Anti-aging potential of apple (Malus domestica) ethanol extract in fibroblast cells exposed to ultraviolet light via modulation of CASP8 expression, total antioxidant capacity (T-AOC) and glutathione (GSH)
Bibliographic record
Abstract
Skin aging is a complex process influenced by extrinsic and intrinsic factors, with ultraviolet (UV) exposure being a primary external contributor. UV radiation initiates reactive oxygen species (ROS) production, causing oxidative stress, apoptosis, and reduced collagen synthesis, leading to premature aging. Caspase-8 (CASP8) plays a key role in apoptosis, while glutathione (GSH) and total antioxidant capacity (T-AOC) are crucial for cellular defense. The use of natural ingredients as photoprotective and anti-aging is increasingly in demand due to their potential safety. Apple (Malus domestica) is known to be rich in bioactive compounds, but its potential to protect skin cells from UV damage still needs to be further investigated. This study aims to evaluate the protective effect of apple extract on UV-exposed fibroblast cells. The apple ethanol extract was prepared using the maceration method. Fibroblast cells were cultured and treated with various extract concentrations (3.13, 6.25, 12.50 µg//mL) before UV exposure. Parameters analyzed included CASP8 gene expression using qRT-PCR, T-AOC, and GSH levels, using colorimetry methods. Apple extract showed a significant protective effect at a 12.5 µg/mL concentration, characterized by decreasing CASP8 expression as a marker of apoptosis. There was an increase in T-AOC and GSH levels. Apple ethanol extract shows significant potential as an anti-aging ingredient through its protective effect on UV-exposed fibroblast cells.
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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".