Genotypic diversity and antifungal susceptibility of <i>Scedosporium</i> species from clinical settings in China
Bibliographic record
Abstract
Abstract Background Scedosporium species have drawn significant interest as inhabitants of polluted soil and water and as cause of high mortality in near‐drowning patients. So far, most cases have been reported from Europe and Australia, while knowledge on their prevalence and genotypic diversity from Asia is scant. Objectives To increase the knowledge of the genetic diversity and in vitro antifungal susceptibility of Scedosporium species involved in human infections from China. Methods Here, we applied the ISHAM‐MLST consensus scheme for molecular typing of Scedosporium species and revealed both high species diversity and high genotypic diversity among 45 Chinese clinical Scedosporium isolates. Results Among the five species, Scedosporium boydii (n = 22) was the most common, followed by S. apiospermum (n = 18), S. aurantiacum (n = 4) and S. dehoogii (n = 1). S. aurantiacum was reported for the first time from clinical samples in China. The predominant sequence types (STs) were ST17 in S. apiospermum, ST4 in S. boydii and ST92 in S. aurantiacum, including four novel STs (ST40, ST41, ST42 and ST43) in S. apiospermum. Based on the CLSI‐M38 A2 criterion, voriconazole was the only antifungal compound with low MIC values (MIC90 ≤ 1 μg/ml) for all Scedosporium isolates in our study. Conclusions The genetic diversity of clinical isolates of Scedosporium species from China is extremely high, with S. boydii being predominant and S. aurantiacum being firstly reported here. VOR was the only antifungal compound with low MIC values for all Scedosporium isolates in our study, which should be recommended as the firstline antifungal treatment against scedosporiosis in China.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".