Do the polyphenolic compounds from natural products can protect the skin from ultraviolet rays?
Bibliographic record
Abstract
Excessive exposure to the sun is a major cause that augment the skin cancer, erythema, edema, abnormal pigmentation and finally suppress the immune system. Due to stratospheric ozone depletion and climate change UV levels are increasing, there is an urgent need to protect human skin from the harmful effects of UV. Compounds with photo- protection activity are very useful in reducing the effect of ultraviolet rays. For this reason, today’s sunscreens that contain one or more different types of chemical filters are used to protect the skin from ultraviolet rays. In the market, several synthetic, UV filter molecules are available, but they have limited use because these active molecules may create adverse effects on human skin such as, cancer, estrogenic activity, or photosensitivity reactions, contact dermatitis, mutations. Therefore, the development of formulations containing plant extracts and algae that may be potentially safer is being extensively studied. For this purpose, we can refer to polyphenol compounds such as flavonoids, which are a branch of natural substances that act as catalysts in the optical phase of photosynthesis, and act as anti-stress agents in plants by removing oxygen free radicals. Natural flavonoids have light and direct protection potential due to their ability to absorb ultraviolet rays and due to their antioxidant ability, as well as anti-inflammatory and immune modulating agents. In this article, the sun photoprotection properties of compounds with polyphenolic structure such as flavonoids derived from plant extracts or algae, as well as new methods in optimizing skin protection products against UV radiation have been investigated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".