Analysis of toxins in snails responsible for two poisoning incidents in China
Bibliographic record
Abstract
Poisoning incidents caused by eating snails Nassarius spp. were reported frequently in the last several years in China. Toxins involved in the poisoning incidents were suspected to be paralytic shellfish toxins (PSTs) produced by toxic algal blooms in adjacent sea areas, since the symptoms of the patients closely resembled those caused by PSTs. However, tetrodotoxin was also reported previously in some snail samples. To elucidate the toxins responsible for the poisoning incident, snail samples collected from Fujian Province and Jiangsu Province in 2002 and 2003, resp., were analyzed with hydrophilic interaction liq. chromatog. coupled with mass spectrometry detector (HILIC-MS). High contents of tetrodotoxin (TTX) and its isomers and derivs., including 4-epiTTX, trideoxyTTX, anhydroTTX, deoxyTTX, oxoTTX, were detected in snail samples. The TTX contents in the snail samples collected from Fujian Province and Jiangsu Province were 44.6 μg/g and 129 μg/g, calibrated with TTX std. TTX and its derivs., rather than PSTs, were responsible for the two poisoning incidents in Fujian Province and Jiangsu Province. The closely resemblance of toxin profile between the two snail samples from Fujiang Province and Jiangsu Province suggested that they might have similar toxin sources. However, the origin of TTX and its derivs. in the snails still need more detailed investigation and research.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".