Exposure to cotton and polyester microfibers leads to different fatty acid profiles and chemical contaminants concentrations in juvenile rainbow trout (<i>Oncorhynchus mykiss</i>)
Bibliographic record
Abstract
Synthetic and non-synthetic microfibers are found in habitats and wildlife globally. Yet, it remains unclear whether different microfiber types affect fish or increase bioaccumulation of sorbed persistent organic pollutants (POPs). To better understand microfiber effects in fish, we tested different microfiber types (cotton and polyester), and to examine microfibers as a vector of chemicals we tested them with and without chemical mixtures (clean microfibers and microfibers exposed to treated wastewater effluent). The effects on survival, growth, condition indices, and fatty acids, along with bioaccumulation of polybrominated diphenyl ethers (PBDEs), were assessed in Rainbow Trout (Oncorhynchus mykiss). Fish were exposed through their diet to ∼100 microfibers/d for 28 d. Fatty acid contents varied between fish exposed to cotton and polyester microfibers (p < 0.05), but the magnitude of these differences were small and not different when compared to control fish. However, fish that were exposed to microfibers with treated wastewater had significantly lower n-3/n-6 fatty acid ratios compared to fish exposed to microfibers without wastewater (regardless of material type), suggesting higher inflammation and stress levels in treatments with microfibers exposed to wastewater. Finally, fish fed cotton microfibers showed higher concentrations of nona-BDEs. Our research suggests that environmentally relevant concentrations of microfibers cause minimal differences in PBDE concentrations and essential fatty acids, although material type may play a role in chemical bioavailability, especially for cotton. Further, our findings confirm that non-synthetic microfibers (e.g., cotton), show impacts in biota. We thus conclude that microfibers broadly, should be considered as potentially carrying having their own unique suites of contaminants, instead of purely focusing on plastic microfibers in research and policy.
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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".