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Record W3041078463 · doi:10.1007/s12649-020-01154-7

Slaughterhouse By-Product Valorization: Hydrolysis Degree Modification for Higher Antimicrobial Recovery by Electroseparation

2020· article· en· W3041078463 on OpenAlexaff
Rémi Przybylski, Laurent Bazinet, Mostafa Kouach, Jean‐François Goossens, Pascal Dhulster, Loubna Firdaous, Naïma Nedjar‐Arroume

Bibliographic record

VenueWaste and Biomass Valorization · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversité Laval
FundersEuropean Commission
KeywordsHydrolysateUltrafiltration (renal)HydrolysisChemistryContext (archaeology)PreservativeFood sciencePeptideHemoglobinAntimicrobialChromatographyPopulationAntimicrobial peptidesBiotechnologyBiochemistryOrganic chemistryBiologyMedicine

Abstract

fetched live from OpenAlex

Abstract In the actual context of food safety and circular economy, the separation of the α137–141 antimicrobial peptide (TSKYR, 653 Da) coming from the hydrolysis of bovine hemoglobin, a non-valorized slaughterhouse by-product, and its reuse as a preservative agent for food products during storage would be of major interest. However, depending on the degree of hydrolysis (DH) of the bovine hemoglobin, the TSKYR peptide environment into the hydrolysate will be different and would impact its recovery yield by electrodialysis with ultrafiltration membranes (EDUF), a hybrid and eco-friendly technology. In this context, five DHs (3, 5, 10, 13 and 18%) were investigated to study the influence of the peptide populations on the α137–141 selective separation by EDUF. It appeared from these results that the most appropriate DH was of 5% since a lower population of peptides between 500 and 1000 Da was present and the subunits of hemoglobin were already digested. Hence, an enrichment factor of about 13 folds for the α137–141 was obtained in comparison with the initial hydrolysate. At our knowledge, it was the first time that the effect of the hydrolysis degree of a protein is demonstrated to impact preferentially the separation of a specific peptide by EDUF. Graphic Abstract

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 score0.173
Threshold uncertainty score0.866

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 head0.023
GPT teacher head0.240
Teacher spread0.216 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

Explore more

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