Amino acid sequence of the AhR1 ligand-binding domain predicts avian sensitivity to dioxin like compounds: In vivo verification in European starlings
Bibliographic record
Abstract
Research has demonstrated that the sensitivity of avian species to the embyrotoxic effects of dioxin-like compounds can be predicted by the amino acid identities at two key sites within the ligand-binding domain of the aryl hydrocarbon receptor 1 (AhR1). The domestic chicken (Gallus gallus domesticus) has been established as a highly sensitive species to the toxic effects of dioxin-like compounds. Results from genotyping and in vitro assays predict that the European starling (Sturnus vulgaris) is also highly sensitive to dioxin-like compound toxicity. The objective of the present study was to test that prediction in vivo. To do this, we used egg injections in field nesting starlings with 3,3',4,4',5-pentachlorobiphenyl (PCB-126), a dioxin-like polychlorinated biphenyl. Eggs were dosed with either the vehicle control or 1 of 5 doses (1.4, 7.1, 15.9, 32.1, and 52.9 ng PCB-126/g egg). A dose-dependent increase in embryo mortality occurred, and the median lethal dose (LD50; 95% confidence interval [CI]) was 5.61 (2.33-9.08) ng/g. Hepatic CYP1A4/5 messenger RNA (mRNA) expression in hatchlings also increased in a dose-dependent manner, with CYP1A4 being more induced than CYP1A5. No effect of dose on morphological measures was seen, and we did not observe any overt malformations. These results indicate that, other than the chicken, the European starling is the most sensitive species to the effects of PCB-126 on avian embryo mortality reported to date, which supports the prediction of relative sensitivity to dioxin-like compounds based on amino acid sequence of the AhR1.
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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".