Plasma PCSK9 preferentially reduces liver LDL receptors in mice
Bibliographic record
Abstract
Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a secreted protein that regulates the expression of LDL receptor (LDLR) protein. Gain-of-function mutations in PCSK9 cause hypercholesterolemia, and loss-of-function mutations result in lower plasma LDL-cholesterol. Here, we investigate the kinetics and metabolism of circulating PCSK9 relative to tissue levels of LDLRs. The administration of recombinant human PCSK9 (32 microg) to mice by a single injection reduced hepatic LDLRs by approximately 90% within 60 min, and the receptor levels returned to normal within 6 h. The half-life of the PCSK9 was estimated to be approximately 5 min. Continuous infusion of PCSK9 (32 microg/h) into wild-type mice caused a approximately 90% reduction in hepatic LDLRs within 2 h and no associated change in the level of LDLR in the adrenals. Parallel studies were performed using a catalytically inactive form of PCSK9, PCSK9(S386A), and similar results were obtained. Infusion of PCSK9(D374Y), a gain-of-function mutation, resulted in accelerated clearance of the mutant PCSK9 and a greater reduction in hepatic LDLRs. Combined, these data suggest that exogenously administrated PCSK9 in plasma preferentially reduces LDLR protein levels in liver at concentrations found in human plasma and that PCSK9's action on the LDLR is not dependent on catalytic activity in vivo.
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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) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".