Molecular profile and epidemiological traits of Streptococcus suis isolated from diseased pigs in western Canada reveal multiple-serotype infection: Implications for disease control
Bibliographic record
Abstract
Objective Streptococcus suis is a major agent of disease in modern swine operations, linked to increased mortality, treatment costs, and secondary infections. Although it is ubiquitous in swine, only a fraction of pigs develop clinical disease. The goals of this study were to profile isolates obtained from diseased pigs in western Canada and to investigate potential associations with disease severity. Procedure Isolates of S. suis (n = 128) from 75 diagnostic submission and 63 premises were paired with epidemiological surveys completed by submitting practitioners (n = 22). Whole-genome sequencing was used to type isolates. Results The most prevalent serotypes identified were 1/2 (7.8%, 10/128), 2 (9.3%, 12/128), 3 (9.3%, 12/128), and 7 (7.8%, 10/128); and sequence types 28 (17%, 23/128) and 839 (14%, 19/128). There was no association between serotype or sequence type and organ source or barn location. Approximately 74% (14/19) of the premises had diseased animals colonized by . 1 S. suis serotype, but only 1 pig was simultaneously infected with multiple serotypes and sequence types. Serotype distribution from diseased pigs in western Canada differed from that of those in other geographic regions. Conclusion Infection of diseased pigs by multiple serotypes should be considered when disease control strategies are implemented. No association between S. suis type and isolation organ was identified.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".