Guidelines for in vivo mouse models of myocardial infarction
Bibliographic record
Abstract
Despite significant improvements in reperfusion strategies, acute coronary syndromes all too often culminate in a myocardial infarction (MI). The consequent MI can, in turn, lead to remodeling of the left ventricle (LV), the development of LV dysfunction, and ultimately progression to heart failure (HF). Accordingly, an improved understanding of the underlying mechanisms of MI remodeling and progression to HF is necessary. One common approach to examine MI pathology is with murine models that recapitulate components of the clinical context of acute coronary syndrome and subsequent MI. We evaluated the different approaches used to produce MI in mouse models and identified opportunities to consolidate methods, recognizing that reperfused and nonreperfused MI yield different responses. The overall goal in compiling this consensus statement is to unify best practices regarding mouse MI models to improve interpretation and allow comparative examination across studies and laboratories. These guidelines will help to establish rigor and reproducibility and provide increased potential for clinical translation.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.013 |
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".