Insulin Action in the Vasculature: Physiology and Pathophysiology
Bibliographic record
Abstract
Studies to date have provided convincing evidence that insulin has an important role in the normal functioning of the vasculature from the perspective of the regulated delivery of nutrients to a tissue bed. This is mediated by an effect on the endothelium analogous to other endothelial responses, and insulin resistance is reflected in, and in part due to, impaired vasodilatory actions of insulin. Because insulin normally stimulates the net production of nitric oxide, which is beneficial in both the short term for vasomotion and antithrombosis, and the long term for inhibition of smooth muscle cell growth and migration, vascular insulin resistance also has important implications for vascular pathophysiology. Further, recent evidence suggests that the hyperinsulinemia accompanying insulin resistance may aggravate this situation by augmenting the endothelial production and release of endothelin-1. The investigation of insulin resistance in the vasculature provides not only a unique and physiologically relevant window onto vascular pathology, but also an opportunity for therapeutic targeting in individuals affected by the clinical states of insulin resistance. The present review highlights the importance of insulin sensitivity in the maintenance of endothelial function and explores the relationships between vascular insulin resistance and whole body glucose disposal. In addition, the recent evidence linking insulin to endothelin-1 production is discussed. Improving insulin sensitivity with insulin sensitizers such as rosiglitazone may represent an important advance in our ability to improve vascular dysfunction in diabetes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".