Amygdalin and exercise training exert a synergistic effect in improving cardiac performance and ameliorating cardiac inflammation and fibrosis in a rat model of myocardial infarction
Bibliographic record
Abstract
plants) on cardiac performance and ventricular remodeling in a rat model of myocardial infarction (MI). We also investigated whether the combination of AMY with exercise training (ExT) has a beneficial synergistic effect in treating MI rats. MI was induced by the ligation of the left anterior descending coronary artery in male SD rats. ExT or AMY treatment was started 1 week after MI and continued for 1 week (short-term) or 8 weeks (long-term). Cardiac function was evaluated by echocardiographic and hemodynamic parameters. Heart tissues were harvested and subjected to 2,3,5-triphenyl-tetrazolium chloride, Masson's trichrome, hematoxylin-eosin, and immunohistochemical staining. Gene expression was determined by quantitative polymerase chain reaction. Western blot gave a qualitative assessment of protein levels. AMY or ExT improved cardiac function and reduced infarct size in MI rats. AMY or ExT also suppressed myocardial fibrosis and attenuated inflammation in the infarct border zone of hearts from MI rats, as evidenced by inhibition of collagen deposition, inflammatory cell infiltration, and pro-inflammatory markers (interleukin 1β, interleukin 6, tumor necrosis factor-α, and cyclooxygenase 2). Notably, the effects of AMY combined with ExT were superior to those of AMY alone or ExT alone. Mechanistically, these beneficial functions were correlated with the inhibition of MI-induced activation of the transforming growth factor-β/Smad pathway. Collectively, AMY and ExT exert a synergistic effect on improving cardiac performance and ameliorating cardiac inflammation and fibrosis after MI, and the effects of long-term intervention were better than short-term intervention.
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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) | 0.001 | 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".