Genotoxicity, cytotoxicity, and reactive oxygen species induced by single‐walled carbon nanotubes and C<sub>60</sub> fullerenes in the FE1‐Muta™Mouse lung epithelial cells
Bibliographic record
Abstract
Viability, cell cycle effects, genotoxicity, reactive oxygen species production, and mutagenicity of C(60) fullerenes (C(60)) and single-walled carbon nanotubes (SWCNT) were assessed in the FE1-Mutatrade markMouse lung epithelial cell line. None of these particles induced cell death within 24 hr at doses between 0 and 200 microg/ml or during long-term subculture exposure (576 hr) at 100 microg/ml, as determined by two different assays. However, cell proliferation was slower with SWCNT exposure and a larger fraction of the cells were in the G1 phase. Exposure to carbon black resulted in the greatest reactive oxygen species generation followed by SWCNT and C(60) in both cellular and cell-free particle suspensions. C(60) and SWCNT did not increase the level of strand breaks, but significantly increased the level of FPG sensitive sites/oxidized purines (22 and 56%, respectively) determined by the comet assay. The mutant frequency in the cII gene was unaffected by 576 hr of exposure to either 100 microg/ml C(60) or SWCNT when compared with control incubations, whereas we have previously reported that carbon black and diesel exhaust particles induce mutations using an identical exposure scenario. These results indicate that SWCNT and C(60) are less genotoxic in vitro than carbon black and diesel exhaust particles.
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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".