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Record W4405388143 · doi:10.1093/jas/skae365

Effects of increasing supplemental zinc to non-implanted and implanted finishing steers

2024· article· en· W4405388143 on OpenAlexaboutno aff
Elizabeth M Messersmith, Stephanie L Hansen

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsAnimal scienceMarbled meatCrossbreedImplantZincDry matterFeedlotChemistryMedicineBiologySurgery

Abstract

fetched live from OpenAlex

The effects of supplemental Zn within steroidal implant strategy on performance, carcass characteristics, trace mineral status, and muscle gene expression were tested in a 59-d study using 128 Angus-crossbred steers (492 ± 29 kg) in a 2 × 4 complete randomized design. Implant strategies included no implant (NoIMP) or Component TE-200 (TE200; Elanco, Greenfield, IN) administered on day 0. Zinc was supplemented at 0, 30, 100, or 150 mg Zn/kg dry matter (Zn0, Zn30, Zn100, Zn150, respectively) from ZnSO4. Steers were stratified by body weight (BW) to pens (n = 5 or 6 steers/pen) equipped with GrowSafe bunks (GrowSafe Systems Ltd., Airdrie, AB, Canada) and assigned treatments (n = 15, 16, or 17 steers/treatment). Cattle were weighed on days -1, 0, 18, and 59 with blood collected on days -1, 18, 40, and 59. Muscle samples were collected from the longissimus thoracis on day 11 and liver samples were collected on day 55 or 56. Data were analyzed using the Mixed Procedure of SAS via contrast statements testing the linear and quadratic response to Zn supplementation within implant treatment and NoIMP vs. TE200 for performance, carcass, blood, and liver parameters. Specific contrast statements were formed for the analysis of gene expression in muscle including: Zn0 vs. Zn150 within NoIMP and TE200, NoIMP vs. TE200 (Zn0 and Zn150 only), and the linear effect of supplementing Zn0, Zn100, and Zn150 within TE200. Steer was the experimental unit. Day 18 BW and days 0 to 18 average daily gain (ADG) were linearly increased due to Zn supplementation within TE200 (P ≤ 0.002) in conjunction with a linear increase from Zn in day 11 muscle epidermal growth factor receptor, matrix metalloproteinase 2, and phosphodiesterase 4B gene expression of TE200 steers (P ≤ 0.05). Plasma Zn on days 18 and 40 linearly increased with increasing Zn supplementation regardless of implant treatment (P ≤ 0.03) and was lesser for TE200 than NoIMP steers on day 18 (P = 0.001). Day 59 BW and hot carcass weight (HCW) were greater for TE200 vs. NoIMP (P ≤ 0.002) and HCW of implanted steers tended to linearly increase with increasing Zn supplementation (P = 0.09). No effects of Zn supplementation were observed in NoIMP for HCW, BW, or ADG (P ≥ 0.17). Yield grade and 12th rib fat tended to quadratically decrease within NoIMP (P ≤ 0.09), with Zn100 being the most lean. These data indicate increasing supplemental Zn influences steroidal implant signaling machinery while increasing the Zn status and implant-induced growth of feedlot cattle.

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)0.001
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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