Polystyrene Nano- and Microplastic Particles Induce an Inflammatory Gene Expression Profile in Rat Neural Stem Cell-Derived Astrocytes In Vitro
Bibliographic record
Abstract
Microplastics are considered an emerging environmental pollutant due to their ubiquitous presence in the environment. However, the potential impact of microplastics on human health warrants further research. Recent studies have reported neurobehavioral and neurotoxic effects in marine and rodent models; however, their impact on the underlying cellular physiology in mammals remains unclear. Herein, we exposed neural stem cells and neural stem cell-derived astrocytes, oligodendrocytes, and neurons to various sizes and concentrations of polystyrene nano- and microplastics. We investigated their cellular uptake, impact on cytotoxicity, and alteration of gene expression through transcriptome profiling. The cell type most affected by decreased viability were astrocytes after 7 days of repeated exposure. Transcriptional analysis showed that 1274 genes were differentially expressed in astrocytes exposed to 500 nm microplastics, but only 531 genes were altered in astrocytes exposed to 50 nm nanoplastics. Both canonical pathway and Kyoto Encyclopedia of Genes and Genomes analysis showed that upregulated pathways were involved in neuroinflammation, innate and adaptive immunity, cell migration, proliferation, extracellular matrix remodeling, and cytoskeleton structures. The downregulated pathways were involved in lipid metabolism, specifically fatty acid oxidation and cholesterol metabolism. Our results show that neural stem cell-derived astrocytes repeatedly exposed to nano- and microplastics for 7 days undergo changes that are hallmarks of astrogliosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".