A Systematic Genotoxicity Assessment of a Suite of Metal Oxide Nanoparticles Reveals Their DNA Damaging and Clastogenic Potential
Bibliographic record
Abstract
Metal oxide nanoparticles (MONP/s) induce DNA damage, which is influenced by their physicochemical properties. In this study, the high-throughput CometChip and micronucleus (MicroFlow) assays were used to investigate DNA and chromosomal damage in mouse lung epithelial cells induced by nano and bulk sizes of zinc oxide, copper oxide, manganese oxide, nickel oxide, aluminum oxide, cerium oxide, titanium dioxide, and iron oxide. Ionic forms of MONPs were also included. The study evaluated the impact of solubility, surface coating, and particle size on response. Correlation analysis showed that solubility in the cell culture medium was positively associated with response in both assays, with the nano form showing the same or higher response than larger particles. A subtle reduction in DNA damage response was observed post-exposure to some surface-coated MONPs. The observed difference in genotoxicity highlighted the mechanistic differences in the MONP-induced response, possibly influenced by both particle stability and chemical composition. The results highlight that combinations of properties influence response to MONPs and that solubility alone, while playing an important role, is not enough to explain the observed toxicity. The results have implications on the potential application of read-across strategies in support of human health risk assessment of MONPs.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".