Coconut water (Cocos Nucifera) is shown to be a source of essential elements present in the form of low-molecular weight stable complexes known for their bio-availability. The total element concentrations were in the range of 0.2-2.7, 0.3-1, 3-14 and 0.5-2 ppm for Fe, Cu, Mn, and Zn, respectively, and varied as a function of the origin of the nut and its maturity. Speciation was investigated by size-exclusion chromatography - inductively coupled plasma mass spectrometry (ICPMS), and hydrophilic interaction liquid chromatography (HILIC) - electrospray-OrbitrapMS. The metal species identified included iron complexes with citrate and malate FeIII(Cit)3(Mal), FeIII(Cit)2(Mal)2, FeIII(Mal)2, glutamine FeIII(Glu)2 and nicotianamine FeII(NA); copper complexes with phenylanine CuII(Phe)2 and CuII(Phe)3 and nicotianamine CuII(NA); zinc complexes with citrate ZnII(Cit)2 and nicotianamine ZnII(NA) and manganese complex with asparagine MnII(Asp)2. The contributions of the individual species to the total elements concentrations could be estimated by HILIC - ICP MS.In this study, pectinase-assisted extraction of cashew apple juice was modeled and optimized using a multi-layer artificial neural network (ANN) coupled with genetic algorithm (GA). The effect of incubation time, incubation temperature, and enzyme concentration on different responses such as yield, turbidity, ascorbic acid content, polyphenol content, total soluble solids, and pH was also determined. The developed ANN has minimum mean squared error values of 0.83, 40.92, 29.01, and 8.95 and maximum R values of 0.9999, 0.9972, 0.9995, and 0.9996 for training, testing, validation, and all data sets, respectively, which shows good agreement between the actual and predicted values. The optimum extraction parameters obtained using the developed ANN-GA were as follows an incubation time of 64 min, incubation temperature of 32 °C, and enzyme concentration of 0.078%. The measured value of responses at the optimized process conditions were in accordance with the predicted values obtained using the developed ANN model.Monoterpenes are non-polar secondary metabolites widely used by industry due to their excellent therapeutic, food-ingredient and cosmetic properties.  https://www.selleckchem.com/products/VX-770.html  However, their low solubility in water limits their use. In this sense, cyclodextrins (CDs) have been widely used to solve these technological challenges. Thus, this study aims to use (-)-borneol as a monoterpene model to prepare inclusion complexes between β-CD and hydroxypropyl-β-CD (HP-β-CD) through different ways and characterize them in order to choose the best inclusion method to improve physicochemical properties of monoterpenes. To achieve this goal, the samples were prepared by physical mixture (PM), paste complex (PA) and freeze-drying complex (FD) and then, extensively characterized by thermal analysis, Fourier-transform infrared spectroscopy, scanning electron microscopy, size particle, X-ray diffraction and nuclear magnetic resonance. The physicochemical results showed that freeze-drying was more effective to form inclusion complexes between (-)-borneol with both CDs. This research highlights the importance of recognizing the best method to prepare inclusion complexes, including food additives as (-)-borneol, to achieve better results in food preparations.Origin verification of 240 French wines from four regions of France was undertaken using isotope and elemental analyses. Our aim was to identify and differentiate the geographical origin of these red wines, and more importantly, to build a classification tool that can be used to verify geographic origin of French red wines using machine learning models. Multivariate analyses of the isotopic and elemental data revealed that it is possible to determine the geographical origin of French wines with a high level of confidence for most regions analyzed in this study. The wine verification accuracy of four French wine producing regions of Bordeaux, Burgundy, Languedoc-Roussillon and Rhone using an Artificial Neural Network (ANN) method was 98.2%. The results also show that ANN is more suitable than Discriminant Analysis for this verification purpose. The most important variables for French wine regional traceability were Mg, Mn, Na, Sr, Ti and Rb.PcoC is a small soluble protein and is considered as a kind of copper carrier in the periplasm. The PcoC protein from E. coli possesses a β-barrel fold with two metal-binding sites of Cu2+ and Cu+. In this work, different spectroscopic techniques were adopted to clarify the stability of PcoC and metals' binding property. As demonstrated in results, Ag+ and Cu2+ are capable of binding with PcoC in a proportion of 11. The constant for PcoC and Cu2+ was (7.27 ± 0.21) × 1013 L/mol. In addition, we have explored how the cofactors affect the PcoC stability, finding that Cu2+ coordination affects both protein stability and unfolding pathway. The intermediate appeared during PcoC-Cu2+ unfolding. Further, the intermediate could be formed as CTAB interacted with PcoC. As found, the intermediate's C-terminal structure was unfolded, whereas the N-terminal was almost unaffected. Furthermore, the capability of the different unfolding degree protein with Cu2+ also indicated that the N-terminal exhibited a strong stability. Based on the anisotropy decay, tryptophan moved at a higher concentration of urea, also showing that the N-terminal was highly stable. In addition, the steered molecular dynamics simulations were performed, showing the rigidness of the N-terminal.In this study, a new "off-on-off" fluorescence strategy for detecting glutathione (GSH) and silver ions (Ag+) is presented. The constructed nanoprobe is composed of B, N co-doped carbon dots (B, N-CDs) and manganese dioxide nanosheets (MnO2 nanosheets), where MnO2 nanosheets serve as a kind of efficient fluorescence quencher. The sensing mechanism of the system is based on the inner filter effect (IFE) and destruction-protection strategy. The assay strategy includes three processes fluorescence quenching of B, N-CDs by MnO2 nanosheets, the deconstruction of MnO2 nanosheets by GSH, the combination between GSH and Ag+. The MnO2 nanosheets are reduced to Mn2+ because of the addition of GSH and restoring the fluorescence intensity of the system, while the formation of the complex between GSH and Ag+ inhibit the reduction of MnO2 nanosheets on account of the addition of Ag+, leading to the decrease in fluorescence of the probe. This strategy allows the quantitative detection of GSH and Ag+ with detection limit of 0.