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Record W2143398242 · doi:10.1128/cmr.00013-07

Type III Secretion Systems and Disease

2007· review· en· W2143398242 on OpenAlexafffund
Bryan Coburn, Inna Sekirov, B. Brett Finlay

Bibliographic record

VenueClinical Microbiology Reviews · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersCanadian Institutes of Health ResearchUniversity of British ColumbiaNational Institutes of HealthMichael Smith Health Research BCHoward Hughes Medical InstituteFoundation for the National Institutes of Health
KeywordsEffectorSecretionVirulenceBiologyCell biologyCytoplasmType three secretion systemImmune systemMicrobiologyImmunologyGeneticsGeneBiochemistry

Abstract

fetched live from OpenAlex

Type III secretion systems (T3SSs) are complex bacterial structures that provide gram-negative pathogens with a unique virulence mechanism enabling them to inject bacterial effector proteins directly into the host cell cytoplasm, bypassing the extracellular milieu. Although the effector proteins vary among different T3SS pathogens, common pathogenic mechanisms emerge, including interference with the host cell cytoskeleton to promote attachment and invasion, interference with cellular trafficking processes, cytotoxicity and barrier dysfunction, and immune system subversion. The activity of the T3SSs correlates closely with infection progression and outcome, both in animal models and in human infection. Therefore, to facilitate patient care and improve outcomes, it is important to understand the T3SS-mediated virulence processes and to target T3SSs in therapeutic and prophylactic development efforts.

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)0.001
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.005

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 head0.155
GPT teacher head0.467
Teacher spread0.312 · 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

Citations643
Published2007
Admission routes2
Has abstractyes

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