UBE2O remodels the proteome during terminal erythroid differentiation
Bibliographic record
Abstract
Removing orphan proteins from the system The degradation of excess subunits of protein complexes is a major quality-control problem for the cell. How such “orphans” are recognized and tagged for degradation is poorly understood. Two papers identify a protein quality-control pathway that acts on some of the most abundant protein complexes in the human body: hemoglobin and ribosomes (see the Perspective by Hampton and Dargemont). Yanagitani et al. show that the central player in this process is an unusual enzyme (UBE2O) that recognizes substrates and tags them for destruction. Other quality-contr ol pathways tend to use separate factors for target selection (often a chaperone), ubiquitin donation (an E2), and ubiquitin conjugati on (an E3). Encoding all three activities in a single factor whose function can be reconstituted in a purified system provides a tractable route to detailed mechanistic and structural dissection. Nguyen et al. show the importance of the UBE2O pathway in the differentiation of red blood cells. Science , this issue p. 472 , p. eaan0218 ; see also p. 450
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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".