Osteosarcoma Pathogenesis Leads the Way to New Target Treatments

Osteosarcoma (OS) is a rare condition with very poor prognosis in a metastatic setting. Basic research has enabled a better understanding of OS pathogenesis and the discovery of new potential therapeutic targets. Phase I and II clinical trials are already ongoing, with some promising results for these patients. This article reviews OS pathogenesis and new potential therapeutic targets.     

QoS metrics-in-the-loop for endowing runtime self-adaptation to robotic software architectures

Multimedia Tools and Applications - The design of robots capable of operating autonomously in changing and unstructured environments, requires using complex software architectures in which,...     

Nickel phosphonate MOF as efficient water splitting photocatalyst

A novel microporous two-dimensional(2D)Ni-based phosphonate metal-organic framework(MOF;denoted as IEF-13)has been successfully synthesized by a simple and green hydrothermal method and fully characterized using a combination of experimental and computational techniques.Structure resolution by single-crystal X-ray diffraction reveals that IEF-13 crystallizes in the triclinic space group Pi having bi-octahedra nickel nodes and a photo/electroactive tritopic phosphonate ligand.Remarkably,this material exhibits coordinatively unsaturated nickel(II)sites,free-P0₃H₂and-P0₃H acidic groups,a C0₂accessible microporosity,and an exceptional thermal and chemical stability.Further,its in-deep optoelectronic characterization evidences a photoresponse suitable for photocatalysis.In this sense,the photocatalytic activity for challenging H₂generation and overall water splitting in absence of any co-catalyst using UV-Vis irradiation and simulated sunlight has been evaluated,constituting the first report for a phosphonate-MOF photocatalyst.IEF-13 is able to produce up to 2,200 fimol of H₂per gram using methanol as sacrificial agent,exhibiting stability,maintaining its crystal structure and allowing its recycling.Even more,170μmol of H₂per gram were produced using IEF-13 as photocatalyst in the absence of any co-catalyst for the overall water splitting,being this reaction limited by the 0₂reduction.The present work opens new avenues for further optimization of the photocatalytic activity in this type of multifunctional materials.     

Extracellular Vesicles in CNS Developmental Disorders

The central nervous system (CNS) is the most complex structure in the body, consisting of multiple cell types with distinct morphology and function. Development of the neuronal circuit and its function rely on a continuous crosstalk between neurons and non-neural cells. It has been widely accepted that extracellular vesicles (EVs), mainly exosomes, are effective entities responsible for intercellular CNS communication. They contain membrane and cytoplasmic proteins, lipids, non-coding RNAs, microRNAs and mRNAs. Their cargo modulates gene and protein expression in recipient cells. Several lines of evidence indicate that EVs play a role in modifying signal transduction with subsequent physiological changes in neurogenesis, gliogenesis, synaptogenesis and network circuit formation and activity, as well as synaptic pruning and myelination. Several studies demonstrate that neural and non-neural EVs play an important role in physiological and pathological neurodevelopment. The present review discusses the role of EVs in various neurodevelopmental disorders and the prospects of using EVs as disease biomarkers and therapeutics.     

Preparation and characterization of chitosan‐based dispersions

Complexation of chitosan in aqueous solutions by low molecular weight electrolytes is one of the simplest methods for the preparation of aqueous chitosan dispersions. In this work, the influence of storage time, sulfate concentration, method of preparation and surfactant content on some properties of the resultant chitosan dispersions (turbidity, viscosity and zeta potential) was analyzed. Turbidimetry was adequate to monitor the formation of particles, while viscometry was suitable to monitor changes in the dispersing phase. An analysis of the properties of these systems, mainly in terms of particle–particle and macromolecule–macromolecule interactions was carried out. Copyright © 2004 Society of Chemical Industry     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

The Simulation of Impact Loads on Beam-type Structures using a Pseudo-dynamic Procedure

Abstract:  This study proposes an alternate method for the analysis of beams with solid cross-section or built as a framed structure and subjected to transverse impact loads from an external striker. The procedure used in the analysis is a combination of two essential tools using pseudo-dynamic techniques. The method reported here involves only one degree of freedom for the structure modelling and assumes an elastic contact between an external striker and the beam structure, which in reality does not happen. As only one degree of freedom is considered in the analysis, some important limitations are inherent to the method proposed here. Essentially, there is the difficulty of modelling the displacement field associated with the transient structure behaviour accurately, as a consequence of fast-rate impact loads. Another difficulty faced by the method refers to a local structure behaviour associated with contact loads. The present method can deal with large displacements in transversely loaded beams associated to a collapse mechanism having a simple geometry and defined with precision from a single parameter. This ensures reasonable accuracy in the evaluation of the strain energy absorbing capacity of transversely impacted beam structures using a single degree of freedom model in a pseudo-dynamic procedure.     

A note on the variance of rank-based selection strategies for genetic algorithms and genetic programming

This paper evaluates different forms of rank-based selection that are used with genetic algorithms and genetic programming. Many types of rank based selection have exactly the same expected value in terms of the sampling rate allocated to each member of the population. However, the variance associated with that sampling rate can vary depending on how selection is implemented. We examine two forms of tournament selection and compare these to linear rank-based selection using an explicit formula. Because selective pressure has a direct impact on population diversity, we also examine the interaction between selective pressure and different mutation strategies.     

The antimicrobial effect of wine on Listeria innocua in a model stomach system

A model stomach, containing a food matrix and a synthetic gastric fluid, was used to study the bactericidal effect of ingested wine on Listeria innocua. Volumes of wine equivalent to the ingestion of one glass and half a bottle, led, over a period of less than 2 h, to a reduction of 3 and 4 logarithmic cycles of the initial population respectively. The influence of ethanol and organic acids, wine constituents with known antimicrobial properties, was investigated. Ethanol exhibited a higher bactericidal effect than the mixture of the main wine organic acids. When testing the organic acids separately, malic and lactic acids were found to have the strongest effect. The combination of ethanol with the organic acids acted synergistically but to a lesser extent than wine itself. The results suggest that the ingestion of wine during a meal may diminish the quantity of Listeria persisting further in the alimentary tract.