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.     

Web-GIS models: accomplishing modularity with aspects

Spatial concerns of Web geographical information systems (Web-GIS) are inherently crosscutting and volatile: crosscutting because they affect multiple functionalities of Web-GIS systems, and volatile because their status may change often. If these concerns are not modularized properly, the quality of Web-GIS services, particularly with regard to adaptation and evolution, can be severely compromised. This paper uses aspect-orientation to model crosscutting and volatile spatial concerns. By modeling both types of concerns, crosscutting and volatile, as candidate aspects, one can use dynamic weaving to add or remove them from a system at runtime. The aspect-oriented approach proposed starts with the identification and specification of crosscutting concerns and follows by composing these using modeling aspects using a transformation approach, an aspect-oriented modeling technique. The conflicts that can emerge due to the composition order are also taken into consideration. Finally, this paper proposes a set of reusable GIS crosscutting concerns, documenting them in a concern catalogue.     

Statistical modeling of dissimilarity increments for d-dimensional data: Application in partitional clustering

This paper addresses the use of high order dissimilarity models in data mining problems. We explore dissimilarities between triplets of nearest neighbors, called dissimilarity increments (DIs). We derive a statistical model of DIs for d-dimensional data (d-DID) assuming that the objects follow a multivariate Gaussian distribution. Empirical evidence shows that the d-DID is well approximated by the particular case d=2. We propose the application of this model in clustering, with a partitional algorithm that uses a merge strategy on Gaussian components. Experimental results, in synthetic and real datasets, show that clustering algorithms using DID usually outperform well known clustering algorithms.     

Analysis of the velocity field of granular hopper flow

We report the analysis of radial characteristics of the flow of granular material through a conical hopper. The discharge is simulated for various orifice sizes and hopper opening angles. Velocity profiles are measured along two radial lines from the hopper cone vertex: along the main axis of the cone and along its wall. An approximate power law dependence on the distance from the orifice is observed for both profiles, although differences between them can be noted. In order to quantify these differences, we propose a Local Mass Flow Index that is a promising tool in the direction of a more reliable classification of the flow regimes in hoppers.     

A methodology for screening of microalgae as a decision making tool for energy and green chemical process applications

The increasing interest for biotechnological use of microalgae demands a methodology for selection of species suitable to support the development of technologies based on the use of such non-conventional renewable raw material, i.e., green industrial applications. The vast and expanding collection of experimental data on both cell growth and biomass composition available in the literature can be used to reduce the cost of the experimental investigations required to support process engineering and optimization. Selecting the appropriate organism requires extracting useful information from such data, a cumbersome task since various multidisciplinary factors must be considered. This paper presents a computer-aided methodology for selecting appropriate algal species given an energy or green chemical process application employing microalgae as a renewable raw material. The approach is “system oriented”, based on biomass composition and chemical processing of the biomass downstream of the CO₂ biofixation and harvesting operations. Quantitative performance results are supported by professional process simulation. Besides comparison of a set of species performances, the proposed methodology also allows the discrimination among distinct algal compositions resulting from different growth conditions for a given species. Furthermore, three categories of screening metrics are proposed to be maximized by the decision making procedure in order to elicit the relevant information. To demonstrate the potential of the proposed methodology, a databank of both biochemical and elemental compositions of microalgal biomass was used in three green applications: Assessment of biomass heating value; production of syngas by gasification of the biomass; and production of Bio-H₂. Within the accuracy of the databank employed to illustrate the procedure, the methodology selected Botryococcus braunii and Isochrysis galbana as potential promising candidates, for the three examined applications.     

Extraction and characterization of highly purified collagen from bovine pericardium for potential bioengineering applications

Bovine pericardium is widely used as a raw material in bioengineering as a source of collagen, a fundamental structural molecule. The physical, chemical, and biocompatibility characteristics of these natural fibers enable their broad use in several areas of the health sciences. For these applications, it is important to obtain collagen of the highest possible purity. The lack of a method to produce these pure biocompatible materials using simple and economically feasible techniques presents a major challenge to their production on an industrial scale. This study aimed to extract, purify, and characterize the type I collagen protein originating from bovine pericardium, considered to be an abundant tissue resource. The pericardium tissue was collected from male animals at slaughter age. Pieces of bovine pericardium were enzymatically digested, followed by a novel protocol developed for protein purification using ion-exchange chromatography. The material was extensively characterized by electrophoresis, scanning electron microscopy, energy dispersive X-ray spectroscopy, and infrared spectroscopy. The results showed a purified material with morphological properties and chemical functionalities compatible with type I collagen and similar to a highly purified commercial collagen. Thus, an innovative and relatively simple processing method was developed to extract and purify type I collagen from bovine tissue with potential applications as a biomaterial for regenerative tissue engineering.     

