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Record W2081950579 · doi:10.3791/50779

Multiplex PCR Assay for Typing of Staphylococcal Cassette Chromosome Mec Types I to V in Methicillin-resistant <em>Staphylococcus aureus</em>

2013· article· en· W2081950579 on OpenAlexafffund
Jo‐Ann McClure, John Conly, Kunyan Zhang

Bibliographic record

VenueJournal of Visualized Experiments · 2013
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsCalgary Laboratory ServicesUniversity of CalgaryAlberta Health Services
FundersCalgary Laboratory ServicesAlberta Health Services
KeywordsSCCmecTypingMultiplexStaphylococcus aureusBiologyMultiplex polymerase chain reactionMethicillin-resistant Staphylococcus aureusMicrobiologyStaphylococcal infectionsPrimer (cosmetics)Computational biologyPolymerase chain reactionGeneticsVirologyGeneBacteriaChemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.381
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2013
Admission routes2
Has abstractyes

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