Colonic luminal proteases activate colonocyte proteinase‐activated receptor‐2 and regulate paracellular permeability in mice
Bibliographic record
Abstract
Luminal activation of protease-activated receptors-2 (PAR(2)) on colonocytes by trypsin or PAR(2)-activating peptide increases colonic paracellular permeability (CPP). The aim of this study was to evaluate the role of proteases from endogenous and bacterial origin in the modulation of CPP and colonocyte PAR(2) expression in mice. CPP was assessed with (51)Cr-EDTA after intracolonic administration of different protease inhibitors. After 12 days of oral antibiotic treatment, measurements of colonic luminal serine protease activity (CLSPA), CPP, mucosal mouse mast cell proteinase-1 (MMCP-1) content, immunochemistry of PAR(2) and assessment of effects of PAR(2) agonist (SLIGRL) and mast cell degranulator (C48/80) on CPP in Ussing chambers were performed. Immunochemistry was repeated after intracolonic trypsin administration. Colonic infusion of protease inhibitors significantly reduced CPP. In antibiotic-treated mice, CLSPA was reduced coupled with a decrease in PAR(2) expression, but with no change in CPP and MMCP-1 content. Trypsin administration restored PAR(2) expression. The increase in CPP induced by SLIGRL and C48/80 was reduced after antibiotic treatment. Protease activity of colonic content plays an important role in the regulation of mucosal barrier through activation of PAR(2).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".