HDL-apoA-I Exchange: Rapid Detection and Association with Atherosclerosis
Bibliographic record
Abstract
High density lipoprotein (HDL) cholesterol levels are associated with decreased risk of cardiovascular disease, but not all HDL are functionally equivalent. A primary determinant of HDL functional status is the conformational adaptability of its main protein component, apoA-I, an exchangeable apolipoprotein. Chemical modification of apoA-I, as may occur under conditions of inflammation or diabetes, can severely impair HDL function and is associated with the presence of cardiovascular disease. Chemical modification of apoA-I also impairs its ability to exchange on and off HDL, a critical process in reverse cholesterol transport. In this study, we developed a method using electron paramagnetic resonance spectroscopy (EPR) to quantify HDL-apoA-I exchange. Using this approach, we measured the degree of HDL-apoA-I exchange for HDL isolated from rabbits fed a high fat, high cholesterol diet, as well as human subjects with acute coronary syndrome and metabolic syndrome. We observed that HDL-apoA-I exchange was markedly reduced when atherosclerosis was present, or when the subject carries at least one risk factor of cardiovascular disease. These results show that HDL-apoA-I exchange is a clinically relevant measure of HDL function pertinent to 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".