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Colonic luminal proteases activate colonocyte proteinase‐activated receptor‐2 and regulate paracellular permeability in mice

2006· article· en· W2091099123 on OpenAlexaff
R Róka, J. Demaude, Nicolas Cénac, Laurent Ferrier, Christel Salvador‐Cartier, Jean Fioramonti, Lionel Buéno

Bibliographic record

VenueNeurogastroenterology & Motility · 2006
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProteasesProteaseTrypsinProtease-activated receptor 2Paracellular transportChemistryReceptorMast cellIntestinal permeabilitySerine proteasePharmacologyBiochemistryBiologyEnzymePermeability (electromagnetism)Immunology

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.243
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations55
Published2006
Admission routes1
Has abstractyes

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