Evaluation of Fluorescence-Based Amplified Fragment Length Polymorphism Analysis for Molecular Typing in Hospital Epidemiology: Comparison with Pulsed-Field Gel Electrophoresis for Typing Strains of Vancomycin-Resistant <i>Enterococcus faecium</i>
Bibliographic record
Abstract
Fluorescence-based amplified fragment length polymorphism (fbAFLP) is a novel assay based on the fluorescent analysis of an amplified subset of restriction fragments. The fbAFLP assay involves the selective PCR amplification of restriction fragments from a total digest of genomic DNA. The ligation of adapters with primer-specific sites coupled with primers containing selective nucleotides allowed the full potential of PCR to be realized while maintaining the advantages of restriction endonuclease analysis. Fluorescence-based fragment analysis with polyacrylamide gel electrophoresis provides the accurate band sizing required for homology assessment. The large number of phylogenetically informative characters obtained by fbAFLP is well suited for cluster analysis and database development. The method demonstrated excellent reproducibility and ease of performance and interpretation. We typed 30 epidemiologically well-characterized isolates of vancomycin-resistant enterococci from an outbreak in a university hospital by fbAFLP. Clustering of fbAFLP data matched epidemiological, microbiological, and pulsed-field gel electrophoresis data. This study demonstrates the unprecedented utility of fbAFLP for epidemiological investigation. Future developments in standardization and automation will set fbAFLP as the "gold standard" for molecular typing in epidemiology.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".