Type I interferon (IFN)-dependent activation of Mnk1 and its role in the generation of growth inhibitory responses
Bibliographic record
Abstract
We provide evidence for the existence of an IFN-regulated cellular pathway involving the mitogen-activated protein kinase (MAPK)-integrating kinase (Mnk) 1. Our data demonstrate that type I (alpha, beta) IFNs induce phosphorylation/activation of Mnk1, which, in turn, regulates phosphorylation of the eukaryotic initiation factor 4E (eIF4E) on Ser-209. Such Mnk activation depends on upstream engagement of Jak1, and requires downstream activation of the Mek/Erk MAPK pathway. In studies using double Mnk1-/-Mnk2-/- knockout mouse embryonic fibroblasts (MEFs), we found that engagement of Mnk kinases is essential for mRNA translation of the Isg15 and Isg54 genes, suggesting an important role for this pathway in mRNA translation of IFN-stimulated genes (ISGs). Importantly, our data demonstrate that pharmacological inhibition of Mnk kinases or siRNA-mediated knockdown of Mnk1 and Mnk2 results in partial reversal of the suppressive effects of IFNalpha on normal and leukemic hematopoietic progenitors, establishing a key role for this pathway in the generation of the growth inhibitory effects of type I IFNs. Together, our findings establish that the Mnk/eIF4E kinase pathway is activated in an IFN-inducible manner and plays important roles in mRNA translation for ISGs and generation of IFN-inducible anti-proliferative responses.
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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 | 0.000 |
| 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".