Intravenous Glucose Acutely Stimulates Intestinal Lipoprotein Secretion in Healthy Humans
Bibliographic record
Abstract
OBJECTIVE: Increased production of intestinal triglyceride-rich lipoproteins (TRLs) contributes to dyslipidemia and increased risk of atherosclerotic cardiovascular disease in insulin resistance and type 2 diabetes. We have previously demonstrated that enteral glucose enhances lipid-stimulated intestinal lipoprotein particle secretion. Here, we assessed whether glucose delivered systemically by intravenous infusion also enhances intestinal lipoprotein particle secretion in humans. APPROACH AND RESULTS: On 2 occasions, 4 to 6 weeks apart and in random order, 10 healthy men received a constant 15-hour intravenous infusion of either 20% glucose to induce hyperglycemia or normal saline as control. Production of TRL-apolipoprotein B48 (apoB48, primary outcomes) and apoB100 (secondary outcomes) was assessed during hourly liquid-mixed macronutrient formula ingestion with stable isotope enrichment and multicompartmental modeling, under pancreatic clamp conditions to limit perturbations in pancreatic hormones (insulin and glucagon) and growth hormone. Compared with saline infusion, glucose infusion induced both hyperglycemia and hyperinsulinemia, increased plasma triglyceride levels, and increased TRL-apoB48 concentration and production rate (P<0.05), without affecting TRL-apoB48 fractional catabolic rate. No significant effect of hyperglycemia on TRL-apoB100 concentration and kinetic parameters was observed. CONCLUSIONS: Short-term intravenous infusion of glucose stimulates intestinal lipoprotein production. Hyperglycemia may contribute to intestinal lipoprotein overproduction in type 2 diabetes. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT02607839.
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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".