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Streptococcus suis outbreak investigation using multiple-locus variable tandem repeat number analysis

2010· article· en· W2079758538 on OpenAlexaff
Wei Li, Changyun Ye, Huaiqi Jing, Zhigang Cui, Xuemei Bai, Dong Jin, Han Zheng, Ailan Zhao, Yanmei Xu, Marcelo Gottschalk, Jianguo Xu

Bibliographic record

VenueMicrobiology and Immunology · 2010
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMultiple Loci VNTR AnalysisBiologyOutbreakTypingSerotypePulsed-field gel electrophoresisStreptococcus suisVariable number tandem repeatVirologyMicrobiologyGeneticsVirulenceGenotypeGene

Abstract

fetched live from OpenAlex

Two outbreaks of Streptococcus suis ST7 occurred in humans in 1998 and 2005 in China. PFGE of chromosome restriction fragments found all ST7 isolates to be indistinguishable. Due to the genetic homogeneity of ST7 isolates, development of a rapid sub-typing method with high discriminatory power for ST7 isolates is required. In this study, a novel method, MLVA, was developed to type S. suis serotype 2 strains. Further, this method was used to analyze outbreak-associated ST7 strains in China. A total of 144 ST7 S. suis isolates were sub-typed into 34 MLVA types. Among these, eight isolates from the 1998 outbreak were sub-typed into five MLVA types, of which four MLVA types were also detected in Sichuan in 2005. These data indicate that the pathogens responsible for the two outbreaks had the same origin. In addition, some observations also provided molecular evidence for the transmission route, possibly indicating that the MLVA method has usefulness in epidemiology. The developed MLVA scheme for S. suis has greater discriminative power than PFGE. The method described here may be useful for identifying the source of S. suis infection and monitoring its spread.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.266
Teacher spread0.253 · 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 designObservational
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

Citations17
Published2010
Admission routes1
Has abstractyes

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