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Record W2142458040 · doi:10.1139/cjm-2015-0166

Creating a customized intracellular niche: subversion of host cell signaling by <i>Legionella</i> type IV secretion system effectors

2015· article· en· W2142458040 on OpenAlexvenueno aff
Ernest C. So, Corinna Mattheis, Edward W. Tate, Gad Frankel, Gunnar N. Schroeder

Bibliographic record

VenueCanadian Journal of Microbiology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilMedical Research CouncilDeutscher Akademischer AustauschdienstImperial College LondonWellcome Trust
KeywordsEffectorLegionella pneumophilaBiologySecretionLegionellaCell biologyVacuoleIntracellular parasiteIntracellularMicrobiologyGeneticsBacteriaCytoplasmBiochemistry

Abstract

fetched live from OpenAlex

The Gram-negative facultative intracellular pathogen Legionella pneumophila infects a wide range of different protozoa in the environment and also human alveolar macrophages upon inhalation of contaminated aerosols. Inside its hosts, it creates a defined and unique compartment, termed the Legionella-containing vacuole (LCV), for survival and replication. To establish the LCV, L. pneumophila uses its Dot/Icm type IV secretion system (T4SS) to translocate more than 300 effector proteins into the host cell. Although it has become apparent in the past years that these effectors subvert a multitude of cellular processes and allow Legionella to take control of host cell vesicle trafficking, transcription, and translation, the exact function of the vast majority of effectors still remains unknown. This is partly due to high functional redundancy among the effectors, which renders conventional genetic approaches to elucidate their role ineffective. Here, we review the current knowledge about Legionella T4SS effectors, highlight open questions, and discuss new methods that promise to facilitate the characterization of T4SS effector functions in the future.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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 teacher head, 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

Citations39
Published2015
Admission routes1
Has abstractyes

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