Cloth-based hybridization array system for the detection of multiple antibiotic resistance genes in Salmonella enterica subsp. enterica serotype Typhimurium DT104
Bibliographic record
Abstract
AIMS: A simple DNA macroarray system was developed for detection of antibiotic resistance and other marker genes associated with the multidrug-resistant food pathogen Salmonella enterica subsp. enterica serotype Typhimurium DT104. METHODS AND RESULTS: A multiplex polymerase chain reaction (PCR) incorporating digoxigenin-dUTP was used to simultaneously amplify seven marker sequences, with subsequent rapid detection of the amplicons by hybridization with an array of probes immobilized on polyester cloth and immunoenzymatic assay of the bound label. This system provided sensitive detection of the different genetic markers in the S. Typhimurium DT104 genome, giving positive reactions with as few as 10 CFU, and the hybridizations were highly specific, with no reactions of amplicons with heterologous probes on the array. CONCLUSIONS: This cloth-based hybridization array system (CHAS) provides a simple, cost-effective tool for monitoring S. Typhimurium DT104 in foods and their production environment. SIGNIFICANCE AND IMPACT OF THE STUDY: The CHAS is a simple and cost-effective tool for the simultaneous detection of amplicons generated in a multiplex PCR, and the concept is broadly applicable to the detection and characterization of food pathogens.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".