Changes in the contents of micro- and trace-elements in wine due to winemaking treatments

Forty-four mineral elements quantified by ICP-OES and ICP-MS were measured in wines, (a) after wine fining, at three pH levels with 10 different bentonites (1 g·l-1), (b) after addition of yeast hulls from 2 suppliers to wine (180 and 360 mg·1-1). Bentonite fining resulted in statistically significant increases of the large majority of elements, but in significant lower levels of Cu, K, Rb and Zn. The addition of yeast hulls caused a statistically significant depletion of the contents of Ce, Cu, Fe, La, Sb, U, V and Y.

Molecular docking simulations on histone deacetylases (Hdac)-1 and-2 to investigate the flavone binding

Histone modifications through acetylation are fundamental for remodelling chromatin and consequently activating gene expression. The imbalance between acetylation and deacetylation activity causes transcriptional dysregulation associated with several disorders. Flavones, small molecules of plant origin, are known to interfere with class I histone deacetylase (HDAC) enzymes and to enhance acetylation, restoring cell homeostasis. To investigate the possible physical interactions of flavones on human HDAC1 and 2, we carried out in silico molecular docking simulations. Our data have revealed how flavone, and other two flavones previously investigated, i.e., apigenin and luteolin, can interact as ligands with HDAC1 and 2 at the active site binding pocket. Regulation of HDAC activity by dietary flavones could have important implications in developing epigenetic therapy to regulate the cell gene expression

Online Learning From Input Versus Offline Memory Evolution in Adult Word Learning: Effects of Neighborhood Density and Phonologically Related Practice

This is the author's accepted manuscript. The original publication is available at http://jslhr.pubs.asha.org/article.aspx?articleid=1851189Purpose. This study investigates adult word learning to determine how neighborhood density and practice across phonologically-related training sets influence on-line learning from input during training versus off-line memory evolution during no-training gaps. Method. Sixty-one adults were randomly assigned to learn low or high density nonwords. Within each density condition, participants were trained on one set of words and then were trained on a second set of words, consisting of phonological neighbors of the first set. Learning was measured in a picture-naming test. Data were analyzed using multilevel modeling and spline regression. Results. Steep learning during input was observed, with new words from dense neighborhoods and new words that were neighbors of recently learned words (i.e., second set words) being learned better than other words. In terms of memory evolution, large and significant forgetting was observed during 1-week gaps in training. Effects of density and practice during memory evolution were opposite of those during input. Specifically, forgetting was greater for high density and second set words than for low density and first set words. Conclusion. High phonological similarity, regardless of source (i.e., known words or recent training), appears to facilitate on-line learning from input but seems to impede off-line memory evolution

NMR profiling of grape musts from some Italian regions

With wine fraud, being a widespread problem [1], the need for more sophisticated and precise analytical methods of its detection remains ever persistent. Nuclear magnetic resonance (NMR) spectroscopy has been widely used for analysis of wine in recent years [2,3], but wine musts were much less studied; in fact, only one paper dealt with the NMR spectra of actual musts [4]. Difficulties arise mostly because grape musts are “live” objects, which undergo rapid fermentation at room temperature, if not inhibited either by freezing or chemical preservative; but even such measures are not sufficient to halt it completely [5]. We have investigated over 300 samples of grape must from 17 of 20 different Italian regions using 1H NMR spectroscopy with water signal suppression, postprocessing in the MatLab software with dynamic alignment [6] and optimized binning [7] to alleviate the effect of fermentation on the chemical shifts of mobile protons. After that, multivariate statistics was performed with techniques such as PCA, PLS-DA and OPLS-DA with respect to various group parameters such as regions, vitivinicultural zones, harvest periods and grape varieties. Advantages and drawbacks of each method were addresse

Determination of regulated and emerging mycotoxins in organic and conventional gluten-free flours by LC-MS/MS

