Effects of Intranasal Insulin on Triglyceride-Rich Lipoprotein Particle Production in Healthy Men
Bibliographic record
Abstract
OBJECTIVE: Insulin administered directly into the brain acutely suppresses hepatic glucose production and triglyceride-rich lipoprotein (TRL) secretion in rodents. In addition, intranasally administered insulin, which selectively raises cerebrospinal fluid insulin concentration, suppresses hepatic glucose production in humans; however, its effect on TRL secretion in humans has not previously been examined. In this study, we examined whether intranasal insulin, administered at a dose that has previously been shown to suppress hepatic glucose production, modulates TRL particle secretion by the liver and intestine in humans. APPROACH AND RESULTS: Nine healthy, normolipidemic, and normoglycemic men participated in a study consisting of 2 randomized study arms. Subjects received intranasal lispro insulin (40 IU) or placebo. Because intranasal insulin results in a rapid and transient increase in systemic insulin concentration after administration, we matched systemic insulin concentrations in the 2 study arms by infusing lispro insulin intravenously for 30 minutes together with intranasal placebo administration. Apo (apolipoprotein) B100-containing (hepatically derived) and apoB48-containing (intestinally derived) TRL lipoprotein particle turnover were measured for the ensuing 10 hours under pancreatic clamp conditions and constant fed state, using stable isotope enrichment techniques and multicompartmental modeling. Under these experimental conditions, no significant effects of intranasal insulin versus placebo on TRL apoB100 or B48 concentrations, fractional catabolic rates, or production rates were observed. CONCLUSIONS: Insulin delivered intranasally at a dose that has been shown to raise cerebrospinal fluid insulin concentration and suppress hepatic glucose production does not affect TRL particle production by the liver and intestine in healthy men. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT03141827.
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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) | 0.001 | 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".