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Record W4388181334 · doi:10.1093/jas/skad341.031

66 Whole-Body Biogeography of the Bacterial Microbiota in Newborn Calves and Response of These Communities to Prenatal Vitamin and Mineral Supplementation

2023· article· en· W4388181334 on OpenAlexaff
Sarah M. Luecke, Devin B. Holman, Kaycie N. Schmidt, Jennifer L Hurlbert, Ana Clara B Menezes, Kerri A Bochantin, James D Kirsch, Friederike Baumgaertner, Kevin K. Sedivec, Kendall C Swanson, Carl R Dahlen, Samat Amat

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyColostrumMicrobiomePhysiologyVaginaGestationFetusPregnancyImmunologyAnatomyAntibodyBioinformatics

Abstract

fetched live from OpenAlex

Abstract During gestation, alterations in maternal nutrition during fetal development may alter growth trajectory and metabolic function in the developing fetus. Additionally, there is increasing evidence that the fetal microbiome also influences developmental outcomes. Research in this area is limited, and gastrointestinal microbiota has been the primary focus in cattle. Our objective was to assess the whole-body biogeography of the newborn calf microbiota and the response of these microbial communities and the calf immune system to prenatal vitamin and mineral (VTM) supplementation. Samples were collected from the hoof, liver, lung, nasal cavity, eye, rumen (tissue and fluid), and vagina of female beef calves that were born from dams that received either prenatal VTM or no VTM (Control; n = 7/group) throughout gestation. Calves were separated from their dams immediately after birth and fed colostrum replacement until euthanasia at 30 h post-initial colostrum feeding. The microbiota from swab and tissue samples were assessed using 16S rRNA gene sequencing (V4) and qPCR. Serum samples were processed for multiplex quantification of 15 cytokines and chemokines. Sequencing revealed the presence of a relatively diverse and complex microbiota in each of the 7 anatomical locations. The community structure of the hoof, liver, ocular, and vaginal microbiota were significantly different from the ruminal microbiota (0.64 ≥ R2 ≥ 0.12, P ≤ 0.003). The respiratory (nasal and lung) had similar community structures to that of ocular, vaginal, and ruminal fluid microbiota (P > 0.11). The ocular, hoof, and vagina had the greatest microbial richness (observed ASVs; P < 0.05) but similar diversity (Shannon; P > 0.05) compared with other samples. The liver and ruminal fluid had the least microbially rich communities, the latter also being the least diverse (P < 0.05). Firmicutes, Actinobacteriota, and Proteobacteria were the dominant phyla across all sample types, but their abundance varied by location. The ruminal fluid and hoof had the greatest bacterial concentration, while the liver, lung and ruminal tissue had reduced bacterial abundance as estimated by qPCR. An influence of VTM supplementation on microbial community structure was only detected in the ruminal fluid microbiota (P < 0.01). While prenatal VTM supplementation did not affect the nasal, lung, liver, and hoof microbiota, differences (P < 0.05) were detected in microbial richness (vagina), diversity (ruminal tissue and fluid, ocular), composition at the phylum level (ruminal tissue, ocular, and vagina), and total bacterial abundance (ocular and vagina). Among the 15 cytokines evaluated, the concentration of IP-10 was increased (P = 0.02) while IL-4 and IL-17A were reduced (P < 0.05)

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 score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.309
Teacher spread0.291 · 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
Published2023
Admission routes1
Has abstractyes

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