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Record W2200388925 · doi:10.7555/jbr.29.20150052

PCSK9 and triglyceride-rich lipoprotein metabolism

2015· review· en· W2200388925 on OpenAlexaff
Druce Irena, Abujrad Hussein, Chye Teik

Bibliographic record

VenueJournal of Biomedical Research · 2015
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsPCSK9EndocrinologyInternal medicineTriglycerideKexinLDL receptorLipoproteinApolipoprotein BPostprandialLipid metabolismProprotein convertaseChemistryBiologyCholesterolMedicineInsulin

Abstract

fetched live from OpenAlex

Pro-protein convertase subtilisin-kexin 9 (PCSK9) is known to affect low-density lipoprotein (LDL) metabolism, but there are indications from several lines of research that it may also influence the metabolism of other lipoproteins, especially triglyceride-rich lipoproteins (TRL). This review summarizes the current data on this possible role of PCSK9. A link between PCSK9 and TRL has been suggested through the demonstration of (1) a correlation between plasma PCSK9 and triglyceride (TG) levels in health and disease, (2) a correlation between plasma PCSK9 and markers of carbohydrate metabolism, which is closely related to TG metabolism, (3) an effect of TG-lowering fibrate therapy on plasma PCSK9 levels, (4) an effect of PCSK9 on postprandial lipemia, (5) an effect of PCSK9 on adipose tissue biology, (6) an effect of PCSK9 on apolipoprotein B production from the liver and intestines, (7) an effect of PCSK9 on receptors other than low density lipoprotein receptor (LDLR) that are involved in TRL metabolism, and (8) an effect of anti-PCSK9 therapy on serum TG levels. The underlying mechanisms are unclear but starting to emerge.

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 imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.207
GPT teacher head0.488
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations38
Published2015
Admission routes1
Has abstractyes

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