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Record W2091161919 · doi:10.1073/pnas.1311029111

Sequential breakdown of 3-phosphorylated phosphoinositides is essential for the completion of macropinocytosis

2014· article· en· W2091161919 on OpenAlexaff
Masashi Maekawa, Terasaka Shimpei, Yasuhiro Mochizuki, Katsuhisa Kawai, Yuka Ikeda, Nobukazu Araki, Edward Y. Skolnik, Tomohiko Taguchi, Hiroyuki Arai

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsSt. Michael's Hospital
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical Sciences
KeywordsPinocytosisEndocytosisCell biologyEndocytic cyclePiBiologyPhosphatasePhosphorylationBiochemistryCell

Abstract

fetched live from OpenAlex

Macropinocytosis is a highly conserved endocytic process by which extracellular fluid and solutes are internalized into cells. Macropinocytosis starts with the formation of membrane ruffles at the plasma membrane and ends with their closure. The transient and sequential emergence of phosphoinositides PI(3,4,5)P3 and PI(3,4)P2 in the membrane ruffles is essential for macropinocytosis. By making use of information in the Caenorhabditis elegans mutants defective in fluid-phase endocytosis, we found that mammalian phosphoinositide phosphatase MTMR6 that dephosphorylates PI(3)P to PI, and its binding partner MTMR9, are required for macropinocytosis. INPP4B, which dephosphorylates PI(3,4)P2 to PI(3)P, was also found to be essential for macropinocytosis. These phosphatases operate after the formation of membrane ruffles to complete macropinocytosis. Finally, we showed that KCa3.1, a Ca(2+)-activated K(+) channel that is activated by PI(3)P, is required for macropinocytosis. We propose that the sequential breakdown of PI(3,4,5)P3 → PI(3,4)P2 → PI(3)P → PI controls macropinocytosis through specific effectors of the intermediate phosphoinositides.

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 score0.018
Threshold uncertainty score0.250

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 studies0.0000.001
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 head0.025
GPT teacher head0.280
Teacher spread0.256 · 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

Citations118
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicCellular transport and secretionFrench-language works237,207