Cellular and molecular features of asthma mucus plugs provide clues about their formation and persistence
Bibliographic record
Abstract
BACKGROUNDMucus plugs form in acute asthma and persist in chronic disease. Although eosinophils are implicated in mechanisms of mucus pathology, many mechanistic details about mucus plug formation and persistence in asthma are unknown.METHODSUsing histology and spatial, single-cell proteomics, we characterized mucus-plugged airways from nontransplantable donor lungs of 14 patients with asthma (9 with fatal asthma and 5 with nonfatal asthma) and individuals acting as controls (10 with chronic obstructive pulmonary disease and 14 free of lung disease). Additionally, we used an airway epithelial cell-eosinophil (AEC-eosinophil) coculture model to explore how AEC mucus affects eosinophil degranulation.RESULTSAsthma mucus plugs were tethered to airways showing infiltration with innate lymphoid type 2 cells and hyperplasia of smooth muscle cells and MUC5AC-expressing goblet cells. Asthma mucus plugs were infiltrated with immune cells that were mostly dual positive for eosinophil peroxidase (EPX) and neutrophil elastase, suggesting that neutrophils internalize EPX from degranulating eosinophils. Indeed, eosinophils exposed to mucus from IL-13-activated AECs underwent CD11b- and glycan-dependent cytolytic degranulation. Dual-positive granulocytes varied in frequency in mucus plugs. Whereas paucigranulocytic plugs were MUC5AC rich, granulocytic plugs had a mix of MUC5AC, MUC5B, and extracellular DNA traps. Paucigranulocytic plugs occurred more frequently in (acute) fatal asthma and granulocytic plugs predominated in (chronic) nonfatal asthma.CONCLUSIONTogether, our data suggest that mucin-rich mucus plugs in fatal asthma form because of acute goblet cell degranulation in remodeled airways and that granulocytic mucus plugs in chronic asthma persist because of a sustaining niche characterized by epithelial cell-mucin-granulocyte cross-talk.FUNDINGNIH grants HL080414, HL107202, and AI077439.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".