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Record W1978010649 · doi:10.4161/pri.21866

The identification of candidate genes and SNP markers for classical bovine spongiform encephalopathy susceptibility

2012· article· en· W1978010649 on OpenAlexaff
Jennifer M. Thomson, Victoria Bowles, Jung-Woo Choi, Urmila Basu, Yan Meng, Paul Stothard, S. S. Moore

Bibliographic record

VenuePrion · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBovine spongiform encephalopathyBiologyPRNPGeneticsSingle-nucleotide polymorphismSNPCandidate geneGeneVirologyAlleleDiseaseGenotypePrion proteinMedicinePathology

Abstract

fetched live from OpenAlex

Classical bovine spongiform encephalopathy is a transmissible prion disease that is fatal to cattle and is a human health risk due to its association with a strain of Creutzfeldt-Jakob disease (vCJD). Mutations to the coding region of the prion gene (PRNP) have been associated with susceptibility to transmissible spongiform encephalopathies in mammals including bovines and humans. Additional loci such as the retinoic acid receptor beta (RARB) and stathmin like 2 (STMN2) have also been associated with disease risk. The objective of this study was to refine previously identified regions associated with BSE susceptibility and to identify positional candidate genes and genetic variation that may be involved with the progression of classical BSE. The samples included 739 samples of either BSE infected animals (522 animals) or non-infected controls (207 animals). These were tested using a custom SNP array designed to narrow previously identified regions of importance in bovine genome. Thirty one single nucleotide polymorphisms were identified at p < 0.05 and a minor allele frequency greater than 5%. The chromosomal regions identified and the positional and functional candidate genes and regulatory elements identified within these regions warrant further research.

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)0.001
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 score0.186
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.281
Teacher spread0.266 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

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