Managing ochratoxin A risk in the grape-wine food chain

The main source of ochratoxin A (OTA) in the wine food chain is the infection of grapes by "black aspergilli" in the field. OTA-producing black aspergilli include principally Aspergillus carbonarius, followed by A. niger and possibly A. tubingensis. They are opportunistic fungi that develop particularly on damaged berries at ripening, although they may occur and form OTA on grapes from veraison to harvest. Climatic conditions (high humidity and temperature) and geographical location are important factors favouring OTA accumulation in grape berries. The severity of aspergillus rot is influenced by excessive irrigation and rainfall prior to harvest, which causes berry splitting. In addition, berry wounds caused by insect attack provide preferential entries for black aspergilli. High OTA levels occur in grapes severely damaged by the grape moth, Lobesia botrana, particularly in Mediterranean areas. Some grape varieties display greater susceptibility to aspergillus rot due to intrinsic genetic characteristics and bunch conformation (i.e. compact>sparse). Control measures for toxigenic mycoflora in the vineyards must consider these critical control points. Proper fungicidal and insecticidal treatments can reduce OTA contamination. Nevertheless, knowledge about the fate of OTA and its distribution in wine and winery by-products is important to manage OTA risk in contaminated stock. In our wine-making experiments, only 4% of the OTA present in grapes remained in the wine--the majority is retained in pressed grape pomaces. OTA concentration remained unchanged in wine after a 1-year aging as well as in all liquid fractions collected during vinification (i.e. must, free run wine, and wine after first and second decantation). Activated carbon can reduce OTA levels in wine but negatively affects wine quality.     

Assessment of interatomic parameters for the reproduction of borosilicate glass structures via DFT-GIPAW calculations

Borates and borosilicates are potential candidates for the design and development of glass formulations with important industrial and technological applications. A major challenge that retards the pace of development of borate/borosilicate based glasses using predictive modeling is the lack of reliable computational models to predict the structure-property relationships in these glasses over a wide compositional space. A major hindrance in this pursuit has been the complexity of boron-oxygen bonding due to which it has been difficult to develop adequate B–O interatomic potentials. In this article, we have evaluated the performance of three B–O interatomic potential models recently developed by Bauchy et al [J. Non-Cryst. Solids, 2018, 498, 294–304], Du et al [J. Am. Ceram. Soc. https://doi.org/10.1111/jace.16082 ] and Edèn et al [Phys. Chem. Chem. Phys., 2018, 20, 8192–8209] aiming to reproduce the short-to-medium range structures of sodium borosilicate glasses in the system 25 Na₂O x B₂O₃ (75 − x) SiO₂ (x = 0-75 mol%). To evaluate the different force fields, we have computed at the density functional theory level the NMR parameters of ¹¹B, ²³Na, and ²⁹Si of the models generated with the three potentials and the simulated MAS NMR spectra compared with the experimental counterparts. It was observed that the rigid ionic models proposed by Bauchy and Du can both reliably reproduce the partitioning between BO₃ and BO₄ species of the investigated glasses, along with the local environment around sodium in the glass structure. However, they do not accurately reproduce the second coordination sphere of silicon ions and the Si–O–T (T = Si, B) and B-O-T distribution angles in the investigated compositional space which strongly affect the NMR parameters and final spectral shape. On the other hand, the core-shell parameterization model proposed by Edén underestimates the fraction of BO₄ species of the glass with composition 25Na₂O 18.4B₂O₃ 56.6SiO₂ but can accurately reproduce the shape of the ¹¹B and ²⁹Si MAS-NMR spectra of the glasses investigations due to the narrower B–O–T and Si-O-T bond angle distributions. Finally, the effect of the number of boron atoms (also distinguishing the BO₃ and BO₄ units) in the second coordination sphere of the network former cations on the NMR parameters have been evaluated.     

A lightweight and cost effective edge intelligence architecture based on containerization technology

World Wide Web - The integration of Cloud computing and Internet of Things led to rapid growth in the edge computing field. This would not be achievable without combining the data centers’...     

FNDC5/Irisin System in Neuroinflammation and Neurodegenerative Diseases: Update and Novel Perspective

Irisin, the circulating peptide originating from fibronectin type III domain-containing protein 5 (FNDC5), is mainly expressed by muscle fibers under peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α) control during exercise. In addition to several beneficial effects on health, physical activity positively affects nervous system functioning, particularly the hippocampus, resulting in amelioration of cognition impairments. Recently, FNDC5/irisin detection in hippocampal neurons and the presence of irisin in the cerebrospinal fluid opened a new intriguing chapter in irisin history. Interestingly, in the hippocampus of mice, exercise increases FNDC5 levels and upregulates brain-derived neurotrophic factor (BDNF) expression. BDNF, displaying neuroprotection and anti-inflammatory effects, is mainly produced by microglia and astrocytes. In this review, we discuss how these glial cells can morphologically and functionally switch during neuroinflammation by modulating the expression of a plethora of neuroprotective or neurotoxic factors. We also focus on studies investigating the irisin role in neurodegenerative diseases (ND). The emerging involvement of irisin as a mediator of the multiple positive effects of exercise on the brain needs further studies to better deepen this issue and the potential use in therapeutic approaches for neuroinflammation and ND.     

A comparison of three multidisciplinarity indices based on the diversity of Scopus subject areas of authors’ documents,their bibliography and their citing papers

Scientometrics - In this paper, we compare the distribution of Elsevier Scopus subject areas of authors’ documents, their bibliographical references and their citing documents. We compute the...     

Multimedia summarization using social media content

In this work, we propose a novel multimedia summarization technique from Online Social Networks (OSNs). In particular, we model each Multimedia Social Network (MSN)—i.e. an OSN focusing on the management and sharing of multimedia information—using an hypergraph based approach and exploit influence analysis methodologies to determine the most important multimedia objects with respect to one or more topics of interest. Successively, we obtain from the list of candidate objects a multimedia summary using a summarization model together with an heuristics that aims to generate summaries with priority (with respect to some user keywords), continuity, variety and not receptiveness features. The performed experiments on Flickr shows the effectiveness of proposed approach.     

GTV<Emphasis Type="SmallCaps">cut</Emphasis> for neuro-radiosurgery treatment planning: an MRI brain cancer seeded image segmentation method based on a cellular automata model

Despite of the development of advanced segmentation techniques, achieving accurate and reproducible gross tumor volume (GTV) segmentation results is still an important challenge in neuro-radiosurgery. Nowadays, magnetic resonance imaging (MRI) is the most prominent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a minimally invasive technology for dealing with inaccessible or insufficiently treated tumors with traditional surgery or radiotherapy. During a treatment planning phase, the GTV is generally contoured by experienced neurosurgeons and radiation oncologists using fully manual segmentation procedures on MR images. Unfortunately, this operative methodology is definitely time-expensive and operator-dependent. Delineation result repeatability, in terms of both intra- and inter-operator reliability, can be achieved only by using computer-assisted approaches. In this paper a novel semi-automatic seeded image segmentation method, based on a cellular automata model, for MRI brain cancer detection and delineation is proposed. This approach, called GTVcut, employs an adaptive seed selection strategy and helps to segment the GTV, by identifying the target volume to be treated using the Gamma Knife device. The accuracy of GTVcut was evaluated on a dataset composed of 32 brain cancers, using both spatial overlap-based and distance-based metrics. The achieved experimental results are very reproducible, showing the effectiveness and the clinical feasibility of the proposed approach.