Polystyrene nanoplastics target electron transport chain complexes in brain mitochondria
Bibliographic record
Abstract
Polystyrene nanoplastics (PS-NPs), derived from the breakdown of environmental plastics, have been detected in multiple tissues including the brain, raising concerns over their potential neurotoxicity. Mitochondrial dysfunction is a hallmark of neurodegenerative diseases, ageing, and exposure to classical neurotoxins and pesticides. In this study we investigated the effects of PS-NPs on mitochondrial function in both non-synaptic and synaptic mitochondria isolated from rat brains. Exposure to PS-NPs significantly reduced oxygen specifically impairing electron flow between complexes I–III, II–III and complex IV. Interestingly, individual activities of complex I or complex II were not significantly affected, suggesting that PS-NPs selectively disrupt electron transfer from complex I to complex III, or from complex II to complex III. Similar inhibition of electron flow between complexes I–III and II–III were identified in synaptic mitochondria, indicating the potential for nanoplastics to affect synaptic plasticity. Our findings reveal a mitochondrial mechanism of PS-NPs-induced neurotoxicity and highlight their potential contribution to brain energy metabolism deficits linked to environmental pollutants. Created in BioRender. • Polystyrene nanoplastics (PS-NPs) inhibit brain mitochondrial respiration. • PS-NPs impair both synaptic and non-synaptic mitochondrial complexes. • PS-NPs selectively impair electron transfer between complexes I–III and II–III. • Findings reveal a novel mechanism of PS-NP neurotoxicity relevant to exposure.
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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".