CLOTH‐BASED HYBRIDIZATION ARRAY SYSTEM FOR DETECTION OF TOXIN GENES ASSOCIATED WITH MAJOR FOODBORNE PATHOGENIC BACTERIA
Bibliographic record
Abstract
ABSTRACT A simple cloth‐based hybridization array system (CHAS) was developed for the identification of toxin genes associated with major foodborne pathogenic bacteria, including toxigenic Escherichia coli, Vibrio cholerae and Salmonella spp. Bacterial isolates were subjected to a multiplex polymerase chain reaction incorporating digoxigenin (DIG)–deoxyuridine triphosphate and primers targeting a variety of toxin genes (verotoxin, Salmonella enterotoxin, cholera toxin and heat‐labile/stable enterotoxin), followed by hybridization of the amplicons with an array of probes immobilized on polyester cloth and subsequent immunoenzymatic assay of the bound DIG label. This system provided sensitive and specific detection of the different target toxin gene markers in a variety of bacterial isolates, exhibiting the expected patterns of reactivity with a panel of bacteria having defined toxigenicity profiles. The CHAS is a cost‐effective tool facilitating the determination of the potential toxigenic profile of bacteria in the food microbiology laboratory, thus contributing valuable information to the risk‐assessment process in the microbiological analysis of foods.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".