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Record W4405543169 · doi:10.1002/cm.21974

Overexpressed Palladin Rescues Enteropathogenic <i>E. coli</i> (<scp>EPEC</scp>) Pedestal Lengths in <scp>ArpC2</scp> Depleted Cells

2024· article· en· W4405543169 on OpenAlexafffund
Kaitlin M. Bruzzini, Sabine Mann, Julian A. Guttman

Bibliographic record

VenueCytoskeleton · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyCell biologyEnteropathogenic Escherichia coliActinEscherichia coliBiochemistry

Abstract

fetched live from OpenAlex

ABSTRACT Enteropathogenic Escherichia coli (EPEC) causes diarrheal disease. Once ingested, these extracellular pathogens attach to the intestinal epithelial cells of their host, collapse the localized microvilli, and generate actin‐rich structures within the host cells that are located beneath the attached bacteria, called “pedestals.” Palladin is an actin‐associated protein that cross‐links and stabilizes actin filaments. This protein also acts as a scaffolding protein for other actin‐binding proteins. Here, we examine the role of Palladin during EPEC infections and show that Palladin is co‐opted by EPEC. Depletion of Palladin resulted in shorter pedestals, and when Palladin containing mutations in either its actin‐ or VASP‐binding domains were overexpressed in cells, pedestals decreased in length. Importantly, we show that the overexpression of Palladin in ArpC2 −/− (Arp2/3 complex–depleted) cells rescued pedestal length. Together, our results demonstrate that Palladin has the ability to rescue pedestal length during EPEC infections when the function of the Arp2/3 complex is diminished.

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.257
Teacher spread0.248 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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