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Therapeutic Intervention Targeting Mucosal Thrombin Or Protease‐Activated‐Receptor 1 Are Protective Against Colitis

2020· article· en· W3016685483 on OpenAlexaff
Jean‐Paul Motta, Simone Palese, David Sagnat, Perrine Rousset, Laura Guiraud, Anissa Edir, Carine Séguy, Laurent Alric, Delphine Bonnet, Barbara Bournet, Louis Buscail, Cyrielle Gilletta, Elisabetta Barocelli, Sylvie Le Grand, Bruno Le Grand, Céline Deraison, Nathalie Vergnolle

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsThrombinInflammatory bowel diseaseMedicineColitisPharmacologyTissue factorProteasesInflammationImmunologyPathologyInternal medicineChemistryCoagulationEnzymeDiseaseBiochemistry

Abstract

fetched live from OpenAlex

Background Current therapies for Inflammatory Bowel Disease (IBD) are unsatisfactory for proper tissue healing. Serine proteases belong to locally produced host factors that can fuel inflammatory processes in tissue from IBD patients, in part through activation of Protease‐Activated Receptors (PAR). We have recently discovered that intestinal epithelium was able to produce active thrombin, suggesting that mucosa itself could be an important source of high thrombin in IBD. Objectives We first aimed to determine whether mucosal thrombin was upregulated in animal models of colitis and in tissues from IBD patients. We then determined whether local thrombin upregulation could contribute to local tissue malfunctions. Finally, we evaluated therapeutic feasibility of local delivering of either direct thrombin inhibitors or PAR antagonist in animal models of colitis. Methods Colonic tissue samples were obtained from diagnosed IBD patients undergoing colonoscopy at the Toulouse Hospital. Colitis was induced by administering trinitrobenzene sulfonic acid (TNBS) in the colon of Wistar rats or C57Bl6 mice. Human tissue collection and animal procedures received ethical approval from local ethic committees. Thrombin (100 U/ml, 10 days), direct thrombin inhibitor (dabigatran, 1 μg/kg, 4 days) and PAR1 antagonist (Vorapaxar, 2.5 mg/kg, 7 days) were administered in the colon of healthy or TNBS animals under light anesthesia. At time of the sacrifice, colonic tissues were harvested and disease severity was assessed. Thrombin expression was detected using PCR, western blot and immunofluorescence. Thrombin activity was quantified in tissue supernatants using specific enzymatic assays. Results We confirmed an increased thrombin protein expression in human mucosal tissue by immunofluorescence and western blots. We found that some, but not all, forms of active thrombin were upregulated, particularly in tissues from Crohn’s disease patients. As observed in human, we found that increased thrombin mRNA expression and activity is also a feature of colitis in animal models of colitis. We demonstrated in vivo that colonic exposure to high dose of active thrombin can cause mucosal damage and tissue dysfunctions. Specific inhibition of thrombin activity, and PAR1 antagonists prevent some intestinal damage in TNBS colitis. Conclusions In this study, using both animal models and human IBD tissues, we showed that upregulation of mucosal thrombin alone can lead to inflammatory insults. We propose that targeting downstream events from high thrombin activity, rather than inhibiting thrombin directly, might be a better option for IBD because mucosal thrombin at low dose plays an important role on maintaining tissue homeostasis. Considering these promising preclinical results on PAR1 antagonist, future clinical studies in IBD patients could therefore be rapidly envisioned, particularly in patients with the strongest upregulation of thrombin activity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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)0.0040.000

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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2020
Admission routes1
Has abstractyes

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