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Record W4410351207 · doi:10.1016/j.foodhyd.2025.111536

Probing the particle formation and aggregation behaviour of gliadin in aqueous ethanol with ultra-small- and small-angle X-ray scattering

2025· article· en· W4410351207 on OpenAlexafffund
Katherine Petker, Fernanda Peyronel, David A. Pink, Iris J. Joye

Bibliographic record

VenueFood Hydrocolloids · 2025
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsSt. Francis Xavier UniversityUniversity of Guelph
FundersArgonne National LaboratoryOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaOffice of ScienceU.S. Department of Energy
KeywordsGliadinSmall-angle X-ray scatteringAqueous solutionParticle (ecology)ScatteringChemistryEthanolParticle sizeChemical engineeringSmall-angle scatteringMaterials scienceChemical physicsFood scienceOpticsPhysicsOrganic chemistryPhysical chemistryBiologyGluten

Abstract

fetched live from OpenAlex

Colloidal gliadin particles show promise for use as interface stabilizers and for the encapsulation and delivery of bioactive molecules in food systems. Gliadin particles can be produced with a simple liquid anti-solvent precipitation (LAS) technique. The dynamics of the protein interactions and conformational changes due to changes in solvent quality during LAS have yet to be fully unravelled. In this study, ultra-small- and small-angle x-ray scattering (USAXS/SAXS) were used to investigate the assembly of gliadin proteins into particles and aggregates throughout LAS. Three regimes of gliadin assembly were identified at high (50−70 v/v%), intermediate (30−40 v/v%), and low (12−20 v/v%) ethanol concentrations. At high ethanol concentrations, primary structural units were identified in the high-q region (q > 2 × 10 -2 Å -1 ), believed to be gliadin molecules with coiled structures (R g1 = 6−7 nm, P 1 ≈ 2). At intermediate ethanol concentrations, polydisperse protein structures were formed. At low ethanol concentrations, two hierarchical structural levels were identified, with gliadin particles (R g2 ≈ 200–500 nm, 3.5 < P 2 < 4) identified at low-q (q < 2 × 10 -2 Å -1 ) believed to be formed by the assembly of primary structural units which had similar size and shape to those identified in high ethanol samples. Analysis with Fourier-transform infrared spectroscopy indicated that gliadin underwent secondary structural changes, with an increase in intermolecular β-sheets as the solvent quality was reduced during particle formation. This multi-scale investigation provides insight into the structural changes and interactions that occur during gliadin particle production with LAS. • The unified fit model was used to identify hierarchical gliadin structures in ethanol. • Polymer coil primary scattering units were identified at high ethanol concentrations. • Primary scattering units assembled into particles at low ethanol concentrations. • Intermolecular β-sheet structures increased when particles were formed.

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)0.000
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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

Citations3
Published2025
Admission routes2
Has abstractno

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