways that current risk assessment methods fail to predict.

Demonstrating a Pilot System to Electrochemically Remediate Groundwater (Northeastern University SRP Center): Scientists designed a scaled-up electrochemical system that combines electricity with the mineral pyrite, a mineral commonly found in the environment, to continuously remove organic and heavy metal contaminants from groundwater for a year.

Mechanism Linking Preconception Arsenic Exposure and Diabetes in Offspring Revealed (University of North Carolina at Chapel Hill SRP Center): Researchers demonstrated how exposure to inorganic arsenic before conception can trigger changes in gene activity that are passed down to offspring and increase their risk of developing diabetes.

Machine Learning Creates More Complete Picture of Groundwater Contamination (Harvard School of Public Health SRP Center): Researchers revealed how machine learning algorithms can fill gaps in sparse or incomplete groundwater datasets by filling in missing data points.

Using a New Model to Identify Health-Impacting Metal Mixtures (Duke University SRP Center): Scientists developed the linear mixed-effects model, a framework for statistical analysis, to quickly and effectively estimate the effects of individual metals and metal mixtures on zebrafish larvae behaviors.

Machine Learning Predicts Efficiency of Micropollutant Removal (North Carolina State University SRP Center): Scientists created machine learning models that can help predict how well granular activated carbon can clean up contaminated water under different scenarios.

Model Predicts PFAS Buildup in Wild Animals (University of Rhode Island SRP Center): Researchers developed a new model that predicts how PFAS move and build up within food webs, laying the groundwork for screening the thousands of PFAS compounds that could potentially pose a risk for ecological or human health.

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