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Record W2074551088 · doi:10.4149/gpb_2009_02_117

What determines the thickness of a biological membrane

2009· article· en· W2074551088 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.

Bibliographic record

VenueGeneral Physiology and Biophysics · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of GuelphBrock UniversityAtomic Energy (Canada)National Research Council CanadaCanadian Nuclear Laboratories
Fundersnot available
KeywordsMembraneLipid bilayerBilayerPhospholipidNeutron diffractionChemistryBiological membraneCholesterolCrystallographyFunction (biology)BiophysicsChemical physicsBiochemistryBiology

Abstract

fetched live from OpenAlex

Membrane thickness is thought to play a key role in protein function. Thus understanding the cell's ability to modulate the thickness of its membranes is essential in elucidating the structure/function relationship in biological membranes. We have investigated the influence of cholesterol on the structure of "thin" (diC14:1PC) and "thick" (diC22:1PC) phospholipid bilayers using oriented multibilayers and small angle neutron diffraction. Neutron contrast variation was used to determine the structure factors and the distribution of water across the bilayers. We found that in response to cholesterol, bilayer thickness changed in a similar fashion in both systems. The thickening of bilayers was rationalized in terms of cholesterol's ordering effect on the lipid's acyl chains, which dominates over the other option of rectifying the hydrophobic mismatch, surprisingly even in the case of diC22:1PC and cholesterol.

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 score0.020
Threshold uncertainty score0.353

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 head0.013
GPT teacher head0.255
Teacher spread0.241 · 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