Distinct Functions of the Mitogen-activated Protein Kinase-activated Protein (MAPKAP) Kinases MK2 and MK3
Bibliographic record
Abstract
In LPS-treated macrophages, activation of STAT3 is considered to be crucial for terminating the production of inflammatory cytokines. By analyzing the role of MAPK-activated protein kinase (MK) 2 and MK3 for LPS-induced STAT3 activation in macrophages, the present study provides evidence that MK2 is crucial for STAT3 activation in response to LPS because it prevents MK3 from impeding IFNβ gene expression. Accordingly, LPS-induced IFNβ gene expression is down-regulated in MK2-deficient macrophages and can be reconstituted by additional ablation of the MK3 gene in MK2/3(-/-) macrophages. This is in contrast to LPS-induced IL-10 expression, which essentially requires the presence of MK2. Further analysis of downstream signaling events involved in the transcriptional regulation of IFNβ gene expression suggests that, in the absence of MK2, MK3 impairs interferon regulatory factor 3 protein expression and activation and inhibits nuclear translocation of p65. This inhibition of p65 nuclear translocation coincides with enhanced expression and delayed degradation of IκBβ, whereas expression of IκBα mRNA and protein is impaired in the absence of MK2. The observation that siRNA directed against IκBβ is able to reconstitute IκBα expression in MK2(-/-) macrophages suggests that enhanced expression and delayed degradation of IκBβ and impaired NFκB-dependent IκBα expression are functionally linked. In summary, evidence is provided that MK2 regulates LPS-induced IFNβ expression and downstream STAT3 activation as it restrains MK3 from mediating negative regulatory effects on NFκB- and interferon regulatory factor 3-dependent LPS signaling.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".