Detection of Legionella spp. by fluorescent in situ hybridization in dental unit waterlines
Bibliographic record
Abstract
AIMS: To confirm the presence of viable Legionella spp. in dental unit waterlines (DUWL) using fluorescent in situ hybridization (FISH) and compare this method with culture approach and also to validate the utility of an enrichment to increase FISH sensitivity. METHODS AND RESULTS: Water samples from 40 dental units were analysed. Three different techniques for detecting Legionella spp. were compared: (i) culture approach, (ii) direct FISH and (iii) FISH with a previous R2A medium enrichment (R2A/FISH). The FISH detection was confirmed by PCR. The use of the direct FISH does not improve significantly the detection of legionellae when compared with the culture. On the contrary, when R2A/FISH was performed, sensitivity was, respectively, two- and threefold higher than that with the direct FISH and culture approach. Using R2A/FISH, 63% of water samples analysed showed a contamination by legionellae. CONCLUSIONS: Legionellae detection by direct FISH and R2A/FISH in dental unit water is possible but is more rapid and more sensitive (R2A/FISH) than the culture approach. SIGNIFICANCE AND IMPACT OF THE STUDY: R2A/FISH showed that several pathogens present in DUWL are viable but may not be culturable. Unlike PCR, R2A/FISH is designed to detect only metabolically active cells and therefore provides more pertinent information on infectious risk.
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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) | 0.000 | 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".