Virulence Studies of Different Sequence Types and Geographical Origins of Streptococcus suis Serotype 2 in a Mouse Model of Infection
Bibliographic record
Abstract
Multilocus sequence typing previously identified three predominant sequence types (STs) of Streptococcus suis serotype 2: ST1 strains predominate in Eurasia while North American (NA) strains are generally ST25 and ST28. However, ST25/ST28 and ST1 strains have also been isolated in Asia and NA, respectively. Using a well-standardized mouse model of infection, the virulence of strains belonging to different STs and different geographical origins was evaluated. Results demonstrated that although a certain tendency may be observed, S. suis serotype 2 virulence is difficult to predict based on ST and geographical origin alone; strains belonging to the same ST presented important differences of virulence and did not always correlate with origin. The only exception appears to be NA ST28 strains, which were generally less virulent in both systemic and central nervous system (CNS) infection models. Persistent and high levels of bacteremia accompanied by elevated CNS inflammation are required to cause meningitis. Although widely used, in vitro tests such as phagocytosis and killing assays require further standardization in order to be used as predictive tests for evaluating virulence of strains. The use of strains other than archetypal strains has increased our knowledge and understanding of the S. suis serotype 2 population dynamics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".