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Record W2743039709 · doi:10.1073/pnas.1700858114

Nasopharyngeal infection by <i>Streptococcus pyogenes</i> requires superantigen-responsive Vβ-specific T cells

2017· article· en· W2743039709 on OpenAlexafffund
Joseph J. Zeppa, Katherine J. Kasper, Ivor Mohorovic, Delfina M. Mazzuca, S. M. Mansour Haeryfar, John K. McCormick

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsLawson Health Research InstituteWestern University
FundersCanadian Institutes of Health ResearchWestern UniversityGovernment of CanadaUniversity of TorontoMcMaster University
KeywordsSuperantigenStreptococcus pyogenesMicrobiologyStreptococcusMedicineBiologyImmunologyStaphylococcus aureusT cellBacteriaImmune systemGenetics

Abstract

fetched live from OpenAlex

Significance Superantigen toxins were defined over 25 years ago for their ability to activate T cells in a T-cell receptor β-chain variable domain-dependent manner. This “Vβ-specific” T-cell activation is the hallmark feature of the superantigen, and although these toxins can mediate dangerous human disease such as toxic shock syndrome, mechanisms that explain why bacteria produce superantigens have remained enigmatic. Herein, we provide evidence that Streptococcus pyogenes utilizes superantigens to target functional, Vβ-specific T cells to promote a state of colonization providing a mechanism that helps explain why bacteria produce toxins that specifically activate T cells of the adaptive immune system. This work also implicates the superantigen exotoxins as potential vaccine candidates against this globally important, human-specific pathogen.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.001

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 head0.060
GPT teacher head0.346
Teacher spread0.286 · 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

Citations71
Published2017
Admission routes2
Has abstractyes

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