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Record W2312928844 · doi:10.1021/jf5005989

Interaction of Flavanols with Amino Acids: Postoxidative Reactivity of the B-Ring of Catechin with Glycine

2014· article· en· W2312928844 on OpenAlexaff
Paula Vanessa Guerra, Varoujan A. Yaylayan

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2014
Typearticle
Languageen
FieldMedicine
TopicTea Polyphenols and Effects
Canadian institutionsMcGill University
Fundersnot available
KeywordsChemistryCatechinMaillard reactionAdductGlycineAmino acidReactivity (psychology)Organic chemistryAntioxidantStereochemistryBiochemistryPolyphenol

Abstract

fetched live from OpenAlex

Flavanol-related structures such as epicatechin and catechins have been associated with potential antioxidant activity in food and are known to interfere with the Maillard reaction through scavenging of reactive dicarbonyl compounds. High-resolution ESI-TOF mass spectrometry and an isotope labeling technique were used to assess the reactivity of glycine with (+)-catechin heated under oxidative conditions at 120 °C for 70 min. Evidence based on accurate mass analysis of the products obtained and the isotope incorporation pattern of [(13)C-1]glycine, [(13)C-2]glycine, and [(15)N]glycine experiments indicated that (+)-catechin formed various adducts with glycine; two of them incorporated a single amino acid, and three adducts incorporated two amino acid moieties. Some of these adducts underwent dehydration reaction at ring C, and in some the C-ring remained intact. Detailed MS/MS analyses of the fragmentation patterns of these adducts have confirmed the addition of amino acid moieties to the oxidized B-ring of (+)-catechin through the formation of Schiff bases. Formation of such nonvolatile (+)-catechin/amino acid adducts provides insight into how amino acid can have the potential of modifying the antioxidant properties of (+)-catechin and how catechin in turn has the potential of modifying the profile of the Maillard reaction.

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 score0.264
Threshold uncertainty score0.149

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 head0.006
GPT teacher head0.204
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 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

Citations51
Published2014
Admission routes1
Has abstractyes

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