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Record W2474612185 · doi:10.1128/mcb.00046-16

Growth of the Mammalian Golgi Apparatus during Interphase

2016· article· en· W2474612185 on OpenAlexafffund
Alex T.‐W. Sin, Rene E. Harrison

Bibliographic record

VenueMolecular and Cellular Biology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaCalifornia Institute of Technology
KeywordsGolgi apparatusInterphaseCell biologyBiologyOrganelleCell cycleMitosisCell divisionCell growthSecretory pathwayCell plateGolgi membraneEndoplasmic reticulumCellCytokinesisBiochemistry

Abstract

fetched live from OpenAlex

During the cell cycle, genetic materials and organelles are duplicated to ensure that there is sufficient cellular content for daughter cells. While Golgi growth in interphase has been observed in lower eukaryotes, the elaborate ribbon structure of the mammalian Golgi apparatus has made it challenging to monitor. Here we demonstrate the growth of the mammalian Golgi apparatus in its protein content and volume during interphase. Through ultrastructural analyses, physical growth of the Golgi apparatus was revealed to occur by cisternal elongation of the individual Golgi stacks. By examining the timing and regulation of Golgi growth, we established that Golgi growth starts after passage through the cell growth checkpoint at late G1 phase and continues in a manner highly correlated with cell size growth. Finally, by identifying S6 kinase 1 as a major player in Golgi growth, we revealed the coordination between cell size and Golgi growth via activation of the protein synthesis machinery in early interphase.

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)0.0010.001

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 head0.004
GPT teacher head0.196
Teacher spread0.192 · 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

Citations16
Published2016
Admission routes2
Has abstractyes

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