PBDEs and PCBs in the liver of the St Lawrence Estuary beluga (Delphinapterus leucas): a comparison of levels and temporal trends with the blubber
Bibliographic record
Abstract
Due to their lipophilic properties, persistent organic pollutants (POPs) are commonly assessed using the blubber of marine mammals. However, these chemicals are also accumulating in other tissues including the liver. Some pollutants, namely perfluorinated alkyl acids, are found predominately in the liver and blood of marine mammals, and thus monitored in those tissues. This raises the question whether any tissue would represent an identical trend of POPs in the SLE beluga. The current study reports the first temporal trends of PBDEs and PCBs in the liver of 65 SLE belugas. Neither ∑₇PBDEs nor major individual PBDE-homolog group concentrations showed significant trends between 1993 and 2007. Also, ∑₃₂PCBs did not change over years, although, tetra-, penta- and hepta-PCB decreased by 7.1, 6.8 and 8.5%, respectively, in males, whereas tetra-, penta- and octa-PCBs declined by 11, 12 and 12.9%, respectively, in females. In order to compare the distribution of POPs between liver and blubber, a lipid normalised concentration ratio R (blubber/liver) for PBDEs and PCBs was calculated for each individual beluga. For all PBDE and several PCB homolog groups, mean R values were not statistically different from unity indicating that the partitioning of these POPs is governed by the tissue lipid-content. Temporal trends of R ratios of PBDEs and PCBs were also examined. There were generally no significant temporal trends except for PBDEs in males where R increased in average by 12.7 ± 2.9% yearly. The stratification of the blubber into a metabolically active (inner) and less active layers (outer blubber) may result in a slower response time of the blubber (full depth) than the liver to the recent change of contamination in the environment and explain the time trend differences between both tissues. This study suggests that the liver is more representative of recent exposure to lipophilic contaminants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".