MODELING COUPLED DIAMETER AND HEMODYNAMIC OSCILLATIONS IN ARTERIOLAR NETWORKS
Bibliographic record
Abstract
Regulation of convective O 2 supply to capillary beds in organs is accomplished by coordinated changes in upstream arteriolar diameter. To study this regulation system, in vivo experiments have been performed using a gas exchange chamber to sinusoidally oscillate the O 2 environment at the surface of a rat skeletal muscle. Capillary hematocrit (H) changes were delayed by several seconds relative to changes in red cell velocity (V) and the delay varied with the animal suggesting geometry dependence. To assess how alterations in diameters led to observed hemodynamics, a computational model was developed that couples variations in network blood flow to conducted diameter changes. The model uses an arteriolar tree that was constructed based on measured data in rat skeletal muscle and a two‐phase (red cells and plasma) time‐dependent model of microvascular blood flow. The initial response to imposed surface O 2 oscillations was simulated by applying diameter oscillations at the distal ends of selected terminal arterioles. The model was used to calculate hemodynamic oscillations in the network and, in particular, examine how the transit time for red cells in the network could lead to the observed delay in changes in H relative to those in V. Initial results show similarities to experimental observations, including decreases in hemodynamic response amplitude with increases in forcing frequency and a delay in H relative to V.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".