Structural Characterization of Maitotoxins Produced by Toxic Gambierdiscus Species
Bibliographic record
Abstract
Identifying compounds responsible for the observed toxicity of the Gambierdiscus species is a critical step to ascertaining whether they contribute to ciguatera poisoning. Macroalgae samples were collected during research expeditions to Rarotonga (Cook Islands) and North Meyer Island (Kermadec Islands), from which two new Gambierdiscus species were characterized, G. cheloniae CAWD232 and G. honu CAWD242. Previous chemical and toxicological investigations of these species demonstrated that they did not produce the routinely monitored Pacific ciguatoxins nor maitotoxin-1 (MTX-1), yet were highly toxic to mice via intraperitoneal (i.p.) injection. Bioassay-guided fractionation of methanolic extracts, incorporating wet chemistry and chromatographic techniques, was used to isolate two new MTX analogs; MTX-6 from G. cheloniae CAWD232 and MTX-7 from G. honu CAWD242. Structural characterization of the new MTX analogs used a combination of analytical chemistry techniques, including LC–MS, LC–MS/MS, HR–MS, oxidative cleavage and reduction, and NMR spectroscopy. A substantial portion of the MTX-7 structure was elucidated, and (to a lesser extent) that of MTX-6. Key differences from MTX-1 included monosulfation, additional hydroxyl groups, an extra double bond, and in the case of MTX-7, an additional methyl group. To date, this is the most extensive structural characterization performed on an MTX analog since the complete structure of MTX-1 was published in 1993. MTX-7 was extremely toxic to mice via i.p. injection (LD50 of 0.235 µg/kg), although no toxicity was observed at the highest dose rate via oral administration (155.8 µg/kg). Future research is required to investigate the bioaccumulation and likely biotransformation of the MTX analogs in the marine food web.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".