The dietary fibre rhamnogalacturonan improves intestinal epithelial barrier function in a microbiota‐independent manner
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Dietary fibre comprises a complex group of polysaccharides that are indigestible but are fermented by gut microbiota, promoting beneficial effects to the intestinal mucosa indirectly through the production of short chain fatty acids. We found that a polysaccharide, rhamnogalacturonan (RGal), from the plant Acmella oleracea, has direct effects on intestinal epithelial barrier function. Our objective was to determine the mechanism whereby RGal enhances epithelial barrier function. EXPERIMENTAL APPROACH: Monolayers of colonic epithelial cell lines (Caco-2, T84) and of human primary cells from organoids were mounted in Ussing chambers to assess barrier function. The cellular mechanism of RGal effects on barrier function was determined using inhibitors of TLR-4 and PKC isoforms. KEY RESULTS: ) significantly enhanced barrier function as shown by increased transepithelial electrical resistance (TER) and reduced fluorescein isothiocyanate (FITC)-dextran flux in Caco-2, T84 and human primary cell monolayers, and accelerated tight junction reassembly in Caco-2 cells in a calcium switch assay. RGal also reversed the barrier-damaging effects of inflammatory cytokines on FITC-dextran flux and preserved the tight junction distribution of occludin. RGal activated TLR4 in TLR4-expressing HEK reporter cells, an effect that was inhibited by the TLR4 inhibitor, C34. The effect of RGal was also dependent on PKC, specifically the isoforms PKCδ and PKCζ. CONCLUSION AND IMPLICATIONS: RGal enhances intestinal epithelial barrier function through activation of TLR4 and PKC signalling pathways. Elucidation of RGal mechanisms of action could lead to new, dietary approaches to enhance mucosal healing in inflammatory bowel diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".