MétaCan
Menu
← Back to cohort

NOVEL REGULATION OF A PAR2‐MEDIATED CELLULAR MIGRATION PROGRAM BY PRO‐INFLAMMATORY CYTOKINES

2019· article· en· W3173962438 on OpenAlexafffundabout
Andrew Vegso, Wallace K. MacNaughton

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsWound healingProteasesCytokineCell migrationReceptorInflammationCell biologyProinflammatory cytokinePhosphorylationIntracellularMedicineImmunologyCellChemistryBiologyInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND Mucosal healing is the gold standard for IBD therapy. However, the mechanisms that determine mucosal healing are complex and need to be better understood to explain why many patients fail to achieve this key goal of therapy. The inflammatory environment is characterized by the presence of several serine proteases that signal through the protease‐activated receptors (PARs). PAR2 is ubiquitously expressed in the epithelial cells of the intestinal mucosa and activation serves a protective role consistent with host defence and repair. While our preliminary findings indicate that activation of PAR2 enhances wound closure, we do not know the cellular mechanisms that underlie this response. We hypothesize that activation of PAR2 induces a cellular migration program in intestinal epithelial cells that enhances mucosal healing in the inflammatory milieu . METHODS Circular wounds were introduced in T84 colonic epithelial cells. Wounded monolayers were treated with the PAR2 activating peptide, 2‐furoyl‐LIGRLO (2fLI, 5 μM), or the control reverse‐sequence peptide, 2‐furoyl‐OLRGIL (2fO, 5 μM), and live cell imaging was utilized to record wound closure over a 24 hr period. In other experiments, a cytokine cocktail consisting of IFNγ (10 ng/mL) and TNFα (10 ng/mL), alone or in combination with 2fLI, was applied to wounded monolayers and wound closure assessed. Intracellular effects of PAR2 activation and cytokine treatment were evaluated by measuring phosphorylation of key canonical signaling proteins using the MSD multi‐plex ELISA array system. EdU staining, with or without Mitomycin C (MMC), an inhibitor of proliferation, was used to determine the effect of cellular proliferation on wound closure. RESULTS PAR2 activation by 2fLI promoted wound closure in a concentration‐dependent manner (0.1 μM – 10 μM) compared to 2fO controls at the 12 and 24 hr timepoints. Interestingly, co‐stimulation with 2fLI and the cytokine cocktail resulted in an enhanced wound closure response at the 12 and 24 hr timepoints that was significantly greater than individual treatments ( p <0.001). Co‐stimulation activated the downstream intracellular targets ERK1/2 and JNK compared to 2fO ( p <0.001), but this activation was not greater than stimulation with 2fLI or cocktail alone, suggesting that MAP kinase activation was not responsible for the enhanced effect. MMC pre‐treatment partially reduced wound closure caused by co‐stimulation with 2fLI/IFNγ/TNFα, indicating that the enhanced wound healing effect was due in part to increased proliferation. CONCLUSIONS These data suggest that both PAR2 activation and cytokine treatment promote wound closure in vitro through both enhanced cell migration and proliferation. The enhanced wound healing response to PAR2 activation in the presence of pro‐inflammatory cytokines suggests that the inflammatory milieu is necessary to initiate a proper wound healing response. Support or Funding Information Canadian Institutes of Health Research (CIHR) This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 score0.002
Threshold uncertainty score0.008

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.250
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
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueThe FASEB Journal→Same topicBlood Coagulation and Thrombosis Mechanisms→French-language works237,207→