Bisphenol A in eggs causes development-specific liver molecular reprogramming in two generations of rainbow trout
Bibliographic record
Abstract
Bisphenol A (BPA) is widely used in the manufacture of plastics and epoxy resins and is prevalent in the aquatic environment. BPA disrupts endocrine pathways in fish, but the long-term developmental implications are unknown. We demonstrate that BPA deposition in the eggs of rainbow trout (Oncorhynchus mykiss), an ecologically and economically important species of fish, reprograms liver metabolism in the offspring and alters the developmental growth trajectory in two generations. Specifically, BPA reduces growth during early development, followed by a catch-up growth post-juveniles. More importantly, we observed a developmental shift in the liver transcriptome, including an increased propensity for protein breakdown during early life stages to lipid and cholesterol synthesis post- juveniles. The liver molecular responses corresponded with the transient growth phenotypes observed in the F1 generation, and this was also evident in the F2 generation. Altogether, maternal and/or ancestral embryonic exposure to BPA affects liver metabolism leading to development-distinct effects on growth, underscoring the need for novel risk assessment strategies for this chemical in the aquatic environment. This is particularly applicable to migratory species, such as salmon, where distinct temporal changes in growth and physiology during development are critical for their spawning success.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".