Athabasca Oil Sands Petcoke Extract Elicits Biochemical and Transcriptomic Effects in Avian Hepatocytes
Bibliographic record
Abstract
Petroleum coke or “petcoke” is a granular carbonaceous material produced during the upgrading of heavy crude oils, including bitumen. Petcoke dust was recently reported as an environmental contaminant in the Athabasca oil sands region, but the ecotoxicological hazards posed by this complex bitumen-derived material—including those to avian species—have not been characterized. In this study, solvent extracts (x) of delayed and fluid petcoke (xDP and xFP) were prepared and dissolved in dimethyl sulfoxide. A water-accommodated fraction of delayed petcoke (waDP) was also prepared. Graded concentrations of xDP, xFP, and waDP were administered to chicken and double-crested cormorant hepatocytes to determine effects on 7-ethoxyresorufin- O -deethylase (EROD) activity, porphyrin accumulation, and mRNA expression. Polycyclic aromatic compounds (PACs) were characterized, and xDP, xFP, and waDP had total PAC concentrations of 93 000, 270, and 5.3 ng/mL. The rank order of biochemical and transcriptomic responses was xDP > xFP > waDP (e.g., EROD EC 50s were lower for xDP compared to xFP and waDP). A total of 22, 18, and 4 genes were altered following exposure to the highest concentrations of xDP, xFP, and waDP, respectively, using a chicken PCR array comprising 27 AhR-related genes. To provide more exhaustive coverage of potential toxicity pathways being impacted, two avian ToxChip PCR arrays—chicken and double-crested cormorant—were utilized, and xDP altered the expression of more genes than xFP. Traditional PAC-related toxicity pathways and novel mechanisms of action were identified in two avian species following petcoke extract exposure. Extrapolation to real-world exposure scenarios must consider the bioavailability of the extracted PACs compared to those in exposed organisms.
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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".