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Record W2141692744 · doi:10.1093/infdis/jir386

Eps15 and Epsin1 Are Crucial for Enteropathogenic Escherichia coli Pedestal Formation Despite the Absence of Adaptor Protein 2

2011· article· en· W2141692744 on OpenAlexafffund
Ann E. Lin, Alexandre Benmerah, Julian A. Guttman

Bibliographic record

VenueThe Journal of Infectious Diseases · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsSimon Fraser University
FundersCanadian Institutes of Health Research
KeywordsEndocytic cycleClathrinInternalizationEnteropathogenic Escherichia coliSignal transducing adaptor proteinCell biologyBiologyEndocytosisMicrobiologyEscherichia coliSignal transductionBiochemistryCell

Abstract

fetched live from OpenAlex

Enteropathogenic Escherichia coli (EPEC) are primarily extracellular pathogens that generate actin-rich structures known as pedestals during their pathogenesis. Surprising evidence has demonstrated that despite maintaining an extracellular location, EPEC require the endocytic protein, clathrin, for pedestal formation. To evaluate the strategies EPEC use to usurp endocytic machinery, we investigated the roles of a number of clathrin-coated pits components, adaptor protein 2 (AP-2), Eps15 and epsin1, during EPEC infections. We demonstrated that in conjunction with clathrin, pedestal formation also required the recruitment of Eps15 and epsin1 but not AP-2. Because AP-2 orchestrates the recruitment of clathrin, Eps15, and epsin1, as well as other adaptors, during assembly of clathrin-coated pits at the plasma membrane, our findings reveal a novel internalization subversion strategy employed by EPEC. These results further emphasize the recent paradigm that endocytic proteins are important for EPEC-mediated disease.

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 score0.003

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 science0.0000.001
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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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

Citations19
Published2011
Admission routes2
Has abstractyes

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