Identification of novel polar aryl hydrocarbon receptor agonists accumulated in liver of black-tailed gulls in Korea using advanced effect-directed analysis
Bibliographic record
Abstract
Although bioaccumulation of persistent organic pollutants in seabirds has been examined, few studies have been conducted to identify previously unidentified substances. Here, aryl hydrocarbon receptor (AhR) agonists were identified in livers of black-tailed gulls from South Korea using effect-directed analysis combined with full-scan screening analysis. Significant AhR-mediated potencies were observed in the polar fractions of liver extracts using H4IIE-luc bioassay. Eight known polar AhR agonists accounted for 11–20% of the total AhR-mediated potencies in the polar fractions; hydrocortisone and rutaecarpine were the major contributors. Twenty-two AhR agonist candidates in the polar fractions were identified using liquid chromatography–quadrupole time-of-flight mass spectrometry during a six-step selection process. Of these, [10]-gingerol, angelicin, corticosterone, eupatilin, etofenprox, oxadixyl, and tretinoin were identified as novel AhR agonists. The contribution to potencies increased with inclusion of novel AhR agonists (27–52%); corticosterone and [10]-gingerol contributed significantly. Quantitative structure-activity relationship suggested that the novel AhR agonists have other potential toxic effects, including carcinogenicity and mutagenicity. Polar AhR agonists have been used for pharmaceuticals and pesticides. Some novel AhR agonists have log KOW > 2 and log KOA ≥ 6, which indicates that these compounds can be biomagnified in air-breathing organisms, such as seabirds.
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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 | 0.000 | 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".