Activation of PI3K–Akt through taurine is critical for propofol to protect rat cardiomyocytes from doxorubicin-induced toxicity
Bibliographic record
Abstract
Myocardial toxicity is one of the major side effects of many chemotherapeutics. It has been shown that propofol can ameliorate the cardiotoxicity of chemotherapeutic agents. In this study, we intend to investigate the role of the PI3K-Akt-Bad signaling pathway in propofol relief of doxorubicin-induced oxidative stress and apoptosis in rat cardiomyocytes. Cultured neonatal rat cardiomyocytes were treated with vehicle, doxorubicin, propofol, or propofol plus doxorubicin in the presence or absence of the PI3K inhibitor LY294002. Cells were harvested 20 h post-exposure to doxorubicin followed by analysis of their cellular taurine content, oxidative/nitrative stresses, and cellular apoptosis. The activation of the PI3K-Akt pathway was analyzed by immunoblotting. FACS, TUNEL, and LDH assays showed that the viability of cardiomyocytes was markedly reduced by doxorubicin, but was improved by propofol. Doxorubicin treatment significantly elevated cellular reactive oxygen and nitrogen contents while lowering the levels of taurine, Akt, and phosphorylated Akt and Bad. The abovementioned doxorubicin-induced changes were reversed by propofol. The protective effects of propofol were abrogated by simultaneous treatment with LY294002. In conclusion, the PI3K-Akt-Bad pathway plays a critical role in conferring the protective effects of propofol against myocardial toxicity from doxorubicin.
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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 | 0.001 |
| 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".