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Record W2137685927 · doi:10.1091/mbc.e08-03-0282

The SM Protein Car/Vps33A Regulates SNARE-mediated Trafficking to Lysosomes and Lysosome-related Organelles

2009· article· en· W2137685927 on OpenAlexfundno aff
Mohammed Akbar, Sanchali Ray, Helmut Krämer

Bibliographic record

VenueMolecular Biology of the Cell · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsnot available
FundersNational Eye InstituteNational Institutes of HealthBoston CollegeHospital for Sick ChildrenWelch Foundation
KeywordsEndosomeBiologyCell biologyLysosomeGolgi apparatusLipid bilayer fusionOrganelleSyntaxinMembrane proteinGeneticsBiochemistryMembraneEndoplasmic reticulum

Abstract

fetched live from OpenAlex

The SM proteins Vps33A and Vps33B are believed to act in membrane fusions in endosomal pathways, but their specific roles are controversial. In Drosophila, Vps33A is the product of the carnation (car) gene. We generated a null allele of car to test its requirement for trafficking to different organelles. Complete loss of car function is lethal during larval development. Eye-specific loss of Car causes late, light-independent degeneration of photoreceptor cells. Earlier in these cells, two distinct phenotypes were detected. In young adults, autophagosomes amassed indicating that their fusion with lysosomes requires Car. In eye discs, endocytosed receptors and ligands accumulate in Rab7-positive prelysosomal compartments. The requirement of Car for late endosome-to-lysosome fusion in imaginal discs is specific as early endosomes are unaffected. Furthermore, lysosomal delivery is not restored by expression of dVps33B. This specificity reflects the distinct pattern of binding to different Syntaxins in vitro: dVps33B predominantly binds the early endosomal Avl and Car to dSyntaxin16. Consistent with a role in Car-mediated fusion, dSyntaxin16 is not restricted to Golgi membranes but also present on lysosomes.

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 score0.010
Threshold uncertainty score0.584

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 head0.003
GPT teacher head0.197
Teacher spread0.194 · 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

Citations88
Published2009
Admission routes1
Has abstractyes

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