MétaCan
Menu
Back to cohort
Record W2331796642 · doi:10.1128/ecosalplus.8.8.4

<i>Salmonella</i> and Enteropathogenic <i>Escherichia coli</i> Interactions with Host Cells: Signaling Pathways

2006· article· en· W2331796642 on OpenAlexaff
Danika L. Goosney, Sonya L. Kujat Choy, B. Brett Finlay

Bibliographic record

VenueEcoSal Plus · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsInimex Pharmaceuticals (Canada)University of British Columbia
Fundersnot available
KeywordsSalmonellaEnteropathogenic Escherichia coliBiologyMicrobiologySalmonella entericaPathogenEffectorVirulenceHost (biology)Signal transductionCell biologyBacteriaGeneGenetics

Abstract

fetched live from OpenAlex

The host-pathogen interaction involves a myriad of initiations and responses from both sides. Bacterial pathogens such as enteropathogenic Escherichia coli (EPEC) and Salmonella enterica have numerous virulence factors that interact with and alter signaling components of the host cell to initiate responses that are beneficial to pathogen survival and persistence. The study of Salmonella and EPEC infection reveals intricate connections between host signal transduction, cytoskeletal architecture, membrane trafficking, and cytokine gene expression. The emerging picture includes elements of molecular mimicry by bacterial effectors and bacterial subversion of typical host events, with the result that EPEC is able to survive and persist in an extracellular milieu, while Salmonella establishes an intracellular niche and is able to spread systemically throughout the host. This review focuses on recent advances in our understanding of the signaling events stemming from the host-pathogen interactions specific to Salmonella and EPEC.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueEcoSal PlusSame topicEscherichia coli research studiesFrench-language works237,207