Genome-wide bacterial toxicity screening uncovers the mechanisms of toxicity of a cationic polystyrene nanomaterial

By exploiting a genome-wide collection of bacterial single-gene deletion mutants, we have studied the toxicological pathways of a 60-nm cationic (amino-functionalized) polystyrene nanomaterial (PS-NH(2)) in bacterial cells. The IC(50) of commercially available 60 nm PS-NH(2) was determined to be 158 μg/mL, the IC(5) is 108 μg/mL, and the IC(90) is 190 μg/mL for the parent E. coli strain of the gene deletion library. Over 4000 single nonessential gene deletion mutants of Escherichia coli were screened for the growth phenotype of each strain in the presence and absence of PS-NH(2). This revealed that genes clusters in the lipopolysaccharide biosynthetic pathway, outer membrane transport channels, ubiquinone biosynthetic pathways, flagellar movement, and DNA repair systems are all important to how this organism responds to cationic nanomaterials. These results, coupled with those from confirmatory assays described herein, suggest that the primary mechanisms of toxicity of the 60-nm PS-NH(2) nanomaterial in E. coli are destabilization of the outer membrane and production of reactive oxygen species. The methodology reported herein should prove generally useful for identifying pathways that are involved in how cells respond to a broad range of nanomaterials and for determining the mechanisms of cellular toxicity of different types of nanomaterials.     

Comparing the impact of bentonite addition for both must clarification and wine fining on the chemical profile of wine from Chambave Muscat grapes

The impact of bentonite fining is generally studied on final wines, and few studies have evaluated it throughout the winemaking process. This work studied the fate of proteins and terpenols, the main targets of bentonite addition, during the processing of Chambave Muscat aromatic grapes. The experimental trials were performed in two vintages (2006 and 2007) and included the following processes: bentonite addition to must only (100 g hL^?1 in both vintages), fining of wine only (100 g hL^?1 in both vintages), double bentonite treatment on must and wine (200 and 150 g hL^?1 in 2006 and in 2007, respectively) and no treatment (control). The results demonstrated that the treatment allowing the best removal of protein was the addition of bentonite to must only. Moreover, a lower removal of free terpenols was observed in samples from double treatment compared with wines fined with bentonite only after alcoholic fermentation.     

Preliminary evaluation of biogenic amines content in Chilean young varietal wines by HPLC

Biogenic amines are organic nitrogenous compounds produced in wines mainly during malolactic fermentation. Its presence is a health risk for sensitive individuals and it could negatively affect the wine quality. The objective of this work was to determine the biogenic amines content in Chilean young varietal wines. For that, a liquid chromatographic method with pre-column derivatization was optimized and validated to achieve a reliable quantification of the most important biogenic amines in wines, i.e. histamine, tyramine, spermine, spermidine, putrescine, cadaverine and phenylethylamine. Using a face-centered central composite design derivatization and chromatographic conditions were optimized. Derivatization with dansyl chloride showed an optimum yield for all biogenic amines at 60 °C during 60 min. These derivatives were optimally separated with a C₁₈ YMC-Pack ODS-A column set a 40 °C using a mobile phase composed of acetonitrile and water under gradient conditions. An effective separation and quantification of the biogenic amines was achieved in 40 min using ultraviolet detection at 254 nm. Validation was established according to ICH guidelines, calibrations in matrix fitted a linear regression model with R² > 0.997. Repeatability (n = 6) and intermediate precision (n = 3) in matrix showed RSD values <2.34% and <3.16%, respectively. This method was applied to determine for the first time the biogenic amines content in Chilean wines. Twenty-seven samples of young varietal wines, i.e. Cabernet Sauvignon (n = 9), Merlot (n = 8) and Carménère (n = 10) were analyzed finding a biogenic amines content from 18.12 to 39.84 mg L^-1, where putrescine showed the highest concentration in all grape varieties. No significant difference was found between grapes varieties regarding total biogenic amines content (P = 0.7842, df = 26). Along with putrescine, histamine and tyramine were the most abundant biogenic amines but similar levels were also observed with spermidine.     

