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Record W2106534186 · doi:10.1093/infdis/jiu239

The LacdiNAc-Specific Adhesin LabA Mediates Adhesion of Helicobacter pylori to Human Gastric Mucosa

2014· article· en· W2106534186 on OpenAlexaff
Yannick Rossez, Philippe Gosset, Ivo G. Boneca, Ana Magalhães, Chantal Ecobichon, Celso A. Reis, Caroline Cieniewski‐Bernard, Marie Joncquel-Chevalier Curt, Renaud Léonard, Emmanuel Maes, Christian Slomianny, Philippe Sansonetti, Jean‐Claude Michalski, Catherine Robbe‐Masselot

Bibliographic record

VenueThe Journal of Infectious Diseases · 2014
Typearticle
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsCanadian Nautical Research Society
FundersCentre National de la Recherche ScientifiqueJames Hutton Institute
KeywordsBacterial adhesinHelicobacter pyloriMucinGastric mucosaMicrobiologyBiologyImmunologyStomachGeneGeneticsVirulenceBiochemistry

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.258
Teacher spread0.245 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations97
Published2014
Admission routes1
Has abstractyes

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