Use of a Novel Double-Crested Cormorant ToxChip PCR Array and the EROD Assay to Determine Effects of Environmental Contaminants in Primary Hepatocytes
Bibliographic record
Abstract
In vitro screening tools and 'omics methods are increasingly being incorporated into toxicity studies to determine mechanistic effects of chemicals and mixtures. To date, the majority of these studies have been conducted with well-characterized laboratory animal models. In the present study, well-established methods developed for chicken embryonic hepatocyte (CEH) studies were extended to a wild avian species, the double-crested cormorant (DCCO; Phalacrocorax auritus), in order to compare the effects of several environmental contaminants on cytotoxicity, ethoxyresorufin O-deethylase (EROD) activity, and mRNA expression. Five organic flame retardants and one plasticizer decreased cormorant hepatocyte viability in a similar manner to that observed in previous studies with CEH. EROD activity was induced in a concentration-dependent manner following exposure to two dioxin-like chemicals and the calculated EC50 values were concordant with domestic avian species from similar species sensitivity categories. Transcriptomic effects were determined using a novel DCCO PCR array, which was designed, constructed and validated in our laboratory based on a commercially available chicken PCR array. The DCCO array has 27 target genes covering a wide range of toxicity pathways. Gene profiles were variable among the 10 chemicals screened; however, good directional concordance was observed with regard to results previously obtained in CEH. Overall, the application of well-established methods (i.e., CEH and chicken PCR array) to the double-crested cormorant demonstrated the portability of the techniques to an indicator species of ecological relevance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".