Modification of Ganglioside Content of Human Gastric Epithelial Cell Membrane Decreases <i>Helicobacter pylori</i> Adhesion
Bibliographic record
Abstract
BACKGROUND: In polarized cells, ganglioside location determines ganglioside function. Diet alters ganglioside content and composition in cell membranes. Ganglioside acts as a receptor for Helicobacter pylori. H pylori infects the stomach epithelium and may cause peptic ulcer disease and gastric cancer. The present study used purified gangliosides to modify the ganglioside composition of human gastric epithelial cells in vitro to reduce H pylori adhesion. METHODS: A human gastric epithelial cell line (NCI-N87) was cultured with a ganglioside mix or with pure ganglioside (GM3 or GD3) at different concentrations (0-30 μg/mL) and ganglioside membrane content of gastric cells was determined after 48 hours. LC/triple quadrupole MS was used to analyse ganglioside concentration. H pylori was inoculated into the culture media of gastric cells previously treated with gangliosides GM3 or GD3 or a combination of GM3 and GD3. RESULTS: GD3 and GM3 content increased in the plasma membrane in a dose-dependent manner. Gastric cells treated with GD3 showed more GM3 content than GD3 (P < 0.01). Ganglioside content was modified in the apical membrane, but GM3 and GD3 were also found in the basolateral membrane after treatments. Gastric cells treated with GM3, GD3 or the combination of GM3:GD3 decreased H pylori adhesion to gastric cells at all ganglioside concentrations tested by 80% compared with untreated gastric cells (P < 0.05). CONCLUSIONS: These observations suggest that GD3 and GM3 present in the stomach lumen may be taken up into the apical gastric membrane and decrease H pylori adhesion to the epithelium.
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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".