Rosemary Extract Inhibits Proliferation, Survival, Akt, and mTOR Signaling in Triple-Negative Breast Cancer Cells
Bibliographic record
Abstract
Breast cancer is the most commonly diagnosed cancer in women. Triple-negative (TN) breast cancer lacks expression of estrogen receptor (ER), progesterone receptor (PR) as well as the expression and/or gene amplification of human epidermal growth factor receptor 2 (HER2). TN breast cancer is aggressive and does not respond to hormone therapy, therefore new treatments are urgently needed. Plant-derived chemicals have contributed to the establishment of chemotherapy agents. In previous studies, rosemary extract (RE) has been found to reduce cell proliferation and increase apoptosis in some cancer cell lines. However, there are very few studies examining the effects of RE in TN breast cancer. In the present study, we examined the effects of RE on TN MDA-MB-231 breast cancer cell proliferation, survival/apoptosis, Akt, and mTOR signaling. RE inhibited MDA-MB-231 cell proliferation and survival in a dose-dependent manner. Furthermore, RE inhibited the phosphorylation/activation of Akt and mTOR and enhanced the cleavage of PARP, a marker of apoptosis. Our findings indicate that RE has potent anticancer properties against TN breast cancer and modulates key signaling molecules involved in cell proliferation and survival.
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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 | 0.001 |
| 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".