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Record W2115913745 · doi:10.1194/jlr.m300448-jlr200

Increased production of VLDL apoB-100 in subjects with familial hypercholesterolemia carrying the same null LDL receptor gene mutation

2004· article· en· W2115913745 on OpenAlexaff
André Tremblay, Benoı̂t Lamarche, Isabelle L. Ruel, Jean‐Charles Hogue, Jean Bergeron, Claude Gagné, Patrick Couture

Bibliographic record

VenueJournal of Lipid Research · 2004
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsApolipoprotein BInternal medicineEndocrinologyFamilial hypercholesterolemiaLDL receptorCatabolismVery low-density lipoproteinHeterozygote advantageCholesterolChemistryLipoproteinNull alleleBiologyGeneMedicineAlleleMetabolismBiochemistry

Abstract

fetched live from OpenAlex

Early radiokinetic studies revealed that the classical metabolic defect in patients with familial hypercholesterolemia (FH) is hypocatabolism of LDL due to decreased LDL receptor activity. However, recent studies have suggested that hepatic oversecretion of apolipoprotein B-100 (apoB-100)-containing lipoproteins could also contribute to the markedly elevated plasma concentrations of LDL-cholesterol found in FH. The aim of this study was to examine the kinetics of apoB-100 labeled with a stable isotope (l-[5,5,5-D(3)] leucine) in five normolipidemic controls and in seven well-characterized FH subjects that included six FH heterozygotes and one FH homozygote carrying the same null LDL receptor gene mutation. As compared with controls, the VLDL apoB-100 production rate was increased by 50% in the FH heterozygotes and by 109% in the FH homozygote. Furthermore, FH subjects had significantly higher LDL apoB-100 pool size and lower LDL apoB-100 fractional catabolic rate than controls. These results indicate that the elevation of plasma LDL-cholesterol found in FH is attributable to both decreased clearance of LDL and increased hepatic production of apoB-100-containing lipoproteins.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.337
Teacher spread0.291 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations49
Published2004
Admission routes1
Has abstractyes

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