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Record W4416451652 · doi:10.1016/j.fochx.2025.103277

Comparison of LC-MS methods for the quantitation of ciguatoxins in fish – A collaborative study

2025· article· en· W4416451652 on OpenAlexaff
Astrid Spielmeyer, Vincent Hort, J. Sam Murray, Cintia Flores, Andrés Sanchez-Henao, Emillie Passfield, Caroline Desbourdes, Lourdes Barreiro-Crespo, Mònica Campàs, Jorge Diogène, Jean Turquet, Christopher R. Loeffler, Maria Rambla-Alegre

Bibliographic record

VenueFood Chemistry X · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Toxins and Detection Methods
Canadian institutionsContinental (Canada)
FundersH2020 European Research CouncilEuropean Social FundAgencia Estatal de InvestigaciónSerono Symposia International FoundationMinisterio de Ciencia e InnovaciónGeneralitat de CatalunyaAgencia Canaria de Investigación, Innovación y Sociedad de la InformaciónAgence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du TravailMinistry of Business, Innovation and EmploymentUniversidad de Las Palmas de Gran CanariaCentres de Recerca de CatalunyaMinisterio de Ciencia, Innovación y UniversidadesEuropean Food Safety AuthorityBanco SantanderUniversità degli Studi di Napoli Federico II
KeywordsCiguatoxinCiguateraFish <Actinopterygii>Certified reference materialsSample (material)

Abstract

fetched live from OpenAlex

Ciguatoxins (CTXs) are marine biotoxins that can contaminate seafood and if consumed can result in ciguatera poisoning (CP). The analysis of CTXs is challenging, as they occur in complex tissue matrices, cause CP symptoms at trace amounts (<1 μg kg −1 ), and certified reference materials are not available. Currently, no standard operating protocols exist for sample preparation or instrumental analysis. Five laboratories worldwide participated in this first-time method comparison study, which used sample extracts containing different CTX groups (CTX4A group, CTX3C group, C-CTX-1) to identify factors impacting CTX quantitation using LC-MS/MS and LC-HRMS. Matrix effects were found to significantly influence CTX quantitation, along with factors such as instrument, eluents, or selected precursor ion. CTXs were quantified using commercially available, non-certified CTX1B and CTX3C standards. Analogues of the CTX groups behaved differently with regard to matrix effects and suitable calibrants with differences of more than a factor of 10 between laboratories. • Five laboratories worldwide participated in a collaborative study for CTX analysis. • CTX analogues in six sample extracts were determined by LC-MS/MS and LC-HRMS. • Varying matrix effects were observed, being instrument and CTX analogue dependent. • The external calibrant used was a determining factor for CTX quantification. • The study provides unprecedented insight into method variability for CTX analysis.

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)0.001
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 score0.181
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.037
GPT teacher head0.432
Teacher spread0.394 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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