A systematic review and experimental study of micro/nanoplastic-induced endocrine disruption in rodents: Potential links to autism spectrum disorder
Bibliographic record
Abstract
Recent research shows that microplastic (diameter < 5 mm) and nanoplastic (diameter < 1 μm) exposures can have endocrine-disrupting effects and lead to autism spectrum disorder (ASD)-like behaviours in rodent models. We combine both a (i) systematic literature review and (ii) experimental study to synthesize the potential mechanisms underlying the link between micro-/nanoplastic (MNP) exposure and ASD, focusing on endocrine disruption and articles utilizing rodent models. First, we identify and discuss trends in the literature, outline research gaps, and suggest future directions. Most articles measured gonadal hormones in male adult rodents and consistently reported decreased testosterone (T), luteinizing hormone (LH) and follicle-stimulating hormone (FSH) with MNP exposure. Females were understudied, with no trends emerging in exposure-induced hormone disruption. Second, we present experimental data demonstrating direct effects of maternal polystyrene NP exposure on neuroendocrine systems and inflammatory markers in the fetal brain. Cytokines, interleukin-2 (IL-2) and interleukin-6 (IL-6), and triiodothyronine (T3) were significantly altered in the fetal brain following prenatal exposure to NPs, and thyroxine (T4) and T were significantly suppressed in female NP-exposed fetuses but not in males. Together, these findings demonstrate that MNP exposure during adulthood and early development affect multiple endocrine systems, including those implicated in autism spectrum disorder, in a sex-dependent manner. We synthesize how such results are important to motivate exposure studies in animals and humans and future regulatory guidelines on MNPs.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".