Localization and regulation of SR-BI in membrane rafts of HepG2 cells
Bibliographic record
Abstract
The scavenger receptor class B, type I (SR-BI) mediates cholesteryl esters (CE) selective uptake from low density lipoprotein (LDL) and high-density lipoprotein (HDL) particles. In a number of tissues expressing caveolin, SR-BI is localized in caveolae. We show using detergent-free sucrose gradients that SR-BI is found in membrane rafts devoid of caveolin-1 in the human hepatoma HepG2 cell. Perturbation of the structure of HepG2 cell membrane rafts with cholesterol oxidase or sphingomyelinase decreased LDL-CE association due to selective uptake by 60%, while HDL3-CE selective uptake was increased 2.3-fold by cholesterol oxidase but was not affected by sphingomyelinase. Sequestration of membrane cholesterol with filipin III decreased LDL-CE selective uptake by 25%, while it had no effect on HDL3-CE selective uptake. Extraction of cell membrane cholesterol with beta-cyclodextrin increased LDL- and HDL3-CE selective uptake by 1.6-fold and 3-fold, respectively. We found that CE-selective uptake from both HDL and LDL occurs by a pathway involving retro-endocytosis in HepG2 cells. An analysis of the effect of SR-BI level on the expression of critical lipid sensor and lipid binding proteins was conducted with stable transformants of HepG2 cell overexpressing SR-BI. We found that liver-type fatty acid binding protein expression level is higher in SR-BI-overexpressing cells and that caveolin-1 and sterol response element binding protein-2 levels are reduced. Thus, in this hepatic cell model, SR-BI is associated with membrane rafts devoid of caveolin and its expression affects intracellular lipid binding and lipid sensor proteins. SR-BI-dependent LDL- and HDL-CE selective uptake are affected differently by the integrity of membrane rafts, but both occur by a retroendocytic pathway in HepG2 cells.
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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 | 0.000 |
| 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".