LDL transcytosis passes through the trans-Golgi network and requires Rab10
Bibliographic record
Abstract
Atherosclerosis begins with the subendothelial retention of LDLs from the circulation. While LDL transcytosis across the endothelium is mediated by scavenger receptor class B type I and activin-like kinase receptor 1 and is usually independent of LDL receptor, the intracellular mechanisms and route of LDL transcytosis remain unclear. Using total internal reflection fluorescence microscopy in LDL receptor-depleted human coronary artery endothelial cells, we found that LDL transcytosis can proceed both directly and indirectly from an intracellular compartment. During LDL transcytosis, LDL was observed to colocalize with the Golgi apparatus over time, specifically with the trans-Golgi network marker TGN46. Systematic examination of endothelial Rab proteins known to regulate Golgi traffic identified Rabs 6a and 10 to be required for LDL transcytosis. Depletion of Rab10 or Rab6a significantly inhibited LDL transcytosis but had no effect on albumin transcytosis. Expression and localization of scavenger receptor class B type I and activin-like kinase receptor 1 were also unimpaired. Conversely, overexpression of Rab10 increased LDL transcytosis. Finally, depletion of Rab10 increased colocalization of LDL with the trans-Golgi network and led to expansion of the Golgi, indicative of impaired exocytosis from the Golgi. However, colocalization of Rab10 with LDL did not increase over time, and Rab10 did not accumulate at the base of the cell, suggesting its role is specifically related to LDL exit from the Golgi rather than direct transport. In summary, during LDL transcytosis, internalized LDL is transported to the Golgi, which serves as a reservoir of LDL that can undergo exocytosis. Our results identify specific Rab proteins as critical regulators of this process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 0.000 |
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 teacher head, 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".