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Health-promoting properties of bioactive proteins and peptides of garlic (Allium sativum)

2023· review· en· W4387223459 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFood Chemistry · 2023
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicGarlic and Onion Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAllium sativumPhytochemicalPeptideProteomicsBiochemistryAntifungalAntioxidantNutraceuticalAllicinBiologyAlliumBiological activityBiotechnologyChemistryTraditional medicineBotanyMedicineMicrobiology

Abstract

fetched live from OpenAlex

Garlic is a popular food spice with diverse and well-established medicinal properties. Many research interests have been directed toward the biological activities of the phytochemical constituents of garlic. However, prospects of its bioactive proteins and peptides have been understudied to date. With the advances in food proteomics/peptide research, a review of studies on garlic bioactive proteins and peptides, especially on their nature, extraction, and biological activities, is timely. Garlic has been reported to express several proteins, endogenous and protein-derived peptides with interesting bioactivities, including antioxidant, anti-inflammatory, antibacterial, antifungal, anti-proliferative, antiviral, anti-hypertensive and immunomodulatory activities, suggesting their therapeutic and pharmacological potentials. Compared to legumes, the low protein contents of garlic bulbs and their low stability are possible limitations that would hinder future applications. We suggest adopting heterologous expression systems for peptide overproduction and stability enhancement. Therefore, we recommend increased scientific interest in the bioactive peptides of garlic and other spice plants.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.896
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.125
GPT teacher head0.288
Teacher spread0.162 · 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