The Role of Food Peptides in Lipid Metabolism during Dyslipidemia and Associated Health Conditions
Bibliographic record
Abstract
Animal and human clinical studies have demonstrated the ability of dietary food proteins to modulate endogenous lipid levels during abnormal lipid metabolism (dyslipidemia). Considering the susceptibility of proteins to gastric proteolytic activities, the hypolipidemic functions of proteins are possibly due, in part, to their peptide fragments. Food-derived peptides may directly modulate abnormal lipid metabolism in cell cultures and animal models of dyslipidemia. The peptides are thought to act by perturbing intestinal absorption of dietary cholesterol and enterohepatic bile acid circulation, and by inhibiting lipogenic enzymatic activities and gene expression in hepatocytes and adipocytes. Recent evidence indicates that the hypolipidemic activities of some peptides are due to activation of hepatic lipogenic transcription factors. However, detailed molecular mechanisms and structural requirements of peptides for these activities are yet to be elucidated. As hypolipidemic peptides can be released during enzymatic food processing, future studies can explore the prospects of combating metabolic syndrome and associated complications using peptide-rich functional food and nutraceutical products.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".