Microbiome diversity, intra-mucosal bacteria and immune integration within normal and asthmatic airway mucosa
Bibliographic record
Abstract
Abstract Asthma is characterized by reduced bronchial bacterial diversity and airway mucosal disruption. We examined spatial distributions of microbial sequences and host mucosal transcripts in bronchial biopsies from healthy controls and adult asthmatics. Bacteria were discovered by 16S ribosomal RNA staining in the lamina propria of all biopsies, with counts positively associated to lumenal bacterial diversity. Weighted correlation network analysis identified fifteen co-expression networks, including distinct programs of adaptive and innate immunity in differing spatial distributions. Stromal bacterial counts correlated significantly with eight of the network eigenvectors in directions compatible with beneficial relationships. The results suggest that dysbiosis may affect mucosal immunity through impaired interactions beneath the epithelial border. Intra-mucosal companion bacteria may be a potential substrate for selective management of immunity in a wide range of diseases. One-Sentence Summary The lung microbiome extends within the airway mucosa and associates spatially and functionally with immune networks.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".