Murine echocardiography and ultrasound imaging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rodent models of cardiac pathophysiology represent a valuable research tool to investigate mechanism of disease as well as test new therapeutics. Echocardiography provides a powerful, non-invasive tool to serially assess cardiac morphometry and function in a living animal. However, using this technique on mice poses unique challenges owing to the small size and rapid heart rate of these animals. Until recently, few ultrasound systems were capable of performing quality echocardiography on mice, and those generally lacked the image resolution and frame rate necessary to obtain truly quantitative measurements. Newly released systems such as the VisualSonics Vevo2100 provide new tools for researchers to carefully and non-invasively investigate cardiac function in mice. This system generates high resolution images and provides analysis capabilities similar to those used with human patients. Although color Doppler has been available for over 30 years in humans, this valuable technology has only recently been possible in rodent ultrasound. Color Doppler has broad applications for echocardiography, including the ability to quickly assess flow directionality in vessels and through valves, and to rapidly identify valve regurgitation. Strain analysis is a critical advance that is utilized to quantitatively measure regional myocardial function. This technique has the potential to detect changes in pathology, or resolution of pathology, earlier than conventional techniques. Coupled with the addition of three-dimensional image reconstruction, volumetric assessment of whole-organs is possible, including visualization and assessment of cardiac and vascular structures. Murine-compatible contrast imaging can also allow for volumetric measurements and tissue perfusion assessment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it