Differential Proteomic Analysis of Noncardia Gastric Cancer from Individuals of Northern Brazil

Gastric cancer is the second leading cause of cancer-related death worldwide. The identification of new cancer biomarkers is necessary to reduce the mortality rates through the development of new screening assays and early diagnosis, as well as new target therapies. In this study, we performed a proteomic analysis of noncardia gastric neoplasias of individuals from Northern Brazil. The proteins were analyzed by two-dimensional electrophoresis and mass spectrometry. For the identification of differentially expressed proteins, we used statistical tests with bootstrapping resampling to control the type I error in the multiple comparison analyses. We identified 111 proteins involved in gastric carcinogenesis. The computational analysis revealed several proteins involved in the energy production processes and reinforced the Warburg effect in gastric cancer. ENO1 and HSPB1 expression were further evaluated. ENO1 was selected due to its role in aerobic glycolysis that may contribute to the Warburg effect. Although we observed two up-regulated spots of ENO1 in the proteomic analysis, the mean expression of ENO1 was reduced in gastric tumors by western blot. However, mean ENO1 expression seems to increase in more invasive tumors. This lack of correlation between proteomic and western blot analyses may be due to the presence of other ENO1 spots that present a slightly reduced expression, but with a high impact in the mean protein expression. In neoplasias, HSPB1 is induced by cellular stress to protect cells against apoptosis. In the present study, HSPB1 presented an elevated protein and mRNA expression in a subset of gastric cancer samples. However, no association was observed between HSPB1 expression and clinicopathological characteristics. Here, we identified several possible biomarkers of gastric cancer in individuals from Northern Brazil. These biomarkers may be useful for the assessment of prognosis and stratification for therapy if validated in larger clinical study sets.

Structural Insights into Human Peroxisome Proliferator Activated Receptor Delta (PPAR-Delta) Selective Ligand Binding

Peroxisome proliferator activated receptors (PPARs delta, alpha and gamma) are closely related transcription factors that exert distinct effects on fatty acid and glucose metabolism, cardiac disease, inflammatory response and other processes. Several groups developed PPAR subtype specific modulators to trigger desirable effects of particular PPARs without harmful side effects associated with activation of other subtypes. Presently, however, many compounds that bind to one of the PPARs cross-react with others and rational strategies to obtain highly selective PPAR modulators are far from clear. GW0742 is a synthetic ligand that binds PPAR delta more than 300-fold more tightly than PPAR alpha or PPAR gamma but the structural basis of PPAR delta: GW0742 interactions and reasons for strong selectivity are not clear. Here we report the crystal structure of the PPAR delta:GW0742 complex. Comparisons of the PPAR delta:GW0742 complex with published structures of PPARs in complex with alpha and gamma selective agonists and pan agonists suggests that two residues (Val312 and Ile328) in the buried hormone binding pocket play special roles in PPAR delta selective binding and experimental and computational analysis of effects of mutations in these residues confirms this and suggests that bulky substituents that line the PPAR alpha and gamma ligand binding pockets as structural barriers for GW0742 binding. This analysis suggests general strategies for selective PPAR delta ligand design.

Short steel and concrete columns under high temperatures

The growing demand for knowledge about the effect of high temperatures on structures has stimulated increasing research worldwide. This article presents experimental results for short composite steel and concrete columns subjected to high temperatures in ovens with or without an axial compression load, numerically analyzes the temperature distribution in these columns after 30 and 60 minutes and compares them with experimental results. The models consist of concrete-filled tubes of three different thicknesses and two different diameters, and the concrete fill has conventional properties that remained constant for all of the models. The stress-strain behavior of the composite columns was altered after exposure to high temperatures relative to the same columns at room temperature, which was most evident in the 60-minute tests due to the higher temperatures reached. The computational analysis adopted temperature rise curves that were obtained experimentally.

Analysis of energy dissipation in stirred suspension polymerisation reactors using computational fluid dynamics

This work evaluates the spatial distribution of normalised rates of droplet breakage and droplet coalescence in liquidliquid dispersions maintained in agitated tanks at operation conditions normally used to perform suspension polymerisation reactions. Particularly, simulations are performed with multiphase computational fluid dynamics (CFD) models to represent the flow field in liquidliquid styrene suspension polymerisation reactors for the first time. CFD tools are used first to compute the spatial distribution of the turbulent energy dissipation rates (e) inside the reaction vessel; afterwards, normalised rates of droplet breakage and particle coalescence are computed as functions of e. Surprisingly, multiphase simulations showed that the rates of energy dissipation can be very high near the free vortex surfaces, which has been completely neglected in previous works. The obtained results indicate the existence of extremely large energy dissipation gradients inside the vessel, so that particle breakage occurs primarily in very small regions that surround the impeller and the free vortex surface, while particle coalescence takes place in the liquid bulk. As a consequence, particle breakage should be regarded as an independent source term or a boundary phenomenon. Based on the obtained results, it can be very difficult to justify the use of isotropic assumptions to formulate particle population balances in similar systems, even when multiple compartment models are used to describe the fluid dynamic behaviour of the agitated vessel. (C) 2011 Canadian Society for Chemical Engineering

