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Record W2046138985 · doi:10.1126/science.1152066

Membrane Phosphatidylserine Regulates Surface Charge and Protein Localization

2008· article· en· W2046138985 on OpenAlexaff
Tony Yeung, Gary E. Gilbert, Jialan Shi, John R. Silvius, András Kapùs, Sergio Grinstein

Bibliographic record

VenueScience · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsMcGill UniversityHospital for Sick ChildrenSt. Michael's Hospital
Fundersnot available
KeywordsPhosphatidylserineEndocytic cyclePhospholipid scramblaseEndosomeCytosolMembraneCell biologyMembrane proteinChemistryTransmembrane proteinEndocytosisSurface chargePhospholipidExocytosisBiophysicsBiochemistryBiologyCellEnzymeReceptor

Abstract

fetched live from OpenAlex

Electrostatic interactions with negatively charged membranes contribute to the subcellular targeting of proteins with polybasic clusters or cationic domains. Although the anionic phospholipid phosphatidylserine is comparatively abundant, its contribution to the surface charge of individual cellular membranes is unknown, partly because of the lack of reagents to analyze its distribution in intact cells. We developed a biosensor to study the subcellular distribution of phosphatidylserine and found that it binds the cytosolic leaflets of the plasma membrane, as well as endosomes and lysosomes. The negative charge associated with the presence of phosphatidylserine directed proteins with moderately positive charge to the endocytic pathway. More strongly cationic proteins, normally associated with the plasma membrane, relocalized to endocytic compartments when the plasma membrane surface charge decreased on calcium influx.

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 score0.004

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 communication0.0010.000
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 head0.008
GPT teacher head0.229
Teacher spread0.221 · 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

Citations1,111
Published2008
Admission routes1
Has abstractyes

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