Airway sensory systems: breathing new life into microbiota-brain communication
Bibliographic record
Abstract
The essential role of the lungs in gas exchange necessitates exposure to possible threats from a dynamic external environment. To protect life-critical functions the airways contain multiple systems that monitor the inhaled environment and elicit appropriate defensive responses. As such the airways represent a key sensory surface with multiple signaling pathways to the brain. Despite the presence of rich and diverse bacterial communities in both upper and lower airways, the respiratory tract has been relatively overlooked compared to the gut regarding its potential as an interface between microbes and the central nervous system. This review draws attention to the respiratory system, specifically the nasal cavity and lungs, and the evidence supporting a microbiota-airway-brain axis. We highlight the olfactory system and the role of the lungs as a sensory organ, monitoring the inhaled environment, as clear examples of airway-brain communication and identify how these communication pathways can be engaged by microbes. We also outline the relationship between the airways and mental health and present the case that the nasal and lung microbiota should be considered alongside that of the gut as potential influencers of brain function, mood, and behavior.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".