Changes in tearing pressure with the geometry of dissections in porcine aortas
Bibliographic record
Abstract
Dissecting aneurysms, or dissections, occur in large arteries by creating a false lumen in the media which is parallel to the true lumen. A tensile force is needed to tear the arterial wall in dissections. This tensile force could be produced in response to the pressure in the false lumen. In this study, tearing pressure was investigated. The studies were done in vitro on fresh isolated porcine thoracic aortas which were pressurized to 130 mmHg (physiological mean pressure). A volume of diluted India ink was injected into the media of the aortic wall to create a cavity called a "bleb". As the size of the bleb increased, the media was dissected. The difference between the pressure inside the bleb and that in the lumen was measured, and defined as tearing pressure. Ten pig thoracic aortas were studied. The results showed that tearing pressure decreased with the volume of blebs at the beginning when the blebs were first formed, and then reached a constant pressure after the shape of blebs did not change. The minimum tearing pressure required for the propagation of dissections is called propagation pressure which is 52/spl plusmn/10(SD) mmHg (n=10) in the range of physiological pressure, indicating that the propagation of dissection might be possible in vivo under physiological conditions. Based on the assumptions that each aortic wall has a constant Young's modulus at large strains and a maximum strain, and shear stress is not an important fact involved in dissections, a mathematical model is established for dissections of the aortic wall. The tearing pressure was inversely proportional to both the radii of blebs and the tangents of the angles at the leading edge of dissections before the blebs had a fixed shape, and then kept as a constant when the shape of blebs did not change. The model explained the change of tearing pressure with the geometry of blebs, and predicted tearing pressure would be lower in old human aortas than in young ones.
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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 | 0.001 |
| 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 | 0.001 |
| 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".