Mechanistic insights into microplastic-induced reproductive toxicity in aquatic organisms: A comprehensive review
Bibliographic record
Abstract
Microplastics (MPs) are widespread contaminants in aquatic ecosystems and pose significant threats to both organisms and the environment. Their small size, high surface area, and capacity to adsorb toxic chemicals allow MPs to infiltrate food webs, affecting organisms across trophic levels. This review explores the intricate mechanisms by which MPs induce reproductive and endocrine toxicity, focusing on their physical and chemical properties, bioaccumulation dynamics, and associated molecular pathways. MPs interfere with hormonal homeostasis, oxidative stress responses, and apoptotic pathways, leading to disruptions in the hypothalamic-pituitary-gonadal axis, impaired steroidogenesis, and gonadal dysfunction. These effects manifest as reduced fertility, altered gametogenesis, and multigenerational reproductive impairments across diverse aquatic taxa. Furthermore, MPs serve as carriers for endocrine-disrupting chemicals, compounding their adverse effects on organisms and aquatic biodiversity. Through a synthesis of recent research, this review identifies key signaling pathways, including MAPK, PI3K-AKT, mTOR, NF-κB, PPAR and NLRP3 inflammasome, that may play a role in MP-induced reproductive toxicity. The findings underscore the urgent need for advanced mitigation strategies, regulatory frameworks, and further research to combat the ecological consequences of MP pollution. Prioritizing targeted interventions is essential to safeguard aquatic biodiversity and ensure ecosystem resilience against the pervasive threat of MPs.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".