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Record W2321696066 · doi:10.1139/cjas-2015-0074

Effects of a non-synonymous <i>CBG</i> gene single nucleotide polymorphism (SNP) on meat-quality traits in Berkshire pigs

2016· article· en· W2321696066 on OpenAlexvenueno aff
Seul Gi Kwon, Jung Hye Hwang, Da Hye Park, Tae‐Wan Kim, Deok Gyeong Kang, Kyung Hee Kang, Il-Suk Kim, Jeongim Ha, Chul Wook Kim

Bibliographic record

VenueCanadian Journal of Animal Science · 2016
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSingle-nucleotide polymorphismSNPBiologyAnimal scienceGeneGlobulinWater holding capacityPolymorphism (computer science)GeneticsFood scienceAlleleGenotypeEndocrinology

Abstract

fetched live from OpenAlex

Corticosteroid-binding globulin (CBG) is a plasma transport protein that has glucocorticoid-binding activity. In the present study, we identified CBG gene expression in several tissues of four pig breeds: Berkshire, Duroc, Landrace, and Yorkshire. Expression of CBG mRNA was detected in the liver of all four breeds, and was the highest in Berkshire pigs. We also found single nucleotide polymorphisms (SNPs) in the CBG gene from Berkshire pigs, including SNP c.919G>A, which corresponds to 307G>R. We analyzed the relationships between this CBG variant and various meat-quality traits. The SNP was significantly associated with backfat thickness, post-mortem pH24h, meat color [CIE a* (redness), CIE b* (yellowness)], water-holding capacity, fat content, moisture content, protein content, cooking loss, and shear force. However, the effects differed by gender: the values were significantly associated with almost all traits in gilts, whereas only cooking loss and shear force were shown significantly in barrows. The variant G allele was associated with decreases in backfat thickness, post-mortem pH24h, CIE a*, fat content, and cooking loss, but with increases in CIE b*, water-holding capacity, moisture content, protein content, and shear force. Because the general correlation between meat-quality traits were not validated in the present study, we suggest that certain SNP might be used in the restrictive application to distinguish meat-quality traits.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.049
GPT teacher head0.307
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2016
Admission routes1
Has abstractyes

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