Wine Lees as Source of Antioxidant Molecules: Green Extraction Procedure and Biological Activity

An ultrasound-assisted extraction method, employing ethanol and water as solvents at low temperature (30 °C) and reduced time (15 min), was proposed to extract bioactive molecules from different cultivars (Magliocco Canino, Magliocco Rosato, Gaglioppo, and Nocera Rosso) of wine lees. All the extract yields were evaluated and their contents of phenolic acids, flavonoids, and total polyphenols were determined by means of colorimetric assays and high-performance liquid chromatography coupled with diode-array detection (HPLC-DAD) and Fourier transform infrared (FTIR) techniques. Radical scavenging assays were performed and the Magliocco Canino extracted with a hydroalcoholic mixture returned the best results both against ABTS (0.451 mg mL−1) and DPPH (0.395 mg mL−1) radicals. The chemometric algorithms principal component analysis (PCA) and partial least square regression (PLS) were used to process the data obtained from all qualitative–quantitative sample determinations with the aim of highlighting data patterns and finding possible correlations between composition and antioxidant features of the different wine lees cultivars and the extraction procedures. Wine lees from Magliocco Canino and Magliocco Rosato were found to be the best vegetable matrices in terms of metabolite content and antioxidant properties. The components extracted with alcoholic or hydroalcoholic solvents, specifically (−)-epigallocatechin gallate, chlorogenic acid, and trans-caftaric acid, were found to be correlated with the antioxidant capacity of the extracts. Multivariate data processing was able to identify the compounds related to the antioxidant features. Two PLS models were optimized by using their concentration levels to predict the IC50 values of the extracts in terms of DPPH and ABTS with high values of correlation coefficient R2, 0.932 and 0.824, respectively, and a prediction error lower than 0.07. Finally, cellular (SH-SY5Y cells) antioxidant assays were performed on the best extract (the hydroalcoholic extract of Magliocco Canino cv) to confirm its biological performance against radical species. All these recorded data strongly outline the aptness of valorizing wine lees as a valuable source of antioxidants

Physical basis of self-assembly. Part 2. A theoretical and experimental study of the self-assembly of a zinc meso-pyridyl porphyrin

A previously reported theoretical treatment for self-assembly macrocyclisations occurring under thermodynamic control has been tested experimentally. The fundamental quantities on which the treatment is based are the effective molarity (EM) of the self-assembling cyclic n-mer and the equilibrium constant for the intermolecular model reaction between monofunctional reactants (Kinter). Provided that estimates of EM and Kinter are available, this treatment can be used to predict not only whether the self-assembly process is more or less favoured, but also the distribution of all the species present in solution. Since Kinter values are approximately known from the literature, we have proposed a method, based on molecular modelling techniques, to estimate the EM. The method has been applied to the self-assembly of Zn(PyP3P), where PyP3P is 5-(4-pyridyl)-10,15,20-triphenylporphyrinato dianion. An EM greater than 0.1 mol L-1 has been estimated for its cyclotetramerisation by PM3 calculations, suggesting that self-assembly should be favoured in solvents like toluene and chloroform. Self-assembly of Zn(PyP3P) has been studied in these solvents by UV/visible spectroscopy. The data are consistent with the formation of the cyclotetramer, and at variance with the model of linear polymerisation. The experimental values of the EM were little affected by the nature of the solvent (EM values were 20 mol L-1 in toluene and 15 mol L-1 in chloroform), indicating that the solvent affects the process of self-assembly mainly through the value of Kinter

Physical basis of self-assembly. Part 2. A theoretical and experimental study of the self-assembly of a zinc meso-pyridyl porphyrin

A previously reported theoretical treatment for self-assembly macrocyclisations occurring under thermodynamic control has been tested experimentally. The fundamental quantities on which the treatment is based are the effective molarity (EM) of the self-assembling cyclic n-mer and the equilibrium constant for the intermolecular model reaction between monofunctional reactants (K-inter). Provided that estimates of EM and K-inter are available, this treatment can be used to predict not only whether the self-assembly process is more or less favoured, but also the distribution of all the species present in solution. Since K-inter values are approximately known from the literature, we have proposed a method, based on molecular modelling techniques, to estimate the EM. The method has been applied to the self-assembly of Zn(PyP3P), where PyP3P is 5-(4-pyridyl)-10,15,20-triphenylporphyrinato dianion. An EM greater than 0.1 mol L-1 has been estimated for its cyclotetramerisation by PM3 calculations, suggesting that self-assembly should be favoured in solvents like toluene and chloroform. Self-assembly of Zn(PyP3P) has been studied in these solvents by UV/visible spectroscopy. The data are consistent with the formation of the cyclotetramer, and at variance with the model of linear polymerisation. The experimental values of the EM were little affected by the nature of the solvent (EM values were 20 mol L-1 in toluene and 15 mol L-1 in chloroform), indicating that the solvent affects the process of self-assembly mainly through the value of K-inter

OXIDATION OF TERMINAL OLEFINS BY HYDROGEN-PEROXIDE CATALYZED BY TETRAKIS(TRIPHENYLPHOSPHINE)PALLADIUM(O)

Terminal olefins can be oxidised under mild conditions in excellent yields and selectivities to methyl ketones by employing an aqueous medium containing hydrogen peroxide as the oxidant and tetrakis(triphenylphosphine)palladium(0) as the catalyst

Analyse de clusters et classification chimiométrique des eaux au sud de Paris

Le but de ce travail consiste à proposer des modèles de classification multivariés pour le contrôle analytique d’un nombre élevé de sources d’eau situé au sud-est de Paris. Ces modèles sont susceptibles d’effectuer une évaluation globale des échantillons par compulsion simultanée d’un grand nombre de paramètres analytiques et ils représentent ensuite un outil valide pour une télésurveillance continue des eaux. Pour la construction des modèles, deux méthodes chimiométriques très avancées ont été utilisées : Analyse de Clusters et Classification, par recours à des logiciels de dernière génération. L’ensemble des objets est composé de 69 points de prélèvement, chacun décrit par 9 paramètres analytiques sélectionnés, concernant des analyses effectuées durant l’année 2004. Dans une première phase on a effectué la distribution des sources en cluster en appliquant à la matrice de données, l’algorithme de type agglomérative hiérarchique Average Linkage, en utilisant comme discriminant le calcul de la Distance Euclidienne entre les objets. Pour l’examen de la similarité, 4 clusters ont été définis, chacun composé par un nombre variable de sources. En ce qui concerne la matrice de données dans laquelle les clusters représentent la variable dépendante, on a appliqué l’algorithme de régression PLS1 (Partial Least Squares) pour la construction d’un modèle multivarié. Le modèle obtenu a donc été soumis aux « procès » d’optimisation et de validation. Le modèle final a été ainsi appliqué à une nouvelle matrice de données, concernant les analyses effectuées en 2005 sur des échantillons analogues, pour apprécier les variations éventuelles dans la Classification des sources considérées. Il a été possible de souligner que la plus grande partie des points de prélèvement, dans le laps de temps d’une année, s’est placée à l’intérieur des clusters d’origine, à l’exception de 8 sources qui ont été classées dans un autre Cluster à la suite de variations statistiquement significatives de quelques paramètres analytiques