PCSK9 deficiency unmasks a sex- and tissue-specific subcellular distribution of the LDL and VLDL receptors in mice
Bibliographic record
Abstract
Proprotein convertase subtilisin kexin type 9 (PCSK9), the last member of the family of Proprotein Convertases related to Subtilisin and Kexin, regulates LDL-cholesterol by promoting the endosomal/lysosomal degradation of the LDL receptor (LDLR). Herein, we show that the LDLR cell surface levels dramatically increase in the liver and pancreatic islets of PCSK9 KO male but not female mice. In contrast, in KO female mice, the LDLR is more abundant at the cell surface enterocytes, as is the VLDL receptor (VLDLR) at the cell surface of adipocytes. Ovariectomy of KO female mice led to a typical KO male pattern, whereas 17β-estradiol (E2) treatment restored the female pattern without concomitant changes in LDLR adaptor protein 1 (also known as ARH), disabled-2, or inducible degrader of the LDLR expression levels. We also show that this E2-mediated regulation, which is observed only in the absence of PCSK9, is abolished upon feeding the mice a high-cholesterol diet. The latter dramatically represses PCSK9 expression and leads to high surface levels of the LDLR in the hepatocytes of all sexes and genotypes. In conclusion, the absence of PCSK9 results in a sex- and tissue-specific subcellular distribution of the LDLR and VLDLR, which is determined by E2 levels.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.004 | 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".