Intestinal host–microbe interactions fuel pulmonary inflammation in cigarette smoke exposed mice
Bibliographic record
Abstract
The gut microbiota has been implicated in numerous aspects of host health and immune regulation. Specifically, recent studies have linked gut microbes to the pathogenesis of chronic obstructive pulmonary disease (COPD), primarily induced by excessive cigarette smoke, although the underlying mechanisms remain elusive. Here, we investigated the role of gastrointestinal (GI) host-microbe interactions on pulmonary health. Using two distinct means of modulating GI host-microbe relations, we dissected how gut microbes fuel pulmonary inflammation in mouse models of cigarette smoke (CS)-induced lung disease. We found that CS caused profound changes to the colonic mucosa, with reduced mucus and increased bacterial encroachment. Modulating host-microbe interactions using antibiotics and recombinant human β-defensin 2 restricted colonic bacterial encroachment, limiting interactions between host and microbe. These strategies resulted in substantial ~50% decrease in pulmonary neutrophil infiltration following both acute and chronic exposure to CS. The reported findings provide additional evidence of a gut-lung axis, offering novel insight into the role of the gut microbiota in pulmonary immune activation, which could represent a novel avenue for future therapeutic strategies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".