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Record W2204670089 · doi:10.1021/acs.jafc.5b04230

Antioxidant Peptides Identified from Ovotransferrin by the ORAC Method Did Not Show Anti-Inflammatory and Antioxidant Activities in Endothelial Cells

2015· article· en· W2204670089 on OpenAlexafffund
Forough Jahandideh, Subhadeep Chakrabarti, Sandra T. Davidge

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Livestock and Meat Agency
KeywordsOxygen radical absorbance capacityOvotransferrinAntioxidantChemistryBiochemistryCell adhesion moleculePeptideVCAM-1SuperoxideTumor necrosis factor alphaSuperoxide dismutaseCell adhesionCellImmunologyEnzymeAntioxidant capacityBiologyEgg white

Abstract

fetched live from OpenAlex

Oxygen radical absorbance capacity (ORAC) is a widely used method of measuring antioxidant capacities of various antioxidant components. Surprisingly, 16 antioxidant peptides previously identified from egg protein ovotransferrin using the ORAC method did not show any anti-inflammatory and antioxidant activities in cells. After simulated gastro-intestinal digestion (GID), several peptide digests significantly reduced the expression of tumor necrosis factor-α (TNF-α)-induced pro-inflammatory intercellular cell adhesion molecule-1 (ICAM-1) by 65.7 ± 10.4% and vascular cell adhesion molecule-1 (VCAM-1) by 53.5 ± 9.6% to 61.0 ± 14.5%, but only GWNI reduced TNF-α-activated superoxide generation by 71.0 ± 12.9% when tested with dihydroethidium (DHE) assay. Mass spectrometer analysis identified two new peptides, GWN and GW, in the GWNI digest; however, only GW reduced TNF-α-induced VCAM-1 expression (64.3 ± 20.6%) significantly compared to the TNF-α treated cells. Our study suggested that ORAC lacked biological relevance in assessing bioactive peptides.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.223
Teacher spread0.212 · 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

Citations53
Published2015
Admission routes2
Has abstractyes

Explore more

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