eIF4E-Binding Proteins 1 and 2 Limit Macrophage Anti-Inflammatory Responses through Translational Repression of IL-10 and Cyclooxygenase-2
Bibliographic record
Abstract
Abstract Macrophages represent one of the first lines of defense during infections and are essential for resolution of inflammation following pathogen clearance. Rapid activation or suppression of protein synthesis via changes in translational efficiency allows cells of the immune system, including macrophages, to quickly respond to external triggers or cues without de novo mRNA synthesis. The translational repressors eIF4E-binding proteins 4E-BP1 and 4E-BP2 (4E-BP1/2) are central regulators of proinflammatory cytokine synthesis during viral and parasitic infections. However, it remains to be established whether 4E-BP1/2 play a role in translational control of anti-inflammatory responses. By comparing translational efficiencies of immune-related transcripts in macrophages from wild-type and 4E-BP1/2 double-knockout mice, we found that translation of mRNAs encoding two major regulators of inflammation, IL-10 and PG-endoperoxide synthase 2/cyclooxygenase-2, is controlled by 4E-BP1/2. Genetic deletion of 4E-BP1/2 in macrophages increased endogenous IL-10 and PGE2 protein synthesis in response to TLR4 stimulation and reduced their bactericidal capacity. The molecular mechanism involves enhanced anti-inflammatory gene expression (sIl1ra, Nfil3, Arg1, Serpinb2) owing to upregulation of IL-10–STAT3 and PGE2–C/EBPβ signaling. These data provide evidence that 4E-BP1/2 limit anti-inflammatory responses in macrophages and suggest that dysregulated activity of 4E-BP1/2 might be involved in reprogramming of the translational and downstream transcriptional landscape of macrophages during pathological conditions, such as infections and cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".