The Assessment Portfolio: A Possible Answer to the Distance Education Assessment Dilemma

ABSTRACT

This “Siteseeing” column provides reviews of Awards sites.     

An Integrated System for UAV Control Using a Neural Network Implemented in a Prototyping Board

Modern aerospace vehicles are expected to have non-conventional flight envelopes and then, in order to operate in uncertain environments, they must guarantee a high level of robustness and adaptability. A Neural Network (NN) controller, with real-time learning capability, can be used in applications with manned or unmanned aerial vehicles. In this paper a novel real-time control system, based on a NN model, in order to control the trajectories of a hexacopter is proposed. The proposed NN is optimized by the analytical calculation of the embedding parameters. The paper shows a performance evaluation, through a real experimental testbed, of the proposed approach in terms of error measures and computation of the angular velocities of the hexacopter.     

Geographical Authentication of Tequila According to its Mineral Content by Means of Support Vector Machines

The elemental profile of tequila samples from the three main production areas of the State of Jalisco, namely Amatitlan, Guadalajara, and Tequila, was used to carry out their geographical characterization. With this aim, the concentration of Al, Ba, Ca, Cu, Fe, K, Mg, Mn, Na, S, Sr, and Zn was determined by inductively coupled plasma atomic emission spectroscopy. Principal component analysis was addressed to visualize data trends. The number of input variables was reduced by means of backward stepwise linear discriminant analysis and support vector machines were used to construct an adequate classification model. The best classification performance was obtained by a linear support vector machine model with 100% of prediction ability.     

Professor Geoffrey Petts (1953–2018): An outstanding interdisciplinary river scientist

This paper provides an introduction and an editorial to this special issue of River Research and Applications by documenting the contributions made by Professor Geoffrey Petts to our interdisciplinary understanding of the functioning of rivers and their floodplains and their sustainable management. We outline Geoff's career, which framed not only his research but its communication through his inspirational teaching but also included very high level and innovative contributions to the management and development of several UK universities. We then explain how and why Geoff was an outstanding interdisciplinary river scientist and how he communicated his science through both integrative books and book chapters and also research papers that developed eight complementary research themes. Lastly, we introduce the papers in this special issue and show how they provide inputs to Geoff's areas of research interest.     

Automatic word naming recognition for an on-line aphasia treatment system

One of the most common effects among aphasia patients is the difficulty to recall names or words. Typically, word retrieval problems can be treated through word naming therapeutic exercises. In fact, the frequency and the intensity of speech therapy are key factors in the recovery of lost communication functionalities. In this sense, speech and language technology can have a relevant contribution in the development of automatic therapy methods. In this work, we present an on-line system designed to behave as a virtual therapist incorporating automatic speech recognition technology that permits aphasia patients to perform word naming training exercises. We focus on the study of the automatic word naming detector module and on its utility for both global evaluation and treatment. For that purpose, a database consisting of word naming therapy sessions of aphasic Portuguese native speakers has been collected. In spite of the different patient characteristics and speech quality conditions of the collected data, encouraging results have been obtained thanks to a calibration method that makes use of the patients’ word naming ability to automatically adapt to the patients’ speech particularities.     

Understanding the diffusion of mobile digital content: a growth curve modelling approach

While the sales of mobile digital content have been growing exponentially, the understanding of its diffusion remains limited in the literature. In this study, we set out to enrich this understanding using a growth curve modelling approach. We applied four widely used growth curve models of innovation diffusion and compared their performance in explaining the diffusion of mobile digital content empirically. Analysis based on the data collected on a product adopted by nearly 30 million mobile phone users over a 149-week period in 31 regions in China revealed that the Gompertz model was the most effective model in depicting the diffusion process, with more than 99 % of the variance explained. Moreover, we found that population, urbanization, education level, and mobile technology usage were significant determinants of various parameters such as the diffusion rate and inflection point of the diffusion process, respectively. Implications for both researchers and practitioners are discussed.