Wall shear stress and atherosclerosis: numerical blood flow simulations in the mouse aortic arch
Bibliographic record
Abstract
The aims of this study were (1) to demonstrate the feasibility of computational fluid dynamic (CFD) modelling of realistic blood flow in the mouse aortic arch, and (2) to determine the relation of wall shear stress and atherosclerosis in the mouse aortic arch. ApoE knockout mice were chosen for this study. The blood flow fraction in the major branches of the mouse aortic arch was measured by ultrasound biomicroscopy. The geometry of the aortic arch was captured by plastic casting and micro CT imaging. Mouse blood viscosities were measured by rheometry. A pathological examination was performed. A well-validated in-house finite element code, which solves the three dimensional Navier-Stokes equations, was used to compute the wall shear stress and velocity patterns in the ascending aorta and the aortic arch. The distribution of the wall shear stress was correlated with the distribution of the atherosclerosis from the pathological examination in order to investigate the effect of wall shear stress on atherosclerosis. It is concluded that CFD modeling of hemodynamics in the mouse aortic arch is feasible. Qualitative impressions show that atherosclerosis was related with the region of low wall shear stress in mouse aortic arch.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".