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Record W2008401674 · doi:10.1021/jf302100m

Comparative Proteomic Analysis of Egg White Proteins under Various Storage Temperatures

2012· article· en· W2008401674 on OpenAlexaff
Ning Qiu, Meihu Ma, Lei Zhao, Wen Liu, Yuqi Li, Yoshinori Mine

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEgg whiteOvalbuminOvotransferrinStorage proteinProteomeClusterinChemistryProteomicsWarehouseTrehaloseBiochemistryFood scienceBiologyImmunology

Abstract

fetched live from OpenAlex

Although the effect of storage temperature was suggested to be a more important factor than that of storage time on changes in unfertilized egg white proteins, no comprehensive analysis of the thermally induced egg white protein changes was carried out. This study presents a proteomic analysis of the changes in unfertilized egg white proteins after 15 days of storage at 4, 20, and 37 °C. Using two-dimensional electrophoresis followed by MALDI-TOF MS/MS, 32 protein spots representing 8 proteins were identified with significant differences in abundance when stored at different temperatures. An accelerated degradation of ovalbumin, possibly resulting from the reduction of antiprotease, was observed after the storage at higher temperature. In addition, an increase in the formation of ovalbumin complexes and a decrease in lipocalin family proteins were detected with increasing storage temperature, which may indicate a thermally promoted change in chicken eggs. The decrease of clusterin during the high-temperature storage was suggested to be an effective biomarker for egg quality evaluation. These findings will give insight into the effects of storage temperature on changes in unfertilized egg white proteins during storage and provide a better understanding of the thermally induced biochemical changes that may affect the egg deteriorative process.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.229
Teacher spread0.208 · 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 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

Citations71
Published2012
Admission routes1
Has abstractyes

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