Effect of Salmonella Typhimurium on the proteome of Pig Gut

Comunicaciones a congreso

Induced systemic resistance against Botrytis cinerea by Micromonospora strains isolated from root nodules

This article is part of the Research Topic: Harnessing useful rhizosphere microorganisms for pathogen and pest biocontrol.-- Edited by: Aurelio Ciancio, Corné M. J. Pieterse and Jesús Mercado-Blanco.Micromonospora is a Gram positive bacterium that can be isolated from nitrogen fixing nodules from healthy leguminous plants, where they could be beneficial to the plant. Their plant growth promoting activity in legume and non-legume plants has been previously demonstrated. The present study explores the ability of Micromonospora strains to control fungal pathogens and to stimulate plant immunity. Micromonospora strains isolated from surface sterilized nodules of alfalfa showed in vitro antifungal activity against several pathogenic fungi. Moreover, root inoculation of tomato plants with these Micromonospora strains effectively reduced leaf infection by the fungal pathogen Botrytis cinerea, despite spatial separation between both microorganisms. This induced systemic resistance, confirmed in different tomato cultivars, is long lasting. Gene expression analyses evidenced that Micromonospora stimulates the plant capacity to activate defense mechanisms upon pathogen attack. The defensive response of tomato plants inoculated with Micromonospora spp. differs from that of non-inoculated plants, showing a stronger induction of jasmonate-regulated defenses when the plant is challenged with a pathogen. The hypothesis of jasmonates playing a key role in this defense priming effect was confirmed using defense-impaired tomato mutants, since the JA-deficient line def1 was unable to display a long term induced resistance upon Micromonospora spp. inoculation. In conclusion, nodule isolated Micromonospora strains should be considered excellent candidates as biocontrol agents as they combine both direct antifungal activity against plant pathogens and the ability to prime plant immunity.This work was supported by MICINN Grant AGL2010-17380 and AGL-2012-39923. Fellowship from CSIC JAE-PREPeer reviewe

Expressing Measurement Uncertainty in OCL/UML Datatypes

Uncertainty is an inherent property of any measure or estimation performed in any physical setting, and therefore it needs to be considered when modeling systems that manage real data. Although several modeling languages permit the representation of measurement uncertainty for describing certain system attributes, these aspects are not normally incorporated into their type systems. Thus, operating with uncertain values and propagating uncertainty are normally cumbersome processes, di cult to achieve at the model level. This paper proposes an extension of OCL and UML datatypes to incorporate data uncertainty coming from physical measurements or user estimations into the models, along with the set of operations de ned for the values of these types.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Interpretable Spectral Variational AutoEncoder (ISVAE) for time series clustering

The best encoding is the one that is interpretable in nature. In this work, we introduce a novel model that incorporates an interpretable bottleneck-termed the Filter Bank (FB)-at the outset of a Variational Autoencoder (VAE). This arrangement compels the VAE to attend on the most informative segments of the input signal, fostering the learning of a novel encoding ${f_0}$ which boasts enhanced interpretability and clusterability over traditional latent spaces. By deliberately constraining the VAE with this FB, we intentionally constrict its capacity to access broad input domain information, promoting the development of an encoding that is discernible, separable, and of reduced dimensionality. The evolutionary learning trajectory of ${f_0}$ further manifests as a dynamic hierarchical tree, offering profound insights into cluster similarities. Additionally, for handling intricate data configurations, we propose a tailored decoder structure that is symmetrically aligned with FB's architecture. Empirical evaluations highlight the superior efficacy of ISVAE, which compares favorably to state-of-the-art results in clustering metrics across real-world datasets

Use and effectiveness of fly goalkeepers in european futsal

Using a fly goalkeeper (FG) is one of futsal´s most specific offensive strategy and gives leverage over the opponent to change the game''s final result. This study will analyze the goals obtained from the use of a FG and relate them to the score momentum variable and others in order to offer a better understanding and to establish if there are differences between main European futsal leagues. Sample made from all offensive situations that lead to a goal while using FG scheme (n=673) during 2014-2015 Spanish, Russian and Italian pro futsal leagues. Observational, nomothetic and multidimensional study. Statistical analysis using the SPSS vr 22 for inferential and descriptive statistics. Chi-square relation for cathegorical variables and Spearman''s Rho to establish non parametrical bi-varial correlations for ordinary variables, establishing significant differences p <0.05. FG strategy obtains 15.33% of the total goals. The league''s behaviour very similar, except in the Italian league, which scores more goals with their attack than against its defence, making differences between goals scored as local and visitor both in attack and defence

AIRPA: An Architecture to Support the Execution and Maintenance of AI-Powered RPA Robots

Robotic Process Automation (RPA) has quickly evolved from automating simple rule-based tasks. Nowadays, RPA is required to mimic more sophisticated human tasks, thus implying its combina tion with Artificial Intelligence (AI) technology, i.e., the so-called intelli gent RPA. Putting together RPA with AI leads to a challenging scenario since (1) it involves professionals from both fields who typically have different skills and backgrounds, and (2) AI models tend to degrade over time which affects the performance of the overall solution. This paper describes the AIRPA project, which addresses these challenges by proposing a software architecture that enables (1) the abstraction of the robot development from the AI development and (2) the monitor, con trol, and maintain intelligent RPA developments to ensure its quality and performance over time. The project has been conducted in the Serv inform context, a Spanish consultancy firm, and the proposed prototype has been validated with reality settings. The initial experiences yield promising results in reducing AHT (Average Handle Time) in processes where AIRPA deployed cognitive robots, which encourages exploring the support of intelligent RPA development.Ministerio de Ciencia, Innovación y Universidades PID2019-105455GB-C31Centro para el Desarrollo Tecnológico Industrial EXP00118029/IDI-20190524Centro para el Desarrollo Tecnológico Industrial P011-19/E0

Multidrug-Resistant Bacterial Foodborne Pathogens: Impact on Human Health and Economy

The drug abuse known to occur during growth of animals intended for food production, because of their use as either a prophylactic or therapeutic treatment, promotes the emergence of bacterial drug resistance. It has been reported that at least 25% of the foodborne isolates show drug resistance to one or more classes of antimicrobials (FAO 2018). There are diverse mechanisms that promote drug resistance. It is known that the use of sub-therapeutic doses of antibiotics in animals intended for food production promotes mutations of some chromosomal genes such as gyrA-parC and mphA, which are responsible for quinolone and azithromycin resistance, respectively. Also, the horizontal transfer of resistance genes as groups (“cassettes”) or plasmids makes the spread of resistance to different bacterial genera possible, among which there could be pathogens. The World Health Organization considers the emergence of multidrug-resistant pathogenic bacteria as a health problem, since the illnesses caused by them complicate the treatment and increase the morbidity and mortality rates. The complication in the illness treatment caused by a multidrug-resistant pathogen causes economic losses to patients for the payment of long stays in hospitals and also causes economic losses to companies due to the absenteeism of their workers