Aromatic Naphthenic Acids in Oil Sands Process-Affected Water, Resolved by GCxGC-MS, Only Weakly Induce the Gene for Vitellogenin Production in Zebrafish (<i>Danio rerio</i>) Larvae
Bibliographic record
Abstract
Process waters from oil sands industries (OSPW) have been reported to exhibit estrogenic effects. Although the compounds responsible are unknown, some aromatic naphthenic acids (NA) have been implicated. The present study was designed to investigate whether aromatic NA might cause such effects. Here we demonstrate induction of vitellogenin genes (vtg) in fish, which is a common bioassay used to indicate effects consistent with exposure to exogenous estrogens. Solutions in water of 20-2000 μg L(-1) of an extract of a total OSPW NA concentrate did not induce expression of vtg in larval zebrafish, consistent with earlier studies which showed that much higher NA concentrations of undiluted OSPW were needed. Although 20-2000 μg L(-1) of an esterifiable NA subfraction of the OSPW NA concentrate did induce expression, this was of much lower magnitude to that induced by much lower concentrations of 17α-ethynyl estradiol, indicating that the effect of the total NAs was only weak. However, given the high NA concentrations and large volumes of OSPW extant in Canada, it is important to ascertain which of these esterifiable NA in the OSPW produce the effect. Up to 1000 μg L(-1) of an OSPW subfraction containing only alicyclic NA, and considered by most authors to be NA sensu stricto, did not produce induction; but, as predicted, 10-1000 μg L(-1) of an aromatic NA fraction did. Such effects by the aromatic acids are again consistent with those of only a weak estrogenic substance. These findings may help to focus studies of the most environmentally significant OSPW-related pollutants, if reproduced in a greater range of OSPW.
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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".