Suppression of Vascular Inflammation by Kinin B1 Receptor Antagonism in a Rat Model of Insulin Resistance
Bibliographic record
Abstract
BACKGROUND: Kinin B1 receptor (B1R) intervenes in a positive feedback loop to amplify and perpetuate the vascular oxidative stress in glucose-fed rats, a model of insulin resistance. This study aims at determining whether B1R blockade could reverse vascular inflammation in this model. METHODS/RESULTS: Young male Sprague-Dawley rats were fed with 10% D-glucose or tap water (controls) for 8 weeks, and during the last week, rats were administered the B1R antagonist SSR240612 (10 mg/kg/day, gavage) or the vehicle. The outcome was determined on glycemia, insulinemia, insulin resistance (homeostasis model assessment index), and on protein or mRNA expression of the following target genes in the aorta (by Western blot and real-time quantitative polymerase chain reaction): B1R, endothelial nitric oxide synthase, inducible nitric oxide synthase, macrophage CD68, macrophage/monocyte CD11b, interleukin (IL) -1β, tumor necrosis factor-α, IL-6, macrophage migration inhibitory factor, intercellular adhesion molecule-1, and E-selectin (endothelial adhesion molecule). Data showed increased expression of all these markers in the aorta of glucose-fed rats except endothelial nitric oxide synthase and tumor necrosis factor-α, which were not affected. SSR240612 reversed hyperglycemia, hyperinsulinemia, insulin resistance, and the upregulation of B1R, inducible nitric oxide synthase, macrophage CD68, and CD11b, IL-1β, inter-cellular adhesion molecule-1, macrophage migration inhibitory factor, and E-selectin in glucose-fed rats, yet it had no significant effect on IL-6 and in control rats. CONCLUSIONS: Kinin B1R antagonism reversed the upregulation of its own receptor and several pro-inflammatory markers in the aorta of glucose-fed rats. These data provide the first evidence that B1R may contribute to the low-grade vascular inflammation in insulin resistance, an early event in the development of type-2 diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".