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Record W6981080979

Diacylglycerol: mechanism and efficacy as a functional oil

2008· dissertation· en· W6981080979 on OpenAlexafffund

Bibliographic record

VenueMspace (University of Manitoba) · 2008
Typedissertation
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsUniversity of Manitoba
FundersHeart and Stroke Foundation of Canada
KeywordsLipogenesisOverweightPostprandialCrossover studyTriglycerideBody weightLipid metabolismEnergy expenditure
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Diaclyglycerol (DAG) oil has the potential as an effective weight control agent as well as an agent to modify overweight related complications. OBJECTIVE: We aim to examine the efficacy of DAG oil (Enova oilTM) on regulating energy expenditure (EE), fat oxidation, body composition, lipid profiles and hepatic lipogenesis in comparison with conventional oils. DESIGN: Twenty-six overweight hypertriglyceridemic women consumed DAG or control oil for 28 days separated by a 4-week washout period using a randomized crossover design. Forty grams of either DAG or control oil were consumed daily by each study subject. RESULTS: DAG oil consumption for a period of 4-week does not alter total EE, fat oxidation, lean mass, fasting lipid profile or fatty acids synthesis rate, but effectively reduces (p<0.05) body weight and adiposity. CONCLUSION: DAG oil maybe an useful agent in the battle against obesity. However, its body weight/composition control effects are not from increasing of lean mass, or postprandial EE and fat oxidation. The consumption of DAG oil for a period of 4-week does not necessarily modify fasting lipid profiles or hepatic lipogenesis to reduce risk of coronary heart diseases in overweight hypertriglyceridemic subjects.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.921
Threshold uncertainty score1.000

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 head0.015
GPT teacher head0.208
Teacher spread0.194 · 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 designBench or experimental
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
Published2008
Admission routes2
Has abstractyes

Explore more

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