An Early–Life Stage Alternative Testing Strategy for Assessing the Impacts of Environmental Chemicals in Birds
Bibliographic record
Abstract
Early-life stage (ELS) toxicity tests are recognized as an advancement over current testing methodologies in terms of cost, animal use, and biological relevance. However, standardized ELS tests are not presently available for some vertebrate taxa, including birds. The present study describes a Japanese quail (Coturnix japonica) ELS test that is a promising candidate for standardization and applies it to test 8 environmental chemicals (ethinylestradiol, benzo[a]pyrene, chlorpyrifos, fluoxetine, lead(II)nitrate, trenbolone, seleno-L-methionine, hexabromocyclododecane). Individual chemicals were injected into the air cell of unincubated Japanese quail eggs at 3 concentrations, all predicted to cause ≤20% mortality. Survival to embryonic day 16 was consistently high (>90%) among the vehicle-injected controls. All chemicals, except ethinylestradiol, were detected in liver tissue, most at concentrations suggestive of embryonic clearance. Adverse effects were observed for 5 of the 8 chemicals; chlorpyrifos (41.1 µg/g) significantly increased developmental abnormalities and decreased embryo and gallbladder mass. Ethinylestradiol (54.2 µg/g) and hexabromocyclododecane (0.02 µg/g) decreased embryo mass and tarsus length, respectively. Benzo[a]pyrene (0.83 µg/g) and fluoxetine hydrochloride (32.7 µg/g) exceeded the 20% mortality cutoff. No effects were observed following lead(II)nitrate, seleno-L-methionine, or trenbolone exposure up to 10.7, 0.07, and 4.4 µg/g, respectively. Overall, our ELS approach was time- and cost-effective, caused minimal mortality in controls, effectively delivered diverse chemicals to the embryo, and permitted identification of apical outcomes, all of which provide support toward standardization. Environ Toxicol Chem 2019;39:141-154. © 2019 SETAC.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".