Real-time PCR and enzyme-linked fluorescent assay methods for detecting Shiga-toxin-producing<i>Escherichia coli</i>in mincemeat samples
Bibliographic record
Abstract
This work aimed to compare real-time polymerase chain reaction (PCR) with the commercially available enzyme-linked fluorescent assay (ELFA) VIDAS ECOLI O157 for detecting Escherichia coli O157 in mincemeat. In addition, a PCR-based survey on Shiga-toxin-producing E. coli (STEC) in mincemeat collected in Italy is presented. Real-time PCR assays targeting the stx genes and a specific STEC O157 sequence (SILO157, a small inserted locus of STEC O157) were tested for their sensitivity on spiked mincemeat samples. After overnight enrichment, the presence of STEC cells could be clearly determined in the 25 g samples containing 10 bacterial cells, while the addition of five bacteria provided equivocal PCR results with Ct values very close to or above the threshold of 40. The PCR tests proved to be more sensitive than the ELFA-VIDAS ECOLI O157, whose detection level started from 50 bacterial cells/25 g of mincemeat. The occurrence of STEC in 106 mincemeat (bovine, veal) samples collected from September to November 2004 at five different points of sale in Italy (one point of sale in Arezzo, Tuscany, central Italy, two in Mantova, Lombardy, Northern Italy, and two in Bologna, Emilia-Romagna, upper-central Italy) was less than 1%. Contamination by the main STEC O-serogroups representing a major public health concern, including O26, O91, O111, O145, and O157, was not detected. This survey indicates that STEC present in these samples are probably not associated with pathogenesis in humans.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".