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Record W3158320893 · doi:10.3168/jds.2020-19827

The effect of neomycin inclusion in milk replacer on the health, growth, and performance of male Holstein calves during preweaning

2021· article· en· W3158320893 on OpenAlexafffund
L.N. Buss, T.T. Yohe, L.R. Cangiano, D.L. Renaud, A.J. Keunen, Le Luo Guan, M.A. Steele

Bibliographic record

VenueJournal of Dairy Science · 2021
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsMaple Leaf FoodsUniversity of AlbertaUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaBayer Animal HealthDairy Farmers of Manitoba
KeywordsNeomycinDiarrheaMedicineAntibioticsAnimal scienceFecesBody weightStarterBovine respiratory diseaseAntimicrobialVeterinary medicineBiologyInternal medicineFood scienceImmunologyMicrobiology

Abstract

fetched live from OpenAlex

The prophylactic use of oral antimicrobials, such as neomycin, in milk replacer (MR) or whole milk is a common practice in calf-rearing that is thought to aid in preventing disease. Heavy reliance on antimicrobials is of concern not only because of the development of antimicrobial resistance, but also because of the potentially negative effects on health. The objective of this study was to investigate the effects of neomycin on calf health and growth performance. One hundred and sixty calves (approximately 3-10 d of age), distributed across 2 experimental periods, were stratified by body weight (BW) and serum total protein, and assigned to 1 of 3 treatments: control (CON; nonmedicated MR, n = 60), short-term antibiotic (ST; neomycin mixed in MR from d 1-14, n = 50), or long-term antibiotic (LT; neomycin in ​MR from d 1-28, n = 50). Arrival BW (47.69 ± 0.87 kg) and serum total protein (5.67 ± 0.09 g/dL) were not different between treatment groups. Neomycin in ST and LT was dosed in MR at a rate of 20 mg/kg of BW and was adjusted weekly according to BW. Calf BW was measured weekly for 49 d, and health indicators (fecal score, attitude score, respiratory score, and rectal temperature), MR intake, starter intake, and the use of additional electrolytes and antimicrobials were recorded daily. Calves in the CON group experienced a higher proportion of days with diarrhea (20.32 ± 0.02%) compared with ST (14.70 ± 0.02%) or LT (13.80 ± 0.02%) calves, as well as longer bouts of diarrhea (7.45 ± 0.38 d, 5.69 ± 0.46 d, and 5.62 ± 0.45 d for CON, ST, and LT calves, respectively). Calves in the CON group also experienced higher fecal scores (score of 0.64 ± 0.04) than ST (score of 0.53 ± 0.04) or LT (score of 0.49 ± 0.04) calves, especially at d 7. However, no differences were observed in other health-related measures. The time to reach first diarrhea and first respiratory illness was not different between treatments, nor was the time to recover from respiratory illness. The time to intervention with additional electrolytes or antimicrobials was not different between treatment groups. Furthermore, growth performance, feed intake, and feed conversion ratio were not different. No differences were found when comparing ST and LT, except in the defined daily dose of total antimicrobials received. Calves in the LT group received a higher overall dose than ST calves, and both ST and LT calves received a higher dose than CON calves, which received no prophylactic antimicrobials. Given that there were no differences in performance variables and no additional health benefits aside from reduced fecal scores in calves fed neomycin, current practices involving the use of antimicrobials on dairy and veal operations need to be considered more prudently.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.309
Teacher spread0.289 · 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

Citations16
Published2021
Admission routes2
Has abstractyes

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