Abstract 407: High Density Lipoprotein Mediated Protection of Macrophages Against Apoptosis Requires Scavenger Receptor Class B Type 1 Activity and Sphingosine-1-Phosphate
Bibliographic record
Abstract
Background/Objectives: Prevention of macrophage apoptosis in advanced atherosclerotic lesions can help stop atherosclerosis progression to vulnerable plaques. High density lipoprotein (HDL) can protect macrophages from apoptosis that has been induced by a variety of agents. We hypothesize that this is the consequence of the sphingolipid, sphingosine-1-phosphate (S1P), specifically carried by HDL, and transferred to S1P receptor 1 (S1PR1) on the cells via the HDL receptor, scavenger receptor class B type 1 (SR-B1). Methods: Apoptosis was induced in murine peritoneal macrophages from wild type and different knockout mice with the ER stress inducing agent tunicamycin. Apoptosis was then observed and detected by terminal deoxynucleotidyl transferase mediated dUTP nick end labeling through fluorescent microscopy. All experiments were conducted with an n of 3 or 4. Results: Treatment of cells with HDL protected them against tunicamycin induced apoptosis. In contrast, pre-treatment of HDL with S1P lyase, which irreversibly cleaves S1P, eliminated the ability of HDL to protect macrophages. Furthermore, HDL-dependent protection of macrophages against apoptosis required both the HDL receptor SRB1 and the S1PR1. Inhibitor of SRB1’s lipid transport activity also prevented HDL dependant protection against apoptosis. Conclusions: These results suggest that the HDL mediated protection of macrophages against apoptosis may involve SRB1 mediated delivery of S1P from HDL to the S1PR1. Understanding the mechanisms by which HDL elicits atheroprotective signalling in macrophages will provide insight into new targets for therapeutic intervention.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.006 | 0.002 |
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".