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Record W2753277897 · doi:10.1039/c7cp03871b

Biomembrane solubilization mechanism by Triton X-100: a computational study of the three stage model

2017· article· en· W2753277897 on OpenAlexaff
Antonio Pizzirusso, Antonio De Nicola, G. J. A. Sevink, Andrea Correa, Michele Cascella, Toshihiro Kawakatsu, Mattia Rocco, Ying Zhao, Massimo Celino, Giuseppe Milano

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsCentre Casa
FundersAgenzia Nazionale per le Nuove Tecnologie, l'Energia e lo Sviluppo Economico SostenibileNorges Forskningsråd
KeywordsMembraneVesicleLipid bilayerMolecular dynamicsChemistryBilayerCurvatureBiological membraneSolubilizationPartition coefficientMembrane curvatureKinetic energyChemical physicsBiophysicsChromatographyComputational chemistryPhysicsBiochemistryGeometryClassical mechanics

Abstract

fetched live from OpenAlex

The solubilization mechanism of lipid membranes in the presence of Triton X-100 (TX-100) is investigated at molecular resolution using molecular dynamics (MD) simulations. Thanks to the large time and length scales accessible by the hybrid particle-field formulation of the models employed here, the complex process of membrane solubilization has been studied, with the goal of verifying the three stage model reported in the literature. DPPC lipid bilayers and vesicles have been studied at different concentrations of the TX-100 detergent employing coarse grained (CG) models. Systems up to ∼600.000 beads, corresponding to more than 2 millions heavy atoms, have been simulated. Moreover, in order to clarify several experimental pieces of evidence, both slow and fast detergent partition scenarios have been investigated. Flat and curved (vesicles) lipid bilayer surfaces, interacting with TX-100, have been considered to study the curvature effects on the detergent partition rate in the membrane. Shape and conformational changes of mixed DPPC/TX-100 vesicles, as a function of TX-100 content, have also been studied. In particular, high curvature surfaces, corresponding to a higher local TX-100 content, promote a membrane rupture. In flat lipid surfaces, on the time scale simulated the detergent partition is almost absent, following a different pathway of the solubilization membrane mechanism.

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 score0.018
Threshold uncertainty score0.802

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 science0.0010.000
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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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

Citations67
Published2017
Admission routes1
Has abstractyes

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