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Record W2898812156 · doi:10.1016/j.jcmgh.2018.10.012

Proteolytic Processing of the Epithelial Adherens Junction Molecule E-Cadherin by Neutrophil Elastase Generates Short Peptides With Novel Wound-Healing Bioactivity

2018· letter· en· W2898812156 on OpenAlexafffund
Marilyn Gordon, Anaïs Chauvin, François‐Michel Boisvert, Wallace K. MacNaughton

Bibliographic record

VenueCellular and Molecular Gastroenterology and Hepatology · 2018
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversité de SherbrookeUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCrohn's and Colitis CanadaUniversity of Calgary
KeywordsAdherens junctionWound healingProteasesNeutrophil elastaseInflammatory bowel diseaseMedicineElastaseImmunologyContext (archaeology)Ulcerative colitisProinflammatory cytokineCadherinInflammationDiseaseBiologyPathologyCellEnzyme

Abstract

fetched live from OpenAlex

We report the novel observation that the inflammatory protease, neutrophil elastase (NE), present in high abundance in inflamed tissue in inflammatory bowel disease (IBD) patients, is capable of cleaving the cellular adherens junction protein, E-cadherin. Proteolysis of E-cadherin by NE generates a variety of short peptides, several of which were observed in patient tissue samples, showing biological activity to promote wound closure in an in vitro model system. This effect is independent of proliferation either in a wounded monolayer or under subconfluent conditions, suggesting a primarily migratory activity upon colonic epithelial monolayers.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.007
GPT teacher head0.201
Teacher spread0.194 · 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

Citations12
Published2018
Admission routes2
Has abstractyes

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