Chlorination and Bromination of Anthracene Affects Aryl Hydrocarbon Receptor Activation and Early Life Stage Mortality in Zebrafish (<i>Danio rerio</i>)
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are known to adversely affect fish through activation of aryl hydrocarbon receptor 2 (AhR). Most studies have focused on 16 priority PAHs, but chlorinated and brominated PAHs are more potent than the parent PAHs in studies using mammalian AhRs. Despite being detected in fish species in situ, no studies have examined their toxicity. The present study investigated the effect of positioning and degree of chlorination and bromination on potency relative to an unsubstituted PAH for in vitro activation of zebrafish ( Danio rerio ) AhR2 and potency for zebrafish early life-stage mortality. Anthracene did not activate the AhR2, but chlorination and bromination strongly affected potency in a position-dependent manner. Seven of 11 halogenated PAHs activated the AhR2 with potency generally increasing with number of substitutions. Bromination had a larger effect on potency than chlorination. Potency for early life-stage toxicity followed the same rank order as that for AhR2 activation. The domain of applicability of an existing cross-species predictive framework was expanded to include halogenated PAHs, representing a significant advancement in risk assessment with immediate utility. Due to their potency and occurrence in the environment, there is a need to objectively assess the risks posed by this class of chemicals.
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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".