Short- and medium-chain chlorinated paraffins in breast milk in Shanghai, China: Occurrence, characteristics, and risk assessment.

As novel contaminants, short-chain chlorinated paraffins (SCCPs) and medium-chain chlorinated paraffins (MCCPs) have been of great concern in the past several years. Shanghai was one of the provinces with the largest chlorinated paraffins (CPs) emission in China; nevertheless, there is currently little information on the human exposure to SCCPs and MCCPs, particularly MCCPs. In this study, 25 breast milk samples were collected in Shanghai from 2016 to 2017.

Suspect, Nontarget Screening, and Toxicity Prediction of Per- and Polyfluoroalkyl Substances in the Landfill Leachate.

Landfills are the final stage of urban wastes containing perfluoroalkyl and polyfluoroalkyl substances (PFASs). PFASs in the landfill leachate may contaminate the surrounding groundwater. As major environmental pollutants, emerging PFASs have raised global concern.

Infant Exposure to PCBs and PBDEs Revealed by Hair and Human Milk Analysis: Evaluation of Hair as an Alternative Biomatrix.

Human hair, as an emerging biological monitoring matrix, has begun to be used in various human exposure studies, but little research has been done on persistent organic pollutants (POPs), especially for the body burden of POPs in infants. In this study, 36 breast-fed infants in Shanghai were recruited for a study to determine their exposure to POPs, including 12 dioxin-like polychlorinated biphenyls (dl-PCBs), 6 indicator PCBs, and 8 polybrominated diphenyl ethers (PBDEs) in the inner layer (internal) and outer layer (external) of infant hair and human milk. The similarity or difference of the POP distribution pattern or concentration among these matrices was investigated, and only weak correlations ( < 0.

Profiling of pesticides and pesticide transformation products in Chinese herbal teas.

Herbal teas have potential health benefits, but they also contain a variety of pesticides and pesticide transformation products (PTPs) that might brings health risks. Our study maps the pesticides and PTPs in two herbal teas (chrysanthemum and Lusterleaf Holly) from two main producing areas in China. Almost all 122 samples contain pesticides, with concentration ranging from 0.

Evaluation and application of machine learning-based retention time prediction for suspect screening of pesticides and pesticide transformation products in LC-HRMS.

Computational QSAR models have gradually been preferred for retention time prediction in data mining of emerging environmental contaminants using liquid chromatography coupled with mass spectrometry. Generally, the model performance relies on the components such as machine learning algorithms, chemical features, and example data. In this study, we evaluated the performances of four algorithms on three feature sets, using 321 and 77 pesticides as the training and validation sets, respectively.

Exposure and health risk assessment of secondary contaminants closely related to brominated flame retardants (BFRs): Polybrominated dibenzo-p-dioxins and dibenzofurans (PBDD/Fs) in human milk in shanghai.

Polybrominated dibenzo-p-dioxins and dibenzofurans (PBDD/Fs), as the secondary environmental pollutants of the widely used brominated flame retardants (BFRs), possess the similar physicochemical and toxic properties as polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs). However, studies on human body exposure to them are extremely limited. In this study, forty human milk samples collected in Shanghai were measured for 13 PBDD/F congeners using gas chromatography-high resolution mass spectrometry (GC-HRMS), to investigate their exposure level and characteristics, potential source and corresponding health risks to breastfed infants.

Comprehensive strategy for analysis of pesticide multi-residues in food by GC-MS/MS and UPLC-Q-Orbitrap.

A rapid and high-throughput method using both GC-MS/MS and UPLC-Q-Orbitrap systems was applied for pesticide multi-residues analysis in food samples. Strategies based on QuEChERs extraction, intelligent data mining tools with in-house/online database, and in-silico fragment prediction system were introduced to screen and identify target/untargeted features. Full-scan combined with data-independent-acquisition modes was evaluated in real sample in an attempt to improve and facilitate the pesticide screening process, of which the results showed that FS-vDIA provided equal detection rate (100%) and far less false positive results than FS-AIF did.