Cardiovascular Patterning as Determined by Hemodynamic Forces and Blood Vessel Genetics
Bibliographic record
Abstract
BACKGROUND: Vascular patterning depends on coordinated timing of arteriovenous specification of endothelial cells and the concomitant hemodynamic forces supplied by the onset of cardiac function. Using a combination of 3D imaging by OPT and embryo registration techniques, we sought to identify structural differences between three different mouse models of cardiovascular perturbation. RESULTS: Endoglin mutant mice shared a high degree of similarity to Mlc2a mutant mice, which have been shown to have a primary developmental heart defect causing secondary vessel remodeling failures. Dll4 mutant mice, which have well-characterized arterial blood vessel specification defects, showed distinct differences in vascular patterning when compared to the disruptions seen in Mlc2a-/- and Eng-/- models. While Mlc2a-/- and Eng-/- embryos exhibited significantly larger atria than wild-type, Dll4-/- embryos had significantly smaller hearts than wild-type, but this quantitative volume decrease was not limited to the developing atrium. Dll4-/- embryos also had atretic dorsal aortae and smaller trunks, suggesting that the cardiac abnormalities were secondary to primary arterial blood vessel specification defects. CONCLUSIONS: The similarities in Eng-/- and Mlc2a-/- embryos suggest that Eng-/- mice may suffer from a primary heart developmental defect and secondary defects in vessel patterning, while defects in Dll4-/- embryos are consistent with primary defects in vessel patterning.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".