MétaCan
Menu
Back to cohort
Record W2989563961 · doi:10.3390/microorganisms7120594

Serine Protease Autotransporters of the Enterobacteriaceae (SPATEs): Out and About and Chopping It Up

2019· review· en· W2989563961 on OpenAlexafffund
Pravil Pokharel, Hajer Habouria, Hicham Bessaiah, Charles M. Dozois

Bibliographic record

VenueMicroorganisms · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsInstitut National de la Recherche ScientifiqueCegep de Saint Hyacinthe
FundersNatural Sciences and Engineering Research Council of CanadaUniversidad Autónoma de Aguascalientes
KeywordsEnterobacteriaceaeBiologyMicrobiologyVirulenceProteasesSerine proteaseEscherichia coliSecretionBacteriaProteaseBiochemistryEnzymeGeneticsGene

Abstract

fetched live from OpenAlex

Autotransporters are secreted proteins with multiple functions produced by a variety of Gram-negative bacteria. In Enterobacteriaceae, a subgroup of these autotransporters are the SPATEs (serine protease autotransporters of Enterobacteriaceae). SPATEs play a crucial role in survival and virulence of pathogens such as Escherichia coli and Shigella spp. and contribute to intestinal and extra-intestinal infections. These high molecular weight proteases are transported to the external milieu by the type Va secretion system and function as proteases with diverse substrate specificities and biological functions including adherence and cytotoxicity. Herein, we provide an overview of SPATEs and discuss recent findings on the biological roles of these secreted proteins, including proteolysis of substrates, adherence to cells, modulation of the immune response, and virulence in host models. In closing, we highlight recent insights into the regulation of expression of SPATEs that could be exploited to understand fundamental SPATE biology.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.022
GPT teacher head0.278
Teacher spread0.256 · 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

Citations44
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueMicroorganismsSame topicAntibiotic Resistance in BacteriaFrench-language works237,207