Medium‐Chain Triglycerides Increase Energy Expenditure and Decrease Adiposity in Overweight Men
Bibliographic record
Abstract
OBJECTIVE: The objectives of this study were to compare the effects of diets rich in medium-chain triglycerides (MCTs) or long-chain triglycerides (LCTs) on body composition, energy expenditure, substrate oxidation, subjective appetite, and ad libitum energy intake in overweight men. RESEARCH METHODS AND PROCEDURES: Twenty-four healthy, overweight men with body mass indexes between 25 and 31 kg/m(2) consumed diets rich in MCT or LCT for 28 days each in a crossover randomized controlled trial. At baseline and after 4 weeks of each dietary intervention, energy expenditure was measured using indirect calorimetry, and body composition was analyzed using magnetic resonance imaging. RESULTS: Upper body adipose tissue (AT) decreased to a greater extent (p < 0.05) with functional oil (FctO) compared with olive oil (OL) consumption (-0.67 +/- 0.26 kg and -0.02 +/- 0.19 kg, respectively). There was a trend toward greater loss of whole-body subcutaneous AT volume (p = 0.087) with FctO compared with OL consumption. Average energy expenditure was 0.04 +/- 0.02 kcal/min greater (p < 0.05) on day 2 and 0.03 +/- 0.02 kcal/min (not significant) on day 28 with FctO compared with OL consumption. Similarly, average fat oxidation was greater (p = 0.052) with FctO compared with OL intake on day 2 but not day 28. DISCUSSION: Consumption of a diet rich in MCTs results in greater loss of AT compared with LCTs, perhaps due to increased energy expenditure and fat oxidation observed with MCT intake. Thus, MCTs may be considered as agents that aid in the prevention of obesity or potentially stimulate weight loss.
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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 | 0.001 |
| 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".