Contribution of prostacyclin regulation in the vascular tone of angiopoietin like‐2 deficient mice
Bibliographic record
Abstract
Vascular tone, in response to acetylcholine (ACh), is controlled by various endothelium‐derived relaxing factors, which include nitric oxide (NO), prostacyclin, and endothelium‐derived hyperpolarizing factor. In turn, contribution of each factor may be influenced by pathologies. As such, in the insulin resistant state, NO production is impaired. Angiopoietin like‐2 (Angptl2), a member of the angiopoietin‐like protein family, was shown to cause insulin resistance related to obesity (Tabata, 2009). Objective An Angptl2 knock‐down (KD) mouse model was generated to study the role of Angptl2 in endothelial function in the femoral artery. Results Femoral arteries of 4‐month old Angptl2 KD and wild‐type (WT) mice showed that NO was responsible for the sensitivity of ACh‐mediated vasodilation in both groups, while prostacyclin contributed to maximal dilation in KD but not in WT. Femoral artery wall thickness of KD (20±1μm) at physiological pressure was smaller than that of WT (25±1μm; P<0.01, n=7), while constriction to phenylephrine was similar in both groups. Although KD and WT mice displayed similar metabolic parameters including fasting glucose level, KD mice showed a higher fasting insulin level (P<0.05, n=7–8). Conclusion Knock‐down of Angptl2 may lead to differences in the prostacyclin signaling pathway in the femoral arteries between the two genotypes of mice. Supported by CIHR MOP14496 and NSERC.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".