Steroid-Insensitive ERK1/2 Activity Drives CXCL8 Synthesis and Neutrophilia by Airway Smooth Muscle
Bibliographic record
Abstract
Severe or refractory asthma affects 5 to 15% of all patients with asthma, but is responsible for more than half of the health burden associated with the disease. Severe asthma is characterized by a dramatic increase in smooth muscle and airway inflammation. Although glucocorticoids are the mainstay of treatment in asthma, they are unable to fully control the disease in individuals with severe asthma. We found that airway smooth muscle cells (ASMCs) from individuals with severe asthma showed elevated activities of the ERK1/ERK2 and p38 MAPK pathways despite treatment with oral and inhaled glucocorticoids, which increased the expression of DUSP1, a phosphatase shown to limit p38 MAPK activity. In ex vivo ASMCs, TNF-α but not IL-17A induced expression of the neutrophil chemoattractant CXCL8. Moreover, TNF-α led to up-regulation of the ERK1/ERK2 and p38 MAPKs pathways, with only the latter being sensitive to pretreatment with the glucocorticoid dexamethasone. In contrast to epithelial and endothelial cells, TNF-α-stimulated CXCL8 synthesis was dependent on ERK1/ERK2 but not on p38 MAPK. Moreover, suppressing ERK1/ERK2 activation prevented neutrophil recruitment by ASMCs, whereas suppressing p38 MAPK activity had no impact. Taken together, these results highlight the ERK1/ERK2 MAPK cascade as a novel and attractive target in severe asthma because the activation of this pathway is insensitive to the action of glucocorticoids and is involved in neutrophil recruitment, contributing the to inflammation seen in the disease.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".