<i>Neosartorya udagawae</i> ( <i>Aspergillus udagawae</i> ), an Emerging Agent of Aspergillosis: How Different Is It from <i>Aspergillus fumigatus</i> ?
Bibliographic record
Abstract
A recent report on several cases of invasive aspergillosis caused by Neosartorya udagawae suggested distinctive patterns of disease progression between N. udagawae and Aspergillus fumigatus. This prompted us to characterize N. udagawae in comparison to A. fumigatus. Our findings showed that both species exist in two mating types at similar ratios and produce gliotoxin. However, the thermotolerance of the two species differs: while A. fumigatus is able to grow at 55 degrees C but not at 10 degrees C, N. udagawae is able to grow at 10 degrees C but fails to grow at >42 degrees C. Furthermore, compared to A. fumigatus, the conidia of N. udagawae require longer incubation periods to germinate at 37 degrees C and are more susceptible to neutrophil attack as well as hydrogen peroxide; N. udagawae is also less virulent in gp91(phox-/-) mice. These findings suggest that growth and susceptibility to the host response might account for the reduced virulence of N. udagawae and the subtle distinction in the progression of the disease caused by the two species.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".