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Record W2998358302 · doi:10.1093/jas/skz258.330

398 Effects of protein level and supplemental methionine in late-gestation on colostrum quality and passive immunity transfer in beef cattle

2019· article· en· W2998358302 on OpenAlexaff
Michaela K S Lievre, Madeline Collins, Kaitlyn V J Lawson, Douglas C. Hodgins, J.P. Cant, I. B. Mandell, Katie M Wood

Bibliographic record

VenueJournal of Animal Science · 2019
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsColostrumIce calvingAnimal scienceRadial immunodiffusionPassive immunityGestationMethionineChemistryLactationBiologyPregnancyAntibodyImmunologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract The objective of this study was to evaluate the influence of metabolizable protein (MP) level and supplemental rumen-protected methionine (RPM) on colostrum quality and passive immunity transfer from beef cows fed during late-gestation. One hundred and forty-seven pregnant Angus crossbred cows and heifers were randomly assigned to one of six dietary treatments based on a 3 x 2 factorial arrangement. Diets included feeding to 90%, 100% and 110% MP requirements (NRC, 2016), offered with (without) 9 g/d of RPM. Cattle were individually fed a partially mixed ration (60% haylage/40% straw for cows; 70% haylage/30% straw for heifers) with supplements top-dressed daily for approximately 56 d prior to calving. Immediately after calving, a colostrum sample was collected from each dam for analysis of milk components, total protein, and IgG concentrations. Two d post-calving, serum samples were collected from each calf for analysis of total protein and IgG concentrations. A refractometer was used to estimate total protein as a preliminary estimate of the transfer of maternal IgG and total IgG concentrations were later determined using Radial Immunodiffusion (RID). Data were analyzed as a completely randomized block design using Proc GLIMMIX in SAS. Level of MP, RPM, and their interaction did not influence concentrations of fat, protein, BHB or SCC in colostrum (P ≥ 0.12). Supplementation of RPM decreased concentrations of MUN (45.92 vs. 54.51 ±3.17 mg/dl; P = 0.04), but did not change IgG (14.66 vs. 15.90 ±0.87 g/dl; P = 0.29). While MP level during gestation did not affect total protein or IgG concentrations in calf serum (P ≥ 0.64), providing supplemental RPM decreased total protein (5.79 vs. 6.33 ±0.13 g/dl; P = 0.002) and IgG concentrations in calf serum (3.44 vs. 4.30 ±0.25 g/dl; P = 0.01). These results suggest that providing supplemental methionine for beef cows during gestation may alter colostrum quality and decrease serum protein and IgG in offspring.

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 score0.004
Threshold uncertainty score0.008

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)0.0010.000

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 head0.065
GPT teacher head0.381
Teacher spread0.316 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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