Inhibitory effect of<i>Aralia elata</i>ethanol extract against skin damage in UVB-exposed human keratinocytes and human dermal fibroblasts
Bibliographic record
Abstract
Purpose: Solar ultraviolet (UV) radiation causes inflammation and matrix metalloproteinase (MMP) overexpression and extracellular matrix depletion, leading to skin photoaging such as wrinkle formation, dryness, and sagging. Activation of MMP is influenced by various molecules such as reactive oxygen species (ROS), proinflammatory cytokines, and transient receptor potential vanilloid type (TRPV)-1, which are increased in UV-irradiated skin cells. Aralia elata (AE) ethanolic extract was reported to inhibit ROS generation caused by UVB-irradiation in keratinocytes. In this study, we investigated the photoprotective effect of AE ethanolic extract on UVB-irradiated human keratinocytes (HaCaT) and human dermal fibroblasts (HDF). Methods: AE was freeze-dried, extracted in 70% ethanol, and concentrated. Skin cells were treated with AE extract for 24 h and then exposed to UVB (55 mJ/cm²). After 48 h of incubation, proinflammatory cytokines, MMP-1, type-1 procollagen, and TRPV-1 levels were measured by ELISA or Western blotting. Results: Treatment with AE extract (100 μg/mL) significantly inhibited UVB-induced IL-6, IL-8, and PGE2 production in HaCaT by 25.6%, 5.3%, and 70.2%, respectively, and also inhibited elevation of MMP-1 and TRPV-1 caused by UVB irradiation by 20.0% and 41.9%, respectively (p < 0.05). In HDF, AE extract treatment significantly inhibited both elevation of MMP-1 and reduction of type-1 procollagen caused by UVB irradiation (p < 0.05). In addition, type-1 procollagen was elevated by AE extract treatment in normal HDFs (p < 0.05). Conclusion: AE 70% ethanol extract has photoprotective ability via reduction of proinflammatory mediators, TRPV-1 and MMP-1 production, and elevation of collagen synthesis. Our findings suggest that AE extract might be a good natural material to protect against UVB-induced premature skin aging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".