Evaluation of pathotype marker genes in Streptococcus suis isolated from human and clinically healthy swine in Thailand
Bibliographic record
Abstract
BACKGROUND: Streptococcus suis is a zoonotic pathogen that causes substantial economic losses in the pig industry and contributes to human infections worldwide, especially in Southeast Asia. Recently, a multiplex polymerase chain reaction (PCR) process was developed to distinguish disease-associated and non-disease-associated pathotypes of S. suis European strains. Herein, we evaluated the ability of this multiplex PCR approach to distinguish pathotypes of S. suis in Thailand. RESULTS: This study was conducted on 278 human S. suis isolates and 173 clinically healthy pig S. suis isolates. PCR identified 99.3% of disease-associated strains in the human isolates and 11.6% of non-disease-associated strains in the clinically healthy pig isolates. Of the clinically healthy pig S. suis isolates, 71.1% were classified as disease-associated. We also detected undetermined pathotype forms in humans (0.7%) and pigs (17.3%). The PCR assay classified the disease-associated isolates into four types. Statistical analysis revealed that human S. suis clonal complex (CC) 1 isolates were significantly associated with the disease-associated type I, whereas CC104 and CC25 were significantly associated with the disease-associated type IV. CONCLUSION: Multiplex PCR cannot differentiate non-disease-associated from disease-associated isolates in Thai clinically healthy pig S. suis strains, although the method works well for human S. suis strains. This assay should be applied to pig S. suis strains with caution. It is highly important that multiplex PCR be validated using more diverse S. suis strains from different geographic areas and origins of isolation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".