Interferon-Dependent Engagement of Eukaryotic Initiation Factor 4B via S6 Kinase (S6K)- and Ribosomal Protein S6K-Mediated Signals
Why this work is in the frame
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Bibliographic record
Abstract
Although the roles of Jak-Stat pathways in type I and II interferon (IFN)-dependent transcriptional regulation are well established, the precise mechanisms of mRNA translation for IFN-sensitive genes remain to be defined. We examined the effects of IFNs on the phosphorylation/activation of eukaryotic translation initiation factor 4B (eIF4B). Our data show that eIF4B is phosphorylated on Ser422 during treatment of sensitive cells with alpha IFN (IFN-alpha) or IFN-gamma. Such phosphorylation is regulated, in a cell type-specific manner, by either the p70 S6 kinase (S6K) or the p90 ribosomal protein S6K (RSK) and results in enhanced interaction of the protein with eIF3A (p170/eIF3A) and increased associated ATPase activity. Our data also demonstrate that IFN-inducible eIF4B activity and IFN-stimulated gene 15 protein (ISG15) or IFN-gamma-inducible chemokine CXCL-10 protein expression are diminished in S6k1/S6k2 double-knockout mouse embryonic fibroblasts. In addition, IFN-alpha-inducible ISG15 protein expression is blocked by eIF4B or eIF3A knockdown, establishing a requirement for these proteins in mRNA translation/protein expression by IFNs. Importantly, the generation of IFN-dependent growth inhibitory effects on primitive leukemic progenitors is dependent on activation of the S6K/eIF4B or RSK/eIF4B pathway. Taken together, our findings establish critical roles for S6K and RSK in the induction of IFN-dependent biological effects and define a key regulatory role for eIF4B as a common mediator and integrator of IFN-generated signals from these kinases.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it