MétaCan
Menu
Back to cohort
Record W2029167074 · doi:10.1083/jcb.201211147

The dynamics of engineered resident proteins in the mammalian Golgi complex relies on cisternal maturation

2013· article· en· W2029167074 on OpenAlexfundno aff
Riccardo Rizzo, Seetharaman Parashuraman, Peppino Mirabelli, Claudia Puri, John M. Lucocq, Alberto Luini

Bibliographic record

VenueThe Journal of Cell Biology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsnot available
FundersAssociazione Italiana per la Ricerca sul CancroInstitute of GeneticsAriad Pharmaceuticals
KeywordsCisternaGolgi apparatusBiologyEndoplasmic reticulumCell biologySecretory pathwayCompartment (ship)Transport proteinSecretory proteinAxoplasmic transportSecretionBiochemistry

Abstract

fetched live from OpenAlex

After leaving the endoplasmic reticulum, secretory proteins traverse several membranous transport compartments before reaching their destinations. How they move through the Golgi complex, a major secretory station composed of stacks of membranous cisternae, is a central yet unsettled issue in membrane biology. Two classes of mechanisms have been proposed. One is based on cargo-laden carriers hopping across stable cisternae and the other on "maturing" cisternae that carry cargo forward while progressing through the stack. A key difference between the two concerns the behavior of Golgi-resident proteins. Under stable cisternae models, Golgi residents remain in the same cisterna, whereas, according to cisternal maturation, Golgi residents recycle from distal to proximal cisternae via retrograde carriers in synchrony with cisternal progression. Here, we have engineered Golgi-resident constructs that can be polymerized at will to prevent their recycling via Golgi carriers. Maturation models predict the progress of such polymerized residents through the stack along with cargo, but stable cisternae models do not. The results support the cisternal maturation mechanism.

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)0.001
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 score0.179
Threshold uncertainty score0.150

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.217
Teacher spread0.207 · 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

Citations71
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Cell BiologySame topicCellular transport and secretionFrench-language works237,207