The diversity, plasticity, and adaptability of cap-dependent translation initiation and the associated machinery
Bibliographic record
Abstract
Translation initiation is a critical facet of gene expression with important impacts that underlie cellular responses to stresses and environmental cues. Its dysregulation in many diseases position this process as an important area for the development of new therapeutics. The gateway translation factor eIF4E is typically considered responsible for ‘global’ or ‘canonical’ m7G cap-dependent translation. However, eIF4E impacts translation of specific transcripts rather than the entire translatome. There are many alternative cap-dependent translation mechanisms that also contribute to the translation capacity of the cell. We review the diversity of these, juxtaposing more recently identified mechanisms with eIF4E-dependent modalities. We also explore the multiplicity of functions played by translation factors, both within and outside protein synthesis, and discuss how these differentially contribute to their ultimate physiological impacts. For comparison, we discuss some modalities for cap-independent translation. In all, this review highlights the diverse mechanisms that engage and control translation in eukaryotes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".