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Record W2165483878 · doi:10.1095/biolreprod.109.076000

Identification of Potentially Damaging Amino Acid Substitutions Leading to Human Male Infertility1

2009· article· en· W2165483878 on OpenAlexaff
Anastasia Kuzmin, Keith Jarvi, Kirk Lo, Leia Spencer, Gary Y.C. Chow, Graham MacLeod, Qianwei Wang, Susannah Varmuza

Bibliographic record

VenueBiology of Reproduction · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
Canadian institutionsMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsBiologyNonsynonymous substitutionAzoospermiaSingle-nucleotide polymorphismGeneticsMale infertilitySNPGeneInfertilityGenotypeGenome

Abstract

fetched live from OpenAlex

There are a number of known genetic alterations found in men with nonobstructive azoospermia, or testicular failure, such as Y microdeletions and cytogenetic abnormalities. However, the etiology of nonobstructive azoospermia is unknown in the majority of men. The aim of this study was to investigate the possibility that unexplained cases of nonobstructive azoospermia are caused by nonsynonymous single-nucleotide polymorphisms (SNPs) in the coding regions of autosomal genes associated with sperm production and fertility. Using a candidate gene approach based on genetics of male infertility in mice, we resequenced nine autosomal genes from 78 infertile men displaying testicular failure using custom-made next-generation resequencing chips. Analysis of the data revealed several novel heterozygous nonsynonymous SNPs in four of nine sequenced genes in 14 of 78 infertile men. Eight SNPs in SBF1, three SNPs in LIMK2, two SNPs in LIPE, and one SNP in TBPL1 were identified. All of the novel mutations were in a heterozygous configuration, suggesting that they may be de novo mutations with dominant negative properties.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.309

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 head0.018
GPT teacher head0.303
Teacher spread0.285 · 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

Citations23
Published2009
Admission routes1
Has abstractyes

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