The ER Glycoprotein Quality Control System
Bibliographic record
Abstract
The endoplasmic reticulum (ER) is the major site for folding and sorting of newly synthesized secretory cargo proteins. One central regulator of this process is the quality control machinery, which retains and ultimately disposes of misfolded secretory proteins before they can exit the ER. The ER quality control process is highly effective and mutations in cargo molecules are linked to a variety of diseases. In mammalian cells, a large number of secretory proteins, whether membrane bound or soluble, are asparagine (N)-glycosylated. Recent attention has focused on a sugar transferase, UDP-Glucose: glycoprotein glucosyl transferase (UGGT), which is now recognized as a constituent of the ER quality control machinery. UGGT is capable of sensing the folding state of glycoproteins and attaches a single glucose residue to the Man9GlcNAc2 glycan of incompletely folded or misfolded glycoproteins. This enables misfolded glycoproteins to rebind calnexin and reenter productive folding cycles. Prolonging the time of glucose addition on misfolded glycoproteins ultimately results in either the proper folding of the glycoprotein or its presentation to an ER associated degradation machinery.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.006 |
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".