Maslinic acid activates mitochondria-dependent apoptotic pathway in cardiac carcinoma
Bibliographic record
Abstract
PURPOSE: Cardiac carcinoma is the most common subtype of gastric cancer and its incidence has increased in recent years. The current chemotherapeutic drugs exhibit limited effectiveness and significant side effects in patients. Maslinic acid (MA) exerts an anti-tumor activity on a wide range of cancers and has no significant side effect; however, the anti-tumor effect of MA on cardiac carcinoma has not yet been explored. METHODS: MTT assays, tumor xenograft animal model, immunoblotting, MMP assessment and flow cytometry were performed in this study. RESULTS: MA was able to suppress the viability of cardiac carcinoma cells in both a time- and dose-dependent manner. This natural compound exhibited no cytotoxicity in normal cells. Its inhibitory effect on tumor growth was further confirmed in a mouse model. Mechanistically, MA induced the activation of p38 MAPK in cardiac carcinoma cells and, in turn, changed their mitochondrial membrane potential (MMP). Finally, caspase cascades were activated by a series of cleavages, leading to apoptosis in cardiac cancer cells. Inhibition of p38 MAPK signaling was able to rescue the effect of MA on cardiac carcinoma cells. CONCLUSION: Our data demonstrated that natural compound, MA, suppressed the growth of cardiac carcinoma by inducing apoptosis via the p38 MAPK/mitochondria/caspase pathway. MA and its derivatives may be promising anti-tumor agents for cardiac carcinoma treatment in the future. (Supplemental Figures available here.).
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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".