Structure-Activity Relationship (SAR) of Phenolics for the Inhibition of 2-Phenylethylamine Formation in Model Systems Involving Phenylalanine and the 13-Hydroperoxide of Linoleic Acid

Conceptual functional-by-design optimisation of the antioxidant capacity of trans-resveratrol, quercetin, and chlorogenic acid: Application in a functional tea

Designing functional foods as delivery systemsmay become a tailored strategy to decrease the risk of noncommunicable diseases. Therefore, this work aims to optimise a combination of t-resveratrol (RES), chlorogenic acid (CHA), and quercetin (QUE) based on antioxidant assays and develop a functional tea formulation enriched with the optimal polyphenol combination (OPM). Experimental results showed that the antioxidant capacity of these compounds is assay- and compound-dependent. A mixture containing 73% RES and 27% QUE maximised the hydroxyl radical scavenging activity and FRAP. OPM upregulated the gene expressions of heme oxygenase-1, superoxide dismutase, and catalase and decreased the reactive oxygen species generation in L929 fibroblasts. Adding OPM (100 mg/L)to a chamomile tea increased FRAP:39%, DPPH:59%; total phenolic content: 57%, iron reducing capacity: 41%, human plasma protection against oxidation: 67%. However, pasteurisation (63 °C/30 min) decreased onlythe DPPH. Combining technology, engineering, and cell biology was effective for functional tea design.

Differentiation of NaCl, NaOH, and β-Phenylethylamine Using Ultraviolet Spectroscopy and Improved Adaptive Artificial Bee Colony Combined with BP-ANN Algorithm

The aim of this study is to enhance the classification performance of the back-propagation-artificial neural network (BP-ANN) algorithm for NaCl, NaOH, β-phenylethylamine (PEA), and their mixture, as well as to avoid the defects of the artificial bee colony (ABC) algorithm such as prematurity and local optimization. In this paper, a method that combined an improved adaptive artificial bee colony (IAABC) algorithm and BP-ANN algorithm was proposed. This method improved the ABC algorithm by adding an adaptive local search factor and mutation factor; meanwhile, it can enhance the abilities of the global optimization and local search of the ABC algorithm and avoid prematurity. The extracted score vectors of the principal component of the ultraviolet (UV) spectrum were used as the input variable of the BP-ANN algorithm. The IAABC algorithm was used to optimize the weight and threshold of the BP-ANN algorithm, and the iterative algorithm was repeated until the output accuracy was reached. The output variable was the classification results of NaCl, NaOH, PEA, and the mixture. Meanwhile, the proposed IAABC-BP-ANN algorithm was compared with discriminant analysis (DA), sigmaid-support vector machine (SVM), radial basis function-SVM (RBF-SVM), BP-ANN, and ABC-BP-ANN. Then, the above algorithms were used to classify NaCl, NaOH, PEA, and the mixture, respectively. In the experiment, four indicators, accuracy, recall, precision, and F-score, were used as the evaluation criteria. In addition, the regression equation parameters of the mixture for the testing set were obtained by BP-ANN, ABC-BP-ANN, and IAABC-BP-ANN models. All of the results showed that IAABC-BP-ANN exhibits better performance than other algorithms. Therefore, IAABC-BP-ANN combined with UV spectroscopy is a potential identification tool for the detection of NaCl, NaOH, PEA, and the mixture.

Formation of heterocyclic aromatic amines with the structure of aminoimidazoazarenes in food products

Thermal food processing has many beneficial consequences, although it also produces some unintentional undesired effects, such as the formation of potentially mutagenic and carcinogenic substances. Among them, the formation of heterocyclic aromatic amines (HAAs) has been related to the declared carcinogenicity of processed meats. In spite of this importance, HAA formation pathways remain mostly unknown, which avoids the design of targeted procedures to inhibit HAA appearance. The objective of this review is to collect information recently appeared that allow advancing in the understanding of how these compounds are produced. Particularly, the possibility that aminoimidazoazarenes are produced similarly to PhIP is discussed, including their formation by cyclizations and oligomerizations of aldehydes and creatinine under usual cooking conditions. Present data suggest that HAA formation might be related to the pool of carbonyl compounds existing in foods, the food carbonylome, which can be controlled by carbonyl-trapping agents, such as amine and phenolic compounds.

Characterization of Carbonyl-Phenol Adducts Produced by Food Phenolic Trapping of 4-Hydroxy-2-hexenal and 4-Hydroxy-2-nonenal

4-Hydroxy-2-alkenals disappear in the presence of food phenolics (i.e., cathechin or quercetin), and the corresponding carbonyl-phenol adducts are produced. In an attempt to identify structure(s) of formed adducts, the reactions between model phenolics (resorcinol, 2-methylresorcinol, orcinol, and 2,5-dimethylresorcinol) and hydroxyalkenals (4-hydroxy-2-hexenal and 4-hydroxy-2-nonenal) were studied and the produced adducts were isolated by column chromatography and unambiguously characterized by one- and two-dimensional nuclear magnetic resonance and mass spectrometry as dihydrobenzofuranols (1), chromane-2,7-diols (2), and 2 H-chromen-7-ols (3). These compounds were mainly produced at slightly basic pH values and moderate temperatures. Their activation energies ( E_a) of formation were ∼25 kJ mol^-1 for adducts 1, ∼32 kJ mol^-1 for adducts 2, and ∼38 kJ mol^-1 for adducts 3. A reaction pathway that explains their formation is proposed. All of these results confirm that, analogously to other lipid-derived carbonyl compounds, phenolics can trap 4-hydroxy-2-alkenals in an efficient way. Obtained results provide the basis for the potential detection of carbonyl-phenol adducts derived from hydroxyalkenals in food products.