Gas-phase reactivity of protonated 2-oxazoline derivatives: mass spectrometry and computational studies

RATIONALE: Oxazolines have attracted the attention of researchers worldwide due to their versatility as carboxylic acid protecting groups, chiral auxiliaries, and ligands for asymmetric catalysis. Electrospray ionization tandem mass spectrometric (ESI-MS/MS) analysis of five 2-oxazoline derivatives has been conducted, in order to understand the influence of the side chain on the gas-phase dissociation of these protonated compounds under collision-induced dissociation (CID) conditions. METHODS: Mass spectrometric analyses were conducted in a quadrupole time-of-flight (Q-TOF) spectrometer fitted with electrospray ionization source. Protonation sites have been proposed on the basis of the gas-phase basicity, proton affinity, atomic charges, and a molecular electrostatic potential map obtained on the basis of the quantum chemistry calculations at the B3LYP/6-31 + G(d, p) and G2(MP2) levels. RESULTS: Analysis of the atomic charges, gas-phase basicity and proton affinities values indicates that the nitrogen atom is a possible proton acceptor site. On the basis of these results, two main fragmentation processes have been suggested: one taking place via neutral elimination of the oxazoline moiety (99 u) and another occurring by sequential elimination of neutral fragments with 72 u and 27 u. These processes should lead to formation of R+. CONCLUSIONS: The ESI-MS/MS experiments have shown that the side chain could affect the dissociation mechanism of protonated 2-oxazoline derivatives. For the compound that exhibits a hydroxyl at the lateral chain, water loss has been suggested to happen through an E2-type elimination, in an exothermic step. Copyright (C) 2012 John Wiley & Sons, Ltd.

Smart histogram analysis applied to the skull-stripping problem in T1-weighted MRI

In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.

A general framework for multi-compartmental analysis of drug chemotherapy dynamics in human immunodeficiency virus type-1 infected individuals

An optimal control strategy for the highly active antiretroviral therapy associated to the acquired immunodeficiency syndrome should be designed regarding a comprehensive analysis of the drug chemotherapy behavior in the host tissues, from major viral replication sites to viral sanctuary compartments. Such approach is critical in order to efficiently explore synergistic, competitive and prohibitive relationships among drugs and, hence, therapy costs and side-effect minimization. In this paper, a novel mathematical model for HIV-1 drug chemotherapy dynamics in distinct host anatomic compartments is proposed and theoretically evaluated on fifteen conventional anti-retroviral drugs. Rather than interdependence between drug type and its concentration profile in a host tissue, simulated results suggest that such profile is importantly correlated with the host tissue under consideration. Furthermore, the drug accumulative dynamics are drastically affected by low patient compliance with pharmacotherapy, even when a single dose lacks. (C) 2012 Elsevier Inc. All rights reserved.

Analysis of elastic functionally graded materials under large displacements via high-order tetrahedral elements

The purpose of this study is to present a position based tetrahedral finite element method of any order to accurately predict the mechanical behavior of solids constituted by functionally graded elastic materials and subjected to large displacements. The application of high-order elements makes it possible to overcome the volumetric and shear locking that appears in usual homogeneous isotropic situations or even in non-homogeneous cases developing small or large displacements. The use of parallel processing to improve the computational efficiency, allows employing high-order elements instead of low-order ones with reduced integration techniques or strain enhancements. The Green-Lagrange strain is adopted and the constitutive relation is the functionally graded Saint Venant-Kirchhoff law. The equilibrium is achieved by the minimum total potential energy principle. Examples of large displacement problems are presented and results confirm the locking free behavior of high-order elements for non-homogeneous materials. (C) 2011 Elsevier B.V. All rights reserved.

Combinatorial-topological framework for the analysis of global dynamics

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4767672]

A new portal for the analysis of human splicing variants

Understanding alternative splicing is crucial to elucidate the mechanisms behind several biological phenomena, including diseases. The huge amount of expressed sequences available nowadays represents an opportunity and a challenge to catalog and display alternative splicing events (ASEs). Although several groups have faced this challenge with relative success, we still lack a computational tool that uses a simple and straightforward method to retrieve, name and present ASEs. Here we present SPLOOCE, a portal for the analysis of human splicing variants. SPLOOCE uses a method based on regular expressions for retrieval of ASEs. We propose a simple syntax that is able to capture the complexity of ASEs.

