Lung Macrophages: Pivotal Immune Effector Cells Orchestrating Acute and Chronic Lung Diseases
Bibliographic record
Abstract
Macrophages are key immune cells, where they play a pivotal role in host defense and tissue homeostasis. The lungs have two major subsets, alveolar macrophages (AMs) found in airspaces and interstitial macrophages (IMs) found in lung tissues. Lung macrophages (LM) are highly heterogeneous and have high levels of plasticity. A long-lasting population of LM with self-renewal ability populate the lung during embryogenesis and monocyte-derived macrophages recruited during infection, inflammation, or tissue repair, which are more short lived. AMs have been the main focus of research due in part to their abundance, accessibility, and ease of isolation compared with IMs. With advances in multichannel flow cytometry and single-cell sequencing, the importance of IMs has been recently appreciated. LM’s functions in the lungs include maintenance of homoeostasis, immune surveillance, removal of cellular debris, tissue repair, clearance of pathogens, and the resolution of inflammation. They also activate the adaptive immune response by functioning as antigen-presenting cells. LMs are pivotal in the pathogenesis of acute and chronic inflammatory lung conditions including lung cancer. This chapter will discuss the ontology, phenotypic heterogeneity, and functions of LM’s and how these characteristics orchestrate and impact common acute and chronic lung conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.020 |
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".