Reactive Oxygen and Nitrogen Species in Defense/Stress Responses Activated by Chitosan in Sycamore Cultured Cells

Chitosan (CHT) is a non-toxic and inexpensive compound obtained by deacetylation of chitin, the main component of the exoskeleton of arthropods as well as of the cell walls of many fungi. In agriculture CHT is used to control numerous diseases on various horticultural commodities but, although different mechanisms have been proposed, the exact mode of action of CHT is still unknown. In sycamore (Acer pseudoplatanus L.) cultured cells, CHT induces a set of defense/stress responses that includes production of H₂O₂ and nitric oxide (NO). We investigated the possible signaling role of these reactive molecules in some CHT-induced responses by means of inhibitors of production and/or scavengers. The results show that both reactive nitrogen and oxygen species are not only a mere symptom of stress conditions but are involved in the responses induced by CHT in sycamore cells. In particular, NO appears to be involved in a cell death form induced by CHT that shows apoptotic features like DNA fragmentation, increase in caspase-3-like activity and release of cytochrome c from the mitochondrion. On the contrary, reactive oxygen species (ROS) appear involved in a cell death form induced by CHT that does not show these apoptotic features but presents increase in lipid peroxidation.     

Update on the Diagnostic Pitfalls of Autopsy and Post-Mortem Genetic Testing in Cardiomyopathies

Inherited cardiomyopathies are frequent causes of sudden cardiac death (SCD), especially in young patients. Despite at the autopsy they usually have distinctive microscopic and/or macroscopic diagnostic features, their phenotypes may be mild or ambiguous, possibly leading to misdiagnoses or missed diagnoses. In this review, the main differential diagnoses of hypertrophic cardiomyopathy (e.g., athlete’s heart, idiopathic left ventricular hypertrophy), arrhythmogenic cardiomyopathy (e.g., adipositas cordis, myocarditis) and dilated cardiomyopathy (e.g., acquired forms of dilated cardiomyopathy, left ventricular noncompaction) are discussed. Moreover, the diagnostic issues in SCD victims affected by phenotype-negative hypertrophic cardiomyopathy and the relationship between myocardial bridging and hypertrophic cardiomyopathy are analyzed. Finally, the applications/limits of virtopsy and post-mortem genetic testing in this field are discussed, with particular attention to the issues related to the assessment of the significance of the genetic variants.     

Sofosbuvir Selects for Drug-Resistant Amino Acid Variants in the Zika Virus RNA-Dependent RNA-Polymerase Complex In Vitro

The nucleotide analog sofosbuvir, licensed for the treatment of hepatitis C, recently revealed activity against the Zika virus (ZIKV) in vitro and in animal models. However, the ZIKV genetic barrier to sofosbuvir has not yet been characterized. In this study, in vitro selection experiments were performed in infected human hepatoma cell lines. Increasing drug pressure significantly delayed viral breakthrough (p = 0.029). A double mutant in the NS5 gene (V360L/V607I) emerged in 3 independent experiments at 40–80 µM sofosbuvir resulting in a 3.9 ± 0.9-fold half- maximal inhibitory concentration (IC₅₀) shift with respect to the wild type (WT) virus. A triple mutant (C269Y/V360L/V607I), detected in one experiment at 80 µM, conferred a 6.8-fold IC₅₀ shift with respect to the WT. Molecular dynamics simulations confirmed that the double mutant V360L/V607I impacts the binding mode of sofosbuvir, supporting its role in sofosbuvir resistance. Due to the distance from the catalytic site and to the lack of reliable structural data, the contribution of C269Y was not investigated in silico. By a combination of sequence analysis, phenotypic susceptibility testing, and molecular modeling, we characterized a double ZIKV NS5 mutant with decreased sofosbuvir susceptibility. These data add important information to the profile of sofosbuvir as a possible lead for anti-ZIKV drug development.     

Building kernels from binary strings for image matching.

In the statistical learning framework, the use of appropriate kernels may be the key for substantial improvement in solving a given problem. In essence, a kernel is a similarity measure between input points satisfying some mathematical requirements and possibly capturing the domain knowledge. In this paper, we focus on kernels for images: we represent the image information content with binary strings and discuss various bitwise manipulations obtained using logical operators and convolution with nonbinary stencils. In the theoretical contribution of our work, we show that histogram intersection is a Mercer's kernel and we determine the modifications under which a similarity measure based on the notion of Hausdorff distance is also a Mercer's kernel. In both cases, we determine explicitly the mapping from input to feature space. The presented experimental results support the relevance of our analysis for developing effective trainable systems.     

A comparative analysis of methods for pruning decision trees

In this paper, we address the problem of retrospectively pruning decision trees induced from data, according to a top-down approach. This problem has received considerable attention in the areas of pattern recognition and machine learning, and many distinct methods have been proposed in literature. We make a comparative study of six well-known pruning methods with the aim of understanding their theoretical foundations, their computational complexity, and the strengths and weaknesses of their formulation. Comments on the characteristics of each method are empirically supported. In particular, a wide experimentation performed on several data sets leads us to opposite conclusions on the predictive accuracy of simplified trees from some drawn in the literature. We attribute this divergence to differences in experimental designs. Finally, we prove and make use of a property of the reduced error pruning method to obtain an objective evaluation of the tendency to overprune/underprune observed in each method     

Effect of Particle Size on Monometallic and Bimetallic (Au,Pd)/C on the Liquid Phase Oxidation of Glycerol

The influence of metal particle size of monometallic and bimetallic supported catalysts (Au, Pd, Au–Pd)/C was studied using as a model reaction the liquid phase oxidation of glycerol. By tuning the metal particle size from 2 to 16 nm a progressive decrease of activity and simultaneously an increase in the selectivity to sodium glycerate was observed. Moreover, the influence of the temperature was studied and it was found that by increasing the temperature, only with a large particle size the formed glycerate was retained and not over-oxidized to tartronate.     

Microfluidic motion for a direct investigation of solvent interactions with PDMS microchannels

Solid surface/liquid interactions play an important role in microfluidics and particularly in manipulation of films, drops and bubbles, a basic requirement for a number of lab-on-chip applications. The behavior of solvents in coated microchannels is difficult to be predicted considering theories; therefore, experimental methods able to estimate the properties at the interface in real time and during the operational regime are amenable. Here, we propose to use an experimental setup to evaluate the effective dynamics of solvents inside PDMS microchannels. The influence of the solvent properties as well as of the channel wall’s wettability on the fluid movements was evaluated. Modification of the channel properties was achieved by introducing Teflon coatings that allow producing stable hydrophobic microchannel walls. The results were fitted according to Washburn-type power-law and compared with theoretical calculations of the parameter β that expresses the dependence of capillary dynamics on surface tension γ, liquid viscosity η, contact angles θ and the hydraulic radius R _H. A comparison between the calculated and the experimental values reveled that parameters other than the contemplated ones influenced the measurements. The main parameter that affects the flow of solvents such as water, methanol ethanol, dimethylformamide, acetonitrile and acetone was found to be the γ/η ratio. Considering these results, the investigation tool described here is believed to be promising to predict the dynamics of common organic solvents inside integrated functional fluidic devices and to accurately control solvent flow, particularly in capillary-driven pumpless systems, a basic requirement for widening the application range of PDMS lab-on-chip devices.