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Record W2973105130 · doi:10.1074/mcp.ra119.001645

BioID Performed on Golgi Enriched Fractions Identify C10orf76 as a GBF1 Binding Protein Essential for Golgi Maintenance and Secretion

2019· article· en· W2973105130 on OpenAlexafffund
Calvin J. Chan, Roberta Le, Kaylan Burns, Khadra Ahmed, Étienne Coyaud, Estelle Laurent, Brian Raught, Paul Melançon

Bibliographic record

VenueMolecular & Cellular Proteomics · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsUniversity of TorontoUniversity of Alberta
FundersCanadian Institutes of Health ResearchInstitute of GeneticsGovernment of Canada
KeywordsGolgi apparatusSecretionCell biologyBrefeldin ABiotinylationCOPISecretory pathwayGolgi membraneBiologyEndoplasmic reticulumChemistryBiochemistry

Abstract

fetched live from OpenAlex

The Golgi-specific Brefeldin-A resistance factor 1 (GBF1) is the only large GEF that regulates Arf activation at the cis- Golgi and is actively recruited to membranes on an increase in Arf-GDP. Recent studies have revealed that GBF1 recruitment requires one or more heat-labile and protease-sensitive protein factor(s) (Quilty et al. , 2018, J. Cell Science, 132). Proximity-dependent biotinylation (BioID) and mass spectrometry from enriched Golgi fractions identified GBF1 proximal proteins that may regulate its recruitment. Knockdown studies revealed C10orf76 to be involved in Golgi maintenance. We find that C10orf76 interacts with GBF1 and rapidly cycles on and off GBF1-positive Golgi structures. More importantly, its depletion causes Golgi fragmentation, alters GBF1 recruitment, and impairs secretion. Homologs were identified in most species, suggesting its presence in the last eukaryotic common ancestor.

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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.004

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 head0.005
GPT teacher head0.230
Teacher spread0.225 · 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

Citations27
Published2019
Admission routes2
Has abstractyes

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