Proteinase‐activated receptors, PAR1 & PAR2, regulate porcine coronary contractility via tyrosine kinase‐MAPKinase signaling involving a cyclooxygenase (COX)‐1 product
Bibliographic record
Abstract
Objective PARs 1 and 2 regulate vascular tension and also trigger both tyrosine kinase (PYK) and MAPKinase signals, in part via EGF receptor (EGFR) transactivation. We hypothesized that PAR‐triggered MAPK and PYK activities regulate porcine coronary artery (PCA) tension via EGFR activation. Methods Contractions of L‐NAME‐treated PCA rings ± functional endothelium stimulated by PAR1/2‐selective activating peptides (PAR‐APs), EGF, angiotensin‐II (AngII) and PGF 2α were monitored in the absence and presence of the signal pathway inhibitors: PP1 (Src kinase), AG1478 (EGFR kinase), U0126 (MAPK), PD98059 (MAPK), and the COX inhibitors, indomethacin (INDO, COX1,2), SC560 (COX1), & NS398 (COX2). Results Endothelium‐independent contractions by PAR1/2‐APs, Ang‐II, and EGF (but not by PGF 2α ) were inhibited by PP1, U0126, & PD98059. AG1478 blocked mainly PAR2‐AP and EGF contractions, Further, PAR‐AP & Ang‐II contractions, blocked by INDO & SC560, were mimicked by arachidonate. In contrast, PGF 2α ‐induced contraction was not affected by any inhibitor used. Conclusions PARs 1 & 2, like AngII, regulate coronary tension via a PYK‐MAPK pathway involving a COX1 metabolite, but by distinct GPCR mechanisms that differentially transactivate the EGFR. Support: CIHR‐Canada, Qatar Foundation NPPR and the Heart & Stroke Foundation of Canada.
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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 | 0.000 |
| 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".