Anti-wrinkle Effect of PLA2-free Bee Venom against UVB-irradiated Human Skin Cells
Bibliographic record
Abstract
The use of bee venom (Apis mellifera L., BV) occasionally causes side effects such as inflammation and allergic reactions in the recipients. Several case reports also suggested the treatment of BV has some limitations in its clinical uses, due to the occurrence of dermal necrosis and anaphylatic reactions. It is generally understood that bee venom allergy is mainly the result of its allergic component, phospholipase A2 (PLA2). The present study was aimed to generate PLA2-free bee venom (PBV) and evaluate its efficacy as skin care and cosmetic preparation, comparing with original bee venom (BV). Our results showed that both BV and PBV exhibited significant protective effects in UVB-irradiated human keratinocyte (HaCaT) and human dermal fibroblast (HDF) cells and they also induced type I collagen synthesis in UVB-irradiated HDF cells except BV at 3 μg/ml. Furthermore, BV and PBV showed the inhibition of UVB-stimulated matrix metalloproteinase-1 (MMP-1), a major collagen degrading enzyme in skin. However, BV, unlike PBV, exhibited strong cytotoxicities in skin cells (both HaCaT and HDF) at its working concentrations of anti-wrinkle effect. The underlying cell signaling mechanisms of anti-wrinkle effects of BV and PBV were demonstrated by the activation of ERK1/2, and p38. Conclusively, PBV appears to be the bee venom of choice with less cytotoxicity and higher efficacy on UVB-irradiated skin cells in comparison with original bee venom (BV). Therefore, PBV can better be used as a cosmetic ingredient exhibiting excellent anti-wrinkle effect against photoaging than original BV.
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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".