COPD: systemic proteomic profiles in frequent and infrequent exacerbators
Bibliographic record
Abstract
Background Some patients with COPD suffer frequent exacerbations (FE). We hypothesised that their systemic proteomic profile would be different from that of non-frequent exacerbators (NFE). The objective of the present study was to contrast the systemic proteomic profile in FEversusNFE. As a reference, we also determined the systemic proteomic profile of healthy controls (HC) and COPD patients during an actual episode of exacerbation (AE). Methods In the analysis we included 40 clinically stable COPD patients (20 FE and 20 NFE), and 20 HC and 10 AE patients. Their plasma samples were analysed by combining two complementary proteomic approaches: label-free liquid chromatography-tandem mass spectrometry and multiplex immunoassays. Gene Ontology annotation, pathway enrichment and network analyses were used to investigate molecular pathways associated with differentially abundant proteins/peptides (DAPs). Results Compared with HC, we identified 40 DAPs in FE, 10 in NFE and 63 in AE. Also compared to HC, pathway functional and protein–protein network analyses revealed dysregulation of inflammatory responses involving innate and antibody-mediated immunity in COPD, particularly in the FE group, as well as during an AE episode. Besides, we only identified alterations in the complement and coagulation cascades in AE. Conclusion There are specific plasma proteome profiles associated with FE, which are partially shared with findings observed during AE, albeit others are uniquely present during the actual episode of AE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".