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Record W2239396023 · doi:10.1111/tra.12374

Calnuc Function in Endosomal Sorting of Lysosomal Receptors

2016· article· en· W2239396023 on OpenAlexafffund
Heidi Larkin, Santiago Costantino, Matthew Seaman, Christine Lavoie

Bibliographic record

VenueTraffic · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-RosemontUniversité de Sherbrooke
FundersMedical Research CouncilNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsEndosomeBiologyCell biologySortingFunction (biology)ReceptorComputational biologyGeneticsIntracellularComputer science

Abstract

fetched live from OpenAlex

Calnuc is a ubiquitous Ca(2+)-binding protein present on the trans-Golgi network (TGN) and endosomes. However, the precise role of Calnuc in these organelles is poorly characterized. We previously highlighted the role of Calnuc in the transport of LRP9, a new member of a low-density lipoprotein (LDL) receptor subfamily that cycles between the TGN and endosomes. The objective of this study was to explore the role of Calnuc in the endocytic sorting of mannose-6-phosphate receptor (MPR) and Sortilin, two well-characterized lysosomal receptors that transit between the TGN and endosomes. Using biochemical and microscopy assays, we showed that Calnuc depletion [by small interfering RNA (siRNA)] causes the misdelivery to and degradation in lysosomes of cationic-independent mannose-6-phosphate receptor (CI-MPR) and Sortilin due to a defect in the endosomal recruitment of retromers, which are key components of the endosome-to-Golgi retrieval machinery. Indeed, we demonstrated that Calnuc depletion impairs the activation and membrane association of Rab7, a small G protein required for the endosomal recruitment of retromers. Overall, our data indicate a novel role for Calnuc in the endosome-to-TGN retrograde transport of lysosomal receptors through the regulation of Rab7 activity and the recruitment of retromers to endosomes.

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 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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 teacher head, 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

Citations11
Published2016
Admission routes2
Has abstractyes

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