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Record W2896068050 · doi:10.1093/femsec/fiy203

Colostrum feeding shapes the hindgut microbiota of dairy calves during the first 12 h of life

2018· article· en· W2896068050 on OpenAlexafffund
Yang Song, Nilusha Malmuthuge, Fuyong Li, Le Luo Guan

Bibliographic record

VenueFEMS Microbiology Ecology · 2018
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Livestock and Meat Agency
KeywordsColostrumBifidobacteriumBiologyMicrobiologyAnimal scienceIleumEscherichia coliLactoseIntestinal mucosaShigellaLactobacillusFecesHindgutBacteriaFood scienceImmunologyInternal medicineEndocrinologyAntibodyBiochemistryEcologyMedicine

Abstract

fetched live from OpenAlex

This study evaluated the effect of feeding non-heated and heated colostrum on the mucosa- and digesta-associated microbiota in the colon of dairy calves during the first 12 h of life. Thirty-two neonatal Holstein male calves were fed: no colostrum (NC, n = 8), non-heated colostrum (FC, n = 12) and heated colostrum (HC (60 °C, 60 min), n = 12) immediately after birth. The abundances of mucosa- and digesta-associated total bacteria were higher in the colon of FC fed calves compared to those fed no colostrum (NC) at 12 h of life. Compare to NC calves, a higher proportion of mucosa- and digesta-associated Clostridium cluster XIVa and Bifidobacterium, and a lower abundance of mucosa and digesta-associated E. coli were detected in the colon of FC and HC fed calves, as well as a tentatively lower relative abundance of Escherichia-Shigella genus in colon mucosa of HC fed calves. In addition, HC calves had lower abundances of E. coli and higher abundances of Bifidobacterium in mucosa-associated microbiota than FC fed calves. Our results suggest that feeding non-heated colostrum immediately after birth benefit neonatal calves with increased Bifidobacterium and decreased opportunistic pathogenic E. coli and Escherichia-Shigella genus in the colon, and feeding heated colostrum can fortify such effects.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.028
GPT teacher head0.275
Teacher spread0.247 · 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.

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

Citations59
Published2018
Admission routes2
Has abstractyes

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