Analysis of the nasal vestibule mycobiome in patients with allergic rhinitis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Advances in culture-independent sequencing methods have been utilised in recent studies to understand the phylogenetic composition of the human microbiome of healthy and diseased skin. Allergic rhinitis (AR) is an inflammatory condition of the nasal cavity caused by environmental allergens. Although nasal microbial communities have been considered important contributors in human health, no studies to date have comprehensively compared fungal communities (mycobiome) of the nasal vestibule using the culture-independent pyrosequencing method. This study aimed to investigate how fungal communities of the nasal vestibule skin surface are influenced by AR. The phylogenetic composition of the nasal vestibule mycobiome of patients with AR was analysed by culture-independent pyrosequencing methods and compared with healthy individuals. A total of 69 fungal genera were identified from both AR samples and healthy controls, and the genus Malassezia predominated in the nasal vestibule. Species-level analysis classified eight different Malassezia species including M. pachydermatis and M. cuniculi, which were normally isolated from animals, and revealed M. restricta to be the most abundant species in the nasal vestibule. Although high interpersonal variation was observed, some of the AR samples displayed significantly higher diversities than healthy controls at both the genus and species level.
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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 | 0.000 | 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 | 0.000 |
| 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 it