It's not just a phase; ubiquitination in cytosolic protein quality control
Bibliographic record
Abstract
The accumulation of misfolded proteins is associated with numerous degenerative conditions, cancers and genetic diseases. These pathological imbalances in protein homeostasis (termed proteostasis), result from the improper triage and disposal of damaged and defective proteins from the cell. The ubiquitin-proteasome system is a key pathway for the molecular control of misfolded cytosolic proteins, co-opting a cascade of ubiquitin ligases to direct terminally damaged proteins to the proteasome via modification with chains of the small protein, ubiquitin. Despite the evidence for ubiquitination in this critical pathway, the precise complement of ubiquitin ligases and deubiquitinases that modulate this process remains under investigation. Whilst chaperones act as the first line of defence against protein misfolding, the ubiquitination machinery has a pivotal role in targeting terminally defunct cytosolic proteins for destruction. Recent work points to a complex assemblage of chaperones, ubiquitination machinery and subcellular quarantine as components of the cellular arsenal against proteinopathies. In this review, we examine the contribution of these pathways and cellular compartments to the maintenance of the cytosolic proteome. Here we will particularly focus on the ubiquitin code and the critical enzymes which regulate misfolded proteins in the cytosol, the molecular point of origin for many neurodegenerative and genetic diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".