Bibliographic record
Abstract
PURPOSE OF REVIEW: In this review we discuss the postprandial pathophysiological mechanisms that promote vascular disease, the evidence for a role of postprandial lipaemia (PPL) in vascular disease and the effect of modifiable and nonmodifiable factors in PPL. RECENT FINDINGS: PPL refers to the dynamic changes in serum lipids and lipoproteins (mainly in serum triglycerides) that occur after a fat load or a meal. Recent data indicate that postprandial or nonfasting triglyceride levels are better predictors of cardiovascular risk, suggesting that efficiency of postprandial handling of triglyceride-rich lipoproteins plays a role in the causation of vascular disease. SUMMARY: The recent finding that postprandial serum triglyceride levels are even better than fasting serum triglyceride levels as predictors of vascular disease indicate that it is better to measure an index of triglyceride-rich lipoproteins (in most cases serum triglyceride levels) in the postprandial period than in the postabsorptive fasting state. Moreover, by the time the postabsorptive state is reached, some of these proatherogenic triglyceride-rich lipoprotein changes may be missed in the measurement.
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 | 0.001 | 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) | 0.007 | 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".