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
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it