Erythrocyte (RBC)‐Released ATP and Vascular Control: When it Works and What if it Does Not?
Bibliographic record
Abstract
Substantial evidence suggests that RBCs contribute to matching of oxygen (O 2 ) supply with demand via release of small amounts of ATP in regions of increased O 2 need, enhancing blood flow appropriately. We simulated this system using a computational model incorporating network geometry and conducted signaling to predict microvascular flow responses to changes in tissue O 2 . To test this innovative model, we used Zucker Diabetic Fatty (ZDF) rats at 7 weeks (pre‐diabetes; high insulin, normal glucose) and at 12 weeks (type II diabetes [DMII]; normal insulin, high glucose). In pre‐diabetes, capillary O 2 supply was decreased without a decrease in capillary density. RBCs exposed to pre‐diabetic insulin levels (1 nM) did not release ATP in response to reduced O 2 and isolated arterioles perfused with insulin treated RBCs did not dilate in response to low extraluminal O 2 . Finally, RBCs of rats and humans with DMII did not release ATP when exposed to low O 2 and isolated arterioles perfused with RBCs of humans with DMII did not dilate in response to low O 2 . These findings in the intact microcirculation and isolated vessels are consistent with predictions of the computational model. This systems biology approach provides novel insights into the mechanisms by which O 2 supply is matched with O 2 demand and will enhance our understanding of the causes of peripheral vascular complications in pre‐ and type II diabetes. (NIH R33 HL089094 )
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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 | 0.000 | 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".