220 research outputs found

    Implementation of Digital Language Learning Opportunities in Higher Education. Guidelines for Good Practice.

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    This publication is aimed at Higher Education policymakers, as well as Languages for Specific Purpose (LSP) lecturers. It contains important theoretical and practical guidelines to improve the implementation of digital-based language learning opportunities in higher education. It also intends to present, examine and reflect on the opportunities related to the use of digital technology in the language learning and teaching process.This publication brings together contributions from the six partners that integrate the QuILL project consortium. (2023-01-06

    The association of food ingredients in breakfast cereal products and fumonisins production: risks identification and predictions

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    Breakfast processed products are remarkably at risk of fungal contamination. This research surveyed the fumonisins concentration in different breakfast products, and carried out in-vitro experiments measuring fumonisins content in different substrates inoculated with Fusarium verticillioides. The pipeline started with the identification of combinations of ingredients for 58 breakfast products. Twenty-three core ingredients, seven nutritional components and production types were analyzed using a Pearson correlation, k-means clustering and principal component analysis to show that no single factor is responsible for high fumonisins detection in processed cereals products. Consequently, decision tree regression was used as a means of determining and visualizing complex logical interactions between the same factors. We clustered the association of ingredients in low, medium, and high risk of fumonisin detection. The analysis showed that high fumonisins concentration is associated with those products that have high maize concentrations coupled especially with high sodium or rice. In a in-vitro experiment, different media were prepared by mixing the ingredients in the proportion found in the first survey and by measuring fumonisins production by Fusarium verticillioides. Results showed that: 1) fumonisins production by F. verticillioides is boosted by the synergistic effect of maize and highly ready carbohydrate content such as white flour; 2) a combination of maize >26%(w/w), rice >2.5%(w/w), NaCl >2.2%(w/w) led to high fumonisins production, while mono-ingredient products were more protective against fumonisins production. The observations in the in-vitro experiments appeared to align with the decision tree model that an increase in ingredient complexity can lead to fumonisins production by Fusarium. However, more research is urgently needed to develop the area of predictive mycology based on the association of processing, ingredients, fungal development, and mycotoxins production

    SARS-CoV-2 variants and their relevant mutational profiles: update summer 2021

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    : Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic caused by it, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been undergoing a genetic diversification leading to the emergence of new variants. Nevertheless, a clear definition of the genetic signatures underlying the circulating variants is still missing. Here, we provide a comprehensive insight into mutational profiles characterizing each SARS-CoV-2 variant, focusing on spike mutations known to modulate viral infectivity and/or antigenicity. We focused on variants and on specific relevant mutations reported by GISAID, Nextstrain, Outbreak.info, Pango, and Stanford database websites that were associated with any clinical/diagnostic impact, according to published manuscripts. Furthermore, 1,223,338 full-length high-quality SARS-CoV-2 genome sequences were retrieved from GISAID and used to accurately define the specific mutational patterns in each variant. Finally, mutations were mapped on the three-dimensional structure of the SARS-CoV-2 spike protein to assess their localization in the different spike domains. Overall, this review sheds light and assists in defining the genetic signatures characterizing the currently circulating variants and their clinical relevance. IMPORTANCE Since the emergence of SARS-CoV-2, several recurrent mutations, particularly in the spike protein, arose during human-to-human transmission or spillover events between humans and animals, generating distinct worrisome variants of concern (VOCs) or of interest (VOIs), designated as such due to their clinical and diagnostic impacts. Characterizing these variants and their related mutations is important in tracking SAR-CoV-2 evolution and understanding the efficacy of vaccines and therapeutics based on monoclonal antibodies, convalescent-phase sera, and direct antivirals. Our study provides a comprehensive survey of the mutational profiles characterizing the important SARS-CoV-2 variants, focusing on spike mutations and highlighting other protein mutations

    Computer-based techniques for lead identification and optimization II: Advanced search methods

