A parameterized analysis of the mechanical stress for co-ronary plaque fibrous caps
Bibliographic record
Abstract
The fibrous cap is a protective layer of connective tissue that covers the core of an atherosclerotic plaque. The rupture of this layer has been commonly associated with acute myocardial infarctions. The thickness of the fibrous cap, the percentage of stenosed area, and the stiffness of the core were studied (commonly associated with vulnerable plaque characteristics) to quantify their effects on the cap’s mechanical stress state by performing analyses using computational fluid-structure interaction (FSI) methods. The mechanical stress levels are significantly increased within the fibrous cap structure at the upstream side of the plaque. As expected, the highest stresses occurred for a severe stenosis and a thin fibrous cap. Interestingly, a weak structural support such as a soft lipid pool beneath the fibrous cap allowed for the hemodynamic pressure gradient forces to displace the fibrous cap in the direction of the flow, resulting in higher strains and thus higher mechanical stresses in the upstream portion of the plaque cap, potentially increasing the risk of cap rupture. The peak stress behavior of the most critical cases (thin fibrous cap and soft lipid core) at various degrees of stenosis was analyzed. For mid-range stenosis from 43% to 75%, there was a plateau region revealing that mild and moderate plaques were quickly exposed to the high stress condition of severe plaques. In conclusion, the particular combination of a mild to severe stenosis, a thin fibrous cap and a soft lipid core resulted in the highest mechanical stresses calculated at the proximal side of the plaque. Mild and moderate plaques can be subjected to stresses similar to severe plaques, possibly contributing to their rupture.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".