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Record W2801197990 · doi:10.1007/s10989-018-9713-x

Production and Identification of Biologically Active Peptides Derived from By-product of Hen Egg-Yolk Phospholipid Extraction

2018· article· en· W2801197990 on OpenAlexaff
Ewelina Eckert, Aleksandra Zambrowicz, Łukasz Bobak, Agnieszka Zabłocka, J. Chrzanowska, Tadeusz Trziszka

Bibliographic record

VenueInternational Journal of Peptide Research and Therapeutics · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of Alberta
FundersEuropean Regional Development FundEuropean CommissionKrajowy Naukowy Osrodek WiodacyNational Research Centre
KeywordsProteaseYarrowiaProteasesChemistryYeastYolkBiochemistryAntioxidantSize-exclusion chromatographySerine proteaseHydrolysateChromatographyPhospholipidFood scienceMembraneEnzymeHydrolysis

Abstract

fetched live from OpenAlex

Biologically active peptides derived from food proteins have been increasingly popular due to their therapeutic properties. This paper attempts to utilize a by-product of phospholipid extraction from egg yolk as a source of peptides with antioxidant [radical scavenging capacity, Fe 2+ chelating effect, reducing power (FRAP)] and ACE-inhibitory activity. In addition, in this research we analysed the ability to release bio-peptides of a non-commercial proteases obtained from Yarrowia lipolytica yeast. Yeast serine protease exert greater ability to evaluate antioxidant and ACE inhibitory activity than yeast aspartyl protease during degradation of protein by-product. Purification procedures including membrane filtration, gel filtration chromatography and reversed-phase high-performance liquid chromatography led to obtain a decapeptide QSLVSVPGMS with strong DPPH free radical scavenging and ACE inhibitory activities. A new application of the serine protease from Y. lipolytica yeast in the production of bioactive peptides from egg yolk protein by-product was demonstrated.

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 score0.036
Threshold uncertainty score0.309

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 head0.043
GPT teacher head0.366
Teacher spread0.322 · 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

Citations36
Published2018
Admission routes1
Has abstractyes

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