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Record W3118125291 · doi:10.3168/jds.2020-18825

Characterization of fecal branched-chain fatty acid profiles and their associations with fecal microbiota in diarrheic and healthy dairy calves

2020· article· en· W3118125291 on OpenAlexafffund
Hangshu Xin, Tao Ma, Yang Xu, Guanqun Chen, Yanhong Chen, Clothilde Villot, D.L. Renaud, M.A. Steele, Le Luo Guan

Bibliographic record

VenueJournal of Dairy Science · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of GuelphUniversity of Alberta
FundersDairy Farmers of ManitobaNational Dairy Industry and Technology SystemChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsFecesDiarrheaBiologyAnimal scienceFood scienceVeterinary medicineMicrobiologyMedicineGastroenterology

Abstract

fetched live from OpenAlex

Branched-chain fatty acids (BCFA) have recently been reported to play a role in human gut health during early life. However, little information is available on the fecal BCFA profiles in young ruminants and whether they are associated with the development of neonatal calf diarrhea. The objectives of this study were to (1) characterize BCFA profiles in feces collected from young calves, (2) compare the fecal BCFA composition between diarrheic and nondiarrheic dairy calves, and (3) explore the potential relationships between BCFA and microbiota in the feces. A total of 32 male Holstein dairy calves (13 ± 3 d old) with the same diet management were grouped as diarrheic (n = 16) or healthy (n = 16) based on fecal score (determined by liquid fecal consistency with some solid particles); diarrhea cases were defined as fecal score ≥2 for at least 2 d. Fecal samples were collected on the seventh day after calf arrival, and the fecal BCFA and microbial profiles were assessed using gas chromatograph and amplicon sequencing, respectively. In total, 7 BCFA were detected in the feces of all dairy calves; however, the concentrations of fecal BCFA differed between diarrheic and nondiarrheic calves. Specifically, the concentrations of iso-C16:0, iso-C17:0, anteiso-C17:0, and total even-chain BCFA were significantly higher in the feces of diarrheic calves. When the associations between BCFA and bacteria were studied, the relative abundance of Eggerthella was positively correlated with the concentrations of iso-C16:0 (ρ = 0.67), iso-17:0 (ρ = 0.77), anteiso-C17:0 (ρ = 0.73), and iso-C18:0 (ρ = 0.65), whereas the relative abundance of Subdoligranulum was positively correlated with the concentrations of iso-C14:0 (ρ = 0.62), iso-C15:0 (ρ = 0.78), and anteiso-C15:0 (ρ = 0.63). Use of random forest algorithm showed that BCFA such as anteiso-C15:0, iso-C16:0, iso-C17:0, iso-C18:0, and total even-chain BCFA could be used as biomarkers to differentiate diarrheic calves from healthy ones. Our findings generated fundamental knowledge on the potential roles of BCFA in neonatal calf gut health. Follow-up studies with larger animal populations are warranted to validate the feasibility of using BCFA as indicators of health status in neonatal calves.

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: Observational
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)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.249
Teacher spread0.238 · 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

Citations35
Published2020
Admission routes2
Has abstractyes

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