The diversity, plasticity, and adaptability of cap-dependent translation initiation and the associated machinery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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.
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.
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) | 0.001 | 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 | 0.000 |
| 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