What is the Efficiency of ATP Signaling from Erythrocytes to Regulate Distribution of O<sub>2</sub> Supply Within the Microvasculature?
Bibliographic record
Abstract
Erythrocytes appear to be ideal sensors for regulating microvascular O(2) supply as they release the potent vasodilator ATP in an O(2) saturation-dependent manner. Whether erythrocytes play a significant role in regulating O(2) supply in the complex environment of diffusional O(2) exchange among capillaries, arterioles, and venules, depends on the efficiency with which erythrocytes signal the vascular endothelium. If one assumes that the distribution of purinergic receptors is uniform throughout the microvasculature, then the most efficient site for signaling should occur in capillaries, where the erythrocyte membrane is in close proximity to the endothelium. ATP released from erythrocytes would diffuse a short distance to P(2y) receptors inducing an increase in blood flow, possibly the result of endothelial hyperpolarization. We hypothesize that this hyperpolarization varies across the capillary bed depending upon erythrocyte supply rate and the flux of O(2) from these erythrocytes to support O(2) metabolism. This would suggest that the capillary bed would be the most effective site for erythrocytes to communicate tissue oxygen needs. Electrically coupled endothelial cells conduct the integrated signal upstream where arterioles adjust vascular resistance, thus enabling ATP released from erythrocytes to regulate the magnitude and distribution of O(2) supply to individual capillary networks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".