Macrophages and the microbiome in chronic obstructive pulmonary disease
Bibliographic record
Abstract
COPD is a heterogeneous disease of the lungs characterised by restricted airflow. Chronic inflammation and recurrent bacterial infections are known to be important driving factors in exacerbations of this disease. Despite a marked increase in the number of alveolar macrophages present in the lungs of COPD patients, there is evidence of reduced clearance of pathogenic bacteria, leading to recurrent infection, exacerbation and subsequent lung function decline. This is thought to be attributed to a defect in the phagocytic capability of both alveolar and monocyte-derived macrophages in COPD. In addition to this defect, there is apparent selectivity in bacterial uptake by COPD macrophages because certain pathogenic genera, such as Haemophilus , Moraxella and Streptococcus , are taken up more readily than others. The respiratory microbiome plays a key role in regulating the host immune response both in health and during chronic inflammation. In patients with COPD, there are distinct changes in the composition of the respiratory microbiome, particularly the lower respiratory tract, where dominance of clinically relevant pathogenic species is commonly observed. Whether there are links between these changes in the microbiome and dysfunctional macrophage phagocytosis has not yet been widely studied. This review aims to discuss what is currently known about these phenomena and to explore interactions between macrophages and the respiratory microbiome.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".