Bioactive Compounds and Quality of Extra Virgin Olive Oil

 Foods 2020, 9(8), 1014

DOI:10.3390/foods9081014

Background: 

Extra virgin olive oil (EVOO) is responsible for a large part of many health benefits associated to Mediterranean diet as it is a fundamental ingredient of this diet. The peculiarities of this golden, highly valued product are in part due to the requirements that must be met to achieve this title, namely, it has to be obtained using exclusively mechanical procedures, its free acidity cannot be greater than 0.8%, it must not show sensory defects, and it has to possess a fruity taste. 

Methods: 

All these characteristics are key factors to EVOO quality, thus the chemical composition of these many health-promoting compounds, such as unsaturated fatty acids (which are also the major compounds, especially oleic acid), as well as minor components such as tocopherols or phenolic compounds (which behave as natural antioxidants) must be preserved. 

Results: 

Due to the presence of all these compounds, the daily consumption of EVOO entails health benefits such as cardioprotective, antioxidant, anti-inflammatory, anti-tumor properties or acting as regulator of the intestinal microbiota, among others. 

Conclusions: 

Taking all together, conserving EVOO chemical composition is essential to preserve its properties, so it is worth to control certain factors during storage like exposure to light, temperature, oxygen presence or the chosen packaging material, to maintain its quality and extend its shelf-life until its consumption.

Influence of tetraconazole on the proteome profile of Saccharomyces cerevisiae Lalvin T73™ strain

Journal of Proteomics, 2020, 227, 103915 

DOI:10.1016/j.jprot.2020.103915

This work aimed to evaluate the modifications on the proteome profile of Saccharomyces cerevisiae T73™ strain as a consequence of its adaptive response to the presence of tetraconazole molecules in the fermentation medium. Pasteurised grape juices were separately supplemented with tetraconazole or a commercial formulation containing 12.5% w/v of tetraconazole at two concentration levels. In addition, experiments without fungicides were developed for comparative purposes.

Proteome profiles of yeasts cultured in the presence or absence of fungicide molecules were different. Independently of the fungicide treatment applied, the highest variations concerning the control sample were observed for those proteins involved in metabolic processes, especially in the metabolism of nitrogen compounds. Tetraconazole molecules altered the abundance of several enzymes involved in the biosynthesis of amino acids, purines, and ergosterol. Moreover, differences in the abundance of several enzymes of the TCA cycle were found. Changes observed were different between the active substance and the commercial formulation.

Significance

The presence of fungicide residues in grape juice has direct implications on the development of the aromatic profile of the wine. These alterations could be related to changes in the secondary metabolism of yeasts. However, the molecular mechanisms involved in the response of yeasts to fungicide residues remains quite unexplored. Through this exhaustive proteomic study, alterations in the amino acids biosynthesis pathways due to the presence of the tetraconazole molecules were observed. Amino acids are precursors of some important higher alcohols and ethyl acetates (such as methionol, 2-phenylethanol, isoamyl alcohol or 2-phenylacetate). Besides, the effect of tetraconazole on the ergosterol biosynthesis pathway could be related to a higher production of medium-chain fatty acids and their corresponding ethyl acetates.

Potential Health Benefit of Garlic Based on Human Intervention Studies: A Brief Overview

 Antioxidants 2020, 9(7), 619 

DOI: 10.3390/antiox9070619

Garlic is a polyphenolic and organosulfur enriched nutraceutical spice consumed since ancient times. Garlic and its secondary metabolites have shown excellent health-promoting and disease-preventing effects on many human common diseases, such as cancer, cardiovascular and metabolic disorders, blood pressure, and diabetes, through its antioxidant, anti-inflammatory, and lipid-lowering properties, as demonstrated in several in vitro, in vivo, and clinical studies. The present review aims to provide a comprehensive overview on the consumption of garlic, garlic preparation, garlic extract, and garlic extract-derived bioactive constituents on oxidative stress, inflammation, cancer, cardiovascular and metabolic disorders, skin, bone, and other common diseases. Among the 83 human interventional trials considered, the consumption of garlic has been reported to modulate multiple biomarkers of different diseases; in addition, its combination with drugs or other food matrices has been shown to be safe and to prolong their therapeutic effects. The rapid metabolism and poor bioavailability that have limited the therapeutic use of garlic in the last years are also discussed.

