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Record W4402541292 · doi:10.1093/jas/skae234.213

433 Use of polyclonal antibodies to improve the efficiency of rumen function

2024· article· en· W4402541292 on OpenAlexaff
Gleise Medeiros da Silva

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPolyclonal antibodiesRumenAntibodyAnimal scienceFunction (biology)ChemistryFood scienceBiologyCell biologyImmunologyFermentation

Abstract

fetched live from OpenAlex

Abstract Technologies such as polyclonal antibody preparations (PAP) have been investigated as a tool to improve rumen function, by targeting specific bacteria or molecules. While PAP can be sourced from the serum of immunized mammals, isolating targeted avian-derived antibodies (immunoglobulin Y; IgY) from egg yolk gained popularity due to its reduced impact on hens and greater IgY concentration in yolks. Advantages of avian-derived PAP utilization include cost-effectiveness and convenient production, high stability, and reduced cross-reactivity compared with other PAPs. Furthermore, IgY does not activate the host immune complement system, as observed with PAP derived from mammalian serum. Several proposed strategies explain how PAP might protect the host. It is suggested that PAP can agglutinate bacteria, inhibit bacterial adhesion, suppress bacterial virulence factors, and neutralize toxins. Avian-derived PAP, mainly administered as a direct-fed product in beef and dairy cattle diets, has been studied for its impact on specific rumen microbial populations, especially during high-grain feeding. Research confirms the effectiveness of PAP-IgY in inhibiting the growth of targeted bacteria. In beef steers, feeding PAP-IgY against Streptococcus bovis and Fusobacterium necrophorum resulted in growth inhibition, while IgY against cellulolytic rumen bacteria also showed efficacy in reducing the growth of the targeted strains in vitro. In other studies, PAP-IgY targeting S. bovis and F. necrophorum increased ruminal pH in beef steers and heifers and dairy cows, while also cattle-fed PAP-IgY against F. necrophorum had reduced severity of liver abscesses. When performance was evaluated, PAP-IgY against S. bovis improved feed efficiency of feedlot beef steers, and milk production increased when dairy cows were supplemented with PAP-IgY against lipopolysaccharides, with no observed impact on cow health status. However, not all studies have consistently demonstrated positive effects of PAP-IgY on nutrient digestibility or on mitigating systemic inflammation during high-grain feeding. A recent study revealed that supplementation with PAP-IgY against Methanobrevibacter ruminantium M1 decreased methane output ex-situ and tended to increase molar proportion of propionate in beef steers. In summary, polyclonal antibody preparations, particularly avian-derived IgY, offer a promising alternative to improve rumen function and animal performance. This is evidenced by increased ruminal pH during high grain feeding, inhibition of targeted bacterial growth, and, most recently, methane reduction. However, not all studies demonstrate consistent effects regarding nutrient digestibility. Further research is needed to refine recommendations, including dosage and antibody combinations, and to explore the broader impacts of PAP-IgY supplementation on ruminal and systemic variables to optimize livestock performance.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.063
GPT teacher head0.363
Teacher spread0.300 · 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 designBench or experimental
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
Published2024
Admission routes1
Has abstractyes

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