The myokine decorin improves the cardiac function in a rat model of isoprenaline-induced myocardial infarction
Bibliographic record
Abstract
Myocardial infarction is a common cause of disability. Decorin is a myokine that has anti-inflammatory, anti-apoptotic effects. Some studies stated that decorin protects myocardium from ischemia. Other studies stated that decorin levels are associated with acute coronary syndrome. The study aimed to investigate the therapeutic role of decorin on cardiac function in a rat model of myocardial infarction. Thirty adult male Wistar rats were divided into control group—rats were subcutaneously injected with normal saline, isoprenaline-injected group—rats were subcutaneously injected with isoprenaline (85 mg/kg) once daily for 2 days to induce myocardial infarction, and decorin ± isoprenaline-injected group—rats were injected as the previous group, followed by decorin injection (0.1 mg/kg) once daily for 7 days. Cardiac hemodynamics, serum lactate dehydrogenase (LDH), creatine kinase–MB (CK–MB), oxidative stress markers, gene expression for myocardial-transforming growth factor beta 1 (TGF-β1), interleukin 1 b (IL-1β), tumor necrosis factor alpha (TNF-α), and cardiac caspase-3 immunohistochemical analysis were done. Isoprenaline + decorin group had significant improvement in cardiac hemodynamics and oxidative stress markers; significant decrease in serum CK–MB, LDH, and myocardial gene expression for TNF-α, IL-1β, and TGF-β1; and decreased cardiac caspase-3 immunoreactivity was present. Therefore, decorin can be used as a therapeutic agent after myocardial infarction as it improved the cardiac function.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".