Lack of phospho-eIF4E worsens experimental colitis by inhibiting Treg suppressive activity
Bibliographic record
Abstract
Phosphorylation of eIF4E by MNK1/2 modulates protein synthesis by controlling the translation of specific mRNAs. Immune cells use the MNK1/2-eIF4E axis to adapt their gene expression in response to environmental cues, but its dysregulated activity promotes disease progression. While recent examples using cancer models have identified CD8 + T-cells as a conduit for the tumor-supporting role of the MNK1/2-eIF4E axis, the impact of phospho-eIF4E on CD4 + T-cell subsets, specifically regulatory T-cells, remains unclear. To fill this knowledge gap, we studied the impact of phospho-eIF4E-deficiency on Treg activity in mice in an inflammatory context using a model of murine colitis and in human PBMCs. We found that Tregs isolated from mice deficient for phospho-eIF4E (expressing a serine-to-alanine mutation at S209) had a diminished ability to control CD4 + T-cell proliferation and IFNγ secretion in vitro. We further report aggravated colitis in mice deficient in phospho-eIF4E accompanied by an increase in CD4 + T-cells expressing IFNγ and a reduction in Tregs in the mesenteric lymph nodes and colon. Mechanistically, T-cells lacking phospho-eIF4E show impaired differentiation into Tregs, and Tregs lacking phospho-eIF4E have reduced FoxP3 expression and diminished migration to the lymph nodes. Using human PBMCs, anti-CTLA-4, but not anti-PD-1, reduced the phospho-eIF4E-expressing Treg population. Taken together, these data highlight a role for phospho-eIF4E in Treg biology and in the control of inflammation. Not applicable.
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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) | 0.001 | 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) | 0.002 | 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".