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On behalf of the Ministry of Agriculture, Nature and Food Quality (LNV), Wageningen Food Safety Research analyses samples of agricultural products of animal origin for dioxins, PCBs, brominated flame retardants (BFRs) and poly- and perfluorinated alkyl substances (PFASs). This includes meat, milk, eggs and fish. The samples are taken at the primary production or processing stage (e.g. in slaughterhouses or raw milk collection services). For dioxin-like compounds, 350 samples are first screened with the DR CALUX® method. Samples giving a signal indicating a level above the lowest action level are regarded as suspected. These samples are further examined using GC/HRMS as confirmatory method. Concerning fish, shellfish and crustaceans, approx. 25 samples are collected at sea by research vessels, at the fish auction, or from whole-sale traders (farmed fish).

Advanced glycation endproducts (AGEs) can be found in protein-and sugar-rich food products processed at high temperatures, which make up a vast amount of the Western diet. The effect of AGE-rich food products on human health is not yet clear and controversy still exists due to possible contamination of samples with endotoxin and the use of endogenous formed AGEs. AGEs occur in food products, both as protein-bound and individual molecules. Which form exactly induces a pro-inflammatory effect is also unknown. In this study, we exposed human macrophage-like cells to dietary AGEs, both in a protein matrix and individual AGEs. It was ensured that all samples did not contain endotoxin concentrations > 0.06 EU/mL. The dietary AGEs induced TNF-alpha secretion of human macrophage-like cells. This effect was decreased by the addition of N(ε)-carboxymethyllysine (CML)-antibodies or a receptor for advanced glycation endproducts (RAGE) antagonist. None of the individual AGEs induce any TNF-alpha, indicating that AGEs should be bound to proteins to exert an inflammatory reaction. These findings show that dietary AGEs directly stimulate the inflammatory response of human innate immune cells and help us define the risk of regular consumption of AGE-rich food products on human health.

Accurate quantification of short-chain chlorinated paraffins (SCCPs) poses an exceptional challenge to analytical chemists. SCCPs are complex mixtures of chlorinated alkanes with variable chain length and chlorination level; congeners with a fixed chain length (n) and number of chlorines (m) are referred to as a congener group CnClm Recently, we resolved individual CnClm by mathematically deconvolving soft ionization high-resolution mass spectra of SCCP mixtures. Here we extend the method to quantifying CnClm by introducing CnClm specific response factors (RFs) that are calculated from 17 SCCP chain-length standards with a single carbon chain length and variable chlorination level. The signal pattern of each standard is measured on APCI-QTOF-MS. RFs of each CnClm are obtained by pairwise optimization of the normal distribution's fit to the signal patterns of the 17 chain-length standards. The method was verified by quantifying SCCP technical mixtures and spiked environmental samples with accuracies of 82-123% and 76-109%, respectively. The absolute differences between calculated and manufacturer-reported chlorination degrees were 0.9 to 1.0%Cl for SCCP mixtures of 49-71%Cl. The quantification method has been replicated with ECNI magnetic sector MS and ECNI-Q:Orbitrap-MS. CnClm concentrations determined with the three instruments were highly correlated (R-2 > 0.90) with each other.

The present study investigated the presence of legacy and emerging per- and polyfluoroalkyl substances (PFASs) in river water collected in 2016 up- and downstream from a fluorochemical production plant, as well as in river water from control sites, in The Netherlands. Additionally, drinking water samples were collected from municipalities in the vicinity from the production plant, as well as in other regions in The Netherlands. The PFOA replacement chemical GenX was detected at all downstream river sampling sites with the highest concentration (812 ng/L) at the first sampling location downstream from the production plant, which was 13 times higher than concentrations of sum perfluoroalkylcarboxylic acids and perfluoroalkanesulfonates (-PFCA+-PFSA). Using high resolution mass spectrometry, 11 polyfluoroalkyl acids belonging to the C2nH2nF2nO2, C2nH2n+2F2nSO4 or C2n+1H2nF2n+4SO4 homologue series were detected, but only in downstream water samples. These emerging PFASs followed a similar distribution as GenX among the downstream sampling sites, suggesting the production plant as the source. Polyfluoroalkyl sulfonates (C2nH2F4nSO3) were detected in all collected river water samples, and therefore appear to be ubiquitous contaminants in Dutch rivers. GenX was also detected in drinking water collected from 3 out of 4 municipalities in the vicinity of the production plant, with highest concentration at 11 ng/L. Drinking water containing the highest level of GenX also contained two C2nH2nF2nO2 homologues.

The present study examined the presence of perfluoroalkyl acids (PFAAs) and selected precursors in the Baltic Sea abiotic environment and guillemot food web, and investigated the relative importance of precursors in food web accumulation of PFAAs. Sediment, water, zooplankton, herring, sprat, and guillemot eggs were analyzed for perfluoroalkane sulfonic acids (PFSAs; C-4,C-6,C-8,C-10) and perfluoroalkyl carboxylic acids (PFCAs; C6-15) along with six perfluorooctane sulfonic acid (PFOS) precursors and 11 polyfluoroalkyl phosphoric acid diesters (diPAPs). FOSA, FOSAA. and its methyl and ethyl derivatives (Me- and EtFOSAA), and 6:2/6:2 diPAP were detected in sediment and water. While FOSA and the three FOSAAs were detected in all biota, a total of nine diPAPs were only detected in zooplankton. Concentrations of PFOS precursors and diPAPs exceeded PFOS and PFCA concentrations, respectively, in zooplankton, but not in fish and guillemot eggs. Although PFOS precursors were present at all trophic levels, they appear to play a minor role in food web accumulation of PFOS based on PFOS precursor/PFOS ratios and PFOS and FOSA isomer patterns. The PFCA pattern in fish could not be explained by the intake pattern based on PFCAs and analyzed precursors, that is, diPAPs. Exposure to additional precursors might therefore be a dominant exposure pathway compared to direct PFCA exposure for fish.