Using mathematical and computational modeling to study dynamic regulation of tissue oxygen delivery
Bibliographic record
Abstract
To investigate how regulation of the convective O 2 supply is related to actual tissue oxygenation, a multi‐pronged approach is being used that involves in vivo microvascular experiments, simplified one‐dimensional (1D) mathematical models, and full 3D numerical simulations. Experimental data is obtained using a gas exchange chamber in the stage of an inverted microscope to alter the O 2 environment at the surface of a rat skeletal muscle. The microvascular response to sine oscillations in chamber O 2 (60 and 120 second periods) is determined by measuring capillary hemodynamics (RBC velocity and hematocrit) and RBC O 2 saturation levels with a functional microvascular imaging system. Oscillations in chamber O 2 can cause oscillations in capillary hemodynamics, or there may be no clear hemodynamic response (‘non‐responders’). For non‐responders, 1D and 3D modeling of the experimental situation have shown that O 2 consumption and capillary‐tissue transport alter tissue O 2 dynamics relative to the classic pure‐diffusion case. This result agrees with available data and has implications for the possible role of O 2 dynamics in flow regulation. Work is now focusing on incorporating observed hemodynamic responses into the O 2 transport models to determine how microvessels of different types (e.g., capillaries vs. arterioles) are involved in flow regulation and what the net result is in terms of tissue oxygenation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".