Divergent effects of low-O<sub>2</sub>tension and iloprost on ATP release from erythrocytes of humans with type 2 diabetes: implications for O<sub>2</sub>supply to skeletal muscle
Bibliographic record
Abstract
Erythrocytes release both O(2) and a vasodilator, ATP, when exposed to reduced O(2) tension. We investigated the hypothesis that ATP release is impaired in erythrocytes of humans with type 2 diabetes (DM2) and that this defect compromises the ability of these cells to stimulate dilation of resistance vessels. We also determined whether a general vasodilator, the prostacyclin analog iloprost (ILO), stimulates ATP release from healthy human (HH) and DM2 erythrocytes. Finally, we used a computational model to compare the effect on tissue O(2) levels of increases in blood flow directed to areas of increased O(2) demand (erythrocyte ATP release) with nondirected increases in flow (ILO). HH erythrocytes, but not DM2 cells, released increased amounts of ATP when exposed to reduced O(2) tension (Po(2) < 30 mmHg). In addition, isolated hamster skeletal muscle arterioles dilated in response to similar decreases in extraluminal O(2) when perfused with HH erythrocytes, but not when perfused with DM2 erythrocytes. In contrast, both HH and DM2 erythrocytes released ATP in response to ILO. In the case of DM2 erythrocytes, amounts of ATP released correlated inversely with glycemic control. Modeling revealed that a functional regulatory system that directs blood flow to areas of need (low O(2)-induced ATP release) provides appropriate levels of tissue oxygenation and that this level of the matching of O(2) delivery with demand in skeletal muscle cannot be achieved with a general vasodilator. These results suggest that the inability of erythrocytes to release ATP in response to exposure to low-O(2) tension could contribute to the peripheral vascular disease of DM2.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".