Flavonols Protect Against UV Radiation-Induced Thymine Dimer Formation in an Artificial Skin Mimic
Bibliographic record
Abstract
PURPOSE: Exposure of skin to ultraviolet light has been shown to have a number of deleterious effects including photoaging, photoimmunosuppression and photoinduced DNA damage which can lead to the development of skin cancer. In this paper we present a study on the ability of three flavonols to protect EpiDerm™, an artificial skin mimic, against UV-induced damage. METHODS: EpiDerm™ samples were treated with flavonol in acetone and exposed to UVA (100 kJ/m(2) at 365 nm) and UVB (9000 J/m(2) at 310 nm) radiation. Secretion of matrix metalloproteinase-1 (MMP-1) and tumor necrosis factor-α (TNF-a) were determined by ELISA, cyclobutane pyrimidine dimers were quantified using LC-APCI-MS. RESULTS: EpiDerm™ treated topically with quercetin significantly decreased MMP-1 secretion induced by UVA (100 µM) or UVB (200 µM) and TNF-a secretion was significantly reduced at 100 µM quercetin for both UVA and UVB radiation. In addition, topically applied quercetin was found to be photostable over the duration of the experiment. EpiDerm™ samples were treated topically with quercetin, kaempferol or galangin (52 µM) immediately prior to UVA or UVB exposure, and the cyclobutane thymine dimers (T-T (CPD)) were quantified using an HPLC-APCI MS/MS method. All three flavonols significantly decreased T-T (CPD) formation in UVB irradiated EpiDerm™, however no effect could be observed for the UVA irradiation experiments as thymine dimer formation was below the limit of quantitation. CONCLUSIONS: Our results suggest that flavonols can provide protection against UV radiation-induced skin damage through both antioxidant activity and direct photo-absorption. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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".