Development of a mismatch amplification mutation assay to correctly serotype isolates of <i>Streptococcus suis</i> serotypes 1, 2, 1/2, and 14
Bibliographic record
Abstract
Streptococcus suis is one of the most important bacterial swine pathogens worldwide and is an emerging pathogen in humans. There are 29 serotypes, and serotyping, which is based on the antigenicity of the capsular polysaccharide (CPS) or on its coding genes, is often part of routine identification and provides further information regarding S. suis virulence and zoonotic potential. Serotypes 2 and 14 possess high zoonotic potential, and serotype 1/2 is the serotype most frequently isolated from diseased pigs in North America. PCR has replaced antibody-based techniques to perform serotyping. However, traditional PCR is not able to differentiate serotype 2 from 1/2 and serotype 1 from 14, given that the only difference in the cps loci of those serotype pairs is a nonsynonymous single-nucleotide polymorphism. We developed a mismatch amplification mutation assay (MAMA)-PCR that was able to correctly serotype 148 isolates previously known to be serotypes 1, 2, 1/2, or 14. This technique will be highly useful in animal and human health laboratories performing PCR serotyping of S. suis isolates.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".