3. Comparing the Induction of CYP1A in American Eel (Anguilla rostrata) and Rainbow Trout (Oncorhynchus mykiss) by the Dioxin‐like Compound 2,3,7,8‐ tetrachlorodibenzo‐p‐dioxin (TCDD)
Bibliographic record
Abstract
The American eel population native to Lake Ontario has declined by 98% since 1985, and the associated fishery in Ontario has been rendered uneconomical. By recognizing the American eel as a “species of concern” under Canada’s Species at Risk Act, the federal government has indicated that conservation of this population is a priority. Conservation is a difficult task, however, considering the underlying mechanism of decline remains unknown. One hypothesized mechanism states that dietary bioaccumulation of dioxin‐like compounds (DLCs) by the female and transfer of these environmental contaminants to her eggs precludes proper development of eel embryos and larvae. These developmental effects have been well characterized in the rainbow trout, and include craniofacial malformations, edema, hemorrhaging, increased mortality, and up‐regulation or induction of the CYP1A enzyme. Therefore, increased CYP1A concentrations may be used as a biomarker for potential toxicity, and a quantitative means of comparing the sensitivity of different organisms to DLCs and their effects. My project uses immunohistochemistry (IHC) and the EROD assay to quantify CYP1A induction in American eel exposed to DLCs, and compares this sensitivity to that of rainbow trout, a reference species. Preliminary EROD results suggest no significant difference between eels and rainbow trout, and results of IHC analysis are currently under examination. If these data suggest an increased sensitivity of the American eel to DLCs, this would substantiate the hypothesis that chemical accumulation in adult eels and exposure to eggs during oogenesis may threaten the viability of embryos and larvae, which would precipitate the catastrophic population decline.
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".