3 resultados para Tissue factor

em Publishing Network for Geoscientific


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Heavy metals (Cd, Cu, Fe, Mn and Zn) concentrations were determined in different tissues (muscle, kidney, liver, brain, gonads, heart and feathers) of Glaucous Gulls (Larus hyperboreus) from Bjornoya and Jan Mayen. The age and spatial dependent variations in heavy metals were quantified and interpreted in view of the three chemometric techniques, i.e. non-parametric Mann-Whitney U test, redundancy gradient analysis and detrended correspondence analysis. The Glaucous Gulls from Bjornoya contained significantly higher (p < 0.05) levels of Cd, Cu and Zn than those inhabited Jan Mayen. Adult birds were characterized by greater (p < 0.01) concentration of muscle, hepatic and renal heavy metals in comparison to chicks. Insignificantly higher slope constant Zn/Cd for the liver than for the kidney may reflect insignificant Cd exposure. Estimate of transfer factor (TF) allows us to assess variations in heavy metal concentrations during the individual development of Glaucous Gulls. It may be stated that there is a distinct increase of bioaccumulation of all the studied metals during subsequent stages of the bird life.

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Polybrominated diphenyl ethers (PBDEs) were analysed in adipose tissue from 92 East Greenland polar bears (Ursus maritimus) sampled during 1999-2001. Mean SumPBDE concentrations were 70 ng/g lipid weight (lw) (range: 22-192 ng/g lw) and showed no relationship with age or sex. Of the 32 analysed PBDE congeners; BDE47, BDE153, BDE99 and BDE100 dominated, and comprised 99.6% of the SumPBDE concentration. The SumPBDE concentration had a highly significant correlation with SumPCB, SumCHL, dieldrin, HCB and SumHCH concentrations. We found a seasonal pattern of median SumPBDE concentration with 1.2 to 1.8 times higher concentrations in March to July than the rest of the year. The seasonal variation also provides a clue to the seasonal exposure, bio-availability, toxic exposure and degradation. We suggest that future geographical PBDE data comparisons may not need corrections for sex or age, but such data sets should be corrected for seasonal variability, using the presented correctional trigonometric regression.