A Study of the Interactions of Heavy Metals in Dairy Matrices Using Fourier Transform Infrared Spectroscopy, Chemometric, and In Silico Analysis.
Alfredo C Benítez-RojasMaría E Jaramillo-FloresOrlando Zaca-MoranIsrael QuirogaRaul Jacobo Delgado-MacuilPublished in: Foods (Basel, Switzerland) (2023)
Heavy metals are among the toxic substances longest recognized by man. Today, due to the myriad sources of exposure, such as contaminated water, food, or air, they have become a major public health problem. This work presents the effects manifested in the infrared spectrum behavior caused by the presence of Cd 2+ , Cr 6+ , and Pb 2+ at different concentrations in three different matrices: water, casein, and milk; observing that the spectral modifications in the regions of different vibrational modes of nucleophilic groups such as -OH, COO- and NH 2 depending on the nature of the metal and its concentration. These findings were correlated in-silico using optimized models in Gabedit software and structural optimization was performed with MOPAC 2016 showing stable structures between the metals and Gln, Hys, Glu, and Phe of casein. By applying chemometrics (Principal Component Analysis), it was possible to observe a good correlation between the experimental data and to discriminate between the type of metal, the matrix that contains it, and the concentration could be represented through linear models that showed adjustments with a value of r 2 ≥ 0.95.
Keyphrases
- heavy metals
- health risk assessment
- health risk
- public health
- risk assessment
- human health
- drinking water
- molecular docking
- sewage sludge
- electronic health record
- data analysis
- molecular dynamics simulations
- big data
- room temperature
- optical coherence tomography
- high resolution
- mass spectrometry
- gas chromatography mass spectrometry
- magnetic resonance imaging
- energy transfer
- magnetic resonance
- global health
- nk cells
- machine learning
- deep learning
- computed tomography
- artificial intelligence
- quantum dots