Kallikrein-mediated cell signalling: targeting proteinase-activated receptors (PARs)
Bibliographic record
Abstract
We tested the hypothesis that human tissue kallikreins (hKs) may regulate signal transduction by cleaving and activating proteinase-activated receptors (PARs). We found that hK5, 6 and 14 cleaved PAR N-terminal peptide sequences representing the cleavage/activation motifs of human PAR1 and PAR2 to yield receptor-activating peptides. hK5, 6 and 14 activated calcium signalling in rat PAR2-expressing (but not background) KNRK cells. Calcium signalling in HEK cells co-expressing human PAR1 and PAR2 was also triggered by hK14 (via PAR1 and PAR2) and hK6 (via PAR2). In isolated rat platelets that do not express PAR1, but signal via PAR4, hK14 also activated PAR-dependent calcium signalling responses and triggered aggregation. The aggregation response elicited by hK14 was in contrast to the lack of aggregation triggered by hK5 and 6. hK14 also caused vasorelaxation in a phenylephrine-preconstricted rat aorta ring assay and triggered oedema in an in vivo model of murine paw inflammation. We propose that, like thrombin and trypsin, the kallikreins must now be considered as important 'hormonal' regulators of tissue function, very likely acting in part via PARs.
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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".