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Record W4385476964 · doi:10.1007/s00216-023-04868-4

Preparation of 18O-labelled azaspiracids for accurate quantitation using liquid chromatography–mass spectrometry

2023· article· en· W4385476964 on OpenAlexafffund
Elliott J. Wright, Juris Meija, Pearse McCarron, Christopher O. Miles

Bibliographic record

VenueAnalytical and Bioanalytical Chemistry · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Toxins and Detection Methods
Canadian institutionsNational Research Council Canada
FundersNational Research Council CanadaOhio State University
KeywordsChemistryChromatographyIsotope dilutionMass spectrometryMarine toxinBiomoleculeStable isotope ratio

Abstract

fetched live from OpenAlex

Abstract Azaspiracids (AZAs) are a group of polyether marine algal toxins known to accumulate in shellfish, posing a risk to human health and the seafood industry. Analysis of AZAs is typically performed using LC–MS, which can suffer from matrix effects that significantly impact the accuracy of measurement results. While the use of isotopic internal standards is an effective approach to correct for these effects, isotopically labelled standards for AZAs are not currently available. In this study, 18 O-labelled AZA1, AZA2, and AZA3 were prepared by reaction with H 2 18 O under acidic conditions, and the reaction kinetics and sites of incorporation were studied using LC–HRMS/MS aided by mathematical analysis of their isotope patterns. Analysis of the isotopic incorporation in AZA1 and AZA3 indicated the presence of four exchangeable oxygen atoms. Excessive isomerization occurred during preparation of 18 O-labelled AZA2, suggesting a role for the 8-methyl group in the thermodynamic stability of AZAs. Neutralized mixtures of 18 O-labelled AZA1 and AZA3 were found to maintain their isotopic and isomeric integrities when stored at −20 °C and were used to develop an isotope-dilution LC–MS method which was applied to reference materials of shellfish matrices containing AZAs, demonstrating high accuracy and excellent reproducibility. Preparation of isotopically labelled compounds using the isotopic exchange method, combined with the kinetic analysis, offers a feasible way to obtain isotopically labelled internal standards for a wide variety of biomolecules to support reliable quantitation. Graphical Abstract

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.351
Teacher spread0.315 · 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.

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

Citations3
Published2023
Admission routes2
Has abstractyes

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