Myocardial Infarction in Neonatal Mice, A Model of Cardiac Regeneration
Bibliographic record
Abstract
Myocardial infarction induced by coronary artery ligation has been used in many animal models as a tool to study the mechanisms of cardiac repair and regeneration, and to define new targets for therapeutics. For decades, models of complete heart regeneration existed in amphibians and fish, but a mammalian counterpart was not available. The recent discovery of a postnatal window during which mice possess regenerative capabilities has led to the establishment of a mammalian model of cardiac regeneration. A surgical model of mammalian cardiac regeneration in the neonatal mouse is presented herein. Briefly, postnatal day 1 (P1) mice are anesthetized by isoflurane and placed on an ice pad to induce hypothermia. After the chest is opened, and the left anterior descending coronary artery (LAD) is visualized, a suture is placed around the LAD to inflict myocardial ischemia in the left ventricle. The surgical procedure takes 10-15 min. Visualizing the coronary artery is crucial for accurate suture placement and reproducibility. Myocardial infarction and cardiac dysfunction are confirmed by triphenyl-tetrazolium chloride (TTC) staining and echocardiography, respectively. Complete regeneration 21 days post myocardial infarction is verified by histology. This protocol can be used to as a tool to elucidate mechanisms of mammalian cardiac regeneration after 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".