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Record W2133676159 · doi:10.1073/pnas.1014125108

<scp>l</scp> -Fucose utilization provides <i>Campylobacter jejuni</i> with a competitive advantage

2011· article· en· W2133676159 on OpenAlexaff
Martin Ståhl, Lorna M. Friis, Harald Nothaft, Xin Liu, Jianjun Li, Christine M. Szymanski, Alain Stintzi

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsInstitute for Biological SciencesAlberta Glycomics CentreUniversity of AlbertaUniversity of Ottawa
Fundersnot available
KeywordsFucoseCampylobacter jejuniMucinVirulenceMicrobiologyBiologyMutantPathogenFucosylationColonizationGlycoproteinBacteriaBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

Campylobacter jejuni is a prevalent gastrointestinal pathogen in humans and a common commensal of poultry. When colonizing its hosts, C. jejuni comes into contact with intestinal carbohydrates, including L-fucose, released from mucin glycoproteins. Several strains of C. jejuni possess a genomic island (cj0480c-cj0490) that is up-regulated in the presence of both L-fucose and mucin and allows for the utilization of L-fucose as a substrate for growth. Strains possessing this genomic island show increased growth in the presence of L-fucose and mutation of cj0481, cj0486, and cj0487 results in the loss of the ability to grow on this substrate. Furthermore, mutants in the putative fucose permease (cj0486) are deficient in fucose uptake and demonstrate a competitive disadvantage when colonizing the piglet model of human disease, which is not paralleled in the colonization of poultry. This identifies a previously unrecorded metabolic pathway in select strains of C. jejuni associated with a virulent lifestyle.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

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 communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.080
GPT teacher head0.274
Teacher spread0.194 · 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 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

Citations218
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicSalmonella and Campylobacter epidemiologyFrench-language works237,207