The Role of Oleuropein, Derived from Olives, in Human Skin Fibroblast Cells: Investigating the Underlying Molecular Mechanisms of Cytotoxicity and Antioxidant and Anti‐Inflammatory Activities
Bibliographic record
Abstract
Oleuropein is the main compound in olives, producing a relatively bitter taste for unprocessed and raw olives. It has been dramatically applied in herbal and traditional medicine and contains several biological functions, anti‐inflammatory effects, antimicrobial characteristics, and anticancer and antioxidant activities. The present study dealt with the cytotoxic effect, reactive oxygen species (ROS) suppressor, and wound‐healing activity of oleuropein on normal skin cells. Oleuropein’s cytotoxic and apoptotic effects were evaluated using MTT, flow cytometry, and DAPI staining. Moreover, oleuropein’s possible free radical scavenging properties were studied through several methods, including the 2, 2‐diphenyl‐1‐picrylhydrazyl (DPPH) and ABTS tests. The scratch assay was performed for wound‐healing features, and qRT‐PCR evaluated the expression of apoptosis‐associated genes. Oleuropein was found to have a cytotoxic effect on skin cells at higher exposure doses. Apoptosis was induced in the flow cytometry histogram of the cells treated with oleuropein. The results also revealed the strong anti‐inflammation and antioxidant effect of oleuropein. They suggested that more studies are necessary to assess the possible pharmacological use of oleuropein to prevent or decrease skin‐related diseases.
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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".