Phenotypes of alveolar macrophages in normal human lung and their polarization with disease
Bibliographic record
Abstract
BACKGROUND Macrophages are crucial components of innate immunity. During inflammatory responses monocytes are recruited into tissues, skewed first toward unpolarized macrophages (M0) and then polarized toward proinflammatory M1 or antiinflammtory M2 functional phenotype. However the different macrophages polarization (M0, M1, M2) in normal human lungs and their plasticity with the disease is not understood. AIM To investigate the phenotype of alveolar macrophages (AM) in normal human lung tissue and their change with disease. METHODS M1 (iNOS + ), M2 (CD206 + ) and M0 (iNOS - /CD206 - ) AM were studied by immunohistochemical and immunofluoresence techniques in human lung sequential slides of 17 nonsmokers (11 with tumor and 6 donors without tumor) 13 smokers without COPD and 23 COPD (11 severe and 12 mild/moderate). Positive AM were counted and expressed as percentage of total AM. RESULTS Baseline AM population in normal donor lungs comprised 57%(31-68) of M0, 31%(24-60) of M1 and 7%(4-16) of M2. However, in nonsmokers with lung cancer M2 increased to 43%(2-65), but not the M1. In smokers M2 [68%(40-86)] was higher than in nonsmokers [43%(2-65)] but did not increase further with COPD severity [61%(36-94) in mild/moderate COPD and 78%(53-98) in severe COPD]. M1 is minimally present in nonsmokers [24%(3-38)] and increases gradually and significantly with worsening COPD [68%(40-93) in mild/moderate COPD and 84%(36-99) in severe COPD]. CONCLUSION The baseline (normal) AM polarization is mainly M0 with a small percentage of proinflammatory M1, which increases along with worsening COPD. M2 increase is probably partially related to the presence of cancer.
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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 | 0.000 |
| 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) | 0.001 | 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".