Beneficial role of tamoxifen in isoproterenol-induced myocardial infarction
Bibliographic record
Abstract
ER-α and ER-β agonist 17β-estradiol is reported to attenuate cardiac hypertrophy. Tamoxifen is a selective estrogen receptor modulator. Hence, the objective of this study was to investigate the effects of tamoxifen in myocardial infarction. For this, tamoxifen was administered to Sprague-Dawley rats for 1-14 days, and isoproterenol (ISO) (100 mg·(kg body mass)(-1)·day(-1)) was administered subcutaneously on the 13th and 14th days of the study in order to induce myocardial infarction, after which, various biochemical, cardiac, and morphometric parameters were evaluated. ISO produced significant dyslipidemia, hypertension, bradycardia, oxidative stress, and an increase in serum cardiac markers. Treatment with tamoxifen significantly controlled dyslipidemia, hypertension, bradycardia, oxidative stress, and reduced serum cardiac markers. The ISO control rats exhibited significant increases in the infarct size of the left ventricle (LV), LV cavity area, cardiac and LV hypertrophic indices, LV-wall thickness, cardiomyocyte diameter, and area. Treatment with tamoxifen significantly reduced infarction as well as hypertrophic and morphometric parameters. ISO also produced significant increases in the LV collagen level, decreases in Na(+)K(+) ATPase activity, and a reduction in the rate of pressure development and decay, which were prevented by tamoxifen treatment. The protective effect of tamoxifen on myocardial infarct was further confirmed by histopathological examination. Our data thus suggest that tamoxifen exerts beneficial effects in ISO-induced myocardial infarction.
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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 | 0.000 |
| 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".