A finite difference model of O<sub>2</sub> transport in aortic valve cusps: importance of intrinsic microcirculation
Bibliographic record
Abstract
Recent studies have reported the presence of a microcirculation within the tissue of aortic valves. To test the hypothesis that this vascular bed is needed to satisfy the oxygen demands of the cusp tissue, a two-dimensional (2D) finite difference model of oxygen diffusion was developed. The in vivo environment was modeled for vascular and avascular cusps using thickness data from precise radiographic measurements of fresh porcine valves, and O2 diffusivity (DO2) and O2 consumption (VO2) values from experimental data. The location and density of the cusp vasculature were determined by the model to prevent oxygen levels from falling to zero. Validation of the model was performed by simulation of the experimental measurements of cusp DO2 and VO2. For a test cusp with uniform thickness, the model returned simulated DO2 and VO2 measurements within 1.43% and 0.18% difference of the true parameter values, respectively. For native cusps, the simulated DO2 measurements were sensitive to thickness variations (-38 to +21% difference), whereas the VO2 measurements were minimally affected (8% difference). An improved DO2 measurement technique was found to reduce these errors to <5% and is recommended for analysis of experimental data. In the avascular case, the model predicted large regions of hypoxic tissue, whereas in the vascular case, the model predicted vessel locations and densities similar to what was experimentally observed in porcine cusps. Overall, the in vivo model developed in this study confirmed the need for an intrinsic microcirculation in the thicker basal regions of aortic cusps.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".