The role of acute and chronic respiratory colonization and infections in the pathogenesis of <scp>COPD</scp>
Bibliographic record
Abstract
COPD is a major global concern, increasingly so in the context of ageing populations. The role of infections in disease pathogenesis and progression is known to be important, yet the mechanisms involved remain to be fully elucidated. While COPD pathogens such as Haemophilus influenzae, Moraxella catarrhalis and Streptococcus pneumoniae are strongly associated with acute exacerbations of COPD (AECOPD), the clinical relevance of these pathogens in stable COPD patients remains unclear. Immune responses in stable and colonized COPD patients are comparable to those detected in AECOPD, supporting a role for chronic colonization in COPD pathogenesis through perpetuation of deleterious immune responses. Advances in molecular diagnostics and metagenomics now allow the assessment of microbe-COPD interactions with unprecedented personalization and precision, revealing changes in microbiota associated with the COPD disease state. As microbial changes associated with AECOPD, disease severity and therapeutic intervention become apparent, a renewed focus has been placed on the microbiology of COPD and the characterization of the lung microbiome in both its acute and chronic states. Characterization of bacterial, viral and fungal microbiota as part of the lung microbiome has the potential to reveal previously unrecognized prognostic markers of COPD that predict disease outcome or infection susceptibility. Addressing such knowledge gaps will ultimately lead to a more complete understanding of the microbe-host interplay in COPD. This will permit clearer distinctions between acute and chronic infections and more granular patient stratification that will enable better management of these features and of COPD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".