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Record W2094494170 · doi:10.1002/humu.21046

BAK1 gene variation and abdominal aortic aneurysms

2009· article· en· W2094494170 on OpenAlexafffund
Bruce Gottlieb, Lorraine E. Chalifour, Benjamin Mitmaker, Nathan Sheiner, Daniel Obrand, Cherrie Abraham, Melissa Meilleur, Tomoko Sugahara, Ghassan Bkaily, Morris Schweitzer

Bibliographic record

VenueHuman Mutation · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsUniversité de SherbrookeMcGill UniversityJewish General Hospital
FundersPfizer CanadaJewish General HospitalPfizer
KeywordsBiologySingle-nucleotide polymorphismSNPGeneticsGeneAlleleAbdominal aortic aneurysmGenetic variationAneurysmGenotype

Abstract

fetched live from OpenAlex

We sought to examine the role of genetics in the multifactorial disease, abdominal aortic aneurysm (AAA), by studying sequence variation in the BAK1 gene (BAK1) that codes for an apoptotic-promoting protein, as chronic apoptosis activation has been linked to AAA development and progression. BAK1 abdominal aorta cDNA from AAA patients and nondiseased individuals were compared with each other, as well as to the BAK1 genomic sequence obtained from matching blood samples. We found specific BAK1 single nucleotide polymorphism (SNP) containing alleles in both aneurysmic (31 cases) and healthy aortic tissue (5 cases) without seeing them in the matching blood samples. These same BAK1 SNPs have been reported, although rarely (average frequency <0.06%), in reference BAK1 DNA sequences. Based on this and other similar observations, we propose a novel hypothesis postulating that multiple variants of genes may preexist in "minority" forms within specific nondiseased tissues and be selected for, when intra- and/or extracellular conditions change. Therefore, the fact that different BAK1 variants can exist in both diseased and nondiseased AA tissues compared to matching blood samples, together with the rare occurrence of these same SNPs in reference sequences, suggests that selection may be a significant factor in AAA ontogeny.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.972
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.260
Teacher spread0.252 · 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

Citations40
Published2009
Admission routes2
Has abstractyes

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