Basal and insulin-regulated free fatty acid and glucose metabolism in humans
Bibliographic record
Abstract
These studies were done to examine the effects of body composition, resting energy expenditure (REE), sex, and fitness on basal and insulin-regulated FFA and glucose metabolism. We performed 137 experiments in 101 nondiabetic, premenopausal women and men, ranging from low normal weight to class III obese (BMI 18.0-40.5 kg/m2). Glucose flux was measured using [6-(2)H2]glucose and FFA kinetics with [9,10-(3)H]oleate under either basal (74 experiments) or euglycemic hyperinsulinemic (1.0 mU.kg FFM(-1).min(-1)) clamp conditions (63 experiments). Consistent with our previous findings, REE and sex independently predicted basal FFA flux, whereas fat-free mass was the best predictor of basal glucose flux; in addition, percent body fat was independently and positively associated with basal glucose flux (total r2 = 0.52, P < 0.0001). Insulin-suppressed lipolysis remained significantly associated with REE (r = 0.25, P < 0.05), but percent body fat also contributed (total adjusted r2 = 0.36, P < 0.0001), whereas sex was not significantly related to insulin-suppressed FFA flux. Glucose disposal during hyperinsulinemia was independently associated with peak VO2, percent body fat, and FFA concentrations (total r2 = 0.63, P < 0.0001) but not with sex. We conclude that basal glucose production is independently related to both FFM and body fatness. In addition, hyperinsulinemia obscures the sex differences in FFA release relative to REE, but brings out the effects of fatness on lipolysis.
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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 | 0.001 |
| 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) | 0.001 | 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".