Insulin decreases atherosclerotic plaque burden and increases plaque stability via nitric oxide synthase in apolipoprotein E-null mice
Bibliographic record
Abstract
It has been argued whether insulin accelerates or prevents atherosclerosis. Although results from in vitro studies have been conflicting, recent in vivo mice studies demonstrated antiatherogenic effects of insulin. Insulin is a known activator of endothelial nitric oxide synthase (NOS), leading to increased production of NO, which has potent antiatherogenic effects. We aimed to examine the role of NOS in the protective effects of insulin against atherosclerosis. Male apolipoprotein E-null mice (8 wk old) fed a high-cholesterol diet (1.25% cholesterol) were assigned to the following 12-wk treatments: control, insulin (0.05 U/day via subcutaneous pellet), N(ω)-nitro-l-arginine methyl ester hydrochloride (l-NAME, via drinking water at 100 mg/l), and insulin plus l-NAME. Insulin reduced atherosclerotic plaque burden in the descending aorta by 42% compared with control (plaque area/aorta lumen area: control, 16.5 ± 1.9%; insulin, 9.6 ± 1.3%, P < 0.05). Although insulin did not decrease plaque burden in the aortic sinus, macrophage accumulation in the plaque was decreased by insulin. Furthermore, insulin increased smooth muscle actin and collagen content and decreased plaque necrosis, consistent with increased plaque stability. In addition, insulin treatment increased plasma NO levels, decreased inducible NOS staining, and tended to increase phosphorylated vasodilator-stimulated phosphoprotein staining in the plaques of the aortic sinus. All these effects of insulin were abolished by coadministration of l-NAME, whereas l-NAME alone showed no effect. Insulin also tended to increase phosphorylated endothelial NOS and total neuronal NOS staining, effects not modified by l-NAME. In conclusion, we demonstrate that insulin treatment decreases atherosclerotic plaque burden and increases plaque stability through NOS-dependent mechanisms.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".