Control of intestinal lipoprotein secretion by dietary carbohydrates
Bibliographic record
Abstract
PURPOSE OF REVIEW: Dyslipidemia is a major risk factor for atherosclerotic cardiovascular disease (CVD). Lipoproteins secreted by the intestine can contribute to dyslipidemia and may increase risk for CVD. This review focuses on how dietary carbohydrates can impact the production of chylomicrons, thereby influencing plasma concentrations of triglycerides and lipoproteins. RECENT FINDINGS: Hypercaloric diets high in monosaccharides can exacerbate postprandial triglyceride concentration. In contrast, isocaloric substitution of monosaccharides into mixed meals has no clear stimulatory or inhibitory effect on postprandial triglycerides. Mechanistic studies with oral ingestion of carbohydrates or elevation of plasma glucose have demonstrated enhanced secretion of chylomicrons. The mechanisms underlying this modulation remain largely unknown but may include enhanced intestinal de novo lipogenesis and mobilization of intestinally stored lipids. SUMMARY: The studies reviewed here have implications for dietary recommendations regarding refined carbohydrate intake and prevention of CVD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.004 | 0.002 |
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".