Do Circulating Extracellular Vesicles Strictly Reflect Bronchoalveolar Lavage Extracellular Vesicles in COPD?
Bibliographic record
Abstract
Cell-derived extracellular vesicles (EVs) found in the circulation and body fluids contain biomolecules that could be used as biomarkers for lung and other diseases. EVs from bronchoalveolar lavage (BAL) might be more informative of lung abnormalities than EVs from blood, where information might be diluted. To compare EVs’ characteristics in BAL and blood in smokers with and without COPD. Same-day BAL and blood samples were obtained in 9 nonsmokers (NS), 11 smokers w/o COPD (S), and 9 with COPD (SCOPD) (FEV1: 59 ± 3% pred). After differential centrifugation, EVs (200–500 nm diameter) were identified by flow cytometry and labeled with cell-type specific antigens: CD14 for macrophage-derived EVs, CD326 for epithelial-derived EVs, CD146 for endothelial-derived EVs, and CD62E for activated-endothelial-derived EVs. In BAL, CD14-EVs were increased in S compared to NS [384 (56–567) vs. 172 (115–282) events/μL; p = 0.007] and further increased in SCOPD [619 (224–888)] compared to both S (p = 0.04) and NS (p < 0.001). CD326-EVs were increased in S [760 (48–2856) events/μL, p < 0.001] and in SCOPD [1055 (194–11,491), p < 0.001] when compared to NS [15 (0–68)]. CD146-EVs and CD62E-EVs were similar in the three groups. In BAL, significant differences in macrophage and epithelial-derived EVs can be clearly detected between NS, S and SCOPD, while these differences were not found in plasma. This suggests that BAL is a better medium than blood to study EVs in lung diseases.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".