A Case-Control Study to Investigate the Serotypes of S. suis Isolates by Multiplex PCR in Nursery Pigs in Ontario, Canada
Bibliographic record
Abstract
Streptococcus suis naturally inhabits the tonsils and nasal cavities of pigs. Some strains can cause systemic infection, leading to a wide range of diseases. A case-control study was conducted to (i) examine serotypes isolated from systemic sites (blood/meninges/spleen) in cases, (ii) determine whether serotypes in systemic sites were found in upper respiratory sites (tonsil/nasal cavity) of the same cases, and (iii) determine the serotypes in upper respiratory sites of case and farm and pen- matched controls. In total, 606 samples from 128 pigs were cultured for S. suis. The isolates were examined for presence of gdh and recN genes by polymerase chain reaction (PCR) and were identified as S. suis if both genes were present. The S. suis isolates were then serotyped using a two step-multiplex PCR. Serotypes 9 (n = 9), (2,1/2) (n = 7) and untypable isolates (n = 7) were most commonly found in systemic sites. Detection of serotypes 9 (p = 0.03) in upper respiratory sites were positively associated with their detection in systemic sites of cases, while a trend was seen with serotype (2,1/2) (p = 0.07). Last, no association between serotypes recovered from upper respiratory sites of cases and controls could be detected. Untypable isolates were detected in high frequency, which warrants further investigation. This study confirms that a variety of serotypes can be found in commercial swine production and shows a difference in serotypes recovered from systemic sites in pigs with clinical signs of S. suis infections.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".