On the suppression of plasma nonesterified fatty acids by insulin during enhanced intravascular lipolysis in humans
Bibliographic record
Abstract
During the fasting state, insulin reduces nonesterified fatty acid (NEFA) appearance in the systemic circulation mostly by suppressing intracellular lipolysis in the adipose tissue. In the postprandial state, insulin may also control NEFA appearance through enhanced trapping into the adipose tissue of NEFA derived from intravascular triglyceride lipolysis. To determine the contribution of suppression of intracellular lipolysis in the modulation of plasma NEFA metabolism by insulin during enhanced intravascular triglyceride lipolysis, 10 healthy nonobese subjects underwent pancreatic clamps at fasting vs. high physiological insulin level with intravenous infusion of heparin plus Intralipid. Nicotinic acid was administered orally during the last 2 h of each 4-h clamp to inhibit intracellular lipolysis and assess insulin's effect on plasma NEFA metabolism independently of its effect on intracellular lipolysis. Stable isotope tracers of palmitate, acetate, and glycerol were used to assess plasma NEFA metabolism and total triglyceride lipolysis in each participant. The glycerol appearance rate was similar during fasting vs. high insulin level, but plasma NEFA levels were significantly lowered by insulin. Nicotinic acid significantly blunted the insulin-mediated suppression of plasma palmitate appearance and oxidation rates by approximately 60 and approximately 70%, respectively. In contrast, nicotinic acid did not affect the marked stimulation of palmitate clearance by insulin. Thus most of the insulin-mediated reduction of plasma NEFA appearance and oxidation can be explained by suppression of intracellular lipolysis during enhanced intravascular triglyceride lipolysis in healthy humans. Our results also suggest that insulin may affect plasma NEFA clearance independently of the suppression of intracellular 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 | 0.000 | 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 | 0.001 |
| 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".