Novel Role of Enteral Monosaccharides in Intestinal Lipoprotein Production in Healthy Humans
Bibliographic record
Abstract
OBJECTIVE: Overproduction of triglyceride-rich lipoproteins (TRLs) by liver and intestine contributes to hypertriglyceridemia and may increase cardiovascular risk. Dietary carbohydrates, especially fructose, have been shown to amplify postprandial lipemia but little is known about its effect on intestinal TRL particle production. Here, we examined intestinal and hepatic TRL particle production in response to enteral glucose or fructose in the presence of enteral lipid. APPROACH AND RESULTS: In 2 randomized studies, 4 to 6 weeks apart, 7 healthy male subjects received intraduodenal infusion of Intralipid plus saline or glucose. TRL-apolipoprotein (apo) B48 and apoB100 kinetics were assessed under pancreatic clamp conditions. In a separate study of another 7 subjects under similar conditions, glucose was replaced by fructose. When coinfused with Intralipid into the duodenum, glucose markedly stimulated TRL-apoB48 production (P<0.01), with a concomitant moderate increase in fractional clearance (P<0.05), resulting in net elevation of TRL-apoB48 concentration. TRL-apoB100 concentration, fractional clearance, and production were not significantly affected by glucose. When glucose was replaced by fructose, both TRL-apoB100 and apoB48 production (P<0.05), but not fractional clearance, were enhanced compared with Intralipid alone. CONCLUSIONS: These results reveal a novel role of monosaccharides in acutely enhancing intestinal lipoprotein particle production, thereby aggravating hyperlipidemia.
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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 | 0.000 |
| 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".