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A Study of the Interactions of Heavy Metals in Dairy Matrices Using Fourier Transform Infrared Spectroscopy, Chemometric, and In Silico Analysis.
Benítez-Rojas, Alfredo C; Jaramillo-Flores, María E; Zaca-Moran, Orlando; Quiroga-Montes, Israel; Delgado-Macuil, Raúl J.
Afiliação
  • Benítez-Rojas AC; Centro de Investigación en Biotecnología Aplicada, Instituto Politécnico Nacional, Santa Inés Tecuexcomac 90700, México.
  • Jaramillo-Flores ME; Ingeniería Bioquímica, Escuela Nacional de Ciencias Biológicas (ENCB), Instituto Politécnico Nacional, México City 07738, México.
  • Zaca-Moran O; Centro de Investigación en Biotecnología Aplicada, Instituto Politécnico Nacional, Santa Inés Tecuexcomac 90700, México.
  • Quiroga-Montes I; Universidad Popular Autónoma del Estado de Puebla (UPAEP) A.C., 21 sur #1103, Barrio de Santiago, Puebla 72410, México.
  • Delgado-Macuil RJ; Centro de Investigación en Biotecnología Aplicada, Instituto Politécnico Nacional, Santa Inés Tecuexcomac 90700, México.
Foods ; 12(9)2023 May 08.
Article em En | MEDLINE | ID: mdl-37174456
ABSTRACT
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 Cd2+, Cr6+, and Pb2+ 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 NH2 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 r2 ≥ 0.95.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Foods Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Foods Ano de publicação: 2023 Tipo de documento: Article