Longitudinal Follow-up of Cardiac Structure and Functional Changes in an Infarct Mouse Model Using Retrospectively Gated Micro-Computed Tomography
Bibliographic record
Abstract
OBJECTIVES: Mouse models of myocardial infarction are valuable in studying the effect of genetic modifications on structural and functional remodeling of the heart. Our group recently developed a method for acquiring three-dimensional images of the beating mouse heart using micro-computed tomography (micro-CT) and retrospective gating. In this study, we evaluated cardiac function in sham and infarcted mice longitudinally, using this novel technique. MATERIALS AND METHODS: Thirteen mice (7 sham-operated, 6 infarcted; male, C57BL/6) were imaged at baseline and at weeks 1, 2, 3, and 4 postligation of the left anterior descending coronary artery. Animals were anesthetized with 1.5% isoflurane; mechanical ventilation was not used. Contrast between blood and tissue was provided by an iodinated blood-pool contrast agent (0.01 mL/g Fenestra VC). The cardiac and respiratory waveforms were recorded during the 50-second scan time, to enable retrospective gating. Once scanning was completed on week 4 postsurgery, hemodynamic measurements were performed using a Millar pressure conductance catheter. RESULTS: There were significant differences in systolic and diastolic volumes, and ejection fraction, between sham and myocardial infarction groups (P < 0.0001). A comparison of ejection fraction derived from both CT and hemodynamic measurements was not significantly different (P > 0.1). CONCLUSIONS: We have demonstrated the first use of dynamic micro-CT for monitoring cardiac remodeling, resulting from myocardial infarction, over time. The fast scan times (<1 minute) and ability to track individual animals over an entire study make this quantitative noninvasive technique a promising tool for in vivo studies of cardiac disease in mouse models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".