P38 MAPK Inhibition Enhances Corticosteroid Effects In Human Epithelial Cells Via Increased Gr Nuclear Localisation
Bibliographic record
Abstract
Background Phospho-p38 MAPK expression is increased in airway epithelial cells in patients with severe asthma and in COPD patients compared to controls. Increased p38 MAPK activation may lead to reduced corticosteroid responsiveness. We have used a human cell bronchial epithelial cell line to investigate the effects of a p38 MAPK inhibitor in combination with a corticosteroid on inflammatory cytokine stimulation. Methods The human epithelial cell line 16HBE14o- was used to determine the effects of dexamethasone (0.1–1000 nM) alone, the p38 MAPK inhibitor BIRB-796 (1–1000 nM) alone and both drugs combined at all concentrations on LPS (1 µg/ml), Poly I:C (100 µg/ml) or TNFα (10 ng/ml) -induced IL-6, IL-8 and RANTES. 16HBE14o- cells were treated with BIRB-796 (1–1000 nM) alone and in combination with dexamethasone (0.1 nM) for 30 min and glucocorticoid receptor (GR) nuclear translocation determined by immunofluorescence. The effects of TNFα stimulation on the phosphorylation of p38 and GR (serine 226) in 16HBE14o- cells were determined by Western blot analysis. Results Maximum inhibition of dexamethasone and BIRB-796 in combination was significantly greater than either drug alone for LPS and TNFα induced IL-6 and IL-8 and for Poly I:C induced RANTES (p < 0.05 all comparisons). BIRB-796 (1000 nM) alone had no effect on GR translocation. BIRB-796 (1000 nM) used in combination with dexamethasone (0.1 nM) significantly increased nuclear GR (76.6% nuclear staining) compared to dexamethasone (0.1 nM) alone (4% nuclear staining). TNFα stimulation increased both p38 and GR serine 226 phosphorylation by 15 min. Pre-incubation with BIRB-796 abolished p38 phosphorylation and reduced GR serine 226 phosphorylation. Conclusion P38 MAPK inhibition enhances the effect of corticosteroids on inflammatory cytokines in human epithelial cells. This enhancement is due to inhibition of p38 dependent phosphorylation of GR serine 226 which leads to increased nuclear localisation of GR.
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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) | 0.005 | 0.001 |
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".