Complexation of high methoxyl pectin with ethanol desolvated whey protein nanoparticles: physico-chemical properties and encapsulation behaviour
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".