Microplastics may induce food dilution and endocrine disrupting effects in fathead minnows (Pimephales promelas), and decrease offspring quality
Bibliographic record
Abstract
Microplastics are a complex environmental contaminant that have been reported to cause a variety of impacts, although the mechanism of these impacts remains unclear. Many studies have investigated either sub-organismal or apical endpoints, while very few have attempted to integrate and link endpoints seen at multiple levels of organization. Here, we exposed fathead minnows to microplastics for their entire lifecycle, from the egg stage through to reproduction, and raised a subset of the offspring in clean water. We show that both preconsumer and environmentally sourced microplastics impact adult growth, lipid storage, and external colouration, suggesting a potential food dilution effect. Environmentally sourced microplastics, but not preconsumer microplastics, had further endocrine disrupting impacts on the parental generation and their offspring in the low concentration treatments such that egg production began later, eggs were less viable, and the offspring had higher rates of malformation. Low dose effects are a typical dose-response for endocrine disrupting contaminants. These results suggest that microplastic exposure, at concentrations relevant to what is being found in the environment, has potential implications for forage fish populations. Our findings also highlight the importance of using an integrative approach to understanding the mechanisms behind how and why microplastics impact organisms.
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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".