Prefertilization Exposure of Rainbow Trout Eggs to Per- and Polyfluoroalkyl Substances to Simulate Accumulation During Oogenesis
Bibliographic record
Abstract
Aqueous film-forming foams (AFFFs) are used in firefighting and are sources of per- and polyfluoroalkyl substances (PFAS) to the environment through surface runoff and groundwater contamination at defense and transportation sites. Little is known regarding the toxicity and bioaccumulation of newer AFFF formulations containing novel PFAS. To mimic maternal transfer of PFAS, prefertilization rainbow trout eggs were exposed to three PFAS using novel methodologies. Batches of unfertilized oocytes were exposed for 3 h to 0, 0.01, 0.1, 1, or 10 µg/ml separately to perfluorooctanoic acid, perfluorohexanoic acid, or perfluorooctanesulfonic acid in either coelomic fluid or Cortland's solution. After exposure, the gametes were fertilized and rinsed with dechlorinated water. Egg yolk was aspirated from a subset of fertilized eggs for PFAS quantification. Each PFAS was detected in yolks of eggs exposed to the respective PFAS, and yolk concentrations were directly proportional to concentrations in aqueous media to which they were exposed. Exposure in coelomic fluid or Cortland's solution resulted in similar concentrations of PFAS in egg yolks. Ratios of PFAS concentrations in oocytes to concentrations in exposure media (oocyte fluid ratios) were <0.99 when exposed from 0.01 to 10 µg/ml and <0.45 when exposed from 0.1 to 10 µg/ml for both media and all three PFAS, demonstrating that the water solubility of the chemicals was relatively great. Prefertilization exposure of eggs effectively introduced PFAS into unfertilized egg yolk. This method provided a means of mimicking maternal transfer to evaluate toxicity to developing embryos from an early stage. This method is more rapid and efficient than injection of individual fertilized eggs and avoids trauma from inserting needles into eggs. Environ Toxicol Chem 2021;40:3159-3165. © 2021 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) | 0.000 | 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) | 0.002 | 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".