The pro-apoptotic effect of chronic contractile activity-induced extracellular vesicles on Lewis Lung Carcinoma cells
Bibliographic record
Abstract
Abstract Regular exercise reduces tumor growth in vivo and in vitro , but the exact mechanisms have yet to be fully elucidated. We have previously shown that chronic contractile activity (CCA) increases the concentration of skeletal muscle-derived EVs, and these in turn increased mitochondrial biogenesis in myoblasts. Here, we hypothesized that skeletal muscle-EVs derived post-CCA will mediate the anti-tumorigenic effects associated with chronic exercise. C2C12 myoblasts were differentiated into myotubes, electrically paced, and EVs isolated from conditioned media from control and CCA myotubes using differential ultracentrifugation. Lewis lung carcinoma (LLC) cells were treated with the total number of control-EVs or CCA-EVs isolated after each day of contractile activity for 4 days. Permeabilized CCA-EVs with or without proteinase K before co-culture with LLC cells were used as controls. Effect of EV treatment on cell count, viability, apoptosis, senescence, migration, and mitochondrial content was measured. CCA-EV treatment reduced cell count by 18% and cell viability by 6% vs. control-EVs. CCA-EVs increased the incidence of apoptotic hallmarks: DNA fragmentation by 13%, Annexin V+/PI+ cells by 21%, and the expression of pro-apoptotic Bax (by 25%) and Bax/Bcl-2 ratio (by 60%) vs. control-EVs. CCA-EVs increased number of senescent cells by 29%, and senescence markers, HMGB1 (by 49%) and p16 (by 92%) vs. control-EVs. When CCA-EVs were pretreated with Triton X-100 with or without proteinase-K, the increase in apoptosis and senescence was abrogated, confirming the effect is due to intact EVs and likely through EV membrane-proteins. CCA-EVs did not have any effect on cell migration and mitochondrial content vs. control-EVs. This study illustrates for the first time the potential of CCA-induced skeletal muscle-EVs in mediating anti-tumorigenic effects traditionally linked with chronic exercise.
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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".