Protease-activated receptor-2 activation: a major actor in intestinal inflammation
Bibliographic record
Abstract
BACKGROUND AND AIMS: The role of protease-activated receptor-2 (PAR(2)) during intestinal inflammation is still unclear due to the fact that PAR(2)-activating peptide has both pro- and anti-inflammatory properties. The aim of this study was to investigate the effects of PAR(2) deficiency (using PAR(2)-deficient mice, PAR(2)(-/-)) in models of colitis, in order to elucidate the role of endogenous PAR(2) in the process of inflammation in the gut. METHODS: Colonic inflammation in wild-type and PAR(2)(-/-) mice was induced by dextran sodium sulfate, trinitrobenzene sulfonic acid (TNBS), a T helper-1 predominant model, or oxazolone, a T helper-2 predominant model. Leukocyte recruitment, assessed by intravital microscopy, and inflammatory parameters (myeloperoxidase (MPO), macroscopic and microscopic damage) were assessed during the development of colitis. Lastly, the protein levels of cyclooxygenases (COXs) and adhesion molecules (ICAM-1, VCAM-1, alpha-M, alpha-4) were assessed by using western blot analysis. RESULTS: In all three models of colitis, MPO activity, macroscopic damage score and bowel thickness were significantly lower in PAR(2)(-/-) mice. Changes in vessel leukocyte recruitment parameters (rolling and adhesion) were also significantly reduced in PAR(2)(-/-) mice compared to wild-type mice after the induction of colitis. The protein expression of ICAM-1, VCAM-1 and alpha-4 was significantly attenuated, whereas the expression of COX-1 was significantly increased in PAR(2)(-/-) mice challenged with TNBS-induced colitis. CONCLUSIONS: The role of endogenous PAR(2) in the gut is pro-inflammatory and independent of the T helper-1 or -2 cytokine profile. Endogenous PAR(2) activation controls leukocyte recruitment in the colon and thus appears as a new potential therapeutic target for the treatment of inflammatory bowel disease.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".