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Record W2472770357 · doi:10.3390/pathogens5030047

Recruitment of Factor H to the Streptococcus suis Cell Surface is Multifactorial

2016· article· en· W2472770357 on OpenAlexafffund
David Roy, Daniel Grenier, Mariela Segura, Annabelle Mathieu‐Denoncourt, Marcelo Gottschalk

Bibliographic record

VenuePathogens · 2016
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsUniversité LavalUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStreptococcus suisMicrobiologyVirulence factorFactor HSialic acidBiologyMutantPathogenComplement factor BComplement systemCellAlternative complement pathwayStrain (injury)ImmunologyVirulenceGeneBiochemistryAntibody

Abstract

fetched live from OpenAlex

Streptococcus suis is an important bacterial swine pathogen and a zoonotic agent. Recently, two surface proteins of S. suis, Fhb and Fhbp, have been described for their capacity to bind factor H-a soluble complement regulatory protein that protects host cells from complement-mediated damages. Results obtained in this study showed an important role of host factor H in the adhesion of S. suis to epithelial and endothelial cells. Both Fhb and Fhbp play, to a certain extent, a role in such increased factor H-dependent adhesion. The capsular polysaccharide (CPS) of S. suis, independently of the presence of its sialic acid moiety, was also shown to be involved in the recruitment of factor H. However, a triple mutant lacking Fhb, Fhbp and CPS was still able to recruit factor H resulting in the degradation of C3b in the presence of factor I. In the presence of complement factors, the double mutant lacking Fhb and Fhbp was similarly phagocytosed by human macrophages and killed by pig blood when compared to the wild-type strain. In conclusion, this study suggests that recruitment of factor H to the S. suis cell surface is multifactorial and redundant.

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 score0.003

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.076
GPT teacher head0.331
Teacher spread0.255 · 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

Citations30
Published2016
Admission routes2
Has abstractyes

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