Comparative Evaluation of a New Fluorescent Carboxyfluorescein Diacetate-Modified Microdilution Method for Antifungal Susceptibility Testing of <i>Candida albicans</i> Isolates
Bibliographic record
Abstract
This report presents a fluorescent carboxyfluorescein diacetate (CFDA)-modified microdilution method used for the susceptibility testing of Candida albicans to amphotericin B, fluconazole, ketoconazole, itraconazole, voriconazole, and flucytosine. Four different broth microdilution susceptibility testing methods were simultaneously evaluated at 24 and 48 h. The MICs determined using the CFDA-modified method (MIC(cfda)) were compared to those obtained by the standard broth microdilution method (MIC(visual)) and a procedure employing the indicator Alamar blue (MIC(alamar)). The reference MIC was determined visually as recommended by the NCCLS M27-A protocol, and then quantified spectrophotometrically following agitation (MIC(spec)). The CFDA-modified microdilution method was demonstrated to effectively determine the MICs for all the antifungal drugs tested at both 24 and 48 h. The results from both the MIC(spec) and MIC(cfda) methods yielded >80% agreement within +/-1 dilution and >90% agreement within +/-2 dilutions at 24 h in comparison to the reference MIC(visual) method, respectively. The trailing growth phenomenon that occurs with azole antifungal drugs and many strains of C. albicans did not inhibit the effectiveness of the MIC(spec) and MIC(cfda) methods. The MIC(spec) and MIC(cfda) methods shared 92.8% agreement within +/-1 dilution at 24 h and 87.6% agreement within +/-1 dilution at 48 h.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".