Analysis of β-N-methylamino-L-alanine (BMAA) in spirulina-containing supplements by liquid chromatography-tandem mass spectrometry
Bibliographic record
Abstract
Over the last decade the amino acid beta-N-methylamino-L-alanine (BMAA) has come under intense scrutiny. International laboratory and epidemiological research continues to support the hypothesis that environmental exposure to BMAA (e.g., through dietary practices, water supply) can promote the risk of various neurodegenerative diseases. A wide variety of cyanobacteria spp. have previously been reported to produce BMAA, with production levels dependent upon species, strain and environmental conditions. Since spirulina (Arthrospira spp.) is a member of the cyanobacteria phylum frequently consumed via dietary supplements, the presence of BMAA in such products may have public health implications. In the current work, we have analyzed ten spirulina-containing samples for the presence of BMAA; six pure spirulina samples from two separate raw materials suppliers, and four commercially-available multi-ingredient products containing 1.45 g of spirulina per 8.5 g serving. Because of controversy surrounding the measurement of BMAA, we have used two complementary liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods: one based on reversed phase LC (RPLC) with derivatization and the other based on hydrophilic interaction LC (HILIC). Potential matrix effects were corrected for by internal standardization using a stable isotope labeled BMAA standard. BMAA was not detected at low limits of detection (80 ng/g dry weight) in any of these product samples. Although these results are reassuring, BMAA analyses should be conducted on a wider sample selection and, perhaps, as part of ongoing spirulina production quality control testing and specifications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".