Volatile Composition of Vernaccia di Oristano Sherry-Like Wine as Affected by Biological Ageing

Forty compounds were identified by gas chromatography and gas chromatography/mass spectrometry in the volatile fraction of Vernaccia di Oristano, an Italian sherry-like wine produced in Sardinia since the 11th century. The individual aromatic compounds were identified and quantified in the original wine, both after biological ageing by inoculation of the original wine with Saccharomyces cerevisiae var bayanus and S cerevisiae var prostoserdovii , and after ageing under sterile conditions. The effects of flor yeasts in terms of production or subtraction of flavour components are discussed.     

Pharmacological Activities of Ruthenium Complexes Related to Their NO Scavenging Properties

Angiogenesis is considered responsible for the growth of primary tumours and of their metastases. With the present study, the effects of three ruthenium compounds, potassiumchlorido (ethylendiamminotetraacetate)rutenate(III) (RuEDTA), sodium (bis-indazole)tetrachloro-ruthenate(III), Na[trans-RuCl₄Ind₂] (KP1339) and trans-imidazoledimethylsulphoxidetetrachloro-ruthenate (NAMI-A), are studied in vitro in models mimicking the angiogenic process. The ruthenium compounds reduced the production and the release of nitrosyls from either healthy macrophages and immortalized EA.hy926 endothelial cells. The effects of NAMI-A are qualitatively similar and sometimes quantitatively superior to those of RuEDTA and KP1339. NAMI-A reduces the production and release of nitric oxide (NO) by the EA.hy926 endothelial cells and correspondingly inhibits their invasive ability; it also strongly inhibits the angiogenesis in matrigel sponges implanted subcutaneously in healthy mice. Taken together, these data support the anti-angiogenic activity of the tested ruthenium compounds and they contribute to explain the selective activity of NAMI-A against solid tumour metastases, the tumour compartment on which angiogenesis is strongly involved. This anti-angiogenic effect may also contribute to the inhibition of the release of metastatic cells from the primary tumour. Investigations on the anti-angiogenic effects of NAMI-A at this level will increase knowledge of its pharmacological properties and it will give a further impulse to the development of this class of innovative metal-based drugs.     

Controlled and automatic processing during animal word list generation in schizophrenia.

Controlled and automatic aspects of semantic-associative functioning in schizophrenia were investigated by evaluating performance on animal word list generation (WLG). Responses from control (n?=?47) and patient (n?=?38) participants were subjected to multidimensional scaling (MDS), cluster analysis (CA), and indices on the basis of number of shared attributes (SA) between consecutive responses. Patient MDS results accounted for less variance and contained more error than control data. CA results yielded fewer and less clear animal-response subgroups among patients yet demonstrated intact associations among strongly related exemplars. The SA indices revealed better clustering and more effective switching among response clusters in controls than patients. Results suggest that animal WLG in schizophrenia is compromised both by aberrant automatic semantic-associative network activation and by controlled processes such as search, access, and selection. This pattern is consistent with prominent frontotemporal pathology evident in the disorder. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Precision Medicine: Determination of Ribavirin Urinary Metabolites in Relation to Drug Adverse Effects in HCV Patients

The most commonly used antiviral treatment against hepatitis C virus is a combination of direct-acting antivirals (DAAs) and ribavirin (RBV), which leads to a shortened duration of therapy and a sustained virologic response until 98%. Nonetheless, several dose-related side effects of RBV could limit its applications. This study aims to measure the urinary concentration of RBV and its main metabolites in order to evaluate the drug metabolism ability of HCV patients and to evaluate the adverse effects, such as anemia, with respect to RBV metabolite levels. RBV and its proactive and inactive metabolites were identified and quantified in the urine of 17 HCV males with severe liver fibrosis using proton nuclear magnetic resonance (¹H-NMR) at the fourth week (TW4) and at the twelfth week of treatment (EOT). Four prodrug urinary metabolites, including RBV, were identified and three of them were quantified. At both the TW4 and EOT stages, six HCV patients were found to maintain high concentrations of RBV, while another six patients maintained a high level of RBV proactive metabolites, likely due to nucleosidase activity. Furthermore, a negative correlation between the reduction in hemoglobin (Hb) and proactive forms was observed, according to RBV-triphosphate accumulation causing the hemolysis. These findings represent a proof of concept regarding tailoring the drug dose in relation to the specific metabolic ability of the individual, as expected by the precision medicine approach.     

MIMOSE: multimodal interaction for music orchestration sheet editors

Multimedia Tools and Applications - The increasing number and accuracy of sensors devoted to human- computer input are supporting the emergence of novel multimodal interaction paradigms. These, in...     

Characterisation of white vinegars of different sources with artificial neural networks

Wine and cider vinegars currently attract growing interest from consumers, giving rise to a consequent increase in supply. A full appreciation of their quality is only possible, however, through recognition of their superior quality when compared with vinegars produced from raw materials of inferior quality. Therefore, it is necessary to pinpoint the parameters that define the quality of these products. Chemico-physical and sensory analysis has been used to draw up artificial neural networks (ANNs), on the basis of a vast sampling of vinegars from various countries, produced from a variety of raw materials, that was already subjected to multivariate statistical analysis. Among the chemical parameters, polyalcohols and other elements such as pH, tartaric acid and proline proved to be highly reliable, whereas other volatile substances and the results of sensory analysis were not very discriminating and could not be used to re-classify samples of unknown origin. The positive results obtained indicate that ANNs are a powerful mathematical tool, since they can be used to construct models that predict the botanical origin of the product and to re-classify samples of unknown origin, without any initial restrictive hypothesis. © 1998 Society of Chemical Industry.     

CABALA—Collaborative architectures based on biometric adaptable layers and activities

The lack of communication and of dynamic adaptation to working settings often hinder stable performances of subsystems of present multibiometric architectures. The calibration phase often uses a specific training set, so that (sub)systems are tuned with respect to well determined conditions. In this work we investigate the modular construction of systems according to CABALA (Collaborative Architectures based on Biometric Adaptable Layers and Activities) approach. Different levels of flexibility and collaboration are supported. The computation of system reliability (SRR), for each single response of each single subsystem, allows to address temporary decrease of accuracy due to adverse conditions (light, dirty sensors, etc.), by possibly refusing a poorly reliable response or by asking for a new recognition operation. Subsystems can collaborate at a twofold level, both in returning a jointly determined answer, and in co-evolving to tune to changing conditions. At the first level, single-biometric subsystems implement the N-Cross Testing Protocol: they work in parallel, but exchange information to reach the final response. At an higher level of interdependency, parameters of each subsystem can be dynamically optimized according to the behavior of their companions. To this aim, an additional Supervisor Module analyzes the single results and, in our present implementation, modifies the degree of reliability required from each subsystem to accept its future responses. The paper explores different combinations of these novel strategies. We demonstrate that as component collaboration increases, the same happens to both the overall system accuracy and to the ability to identify unstable subsystems.