Expansion of a Population of Large Monocytes (Atypical Monocytes) in Peripheral Blood of Patients with Acute Exacerbations of Chronic Obstructive Pulmonary Diseases
Bibliographic record
Abstract
Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is closely associated with airway inflammation including monocytes, lymphocytes, and neutrophils. Monocytes play an essential role in the pathogenesis of chronic obstructive pulmonary disease (COPD). To elucidate the association of circulating monocyte alteration with AECOPD, we analyzed monocyte subpopulation in the peripheral blood of 16 healthy volunteers and 22 AECOPD patients at the stages of admission and remission after clinical therapy. We found a dramatic increase of a previously unreported population of large size circulating atypical monocytes (A Mo) in AECOPD patients, characterized by higher forward scatter and lower side scatter values than the typical monocytes (T Mo) which were observed predominantly in healthy individuals. Further analysis showed that A Mo expressed higher levels of CD16, intercellular adhesion molecule 1 (ICAM-1), and chemotactic protein-1 receptor-2 (CCR2) than T Mo. In contrast, the expression of class II antigen (HLA-DR) by A Mo was lower than T Mo. More importantly, we observed that the percentage of circulating A Mo among total monocytes correlated with the length of hospital stay (time to remission) and disease duration. The data suggest that circulating A Mo might have the potential to serve as a biomarker in the diagnosis and prognosis of AECOPD.
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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 | 0.001 | 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".