HDL-Mediated Cellular Cholesterol Efflux Assay Method.
Bibliographic record
Abstract
Biomarkers of high-density lipoprotein (HDL) function may provide mechanistic insights and better cardiovascular risk discrimination than HDL-cholesterol mass. The purpose of this work is to describe a simplified experimental protocol that can be used in the determination of cholesterol efflux from macrophages cultured cells and be brought to a medium throughput volume. The cellular cholesterol efflux assay is designed to quantify the rate of cholesterol efflux from cultured cells to an acceptor particle or to plasma. This assay is multi step, cell based assay. Various factors, if not carefully controlled may influence the accuracy and reproducibility of the assay. Attempts were made to address factors influencing this assay and to provide a standardized method that is relatively rapid and scalable. We demonstrate that further centrifugation of the HDL fraction is necessary to avoid apolipoprotein B contamination when using polyethylene glycol (PEG) method. We demonstrate also no effect on cholesterol efflux efficiency when using PEG with plasma or serum. This method has been previously applied in our laboratory in context of cardiovascular research, cardiovascular disease and pharmacologic therapies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".