Aspergillus Species in Lower Respiratory Tract of Hospitalized Patients from Shanghai, China: Species Diversity and Emerging Azole Resistance
Bibliographic record
Abstract
Purpose: To investigate species diversity and prevalence of antifungal resistance among clinical isolates of Aspergillus spp. in Shanghai, China. Patients and Methods: In this study, the Aspergillus spp. isolates were analyzed by multilocus sequence typing (MLST) targeting the internal transcribed spacer (ITS) regions, and partial β-tubulin ( BenA ) and calmodulin ( CaM ) genes. The susceptibilities of these isolates to nine antifungal agents were determined according to the protocol in document M38-A3 established by the Clinical and Laboratory Standards Institute (CLSI). Results: The most common Aspergillus spp. was A. fumigatus (58.2%), followed by the A. flavus complex (23.5%), and A. niger complex (15.3%). Isolates belonging to A. tamarii and A. effusus of the A. flavus complex and A. tubingensis and A. awamori of the A. niger complex were identified. Moreover, several mutations were found in the azole target cyp51A gene (TR 46 /Y121F/T289A and F46Y, G89G, M172V, N248T and D255E) in azole-resistant isolates of A. fumigatus . Conclusion: The results of our study revealed a diversity of species in the lower respiratory tract of inpatients in Shanghai and approximately 9% of our isolates were resistant to at least one of the triazole antifungals. Formulation of local treatment strategies to combat emerging azole resistance and species diversity in clinically relevant Aspergillus spp. is needed. Keywords: Aspergillus , antifungal susceptibility, identification, molecular typing, 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".