A review of the neurobehavioural, physiological, and reproductive toxicity of microplastics in fishes
Bibliographic record
Abstract
Microplastics (MPs) have emerged as widespread environmental pollutants, causing significant threats to aquatic ecosystems and organisms. This review examines the toxic effects of MPs on fishes, with a focus on neurobehavioural, physiological, and reproductive impacts, as well as the underlying mechanisms of toxicity. Evidence indicates that MPs induce a range of neurobehavioural abnormalities in fishes, affecting social interactions and cognitive functions. Altered neurotransmitter levels are identified as a key mechanism driving behavioural alterations following MP exposure. Physiological abnormalities in fishes exposed to MPs are also reported, including neurotoxicity, immunotoxicity, and oxidative stress. These physiological disruptions can compromise the individual health of aquatic organisms. Furthermore, reproductive abnormalities linked to MP exposure are discussed, with a particular emphasis on disruptions in endocrine signaling pathways. These disruptions can impair reproductive success in fish species, impacting population numbers. Here we explore the critical role of endocrine disruptions in mediating reproductive effects after exposure to MPs, focusing primarily on the hypothalamic-pituitary-gonadal axis. Our review highlights the urgent need for interdisciplinary research efforts aimed at elucidating the full extent of MP toxicity and its implications for aquatic ecosystems. Lastly, we identify knowledge gaps for future research, including investigations into the transgenerational impacts, if any, of MP exposure and quantifying synergetic/antagonistic effects of MPs with other environmental pollutants. This expanded knowledge regarding the potential risks of MPs to aquatic wildlife is expected to aid policymakers in developing mitigation strategies to protect aquatic species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".