Chemical Characterization and Volatile Profile of Trebbiano di Lugana Wine: A Case Study

In this study, the volatile profile of Trebbiano di Lugana wine was determined and its chemical composition was considered to understand its potential longevity. Seven wine samples produced in different years (2005-2017) were collected by the same winery and analyzed up to 13 years after bottling. Color, total and polymeric phenols, glutathione, free volatiles and sensory characteristics were assessed. The color turned from yellow to an increased brownish hue as the aging time increased; nonetheless, it was stable up to five years from the production. Thirty-six aroma compounds were detected including higher alcohols, esters, and norisoprenoids (\u3b2-damascenone and \u3b2-oxo-ionone). While higher alcohols did not show a dependence on the different years of production, a decrease of esters was found over aging with the exception of wine produced in 2009, the latter showing higher levels of glutathione that could limit esters' hydrolysis. The perception of floral and fruity notes was dependent on the storage time with little differences up to five years after bottling. Trebbiano di Lugana wine could be suitable for aging and this aptitude might be further improved also through the proper choice of closure and packaging systems to encourage logistic and marketing strategies

Techniques for Complex Analysis of Contemporary Data

Contemporary data objects are typically complex, semi-structured, or unstructured at all. Besides, objects are also related to form a network. In such a situation, data analysis requires not only the traditional attribute-based access but also access based on similarity as well as data mining operations. Though tools for such operations do exist, they usually specialise in operation and are available for specialized data structures supported by specific computer system environments. In contrary, advance analyses are obtained by application of several elementary access operations which in turn requires expert knowledge in multiple areas. In this paper, we propose a unification platform for various data analytical operators specified as a general-purpose analytical system ADAMiSS. An extensible data-mining and similarity-based set of operators over a common versatile data structure allow the recursive application of heterogeneous operations, thus allowing the definition of complex analytical processes, necessary to solve the contemporary analytical tasks. As a proof-of-concept, we present results that were obtained by our prototype implementation on two real-world data collections: the Twitter Higg's boson and the Kosarak datasets

A mathematical model for the optimization of the non-metallic mining supply chain in the mining district of Calamarí-Sucre (Colombia)

This article presents a mathematical model of the Supply chain of non-metallic mining. The model considers uncertainty scenarios in materials, elements for capacity planning in a multilevel chain and with multiple products. The mathematical model is collaborative and maximizes the profits of the actors in the supply chain. The model is implemented in Calamarí-Sucre mining district (Colombia). The scenario is applied to the extraction, processing, storage, and distribution of limestone. To solve the model, the GAMS software was used through libraries of relaxed mixed nonlinear programming - RMINLP and the DICOPT solver. The results indicate that the greatest benefits occur in a scenario of the high provision of raw materials. The equity in the economic benefits show a dynamics of vertical integration in the sector. The model applied to non-metallic mining complexes helps determine optimal strategies and decisions in different echelons

Model of optimization of mining complex for the planning of flow of quarry production of limestone in multiple products and with elements for the analysis of the capacity

Activities in mining complexes contain multiple decisions that affect the operations of the system for the extraction, transformation, transport and storage of various subsoil components. The purpose of this research is the planning of continuous flow production systems for mixed products, in non-metallic mining extraction processes, considering bottlenecks and capacity planning. This paper presents a model for production, based on mathematical optimization, that facilitates the planning and management of operations in the area of extraction, crushing and transformation of a quarry of aggregates for construction, considering the resources and the constraints that allow to define effective strategies in the increase of the productivity of the lines of low production environment by scenarios. This research develops an analysis of bottlenecks and contrasts the nature of the production system by means of a mathematical model of optimization, which considers the capacities and balances in the flows of the Limestone production line. The mathematical model that maximizes profits can be adapted to systems of continuous flow production in mining complexes where their products are part of a reverse logistics process, analysis of alternatives of extraction, transformation and transport

Tumor Susceptibility Gene 101 (TSG101) Is a Novel Binding-Partner for the Class II Rab11-FIPs

The Rab11-FIPs (Rab11-family interacting proteins; henceforth, FIPs) are a family of Rab11a/Rab11b/Rab25 GTPase effector proteins implicated in an assortment of intracellular trafficking processes. Through proteomic screening, we have identified TSG101 (tumor susceptibility gene 101), a component of the ESCRT-I (endosomal sorting complex required for transport) complex, as a novel FIP4-binding protein, which we find can also bind FIP3. We show that α-helical coiled-coil regions of both TSG101 and FIP4 mediate the interaction with the cognate protein, and that point mutations in the coiled-coil regions of both TSG101 and FIP4 abrogate the interaction. We find that expression of TSG101 and FIP4 mutants cause cytokinesis defects, but that the TSG101-FIP4 interaction is not required for localisation of TSG101 to the midbody/Flemming body during abscission. Together, these data suggest functional overlap between Rab11-controlled processes and components of the ESCRT pathway

Identification of Combinatorial Patterns of Post-Translational Modifications on Individual Histones in the Mouse Brain

Post-translational modifications (PTMs) of proteins are biochemical processes required for cellular functions and signalling that occur in every sub-cellular compartment. Multiple protein PTMs exist, and are established by specific enzymes that can act in basal conditions and upon cellular activity. In the nucleus, histone proteins are subjected to numerous PTMs that together form a histone code that contributes to regulate transcriptional activity and gene expression. Despite their importance however, histone PTMs have remained poorly characterised in most tissues, in particular the brain where they are thought to be required for complex functions such as learning and memory formation. Here, we report the comprehensive identification of histone PTMs, of their combinatorial patterns, and of the rules that govern these patterns in the adult mouse brain. Based on liquid chromatography, electron transfer, and collision-induced dissociation mass spectrometry, we generated a dataset containing a total of 10,646 peptides from H1, H2A, H2B, H3, H4, and variants in the adult brain. 1475 of these peptides carried one or more PTMs, including 141 unique sites and a total of 58 novel sites not described before. We observed that these PTMs are not only classical modifications such as serine/threonine (Ser/Thr) phosphorylation, lysine (Lys) acetylation, and Lys/arginine (Arg) methylation, but also include several atypical modifications such as Ser/Thr acetylation, and Lys butyrylation, crotonylation, and propionylation. Using synthetic peptides, we validated the presence of these atypical novel PTMs in the mouse brain. The application of data-mining algorithms further revealed that histone PTMs occur in specific combinations with different ratios. Overall, the present data newly identify a specific histone code in the mouse brain and reveal its level of complexity, suggesting its potential relevance for higher-order brain functions

Metabotropic action of postsynaptic kainate receptors triggers hippocampal long-term potentiation

Long-term potentiation (LTP) in the rat hippocampus is the most extensively studied cellular model for learning and memory. Induction of classical LTP involves an NMDA receptor- and calcium-dependent increase in functional synaptic AMPA receptors mediated by enhanced recycling of internalized AMPA receptors back to the postsynaptic membrane. Here we report a novel, physiologically relevant NMDA receptor-independent mechanism that drives increased AMPA receptor recycling and LTP. This pathway requires the metabotropic action of kainate receptors and activation of G-protein, protein kinase C and phospholipase C. Like classical LTP, kainate receptor-dependent LTP recruits recycling endosomes to spines, enhances synaptic recycling of AMPA receptors to increase their surface expression and elicits structural changes in spines, including increased growth and maturation. These data reveal a new and previously unsuspected role for postsynaptic kainate receptors in the induction of functional and structural plasticity in the hippocampus