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Record W2179447207 · doi:10.1091/mbc.e15-02-0086

The Myopic-Ubpy-Hrs nexus enables endosomal recycling of Frizzled

2015· article· en· W2179447207 on OpenAlexafffund
Tirthadipa Pradhan‐Sundd, Esther M. Verheyen

Bibliographic record

VenueMolecular Biology of the Cell · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsSimon Fraser University
FundersCanadian Institutes of Health Research
KeywordsEndosomeFrizzledBiologyCell biologyWnt signaling pathwayUbiquitin ligaseUbiquitinGene knockdownTransmembrane proteinTransport proteinSignal transductionGeneticsReceptorIntracellularCell cultureGene

Abstract

fetched live from OpenAlex

Endosomal trafficking of signaling proteins plays an essential role in cellular homeostasis. The seven-pass transmembrane protein Frizzled (Fz) is a critical component of Wnt signaling. Although Wnt signaling is proposed to be regulated by endosomal trafficking of Fz, the molecular events that enable this regulation are not completely understood. Here we show that the endosomal protein Myopic (Mop) regulates Fz trafficking in the Drosophila wing disk by inhibiting the ubiquitination and degradation of Hrs. Deletion of Mop or Hrs results in endosomal accumulation of Fz and therefore reduced Wnt signaling. The in situ proximity ligation assay revealed a strong association between Mop and Hrs in the Drosophila wing disk. Overexpression of Hrs rescues the trafficking defect caused by mop knockdown. Mop aids in the maintenance of Ubpy, which deubiquitinates (and thus stabilizes) Hrs. In the absence of the ubiquitin ligase Cbl, Mop is dispensable. These findings support a previously unknown role for Mop in endosomal trafficking of Fz in Wnt-receiving cells.

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 communication0.0000.000
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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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

Citations14
Published2015
Admission routes2
Has abstractyes

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