Delivery of Curcumin Using Skim Milk or Oil in Water Emulsions: Effect of the Matrices on Cellular Uptake
Bibliographic record
Abstract
To enhance the curcumin delivery in a variety of food grade matrices namely spray dried ethanolic curcumin in fresh skim milk (Spray dried Cu-SM), a fresh mixture of ethanolic curcumin and skim milk (Fresh Cu-SM) a powder mixture of curcumin and skim milk powder (Powder Cu-SMP) and oil in water emulsion (Emulsion) were studied. The cellular uptake of curcumin from the respective matrices was studied on Caco-2 cell monolayers. Spray dried Cu-SM showed higher encapsulation efficiency compared to a corresponding Powder Cu-SMP and an oil-in-water emulsion (40% oil) bearing curcumin. Furthermore, ethanolic administration of curcumin in spray dried form enhanced the cellular uptake of curcumin considerably higher than non-ethanolic samples (approx. 4 times). Overall, milk protein based vectors were found to perform better than emulsion samples. These findings highlighted the fact that curcumin uptake may be tailored by fine tuning of curcumin delivery vehicles which highlights possible application of powders as functional foods.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".