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Record W3208106981 · doi:10.3390/foods10112696

Production, Purification, and Potential Health Applications of Edible Seeds’ Bioactive Peptides: A Concise Review

2021· review· en· W3208106981 on OpenAlexafffund
Mrinal Samtiya, Sovon Acharya, Kush Kumar Pandey, Rotimi E. Aluko, Chibuike C. Udenigwe, Tejpal Dhewa

Bibliographic record

VenueFoods · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of OttawaUniversity of Manitoba
FundersScience and Engineering Research BoardNatural Sciences and Engineering Research Council of CanadaDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsBiotechnologyBiochemical engineeringChemistryFood scienceBiologyEngineering

Abstract

fetched live from OpenAlex

Edible seeds play a significant role in contributing essential nutritional needs and impart several health benefits to improve the quality of human life. Previous literature evidence has confirmed that edible seed proteins, their enzymatic hydrolysates, and bioactive peptides (BAPs) have proven and potential attributes to ameliorate numerous chronic disorders through the modulation of activities of several molecular markers. Edible seed-derived proteins and peptides have gained much interest from researchers worldwide as ingredients to formulate therapeutic functional foods and nutraceuticals. In this review, four main methods are discussed (enzymatic hydrolysis, gastrointestinal digestion, fermentation, and genetic engineering) that are used for the production of BAPs, including their purification and characterization. This article's main aim is to provide current knowledge regarding several health-promoting properties of edible seed BAPs in terms of antihypertensive, anti-cancer, antioxidative, anti-inflammatory, and hypoglycemic activities.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.336
Teacher spread0.311 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations32
Published2021
Admission routes2
Has abstractyes

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