Bibliographic record
Abstract
PURPOSE OF REVIEW: Proprotein convertase subtilisin/kexin type-9 (PCSK9) binds to LDL receptor (LDLR) and targets it for lysosomal degradation in cells. Decreased hepatic clearance of plasma LDL-cholesterol is the primary gauge of PCSK9 activity in humans; however, PCSK9's evolutionary role may extend to other lipoprotein classes and processes. This review highlights studies that are providing novel insights into physiological regulation of PCSK9 transcription and plasma PCSK9 activity. RECENT FINDINGS: Recent studies indicate that circulating PCSK9 binds to apolipoprotein B100 on LDL particles, which in turn inhibits PCSK9's ability to bind to cell surface LDLRs. Negative feedback of secreted PCSK9 activity by LDL could serve to increase plasma excursion of triglyceride-rich lipoproteins and monitor lipoprotein remodeling. Recent findings have identified hepatocyte nuclear factor-1α as a key transcriptional regulator that cooperates with sterol regulatory element-binding protein-2 to control PCSK9 expression in hepatocytes in response to nutritional and hormonal inputs, as well as acute inflammation. SUMMARY: PCSK9 is an established target for cholesterol-lowering therapies. Further study of PCSK9 regulatory mechanisms may identify additional control points for pharmacological inhibition of PCSK9-mediated LDLR degradation. PCSK9 function could reflect ancient roles in the fasting-feeding cycle and in linking lipoprotein metabolism with innate immunity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".