Apple Extract ( <i>Malus</i> sp.) and Rutin as Photochemopreventive Agents: Evaluation of Ultraviolet B-Induced Alterations on Skin Biopsies and Tissue-Engineered Skin
Bibliographic record
Abstract
The skin is exposed to the solar ultraviolet B (UVB) radiation, which leads to the formation of several types of skin damage responsible for cancer initiation and aging. Malus sp. is a genus of apples, which are a good source of polyphenolic compounds. Malus sp. and more precisely one of its components, rutin, have preventive effects on many diseases caused by reactive oxygen species. In addition, previous studies have suggested the topical usage of the extract as a cosmetic product to prevent skin damage caused by oxidative stress. In this study, we evaluated the efficacy of two topical formulations containing 1.25% of Malus sp. extract and the equivalent amount of rutin (0.75%). The photochemopreventive effect was assessed on two three-dimensional (3D) skin models, that is, ex vivo skin explants and 3D tissue-engineered skin to compare the models. Both formulations protected against the UVB-induced increase in sunburn cell formation, as well as caspase-3 activation and cyclobutane pyrimidine dimer formation in both skin models. Furthermore, the formulations inhibited the lipid peroxidation and the metalloproteinase formation induced by UVB radiation. The tissue-engineered skins and the skin explants provided effective tools to assess the UVB-induced damages. These results support use of the Malus sp. extract and rutin as skin photochemopreventive agents for topical application.
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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 | 0.000 | 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".