Performance of common primary and chromogenic culture media for MALDI-TOF MS identification of clinically relevant yeasts
Bibliographic record
Abstract
ABSTRACT Timely and accurate identification of yeasts is essential for adequate treatment, considering the increase in antifungal resistance of some species, particularly for C. auris . Current matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) manufacturer’s protocol for identification of yeasts requires 24- to 72-h cultivation on Sabouraud dextrose media (SAB), but not some of the mainstay primary culture media used in mycology such as inhibitory mold agar (IMA), Mycosel, CHROMagar Candida Plus, and CHROMagar Candida. As culture media can influence MALDI-TOF MS identification results, this study evaluated the accuracy and performance of identification of clinically relevant yeasts on these first-line media using the VITEK-MS MALDI-TOF MS system. IMPORTANCE In this study, a panel of 140 strains (21 species) was used to assess the performance of the selected media. Although not in the manufacturer’s list of accepted media, IMA and chromogenic media are suitable for the identification of yeasts on the VITEK-MS systems. CHROMagar Candida Plus allowed the identification of 135/140 isolates tested after 24-h incubation similar to SAB reference media (137/140). Yeast isolates that grew on Mycosel selective media were also reliably identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. VITEK-MS system with IVD database V3.2 correctly identified C. auris strains to the species level on CHROMagar Candida Plus alleviating the need for subcultivation and reduced turnaround time (24–72 h) to identification for patient screening.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".