Analysis of energetically biased transcripts of viruses and transposable elements

RNA interference (RNAi) is a natural endogenous process by which double-stranded RNA molecules trigger potent and specific gene silencing in eukaryotic cells and is characterized by target RNA cleavage. In mammals, small interfering RNAs (siRNAs) are the trigger molecules of choice and constitute a new class of RNA-based antiviral agents. In an efficient RNAi response, the antisense strand of siRNAs must enter the RNA-induced silencing complex (RISC) in a process mediated by thermodynamic features. In this report, we hypothesize that silent mutations capable of inverting thermodynamic properties can promote resistance to siRNAs. Extensive computational analyses were used to assess whether continuous selective pressure that promotes such mutations could lead to the emergence of viral strains completely resistant to RNAi (i.e., prone to transfer only the sense strands to RISC). Based on our findings, we propose that, although synonymous mutations may produce functional resistance, this strategy cannot be systematically adopted by viruses since the longest RNAi-refractory sequence is only 10 nt long. This finding also suggests that all mRNAs display fluctuating thermodynamic landscapes and that, in terms of thermodynamic features, RNAi is a very efficient antiviral system since there will always be sites susceptible to siRNAs.

Texture analysis of high resolution MRI allows discrimination between febrile and afebrile initial precipitating injury in mesial temporal sclerosis

A computational pipeline combining texture analysis and pattern classification algorithms was developed for investigating associations between high-resolution MRI features and histological data. This methodology was tested in the study of dentate gyrus images of sclerotic hippocampi resected from refractory epilepsy patients. Images were acquired using a simple surface coil in a 3.0T MRI scanner. All specimens were subsequently submitted to histological semiquantitative evaluation. The computational pipeline was applied for classifying pixels according to: a) dentate gyrus histological parameters and b) patients' febrile or afebrile initial precipitating insult history. The pipeline results for febrile and afebrile patients achieved 70% classification accuracy, with 78% sensitivity and 80% specificity [area under the reader observer characteristics (ROC) curve: 0.89]. The analysis of the histological data alone was not sufficient to achieve significant power to separate febrile and afebrile groups. Interesting enough, the results from our approach did not show significant correlation with histological parameters (which per se were not enough to classify patient groups). These results showed the potential of adding computational texture analysis together with classification methods for detecting subtle MRI signal differences, a method sufficient to provide good clinical classification. A wide range of applications of this pipeline can also be used in other areas of medical imaging. Magn Reson Med, 2012. (c) 2012 Wiley Periodicals, Inc.

The nature of Ru-NO bonds in ruthenium tetraazamacrocycle nitrosyl complexes-a computational study

Ruthenium complexes including nitrosyl or nitrite complexes are particularly interesting because they can not only scavenge but also release nitric oxide in a controlled manner, regulating the NO-level in vivo. The judicious choice of ligands attached to the [RuNO] core has been shown to be a suitable strategy to modulate NO reactivity in these complexes. In order to understand the influence of different equatorial ligands on the electronic structure of the Ru-NO chemical bonding, and thus on the reactivity of the coordinated NO, we propose an investigation of the nature of the Ru-NO chemical bond by means of energy decomposition analysis (EDA), considering tetraamine and tetraazamacrocycles as equatorial ligands, prior to and after the reduction of the {RuNO}(6) moiety by one electron. This investigation provides a deep insight into the Ru-NO bonding situation, which is fundamental in designing new ruthenium nitrosyl complexes with potential biological applications.

An in-depth analysis of the HIV-1/AIDS dynamics by comprehensive mathematical modeling

This work presents major results from a novel dynamic model intended to deterministically represent the complex relation between HIV-1 and the human immune system. The novel structure of the model extends previous work by representing different host anatomic compartments under a more in-depth cellular and molecular immunological phenomenology. Recently identified mechanisms related to HIV-1 infection as well as other well known relevant mechanisms typically ignored in mathematical models of HIV-1 pathogenesis and immunology, such as cell-cell transmission, are also addressed. (C) 2011 Elsevier Ltd. All rights reserved.

Can neuroimaging be used as a support to diagnosis of borderline personality disorder? An approach based on computational neuroanatomy and machine learning

Several recent studies in literature have identified brain morphological alterations associated to Borderline Personality Disorder (BPD) patients. These findings are reported by studies based on voxel-based-morphometry analysis of structural MRI data, comparing mean gray-matter concentration between groups of BPD patients and healthy controls. On the other hand, mean differences between groups are not informative about the discriminative value of neuroimaging data to predict the group of individual subjects. In this paper, we go beyond mean differences analyses, and explore to what extent individual BPD patients can be differentiated from controls (25 subjects in each group), using a combination of automated-morphometric tools for regional cortical thickness/volumetric estimation and Support Vector Machine classifier. The approach included a feature selection step in order to identify the regions containing most discriminative information. The accuracy of this classifier was evaluated using the leave-one-subject-out procedure. The brain regions indicated as containing relevant information to discriminate groups were the orbitofrontal, rostral anterior cingulate, posterior cingulate, middle temporal cortices, among others. These areas, which are distinctively involved in emotional and affect regulation of BPD patients, were the most informative regions to achieve both sensitivity and specificity values of 80% in SVM classification. The findings suggest that this new methodology can add clinical and potential diagnostic value to neuroimaging of psychiatric disorders. (C) 2012 Elsevier Ltd. All rights reserved.