Preserved arterial vasodilatation via endothelial protease-activated receptor-2 in obese type 2 diabetic mice
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: In non-obese diabetic animals, protease-activated receptor-2 (PAR2) agonists are more effective vasodilators, which is attributed to increased COX-2 and endothelial NOS (eNOS) activities. Under conditions of diabetes and obesity, the effectiveness of PAR2 agonists is unknown. We compared the vasodilator responses of small calibre mesenteric arteries from obese diabetic B6.BKS(D)-Lepr(db) /J (db/db) induced by PAR2-activating agonists 2-furoyl-LIGRLO-amide (2fly) and trypsin to those obtained in controls [C57BL/6J (C57)], and assessed the contributions of COX, NOS and calcium-activated potassium channels (K(Ca)) to these responses. EXPERIMENTAL APPROACH: Arteries mounted in wire myographs under isometric tension conditions were contracted submaximally by U46619 then exposed to vasodilators. mRNA and protein expression of PAR2, eNOS and soluble GC (sGC) were determined by real-time PCR and Western blots. KEY RESULTS: ACh- and nitroprusside-induced relaxations were attenuated in db/db compared with C57. In contrast, 2fly- and trypsin-induced relaxations were largely retained in db/db. A NOS inhibitor partly inhibited ACh- and 2fly-induced relaxations in C57, but not those in db/db. Inhibitors of the COX-cAMP pathway (FR122044, SC560, NS398, SC58125, SQ22536, CAY10441) did not affect these relaxation responses in either strain. Charybdotoxin (BK(Ca), SK3.1 blocker), but not iberiotoxin (BK(Ca) blocker), inhibited responses to the PAR2 agonists in db/db. In db/db protein levels of eNOS were higher, whereas those of sGC were lower than in C57. PAR2 mRNA expression in db/db was higher than in C57. CONCLUSIONS AND IMPLICATIONS: PAR2-mediated vasodilatation is protected against the negative effects of obesity and diabetes in mice. In diabetic vascular dysfunction, preserved PAR2 vasodilatation was linked to activation of SK3.1.
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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 | 0.001 |
| 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".