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Record W2115614955 · doi:10.1096/fj.13-241158

Dynamics of KRas on endosomes: involvement of acidic phospholipids in its association

2014· article· en· W2115614955 on OpenAlexaff
Mariona Gelabert‐Baldrich, David Soriano‐Castell, Marı́a Calvo, Albert Lu, Arnau Viña‐Vilaseca, Carles Rentero, Albert Pol, Sergio Grinstein, Carlos Enrich, Francesc Tebar

Bibliographic record

VenueThe FASEB Journal · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsHospital for Sick Children
FundersMinisterio de Ciencia e Innovación
KeywordsEndosomeAssociation (psychology)ChemistryDynamics (music)Cell biologyBiochemistryBiologyPsychologyReceptor

Abstract

fetched live from OpenAlex

The endocytic compartment is emerging as a functional platform for controlling important cellular processes. We have found that ∼10 to 15% of total KRas, a protein that is frequently mutated in cancer, is present on endosomes, independent of its activation state. The dynamics of GFP-KRas wild-type (WT) and constitutively active or inactive mutants on endosomes were analyzed by fluorescence recovery after photobleaching (FRAP) microscopy. The measurements revealed an extraordinarily fast recovery of KRas WT [half-time (HT), ∼1.3 s] compared to HRas, Rab5, and EGFR, with the active KRasG12V mutant being significantly faster and more mobile (HT, ∼1 s, and ∼82% of exchangeable fraction) than the inactive KRasS17N (HT, ∼1.6 s, and ∼60% of exchangeable fraction). KRas rapidly switches from the cytoplasm to the endosomal membranes by an electrostatic interaction between its polybasic region and the endosomal acidic phospholipids, mainly phosphatidylserine.-Gelabert-Baldrich, M., Soriano-Castell, D., Calvo, M., Lu, A., Viña-Vilaseca, A., Rentero, C., Pol, A., Grinstein, S. Enrich, C., Tebar, F. Dynamics of KRas on endosomes: involvement of acidic phospholipids in its association.

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 score0.011
Threshold uncertainty score0.211

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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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

Citations20
Published2014
Admission routes1
Has abstractyes

Explore more

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