Accumulation of ligands for aryl hydrocarbon and sex steroid receptors in fish exposed to treated effluent from a bleached sulfite/groundwood pulp and paper mill
Bibliographic record
Abstract
The accumulation of ligands for the aryl hydrocarbon receptor (AhR) and fish sex steroid receptors was investigated using two separate controlled fish exposures to final effluent from a bleached sulfite/groundwood mill in New Brunswick, Canada. In the first experiment, hepatic tissue extracts from exposed fish were fractionated according to lipophilicity. Fractions with different octanol-water (Kow) partition coefficients were tested for the presence of bioavailable chemicals that function as ligands for the AhR in H4IIE cells, rainbow trout hepatic estrogen receptors (ER), goldfish testicular androgen receptors (AR), and goldfish sex steroid binding protein (SSBP). Fish accumulated ligands for each receptor after 4-d exposure to effluent. Single fractions contained ligands for the AhR and the ER, while multiple fractions competed for the AR and SSBP. Fish also accumulated ligands for the AhR and SSBP from Saint John River dilution water, indicating upstream sources of bioactive substances. Semipermeable-membrane devices deployed concurrently with fish accumulated ligands from effluent for all receptors except the ER. In the second experiment, accumulated ligands were evaluated after exposure of fish to effluent for two different durations and following a depuration period. Hepatic mixed function oxygenase activity and whole-liver hormonal activity, measured as binding to SSBP, returned to background following 6 d depuration and were reduced but still significant after 12-d exposure to effluent. Whole-liver extract affinities for the AR were maintained after extended exposure and depuration, indicating the potential for AR ligands to bioaccumulate. The accumulation of AhR ligands and ligands for sex steroid receptors provides a mechanistic linkage to effects on growth, development, and performance of fish exposed to effluent from this and other mills.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Bench or experimental | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".