Assessment of Human Mycotoxin Exposure in Hungary by Urinary Biomarker Determination and the Uncertainties of the Exposure Calculation: A Case Study.
Judit Szabó-FodorMária Szeitzné-SzabóBrigitta BótaTamás SchieszlCserne AngeliLucia GambacortaMichele SolfrizzoAndrás SzabóMelinda KovácsPublished in: Foods (Basel, Switzerland) (2021)
Urinary biomarkers of mycotoxin exposure were evaluated in the case of healthy people ( n = 41) and coeliac patients ( n = 19) by using a multi-biomarker LC-MS/MS immunoaffinity based method capable to analyse biomarkers of nine mycotoxins, i.e., fumonisin B1 (FB1), fumonisin B2 (FB2), deoxynivalenol (DON), zearalenone (ZEN), ochratoxin A (OTA), Aflatoxin B1 (AFB1), T-2 toxin, HT-2 toxin and Nivalenol (NIV). Urinary biomarker concentrations were used to calculate the probable daily intake (PDI) of fumonisin B1, deoxynivalenol, zearalenone and ochratoxin A and compared with their tolerable daily intake (TDI). The human urinary excretion rate values reported in the literature and the 24 h excretion rate measured in piglets were used to estimate and compare the PDI values of the four mycotoxins. The highest mean biomarker concentrations were found for DON (2.30 ng/mL for healthy people and 2.68 ng/mL for coeliac patients). Mean OTA concentration was significantly higher (p < 0.001) in healthy people compared to coeliac patients. PDI calculated with piglets excretion data exceeded the TDI values by a much smaller percentage than when they were calculated from human data, especially for FB 1 . The uncertainties arising from the different calculations can be well perceived on the basis of these data.
Keyphrases
- end stage renal disease
- ejection fraction
- endothelial cells
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- prognostic factors
- escherichia coli
- systematic review
- physical activity
- depressive symptoms
- mental health
- induced pluripotent stem cells
- machine learning
- big data
- body mass index
- social support
- weight gain
- molecular dynamics
- density functional theory
- deep learning
- simultaneous determination
- data analysis