Proprotein Convertase Subtilisin Kexin9 (PCSK9): A Novel Target For Cholesterol Regulation
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Proprotein Convertase Subtilisin Kexin9 (PCSK9), originally called Neural Apoptosis-Regulated Convertase1 (NARC1), is the latest member of mammalian subtilase super-family. Since its discovery in 2003, it has drawn significant attention because of its function in the degradation of Low Density Lipoprotein Receptor (LDL-R). LDL-R removes circulating LDL-cholesterol (LDL-C) in the blood. Increased level of PCSK9 functional activity will lead to an accumulation of cholesterol in the blood - a high risk factor for cardiovascular disease. This is confirmed by PCSK9 knock out and transgenic animals, various biochemical and clinical studies involving “gain and loss of function” genetic mutations of PCSK9 found in various subset of populations. Owing to this finding, development of strategies for inhibition of PCSK9 function has drawn significant research interest for therapeutic intervention of hypercholesterolemia. Thus PCSK9 is a target for the development of new cholesterol lowering drugs. Keywords: Proprotein convertase subtilisin Kexin9 (PCSK9), low density lipoprotein receptor, low density lipoproteincholesterol, hypercholesterolemia, cholesterol lowering agents, PCSK9 inhibitors, Hypercholesterolemia (ADH), trans Golgi network (TGN), lysosome compartments, fluorogenic peptide
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it