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Angiotensin‐I Converting Enzyme Inhibitory and Antioxidant Activities of Egg Protein Hydrolysates Produced with Gastrointestinal and Nongastrointestinal Enzymes

2011· article· en· W2090694370 on OpenAlexafffund
Sun-Jong You

Bibliographic record

VenueJournal of Food Science · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaWorld Health Organization
KeywordsHydrolysateAntioxidantEnzymeInhibitory postsynaptic potentialChemistryAngiotensin-converting enzymeRenin–angiotensin systemPharmacologyBiochemistryEndocrinologyBiologyHydrolysis

Abstract

fetched live from OpenAlex

Egg is a well-known rich source of bioactive peptides. In this study, egg protein (egg white and egg yolk proteins) hydrolysates were produced with gastrointestinal enzymes (pepsin and pancreatin) or nongastrointestinal enzymes (thermolysin and alcalase), and fractionated by ultrafiltration and cation exchange chromatography. Angiotensin-I converting enzyme (ACE) inhibitory and antioxidant activities, amino acid composition and molecular weight distribution were studied, and the physicochemical properties were related with the bioactivities. Our results showed that egg protein hydrolysates produced with non-GI enzymes (thermolysin and alcalase) showed significantly higher ACE inhibitory activity, whereas similar or even lower antioxidative activities, than those of hydrolysates produced with GI enzymes. ACE-inhibitory activity significantly correlated with the amino acid composition, especially the proportion of positively charged amino acid, whereas antioxidant activities correlated with the proportion of low molecular weight peptides under 500 Da. Understanding the relationship between the bioactivities and physicochemical properties of the hydrolysates/fractions is important to facilitate the development technologies for preparing fractions with improved bioactivities.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.211
Teacher spread0.197 · 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

Citations65
Published2011
Admission routes2
Has abstractyes

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