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Record W2072890050 · doi:10.1021/bm900989y

Elaboration and Characterization of Soy/Zein Protein Microspheres for Controlled Nutraceutical Delivery

2009· article· en· W2072890050 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiomacromolecules · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsNutraceuticalSoy proteinChemistrySwellingKineticsWhey proteinControlled releaseWhey protein isolateChemical engineeringCrystallinityChromatographyFood science

Abstract

fetched live from OpenAlex

Microspheres (15-25 microm) of soy protein isolate (SPI), zein, and SPI/zein blends were prepared using a cold gelation method as possible delivery systems for nutraceutical products. Microsphere matrix crystalline structure, swelling behavior, and nutrient load release kinetics in simulated gastrointestinal fluids were investigated. SPI microspheres showed early burst release of the model nutrient, whereas zein microspheres showed very slow release in both simulated gastric and intestinal fluids. Blending of SPI and zein provides a convenient method of adjusting the hydrophobicity and crystallinity of the protein matrix and hence its swelling behavior and in vivo nutrient release kinetics. Diffusion plays a major role in regulating nutrient release. SPI/zein microspheres blended at ratios of 5:5 and 3:7 showed near zero-order release kinetics over the test period in simulated intestinal buffer and thus have potential as delivery vehicles for nutraceutical products in functional foods.

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 score0.031
Threshold uncertainty score0.192

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 head0.225
Teacher spread0.212 · 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