Discovery of an Allosteric Ligand Binding Site in SMYD3 Lysine Methyltransferase

SMYD3 is a multifunctional epigenetic enzyme with lysine methyltransferase activity and various interaction partners. It is implicated in the pathophysiology of cancers but with an unclear mechanism. To discover tool compounds for clarifying its biochemistry and potential as a therapeutic target, a set of drug-like compounds was screened in a biosensor-based competition assay. Diperodon was identified as an allosteric ligand; its R and S enantiomers were isolated, and their affinities to SMYD3 were determined (K_D=42 and 84 μM, respectively). Co-crystallization revealed that both enantiomers bind to a previously unidentified allosteric site in the C-terminal protein binding domain, consistent with its weak inhibitory effect. No competition between diperodon and HSP90 (a known SMYD3 interaction partner) was observed although SMYD3–HSP90 binding was confirmed (K_D=13 μM). Diperodon clearly represents a novel starting point for the design of tool compounds interacting with a druggable allosteric site, suitable for the exploration of noncatalytic SMYD3 functions and therapeutics with new mechanisms of action.     

Adhesion of resin cements to contaminated zirconia resin cements on zirconia: effect saliva-contamination and surface conditioning

This study evaluated the adhesion of resin cements to zirconia after saliva contamination using resin cements with different chemistries. Zirconia discs (N?=?240, n?=?10 per group) were randomly divided into three groups: (a) C: No contamination (Control), (b) S: Contamination with saliva, (c) S?+?AA: Contamination with saliva followed by air-abrasion (CoJet). While half of the specimens were not conditioned, the other half were conditioned with 37.5% H₃PO₄ for 60?s. After rinsing, all specimen surfaces were silanized (Monobond Plus). Resin cements based on either methacrylate (Variolink II–VL) or MDP monomer (Panavia 21-PN) were polymerized on the substrates. The specimens were randomly divided into two further groups to be tested either after (a) 24?h dry storage at 37?°C or (b) thermocycling (×5000, 5–55?°C). Microshear bond (MSB) tests were conducted in a Universal Testing Machine and failure types were analyzed. Data were analyzed using Univariate analysis and Tukey’s tests (alpha = 0.05). While saliva contamination, 37.5% H₃PO₄ application (p?<?.001) and aging (p?<?.05) significantly affected the bond results, cement type did not show significant difference after aging (p?>?.05). Adhesive strength of PN (1.2–4.4?MPa) on saliva contaminated and etched zirconia was more stable than that of VL (0–2.8?MPa). After aging, bond strength results decreased the most with VL (3–100%) compared to PN (32–71%) but the decrease was less in the air-abraded groups after aging (VL: 3%; PN: 32%). Exclusively adhesive failures were experienced in all groups.     

Transmission of Bacterial Zoonotic Pathogens between Pets and Humans: The Role of Pet Food

Recent Salmonella outbreaks associated with dry pet food and treats raised the level of concern for these products as vehicle of pathogen exposure for both pets and their owners. The need to characterize the microbiological and risk profiles of this class of products is currently not supported by sufficient specific data. This systematic review summarizes existing data on the main variables needed to support an ingredients-to-consumer quantitative risk model to (1) describe the microbial ecology of bacterial pathogens in the dry pet food production chain, (2) estimate pet exposure to pathogens through dry food consumption, and (3) assess human exposure and illness incidence due to contact with pet food and pets in the household. Risk models populated with the data here summarized will provide a tool to quantitatively address the emerging public health concerns associated with pet food and the effectiveness of mitigation measures. Results of such models can provide a basis for improvements in production processes, risk communication to consumers, and regulatory action.     

Critical Role for the Protons in FRTL-5 Thyroid Cells: Nuclear Sphingomyelinase Induced-Damage

Proliferating thyroid cells are more sensitive to UV-C radiations than quiescent cells. The effect is mediated by nuclear phosphatidylcholine and sphingomyelin metabolism. It was demonstrated that proton beams arrest cell growth and stimulate apoptosis but until now there have been no indications in the literature about their possible mechanism of action. Here we studied the effect of protons on FRTL-5 cells in culture. We showed that proton beams stimulate slightly nuclear neutral sphingomyelinase activity and inhibit nuclear sphingomyelin-synthase activity in quiescent cells whereas stimulate strongly nuclear neutral sphingomyelinase activity and do not change nuclear sphingomyelin-synthase activity in proliferating cells. The study of neutral sphingomyelinase/sphingomyelin-synthase ratio, a marker of functional state of the cells, indicated that proton beams induce FRTL-5 cells in a proapoptotic state if the cells are quiescent and in an initial apoptotic state if the cells are proliferating. The changes of cell life are accompanied by a decrease of nuclear sphingomyelin and increase of bax protein.     

