Reactivity of β-Methylamino-<scp>l</scp>-alanine in Complex Sample Matrixes Complicating Detection and Quantification by Mass Spectrometry
Bibliographic record
Abstract
β-methylamino-l-alanine (BMAA) is a naturally occurring nonprotein amino acid originally discovered in cycad seeds and traditional foods of the Chamorro people of Guam. Recent research has implicated BMAA as a potential factor in neurodegenerative disease and described the production of BMAA in cyanobacteria, but conflicting results have complicated the interpretation of data. We hypothesized that the reactivity of BMAA with metal ions in the sample matrix and the formation of metal adducts in electrospray ionization mass spectrometry (MS) analysis confound results. Dilute solutions of TCA, MgCl(2), NaCl, CuCl(2), ZnCl(2) (0.01 M), or artificial ocean water (Instant Ocean, 3.5 g/L) reduced the signal attributable to the BMAA M + H(+) peak by 78-99.7%. The degree of adduct formation was significantly affected by MS settings such as induction voltage. A number of the detected ion peaks in BMAA standards were consistent with the formation of metal-BMAA complexes in addition to the adduct formation. A standard of Zn(BMAA)(2) was synthesized, and the effects of sample preparation, derivatization, column chromatography, pH, and interactions with serine were determined. Together, these data demonstrate that sample matrix, formation of adducts, and mass spectrometry settings complicate analysis of BMAA, that analysis by detection of the parent ion and daughter ion fragmentation patterns are highly susceptible to false negative findings, and that failure to detect BMAA cannot be considered proof of absence of the compound.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".