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Record W4384932491 · doi:10.3390/genes14071479

Investigating the Genetic Background of Spastic Syndrome in North American Holstein Cattle Based on Heritability, Genome-Wide Association, and Functional Genomic Analyses

2023· article· en· W4384932491 on OpenAlexaff
Anna Neustaeter, Luiz F. Brito, W. J. Brad Hanna, John D. Baird, Flávio S. Schenkel

Bibliographic record

VenueGenes · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurological diseases and metabolism
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGenome-wide association studyBiologyCandidate geneSingle-nucleotide polymorphismGeneticsNeuroscienceGene

Abstract

fetched live from OpenAlex

Spastic syndrome is a chronic, progressive disorder of adult cattle characterized by episodes of sudden involuntary muscle contractions or spasms of the extensor and abductor muscles of one or both hind limbs. In this study, a case-control genome-wide association study (GWAS) was performed on an adult Holstein cattle cohort. Based on the 50 K and high-density (HD) SNP panel GWAS, we identified 98 and 522 SNPs, respectively. The most significant genomic regions identified are located on BTA9 at approximately 87 megabase pairs (Mb) and BTA7 between 1 and 20 Mb. Functional analyses of significant SNPs identified genes associated with muscle contraction, neuron growth or regulation, and calcium or sodium ion movement. Two candidate genes (FIG4 and FYN) were identified. FIG4 is ubiquitously expressed in skeletal muscle and FYN is involved with processes such as forebrain development, neurogenesis, locomotion, neurogenesis, synapse development, neuron migration, and the positive regulation of neuron projection development. The CACNA1A gene, which codes for a calcium channel subunit protein in the calcium signaling pathway, seems the most compelling candidate gene, as many calcium ion channel disorders are non-degenerative, and produce spastic phenotypes. These results suggest that spastic syndrome is of polygenic inheritance, with important genomic areas of interest on BTA7 and BTA9.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.072
GPT teacher head0.286
Teacher spread0.214 · 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 designObservational
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

Citations5
Published2023
Admission routes1
Has abstractyes

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