Alternaria toxins alternariol and alternariol monomethyl ether in grain foods in Canada
Bibliographic record
Abstract
Alternaria alternata has been reported to be the most common fungus on Canadian Western wheat. The Alternaria toxins alternariol (AOH) and alternariol monomethyl ether (AME) are mutagenic in vitro and there is also limited evidence for carcinogenic properties. They have been found in wheat from Europe, Argentina, China and Australia, but they have not been looked for in Canadian grains or grain foods. In the present study, 83 samples of grain-based food sold in Canada, including flour, bran, breakfast cereals, infant cereals and bread, were analysed for AOH and AME using extraction with methanol, clean-up on combined aminopropyl/C18 solid phase extraction (SPE) columns, and liquid chromatography (LC) with tandem mass spectrometric (MS/MS) determination. The overall average recoveries of AOH and AME from a variety of spiked cereal foods (n = 13) were 45 ± 9% and 53 ± 9%, which could be attributed mainly to MS matrix effects The instrumental limits of detection (LOD) were 0.34 ng/g and 0.13 ng/g for AOH and AME, respectively, and the instrumental limits of quantitation (LOQ) were 1.1 and 0.43 ng/g. Of 83 samples analysed, 70 were positive for AOH (up to 63 ng/g, in a soft wheat bran) and 64 contained AME (up to 12 ng/g in a bran-based breakfast cereal). Of particular interest was the presence of AOH and/or AME in 27 out of 30 infant foods (up to 4.4 ng/g and 9.0 ng/g, respectively, in a sample of multigrain cereal).
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".