Cardiac Overexpression of S100A6 Attenuates Cardiomyocyte Apoptosis and Reduces Infarct Size After Myocardial Ischemia‐Reperfusion
Bibliographic record
Abstract
BACKGROUND: Cardiomyocyte-specific transgenic mice overexpressing S100A6, a member of the family of EF-hand calcium-binding proteins, develop less cardiac hypertrophy, interstitial fibrosis, and myocyte apoptosis after permanent coronary ligation, findings that support S100A6 as a potential therapeutic target after acute myocardial infarction. Our purpose was to investigate S100A6 gene therapy for acute myocardial ischemia-reperfusion. METHODS AND RESULTS: We first performed in vitro studies to examine the effects of S100A6 overexpression and knockdown in rat neonatal cardiomyocytes. S100A6 overexpression improved calcium transients and protected against apoptosis induced by hypoxia-reoxygenation via enhanced calcineurin activity, whereas knockdown of S100A6 had detrimental effects. For in vivo studies, human S100A6 plasmid or empty plasmid was delivered to the left ventricular myocardium by ultrasound-targeted microbubble destruction in Fischer-344 rats 2 days prior to a 30-minute ligation of the left anterior descending coronary artery followed by reperfusion. Control animals received no therapy. Pretreatment with S100A6 gene therapy yielded a survival advantage compared to empty-plasmid and nontreated controls. S100A6-pretreated animals had reduced infarct size and improved left ventricular systolic function, with less myocyte apoptosis, attenuated cardiac hypertrophy, and less cardiac fibrosis. CONCLUSIONS: S100A6 overexpression by ultrasound-targeted microbubble destruction helps ameliorate myocardial ischemia-reperfusion, resulting in lower mortality and improved left ventricular systolic function post-ischemia-reperfusion via attenuation of apoptosis, reduction in cardiac hypertrophy, and reduced infarct size. Our results indicate that S100A6 is a potential therapeutic target for acute 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) | 0.001 | 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".