MétaCan
Menu
Back to cohort
Record W2324423253 · doi:10.1097/mol.0b013e3283613bb7

Recent advances in dietary proteins and lipid metabolism

2013· review· en· W2324423253 on OpenAlexaff
Dalia El Khoury, G. Harvey Anderson

Bibliographic record

VenueCurrent Opinion in Lipidology · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLipid metabolismBiochemistryIsoflavonesMetabolismAmino acidCholesterolChemistryBiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: There is growing interest in defining the dietary approaches for the management of lipid disorders. This review focuses on dietary proteins. RECENT FINDINGS: Increasing protein intake was coupled with improved lipid profiles in humans and animals. However, most studies increased the protein content by reducing that of fat or carbohydrate or both, making unclear the role of protein alone. Mechanisms of action differ with the sources of proteins, because of amino acid composition and bioactive peptides encrypted in their sequences. Soy protein was investigated the most, and many studies show that its consumption reduces blood cholesterol. The role of other constituents including isoflavones is debated. Short-term studies are consistent in showing lipid-lowering properties of whey proteins, attributed to their relative high content in branched chain amino acids. A limited number of studies, the majority being on animals, have shown hypocholesterolemic activities of fish proteins. SUMMARY: Dietary proteins regulate lipid metabolism in a manner dependent on their quantity and composition. There is a general consensus that proteins slow lipid absorption and synthesis, and promote lipid excretion. The benefits of dietary proteins remain to be confirmed in individuals with lipid abnormalities, for formulation of optimal dietary alternatives for the management of lipid disturbances.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.082
GPT teacher head0.380
Teacher spread0.298 · 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.

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

Citations62
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in LipidologySame topicProtein Hydrolysis and Bioactive PeptidesFrench-language works237,207