Review article: proteinase‐activated receptors — novel signals for gastrointestinal pathophysiology
Bibliographic record
Abstract
Proteinase-activated receptors (PARs) have the common property of being activated by the proteolytic cleavage of their extracellular N-terminal domain. The new NH2-terminus acts as a 'tethered ligand' binding and activating the receptor itself. Four members of this family have been cloned, three of which are activated by thrombin (PAR-1, PAR-3 and PAR-4) while the fourth (PAR-2) is activated by trypsin or mast cell tryptase. In physiological or pathophysiological conditions, the gastrointestinal tract is exposed more than other tissues to proteinases (digestive enzymes, proteinases from pathogens or proteinases from inflammatory cells) that can activate PARs. Since PARs are highly expressed throughout the gastrointestinal tract, the study of the role of PARs in these tissues appears to be particularly important. It has already been shown that PAR-2 activation induces calcium mobilization and eicosanoid production in enterocytes as well as changes in ion transport in jejunal tissue segments. PAR-2 activation also causes calcium mobilization and stimulates amylase release from pancreatic acini. Moreover, both PAR-1 and PAR-2 activation can alter the gastrointestinal motility. In inflammatory or allergic conditions, the proteinases that constitute the major agonists for PARs (thrombin, trypsin and mast cell tryptase) are usually released. The activation of PARs by these proteinases might contribute to the gastrointestinal disorders associated with these pathologies. A complete understanding of the role of PARs in the gastrointestinal tract will require the development of selective receptor antagonists that are not yet available. Nonetheless, the use of PAR agonists has already highlighted new potential functions for proteinases in the gastrointestinal tract, thus the control of PAR activation might represent a promising therapeutic target.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.009 |
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".