Landscape-scale exposure to multiazole-resistant <i>Aspergillus fumigatus</i> bioaerosols
Bibliographic record
Abstract
Abstract We demonstrate country-wide exposures to aerosolized spores of a human fungal pathogen, Aspergillus fumigatus , that has acquired resistance to first line azole clinical antifungal drugs. Assisted by a network of citizen scientists across the United Kingdom, we show that 1 in 20 viable aerosolized spores of this mold are resistant to the agricultural fungicide tebuconazole and 1 in 140 spores are resistant to the four most used azoles for treating clinical aspergillosis infections. Season and proximity to industrial composters were associated with growth of A. fumigatus from air samples, but not with the presence of azole resistance, and hotspots were not stable between sampling periods suggesting a high degree of atmospheric mixing. Genomic analysis shows no distinction between those resistant genotypes found in the environment and in patients, indicating that ~40% (58/150 sequenced genomes) of azole-resistant A. fumigatus infections are acquired from environmental exposures. Due to the ubiquity of this measured exposure, it is crucial that we determine source(s) of azole-resistant A. fumigatus , who is at greatest risk of exposure and how to mitigate these exposures, in order to minimize treatment failure in patients with aspergillosis. One sentence summary UK-wide citizen science surveillance finds a ubiquitous exposure to aerosolized spores of a human fungal pathogen that have evolved in the environment cross-resistance to essential clinical antifungal drugs
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".