Coupling Interrupted Fischer and Multicomponent Joullié-Ugi to Chase Chemical Diversity: from Batch to Sustainable Flow Synthesis of Peptidomimetics

The generation of peptidomimetic substructures for medicinal chemistry purposes requires effective and divergent synthetic methods. We present in this work an efficient flow process that allows quick modulation of reagents for Joullié-Ugi multicomponent reaction, using spiroindolenines as core motifs. This sterically hindered imine equivalent could successfully be diversified using various isocyanides and amino acids in generally good space-time yields. A telescoped flow process combining interrupted Fischer reaction for spiroindolenine synthesis and subsequent Joullié-Ugi-type modification resulted in product formation in very good overall yield in less than 2 hours compared to 48 hours required in batch mode. The developed protocol can be seen as a general tool for rapid and facile generation of peptidomimetic compounds. We also showcase preliminary biological assessments for the prepared compounds.     

Experimental study on micro manufacturing of carbon nanotube (CNT) plastic composites

In recent years, innovative materials such as carbon nanotube composites are finding growing interest in several industrial sectors, from sports and leisure to electronics, automotive, aircraft, and defence. The reinforcing influence of the carbon nanotube is of prime interest. However, technological issues concerning the production methods and the manufacturing processes of carbon nanotube components limit the industrial application of this innovative and interesting material, especially whether small features are required. For this reason, manufacturing strategy involving new production technologies must be designed and developed. This paper studies the challenges of a manufacturing chain based on two manufacturing processes: injection moulding and micro milling. A case study based on these innovative processes is reported and discussed. The propagation chain effect and the influence of each considered process parameter on cutting force and geometrical accuracy of the features (the key characteristics of the process chain) were assessed by means of statistical analysis of variance (ANOVA). The ANOVA analysis demonstrated that cutting forces in micro milling are mainly influenced by the material and percentage of carbon nanotubes, while the main parameter influencing the geometrical accuracy of micro features is the matrix material.     

Validation of hot ring rolling industrial process 3D simulation

Ring rolling is a hot forming process used in the production of railway tyres, anti friction bearing races and different ring shaped work pieces for automotive energy production and aerospace applications. The advantages of ring rolling process include short production time, uniform quality, closed tolerances, good material quality and considerable saving in material cost. Despite the benefits some problems still exist according to a correct selection of the process parameters. Due to the nature of the process different rolling mills (driving, idle and axial rolls) are involved and the correct selection of the process parameters is not so feasible. Moreover an experimental approach to solve this problem risks to be more expensive. Actually FE codes are available to simulate the non linear problem that characterizes a ring rolling process. In this work a FE model, based on Deform 3D software, was tested versus experimental results acquired from an industrial plant. The accuracy of the FE model was analyzed through a dual comparison: by geometrical and by physical aspects. A good agreement was found between experimental and numerical results for both comparisons and, as a consequence, this code could be used in order to investigate and optimize the process parameters that characterize the ring rolling process in a virtual not expensive environment. The validated model will allow the studies of more environment-friend process configurations.     

A genetic expectation-maximization method for unsupervised change detection in multitemporal SAR imagery

In this paper, we present a novel, automatic and unsupervised change-detection approach to the analysis of single-channel single-polarization multitemporal SAR images. The statistical parameters of the changed and unchanged classes, which are assumed to follow a generalized Gaussian (GG) distribution in the analysed log-ratio image, are explicitly estimated by the expectation-maximization (EM) algorithm initialized with a robust strategy based on genetic algorithms (GAs). In addition, the proposed approach integrates two further processing capabilities. The first one intends to cope with the problem of the automatic detection of multiple changes in the scene. This is carried out by modelling the log-ratio image histogram with a multimodal GG mixture whose number of components is estimated basing on the Bayesian information criterion (BIC). The second processing capability allows exploitation of spatial contextual information in the change detection process through a Markovian formulation. Results obtained on both simulated and real data are reported and discussed.