Quantitative Assessment of Regional Myocardial Function in Mice by Tissue Doppler Imaging
Bibliographic record
Abstract
BACKGROUND: Tissue Doppler imaging (TDI) is a novel echocardiographic method to quantify regional myocardial function. The objective of this study was to assess whether myocardial velocities and strain rate (SR) could be obtained by TDI in mice and whether these indices accurately quantified alterations in left ventricular (LV) systolic function. METHODS AND RESULTS: TDI was performed in 10 healthy mice to measure endocardial (v(endo)) and epicardial systolic velocities and SR. In further experiments, TDI indices were compared with dP/dt(max) and with sonomicrometer-derived regional velocities, at rest and after administration of dobutamine or esmolol. TDI indices were also studied serially in 8 mice before and 4 and 7 hours after endotoxin challenge. Myocardial velocities and SR were obtained in all mice with low measurement variability. TDI indices increased with administration of dobutamine (v(endo) from 2.2+/-0.3 to 3.8+/-0.2 cm/s [P<0.01]; SR from 12+/-2 to 20+/-2 s(-1) [P<0.05]) and decreased with administration of esmolol (v(endo) 1.4+/-0.2 cm/s [P<0.05]; SR 6+/-1 s(-1) [P<0.01]). Both indices correlated strongly with dP/dt(max) (r2=0.79 for SR and r2= 0.69 for v(endo); both P<0.0001). SR and shortening fraction were predictors of dP/dt(max) even after adjustment for the confounding effect of the other variables. V(endo) correlated closely with sonomicrometer-measured velocity (r2=0.71, P<0.0005). After endotoxin challenge, decreases in both v(endo) and SR were detected before decreases in shortening fraction became manifest. CONCLUSIONS: Myocardial velocities and SR can be measured noninvasively in mice with the use of TDI. Both indices are sensitive markers for quantifying LV global and regional function in mice.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".