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Record W3134171751 · doi:10.1093/jcag/gwab002.186

A188 TARGETING RIPK2 TO TREAT INTESTINAL INFLAMMATION CAUSED BY SHIP DEFICIENCY

2021· article· en· W3134171751 on OpenAlexaff
Y Pang, Susan C. Menzies, Shairaz Baksh, Laura M. Sly

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsNOD2InflammationXIAPMedicineCytokineImmunologyMuramyl dipeptideCrohn's diseaseImmune systemCancer researchBiologyInternal medicineApoptosisDiseaseInnate immune systemCaspaseProgrammed cell death

Abstract

fetched live from OpenAlex

Abstract Background Crohn’s disease (CD) is a form of inflammatory bowel disease characterized by chronic inflammation along the gastrointestinal tract. We have described the SHIP-/- mouse model of CD-like intestinal inflammation. SHIP-/- mice develop spontaneous ileal inflammation that is characterized by villus hyperplasia and disorganization, edema, immune cell infiltration, ulceration, loss of goblet cells, and muscle wall thickening. SHIP deficiency in people with CD has been associated with a more severe and treatment-refractory disease. Interestingly, NOD2 gene variants, which are the most profound genetic associations for CD, are also associated with a more severe CD phenotype. Muramyl dipeptide (MDP) is a molecular associated microbial pattern, which activates the NOD2 signalling pathway. Recently, SHIP has been reported to play a role in the NOD2 pathway by disrupting the downstream interaction between RIPK2 and XIAP required for NOD2-mediated NFκB activation and pro-inflammatory cytokine production. Aims Based on this, we hypothesized that SHIP deficiency contributes to inflammation in CD by increasing NOD2-mediated pro-inflammatory cytokine production. Moreover, RIPK2 inhibitors will block intestinal inflammation caused by SHIP deficiency by blocking RIPK2-XIAP interactions required for NOD2 signalling and resultant pro-inflammatory cytokine production. To test this hypothesis, my aim was to determine the effect of RIPK2 inhibitors on the development of spontaneous intestinal inflammation in SHIP-/- mice. Methods 6 week-old SHIP-/- mice (and SHIP+/+ mice controls) were treated with RIPK2 inhibitors, FCG806791773 or Z1210264067, by intra-pertioneal injections every other day for 2 weeks and compared to SHIP-/- mice treated with 2% DMSO in PBS, as a vehicle control. On Day 14, distal ilea were harvested and gross pathology was assessed. Cross-sections of the ilea were H&E stained to evaluate histological damage based on villi architecture, edema, immune cell infiltration, ulceration, goblet cell loss, and muscle wall thickening. Results As expected, SHIP+/+ mice did not have gut pathology and their healthy gut phenotype was not affected by RIPK2 inhibitors. SHIP-/- mice had ileal inflammation that was evident in gross pathology and in H&E-stained tissue sections. Importantly, SHIP-/- mice treated with RIPK2 inhibitors, FCG806791773 or Z1210264067, had reduced gross pathology compared to vehicle control-treated mice. Z1210264067 treated SHIP-/- mice also had significantly lower histological damage compared to vehicle control-treated SHIP-/- mice. Conclusions RIPK2 inhibitors reduced gross and histopathology in SHIP-/- mice suggesting that RIPK2 inhibitors may be an effective treatment for people with CD, and may be particularly effective in people with CD, who harbor NOD2 risk variants and/or have low SHIP activity. Funding Agencies CCC, CIHR

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.005
GPT teacher head0.208
Teacher spread0.203 · 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
Published2021
Admission routes1
Has abstractyes

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