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Record W3132075539 · doi:10.6000/1927-520x.2021.10.01

Sequencing and Analysis of the Myostatin Gene (GDF-8) in Bubalus bubalis Young Animals to Determine the Existence of Possible Mutations Expressed in Double Musculature Phenotype

2021· article· en· W3132075539 on OpenAlexvenueno aff
María Angélica Reyes Páez, Natalia Johana Rojas Tovar, Geovanny Mendoza-Sánchez, Marcela Fernández Muñoz, Boris Julián Sepúlveda Molina, Andrés Felipe Santander Torres, J. Berdugo, Jhon Didier Ruíz Buitrago

Bibliographic record

VenueJournal of Buffalo Science · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsBubalusMyostatinBiologyBreedExonGeneticsPhenotypeGeneMutation

Abstract

fetched live from OpenAlex

Since the 19th century, the presentation of bovines with disproportionate muscle development have been associated with mutations that inhibit the action of the myostatin gene, it is referred to as double muscle mutation, which is common in some European Bos taurus breeds but it is not reported in buffaloes Bubalus bubalis. This study aims to evaluate if the phenotype observed in 6 young buffaloes with disproportionate muscle development has the same myostatin mutation reported in cattle. DNA was obtained from the blood of the animals of the Murrah breed. First, second and third exon was amplified end point PCR; the fragments were sequenced using capillary electrophoresis. Holstein cattle (Bos taurus) was used As control for normal phenotype. The results obtained from the comparison of the sequence of the myostatin gene show that the observed double-muscled phenotype did not show differences from normal controls. Interspecific variation was demonstrated by comparing exons two and three of the gene, finding 12 variations between the Bos taurus and Bubalus bubalis species in the evaluated fragments. It is necessary to study physiology, and the animals to explain the phenotype observed in buffaloes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.281
Teacher spread0.263 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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