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Record W1971082304 · doi:10.4161/trla.28109

Co-translational mechanisms of quality control of newly synthesized polypeptides

2014· review· en· W1971082304 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTranslation · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsRibosomeProteasomeUbiquitinProtein foldingTranslation (biology)Protein biosynthesisFolding (DSP implementation)Cell biologyChemistryBiochemistryMessenger RNABiologyRNAGene

Abstract

fetched live from OpenAlex

During protein synthesis, nascent polypeptides emerge from ribosomes to fold into functional proteins. Misfolding of newly synthesized polypeptides (NSPs) at this stage leads to their aggregation. These misfolded NSPs must be expediently cleared to circumvent the deleterious effects of protein aggregation on cell physiology. To this end, a sizable portion of NSPs are ubiquitinated and rapidly degraded by the proteasome. This suggests the existence of co-translational mechanisms that play a pivotal role in the quality control of NSPs. It is generally thought that ribosomes play a central role in this process. During mRNA translation, ribosomes sense errors that lead to the accumulation of aberrant polypeptides, and serve as a hub for protein complexes that are required for optimal folding and/or proteasome-dependent degradation of misfolded polypeptides. In this review, we discuss recent findings that shed light on the molecular underpinnings of the co-translational quality control of NSPs.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.893
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.051
GPT teacher head0.341
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it