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Record W3008239302 · doi:10.1083/jcb.201906130

Defining the subcellular distribution and metabolic channeling of phosphatidylinositol

2019· article· en· W3008239302 on OpenAlexfundno aff
Joshua G. Pemberton, Yeun Ju Kim, Jana Humpolíčková, Andrea Eisenreichová, Nivedita Sengupta, Dániel J. Tóth, Evžen Bouřa, Tamás Balla

Bibliographic record

VenueThe Journal of Cell Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentEuropean Regional Development FundNatural Sciences and Engineering Research Council of CanadaAkademie Věd České Republiky
KeywordsPhosphatidylinositolEndosomeCell biologyCytosolGolgi apparatusSubcellular localizationPiBiologyBiochemistryOrganellePhospholipase DSignal transductionEnzymeCytoplasmEndoplasmic reticulumIntracellular

Abstract

fetched live from OpenAlex

Phosphatidylinositol (PI) is an essential structural component of eukaryotic membranes that also serves as the common precursor for polyphosphoinositide (PPIn) lipids. Despite the recognized importance of PPIn species for signal transduction and membrane homeostasis, there is still a limited understanding of the relationship between PI availability and the turnover of subcellular PPIn pools. To address these shortcomings, we established a molecular toolbox for investigations of PI distribution within intact cells by exploiting the properties of a bacterial enzyme, PI-specific PLC (PI-PLC). Using these tools, we find a minor presence of PI in membranes of the ER, as well as a general enrichment within the cytosolic leaflets of the Golgi complex, peroxisomes, and outer mitochondrial membrane, but only detect very low steady-state levels of PI within the plasma membrane (PM) and endosomes. Kinetic studies also demonstrate the requirement for sustained PI supply from the ER for the maintenance of monophosphorylated PPIn species within the PM, Golgi complex, and endosomal compartments.

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 score0.027
Threshold uncertainty score0.172

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 head0.004
GPT teacher head0.205
Teacher spread0.200 · 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

Citations91
Published2019
Admission routes1
Has abstractyes

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