Acute toxicity, behaviour, metabolism, and transcriptomic points of departure in embryo-larval zebrafish exposed to nine different PFAS
Bibliographic record
Abstract
Most per- and poly-fluoroalkyl substances (PFAS) lack toxicity data, and the hazards associated with different PFAS chemical structures have not been systematically assessed using in vivo models. To address this gap, we compared the toxicity of nine PFAS in embryo-larval zebrafish, an emerging alternative to conventional in vivo models. Exposures were conducted from 0 to 5 days post-fertilization with semi-static renewal. We then evaluated three apical toxicity endpoints (developmental toxicity (mortality/malformation), swimming behavior, and metabolic activity) alongside transcriptomic changes using high-throughput transcriptomics. These data were used to derive apical and transcriptomic points of departure (aPODs and tPODs, respectively). Transcriptomic benchmark concentration modeling in BMDExpress v3.2 was performed to derive tPODs using multiple approaches. Overall, PFAS potency increased with longer fluorinated carbon chain lengths and for PFAS containing sulfonic groups. tPODs were generally the most sensitive endpoints, typically falling within 10-fold range below aPODs. These results support previous findings that tPODs provide suitably conservative PODs in chemical assessments. Our results contribute new data on PFAS toxicity in early-life stage toxicity and demonstrate an economical and ethically viable high-throughput platform for systematic evaluation of chemical hazards and potencies for risk assessment applications. • PFAS-exposed zebrafish revealed concentration-dependent responses • Longer-chain PFAS with -SO 3 showed greater toxicity at molecular and apical levels • Transcriptomic POD (tPOD) provided more sensitive thresholds than apical POD • Integrated toxicity ranking was PFDS>PFOS>PFNA≥PFDA>PFHxS>PFOA ≥PFHxA≥PFBS≥PFBA • tPOD approach using early zebrafish is powerful for systematic chemical assessment
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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 | 0.001 |
| 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".