Life Cycle Exposure to Environmentally Relevant Concentrations of Diphenyl Phosphate (DPhP) Inhibits Growth and Energy Metabolism of Zebrafish in a Sex-Specific Manner
Bibliographic record
Abstract
Due to commercial uses and environmental degradation of aryl phosphate esters, diphenyl phosphate (DPhP) is frequently detected in environmental matrices and is thus of growing concern worldwide. However, information on potential adverse effects of chronic exposure to DPhP at environmentally realistic concentrations was lacking. Here, we investigated the effects of life cycle exposure to DPhP on zebrafish at environmentally relevant concentrations of 0.8, 3.9, or 35.6 μg/L and employed a dual-omics approach (metabolomics and transcriptomics) to characterize potential modes of action. Exposure to DPhP at 35.6 μg/L for 120 days resulted in significant reductions in body mass and length of male zebrafish, but did not cause those same effects to females. Predominant toxicological mechanisms, including inhibition of oxidative phosphorylation, down-regulation of fatty acid oxidation, and up-regulation of phosphatidylcholine degradation, were revealed by integrated dual-omics analysis and successfully linked to adverse outcomes. Activity of succinate dehydrogenase and protein content of carnitine O -palmitoyltransferase 1 were significantly decreased in livers of male fish exposed to DPhP, which further confirmed the proposed toxicological mechanisms. This study is the first to demonstrate that chronic, low-level exposure to DPhP can retard growth via inhibiting energy output in male zebrafish.
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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".