Spanish Melon Landraces: Revealing Useful Diversity by Genomic,Morphological, and Metabolomic Analysis

Spain is a secondary centre of the diversification of the melon (Cucumis melo L.), with high diversity represented in highly appreciated landraces belonging to the Flexuosus and Ibericus groups. A collection of 47 accessions of Flexuosus, Chate, Piel de Sapo, Tendral, Amarillo, Blanco, and Rochet was analysed using a genotyping-by-sequencing (GBS) approach. A total of 66,971 quality SNPs were identified. Genetic analysis differentiated Ibericus accessions and exotic materials (Ameri, Momordica, Kachri, and Agrestis), while Flexuous accessions shared ancestry between them. Within the Ibericus group, no clear genomic distinction could be identified for the different landraces evaluated, with accessions of different landraces showing high genetic similarity. The morphological characterization confirmed that the external colour and fruit shape had been used as recognition patterns for Spanish melon landraces, but variability within a landrace exists. Differences were found in the sugars and acid and volatile profiles of the materials. Flexuosus and Chate melons at the immature commercial stage accumulated malic acid and low levels of hexoses, while Ibericus melons accumulated high contents of sucrose and citric acid. Specific trends could be identified in the Ibericus landraces. Tendral accumulated low levels of sugars and citric acid and high of malic acid, maintaining higher firmness, Rochet reached higher levels of sugars, and Amarillo tended to lower malic acid contents. Interestingly, high variability was found within landraces for the acidic profile, offering possibilities to alter taste tinges. The main volatile organic compounds (VOCs) in Flexuosus and Chate were aldehydes and alcohols, with clear differences between both groups. In the Ibericus landraces, general trends for VOC accumulation could be identified, but, again, a high level of variation exists. This situation highlights the necessity to develop depuration programs to promote on-farm in situ conservation and, at the same time, offers opportunities to establish new breeding program targets and to take advantage of these sources of variation.     

Effects of the Treatment with Flavonoids on Metabolic Syndrome Components in Humans: A Systematic Review Focusing on Mechanisms of Action

Diets high in bioactive compounds, such as polyphenols, have been used to mitigate metabolic syndrome (MetS). Polyphenols are a large group of naturally occurring bioactive compounds, classified into two main classes: non-flavonoids and flavonoids. Flavonoids are distributed in foods, such as fruits, vegetables, tea, red wine, and cocoa. Studies have already demonstrated the benefits of flavonoids on the cardiovascular and nervous systems, as well as cancer cells. The present review summarizes the results of clinical studies that evaluated the effects of flavonoids on the components of the MetS and associated complications when offered as supplements over the long term. The results show that flavonoids can significantly modulate several metabolic parameters, such as lipid profile, blood pressure, and blood glucose. Only theaflavin and catechin were unable to affect metabolic parameters. Moreover, only body weight and body mass index were unaltered. Thus, the evidence presented in this systematic review offers bases in support of a flavonoid supplementation, held for at least 3 weeks, as a strategy to improve several metabolic parameters and, consequently, reduce the risk of diseases associated with MetS. This fact becomes stronger due to the rare side effects reported with flavonoids.     

Exploring networks with traceroute-like probes: Theory and simulations

Mapping the Internet generally consists in sampling the network from a limited set of sources by using traceroute-like probes. This methodology, akin to the merging of different spanning trees to a set of destination, has been argued to introduce uncontrolled sampling biases that might produce statistical properties of the sampled graph which sharply differ from the original ones. In this paper, we explore these biases and provide a statistical analysis of their origin. We derive an analytical approximation for the probability of edge and vertex detection that exploits the role of the number of sources and targets and allows us to relate the global topological properties of the underlying network with the statistical accuracy of the sampled graph. In particular, we find that the edge and vertex detection probability depends on the betweenness centrality of each element. This allows us to show that shortest path routed sampling provides a better characterization of underlying graphs with broad distributions of connectivity. We complement the analytical discussion with a throughout numerical investigation of simulated mapping strategies in network models with different topologies. We show that sampled graphs provide a fair qualitative characterization of the statistical properties of the original networks in a fair range of different strategies and exploration parameters. Moreover, we characterize the level of redundancy and completeness of the exploration process as a function of the topological properties of the network. Finally, we study numerically how the fraction of vertices and edges discovered in the sampled graph depends on the particular deployements of probing sources. The results might hint the steps toward more efficient mapping strategies.     

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.     

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.     

Self-adaptive systems: A survey of current approaches,research challenges and applications

Self-adaptive software is capable of evaluating and changing its own behavior, whenever the evaluation shows that the software is not accomplishing what it was intended to do, or when better functionality or performance may be possible. The topic of system adaptivity has been widely studied since the mid-60s and, over the past decade, several application areas and technologies relating to self-adaptivity have assumed greater importance. In all these initiatives, software has become the common element that introduces self-adaptability. Thus, the investigation of systematic software engineering approaches is necessary, in order to develop self-adaptive systems that may ideally be applied across multiple domains. The main goal of this study is to review recent progress on self-adaptivity from the standpoint of computer sciences and cybernetics, based on the analysis of state-of-the-art approaches reported in the literature. This review provides an over-arching, integrated view of computer science and software engineering foundations. Moreover, various methods and techniques currently applied in the design of self-adaptive systems are analyzed, as well as some European research initiatives and projects. Finally, the main bottlenecks for the effective application of self-adaptive technology, as well as a set of key research issues on this topic, are precisely identified, in order to overcome current constraints on the effective application of self-adaptivity in its emerging areas of application.     

A parallel evolutionary algorithm for technical market indicators optimization

This paper deals with the optimization of parameters of technical indicators for stock market investment. Price prediction is a problem of great complexity and, usually, some technical indicators are used to predict market trends. The main difficulty in using technical indicators lies in deciding a set of parameter values. We proposed the use of Multi-Objective Evolutionary Algorithms (MOEAs) to obtain the best parameter values belonging to a collection of indicators that will help in the buying and selling of shares. The experimental results indicate that our MOEA offers a solution to the problem by obtaining results that improve those obtained through technical indicators with standard parameters. In order to reduce execution time is necessary to parallelize the executions. Parallelization results show that distributing the workload of indicators in multiple processors to improve performance is recommended. This parallelization has been performed taking advantage of the idle time in a corporate technology infrastructure. We have configured a small parallel grid using the students Labs of a Computer Science University College.