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Record W2168627804 · doi:10.1039/c4sm00372a

Acetylsalicylic acid (ASA) increases the solubility of cholesterol when incorporated in lipid membranes

2014· article· en· W2168627804 on OpenAlexaff
Richard J. Alsop, Matthew A. Barrett, Songbo Zheng, Hannah Dies, Maikel C. Rheinstädter

Bibliographic record

VenueSoft Matter · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsNational Research Council CanadaMcMaster University
Fundersnot available
KeywordsMembraneMembrane fluidityCholesterolChemistryLipid bilayerSolubilityBiophysicsBiochemistryOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Cholesterol has been well established as a mediator of cell membrane fluidity. By interacting with lipid tails, cholesterol causes the membrane tails to be constrained thereby reducing membrane fluidity, well known as the condensation effect. Acetylsalicylic acid (ASA), the main ingredient in aspirin, has recently been shown to increase fluidity in lipid bilayers by primarily interacting with lipid head groups. We used high-resolution X-ray diffraction to study both ASA and cholesterol coexisting in model membranes of dimyristoylphosphatidylcholine (DMPC). While a high cholesterol concentration of 40 mol% cholesterol leads to the formation of immiscible cholesterol bilayers, as was reported previously, increasing the amount of ASA in the membranes between 0 to 12.5 mol% was found to significantly increase the fluidity of the bilayers and dissolve the cholesterol plaques. We, therefore, present experimental evidence for an interaction between cholesterol and ASA on the level of the cell membrane at elevated levels of cholesterol and ASA.

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 score0.020
Threshold uncertainty score0.467

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 head0.230
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 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

Citations29
Published2014
Admission routes1
Has abstractyes

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