Amplification of Inflammation in Emphysema and its Association with Latent Adenoviral Infection
Bibliographic record
Abstract
This study examines the hypothesis that the cigarette smoke-induced inflammatory process is amplified in severe emphysema and explores the association of this response with latent adenoviral infection. Lung tissue from patients with similar smoking histories and either no (n = 7), mild (n = 7), or severe emphysema (n = 7) was obtained by lung resection. Numbers of polymorphonuclear cells (PMN), macrophages, B cells, CD4, CD8 lymphocytes, and eosinophils present in tissue and airspaces and of epithelial cells expressing adenoviral E1A protein were determined using quantitative techniques. Severe emphysema was associated with an absolute increase in the total number of inflammatory cells in the lung tissue and airspaces. The computed tomography (CT) determined extent of lung destruction was related to the number of cells/m(2) surface area by R(2) values that ranged from 0.858 (CD8 cells) to 0.483 (B cells) in the tissue and 0.630 (CD4 cells) to 0.198 (B cells) in the airspaces. These changes were associated with a 5- to 40-fold increase in the number of alveolar epithelial cells expressing adenoviral E1A protein in mild and severe disease, respectively. We conclude that cigarette smoke-induced lung inflammation is amplified in severe emphysema and that latent expression of the adenoviral E1A protein expressed by alveolar epithelial cells influenced this amplification process.
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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 | 0.001 |
| 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".