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Record W2920852356 · doi:10.1093/jcag/gwz006.251

A252 THE DIETARY FIBRE, RHAMNOGALACTURONAN (RGAL), DRIVES AN INFLAMMATORY GENE EXPRESSION PROFILE IN INTESTINAL EPITHELIAL CELLS

2019· article· en· W2920852356 on OpenAlexaffabout
Jinsai Shang, Cristiane Hatsuko Baggio, Antonia Maiara Marques do Nascimento, Thales R. Cipriani, Wallace K. MacNaughton

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInflammationTranscriptomeInflammatory bowel diseaseWound healingEpitheliumImmunologyIntestinal epitheliumBiologyCell biologyIntestinal mucosaCaco-2Barrier functionGene expressionCellPathologyMedicineGeneInternal medicineDiseaseBiochemistryGenetics

Abstract

fetched live from OpenAlex

Impaired mucosal healing in the intestinal epithelium has been linked to inflammatory bowel disease (IBD). While the resolution of inflammation was historically perceived to be a passive process of mucosal healing, we have begun to appreciate that cells and mediators that have traditionally been considered pro-inflammatory, are also crucial in the resolution of inflammation. Specifically, recent evidence suggests that neutrophils, while important contributors to acute inflammation, are also key elements in the pro-resolution microenvironment that promotes mucosal healing in the inflamed gut. Our previous data have shown that administration of the dietary fibre, rhamnogalacturonan (RGal), reduces disease severity in a murine model of DSS colitis. Additionally, apical treatment of the Caco-2 human intestinal epithelial cell line with RGal induces an increase in transepithelial electrical resistance (TER) and accelerates wound-healing in vitro. We hypothesized that RGal promotes a healing response in epithelial cells via the production of mediators that contribute to the establishment of a pro-resolution microenvironment. The aims of this project are to (1) Characterize the receptor(s) and signalling pathways activated by RGal in intestinal epithelial cells and (2) determine the ability of RGal to create a pro-resolution inflammatory milieu and mediate neutrophil-epithelial interactions. In order to determine the transcriptionally dependent effects of RGal on epithelial function, Caco-2 monolayers were treated apically for 6, 12 and 24h with RGal, and RNA collected for transcriptome sequencing. Genes with changes in expression more than 3-fold were entered into Enrichr for pathway analysis. In order to confirm changes in protein expression from transcriptome sequencing data, Meso Scale Discovery (MSD) multi-array immunoassay was performed. RGal differentially induced changes in gene expression 6, 12 and 24h post-treatment. While RGal had no significant effect on tight junction gene expression 6h post-treatment, RGal upregulated the expression of inflammatory response genes including neutrophil regulatory genes (CXCL1, 243.9-fold; CXCL2, 15.2-fold; CXCL3, 58.8-fold; CXCL5, 57-fold; CXCL8, 515.6-fold; G-CSF, 18-fold; n=3; p<0.05). Consistent with gene expression data, MSD multi-plex immunoassay revealed an upregulation in CXCL8 family chemokines. For example, CXCL8 production was increased in cell lysates 116.1-fold 2h post-treatment (n=3; p<0.01) and secretion of CXCL8 was increased 11.8-fold in cell supernatants 8h post-treatment (n=3; p<0.05). RGal drives the expression of neutrophil regulatory genes in intestinal epithelial cells. Thus, RGal may contribute a pro-resolution inflammatory milieu by facilitating neutrophil-epithelial interactions. Natural Sciences and Engineering Research Council of Canada (NSERC); The American Physiological Society (APS)

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 score0.005

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)0.0010.001

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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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 routes2
Has abstractyes

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