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Record W2802938056 · doi:10.5650/jos.ess17221

Delivery of Curcumin Using Skim Milk or Oil in Water Emulsions: Effect of the Matrices on Cellular Uptake

2018· review· en· W2802938056 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.

Bibliographic record

VenueJournal of Oleo Science · 2018
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicMicroencapsulation and Drying Processes
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCurcuminEmulsionChemistrySkimmed milkSpray dryingFood scienceChromatographyOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

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.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.825
Threshold uncertainty score0.202

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.059
GPT teacher head0.318
Teacher spread0.258 · 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