Inhibition of Prostate Cancer Cell Survival and Proliferation by Carnosic Acid Is Associated with Inhibition of Akt and Activation of AMPK Signaling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Prostate cancer, accounting for 375,304 deaths in 2020, is the second most prevalent cancer in men worldwide. While many treatments exist for prostate cancer, novel therapeutic agents with higher efficacy are needed to target aggressive and hormone-resistant forms of prostate cancer, while sparing healthy cells. Plant-derived chemotherapy drugs such as docetaxel and paclitaxel have been established to treat cancers including prostate cancer. Carnosic acid (CA), a phenolic diterpene found in the herb rosemary (Rosmarinus officinalis) has been shown to have anticancer properties but its effects in prostate cancer and its mechanisms of action have not been examined. CA dose-dependently inhibited PC-3 and LNCaP prostate cancer cell survival and proliferation (IC50: 64, 21 µM, respectively). Furthermore, CA decreased phosphorylation/activation of Akt, mTOR, and p70 S6K. A notable increase in phosphorylation/activation of AMP-activated kinase (AMPK), acetyl-CoA carboxylase (ACC) and its upstream regulator sestrin-2 was seen with CA treatment. Our data indicate that CA inhibits AKT-mTORC1-p70S6K and activates Sestrin-2-AMPK signaling leading to a decrease in survival and proliferation. The use of inhibitors and small RNA interference (siRNA) approaches should be employed, in future studies, to elucidate the mechanisms involved in carnosic acid’s inhibitory effects of prostate cancer.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it