The LacdiNAc-Specific Adhesin LabA Mediates Adhesion of Helicobacter pylori to Human Gastric Mucosa
Bibliographic record
Abstract
Adhesion of Helicobacter pylori to the gastric mucosa is a necessary prerequisite for the pathogenesis of H. pylori-related diseases. In this study, we investigated the GalNAcβ1-4GlcNAc motif (also known as N,N'-diacetyllactosediamine [lacdiNAc]) carried by MUC5AC gastric mucins as the target for bacterial binding to the human gastric mucosa. The expression of LacdiNAc carried by gastric mucins was correlated with H. pylori localization, and all strains tested adhered significantly to this motif. Proteomic analysis and mutant construction allowed the identification of a yet uncharacterized bacterial adhesin, LabA, which specifically recognizes lacdiNAc. These findings unravel a target of adhesion for H. pylori in addition to moieties recognized by the well-characterized adhesins BabA and SabA. Localization of the LabA target, restricted to the gastric mucosa, suggests a plausible explanation for the tissue tropism of these bacteria. These results pave the way for the development of alternative strategies against H. pylori infection, using adherence inhibitors.
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 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".