Genotypic and Phenotypic Investigation of Clinical Aspergillus isolates from Iran Indicates Nosocomial Transmission Events of Aspergillus flavus
Bibliographic record
Abstract
Aspergillosis is one of the most common human fungal infections. The invasive form of this infectious disease has high mortality rates. Moreover, antifungal resistance has been increasing, thereby limiting treatment options. In Iran, limited species distribution, genotyping and susceptibility data regarding aspergillosis is available, especially during the COVID-19 pandemic. In the current study, 124 patients with proven (n = 31), probable (n = 24) and possible (n = 46) aspergillosis and aspergillus colonization (n = 19) were investigated. Isolates were identified to species level based on calmodulin sequencing. Antifungal susceptibility testing was performed with microbroth dilution against common antifungal agents, i.e. amphotericin B, azoles and echinocandins. Additionally, short tandem repeat genotyping was conducted on common Aspergillus species to assess genetic relatedness. Aspergillus flavus was the most common species for proven aspergilossis cases, followed by identification of single cases of A. fumigatus, A. terreus, A. niger. These Aspergillus species were also mostly found in other patients with probably aspergillosis, in addition to four cases of possible aspergillosis with rare or cryptic species A. candidus, A. citrinoterreus, A. tubingensis and A. fumigatiaffinis, respectively. Using available epidemiological cutoff values (ECVs) no isolates were non-wild type to the tested antifungal drugs, while the A. fumigatiaffinis and A. citrinoterreus isolate demonstrated reduced susceptibility to respectively amphotericin B and Itraconazole, and amphotericin B only. With high-resolution short tandem repeat genotyping, several A. flavus clusters were found and their spatial and temporal clustering suggested nosocomial origins. To conclude, aspergillosis cases in Iran were caused by diverse but susceptible species, with A. flavus being dominant and associated with several events of potential nosocomial transmission.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".