In Vitro Assays to Identify Metabolism-Disrupting Chemicals with Diabetogenic Activity in a Human Pancreatic β-Cell Model

There is a need to develop identification tests for Metabolism Disrupting Chemicals (MDCs) with diabetogenic activity. Here we used the human EndoC-βH1 β-cell line, the rat β-cell line INS-1E and dispersed mouse islet cells to assess the effects of endocrine disruptors on cell viability and glucose-stimulated insulin secretion (GSIS). We tested six chemicals at concentrations within human exposure (from 0.1 pM to 1 µM). Bisphenol-A (BPA) and tributyltin (TBT) were used as controls while four other chemicals, namely perfluorooctanoic acid (PFOA), triphenylphosphate (TPP), triclosan (TCS) and dichlorodiphenyldichloroethylene (DDE), were used as “unknowns”. Regarding cell viability, BPA and TBT increased cell death as previously observed. Their mode of action involved the activation of estrogen receptors and PPARγ, respectively. ROS production was a consistent key event in BPA-and TBT-treated cells. None of the other MDCs tested modified viability or ROS production. Concerning GSIS, TBT increased insulin secretion while BPA produced no effects. PFOA decreased GSIS, suggesting that this chemical could be a “new” diabetogenic agent. Our results indicate that the EndoC-βH1 cell line is a suitable human β-cell model for testing diabetogenic MDCs. Optimization of the test methods proposed here could be incorporated into a set of protocols for the identification of MDCs.     

Polymerizable Skin Hydrogel for Full Thickness Wound Healing

The skin is the largest organ in the human body, comprising the main barrier against the environment. When the skin loses its integrity, it is critical to replace it to prevent water loss and the proliferation of opportunistic infections. For more than 40 years, tissue-engineered skin grafts have been based on the in vitro culture of keratinocytes over different scaffolds, requiring between 3 to 4 weeks of tissue culture before being used clinically. In this study, we describe the development of a polymerizable skin hydrogel consisting of keratinocytes and fibroblast entrapped within a fibrin scaffold. We histologically characterized the construct and evaluated its use on an in vivo wound healing model of skin damage. Our results indicate that the proposed methodology can be used to effectively regenerate skin wounds, avoiding the secondary in vitro culture steps and thus, shortening the time needed until transplantation in comparison with other bilayer skin models. This is achievable due to the instant polymerization of the keratinocytes and fibroblast combination that allows a direct application on the wound. We suggest that the polymerizable skin hydrogel is an inexpensive, easy and rapid treatment that could be transferred into clinical practice in order to improve the treatment of skin wounds.     

A viral system algorithm to optimize the car dispatching in elevator group control systems of tall buildings

Nowadays is very common the presence of tall buildings in the business centres of the main cities of the world. Such buildings require the installation of numerous lifts that are coordinated and managed under a unique control system. Population working in the buildings follows a similar traffic pattern generating situations of traffic congestion. The problem arises when a passenger makes a hall call wishing to travel to another floor of the building. The dispatching of the most suitable car is the optimization problem we are tackling in this paper. We develop a viral system algorithm which is based on a bio-inspired virus infection analogy to deal with it. The viral system algorithm is compared to genetic algorithms, and tabu search approaches that have proven efficiency in the vertical transportation literature. The experiments undertaken in tall buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars, provide valuable results and show how viral system outperforms such soft computing algorithms.     

From latex specifications to parallel codes

The advent of multicore systems, joined to the potential acceleration of the graphics processing units, has given us a low cost computation capability unprecedented. The new systems alleviate some well-known important architectural problems at the expense of a considerable increment of the programmability wall. Heterogeneity, at both the architectural and programming levels, poses a great challenge to programmers. As a contribution, we propose a development methodology for the automatic source-to-source transformation on specific domains. This methodology is successfully instantiated as a framework to solve Dynamic Programming problems. As a result of applying our framework, the end user (a physicist, a mathematician or a biologist) can express her problem through a latex equation and automatically derive efficient parallel codes for current homogeneous or heterogeneous architectures. The approach allows an easy portability to new emergent architectures.     

‘Long autonomy or long delay?’ The importance of domain in opinion mining

Nowadays, people do not only navigate the web, but they also contribute contents to the Internet. Among other things, they write their thoughts and opinions in review sites, forums, social networks, blogs and other websites. These opinions constitute a valuable resource for businesses, governments and consumers. In the last years, some researchers have proposed opinion extraction systems, mostly domain-independent ones, to automatically extract structured representations of opinions contained in those texts. In this work, we tackle this task in a domain-oriented approach, defining a set of domain-specific resources which capture valuable knowledge about how people express opinions on a given domain. These resources are automatically induced from a set of annotated documents. Some experiments were carried out on three different domains (user-generated reviews of headphones, hotels and cars), comparing our approach to other state-of-the-art, domain-independent techniques. The results confirm the importance of the domain in order to build accurate opinion extraction systems. Some experiments on the influence of the dataset size and an example of aggregation and visualization of the extracted opinions are also shown.     

A semantic role labelling-based framework for learning ontologies from Spanish documents

Currently, most of the information available in the Web is adapted primarily for human consumption, but there is so much information that can no longer be processed by a person in a reasonable time, either in digital or physical formats. To solve this problem, the idea of the Semantic Web arose. The Semantic Web deals with adding machine-readable information to Web pages. Ontologies represent a very important element of this web, as they provide a valid and robust structure to represent knowledge based on concepts, relations, axioms, etc. The need for overcoming the bottleneck provoked by the manual construction of ontologies has generated several studies and research on obtaining semiautomatic methods to learn ontologies. In this sense, this paper proposes a new ontology learning methodology based on semantic role labeling from digital Spanish documents. The method makes it possible to represent multiple semantic relations specially taxonomic and partonomic ones in the standardized OWL 2.0. A set of experiments has been performed with the approach implemented in educational domain that show promising results.     

Error evaluation on experimental stress–strain curve obtained from tube bulging test

To get precise material data for advanced numerical modelling of tube hydroforming process, the tube bulging test is recommended. Stresses and strains in the tube cannot be evaluated easily and several approaches have been proposed. A review is proposed and points out their advantages and drawbacks.     

Salt Concentration Effects in Planar Light‐Emitting Electrochemical Cells

Incorporation of ions in the active layer of organic semiconductor devices may lead to attractive device properties like enhanced injection and improved carrier transport. In this paper, we investigate the effect of the salt concentration on the operation of light‐emitting electrochemical cells, using experiments and numerical calculations. The current density and light emission are shown to increase linearly with increasing ion concentration over a wide range of concentrations. The increasing current is accompanied by an ion redistribution, leading to a narrowing of the recombination zone. Hence, in absence of detrimental side reactions and doping‐related luminescence quenching, the ion concentration should be as high as possible.