Development of a Comprehensive Toxicity Pathway Model for 17α-Ethinylestradiol in Early Life Stage Fathead Minnows (<i>Pimephales promelas</i>)
Bibliographic record
Abstract
Abstract There is increasing pressure to develop alternative ecotoxicological risk assessment approaches that do not rely on expensive, time-consuming, and ethically questionable live animal testing. This study aimed to develop a comprehensive early life stage toxicity pathway model for the exposure of fish to estrogenic chemicals that is rooted in mechanistic toxicology. Embryo-larval fathead minnows (FHM; Pimephales promelas) were exposed to graded concentrations of 17α-ethinylestradiol (water control, 0.01% DMSO, 4, 20, and 100 ng/L) for 32 days. Fish were assessed for transcriptomic and proteomic responses at 4 days post-hatch (dph), and for histological and apical end points at 28 dph. Molecular analyses revealed core responses that were indicative of observed apical outcomes, including biological processes resulting in overproduction of vitellogenin and impairment of visual development. Histological observations indicated accumulation of proteinaceous fluid in liver and kidney tissues, energy depletion, and delayed or suppressed gonad development. Additionally, fish in the 100 ng/L treatment group were smaller than controls. Integration of omics data improved the interpretation of perturbations in early life stage FHM, providing evidence of conservation of toxicity pathways across levels of biological organization. Overall, the mechanism-based embryo-larval FHM model showed promise as a replacement for standard adult live animal tests.
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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 | 0.001 |
| 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 | 0.001 |
| 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".