Probing the possibility of lesion formation/progression in vicinity of a primary atherosclerotic plaque: A fluid–solid interaction study and angiographic evidences
Bibliographic record
Abstract
It is shown that certain locations in the arterial tree, such as coronary and cerebral arteries, are more prevalent to plaque formation. Endothelial activation and consequent plaque development are attributed to local hemodynamic parameters such as wall shear stress (WSS), oscillatory shear index (OSI), relative residence time (RRT), and stress phase angle. After a certain level of plaque progression, these hemodynamic parameters are disturbed before and after the plaque. In the current study, it is hypothesized that the vicinity of a primary lesion is susceptible for further degeneration and second plaque formation. A fluid-solid interaction (FSI) model of the coronary artery with different levels of asymmetric constriction, is simulated and the trend of hemodynamic parameters were studied in both of the plaque side (PS) and the opposite wall (facing the plaque [PF]). Also, a novel factor is introduced that can identify the high-risk regions associated with WSS oscillations to negative values. Our results indicate that when more than half of the artery is constricted, the downstream of the plaque is highly exposed to endothelial pathogenesis the PS, such that negative WSS, and as well, critical values of OSI and RRT, that is, -1.2 Pa, 0.42 and 6.5 s, respectively arise in this region. PS endothelial cells in this region exposed to the highest risk of atherosclerosis based on the proposed index (3 out of 3). As well, three cases of angiographic images are provided that confirms existence of secondary lesion close to the primary one as predicted by our computational simulations.
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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 | 0.001 | 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".