The role of eukaryotic initiation factor 5B (eIF5B) in cell cycle regulation
Bibliographic record
Abstract
Gene expression is critically regulated at the transcriptional, translational, and post-translational levels. Dysregulation and altered mechanisms of translational control have significant consequences in processes including cell growth, cell death, cell proliferation, and maturation. Initiation is the rate- limiting step of translation, which is inhibited under physiological stress conditions. During the integrated stress response, the α subunit of eukaryotic initiation factor 2 (eIF2) is phosphorylated. This phosphorylation attenuates general translation, by preventing the reformation of the necessary ternary complex. Despite the attenuation of general translation, certain mRNAs containing upstream open reading frames (uORFs) are favorably translated during this condition. uORFs are mRNA elements with a start codon in the 5’ UTR that is out-of-frame with the main coding sequence. Bioinformatic studies have shown 49% of human transcripts to contain uORFs. Preliminary data suggests that the depletion of eIF5B parallels the effects of phosphorylation of eIF2α. eIF5B depletion has been observed to inhibit global translation, while enhancing the translation of certain uORF-containing mRNAs. The Thakor lab has shown the protein p27 to be upregulated when eIF5B is knocked down in U343 (human glioblastoma multiforme) cells. As p27 is a cyclin-dependent kinase inhibitor (CKI), which controls cell progression from the G1 to S phase, this suggests a significant role for eIF5B in the cell cycle. However, eIF5B depletion has been observed to not have significant effects on the cyclin-dependent kinase inhibitor: p21. Further, PI staining and flow cytometric analysis have demonstrated that eIF5B does not have any significant effects on the cell cycle. This data suggests that eIF5B has a significant role in the regulation of p27, but does not contribute to cell cycle regulation. *Indicates presenter
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".