Emerging investigator series: nontargeted screening of aryl hydrocarbon receptor agonists in endangered beluga whales from the St. Lawrence Estuary: beyond legacy contaminants
Bibliographic record
Abstract
The elevated concentrations of organohalogen contaminants in the endangered St. Lawrence Estuary (SLE) belugas have prompted the hypothesis that aryl hydrocarbon receptor (AhR) activity may be a contributor towards their potential adverse effects. While indirect associations between AhR and contaminant levels have been reported in SLE beluga tissues, AhR activity was never directly measured. Using bioassays and nontargeted analysis, this study contrasted AhR activity and agonist profiles between pooled tissue extracts of endangered SLE and non-threatened Arctic belugas. Tissue extracts of SLE belugas exhibited significantly higher overall AhR activity than that of Arctic belugas, with a 2000s SLE beluga liver extract exerting significantly higher activity than blubber extracts of SLE and Arctic belugas from the same time period. Contrary to our expectations, well-known AhR agonists detected by nontargeted analysis, including polychlorinated biphenyls (PCBs), were only minor contributors to the observed AhR activity. Instead, Tox21 suspect screening identified more polar chemicals, such as dyes and natural indoles, as potential contributors. Notably, the natural product bromoindole was selectively detected in SLE beluga liver at high abundance and was further confirmed as an AhR agonist. These findings highlighted the significance of the AhR-mediated toxicity pathway in belugas and underscored the importance of novel AhR agonists, particularly polar compounds, in its induction.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".