Quantification of microcystin-producing cyanobacteria and E. coli in water by 5'-nuclease PCR
Bibliographic record
Abstract
AIMS: 5'-Nuclease (real-time, quantitative) PCR methodologies were developed and applied as diagnostic tools for the detection of microcystin-producing cyanobacteria and Escherichia coli in water. METHODS AND RESULTS: PCR was used to detect regions of the lacZ gene in E. coli, and the microcystin synthetase gene in microcystin-producing cyanobacteria. In environmental water samples, natural inhibitors to PCR were effectively removed with a prefiltration step and an EDTA wash. A lower detection limit of 10 cells ml(-1) was obtained with endpoint PCR detection. 5'-Nuclease PCR was used for microbial quantification of 1 ml inoculated water samples. We were able to detect down to three copies of our target genes per sample within about 2 h (post-DNA isolation) for both E. coli and microcystin-producing cyanobacteria. CONCLUSIONS: 5'-Nuclease PCR offers a rapid and sensitive method of bacterial quantification in water samples. SIGNIFICANCE AND IMPACT OF THE STUDY: 5'-Nuclease PCR can be adopted as an effective diagnostic tool for monitoring microbiological water quality, through coliform quantification, and detection of other waterborne microbial pathogens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".