Ganglioside Alters Phospholipase Trafficking, Inhibits NF-κB Assembly, and Protects Tight Junction Integrity
Bibliographic record
Abstract
Background and Aims: Dietary gangliosides are present in human milk and consumed in low amounts from organ meats. Clinical and animal studies indicate that dietary gangliosides attenuate signaling processes that are a hallmark of inflammatory bowel disease (IBD). Gangliosides decrease pro-inflammatory markers, improve intestinal permeability, and reduce symptoms characteristic in patients with IBD. The objective of this study was to examine mechanisms by which dietary gangliosides exert beneficial effects on intestinal health. Methods: Studies were conducted in vitro using CaCo-2 intestinal epithelial cells. Gangliosides were extracted from milk powder and incubated with differentiated CaCo-2 cells after exposure to pro-inflammatory stimuli. Gut barrier integrity was assessed by electron microscopy, epithelial barrier function was examined by measuring transepithelial electric resistance, and content of HBD-2, IL-23, NF-κB, and sPLA2 was assessed by ELISA. Results: Ganglioside attenuated the decrease in integrity of tight junctions induced by pro-inflammatory stimuli and improved epithelial barrier function (P < 0.05). Ganglioside decreased the basolateral secretion of sPLA2 (P ≤ 0.05), lowered HBD-2 and IL-23 levels (P ≤ 0.05), and inhibited NF-κB activation (P ≤ 0.05). Conclusions: In summary, the present study indicates that ganglioside GD3 improves intestinal integrity by altering sPLA2 trafficking, and the production of pro-inflammatory mediators is mitigated by decreasing assembly of the NF-κB complex. Dietary gangliosides may have promising potential beneficial effects in IBD as decreased inflammatory signaling, improved intestinal integrity, and maintenance of epithelial barrier function have been demonstrated in vitro.
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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".