Algerian Workers' Exposure to Mycotoxins-A Biomonitoring Study.
Marta I MendesSara Cristina CunhaIméne RebaiJosé Oliveira FernandesPublished in: International journal of environmental research and public health (2023)
Mycotoxins, produced by fungi as secondary metabolites, have the potential to induce both short-term and long-term toxic consequences in animals and humans. The present study aimed to determine multi-mycotoxin levels in Algerian workers using urine as the target. A method based on a QuEChERS (quick, easy, cheap, effective, rugged, and safe) extraction procedure followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) was optimized and validated for the determination of eleven mycotoxins in 96 urine samples. Different sorbents were tested to be used in the dispersive solid-phase extraction (d-SPE) cleanup step of QuEChERS. The final method was fit-for-purpose and showed good analytical performance in terms of specificity, linearity, and precision. All samples contained at least two mycotoxins, and toxin-2 (T-2) was the most common, being found in 92.7% of the samples, followed by zearalenone (ZEN) in 90.6% of positive samples, and ochratoxin A (OTA) in 86.4%. T-2 levels ranged from 0.3 μg/L to 36.3 μg/L, while OTA ranged from 0.3 μg/L to 3.5 μg/L, and ZEN ranged from 7.6 μg/L to 126.8 μg/L. This was the first mycotoxin biomonitoring study carried out in the Algerian population. The findings highlight the need for accurate data for better risk assessment and for the development of better regulation to manage mycotoxin contamination in this country.
Keyphrases
- solid phase extraction
- liquid chromatography tandem mass spectrometry
- simultaneous determination
- high performance liquid chromatography
- molecularly imprinted
- gas chromatography mass spectrometry
- tandem mass spectrometry
- ms ms
- risk assessment
- liquid chromatography
- ultra high performance liquid chromatography
- gas chromatography
- high resolution mass spectrometry
- human health
- minimally invasive
- ionic liquid
- data analysis