Regulation of SR-BI-mediated selective lipid uptake in Chinese hamster ovary-derived cells by protein kinase signaling pathways
Bibliographic record
Abstract
Scavenger receptor, class B, type I (SR-BI) mediates binding and internalization of a variety of lipoprotein and nonlipoprotein ligands, including HDL. Studies in genetically engineered mice revealed that SR-BI plays an important role in HDL reverse cholesterol transport and protection against atherosclerosis. Understanding how SR-BI's function is regulated may reveal new approaches to therapeutic intervention in atherosclerosis and heart disease. We utilized a model cell system to explore pathways involved in SR-BI-mediated lipid uptake from and signaling in response to distinct lipoprotein ligands: the physiological ligand, HDL, and a model ligand, acetyl LDL (AcLDL). In Chinese hamster ovary-derived cells, murine SR-BI (mSR-BI) mediates lipid uptake via distinct pathways that are dependent on the lipoprotein ligand. Furthermore, HDL and AcLDL activate distinct signaling pathways. Finally, mSR-BI-mediated selective lipid uptake versus endocytic uptake are differentially regulated by protein kinase signaling pathways. The protein kinase C (PKC) activator PMA and the phosphatidyl inositol 3-kinase inhibitor wortmannin increase the degree of mSR-BI-mediated selective lipid uptake, whereas a PKC inhibitor has the opposite effect. These data demonstrate that SR-BI's selective lipid uptake activity can be acutely regulated by intracellular signaling cascades, some of which can originate from HDL binding to murine SR-BI itself.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".