Multiplex PCR Assay for Typing of Staphylococcal Cassette Chromosome Mec Types I to V in Methicillin-resistant <em>Staphylococcus aureus</em>
Bibliographic record
Abstract
Staphylococcal Cassette Chromosome mec (SCCmec) typing is a very important molecular tool for understanding the epidemiology and clonal strain relatedness of methicillin-resistant Staphylococcus aureus (MRSA), particularly with the emerging outbreaks of community-associated MRSA (CA-MRSA) occurring on a worldwide basis. Traditional PCR typing schemes classify SCCmec by targeting and identifying the individual mec and ccr gene complex types, but require the use of many primer sets and multiple individual PCR experiments. We designed and published a simple multiplex PCR assay for quick-screening of major SCCmec types and subtypes I to V, and later updated it as new sequence information became available. This simple assay targets individual SCCmec types in a single reaction, is easy to interpret and has been extensively used worldwide. However, due to the sophisticated nature of the assay and the large number of primers present in the reaction, there is the potential for difficulties while adapting this assay to individual laboratories. To facilitate the process of establishing a MRSA SCCmec assay, here we demonstrate how to set up our multiplex PCR assay, and discuss some of the vital steps and procedural nuances that make it successful.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".