Inhibition of Human Lung Cancer Cell Proliferation and Survival by Post-Exercise Serum Is Associated with the Inhibition of Akt, mTOR, p70 S6K, and Erk1/2
Bibliographic record
Abstract
Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancer cases, and for the most cancer-related deaths. The survival pathway of Akt, its downstream effectors, the mammalian target of rapamycin (mTOR) and ribosomal protein S6 kinase (p70 S6K), and the Ras-extracellular signal-regulated kinase (Erk1/2) pathways are activated in cancer leading to cell survival and growth. Thus, approaches that inhibit these signaling molecules may prove useful in the fight against lung cancer. Exercise is associated with health benefits and a limited number of studies indicate that serum from physically active individuals inhibit mammary and prostate cancer cell growth. In this study, we examined the effects of post exercise serum on proliferation, survival, and signaling cascades of human NSCLC cells. Blood was collected from male subjects prior to, 5 min, 1 h, and 24 h after a single bout of high intensity interval exercise on a cycle ergometer. Exposure of NSCLC cells to post exercise serum resulted in the inhibition of cell proliferation and survival, as well as significant reduction of phosphorylated/activated Akt, mTOR, p70 S6K, and Erk1/2 levels compared to cells treated with serum taken pre-exercise. Our data suggest that post exercise serum has anti-cancer properties in lung cancer and deserves further systematic investigation in animal models.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".