MétaCan
Menu
Back to cohort
Record W2908877984 · doi:10.1021/acs.jctc.8b00933

Cholesterol Flip-Flop in Heterogeneous Membranes

2019· article· en· W2908877984 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Chemical Theory and Computation · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanadian Institutes of Health ResearchAlberta Innovates - Health Solutions
KeywordsMembraneFlipCholesterolBilayerMolecular dynamicsWork (physics)Chemical physicsMoleculeFlip-flopMaterials scienceChemistryBiophysicsNanotechnologyComputational chemistryPhysicsOptoelectronicsBiochemistryBiologyThermodynamics

Abstract

fetched live from OpenAlex

Cholesterol is the most abundant molecule in the plasma membrane of mammals. Its distribution across the two membrane leaflets is critical for understanding how cells work. Cholesterol trans-bilayer motion (flip-flop) is a key process influencing its distribution in membranes. Despite extensive investigations, the rate of cholesterol flip-flop and its dependence on the lateral heterogeneity of membranes remain uncertain. In this work, we used atomistic molecular dynamics simulations to sample spontaneous cholesterol flip-flop events in a DPPC:DOPC:cholesterol mixture with heterogeneous lateral distribution of lipids. In addition to an overall flip-flop rate at the time scale of sub-milliseconds, we identified a significant impact of local environment on flip-flop rate. We discuss the atomistic details of the flip-flop events observed in our simulations.

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.

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 score0.007
Threshold uncertainty score0.232

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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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