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    This paper focuses on advanced computational techniques for identifying and optimizing lead molecules, such as metadynamics and a novel dynamic 3D pharmacophore analysis method called Dynophores. In this paper, the first application of the funnel metadynamics of the Berberine binding to G-quadruplex DNA is depicted, disclosing hints for drug design, in particular clarifying water's role and suggesting the design of derivatives able to replace the solvent-mediated interactions between ligand and DNA to achieve more potent and selective activity. Secondly, the novel dynamic pharmacophore approach is an extension of the classic 3D pharmacophores, with statistical and sequential information about the conformational flexibility of a molecular system derived from molecular dynamics (MD) simulations

    Bifunctional Amidophosphonate Molecules for Uranium Extraction in Nitrate Acidic Media

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    International audienceBifunctional amidophosphonate derivatives, already known as efficient ligands in uranium extraction from phosphoric media, have been evaluated and compared to the conventional trin-butyl phosphate (TBP) for uranium extraction from nitric medium. The efficiency of U extraction and its selectivity towards competing elements such as Th, Zr, Mo, Fe and V was evaluated with various ligand structures. It was found that extractant molecules containing a monosaponified phosphonate moiety instead of phosphonate moieties are less effective and selective. Furthermore, it was observed that alkylation of the methylene bridge linking the two functional groups prevent the formation of precipitates during the uranium loading. Effects of acidity as well as ligand concentration were also investigated to estimate the loading capacity of the molecules. More detailed stoichiometry and transfer energy were further determined by the slope analysis method and a thermodynamic study. The possible uranium recovery from the organic phase has finally been demonstrated thanks to stripping steps at low nitric acid concentration

    Folding intermediate states of the parallel human telomeric G-quadruplex DNA explored using Well-Tempered Metadynamics

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    An increasingly comprehension of the folding intermediate states of DNA G-quadruplexes (G4s) is currently an important scientific challenge, especially for the human telomeric (h-tel) G4s-forming sequences, characterized by a highly polymorphic nature. Despite the G-triplex conformation was proposed as one of the possible folding intermediates for the antiparallel and hybrid h-tel G4s, for the parallel h-tel topology with an all-anti guanine orientation, a vertical strand-slippage involving the G-triplets was proposed in previous works through microseconds-long standard molecular dynamics simulations (MDs). Here, in order to get further insights into the vertical strand-slippage and the folding intermediate states of the parallel h-tel G4s, we have carried out a Well-Tempered Metadynamics simulation (WT-MetaD), which allowed us to retrieve an ensemble of six G4s having two/G-tetrad conformations derived by the G-triplets vertical slippage. The insights highlighted in this work are aimed at rationalizing the mechanistic characterisation of the parallel h-tel G4 folding process

    Multi-Targeting Bioactive Compounds Extracted from Essential Oils as Kinase Inhibitors

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    Essential oils (EOs) are popular in aromatherapy, a branch of alternative medicine that claims their curative effects. Moreover, several studies reported EOs as potential anti-cancer agents by inducing apoptosis in different cancer cell models. In this study, we have considered EOs as a potential resource of new kinase inhibitors with a polypharmacological profile. On the other hand, computational methods offer the possibility to predict the theoretical activity profile of ligands, discovering dangerous off-targets and/or synergistic effects due to the potential multi-target action. With this aim, we performed a Structure-Based Virtual Screening (SBVS) against X-ray models of several protein kinases selected from the Protein Data Bank (PDB) by using a chemoinformatics database of EOs. By evaluating theoretical binding affinity, 13 molecules were detected among EOs as new potential kinase inhibitors with a multi-target profile. The two compounds with higher percentages in the EOs were studied more in depth by means Induced Fit Docking (IFD) protocol, in order to better predict their binding modes taking into account also structural changes in the receptor. Finally, given its good binding affinity towards five different kinases, cinnamyl cinnamate was biologically tested on different cell lines with the aim to verify the antiproliferative activity. Thus, this work represents a starting point for the optimization of the most promising EOs structure as kinase inhibitors with multi-target feature
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