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Record W2597421957 · doi:10.3168/jds.2016-12236

Invited review: Milk phospholipid vesicles, their colloidal properties, and potential as delivery vehicles for bioactive molecules

2017· review· en· W2597421957 on OpenAlexafffund
Elena Arranz, Milena Corredig

Bibliographic record

VenueJournal of Dairy Science · 2017
Typereview
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsUniversity of Guelph
FundersDairy Farmers of OntarioFundación Alfonso Martín Escudero
KeywordsLiposomePhospholipidChemistryMembraneVesicleDrug deliveryBiophysicsBiochemistryBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

The milk fat globule membrane (MFGM) is a unique colloidal assembly of phospholipids and proteins, with numerous potential applications as functional ingredient. The phospholipid components of the MFGM are gaining interest as they are a useful matrix for use as a constituent of delivery systems such as liposomes. Liposomes formulated with milk phospholipids are becoming an alternative to other sources of phospholipids such as soybean or egg yolk. However, incorporation of phospholipids fractionated from the milk fat globule membrane in dairy products requires an in-depth understanding of the functional properties of phospholipids. In particular, it is critical to understand which factors play a role in their stability and bioefficacy as delivery systems. Moreover, chemical and physical modifications of phospholipid liposomes occurring during digestion and the fate of the encapsulated compounds are very important to understand. This review discusses recent findings on the structure and functionality of MFGM, the bioactivity of the phospholipids fraction, their utilization as delivery systems, and their stability through gastrointestinal transit.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.095
GPT teacher head0.353
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations51
Published2017
Admission routes2
Has abstractyes

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