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Record W7061931217

Role of the «proprotein convertase subtilisin/kexin 5» gene in high-density lipoprotein metabolism: potential implications for atherosclerotic cardiovascular disease development

2009· dissertation· en· W7061931217 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueeScholarship@McGill (McGill) · 2009
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Power Generation Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPCSK9International HapMap ProjectSingle-nucleotide polymorphismSNPProprotein convertaseLipoproteinLipoprotein(a)HaplotypeApolipoprotein BAllele
DOInot available

Abstract

fetched live from OpenAlex

Low plasma high-density lipoprotein cholesterol (HDL-C) is a wellestablished risk factor for coronary artery disease (CAD).The proprotein convertase subtilisin/kexin 5 (PC5/PCSK5) is known to inactivate endothelial lipase, enzyme critical in modulating HDL-C levels.In this study, we investigated the role of human PCSK5 genetic variants on HDL-C.We examined haplotypes at the PCSK5 locus in 9 multigenerational families with HDL-C<10 th percentile and discovered segregation with low HDL-C in one family.We genotyped novel single nucleotide polymorphisms (SNPs) found through sequencing and tagSNPs from the HapMap Project (n=182 total) in 457 individuals with CAD and identified 9 SNPs associated with HDL-C (P<0.05), the strongest being rs11144782 (minor allele frequency 0.164, p=0.002).This SNP decreased HDL-C by 0.076 mmol/L in a gene dosage-effect and was also associated with very lowdensity lipoprotein (P=0.039),triglycerides (P=0.049) and apolipoprotein B (P=0.022) levels.We conclude that variability at PCSK5 influences HDL-C levels and consequently, CAD risk.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.429
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.197
Teacher spread0.188 · 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