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Record W2315430544 · doi:10.1021/jf502751n

Thermally Induced Oxidative Decarboxylation of Copper Complexes of Amino Acids and Formation of Strecker Aldehyde

2014· article· en· W2315430544 on OpenAlexafffund
Ossanna Nashalian, Varoujan A. Yaylayan

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryStrecker amino acid synthesisDecarboxylationAldehydeOxidative decarboxylationMaillard reactionAlanineAmino acidOxidative deaminationOrganic chemistryGlycineSchiff baseAcetaldehydeOxidative phosphorylationCopperPolymer chemistryBiochemistryEthanol

Abstract

fetched live from OpenAlex

In the Maillard reaction, independent degradations of amino acids play an important role in the generation of amino-acid-specific products, such as Strecker aldehydes or their Schiff bases. Such oxidative decarboxylation reactions are expected to be enhanced in the presence of metals. Preliminary studies performed through heating of alanine and various metal salts (Cu, Fe, Zn, and Ca) under pyrolytic conditions indicated that copper(II) and iron(III) because of their high oxidation potentials were the only metals able to induce oxidative decarboxylation of amino acids and formation of Strecker aldehyde or its derivatives as detected by gas chromatography/mass spectrometry. Furthermore, studies performed with synthetic alanine and glycine copper complexes indicated that they constituted the critical intermediates undergoing free-radical oxidative degradation, followed by the loss of carbon dioxide and the generation of Strecker aldehydes, which were detected either as stable Schiff base adducts or incorporated in moieties, such as pyrazine or pyridine derivatives.

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 score0.051
Threshold uncertainty score0.190

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 head0.254
Teacher spread0.239 · 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

Citations42
Published2014
Admission routes2
Has abstractyes

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