Modelling of hemodynamic stress effects on rupture mechanics and fibrous cap collagen architecture of atherosclerotic plaques
Bibliographic record
Abstract
Cardiovascular plaque rupture in atherosclerosis has been associated extensively with Acute Myocardial Infarctions, a leading cause of death. The mechanics and progression of plaque rupture are not yet fully understood. A protective fibrous cap made of collagen fibers and smooth muscle cells covers the plaque's necrotic core. These fibers provide strength and elasticity to the cap tissue as they realign over time to the prevalent tensile stress orientations as an efficient method to optimize strength without increasing weight and metabolic costs [1].Fluid structure interaction simulations of normal hemodynamic conditions in a stenosed artery were performed to evaluate stress distribution and orientation within the plaque's main constituents, and to predict the cap's collagen fiber architecture and subsequently its vulnerability.The results show that the principal stress orientations gradually shift from circumferential at the nonstenosed sections of the artery to longitudinal at the peak of the stenosis. This gradual shift can be seen in the collagen architecture of actual histopathological studies of diseased vessels.The higher magnitude stress zones also indicate where plaque disruption may initiate and how fissure propagation can occur. Based on these results we could hypothesize that the rupture mechanics can be treated as a biocomposite matrix failure as fissuring seems to run parallel to the collagen fibers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".