MétaCan
Menu
Back to cohort
Record W2101378591 · doi:10.1172/jci15707

The crucial role of Campylobacter jejuni genes in anti-ganglioside antibody induction in Guillain-Barré syndrome

2004· article· en· W2101378591 on OpenAlexaff
Peggy C. R. Godschalk, Astrid P. Heikema, Michel Gilbert, Tomoko Komagamine, C. Wim Ang, Jobine Glerum, Denis Brochu, Jianjun Li, Nobuhiro Yuki, Bart C. Jacobs, Alex van Belkum, Hubert P. Endtz

Bibliographic record

VenueJournal of Clinical Investigation · 2004
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsInstitute for Biological Sciences
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsCampylobacter jejuniGuillain-Barre syndromeGeneAntibodyGangliosideMicrobiologyCampylobacterVirologyAntibody responseBiologyMedicineImmunologyGeneticsBacteria

Abstract

fetched live from OpenAlex

Molecular mimicry of Campylobacter jejuni lipo-oligosaccharides (LOS) with gangliosides in nervous tissue is considered to induce cross-reactive antibodies that lead to Guillain-Barre syndrome (GBS), an acute polyneuropathy. To determine whether specific bacterial genes are crucial for the biosynthesis of ganglioside-like structures and the induction of anti-ganglioside antibodies, we characterized the C. jejuni LOS biosynthesis gene locus in GBS-associated and control strains. We demonstrated that specific types of the LOS biosynthesis gene locus are associated with GBS and with the expression of ganglioside-mimicking structures. Campylobacter knockout mutants of 2 potential GBS marker genes, both involved in LOS sialylation, expressed truncated LOS structures without sialic acid, showed reduced reactivity with GBS patient serum, and failed to induce an anti-ganglioside antibody response in mice. We demonstrate, for the first time, to our knowledge, that specific bacterial genes are crucial for the induction of anti-ganglioside antibodies.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.036
GPT teacher head0.351
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations201
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical InvestigationSame topicPeripheral Neuropathies and DisordersFrench-language works237,207