Seven-day overfeeding enhances adipose tissue dietary fatty acid storage and decreases myocardial and skeletal muscle dietary fatty acid partitioning in healthy subjects
Bibliographic record
Abstract
Increased myocardial partitioning of dietary fatty acids (DFA) and decreased left ventricular (LV) function is associated with insulin resistance in prediabetes. We hypothesized that enhanced myocardial DFA partitioning and reduced LV function might be induced concomitantly with reduced insulin sensitivity upon a 7-day hypercaloric (+50% in caloric intake), high-saturated fat (~11%energy), and simple carbohydrates (~54%energy) diet (HIGHCAL) versus an isocaloric diet (ISOCAL) with a moderate amount of saturated fat (~8%energy) and carbohydrates (~50%energy). Thirteen healthy subjects (7 men/6 women) underwent HIGHCAL versus ISOCAL in a randomized crossover design, with organ-specific DFA partitioning and LV function measured using the oral 14( R,S)-[18F]fluoro-6-thia-heptadecanoic acid and [11C]acetate positron emission tomography methods at the end of both interventions. HIGHCAL induced a decrease in insulin sensitivity indexes with no significant change in body composition. HIGHCAL led to increased subcutaneous abdominal (+4.2 ± 1.6%, P < 0.04) and thigh (+2.4 ± 1.2%, P < 0.08) adipose tissue storage and reduced cardiac (−0.31 ± 0.11 mean standard uptake value [(SUV), P < 0.03] and skeletal muscle (−0.17 ± 0.08 SUV, P < 0.05) DFA partitioning without change in LV function. We conclude that early increase in adipose tissue DFA storage protects the heart and skeletal muscles from potential deleterious effects of DFA.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".