Detection of Cyanotoxins in Algae Dietary Supplements
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Algae dietary supplements are marketed worldwide as natural health products. Although their proprieties have been claimed as beneficial to improve overall health, there have been several previous reports of contamination by cyanotoxins. These products generally contain non-toxic cyanobacteria, but the methods of cultivation in natural waters without appropriate quality controls allow contamination by toxin producer species present in the natural environment. In this study, we investigated the presence of total microcystins, seven individual microcystins (RR, YR, LR, LA, LY, LW, LF), anatoxin-a, dihydroanatoxin-a, epoxyanatoxin-a, cylindrospermopsin, saxitoxin, and β-methylamino-l-alanine in 18 different commercially available products containing Spirulina or Aphanizomenon flos-aquae. Total microcystins analysis was accomplished using a Lemieux oxidation and a chemical derivatization using dansyl chloride was needed for the simultaneous analysis of cylindrospermopsin, saxitoxin, and β-methylamino-l-alanine. Moreover, the use of laser diode thermal desorption (LDTD) and ultra-high performance liquid chromatography (UHPLC) both coupled to high resolution mass spectrometry (HRMS) enabled high performance detection and quantitation. Out of the 18 products analyzed, 8 contained some cyanotoxins at levels exceeding the tolerable daily intake values. The presence of cyanotoxins in these algal dietary supplements reinforces the need for a better quality control as well as consumer’s awareness on the potential risks associated with the consumption of these supplements.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 it