Unlocking the Anti-Aging Potential of Apple (Malus domestica) Extract: In Vitro Modulation of TIMP-1, Casp-3, and GPX Gene Expression in Fibroblast Cells
Bibliographic record
Abstract
Ultraviolet (UV) exposure accelerates skin aging by inducing oxidative stress, apoptosis, and extracellular matrix degradation. Malus domestica (apple) extract (AE) is rich in antioxidants and bioactive compounds that may counteract these effects. This study evaluates the protective effects of AE on fibroblast cells exposed to UV radiation by assessing the expression of Tissue Inhibitor of Metalloproteinase 1 (TIMP-1), Caspase 3 (Casp-3), and Glutathione Peroxidase (GPX). Fibroblast cells were exposed to UV radiation and treated with different concentrations of AE (3.13, 6.25, 12.5 µg/mL). Gene expression levels of TIMP-1, Casp-3, and GPX were analyzed using qRT-PCR. AE significantly increased TIMP-1 and GPX expression while downregulating Casp-3 in a concentration-dependent manner. The highest concentration (12.5 µg/mL) demonstrated the most pronounced protective effects. These results suggest that apple extract enhances extracellular matrix stability, reduces oxidative stress, and inhibits apoptosis in UV-exposed fibroblasts. AE exhibits potent anti-aging properties by modulating key molecular pathways involved in skin damage. This study provides scientific evidence supporting its potential as an active ingredient in skincare formulations for UV protection and skin rejuvenation. HIGHLIGHTS Apple extract significantly upregulated TIMP-1 and GPX expression while downregulating Casp-3, indicating enhanced extracellular matrix stability and reduced apoptosis. The findings suggest that apple extract mitigates oxidative stress and inhibits apoptosis, which are key contributors to skin aging. A dose-dependent effect was observed, with the highest concentration (12.5 µg/mL) demonstrating the most significant anti-aging impact. GRAPHICAL ABSTRACT
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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".