Dietary carbohydrates and intestinal lipoprotein production
Bibliographic record
Abstract
PURPOSE OF REVIEW: To review new evidence that dietary monosaccharides enhance intestinal chylomicron secretion. RECENT FINDINGS: There is abundant evidence linking diets that are high in carbohydrate content with hypertriglyceridemia. In addition, epidemiological studies reveal that the increase in dietary sugars and refined carbohydrates are associated with the rising prevalence of the metabolic syndrome and type 2 diabetes. Association studies, however, cannot prove causation. Mechanistic studies to date have focused on the link between carbohydrate ingestion and hepatic very low-density lipoprotein metabolism, with very little appreciation that dietary carbohydrates may also regulate intestinal lipid absorption and chylomicron secretion. We have recently studied this phenomenon in healthy humans and have shown that both glucose and fructose, infused concomitantly with a lipid emulsion directly into the duodenum and under conditions of a pancreatic clamp, stimulate chylomicron particle secretion. There are a paucity of data regarding the cellular and molecular mechanisms of this effect, which remains largely unknown and a matter of speculation. SUMMARY: Sugar in the diet enhances dietary fat absorption and chylomicron secretion. Whether this phenomenon contributes quantitatively to the well described hypertriglyceridemia that occurs with diets high in carbohydrate and low in fat requires further investigation, as does the underlying cellular mechanism. A thorough understanding of this phenomenon could provide useful information to optimize dietary guidelines.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".