The double jeopardy of HDL
Bibliographic record
Abstract
The ability of high-density lipoprotein (HDL) to promote cholesterol efflux is thought to be important in its protection against cardiovascular disease. Anti-inflammatory properties of HDL have emerged as additional properties that may also be important. HDL appears to have evolved as part of the innate immune system functioning to inhibit inflammation in the absence of an acute phase response (APR) but functioning to increase inflammation in the presence of an APR. Inbred strains of mice that are genetically susceptible to atherosclerosis have pro-inflammatory HDL, while inbred strains that are resistant to atherosclerosis have anti-inflammatory HDL. In one small study, humans with coronary heart disease (CHD) or CHD equivalents had pro-inflammatory HDL prior to statin therapy and about half continued to have pro-inflammatory HDL after statin therapy despite a profound decrease in plasma lipids. Pro-inflammatory HDL was relatively weak in its ability to promote cholesterol efflux while anti-inflammatory HDL was better in promoting cholesterol efflux. In other studies, oxidative alterations of the major protein of HDL, apolipoprotein A-I (apoA-I), impaired the ability of the apoA-I to promote cholesterol efflux. Thus, HDL structure and function may be more important than HDL-cholesterol levels in predicting risk for cardiovascular disease.
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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".