Atherosclerosis-associated hepatic secretion of VLDL but not PCSK9 is dependent on cargo receptor protein Surf4
Bibliographic record
Abstract
Plasma LDL is produced from catabolism of VLDL and cleared from circulation mainly via the hepatic LDL receptor (LDLR). Proprotein convertase subtilisin/kexin type 9 (PCSK9) promotes LDLR degradation, increasing plasma LDL-C levels. Circulating PCSK9 is mainly secreted by the liver, whereas VLDL is exclusively secreted by hepatocytes. However, the mechanism regulating their secretion is not completely understood. Surfeit 4 (Surf4) is a cargo receptor localized in the ER membrane. It recruits cargos into coat protein complex II vesicles to facilitate their secretion. Here, we investigated the role of Surf4 in VLDL and PCSK9 secretion. We generated Surf4 liver-specific knockout mice and found that knockout of Surf4 did not affect PCSK9 secretion, whereas it significantly reduced plasma levels of cholesterol, triglyceride, and lipid-binding protein apolipoprotein B (apoB). In cultured human hepatocytes, Surf4 coimmunoprecipitated and colocalized with apolipoprotein B100, and Surf4 silencing reduced secretion of apolipoprotein B100. Furthermore, knockdown of Surf4 in LDLR knockout ( Ldlr −/− ) mice significantly reduced triglyceride secretion, plasma levels of apoB and non-HDL-C, and the development of atherosclerosis. However, Surf4 liver-specific knockout mice and Surf4 knockdown in Ldlr −/− mice displayed similar levels of liver lipids and plasma alanine aminotransferase activity as control mice, indicating that inhibition of Surf4 does not cause notable liver damage. Expression of stearoyl-CoA desaturase-1 was also reduced in the liver of these mice, suggesting a reduction in de novo lipogenesis. In summary, hepatic deficiency of Surf4 reduced VLDL secretion and the development of atherosclerosis but did not cause significant hepatic lipid accumulation or liver damage.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".