Stability assessment of extracts obtained from Arbutus unedo L. fruits in powder and solution systems using machine-learning methodologies

 Food Chem. 2020, 333,127460

Arbutus unedo L. (strawberry tree) has showed considerable content in phenolic compounds, especially flavan-3-ols (catechin, gallocatechin, among others). The interest of flavan-3-ols has increased due their bioactive actions, namely antioxidant and antimicrobial activities, and by association of their consumption to diverse health benefits including the prevention of obesity, cardiovascular diseases or cancer. These compounds, mainly catechin, have been showed potential for use as natural preservative in foodstuffs; however, their degradation is increased by pH and temperature of processing and storage, which can limit their use by food industry. To model the degradation kinetics of these compounds under different conditions of storage, three kinds of machine learning models were developed: i) random forest, ii) support vector machine and iii) artificial neural network. The selected models can be used to track the kinetics of the different compounds and properties under study without the prior knowledge requirement of the reaction system.

Preventive potential and mechanism of dietary polyphenols on the formation of heterocyclic aromatic amines

 Food Frontiers, 2020, 1, 134-151

https://doi.org/10.1002/fft2.30

Thermal processing is the most important and popular domestic cooking method. More than 30 heterocyclic aromatic amines have been identified in cooked meat using various methods. This review highlights preventive potential and mechanism of dietary polyphenols on the formation of heterocyclic amines. Tea, coffee, fruits, vegetable, and spice extracts rich in polyphenols exerted significant inhibition against the formation of heterocyclic aromatic amines. Some polyphenols, such as naringenin and epigallocatechin 3‐O‐gallate, can actively participate into food chemistry reaction to trap Strecker aldehyde and lower the formation of heterocyclic aromatic amines. In addition, some polyphenols can lower the mutagenicity of heterocyclic aromatic amines. More specifically, polyphenols possessing two hydroxyl groups at the meta position of aromatic ring are the most efficient one, but the presence of carboxylic or alkyl groups as substituents in the aromatic ring slightly reduced the inhibitory effect.

Application of Rank Annihilation Factor Analysis for Antibacterial Drugs Determination by Means of pH Gradual Change-UV Spectral Data

 Antibiotics 2020, 9(7), 383

DOI: 10.3390/antibiotics9070383

The main objective of this study was to develop a simple and efficient spectrophotometric technique combined with chemometrics for the simultaneous determination of sulfamethoxazole (SMX) and trimethoprim (TMP) in drug formulations. Specifically, we sought: (i) to evaluate the potential use of rank annihilation factor analysis (RAFA) to pH gradual change spectrophotometric data in order to provide sufficient accuracy and model robustness; and (ii) to determine SMX and TMP concentration in drug formulations without tedious pre-treatments such as derivatization or extraction techniques which are time-consuming and require hazardous solvents. In the proposed method, the spectra of the sample solutions at different pH values were recorded and the pH-spectra bilinear data matrix was generated. On these data, RAFA was then applied to estimate the concentrations of SMX and TMP in synthetic and real samples. Applying RAFA showed that the two drugs could be determined simultaneously with concentration ratios of SMX to TMP varying from 1:30 to 30:1 in the mixed samples (concentration range is 1–30 µg mL−1 for both components). The limits of detection were 0.25 and 0.38 µg mL−1 for SMX and TMP, respectively. The proposed method was successfully applied to the simultaneous determination of SMX and TMP in some synthetic, pharmaceutical formulation and biological fluid samples. In addition, the means of the estimated RSD (%) were 1.71 and 2.18 for SMX and TMP, respectively, in synthetic mixtures. The accuracy of the proposed method was confirmed by spiked recovery test on biological samples with satisfactory results (90.50–109.80%).

Stability assessment of extracts obtained from Arbutus unedo L. fruits in powder and solution systems using machine-learning methodologies

 Food Chemistry, 2020, 33, 127460

DOI:10.1016/j.foodchem.2020.127460

Arbutus unedo L. (strawberry tree) has showed considerable content in phenolic compounds, especially flavan-3-ols (catechin, gallocatechin, among others). The interest of flavan-3-ols has increased due their bioactive actions, namely antioxidant and antimicrobial activities, and by association of their consumption to diverse health benefits including the prevention of obesity, cardiovascular diseases or cancer. These compounds, mainly catechin, have been showed potential for use as natural preservative in foodstuffs; however, their degradation is increased by pH and temperature of processing and storage, which can limit their use by food industry. To model the degradation kinetics of these compounds under different conditions of storage, three kinds of machine learning models were developed: i) random forest, ii) support vector machine and iii) artificial neural network. The selected models can be used to track the kinetics of the different compounds and properties under study without the prior knowledge requirement of the reaction system.