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Record W1982956224 · doi:10.1126/science.1191542

Peripheral Protein Quality Control Removes Unfolded CFTR from the Plasma Membrane

2010· article· en· W1982956224 on OpenAlexafffund
Tsukasa Okiyoneda, Hervé Barrière, Miklós Bagdány, Wael M. Rabeh, Kai Du, Jörg Höhfeld, Jason C. Young, Gergely L. Lukács

Bibliographic record

VenueScience · 2010
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsEndoplasmic reticulumCell biologyUbiquitinCystic fibrosis transmembrane conductance regulatorEndoplasmic-reticulum-associated protein degradationMembrane proteinTransmembrane proteinChemistryUnfolded protein responseInternalizationProtein degradationBiochemistryBiologyCellMembrane

Abstract

fetched live from OpenAlex

Therapeutic efforts to restore biosynthetic processing of the cystic fibrosis transmembrane conductance regulator lacking the F508 residue (DeltaF508CFTR) are hampered by ubiquitin-dependent lysosomal degradation of nonnative, rescued DeltaF508CFTR from the plasma membrane. Here, functional small interfering RNA screens revealed the contribution of chaperones, cochaperones, and ubiquitin-conjugating and -ligating enzymes to the elimination of unfolded CFTR from the cell surface, as part of a peripheral protein quality-control system. Ubiquitination of nonnative CFTR was required for efficient internalization and lysosomal degradation. This peripheral protein quality-control mechanism probably participates in the preservation of cellular homeostasis by degrading damaged plasma membrane proteins that have escaped from the endoplasmic reticulum quality control or are generated by environmental stresses in situ.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.335
Teacher spread0.317 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations407
Published2010
Admission routes2
Has abstractyes

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