Glycosylation and the activation of proteinase‐activated receptor 2 (PAR<sub>2</sub>) by human mast cell tryptase
Bibliographic record
Abstract
1. Human mast cell tryptase appears to display considerable variation in activating proteinase-activated receptor 2 (PAR(2)). We found tryptase to be an inefficient activator of wild-type rat-PAR(2) (wt-rPAR(2)) and therefore decided to explore the factors that may influence tryptase activation of PAR(2). 2. Using a 20 mer peptide (P20) corresponding to the cleavage/activation sequence of wt-rPAR(2), tryptase was as efficient as trypsin in releasing the receptor-activating sequence (SLIGRL.). However, in the presence of either human-PAR(2) or wt-r PAR(2) expressing cells, tryptase could only activate PAR(2) by releasing SLIGRL from the P20 peptide, suggesting that PAR(2) expressed on the cells was protected from tryptase activation. 3. Three approaches were employed to test the hypothesis that PAR(2) receptor glycosylation restricts tryptase activation. (a) pretreatment of wt-rPAR(2) expressing cells or human embryonic kidney cells (HEK293) with vibrio cholerae neuraminidase to remove oligosaccharide sialic acid, unmasked tryptase-mediated PAR(2) activation. (b) Inhibiting receptor glycosylation in HEK293 cells with tunicamycin enabled tryptase-mediated PAR(2) activation. (c) Wt-rPAR(2) devoid of the N-terminal glycosylation sequon (PAR(2)T25(-)), but not rPAR(2) devoid of the glycosylation sequon located on extracellular loop-2 (PAR(2)T224A), was selectively and substantially (>30 fold) more sensitive to tryptase compared with the wt-rPAR(2). 4. Immunocytochemistry using antisera that specifically recognized the N-terminal precleavage sequence of PAR(2) demonstrated that tryptase released the precleavage domain from PAR(2)T25(-) but not from wt-rPAR(2). 5. Heparin : tryptase molar ratios of greater than 2 : 1 abrogated tryptase activation of PAR(2)T25(-). 6. Our results indicate that glycosylation of PAR(2) and heparin-inhibition of PAR(2) activation by tryptase could provide novel mechanisms for regulating receptor activation by tryptase and possibly other proteases.
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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) | 0.001 | 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".