Unveiling the Molecular Effects of Replacement and Legacy PFASs: Transcriptomic Analysis of Zebrafish Embryos Reveals Surprising Similarities and Potencies
Bibliographic record
Abstract
The prevalence of per- and poly fluoroalkyl substances (PFASs) in the environment has prompted restrictions on legacy PFASs due to their recognized toxic effects. Consequently, alternative "replacement" PFASs have been introduced and are prevalent in environmental matrices. Few studies have investigated the molecular effects of both legacy and replacement PFASs under short-term exposures. This study aimed to address this by utilizing transcriptomic sequencing to compare the molecular impacts of exposure to concentrations 0.001-5 mg/L of the legacy PFOS and two of its replacements, PFECHS and FBSA. Using zebrafish embryos, the research assessed apical effects (mortality, morphology, and growth), identified differentially expressed genes (DEGs) and enriched pathways, and determined transcriptomic points of departure (tPoDs) for each compound. Results indicated that PFOS exhibited the highest relative potency, followed by PFECHS and then FBSA. While similarities were observed among the ranked DEGs across all compounds, over-representation analysis revealed slight differences. Notably, PFOS demonstrated the lowest tPoD identified to date. These findings raise concerns regarding the safety of emerging replacement PFASs and challenge assumptions about PFAS toxicity solely resulting from their accumulative potential. As replacement PFASs proliferate in the environment, this study underscores the need for heightened scrutiny of their effects and questions current regulatory thresholds.
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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".