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.     

An Effective Software Pipelining Algorithm for Clustered Embedded VLIW Processors

This paper proposes a software pipelining framework, CALiBeR (ClusterAware Load Balancing Retiming Algorithm), suitable for compilers targetingclustered embedded VLIW processors. CALiBeR can be used by embedded systemdesigners to explore different code optimization alternatives, that is, high-qualitycustomized retiming solutions for desired throughput and program memory sizerequirements, while minimizing register pressure. An extensive set of experimentalresults is presented, demonstrating that our algorithm compares favorablywith one of the best state-of-the-art algorithms, achieving up to 50% improvementin performance and up to 47% improvement in register requirements. In orderto empirically assess the effectiveness of clustering for high ILP applications,additional experiments are presented contrasting the performance achievedby software pipelined kernels executing on clustered and on centralized machines.     

Sequential batch reactor for eucalypt kraft pulp effluent treatment with Trametes versicolor

BACKGROUND: A sequential batch reactor (SBR) was used for eucalypt kraft pulp effluent treatment with Trametes versicolor. A 2³ full factorial design and response surface methodology were applied to optimise the batch fermentation conditions. Effluent concentration, culture medium and inoculum age were the factors selected for this study in order to optimise the reduction of chemical oxygen demand (COD). RESULTS: The presence of Trametes Defined Medium (TDM) in the fermentation was required to obtain a significant COD reduction. Experiments in the batch reactor confirmed, in general, the predicted results of optimisation developed from Erlenmeyer batch assays. The T. versicolor culture remained active during 42 days of study in the SBR, providing approximately 80% of COD reduction. CONCLUSION: Trametes versicolor may be considered as very promising for the biological treatment of effluents from kraft pulp mills in an SBR system instead of the activated sludge mixed cultures traditionally used. Copyright © 2008 Society of Chemical Industry     

Do individual factors matter? A survey of scientists’ patenting in Portuguese public research organisations

This paper addresses scientists’ behaviour regarding the patenting of knowledge produced in universities and other public sector research organisations (PSROs). Recent years have witnessed a rapid growth in patenting and licensing activities by PSROs. We argue that the whole process depends to a certain extent on scientists’ willingness to disclose their inventions. Given this assumption, we conduct research into individual behaviour in order to understand scientists’ views concerning the patenting of their research results. Data from a questionnaire survey of Portuguese researchers from nine PSROs in life sciences and biotechnology is presented and analysed and complemented with in-depth interviews. The results reveal that overall the scientists surveyed show a low propensity to become involved in patenting and licensing activities, despite the fact that the majority had no “ethical” objections to the disclosure of their inventions and the commercial exploitation of these. Perceptions about the impacts of these activities on certain fundamental aspects of knowledge production and dissemination are however divergent. This may account for the low participation levels. Furthermore, most scientists perceived the personal benefits deriving from this type of activity to be low. Similarly, the majority also believed that there are many difficulties associated with the patenting process and that they receive limited support from their organisations, which lack the proper competences and structures to assist with patenting and licensing.     

Microstructural modeling approach applied to rock material

The importance of the microstructural parameters in rock mechanical behavior has been investigated by several authors. Moreover, the Weibull statistical model has been used to characterize the heterogeneity of several materials on the basis of the concept that the microscopic defects within the material determine their mechanical strength. The modeling of different rocks is a topic that is fundamental for the prediction of rock fragmentation. In this article, the analysis of rock microstructure is performed using the microstructural modeling approach, which consists of the simplification, quantification, and modeling of the main properties of rock microstructure. The grain size, grain shape, and microcracks are modeled by means of statistical density functions, namely, Cauchy, chi-squared, exponential, extreme value, gamma, Laplace, normal, uniform, and Weibull. It is found that the Weibull distribution is the most appropriate statistical model of the grain size and grain shape, when compared with the other eight statistical models. Regarding microcracks, the results show that the gamma distribution is the most appropriate model. The Weibull and gamma distributions are then used to analyze the heterogeneity of the microstructure. This is done by comparison of the statistical models of each microstructural property evaluated in several thin sections of the same rock. It is found that with respect to grain size and grain shape, the rock is homogeneous, while the size distribution of the microcracks shows a clear trend toward less homogeneity. The microstructural modeling approach is important for modeling, characterizing, and analyzing the microstructure of rock material. Among other applications, it can be used to explain differences in the mechanical behavior obtained in testing several specimens.     

