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Record W2040094608 · doi:10.1002/qua.24015

Temperature dependence of the molecular conformations of dilauroyl phosphatidylcholine: A density functional study

2012· article· en· W2040094608 on OpenAlexafffund
Tzonka Mineva, Saïlaja Krishnamurty, Dennis R. Salahub, Annick Goursot

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaGrand Équipement National De Calcul Intensif
KeywordsMolecular dynamicsChemistryPhosphatidylcholineChemical physicsIntramolecular forceAlkaneDensity functional theoryMoleculeLipid bilayerComputational chemistryHydrocarbonStereochemistryMembranePhospholipidOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Born–Oppenheimer molecular dynamics (BOMD) in combination with density functional theory, augmented with a damped empirical dispersion term, has been used to study the behavior of dilauroyl phosphatidylcholine (DLPC) isomers with temperature. In contrast to dimyristoyl phosphatidylcholine (DMPC), the BOMD results show the presence of various conformations at different temperatures. The molecular order–disorder process, quantified by the distance‐fluctuation criterion as a function of temperature, is characterized by two transitions. This is in line with the known two‐phase transitions of DLPC bilayers, involving trans to gauche conformational changes in the alkane chains. The different temperature dependence of the DLPC and DMPC molecules suggests that the experimentally observed unusual dynamics of DLPC bilayers compared to that of longer chain lipids is governed to a large extent by the intramolecular dynamics. A first‐principles methodology applied at the molecular level can thus be an appropriate tool for microscopic analysis of the order–disorder transitions, which are related to the molecular structural transformations within large assemblies. © 2012 Wiley Periodicals, Inc.

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 score0.002
Threshold uncertainty score0.304

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 head0.262
Teacher spread0.253 · 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

Citations7
Published2012
Admission routes2
Has abstractyes

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