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Record W2136345561 · doi:10.1091/mbc.e03-08-0625

Countercurrent Distribution of Two Distinct SNARE Complexes Mediating Transport within the Golgi Stack

2004· article· en· W2136345561 on OpenAlexfundno aff
Allen Volchuk, Mariella Ravazzola, Alain Perrelet, William Eng, Maurizio Di Liberto, Oleg Varlamov, Masayoshi Fukasawa, Thomas Engel, Thomas Söllner, James E. Rothman, Lelio Orci

Bibliographic record

VenueMolecular Biology of the Cell · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsnot available
FundersMedical Research Council CanadaNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsGolgi apparatusSyntaxinBiologySNARE complexCell biologyProtein subunitBiophysicsLipid bilayer fusionMembrane proteinMembraneBiochemistryGeneEndoplasmic reticulum

Abstract

fetched live from OpenAlex

Genetic and biochemical evidence has established that a SNARE complex consisting of syntaxin 5 (Sed5)-mYkt6 (Ykt6)-GOS28 (Gos1)-GS15 (Sft1) is required for transport of proteins across the Golgi stack in animals (yeast). We have utilized quantitative immunogold labeling to establish the cis-trans distribution of the v-SNARE GS15 and the t-SNARE subunits GOS28 and syntaxin 5. Whereas the distribution of the t-SNARE is nearly even across the Golgi stack from the cis to the trans side, the v-SNARE GS15 is present in a gradient of increasing concentration toward the trans face of the stack. This contrasts with a second distinct SNARE complex, also required for intra-Golgi transport, consisting of syntaxin 5 (Sed5)-membrin (Bos1)-ERS24 (Sec22)-rBet1 (Bet1), whose v-(rBet1) and t-SNARE subunits (membrin and ERS24), progressively decrease in concentration toward the trans face. Transport within the stack therefore appears to utilize countercurrent gradients of two Golgi SNAREpins and may involve a mechanism akin to homotypic fusion.

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 score0.058
Threshold uncertainty score0.436

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 head0.239
Teacher spread0.231 · 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

Citations100
Published2004
Admission routes1
Has abstractyes

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