Endocrine disrupting potential of PAHs and their alkylated analogues associated with oil spills
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) and alkylated PAHs are known to be major toxic contaminants in spills of petroleum hydrocarbons (oil). Spilled oil undergoes weathering and over time, PAHs go through a series of compositional changes. PAHs can disrupt endocrine functions, and the type of functions affected and associated potencies vary with the type and alkylation status of PAH. In this study, the potential of five major PAHs of crude oil, i.e., naphthalene, fluorene, dibenzothiophene, phenanthrene, and chrysene, and their alkylated analogues (n = 25), to disrupt endocrine functions was evaluated by use of MVLN-luc and H295R cell lines. In the MVLN-luc bioassay, seven estrogen receptor (ER) agonists were detected among 30 tested PAHs. The greatest ER-mediated potency was observed for 1-methylchrysene (101.4%), followed by phenanthrene and its alkylated analogues (range of %-E2max from 1.6% to 47.3%). In the H295R bioassay, significantly greater syntheses of steroid hormones were observed for 20 PAHs. For major PAHs and their alkylated analogues, disruption of steroidogenesis appeared to be more significant than ER-mediated effects. The number and locations of alkyl-moieties alone could not explain differences in the types or the potencies of toxicities. This observation shows that disruption of endocrine functions by some constituents of oil spills could be underestimated if only parent compounds are considered in assessments of hazard and risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".