Corticosteroids and β<sub>2</sub>‐agonists upregulate mitogen‐activated protein kinase phosphatase 1: <i>in vitro</i> mechanisms
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Airway remodelling is a consequence of long-term inflammation and MAPKs are key signalling molecules that drive pro-inflammatory pathways. The endogenous MAPK deactivator--MAPK phosphatase 1 (MKP-1)--is a critical negative regulator of the myriad pro-inflammatory pathways activated by MAPKs in the airway. EXPERIMENTAL APPROACH: Herein we investigated the molecular mechanisms responsible for the upregulation of MKP-1 in airway smooth muscle (ASM) by the corticosteroid dexamethasone and the β₂-agonist formoterol, added alone and in combination. KEY RESULTS: MKP-1 is a corticosteroid-inducible gene whose expression is enhanced by long-acting β₂-agonists in an additive manner. Formoterol induced MKP-1 expression via the β₂-adrenoceptor and we provide the first direct evidence (utilizing overexpression of PKIα, a highly selective PKA inhibitor) to show that PKA mediates β₂-agonist-induced MKP-1 upregulation. Dexamethasone activated MKP-1 transcription in ASM cells via a cis-acting corticosteroid-responsive region located between -1380 and -1266 bp of the MKP-1 promoter. While the 3'-untranslated region of MKP-1 contains adenylate + uridylate elements responsible for regulation at the post-transcriptional level, actinomycin D chase experiments revealed that there was no increase in MKP-1 mRNA stability in the presence of dexamethasone, formoterol, alone or in combination. Rather, there was an additive effect of the asthma therapeutics on MKP-1 transcription. CONCLUSIONS AND IMPLICATIONS: Taken together, these studies allow us a greater understanding of the molecular basis of MKP-1 regulation by corticosteroids and β₂-agonists and this new knowledge may lead to elucidation of optimized corticosteroid-sparing therapies in the future.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".