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Modulation of membrane curvature by peptides

2000· review· en· W2160045415 on OpenAlex
Richard M. Epand

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

VenueBiopolymers · 2000
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsMcMaster University
Fundersnot available
KeywordsChemistryLipid bilayer fusionFusionCurvatureMembraneMembrane curvatureBiophysicsPeptideLiposomeBiochemistryLipid bilayerGeometryBiology

Abstract

fetched live from OpenAlex

The fusion of two stable bilayers likely proceeds through intermediates in which the membrane acquires curvature. The insertion of peptides into the membrane will affect its curvature tendency. Studies with a number of small viral fusion peptides indicate that these peptides promote negative curvature at low concentration. This is in accord with the curvature requirements to initiate membrane fusion according to the stalk-pore model. Although a characteristic of fusion peptides, the promotion of negative curvature is only one of several mechanisms by which fusion proteins accelerate the rate of fusion. In addition, the fusion peptide itself, as well as other regions in the viral fusion protein, facilitates membrane fusion by mechanisms that are largely independent of curvature. Leakage of the internal aqueous contents of liposomes is another manifestation of the alteration of membrane properties. Peptides exhibit quite different relative potencies between fusion and leakage that is determined by the structure and mode of insertion of the peptide into the membrane.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.015
GPT teacher head0.290
Teacher spread0.275 · 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