New Quadriplex PCR Assay for Detection of Methicillin and Mupirocin Resistance and Simultaneous Discrimination of<i>Staphylococcus aureus</i>from Coagulase-Negative Staphylococci
Why this work is in the frame
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Bibliographic record
Abstract
Major challenges in diagnostic molecular microbiology are to develop a simple assay to distinguish Staphylococcus aureus from the less virulent but clinically important coagulase-negative staphylococci (CoNS) and to simultaneously determine their antibiotic resistance profiles. Multiplex PCR assays have been developed for the detection of methicillin- and mupirocin-resistant S. aureus and CoNS but not for the simultaneous discrimination of S. aureus from CoNS. We designed a new set of Staphylococcus genus-specific primers and developed a novel quadriplex PCR assay targeting the 16S rRNA (Staphylococcus genus specific), nuc (S. aureus species specific), mecA (a determinant of methicillin resistance), and mupA (a determinant of mupirocin resistance) genes to identify most staphylococci, to discriminate S. aureus from CoNS and other bacteria, and to simultaneously detect methicillin and mupirocin resistance. Validation of the assay with 96 ATCC control strains and 323 previously characterized clinical isolates, including methicillin- and mupirocin-sensitive and -resistant S. aureus and CoNS isolates and other bacteria, demonstrated 100% sensitivity, specificity, and accuracy. This assay represents a simple, rapid, accurate, and reliable approach for the detection of methicillin- and mupirocin-resistant staphylococci and offers the hope of preventing their widespread dissemination through early and reliable detection.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it