10-Gingerol Inhibits Ovarian Cancer Cell Growth by Inducing G2Arrest
Bibliographic record
Abstract
Purpose: Gingerol homologs found in the rhizomes of ginger plants have the potential to benefithuman health, including the prevention and treatment of cancer. This study evaluated the effectof 10-gingerol on ovarian cancer cell (HEY, OVCAR3, and SKOV-3) growth.Methods: Cell growth was measured by MTT assays, flow cytometry was used to assess cellproliferation, cytotoxicity and cell cycle progression, and western blotting was used to measurecyclin protein expression.Results: Ovarian cancer cells that were treated with 10-gingerol experienced a time- anddose-dependent decrease in cell number, which was due to a reduction in cell proliferationrather than a cytotoxic effect. Reduced proliferation of 10-gingerol-treated ovarian cancercells was associated with an increased percentage of cells in G2 phase of the cell cycle anda corresponding reduction in the percentage of cells in G1. Ovarian cancer cells also showeddecreased cyclin A, B1, and D3 expression following exposure to 10-gingerol.Conclusion: These findings revealed that 10-gingerol caused a G2 arrest-associated suppressionof ovarian cancer cell growth, which may be exploited in the management of ovarian cancer.
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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".