Effect of Endothelium-Specific Insulin Resistance on Endothelial Function In Vivo
Bibliographic record
Abstract
OBJECTIVE: Insulin resistance is an independent risk factor for the development of cardiovascular atherosclerosis. A key step in the development of atherosclerosis is endothelial dysfunction, manifest by a reduction in bioactivity of nitric oxide (NO). Insulin resistance is associated with endothelial dysfunction; however, the mechanistic relationship between these abnormalities and the role of impaired endothelial insulin signaling versus global insulin resistance remains unclear. RESEARCH DESIGN AND METHODS: To examine the effects of insulin resistance specific to the endothelium, we generated a transgenic mouse with endothelium-targeted overexpression of a dominant-negative mutant human insulin receptor (ESMIRO). This receptor has a mutation (Ala-Thr(1134)) in its tyrosine kinase domain that disrupts insulin signaling. Humans with the Thr(1134) mutation are insulin resistant. We performed metabolic and vascular characterization of this model. RESULTS: ESMIRO mice had preserved glucose homeostasis and were normotensive. They had significant endothelial dysfunction as evidenced by blunted aortic vasorelaxant responses to acetylcholine (ACh) and calcium ionophore. Furthermore, the vascular action of insulin was lost in ESMIRO mice, and insulin-induced endothelial NO synthase (eNOS) phosphorylation was blunted. Despite this phenotype, ESMIRO mice demonstrate similar levels of eNOS mRNA and protein expression to wild type. ACh-induced relaxation was normalized by the superoxide dismutase mimetic, Mn(III)tetrakis(1-methyl-4-pyridyl) porphyrin pentachloride. Endothelial cells of ESMIRO mice showed increased superoxide generation and increased mRNA expression of the NADPH oxidase isoforms Nox2 and Nox4. CONCLUSIONS: Selective endothelial insulin resistance is sufficient to induce a reduction in NO bioavailability and endothelial dysfunction that is secondary to increased generation of reactive oxygen species. This arises independent of a significant metabolic phenotype.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".