Detection of Streptococcus suis in Bioaerosols of Swine Confinement Buildings
Bibliographic record
Abstract
Streptococcus suis is an important swine pathogen that can cause septicemia, meningitis, and pneumonia. Also recognized as an emerging zoonotic agent, it is responsible for outbreaks of human infections in Asian countries. Serotype 2 is the predominant isolate from diseased animals and humans. The aerosolization of S. suis in the air of swine confinement buildings (SCB) was studied. The presence of S. suis in bioaerosols was monitored in SCB where cases of infection had been reported and in healthy SCB without reported infections. Using a quantitative-PCR (qPCR) method, we determined the total number of bacteria (1 × 10(8) to 2 × 10(8) airborne/m(3)), total number of S. suis bacteria (4 × 10(5) to 10 × 10(5) airborne/m(3)), and number of S. suis serotype 2 and 1/2 bacteria (1 × 10(3) to 30 × 10(3) airborne/m(3)) present in the air. S. suis serotypes 2 and 1/2 were detected in the air of all growing/finishing SCB that had documented cases of S. suis infection and in 50% of healthy SCB. The total number of bacteria and total numbers of S. suis and S. suis serotype 2 and 1/2 bacteria were monitored in one positive SCB during a 5-week period, and it was shown that the aerosolized S. suis serotypes 2 and 1/2 remain airborne for a prolonged period. When the effect of aerosolization on S. suis was observed, the percentage of intact S. suis bacteria (showing cell membrane integrity) in the air might have been up to 13%. Finally S. suis was found in nasal swabs from 14 out of 21 healthy finishing-SCB workers, suggesting significant exposure to the pathogen. This report provides a better understanding of the aerosolization, prevalence, and persistence of S. suis in SCB.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".