The extradomain a of fibronectin enhances the efficacy of lipopolysaccharide defective Salmonella bacterins as vaccines in mice

The Extradomain A from fibronectin (EDA) has an immunomodulatory role as fusion protein with viral and tumor antigens, but its effect when administered with bacteria has not been assessed. Here, we investigated the adjuvant effect of EDA in mice immunizations against Salmonella enterica subspecies enterica serovar Enteritidis (Salmonella Enteritidis). Since lipopolysaccharide (LPS) is a major virulence factor and the LPS O-polysaccharide (O-PS) is the immunodominant antigen in serological diagnostic tests, Salmonella mutants lacking O-PS (rough mutants) represent an interesting approach for developing new vaccines and diagnostic tests to differentiate infected and vaccinated animals (DIVA tests). Here, antigenic preparations (hot-saline extracts and formalin-inactivated bacterins) from two Salmonella Enteritidis rough mutants, carrying either intact (SE Delta waaL) or deep-defective (SE Delta gal) LPS-Core, were used in combination with EDA. Biotinylated bacterins, in particular SE Delta waaL bacterin, decorated with EDAvidin (EDA and streptavidin fusion protein) improved the protection conferred by hot-saline or bacterins alone and prevented significantly the virulent infection at least to the levels of live attenuated rough mutants. These findings demonstrate the adjuvant effect of EDAvidin when administered with biotinylated bacterins from Salmonella Enteritidis lacking O-PS and the usefulness of BEDA-SE Delta waaL as non-live vaccine in the mouse model.

A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models

This paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point detection and for orientation map extraction. Then, we focus on the different learning models considered to build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction, singular point detection, orientation extraction and learning methods are presented. A critical view of the existing literature have led us to present a discussion on the existing methods and their drawbacks such as difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On this account, an experimental analysis of the most relevant methods is carried out in the second part of this paper, and a new method based on their combination is presented.

A survey of fingerprint classification Part II: experimental analysis and ensemble proposal

In the first part of this paper we reviewed the fingerprint classification literature from two different perspectives: the feature extraction and the classifier learning. Aiming at answering the question of which among the reviewed methods would perform better in a real implementation we end up in a discussion which showed the difficulty in answering this question. No previous comparison exists in the literature and comparisons among papers are done with different experimental frameworks. Moreover, the difficulty in implementing published methods was stated due to the lack of details in their description, parameters and the fact that no source code is shared. For this reason, in this paper we will go through a deep experimental study following the proposed double perspective. In order to do so, we have carefully implemented some of the most relevant feature extraction methods according to the explanations found in the corresponding papers and we have tested their performance with different classifiers, including those specific proposals made by the authors. Our aim is to develop an objective experimental study in a common framework, which has not been done before and which can serve as a baseline for future works on the topic. This way, we will not only test their quality, but their reusability by other researchers and will be able to indicate which proposals could be considered for future developments. Furthermore, we will show that combining different feature extraction models in an ensemble can lead to a superior performance, significantly increasing the results obtained by individual models.

La economía solidaria como movimiento social: el caso de REAS-Navarra

El estudio determina las características de la Economía Solidaria, desde la perspectiva de los movimientos sociales, en el marco del análisis de las auditorías de REASNavarra. Se contextualizan mediante revisión bibliográfica las características, tanto de la Economía Social y Solidaria (ESS) como de la Economía Social, y se contrasta con el caso particular de Navarra (España). Para el análisis de dichas auditorías se utilizó un enfoque metodológico longitudinal, resultando del mismo una “foto” representativa del comportamiento de las empresas de REAS-Navarra a lo largo de los años (2009, 2011 y 2013). El estudio concluye que REAS-Navarra, si bien cumple con criterios defendidos desde la Economía Solidaria, presenta debilidades en cuanto a la metodología utilizada para auditar sus empresas, y de los resultados del análisis de las auditorías sociales se desprenden dudas respecto al nivel de autonomía y democracia en estas empresas, lo que puede significar un riesgo para su continuidad.

Plan de marketing Berlys

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