Potential pitfalls in the quantitative molecular detection of<i>Escherichia coli</i>O157:H7 in environmental matrices
Bibliographic record
Abstract
The detection sensitivity and potential interference factors of a commonly used assay based on real-time polymerase chain reaction (PCR) for Escherichia coli O157:H7 using eae gene-specific primers were assessed. Animal wastes and soil samples were spiked with known replicate quantities of a nontoxigenic strain of E. coli O157:H7 in a viable or dead state and as unprotected DNA. The detection sensitivity and accuracy of real-time PCR for E. coli O157:H7 in animal wastes and soil is low compared to enrichment culturing. Nonviable cells and unprotected DNA were shown to produce positive results in several of the environmental samples tested, leading to potential overestimates of cell numbers due to prolonged detection of nonviable cells. This demonstrates the necessity for the specific calibration of real-time PCR assays in environmental samples. The accuracy of the eae gene-based detection method was further evaluated over time in a soil system against an activity measurement, using the bioluminescent properties of an E. coli O157:H7 Tn5luxCDABE construct. The detection of significant numbers of viable but nonculturable (VBNC) as well as nonviable and possibly physically protected cells as shown over a period of 90 days further complicates the use of real-time PCR assays for quick diagnostics in environmental samples and infers that enrichment culturing is still required for the final verification of samples found positive by real-time PCR methods.
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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 | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".