Inhibition of inflammatory gene expression by dexamethasone partly depends on the phosphatase, MKP-1 (DUSP1)
Bibliographic record
Abstract
Acting on the glucocorticoid receptor (GR), inhaled glucocorticoids (GCs) are a cornerstone in the treatment of asthma and suppress airway inflammation by reducing inflammatory gene expression. Traditionally, GR was believed to directly repress inflammatory gene transcription (transrepression). However, evidence also suggests that GC-dependent gene expression (transactivation) plays an important repressive role. Since repression of interleukin-8 (IL8) and GM-CSF (CSF2) by dexamethasone (Dex) depends on gene expression, we now examine the repressive role of Dex-induced mitogen-activated protein kinase (MAPK) phosphatase (MKP)-1 (DUSP1). METHODS: Pulmonary A549 epithelial cells were treated with IL-1β (1 ng/ml), with/without Dex (1 µM). Inflammatory gene expression was assessed by real-time PCR and ELISA, and MAPK activation by western blotting. Roles for MAPKs were explored with selective inhibitors and roles for MKP-1 were tested by over-expression and siRNA silencing. RESULTS: IL-1β rapidly increased inflammatory gene expression and this was MAPK-dependent. MKP-1 over-expression repressed expression of many IL-1β-induced inflammatory genes, including IL8 and CSF2. Inflammatory gene expression was significantly repressed by Dex in a manner that was modestly and transiently reversed by silencing of Dex-induced MKP-1. Conclusions: The apparently partial and transient role of MKP-1 in the repression of inflammatory gene expression, for example IL8 and CSF2, by Dex suggests that additional GC-induced gene products are also important. This provides a rational for functional screening of GC-inducible genes that may show repressive functions.
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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) | 0.001 | 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".