<title>Deleterious effects of sunscreen titanium dioxide nanoparticles on DNA: efforts to limit DNA damage by particle surface modification</title>
Bibliographic record
Abstract
Sunlight can have deleterious effects on humans: causes sunburns and is the principal cause of skin cancers. Usage of TiO2 (and ZnO) in sunscreen lotions, widely used as UVA/UVB blockers, and intended to prevent sunburns and to protect consumers from skin cancers (carcinomas and melanomas) is examined. Although used to mineralize many undesired organic pollutants, TiO2 is considered to be a safe physical sunscreen agent because it reflects and scatters both UVB (290-320 nm) and UVA (320-400 nm) sunlight; however, it also absorbs substantial UV radiation which, in aqueous media, yields hydroxyl radial ((DOT)OH) species. These species cause substantial damage to DNA (J. Photochem.Photobio.A:Chem.,111(1997)205). Most importantly, sunlight-illuminated sunscreen TiO2 particles catalyze DNA damage both in vitro and in human cells (FEBS Letters, 418 (1997)87). These results raise concerns on the overall effects of sunscreens and raise the question on the suitability of photoactive TiO2 as a sunscreen component without further studies. The photocatalytically active nature of these metal oxides necessitates some changes since even the TiO2 specimens currently used in suncreams cause significant DNA strand breaks.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".