Characterization of circulatory disorders in β-thalassemic mice by noninvasive ultrasound biomicroscopy
Bibliographic record
Abstract
Beta-thalassemia is an inherited hematological disease caused by a decrease or absence of production of beta-globin that requires chronic therapeutic interventions. This condition leads to important arterial and venous thromboembolic events, transitory ischemic attacks, and microcirculatory obstructions, indicative of circulatory disturbances. To investigate the presence of microcirculatory disorders without the confounding effect of treatments, we used beta-thalassemic mice with typical clinical characteristics of human beta-thalassemia major. One impediment to the understanding of microcirculatory physiology, in particular for beta-thalassemic mice, has been the lack of an appropriate noninvasive imaging approach. We thus developed a novel noninvasive high-frequency ultrasound imaging method to evaluate murine vascular hemodynamic properties. In our beta-thalassemic mice, total peripheral vascular resistance was significantly increased (P < 0.01) compared with wildtype littermates, whereas mean blood pressure, heart rate, and cardiac output were similar (P = nonsignificant). Importantly, the vascular hemodynamics in beta-thalassemic mice were significantly affected according to the Pourcelot indexes measured in the common carotid artery and abdominal aorta (P < 0.01 and P < 0.05, respectively). Hence, our beta-thalassemia characterization of vascular hemodynamics by noninvasive ultrasonic approaches proves the existence and provides unique quantitative assessment of microcirculatory flow disturbances in those 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".