Increased mutant frequency by carbon black, but not quartz, in the <i>lacZ</i> and <i>cII</i> transgenes of muta<sup>™</sup>mouse lung epithelial cells
Bibliographic record
Abstract
Carbon black and quartz are relatively inert solid particulate materials that are carcinogenic in laboratory animals. Quartz is a human carcinogen, whereas data on carbon black are contradictory, and there are few data on mammalian mutagenesis. We determined the mutant frequency following eight repeated 72-hr incubations with 75 mug/ml carbon black (Printex 90) or 100 mug/ml quartz (SRM1878a) particles in the FE1 Muta Mouse lung epithelial cell line. For carbon black exposed cells, the mutant frequency was 1.40-fold (95% CI: 1.22-1.58) for cII and 1.23-fold (95% CI: 1.10-1.37) for lacZ compared with identically passaged untreated cells. Quartz did not significantly affect the mutant frequency. Carbon black also induced DNA strand breaks (P = 0.02) and oxidized purines (P = 0.008), as measured by the Comet assay. Quartz induced marginally more oxidized purines, but no change in strand breaks. We detected five (phenanthrene, flouranthene, pyrene, benzo[a]anthracene, and chrysene) of the 16 EPA priority polycyclic aromatic hydrocarbons (PAHs) in an extract of carbon black. The detected PAHs are only weakly mutagenic compared with benzo[a]pyrene, and were present in very low amounts. In conclusion, carbon black was weakly mutagenic in vitro at the cII and lacZ loci. It also induced DNA strand breaks and oxidized DNA bases. More studies are essential for understanding the biological significance of these findings, and clearly documenting DNA sequence changes. The results do not necessarily imply that other carbonaceous nano materials are genotoxic.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".