Prolonged AMP-activated protein kinase induction impairs vascular functions
Bibliographic record
Abstract
AMP-activated protein kinase (AMPK) is a regulator of cellular metabolism and is involved in the pathogenesis of several diseases, including type 2 diabetes and cardiovascular diseases. Data showing the effects of AMPK on vasculature are controversial. Therefore, the aim of this study was to determine the impact of prolonged AMPK activation on vascular functions. For this purpose we have examined the role of AMPK in endothelium-dependent and -independent relaxation and vascular contractions. For this, we incubated thoracic aortic rings, from rats, with AMPK activator 5-aminoimidazole-4-carboxamide-1-4-ribofuranoside (AICAR, 500 μmol/L or 2 mmol/L) in the presence or absence of AMPK inhibitor compound C (10 μmol/L). Next, cumulative dose-response curves to acetylcholine (ACh) (10(-9)-10(-4) mol/L), nitroglycerine (NG) (10(-9)-3 × 10(-5) mol/L), and noradrenaline (NA) (10(-9)-10(-4) mol/L) were obtained. Endothelial nitric oxide synthase (eNOS) protein expression was determined. Our results show that endothelium-dependent relaxation was inhibited after AICAR treatment, and that this effect was reversed by AMPK inhibition. Moreover, AICAR enhanced the contractile response to NA and caused a decrease in eNOS protein expression. In conclusion, prolonged AMPK induction causes endothelial impairment, possibly via increased degradation and (or) reduced expression of eNOS.
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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) | 0.000 | 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".