Calibration Model for Water Distribution Network Using Pressures Estimated by Artificial Neural Networks

The success of hydraulic simulation models of water distribution networks is associated with the ability of these models to represent real systems accurately. To achieve this, the calibration phase is essential. Current calibration methods are based on minimizing the error between measured and simulated values of pressure and flow. This minimization is based on a search of parameter values to be calibrated, including pipe roughness, nodal demand, and leakage flow. The resulting hydraulic problem contains several variables. In addition, a limited set of known monitored pressure and flow values creates an indeterminate problem with more variables than equations. Seeking to address the lack of monitored data for the calibration of Water Distribution Networks (WDNs), this paper uses a meta-model based on an Artificial Neural Network (ANN) to estimate pressure on all nodes of a network. The calibration of pipe roughness applies a metaheuristic search method called Particle Swarm Optimization (PSO) to minimize the objective function represented by the difference between simulated and forecasted pressure values. The proposed method is evaluated at steady state and over an extended period for a real District Metering Area (DMA), named Campos do Conde II, and the hypothetical network named C-town, which is used as a benchmark for calibration studies.     

A Review of Element-Based Galerkin Methods for Numerical Weather Prediction: Finite Elements,Spectral Elements,and Discontinuous Galerkin

Numerical weather prediction (NWP) is in a period of transition. As resolutions increase, global models are moving towards fully nonhydrostatic dynamical cores, with the local and global models using the same governing equations; therefore we have reached a point where it will be necessary to use a single model for both applications. The new dynamical cores at the heart of these unified models are designed to scale efficiently on clusters with hundreds of thousands or even millions of CPU cores and GPUs. Operational and research NWP codes currently use a wide range of numerical methods: finite differences, spectral transform, finite volumes and, increasingly, finite/spectral elements and discontinuous Galerkin, which constitute element-based Galerkin (EBG) methods. Due to their important role in this transition, will EBGs be the dominant power behind NWP in the next 10 years, or will they just be one of many methods to choose from? One decade after the review of numerical methods for atmospheric modeling by Steppeler et al. (Meteorol Atmos Phys 82:287–301, 2003), this review discusses EBG methods as a viable numerical approach for the next-generation NWP models. One well-known weakness of EBG methods is the generation of unphysical oscillations in advection-dominated flows; special attention is hence devoted to dissipation-based stabilization methods. Since EBGs are geometrically flexible and allow both conforming and non-conforming meshes, as well as grid adaptivity, this review is concluded with a short overview of how mesh generation and dynamic mesh refinement are becoming as important for atmospheric modeling as they have been for engineering applications for many years.     

Impact of white-matter mask selection on DTI histogram-based metrics as potential biomarkers in cerebral small vessel disease

Magnetic Resonance Materials in Physics, Biology and Medicine - Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small...     

Impact assessment of odours emitted by a wastewater treatment plant

Complaints from the Domingos Martins population about sewage odours in the city made the district attorney order an impact assessment of the odours emitted by the city wastewater treatment plant (WWTP). This study comprised various techniques, models and population surveys. In 2007, an odour emission model proved that the main hydrogen sulphide emitter was the aeration tank of the WWTP (13.5 g h(-1)) and such emissions, according to CALPUFF model, should be perceived in the whole Domingos Martins city centre area. In this area, 58% of those interviewed were annoyed by the WWTP odours. However, in 2009, the odour monitoring panel recorded few odour occurrences. A second population survey showed that hereafter only 20% of those interviewed were annoyed by the WWTP emissions. Odour emission and dispersion models run with 2010 data proved a drastic reduction of the WWTP aeration tank emissions and consequently the city centre was not bothered by WWTP emissions anymore. The odour emission reduction was due to the modification of the WWTP aeration tank system. Despite the odour emission reduction, houses located southeast of the WWTP were still annoyed by sewage odours. However, in this part of the town, other sources of sewage odours have been found.     

Chitosan amphiphiles provide new drug delivery opportunities

Chitosan, an acid soluble and renewable biopolymer, was first studied as a drug delivery agent in 1990. This review focuses on the relatively newer self‐assembling chitosan amphiphiles and their use as drug delivery agents. Chitosan amphiphiles, first introduced in the late 1990s, are prepared by conjugating hydrophobic and sometimes additional hydrophilic units to chitosan. These amphiphiles self‐assemble in aqueous media at neutral pH to form micelles, with critical micellar concentrations (CMCs) ranging from 0.09 to 700 µg mL^?1. The CMCs depend on the actual molecular architecture, molecular weight and hydrophobic character, but are typically lower than the values reported for block copolymer amphiphiles. As well as linear amphiphiles in which chitosan is derivatised with hydrophobic pendant groups, new claw amphiphiles have been prepared in which chitosan amphiphiles radiate geometrically from a dendrimer core. These chitosan amphiphiles (linear and claw) have been exploited as drug delivery agents and they increase the oral bioavailability of hydrophobic drugs up to sixfold, deliver hydrophobic drugs to tumours, genes to the liver via the intravenous route, genes to the muscle via the intramuscular routes and small interfering RNAs to tumours via the intratumoural route. Chitosan amphiphile nanoparticles also deliver peptides to the brain via the intravenous and oral routes. © 2014 Society of Chemical Industry