Obesity‐related Changes in High‐density Lipoprotein Metabolism
Bibliographic record
Abstract
Obesity is associated with a 3-or-more-fold increase in the risk of fatal and nonfatal myocardial infarction (1,2,3,4,5,6). The American Heart Association has reclassified obesity as a major, modifiable risk factor for coronary heart disease (7). The increased prevalence of premature coronary heart disease in obesity is attributed to multiple factors (8,9,10). A principal contributor to this serious morbidity is the alterations in plasma lipid and lipoprotein levels. The dyslipidemia of obesity is commonly manifested as high plasma triglyceride levels, low high-density lipoprotein cholesterol (HDLc), and normal low-density lipoprotein cholesterol (LDLc) with preponderance of small dense LDL particles (7,8,9,10). However, there is a considerable heterogeneity of plasma lipid profile in overweight and obese people. The precise cause of this heterogeneity is not entirely clear but has been partly attributed to the degree of visceral adiposity and insulin resistance. The emergence of glucose intolerance or a genetic predisposition to familial combined hyperlipidemia will further modify the plasma lipid phenotype in obese people (11,12,13,14,15).
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.003 |
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".