Comprehensive Echocardiographic Assessment of the Right Ventricle in Murine Models
Bibliographic record
Abstract
BACKGROUND: Non-invasive high-resolution echocardiography to evaluate cardiovascular function of small animals is increasingly being used due to availability of genetically engineered murine models. Even though guidelines and standard values for humans were revised by the American Society of Echocardiography, evaluations on murine models are not performed according to any standard protocols. These limitations are preventing translation of preclinical evaluations to clinical meaningful conclusions. We have assessed the right heart of two commonly used murine models according to standard clinical guidelines, and provided the practical guide and sample values for cardiac assessments. METHODS: Right heart echocardiography evaluations of CD1 and C57BL/6 mice were performed under 1-3% isoflurane anesthesia using Vevo® 2100 Imaging System with a high-frequency (18-38 MHz) probe (VisualSonics MS400). We have provided a practical guide on how to image and assess the right heart of a mouse which is frequently used to evaluate development of right heart failure due to pulmonary hypertension. RESULTS: < 0.05) size, and pulmonary artery diameter in CD1 mice (n = 11) compared to C57BL/6 mice (n = 15). Right heart systolic and diastolic functions were similar for both strains. CONCLUSION: Our practical guide on how to image and assess the right heart of murine models provides the first comprehensive values which can be used for preclinical research studies using echocardiography. Additionally, our results indicate that there is a high variability between mouse species and experimental models should be carefully selected for cardiac evaluations.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".