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Record W2058973400 · doi:10.1139/v08-031

Oxyhalogen–sulfur chemistry — Kinetics and mechanism of the bromate oxidation of cysteamine

2008· article· en· W2058973400 on OpenAlexvenueno aff
Moshood K. Morakinyo, Edward Chikwana, Reuben H. Simoyi

Bibliographic record

VenueCanadian Journal of Chemistry · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAldose Reductase and Taurine
Canadian institutionsnot available
FundersDivision of ChemistryNational Science Foundation
KeywordsCysteamineChemistryBromateBromineTaurineKineticsOxidizing agentAqueous solutionMedicinal chemistryInorganic chemistryReaction mechanismOrganic chemistryNuclear chemistryBromideCatalysisBiochemistryAmino acid

Abstract

fetched live from OpenAlex

The kinetics and mechanism of the oxidation of the biologically important molecule, cysteamine, by acidic bromate and molecular bromine have been studied. In excess acidic bromate conditions, cysteamine is oxidized to N-brominated derivatives, and in excess cysteamine the oxidation product is taurine according to the following stoichiometry: BrO 3 – + H 2 NCH 2 CH 2 SH → H 2 NCH 2 CH 2 SO 3 H + Br – . There is quantitative formation of taurine before N-bromination commences. Excess aqueous bromine oxidizes cysteamine to give dibromotaurine: 5Br 2 + H 2 NCH 2 CH 2 SH + 3H 2 O → Br 2 NCH 2 CH 2 SO 3 H + 8Br – + 8H + , while excess cysteamine conditions gave monobromotaurine. The oxidation of cysteamine by aqueous bromine is effectively diffusion-controlled all the way to the formation of monobromotaurine. Further formation of dibromotaurine is dependent on acid concentrations, with highly acidic conditions inhibiting further reaction towards formation of dibromotaurine. The formation of the N-brominated derivatives of taurine is reversible, with taurine regenerated in the presence of a reducing agent such as iodide. This feature makes it possible for taurine to moderate hypobromous acid toxicity in the physiological environment.Key words: cysteamine, hypobromous acid, toxicities, antioxidant.

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 score0.003
Threshold uncertainty score0.373

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 head0.183
Teacher spread0.176 · 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

Citations9
Published2008
Admission routes1
Has abstractyes

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