Abstract 12674: LDL Transcytosis by SR-BI Requires Signaling That is Distinct From Reverse Cholesterol Transport
Bibliographic record
Abstract
Introduction: How LDL crosses an intact endothelial layer to initiate atherosclerosis is poorly understood, although it is postulated to involve LDL transcytosis. To date, technical limitations have greatly limited the study of its molecular mechanisms. We have recently devised an assay for quantifying LDL transcytosis by primary human coronary artery endothelial cells and have reported an unexpected role for the scavenger receptor SR-BI. SR-BI is best known as the HDL receptor and mediates reverse cholesterol transport; its downstream signaling involves the adaptor PDZK1 and endothelial nitric oxide synthase (eNOS). However, whether SR-BI internalization and its canonical signaling pathway are required for LDL transcytosis is unknown. Hypothesis: We hypothesized that LDL transcytosis and reverse cholesterol transport require different signaling pathways. Methods: Transcytosis of DiI-labeled LDL by primary human coronary artery endothelial cells was studied by total internal reflection fluorescence microscopy. The role of lipid rafts, PDZK1, eNOS and MAP kinases was studied by siRNA and pharmacological inhibitors. Results: Incubation with LDL induced the internalization of SR-BI, which was enriched in lipid rafts. Knockdown of caveolin-1 significantly attenuated LDL transcytosis. Coronary endothelial cells expressed low levels of PDZK1 and knockdown by siRNA had no effect on transcytosis. Similarly, inhibition of eNOS or addition of exogenous nitric oxide (NO) by NO-donors did not affect LDL transcytosis. Over-expression of G420H-SR-BI, a mutant receptor which does not perform reverse cholesterol transport, actually induced LDL transcytosis while the SR-BI inhibitor BLT-1, which prevents reverse cholesterol transport, had no effect on LDL transcytosis. Finally, inhibition of c-Jun N-terminal kinase (JNK) significantly attenuated LDL transcytosis. Conclusions: SR-BI is internalized during LDL transcytosis but PDZK1 and nitric oxide are not required. Instead, JNK kinase is involved. These data raise the possibility that reverse cholesterol transport and LDL transcytosis by SR-BI are regulated separately. These findings suggest that LDL transcytosis by SR-BI may constitute a novel therapeutic target for atherosclerosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".