Development of a PCR assay for rapid detection of<i>Cronobacter</i>spp. from food
Bibliographic record
Abstract
The occurrence of outbreaks of necrotizing meningitis caused by Cronobacter spp. in neonates highlights the need for rapid detection and accurate identification of this pathogenic species. The gold standard for isolation and identification of Cronobacter spp. from powdered infant formula is time consuming and labor intensive. The gyrB gene that encodes the B subunit of DNA gyrase (topoisomerase type II) was found to be suitable for the identification of Cronobacter spp. A region of the gyrB gene of 38 Cronobacter spp. strains and 5 Enterobacter spp. strains was amplified and sequenced, and a pair of primers was designed and synthesized based on the sequence of the gyrB gene. A polymerase chain reaction (PCR) system was developed and optimized to detect Cronobacter spp. The PCR assay amplified a 438 bp DNA product from all 38 Cronobacter spp. strains tested but not from 34 other bacteria. The detection limit was 1.41 pg/PCR (equivalent 282 genomic copies) when the genomic DNA of Cronobacter sakazakii ATCC 29544 was 10-fold diluted. Infant formula powders from 3 different commercial brands were inoculated with strains ATCC 29544 at a level of 56 colony-forming units, and the target fragment were produced after samples were enriched for 6 h at 37 °C. Twenty-five food samples were evaluated by the PCR assay and the conventional method. A PCR product of the expected size was obtained from 3 samples; however, Cronobacter spp. strains were isolated from only 2 samples by the conventional method. This method is a useful tool for rapid identification of Cronobacter spp. in food and potentially environmental samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".