Similar adaptive immune response in COPD patients with and without α1 antitrypsin deficiency
Bibliographic record
Abstract
Rationale. COPD is a complex disease characterized by variable degree of lung damage in response to cigarette smoke. An elastase/antielastase imbalance, along with innate immunity, is believed to account for lung destruction in α1-antitrypsin deficiency (AATD), however it is now apparent that AAT has important immune regulatory roles. Aim. To assess adaptive immunity in COPD patients with AATD and compare it to that present in COPD patients with similar disease severity but with normal AAT-levels. Methods. By immunohistochemistry we quantified the number of B cells, T-cells (CD4,CD8), neutrophils and macrophages in lung tissue of severe COPD patients with (n=10) and without (n=22) AATD undergoing lung transplantation, as well as smoking (n=16) and non-smoking (n=8) controls. Results. The two groups of patients with severe COPD, with and without AATD, had similar numbers of B-lymphocytes [median (range): 1.9 (0-4.4) and 1.1 (0-5) cells/mm], CD8 [3.4 (0.6-6.8) and 4.1 (3.1-6.8)] and CD4 T-lymphocytes [5.5 (1-10.8) and 6.0 (1.6-11.9)] that were higher when compared to the control groups (p<0.05). The number of neutrophils and alveolar macrophages was similar in the 4 groups. Lymphocytes in alveolar walls, particularly B-lymphocytes, correlated with the number of lymphoid follicles (r=0.59 p<0.0001) and with FEV1 (r=-0.49 p<0.001). Conclusions. The lung inflammatory pattern in severe COPD with AATD is indistinguishable from the one found in COPD without AATD, suggesting that in both conditions an adaptive immune response is an important pathogenetic factor. Funded by Padua University, CARIPARO, Chiesi.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".