Foamy macrophage responses in the rat lung following exposure to inhaled pharmaceuticals: a simple, pragmatic approach for inhaled drug development
Bibliographic record
Abstract
Successes in the field of respiratory medicines are largely limited to three main target classes: β2 -adrenergic receptor agonists, muscarinic antagonists and corticosteroids. A significant factor in attrition during the development of respiratory medicines is the induction of foamy macrophage responses, particularly, in rats. The term foamy macrophage describes a vacuolated cytoplasmic appearance, seen by light microscopy, which is ultrastructurally characterized by the presence of lysosomal lamellar bodies, neutral lipid droplets or drug particles. We propose a simple classification, based light-heartedly on the theme 'the good, the bad and the ugly', which allows important distinctions to be made between phenotypes, aetiologies and adversity. Foamy macrophages induced in rat lungs by exposure to inhaled β2 -agonists, antimuscarinics and corticosteroids are simple aggregates of uniform cells without other associated pathologies. In contrast, macrophage reactions induced by some other inhaled drug classes are more complex, associated with neutrophilic or lymphocytic infiltrations with/without damage to the adjacent alveolar walls. Foamy macrophage responses induced by inhaled drugs may be ascribed to either phagocytosis of poorly soluble drug particles, or to pharmacology. Both corticosteroids and β2 -agonists increase surfactant synthesis whereas muscarinic antagonists may decrease surfactant breakdown, due to inhibition of phospholipase C, both of which lead to phagocytosis of excess surfactant. Simple foamy macrophage responses are considered non-adverse, whereas ones that are more complex are designated as adverse. The development of foamy macrophage responses has led to confusion in interpretation and we hope this review helps clarify what is in fact a relatively simple, predictable, easily interpretable, commonly induced change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".