ROS-dependent degeneration of human neurons induced by environmentally relevant levels of micro- and nanoplastics of diverse shapes and forms
Bibliographic record
Abstract
Our study explores the pressing issue of micro- and nanoplastics (MNPs) inhalation and their subsequent penetration into the brain, highlighting a significant environmental health concern. We demonstrate that MNPs can indeed penetrate murine brain, warranting further investigation into their neurotoxic effects in humans. We then proceed to test the impact of MNPs at environmentally relevant concentrations, with focusing on variations in size and shape. Our findings reveal that these MNPs induce oxidative stress, cytotoxicity, and neurodegeneration in human neurons, with cortical neurons being more susceptible than nociceptors. Furthermore, we examine the role of biofilms on MNPs, demonstrating that MNPs can serve as a vehicle for pathogenic biofilms that significantly exacerbate these neurotoxic effects. This sequence of investigations reveals that minimal MNPs accumulation can cause oxidative stress and neurodegeneration in human neurons, significantly risking brain health and highlights the need to understand the neurological consequences of inhaling MNPs. Overall, our developed in vitro testing battery has significance in elucidating the effects of environmental factors and their associated pathological mechanisms in human neurons.
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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".