Impact of Incremental Perfusion Loss on Oxygen Transport in a Capillary Network Mathematical Model
Bibliographic record
Abstract
OBJECTIVES: To quantify how incremental capillary PL, such as that seen in experimental models of sepsis, affects tissue oxygenation using a computation model of oxygen transport. METHODS: A computational model was applied to capillary networks with dimensions 84 × 168 × 342 (NI) and 70 × 157 × 268 (NII) μm, reconstructed in vivo from rat skeletal muscle. FCD loss was applied incrementally up to ~40% and combined with high tissue oxygen consumption to simulate severe sepsis. RESULTS: A loss of ~40% FCD loss decreased median tissue PO2 to 22.9 and 20.1 mmHg in NI and NII compared to 28.1 and 27.5 mmHg under resting conditions. Increasing RBC SR to baseline levels returned tissue PO2 to within 5% of baseline. HC combined with a 40% FCD loss, resulted in tissue anoxia in both network volumes and median tissue PO2 of 11.5 and 8.9 mmHg in NI and NII respectively; median tissue PO2 was recovered to baseline levels by increasing total SR 3-4 fold. CONCLUSIONS: These results suggest a substantial increase in total SR is required in order to compensate for impaired oxygen delivery as a result of loss of capillary perfusion and increased oxygen consumption during sepsis.
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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 | 0.001 |
| 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".