Reports of PFBS in wild mammalian tissues are relatively uncommon

Reports of PFBS in wild mammalian tissues are relatively uncommon in the international literature and has only recently

been found in harbor seals from the Dutch Wadden Sea (1.74–3.28 ng/g spleen) (Van de Vijver et al., 2005), in harbor seals from the German Bight (up to 3.1 ng/g liver) (Ahrens et al., 2009) and in gray seals from the Baltic Sea (up to 3.5 ng/g liver) (Kratzer et al., 2011). The concentrations were approximately the same as in Tariquidar in vitro the mink in our study (Table 1), although PFBS was only found in 27–55% of the samples (compared to 89% in our study). In addition, PFBS has been found in sea turtles from the east coast of USA (< 0.02–0.846 and < 0.01–0.195 ng/g serum) (Keller et al., 2012 and O'Connell et al., 2010). In contrast, PFBS was below detection limit in all samples of Arctic and North Atlantic pilot whale, ringed seal, minke whale, harbor porpoise, hooded seal, white-sided dolphin and fin whales (Rotander et al., 2012). Also, PFBS was not detected in ringed seal populations in the Canadian Arctic (Butt et al., 2007 and Butt et al., 2008), nor in common guillemot from the Baltic Sea (Berger, 2008) or harbor porpoise in the North and Baltic Sea (Huber et al., 2012). PFBS is persistent (Quinete et al., 2010), but not expected to be as bioaccumulative as PFAAs with longer carbon chains (Conder et al., 2008). However, as a replacement

for PFOS, the use of this compound will probably increase in the future. HSP mutation Mink, with its wide geographical distribution and the proximity of its habitat to human activities, could be a suitable sentinel species for monitoring PFBS exposure to mammals. The sampling areas in this study were selected because of their assumed differences in contamination and this was confirmed by the multiple regression find more model,

which showed that area of sampling was significantly influencing the concentrations of PFHxS, PFOS, PFNA, PFDA and PFUnDA (p = < 0.001–0.01). The multiple regression models explained 18–53% of the variation in the tissue concentrations. Pairwise comparisons of least squares between the areas are given in Table 1. To visualize the variation in contaminant concentrations in the four areas, a PCA model (R2 = 0.52, Q2 = 0.119) containing 3 significant principal components according to cross validation was calculated. Scores and loadings plots of component 1 versus component 2 are given in Fig. 1 and Fig. 2, explaining 23% and 15% of the variance, respectively. The scores plot is a summary of the relationships among the observations (mink). The loadings plot can be used to interpret the patterns seen in the scores plot, as the plots are superimposable. Plots of component 2 versus 3, the descriptive data for the components and the R2 and Q2 calculated for each variable are found in the Supplementary data. In the PCA scores plot (Fig.

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