Inhibition of Non-Small Cell Lung Cancer Proliferation and Survival by Rosemary Extract Is Associated with Activation of ERK and AMPK
Bibliographic record
Abstract
Non-small cell lung cancer (NSCLC) represents an aggressive form of lung cancer which often develops resistance to chemo- and radiotherapy emphasizing a need to identify novel treatment agents to combat it. Many plants contain compounds with anti-inflammatory, antimicrobial, antidiabetic, and anticancer properties and some plant-derived chemicals are used in the treatment of cancer. A limited number of in vitro and in vivo animal studies provide evidence of anticancer effects of rosemary (Rosmarinus officinalis) extract (RE); however, no studies have explored its role in H1299 NSCLC cells, and its underlying mechanism(s) of action are not understood. The current study examined the effects of RE on H1299 cell proliferation, survival, and migration using specific assays. Additionally, immunoblotting was used to investigate the effects of RE treatment on signalling molecules implicated in cell growth and survival. Treatment with RE dose-dependently inhibited H1299 proliferation with an IC50 value of 19 µg/mL. Similarly, RE dose-dependently reduced cell survival, and this reduction correlated with increased levels of cleaved poly (ADP-ribose) polymerase (PARP), a marker of apoptosis. RE was also able to inhibit cell migration as assessed with a wound healing assay. These cellular effects of RE were associated with an increase in phosphorylated levels of extracellular signal-regulated kinase (ERK), AMP-activated protein kinase (AMPK), and its downstream targets ACC, the mTORC1 protein raptor, and decreased p70S6K phosphorylation. More studies are required to fully examine the effects of RE against NSCLC.
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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 | 0.001 |
| 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".