Fast and sensitive detection of Trichophyton rubrum DNA from the nail samples of patients with onychomycosis by a double-round polymerase chain reaction-based assay
Bibliographic record
Abstract
BACKGROUND: Trichophyton rubrum is one of the most frequently isolated pathogens in onychomycosis. Isolation of T. rubrum from nail samples by traditional methods is time-consuming and has a high false-negative rate of detection. OBJECTIVES: To investigate the detection of T. rubrum in nail samples using DNA detection methods. METHODS: A total of 62 nail samples from onychomycosis patients with T. rubrum infection were evaluated by culture on Sabouraud's dextrose agar plus chloramphenicol, cycloheximide and gentamicin and compared with genotyping methods utilizing DNA extracted directly from nails. Trichophyton rubrum DNA isolated directly from nails was amplified using two different conserved regions [actin gene and internal transcribed spacer 1 (ITS)] in double-round polymerase chain reaction (PCR) assays. RESULTS: Forty-eight of 62 (77.4%) samples were potassium hydroxide (KOH) positive, but T. rubrum culture was positive in only 14 of 62 (22.6%) samples. By contrast, direct T. rubrum DNA detection rate was 59.7% (37/62) by actin gene and 45.2% (28/62) by ITS1 region PCR assays corresponding to higher detection frequencies compared with culture with P < 0.001 and < 0.008, respectively. The combined detection of actin and ITS1 was 69.4% (43/62). Interestingly, T. rubrum DNA was detected in 9 out of 14 (64.3%) of KOH- and culture-negative samples. Importantly, 15 culture-negative samples collected from patients undergoing antifungal treatment tested PCR positive using the actin region. CONCLUSIONS: These results suggest that a direct DNA detection protocol is more sensitive, accurate and faster than traditional culture-based methods. It can be useful to detect T. rubrum in patients undergoing antifungal therapy and who have been reported mycologically cured on the basis of a culture-based method.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".