Surface-enhanced Raman spectroscopy (SERS) has gained significant attention for its ability to detect environmental contaminants with high sensitivity and specificity. The cost-effectiveness and potential portability of the technique further enhance ...
Machine learning exhibits excellent performance in terms of predictive power. We aimed to construct an interpretable machine learning model utilizing National Health and Nutrition Examination Survey data to investigate the relationship between heavy ...
Endocrine-disrupting chemicals (EDCs) pollution is a major global environmental issue. Assessing the multiple toxic effects of EDCs is key to managing their risks. This study successfully developed an EDCs classification and recognition model based o...
Environmental chemicals can enter the human body through various exposure pathways, potentially leading to neurotoxic effects that pose significant health risks. Many such chemicals have been identified as neurotoxic, but the molecular mechanisms und...
The growing prevalence of environmental pollutants has raised concerns about their potential role in thyroid dysfunction and related disorders. Previous research suggests that various chemicals, including plasticizers like acetyl tributyl citrate (AT...
Early pregnancy loss (EPL) may result from exposure to emerging contaminants (ECs), although the underlying mechanisms remain poorly understood. This case-control study measured over 2000 serum features, including 37 ECs, 6 biochemicals, and 2057 end...
We investigated the impacts of personal care products (PCPs) on dermal exposure to semi-volatile organic compounds (SVOCs), including phthalates, organophosphate esters, polycyclic aromatic hydrocarbons (PAHs), ultraviolet filters, and p-phenylenedia...
p-phenylenediamine antioxidants (PPDs) are extensively used in rubber manufacturing for their potent antioxidative properties, but PPDs and 2-anilino-5-[(4-methylpentan-2yl)amino]cyclohexa-2,5-diene-1,4-dione (6PPDQ) pose potential environmental and ...
The nano-self-assembly of natural organic matter (NOM) profoundly influences the occurrence and fate of NOM and pollutants in large-scale complex environments. Machine learning (ML) offers a promising and robust tool for interpreting and predicting t...
Over the past decades, exposure to per- and polyfluoroalkyl substances (PFAS), a group of synthetic chemicals notorious for their environmental persistence, has been shown to pose increased health risks. Despite that some PFAS were reported to have e...