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A simple procedure for sulfation and 35S radiolabelling of paralytic shellfish poisoning (PSP) gonyautoxins

2006· article· en· W2158263326 on OpenAlexafffund
M. V. Laycock, Jaroslav A. Kralovec, Robert C. Richards

Bibliographic record

VenueNatural Toxins · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Toxins and Detection Methods
Canadian institutionsInstitute for Marine Biosciences
FundersNational Research Council Canada
KeywordsSaxitoxinChemistrySulfateSulfationChromatographyHydrolysisParalytic shellfish poisoningDimethylformamideToxinShellfishOrganic chemistryBiochemistrySolventFishery

Abstract

fetched live from OpenAlex

A method is described to sulfate PSP toxins at various positions in the molecule and to prepare 35S labelled compounds using H2(35)SO4 in the presence of dicyclohexylcarbodiimide (DCC). The 11-sulfates of saxitoxin and neosaxitoxin, known as gonyautoxins, are often the most abundant of the PSP toxins in algae and contaminated shellfish. Receptor site binding and antibody assays based on these analogues should, therefore, better reflect toxicity than those in which saxitoxin is used. Although the specific activity of 35S-gonyautoxins is lower than that of commercially available 3H-saxitoxin, the label is strongly bound and is not lost through proton exchange with water as occurs with tritiated saxitoxin. The labelling procedure is rapid, inexpensive and can be done on a small scale. Sulfate can be removed from the 11-position of GTX's in methanolic-HCl and from the 21-position by mild acid hydrolysis and H2(35)SO4 added in 5-10-fold excess. Addition or exchange occurs rapidly on mixing DCC in dimethylformamide with dry toxin and sulfate. Reaction conditions were optimized and reaction products identified by capillary electrophoresis, autoradiography and ionspray mass spectrometry. Together with methods for selective removal of sulfate, the sulfation reaction provides an additional way to prepare some of the naturally occurring derivatives of saxitoxin, many of which are sulfates.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.536

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 head0.008
GPT teacher head0.252
Teacher spread0.244 · 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

Citations4
Published2006
Admission routes2
Has abstractyes

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