Glucose-stimulated insulin secretion causes an insulin-dependent nitric oxide–mediated vasodilation in the blood supply of the rat sciatic nerve
Bibliographic record
Abstract
This study tested the hypothesis that acute hyperglycemia reduces sciatic nerve blood flow in Sprague-Dawley rats. Anesthetized rats underwent cannulation of their right jugular vein (for anesthetic/nutrient/drug infusion) and right carotid artery (for continuous blood pressure measurement via pressure transducer). The left sciatic nerve was exposed and nerve blood velocity (NBV) was assessed from an arterial segment lying superficially along the sciatic nerve (Doppler ultrasound, 40 MHz). NBV and mean arterial pressure (MAP) values were collected, and an index of nerve vascular conductance (NVC) was established (NBV/MAP) at baseline and at 5, 10, 20, and 30 min (and 80 min for insulin) following 1) low glucose infusion, 1 g/kg (50% solution); 2) high glucose infusion, 3 g/kg; 3) high glucose infusion in the absence of a functioning pancreas; 4) euglycemic hyperinsulinemic clamp-insulin infusion (10 mU·kg⁻¹·min⁻¹; 0.4 IU/ml); 5) high glucose infusion + NG-nitro-L-arginine methyl ester (L-NAME) infusion (30 mg/kg); and 6) L-NAME alone followed 20 min later by high glucose infusion. High glucose infusion increased NVC by ~120% relative to baseline (P < 0.001), and this dilation was attenuated in rats without a functioning pancreas (i.e., without insulin secretion) (P = 0.004) and following L-NAME infusion (P = 0.011). Therefore, the vasodilation in rat sciatic nerve during glucose infusion was dependent upon the insulin response and acted through a nitric oxide synthase pathway.
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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 | 0.001 |
| 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".