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Record W2031451938 · doi:10.1039/c2fo10235h

Complexation of high methoxyl pectin with ethanol desolvated whey protein nanoparticles: physico-chemical properties and encapsulation behaviour

2012· article· en· W2031451938 on OpenAlexaff
İbrahim Gülseren, Fang Yuan, Milena Corredig

Bibliographic record

VenueFood & Function · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsWhey protein isolateChemistryNanoparticlePectinWhey proteinParticle sizeChemical engineeringDilutionEthanolAqueous solutionChromatographyDrop (telecommunication)Organic chemistryFood sciencePhysical chemistryThermodynamics

Abstract

fetched live from OpenAlex

Using a desolvation method, whey protein isolate (WPI) nanoparticles were prepared and mixed with high methoxyl pectin (HMP) solutions (DE 72.8) to form WPI-HMP supramolecular complexes at low pH. Aqueous dispersions containing 5% WPI at pH 9 were desolvated with ethanol, and then diluted in HMP solutions at pH 3. Changes in particle size of the HMP-WPI complexes were studied as a function of HMP concentration. Upon dilution of the WPI nanoparticles in 0.05% HMP at pH 3, the average apparent diameter (d(90)) was around 270 nm, and there were no differences with desolvation level. These nanoparticles would undergo coarsening with storage at room temperature. The complexes showed to withstand homogenization and although heating increased aggregation, the particle size of the heated suspensions improved after homogenization. In addition, the suspensions demonstrated higher interfacial pressures (measured by drop tensiometry) compared to the corresponding unprocessed, desolvated or heated WPI solutions, suggesting their employment as surface active ingredients. The encapsulation efficiency of the desolvated WPI suspensions and desolvated WPI-HMP complex suspensions was studied using a model hydrophilic dye. In all cases, appreciable amounts of dye molecule were encapsulated and retained by the nanoparticles during storage at pH 3.

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 score0.104
Threshold uncertainty score0.218

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 head0.056
GPT teacher head0.205
Teacher spread0.148 · 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

Citations12
Published2012
Admission routes1
Has abstractyes

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