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Record W3179265019 · doi:10.3390/biom11071016

Lipoprotein Lipase and Its Delivery of Fatty Acids to the Heart

2021· review· en· W3179265019 on OpenAlexafffund
Rui Shang, Brian Rodrigues

Bibliographic record

VenueBiomolecules · 2021
Typereview
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsLipoprotein lipaseLipolysisTriglycerideAdipose triglyceride lipaseInternal medicineEndocrinologyLipoproteinLipaseChemistryBiochemistryBiologyEnzymeAdipose tissueMedicineCholesterol

Abstract

fetched live from OpenAlex

Ninety percent of plasma fatty acids (FAs) are contained within lipoprotein-triglyceride, and lipoprotein lipase (LPL) is robustly expressed in the heart. Hence, LPL-mediated lipolysis of lipoproteins is suggested to be a key source of FAs for cardiac use. Lipoprotein clearance by LPL occurs at the apical surface of the endothelial cell lining of the coronary lumen. In the heart, the majority of LPL is produced in cardiomyocytes and subsequently is translocated to the apical luminal surface. Here, vascular LPL hydrolyzes lipoprotein-triglyceride to provide the heart with FAs for ATP generation. This article presents an overview of cardiac LPL, explains how the enzyme works, describes key molecules that regulate its activity and outlines how changes in LPL are brought about by physiological and pathological states such as fasting and diabetes, respectively.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.042
GPT teacher head0.330
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations33
Published2021
Admission routes2
Has abstractyes

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