Gluten-free cereal products have grown in popularity in recent years as they are perceived as “healthier” alternatives and can be safely consumed by celiac patients, and people with gluten intolerance or wheat allergies. Molds that produce mycotoxins contaminate cereal crops, posing a threat to global food security. Maximum levels have been set for certain mycotoxins in cereal flours; however, little is known about the levels of emerging mycotoxins in these flours. The aim of this study was to develop an efficient, sensitive, and selective method for the detection of four emerging (beauvericin and enniatins A1, B, and B1) and three regulated (aflatoxin B1, zearalenone, and deoxynivalenol) mycotoxins in gluten-free flours. Ultrasound-assisted matrix solid-phase dispersion was used in the extraction of these mycotoxins from flour samples. The validated method was utilized for the LC-MS/MS analysis of conventional and organic wholegrain oat and rice flours. Six of the seven target mycotoxins were detected in these samples. Multi-mycotoxin contamination was found in all flour types, particularly in conventional wholegrain oat flour. Despite the low detection frequency in rice flour, one sample was found to contain zearalenone at a concentration of 83.2 µg/kg, which was higher than the level set by the European Commission for cereal flours. The emerging mycotoxins had the highest detection frequencies; enniatin B was present in 53% of the samples at a maximum concentration of 56 µg/kg, followed by enniatin B1 and beauvericin, which were detected in 46% of the samples, and at levels reaching 21 µg/kg and 10 µg/kg, respectively. These results highlight the need to improve the current knowledge and regulations on the presence of mycotoxins, particularly emerging ones, in gluten-free flours and cereal-based product

Aromatic characterization of Moscato Giallo by GC-MS/MS and stable isotopic ratio analysis of the major volatile compounds

Among the Moscato grapes, Moscato Giallo is a winegrape variety characterized by a highcontent of free and glycosylated monoterpenoids, which gives very aromatic wines. Thearomatic bouquet of Moscato Giallo is strongly influenced by the high concentration of linalool, geraniol, linalool oxides, limonene, α-terpineol, citronellol, HO-trienol, HO-diols, 8-Hydroxylinalool, geranic acid and β-myrcene, that give citrus, rose, and peach notes. Except the quali-quantitative analysis, no investigations regarding the isotopic values of the target volatile compounds are documented in literature. Stable isotope ratio analysis represents a modern and powerful tool used by the laboratories responsible for official consumer protection, for the food quality and genuineness assessment. In this study, samples of Moscato Giallo were collected during the harvest season in 2019 from two Italian regions:Trentino – Alto Adige and Veneto, known lands for the cultivation of this aromatic variety. The flavor compounds were extracted from grapes and wines, after alcoholic fermentation of grape juice, and analysed by GC-MS/MS. The results confirmed the presence of typical terpenoids both in free and glycosylated form, responsible for the characteristic aroma of Moscato Giallo variety. The aromatic compounds were also analysed by GC-C\Py-IRMS for a preliminary investigation. The compound-specific isotope ratio analysis allowed to determine the carbon (δ13C) and hydrogen (δ2H) isotopic signatures of the major volatile compounds for the first time

The effect of incremental changes in phonotactic probability and neighborhood density on word learning by preschool children

This is the author's accepted manuscript. The original publication is available at http://jslhr.pubs.asha.org/article.aspx?articleid=1797302Purpose. Phonotactic probability or neighborhood density have predominately been defined using gross distinctions (i.e., low vs. high). The current studies examined the influence of finer changes in probability (Experiment 1) and density (Experiment 2) on word learning. Method. The full range of probability or density was examined by sampling five nonwords from each of four quartiles. Three- and 5-year-old children received training on nonword-nonobject pairs. Learning was measured in a picture-naming task immediately following training and 1-week after training. Results were analyzed using multi-level modeling. Results. A linear spline model best captured nonlinearities in phonotactic probability. Specifically word learning improved as probability increased in the lowest quartile, worsened as probability increased in the midlow quartile, and then remained stable and poor in the two highest quartiles. An ordinary linear model sufficiently described neighborhood density. Here, word learning improved as density increased across all quartiles. Conclusion. Given these different patterns, phonotactic probability and neighborhood density appear to influence different word learning processes. Specifically, phonotactic probability may affect recognition that a sound sequence is an acceptable word in the language and is a novel word for the child, whereas neighborhood density may influence creation of a new representation in long-term memory