AIMC Topic: Persistent Organic Pollutants

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Assessment of POPs in foods from western China: Machine learning insights into risk and contamination drivers.

Environment international
Persistent organic pollutants (POPs), including PCDD/Fs, PCBs, and PBDEs, are major environmental and food safety concerns due to their bioaccumulative and toxic properties. However, comprehensive research on the concentrations and influencing factor...

High-throughput prediction of oral acute toxicity in Rat and Mouse of over 100,000 polychlorinated persistent organic pollutants (PC-POPs) by interpretable data fusion-driven machine learning global models.

Journal of hazardous materials
This study utilized available oral acute toxicity data in Rat and Mouse for polychlorinated persistent organic pollutants (PC-POPs) to construct data fusion-driven machine learning (ML) global models. Based on atom-centered fragments (ACFs), the coll...

Utilizing machine learning to classify persistent organic pollutants in the serum of pregnant women: a predictive modeling approach.

Environmental science and pollution research international
Polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs), and per- and poly-fluoroalkyl substances (PFAS) are persistent organic pollutants (POPs) that remain de...

Toxicity evaluation and oxidative stress response of fumaronitrile, a persistent organic pollutant (POP) of industrial waste water on tilapia fish (Oreochromis mossambicus).

Environmental research
The study was designed to determine the impact of acute toxicity of fumaronitrile exposure through tissue damaging, oxidative stress enzymes and histopathological studies in gills, liver and muscle cells of freshwater tilapia fish (Oreochromis mossam...