Comparing expression and activity of PCSK9 in SPRET/EiJ and C57BL/6J mouse strains shows lack of correlation with plasma cholesterol
Bibliographic record
Abstract
Objective Low-density lipoprotein receptor (LDLR) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are opposing regulators of plasma LDL-cholesterol levels. The PCSK9 gene exhibits many single or compound polymorphisms within or among mammalian species. This is case between the SPRET/EiJ (SPRET) and C57BL/6J (B6) mouse strains. We examined whether these polymorphisms could be associated with differential expression and activity of their respective PCSK9 molecules. Methods Liver expression of LDLR and PCSK9 transcripts were assessed by RT-PCR, and that of their corresponding proteins by immunoblotting . Purified recombinant PCSK9 proteins were assayed for their ability to degrade LDLR. Pcsk9 gene proximal promoters were tested for activation of a luciferase reporter gene. Results SPRET and B6 mice carried comparable levels of plasma cholesterol in spite of the fact that SPRET mice expressed less PCSK9 and more LDLR in liver. There were indels and single-base differences between their Pcsk9 cDNA and promoter sequences . Ex vivo , SPRET PCSK9 protein was less secreted but was more active at degrading LDLR. Its gene promoter was more active at driving expression of the luciferase reporter. Conclusions Collectively, these results suggest that, compared to the B6 mouse , the SPRET mouse may represent an example of absence of direct correlation between PCSK9 and cholesterol levels in plasma, due to genetic variations leading to reduced secretion of PCSK9 associated with greater LDLR-degrading activity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".