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Record W4392785690 · doi:10.1098/rspa.2023.0545

Contact-line bending energy controls phospholipid vesicle adhesion

2024· article· lv· W4392785690 on OpenAlexafffund
Reghan J. Hill, Adel Al-Amodi

Bibliographic record

VenueProceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2024
Typearticle
Languagelv
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVesicleAdhesionBendingPhospholipidLine (geometry)Materials scienceBiophysicsChemistryComposite materialBiologyMembraneGeometryBiochemistryMathematics

Abstract

fetched live from OpenAlex

Phospholipid bilayer bending energy is often discarded in the analysis of vesicle adhesion on the basis of a dimensionless parameter w = − Δ U R 0 2 / κ b ≫ 1 (interaction energy Δ U , spherical radius R 0 , bending rigidity κ b ), considered a regime of strong adhesion. In this study, we propose a model by which bending energy in a singular proximity of the contact line balances the adhesion energy. This is developed for a regime in which the membrane correlation length ξ is small compared with the vesicle radius R 0 , so a spherical cap with circular footprint presents an effective contact angle θ . Experiments are conducted in which the adhesion of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) vesicles to hyaluronic acid hydrogel substrates is controlled by tuning the van der Waals attraction with systematic change in the hydrogel concentration. Theoretical interpretation of the data furnishes a dimensionless model parameter α ≈ 2 – 10 for contact angles θ ≈ 20 – 80 ∘ , beyond which vesicles collapse into discs. We show that the van der Waals interaction energy varies in the range − Δ U ≈ 0.14 – 0.68 μ J m − 2 in response to varying the hydrogel concentration in a range c ha ≈ 2 – 10 %. The analysis provides a foundation for exploring vesicle–hydrogel interactions with electro-steric influences; these are poorly understood but pertinent in a wide variety of biological and technological applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.002

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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Royal Society A Mathematical Physical and Engineering SciencesSame topicLipid Membrane Structure and BehaviorFrench-language works237,207