Public Health Implications of Airborne <i>Candida</i>: Viability, Drug Resistance, and Genetic Links to Clinical Strains
Bibliographic record
Abstract
Candida is the largest genus of medically significant yeasts, causing diseases ranging from mucosal to life-threatening invasive infections. Airborne transmission of Candida has gained attention following its genotypic detection in ambient air and isolation in occupational air. However, more comprehensive phenotypic evidence, including viability, antifungal resistance, and phylogenetic relatedness to clinical strains, is needed in ambient air, with implications for community-level exposure, colonization, and infection. To address this gap, we sampled air at an urban and a coastal site using six-stage Andersen impactors. Viable isolates of C. parapsilosis, C. albicans, and C. tropicalis ─all World Health Organization priority fungal pathogens─were recovered from ambient urban air, primarily associated with respirable particle sizes (2.1–7 μm) across seasons. Antifungal susceptibility testing identified C. parapsilosis as the predominant multidrug-resistant species. Whole-genome sequencing revealed airborne C. parapsilosis shared 99.53% genetic similarity with nearby clinical strains, differing by only 94 out of 20,206 single-nucleotide polymorphisms. This suggests the plausibility of community-acquired infection via airborne routes. These findings highlight the need to investigate airborne transmission from environmental reservoirs to human colonization and infection. This is particularly critical under urban megatrends and climate change, emphasizing an emerging microbial hazard beyond antibiotic-resistant bacteria within the One Health framework.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| 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 teacher head, 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".