RF integrated inductor modeling and its application to optimization-based design

In this paper an optimization-based approach for the design of RF integrated inductors is addressed. For the characterisation of the inductor behaviour the double ??-model is used. The use of this model is twofold. On one hand it enables the generation of the inductor characterisation in a few seconds. On the other hand its integration into the optimization procedure is straightforward. For the evaluation of the model element values analytical expressions based on technology parameters as well as on the device geometric characteristics are used. The use of a technology-based methodology for the evaluation of the model parameters grants the adaptability of the model to any technology. The inductor analytical characterization is integrated into an optimization-based tool for the automatic design of RF integrated inductors. This tool uses a modified genetic algorithm (MGA) optimization procedure, which has proved its validation in previous work. Due to the design parameter constraints nature as well as the topology constraints, discrete variables optimization techniques are used. The accuracy of the results is checked against a non-commercial software.     

Use of Ozonated Water for Disinfecting Gastrointestinal Endoscopes

The reprocessing of endoscopes is a complex procedure due to their structural design. In the constant search for new antimicrobial substances, recent studies with ozone have yielded great benefits. The present study evaluated the effects of ozonated water used to disinfect endoscopes comparing its efficacy with the conventional technique (2% glutaraldehyde). According to the results obtained, when ozonated water was used (330 mg.min.L^?1), induced a 2 log reduction of the viable microorganisms under the conditions tested. Ozonated water was a potent gastrointestinal endoscopic sanitizer, suggesting it is a feasible alternative for disinfection.     

Short communication: Passive shedding of Mycobacterium avium ssp. paratuberculosis in commercial dairy goats in Brazil

Goat farming is a low-cost alternative to dairy production in developing countries. In Brazil, goat production has increased in recent years due in part to the implementation of programs encouraging this activity. Mycobacterium avium ssp. paratuberculosis (MAP) is the causative agent of paratuberculosis, a disease that causes chronic granulomatous enteritis in ruminants, but MAP transmission dynamics are still poorly understood in goats. In a previously published study of our research group, 10 dairy goat farms (467 animals) from Minas Gerais state were analyzed for MAP detection; 2 fecal cultures and 11 milk samples tested positive for MAP by conventional PCR and were confirmed by sequencing. Because no clinical signs were observed over 1 yr of monitoring, we hypothesized that these MAP-positive goats could be passive shedders. Thus, in the present study, 4 positive goats (4/13) from the previous study were purchased and feces and milk samples were collected for evaluation (twice, with an interval of 3 mo between tests) by culture of MAP, IS900 PCR, or both. All analyses were negative for MAP. At the last time point, blood samples were collected for ELISA, the animals were killed, and tissues collected for tissue culture and histopathology. At necropsy, no macroscopic lesions related to paratuberculosis were observed. Similarly, no histological changes were observed and MAP in samples stained by Ziehl–Neelsen was not detected. These animals were characterized as potential passive shedders with upward contamination of the teat canal by MAP. This is the first report of the passive shedding phenomenon in goats in Brazil and it highlights the importance of identifying these animals for control programs and to ensure the quality of dairy products.     

On extremal dependence: some contributions

The usual coefficients of tail dependence are based on exceedances of high values. These extremal events are useful and widely used in literature but an adverse situation may also occur with the upcrossing of a high level. In this context we define upcrossings-tail dependence coefficients and analyze all types of dependence coming out. We will prove that these coefficients are related to multivariate tail dependence coefficients already known in literature. We shall see that the upcrossings-tail dependence coefficients have the interesting feature of congregating both ??temporal?? and ??spatial?? dependence. The coefficients of tail dependence can also be applied to stationary sequences and hence measure the tail dependence in time. Results concerning connections with the extremal index and the upcrossings index as well as with local dependence conditions will be stated. Several illustrative examples will be exploited and a small note on inference will be given by presenting estimators derived from the stated results and respective properties.