Time-dependent relative potency factors for polycyclic aromatic hydrocarbons and their derivatives in the H4IIE-luc bioassay
Bibliographic record
Abstract
The H4IIE-luc transactivation bioassay for aryl hydrocarbon receptor (AhR) agonists was used to investigate the relative potency factors (REPs) of 22 individual polycyclic aromatic hydrocarbons (PAHs) and their oxygenated-, methylated-, and N-containing derivatives (azaarenes), which are often present in PAH-contaminated soils. Naphthacene and dibenz[ah]acridine exhibited greater AhR-mediated potency, whereas lesser molecular-weight azaarenes were less potent AhR agonists. Six oxygenated PAHs had calculable REPs, but their potencies were less than their parent PAHs. Unlike the parent, unsubstituted PAHs, oxidation of methylated PAHs seemed to increase the AhR-mediated potency of the compounds, with 2-methylanthracene-9,10-dione being almost 2 times more potent than 2-methylanthracene. Both bioassay and gas chromatography-mass spectrometry analysis were used to examine the exposure time-dependent effects on the REPs at 24 h, 48 h, and 72 h of exposure in the H4IIE-luc transactivation bioassay. Changes in concentrations of 5 compounds including the model reference 2,3,7,8-tetrachlorodibenzo-p-dioxin in the cell culture wells were measured, and the amounts in the cell medium, in the cells, and adsorbed to the wells was determined and the influence on the REPs was studied. Declining REP values with increased duration of exposure were shown for all compounds, which we concluded were a consequence of the metabolism of PAHs and PAH derivatives in H4IIe-luc cells. The present study provides new knowledge regarding the degradation and distribution of compounds in the wells during exposure.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".