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Development of faba protein-tannic acid conjugate via free radical grafting: Evaluation of interaction mechanisms and antioxidative properties

2024· article· en· W4405428278 on OpenAlexafffund
Shahrzad Sharifimehr, Jason Maley, Supratim Ghosh

Bibliographic record

VenueFood Chemistry · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationMinistry of Agriculture - SaskatchewanUniversity of Saskatchewan
KeywordsTannic acidConjugateGraftingChemistryBiochemistryOrganic chemistryMathematicsPolymer

Abstract

fetched live from OpenAlex

A soluble fraction of faba bean protein was conjugated with tannic acid via the free-radical grafting method using a mixture of ascorbic acid and hydrogen peroxide. Surface plasmon resonance showed a strong bonding between them, while the free amino and thiol group measurements indicated tannic acid's bonding with the amino groups and cysteine residues on the proteins. Structural analysis using intrinsic fluorescence and surface hydrophobicity demonstrated tannic acid's interaction with the aromatic and hydrophobic amino acids of the protein. The conjugate showed about 77 % DPPH, 89 % ABTS, and 83 % hydroxyl radical scavenging activities and superior ferric-reducing ability compared to the protein alone and the mixture of protein and tannic acid. Electron paramagnetic resonance (EPR) spectroscopy revealed 97.8 % radical scavenging ability of the conjugate, comparable to the pure tannic acid. The exceptional antioxidative properties of conjugate can be utilized to delay lipid oxidation in protein-stabilized oil-in-water emulsions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.054
GPT teacher head0.250
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2024
Admission routes2
Has abstractyes

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