Antifungal Susceptibility Testing of Aspergillus spp. by Using a Composite Correlation Index (CCI)-Based Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry Method Appears To Not Offer Benefit over Traditional Broth Microdilution Testing
Bibliographic record
Abstract
ABSTRACT Aspergillus spp. cause serious invasive lung infections, and Aspergillus fumigatus is the most commonly encountered clinically significant species. Voriconazole is considered to be the drug of choice for treating A. fumigatus infections; however, rising resistance rates have been reported. We evaluated a matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS)-based method for the differentiation between wild-type and non-wild-type isolates of 20 Aspergillus spp. (including 2 isolates of Aspergillus ustus and 1 of Aspergillus calidoustus that were used as controls due their intrinsic low azole susceptibility with respect to the in vitro response to voriconazole). At 30 and 48 h of incubation, there was complete agreement between Cyp51A sequence analysis, broth microdilution, and MALDI-TOF MS classification of isolates as wild type or non-wild type. In this proof-of-concept study, we demonstrated that MALDI-TOF MS can be used to accurately detect A. fumigatus strains with reduced voriconazole susceptibility. However, rather than proving to be a rapid and simple method for antifungal susceptibility testing, this particular MS-based method showed no benefit over conventional testing 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".