Type 2 diabetes impairs vascular responsiveness to nitric oxide, but not the venoarteriolar reflex or post‐occlusive reactive hyperaemia in forearm skin
Bibliographic record
Abstract
The venoarteriolar reflex (VAR) is a local mechanism by which vasoconstriction is mediated in response to venous congestion. This response may minimize tissue overperfusion, preventing capillary damage and oedema. Post-occlusive reactive hyperaemia (PORH) is used to assess microvascular function by performing a brief local arterial occlusion resulting in a subsequent rapid transient vasodilation. In the current study, we hypothesized that type 2 diabetes (T2D) attenuates VAR and PORH responses in forearm skin in vivo. In 11 healthy older adults (Control, 58 ± 8 years) and 13 older adults with controlled T2D (62 ± 10 years), cutaneous blood flow measured by laser-Doppler flowmetry was monitored following a 3-min venous occlusion of 45 mm Hg that elicited the VAR, followed by a 3-min recovery period and then a 5-min arterial occlusion of 240 mm Hg that induced PORH. Finally, sodium nitroprusside, a nitric oxide donor, was administered to induce maximum vasodilation. VAR and PORH variables were similar between groups. By contrast, maximal cutaneous blood flow induced by sodium nitroprusside was lower in the T2D group. Taken together, our observations indicate that T2D impairs vascular smooth muscle responsiveness to nitric oxide, but not VAR and PORH in forearm skin.
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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".