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Delineating cytokine signaling pathways in ulcerative colitis and Crohn's disease through colonic mucosa gene expression profiles.

2011· article· en· W2775594803 on OpenAlexfundno aff
George P. Christophi, Runsheng Rong, Paul Massa, Philip G. Holtzapple, S.K. Landas

Bibliographic record

VenueInflammatory Bowel Diseases · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUlcerative colitisInflammatory bowel diseaseCrohn's diseaseMedicineColitisCytokineSignal transductionGene expressionIntestinal mucosaGeneImmunologyDiseaseBiologyPathologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Cytokine signaling pathways play a central role in the pathogenesis of inflammatory bowel disease (IBD). Numerous clinical studies have shown that several inflammatory cytokines are elevated in active IBD and recent genome-wide association studies have provided evidence of intricate immune pathways that confer susceptibility to IBD. Despite this extensive knowledge on molecular mechanisms of IBD pathogenesis, the main diagnostic modality for IBD and differentiation between ulcerative colitis (UC) and Crohn's disease (CD) is the histopathologic evaluation of colon biopsy samples. This study aims to delineate the cytokine signaling pathways in colonic mucosa of CD and UC patients, explore possible molecular markers for IBD diagnosis, and identify novel immune-mediators of IBD pathogenesis. The study quantifies gene expression levels from formalin-fixed, paraffin-embedded (FFPE) archived colonic mucosa samples. Based on established clinical diagnosis and strict histopathological inclusion/exclusion criteria, fifty colon biopsy samples were assigned into five categories: 1) severe/active UC, 2) severe/active CD 3) quiescent UC, 4) quiescent CD, and 5) normal control subjects. Gene expression is analyzed by quantitative real-time RT-PCR. Highly efficient mRNA isolation techniques, RT-PCR enzymes, cDNA conversion using random hexamers, and gene-specific primers generating short amplicons (70-150bp) allows successful quantification of gene expression from these formalin-fixed tissues. This study investigates the expression of more than twenty genes, including the cytokines TNF- α, IFN-γ, IL-12, IL-23, IL-17, IL-10, IL-13, IL-33. Also, downstream cytokine-induced inflammatory genes are quantified, including the transcription factors T-bet, GATA-3, FoxP3, the chemokines MCP-1, IP-10, CCL17, the proteases ADAM8, MMP3, Kallikrein 6, the adhesion molecules VCAM, ICAM-1, VLA-4, and the enzymes iNOS, COX2, NOX2/gp91phox. These data should provide insights into the pathogenesis of IBD though identifying novel immune-mediators and elucidating distinct signaling networks in CD and UC. Furthermore, gene profiling utilizing FFPE tissue is practical, it can be used retrospectively, and importantly it has been successfully integrated into clinical practice with good prognostic value in cancer patients. Thus, this study aims to develop additional practical molecular tools for the diagnosis and prognosis of IBD and differentiate between UC and CD. Finally, several biologic agents targeting TNF-α, IL-12/23 p40, IL-6r, α4 integrins, CCR9, CD40, and MyD88 are novel promising IBD treatments and this study provides a convenient approach that can be used to identify molecular markers that can predict the response to these treatments.

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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.017
GPT teacher head0.236
Teacher spread0.219 · 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
Published2011
Admission routes1
Has abstractyes

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