METABOLIC TRANSFORMATION SHAPES POLYCHLORINATED BIPHENYL AND POLYBROMINATED DIPHENYL ETHER PATTERNS IN BELUGA WHALES (<i>DELPHINAPTERUS LEUCAS</i>)
Bibliographic record
Abstract
While the accumulation of persistent contaminants in marine mammals can be attributed directly to their prey, the role of metabolism in shaping patterns is often overlooked. In the present study, the authors investigated the role of metabolic transformation in influencing polychlorinated biphenyl (PCB) and polybrominated diphenyl ether (PBDE) patterns in offshore and nearshore groups of beluga whales (Delphinapterus leucas) and their prey. Congener profiles and principal components analysis (PCA) revealed similar PCB and PBDE patterns in beluga whales feeding either offshore or nearshore, despite divergent contaminant patterns in the putative prey of these two feeding groups. The clustering of PCBs into metabolically derived structure-activity groups (SAGs) and the separation of metabolizable and recalcitrant groups along principal component 1 of the PCA revealed the important role of metabolic transformation in shaping PCB patterns in beluga. Lack of metabolism for congeners with high ortho-chlorine content was revealed by metabolic slopes equal to or greater than 1.0. Metabolic slopes for all other SAGs were less than 1.0 (p<0.001), suggesting metabolism of congeners with ortho-meta and meta-para vicinal hydrogens via induction of cytochrome P450 enzymes (CYP1A/2B/3A). Metabolic indices less than 1.0 for PBDEs (p<0.001) suggested that beluga metabolized these poorly understood flame retardants. The strikingly similar PCB patterns in a captive beluga and free-ranging beluga from the Beaufort Sea provide additional evidence that metabolic transformation is a dominant driver of contaminant patterns in beluga.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".