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Record W4415355040 · doi:10.1016/j.psj.2025.105980

Protein oxidation in feed: Occurrence, monitoring, and mitigation strategies

2025· article· en· W4415355040 on OpenAlexaff
Peng Lu, Peng Wang, Yanmin Zhou, Chengbo Yang

Bibliographic record

VenuePoultry Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAntioxidantAmino acidFood proteinReactive oxygen speciesDigestion (alchemy)Oxidation reductionCovalent bondProtein quality

Abstract

fetched live from OpenAlex

Protein oxidation is defined as a covalent modification caused by reactive oxygen species (ROS) or secondary oxidized by-products. The mechanisms and influences of protein oxidation on animal-derived food quality have been studied for many years, but its effects on feedstuff and animal health are largely unknown. Protein oxidation causes oxidation in both amino acid side chains and protein backbones, resulting in the formation of harmful substances and a decrease in nutritional value. Excessive levels of protein oxidation in animal diets have been associated with various biological consequences in animals, including reduced growth performance, compromised antioxidant capacity, immune disorders, and intestinal digestion and absorption, and antioxidant capacity. Protein oxidation in feeds can be detected by various methods such as spectrophotometric assay and fluorescence spectroscopy and controlled by several approaches such as supplementation of antioxidants and nutrition regulation. In this review, the basic principles of protein oxidation and its detection methods, effects on animals, and preventive strategies are discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.727
Threshold uncertainty score0.165

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.288
Teacher spread0.259 · 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.

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

Citations3
Published2025
Admission routes1
Has abstractyes

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