Rapid detection of <i>Cronobacter sakazakii</i> by real-time PCR based on the <i>cgcA</i> gene and TaqMan probe with internal amplification control
Bibliographic record
Abstract
Cronobacter sakazakii is a severe virulent strain that is frequently detected in powdered infant formula (PIF). Therefore, it is necessary to develop a fast and specific detection method. The specificity of our newly developed quantitative real-time PCR (qRT-PCR) was validated with DNA from 46 strains. Among them, 12 C. sakazakii strains were correctly amplified, whereas no positive florescent signal was observed from 34 nontarget controls. The detection limit of C. sakazakii was about 110 CFU/mL in broth and 1100 CFU/g in PIF. After enrichment in buffered peptone water for 6 h, our developed qRT-PCR assay could reliably detect C. sakazakii when the inoculation level was as low as 2 CFU/25 g (0.08 CFU/g) in PIF. The growth of C. sakazakii could be inhibited by the presence of Lactobacillus pentosus and Bacillus cereus, which used a longer enrichment period before the isolation was accomplished. However, at 5 and 50 CFU/25 g inoculation levels of C. sakazakii in the presence of 4 × 10(6) CFU L. pentosus/25 g or of 2 × 10(4) CFU B. cereus/25 g, the qRT-PCR assay could detect the presence of Cronobacter even though these artificially spiked samples were negative in culture. Therefore, our results indicated that the qRT-PCR assay could detect samples containing inhibitors and could avoid false negatives by using an internal amplification control.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".