Use of repetitive sequence-based polymerase chain reaction for molecular epidemiologic analysis of Streptococcus equi subspecies equi
Bibliographic record
Abstract
OBJECTIVE: To determine whether repetitive sequence-based polymerase chain reaction (rep-PCR) could be used to differentiate Streptococcus equi isolates, to examine S equi isolates from throughout the world, and to determine whether a horse had > 1 subtype of S equi during an outbreak of disease. SAMPLE POPULATION: An initial group of 32 S equi isolates, 63 S equi isolates from various geographic areas, and 17 S equi isolates obtained during outbreaks of disease. PROCEDURE: An aliquot of S equi genomic DNA was amplified, using enterobacterial repetitive intergenic consensus primers. Gel electrophoresis was performed on 1.5% agarose gels, and a computed-assisted program was used to compare rep-PCR results. RESULTS: Use of these primers to analyze 100 ng of S equi genomic DNA resulted in patterns of 6 to 14 bands. The 32 initial isolates were separated into 7 rep-PCR subtypes. There were 30 rep-PCR subtypes found among 29 S equi isolates obtained from Minnesota, Michigan, Canada, and Australia and 34 S equi isolates obtained from Kentucky and other sources. Furthermore, the same clone was identified in several horses during an outbreak of disease. Infected horses on the same farm all had a single clone of S equi. CONCLUSION AND CLINICAL RELEVANCE: Analysis of these results suggests that rep-PCR is useful for delineating S equi into rep-PCR subtypes. Results revealed that isolates with the same geographic source or similar date of collection did not always have the same rep-PCR subtype. A single clone of S equi usually predominated during an outbreak of disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".