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Record W3171749917

Sources, Production, and Clinical Treatments of Milk Fat Globule Membrane for Infant Nutrition and Well-Being

2020· article· en· W3171749917 on OpenAlexaff
Javier Fontecha, Lauren Brink, Steven S. Wu, Yves Pouliot, Francesco Visioli, Rafael Jiménez‐Flores

Bibliographic record

VenuePMC · 2020
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSphingolipidImmune systemMedicineInflammationPhysiologyGlycolipidImmunologyBiologyEndocrinologyBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Research on milk fat globule membrane (MFGM) is gaining traction. The interest is two-fold; on the one hand, it is a unique trilayer structure with specific secretory function. On the other hand, it is the basis for ingredients with the presence of phospho- and sphingolipids and glycoproteins, which are being used as food ingredients with valuable functionality, in particular, for use as a supplement in infant nutrition. This last application is at the center of this Review, which aims to contribute to understanding MFGM's function in the proper development of immunity, cognition, and intestinal trophism, in addition to other potential effects such as prevention of diseases including cardiovascular disease, impaired bone turnover and inflammation, skin conditions, and infections as well as age-associated cognitive decline and muscle loss. The phospholipid composition of MFGM from bovine milk is quite like human milk and, although there are some differences due to dairy processing, these do not result in a chemical change. The MFGM ingredients, as used to improve the formulation in different clinical studies, have indeed increased the presence of phospholipids, sphingolipids, glycolipids, and glycoproteins with the resulting benefits of different outcomes (especially immune and cognitive outcomes) with no reported adverse effects. Nevertheless, the precise mechanism(s) of action of MFGM remain to be elucidated and further basic investigation is warranted.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.613
Threshold uncertainty score0.328

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 head0.032
GPT teacher head0.326
Teacher spread0.294 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2020
Admission routes1
Has abstractyes

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