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Record W2970189291 · doi:10.1111/cmi.13107

Here, there, and everywhere: How pathogenic<i>Escherichia coli</i>sense and respond to gastrointestinal biogeography

2019· review· en· W2970189291 on OpenAlexafffund
Sarah E. Woodward, Zakhar Krekhno, B. Brett Finlay

Bibliographic record

VenueCellular Microbiology · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsCanada's Michael Smith Genome Sciences CentreMichael Smith Health Research BCUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsCitrobacter rodentiumBiologyColonisationMicrobiologyEnteropathogenic Escherichia coliEffectorSecretionPathogenHost (biology)Gastrointestinal tractType three secretion systemCitrobacterEscherichia coliIntestinal epitheliumEnterobacteriaceaeVirulenceColonizationEpitheliumImmunologyEcologyGeneticsGene

Abstract

fetched live from OpenAlex

Gastrointestinal (GI) pathogens enteropathogenic and enterohaemorrhagic Escherichia coli (EPEC and EHEC), and related mouse pathogen Citrobacter rodentium, are referred to as attaching and effacing (AE) pathogens for the lesions they form upon colonisation of the host epithelium. EPEC, EHEC, and C. rodentium are well known to use a type III secretion system to intimately attach to intestinal cells and secrete bacterial effectors to manipulate host cell processes. Less well known is the ability of AE pathogens to overcome significant physiological and microbial barriers and target specific gut niches for initial colonisation of the host epithelium. This review considers recent work highlighting the biogeography of the GI tract as it applies to colonisation by enteric pathogens, including environmental barriers to enteric infection, signals sensed by AE pathogens for navigation of the GI tract, and the tools AE pathogens use to respond to the changing host environment.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.023
GPT teacher head0.272
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations35
Published2019
Admission routes2
Has abstractyes

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