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Record W2809297194 · doi:10.1017/s1751731118001210

Feedlot performance and immune function analysis of implanted and non-implanted steers selected for alcohol dehydrogenase 1 C (ADH1C) genotype and fed a low vitamin A diet

2018· article· en· W2809297194 on OpenAlexafffund
K.M. Madder, J. J. McKinnon, G.W. Torres, K.G. Krone, J. L. Duncombe, Chris Luby, Fiona Buchanan

Bibliographic record

Venueanimal · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Saskatchewan
FundersAlberta Livestock and Meat Agency
KeywordsMarbled meatFeedlotAnimal scienceBeef cattleBreedPopulationImplantMedicineIntramuscular fatInternal medicineBiologyEndocrinologySurgery

Abstract

fetched live from OpenAlex

Previous studies have shown that the interaction between limiting vitamin A (VA) and an alcohol dehydrogenase 1 C (ADH1C) variant in beef cattle results in increased intramuscular fat in the longissimus thoracis muscle in one genotype when fed low dietary VA. Although quality grade is important for increased profitability and improving taste characteristics of beef products, limiting VA too drastically can impair animal welfare. The objectives of this study were to determine if this marker-assisted management strategy would be effective, and whether any impairment in immune function would occur in a feedlot setting. Mixed breed beef steers (n=2000) were sorted into 40 feedlot pens so that all combinations of ADH1C genotype (TT or CT), VA level (50% or 100% of recommended) and hormonal implant status (implanted (IMP) or non-implanted (NI)) were equally represented within the population. The VA×ADH1C interaction was not observed. An implant status × ADH1C interaction was observed with average daily gain (ADG; P=0.03). Steers that were IMP and CT had higher ADG than IMP TT (CT=1.69 and TT=1.62 kg/day), whereas both genotypes in the NI steers were lower (CT=1.29 and TT=1.32 kg/day). Implant status was shown to affect dry matter intake (DMI; IMP=8.55 and NI=7.87 kg; P<0.01), total days-on-feed (IMP=164.4 and NI 210.5 days; P<0.01), USDA yield grade (YIELD; IMP=2.40 and NI=2.77; P<0.01), marbling score (MARB; IMP=392 and NI=455; P<0.01), longissimus thoracis area (LTA; IMP=85.0 and NI=80.7 cm2; P=0.01) and backfat thickness (FAT; IMP=8.0 and NI 10.0 mm; P<0.01). Overall, IMP animals finished on fewer total days-on-feed with higher ADG, DMI, larger LTA, and lower YIELD, MARB and FAT. To investigate immune function parameters, crossbred steers (n=18) were selected from a prior feeding trial so that all combinations of ADH1C (TT, CT and CC) and VA (25% or 75%) were equally represented. Blood cell count analysis and peripheral blood mononuclear cell proliferation and stimulation assays were conducted. None of these immune parameters were affected by VA level. Treatment and mortality records were examined in the 2000 steer population, where no correlations with ADH1C, implant status or VA level were observed. Due to no VA × ADH1C interaction, this nutrigenetic marker-assisted management strategy is not effective at this time in commercial beef cattle feedlots, however, supplementing VA at a level as low as 25% of recommended in finishing rations would likely not result in signs of immune dysfunction.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.239

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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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

Citations1
Published2018
Admission routes2
Has abstractyes

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