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Record W4389138059 · doi:10.1163/23524588-20220159

Limited hydrolysis combined with glycation modification of silkworm pupae (Bombyx mori) proteins: structure-function relationship

2023· article· en· W4389138059 on OpenAlexaff
Shaolin Xie, Xiaotian Wang, Ying Zhou, Lu Ma, Yong Hou, Olugbenga P. Soladoye, Yuan Zhang, Yu Fu

Bibliographic record

VenueJournal of Insects as Food and Feed · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsAlberta Crop Industry Development FundGovernment of CanadaAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBombyx moriGlycationHydrolysisChemistryPupaXyloseBiochemistryBombyxEnzymatic hydrolysisSugarPosttranslational modificationFood scienceEnzymeBiologyLarvaBotany

Abstract

fetched live from OpenAlex

Abstract In order to explore the impacts of limited hydrolysis combined with glycation modification on the structure, functional properties, allergenicity, and volatile compounds of silkworm pupae protein, the crude silkworm pupae protein was firstly extracted by alkaline-solution method, followed by Alcalase-treated limited hydrolysis for 10-30 min. Xylose was subsequently added and reacted for 1 h at 95 °C. Afterwards, the structure, functionality, allergenicity, and volatile compounds before and after modification were analysed. The molecular weight of modified silkworm pupae protein was remarkably decreased. The solubility was improved from 4.7 to 28.6%. The foaming ability was elevated by 21%. The in vitro digestibility was elevated by 34.0-44.4%. Furthermore, the abundance of six potential allergic proteins was remarkably reduced. In addition, the contents of off-flavour compounds in modified silkworm pupae proteins substantially decreased. Overall, limited hydrolysis combined with glycation modification can improve the functionality and flavour of silkworm pupae protein, while reduce the allergenicity.

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 score0.241
Threshold uncertainty score0.403

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 head0.015
GPT teacher head0.235
Teacher spread0.220 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

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