Impact of serotype and sequence type on the preferential aerosolization of Streptococcus suis
Bibliographic record
Abstract
BACKGROUND: Streptococcus suis is a swine pathogen that causes pneumonia, septicemia and meningitis. It is also an important zoonotic agent responsible of several outbreaks in China. S. suis strains are classified into 35 serotypes based on the composition of their polysaccharide capsule. S. suis serotype 2 causes the majority of severe infections in pigs and in human, and can be further subdivided into sequence types (STs) based on multilocus sequence typing. The ST1 is associated with highly virulent strains. In North America, the strains most commonly isolated belong to ST25 and ST28, which are respectively moderately and weakly virulent in a mouse model. The presence of S. suis bioaerosols in the air of swine confinement buildings has been previously demonstrated. The aim of this study was to better understand the aerosolization behaviour of S. suis by investigating the preferential aerosolization of various strains of S. suis, belonging to different serotypes or STs, using in-house developed environmental chamber and bubble-burst nebulizer. qPCR technology was used to analyze the ratio of S. suis strains. RESULTS: The results suggest that the highly virulent serotype 2 ST1 strains are preferentially aerosolized and that the S. suis preferential aerosolization is a strain-dependent process. CONCLUSION: These observations will need to be confirmed using a larger number of strains. This study is a proof of concept and increases our knowledge on the potential aerosol transmission of S. suis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".