Glucose infusion (3g/kg) increases nerve vascular conductance through an insulin‐mediated nitric oxide mechanism in rats
Bibliographic record
Abstract
We tested the hypothesis that acute hyperglycemia will reduce nerve vascular conductance (NVC) in rats. Sprague‐Dawley rats (N=25) were anaesthetised, blood pressure (MAP) was monitored with a pressure transducer and the left sciatic nerve was exposed from the dorsal side. Doppler ultrasound (40‐MHz: Vevo 2100 ‐ VisualSonics) was used to measure nerve blood flow velocity in an arterial segment along the nerve. Rats underwent one of four systemic intravenous glucose infusion protocols (1: 1g/kg body mass glucose; 2) 3g/kg glucose; 3) 3g/kg + 15mg/kg of L‐NAME and 4) 15mg/kg of L‐NAME alone + 3g/kg of glucose after 20min), as well as an isovolumetric saline infusion (saline did not affect NVC). An additional group was injected with streptozotocin (60mg/kg) with an insulin pellet implanted subcutaneously to produce a normoglycemic, non‐insulin responsive condition; these animals also underwent the 3g/kg glucose infusion. Relative to baseline 3g/kg increased (P<0.01) NVC (NBVF/MAP; ~ 125%). This dilation was blunted in the L‐NAME and non‐insulin responsive groups (both NS). Therefore, hyperglycemia‐induced increases in NVC appear to be mediated by an insulin‐stimulated NO mechanism. Funded by a CIHR
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".