Diacylglycerol: mechanism and efficacy as a functional oil
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".