Influence of Early Bilingual Exposure in the Developing Human Brain.

190 p.La adquisición del lenguaje es un proceso que ese encuentra determinado tanto por mecanismos de desarrollo cognitivo, como por la experiencia lingüística durante los primeros años de vida. Aunque se trata de un proceso relativamente complejo, los bebés muestran una gran habilidad para el aprendizaje del lenguaje. Un entorno de aprendizaje lingüístico bilingüe podría considerarse aun más complejo, ya que los bebés están expuestos a las características lingüísticas de dos lenguas simultáneamente. En primer lugar, los bebés que crecen en un entorno bilingüe tienen que ser capaces de darse cuenta de que están expuestos a dos lenguas diferentes, y posteriormente deben separar y aprender las características especificas de cada una de ellas; por ejemplo, los distintos fonemas, palabras o estructuras gramaticales. Aunque la exposición lingüística total de los bebés bilingües debería ser comparable a la de los bebés monolingües, es probable que la exposición a cada una de las lenguas de su entorno sea menor, ya que tienen que dividir su tiempo de exposición entre ambas. Si bien los bebés bilingües parecen no tener problemas para enfrentarse a un contexto de aprendizaje potencialmente más complejo, ya que alcanzan las distintas etapas de adquisición del lenguaje a un ritmo similar a los bebés monolingües, sí se han observado adaptaciones a nivel conductual y a nivel de funcionamiento cerebral que podrían producirse como consecuencia de este contexto.Basque Center on cognition, brain and languag

Influence of Early Bilingual Exposure in the Developing Human Brain.

190 p.La adquisición del lenguaje es un proceso que ese encuentra determinado tanto por mecanismos de desarrollo cognitivo, como por la experiencia lingüística durante los primeros años de vida. Aunque se trata de un proceso relativamente complejo, los bebés muestran una gran habilidad para el aprendizaje del lenguaje. Un entorno de aprendizaje lingüístico bilingüe podría considerarse aun más complejo, ya que los bebés están expuestos a las características lingüísticas de dos lenguas simultáneamente. En primer lugar, los bebés que crecen en un entorno bilingüe tienen que ser capaces de darse cuenta de que están expuestos a dos lenguas diferentes, y posteriormente deben separar y aprender las características especificas de cada una de ellas; por ejemplo, los distintos fonemas, palabras o estructuras gramaticales. Aunque la exposición lingüística total de los bebés bilingües debería ser comparable a la de los bebés monolingües, es probable que la exposición a cada una de las lenguas de su entorno sea menor, ya que tienen que dividir su tiempo de exposición entre ambas. Si bien los bebés bilingües parecen no tener problemas para enfrentarse a un contexto de aprendizaje potencialmente más complejo, ya que alcanzan las distintas etapas de adquisición del lenguaje a un ritmo similar a los bebés monolingües, sí se han observado adaptaciones a nivel conductual y a nivel de funcionamiento cerebral que podrían producirse como consecuencia de este contexto.Basque Center on cognition, brain and languag

Effect of Industry 4.0 on Education Systems: An Outlook

Congreso Universitario de Innovación Educativa En las Enseñanzas Técnicas, CUIEET (26º. 2018. Gijón

Effect of prewhitening in resting-state functional near-infrared spectroscopy data

Published: 24 October 2018Near-infrared spectroscopy (NIRS) offers the potential to characterize resting-state functional connectivity (RSFC) in populations that are not easily assessed otherwise, such as young infants. In addition to the advantages of NIRS, one should also consider that the RS-NIRS signal requires specific data preprocessing and analysis. In particular, the RS-NIRS signal shows a colored frequency spectrum, which can be observed as temporal autocorrelation, thereby introducing spurious correlations. To address this issue, prewhitening of the RS-NIRS signal has been recently proposed as a necessary step to remove the signal temporal autocorrelation and therefore reduce false-discovery rates. However, the impact of this step on the analysis of experimental RS-NIRS data has not been thoroughly assessed prior to the present study. Here, the results of a standard preprocessing pipeline in a RS-NIRS dataset acquired in infants are compared with the results after incorporating two different prewhitening algorithms. Our results with a standard preprocessing replicated previous studies. Prewhitening altered RSFC patterns and disrupted the antiphase relationship between oxyhemoglobin and deoxyhemoglobin. We conclude that a better understanding of the effect of prewhitening on RS-NIRS data is still needed before directly considering its incorporation to the standard preprocessing pipeline.This research was possible due to the support of the Basque Government predoctoral grant PRE_2016_2_0188 to Borja Blanco, as well as the support of the Spanish Ministry of Economy and Competitiveness through the project PSI 2014-54512-P, Juan de la Cierva Fellowship (IJCI-2014-20821) and the “Severo Ochoa” Programme for Centres/Units of Excellence in R & D (SEV-2015-490)

SeSo-GEO : e-learning apoyado por la web semántica y social : herramienta de gestión de exámenes on-line

La educación a distancia, o e-learning, se ha convertido en los últimos años, en una de las grandes alternativas a la educación presencial tradicional. Este hecho, ha provocado la proliferación de diversos sistemas de evaluación en línea que se han ido desarrollando conjuntamente con los propios sistemas e-learning. Paralelamente al concepto e-learning, han surgido y se han ido formando otros conceptos innovadores entorno a la Web, que han sido bautizados como “Web Social” y “Web Semántica” respectivamente. El presente proyecto, expone un sistema de evaluación de contenidos, en el cual se han aplicado sendos conceptos. Así, SeSo-GEO es una herramienta capaz de generar y compartir a través de búsquedas semánticas, un conocimiento entre distintas plataformas centradas en la enseñanza asistida por ordenador.Ingeniería en Informátic

P4P: a peptidome-based strain-level genome comparison web tool

Peptidome similarity analysis enables researchers to gain insights into differential peptide profiles, providing a robust tool to discriminate strain-specific peptides, true intra-species differences among biological replicates or even microorganism-phenotype variations. However, no in silico peptide fingerprinting software existed to facilitate such phylogeny inference. Hence, we developed the Peptidomes for Phylogenies (P4P) web tool, which enables the survey of similarities between microbial proteomes and simplifies the process of obtaining new biological insights into their phylogeny. P4P can be used to analyze different peptide datasets, i.e. bacteria, viruses, eukaryotic species or even metaproteomes. Also, it is able to work with whole proteome datasets and experimental mass-to-charge lists originated from mass spectrometers. The ultimate aim is to generate a valid and manageable list of peptides that have phylogenetic signal and are potentially sample-specific. Sample-to-sample comparison is based on a consensus peak set matrix, which can be further submitted to phylogenetic analysis. P4P holds great potential for improving phylogenetic analyses in challenging taxonomic groups, biomarker identification or epidemiologic studies. Notably, P4P can be of interest for applications handling large proteomic datasets, which it is able to reduce to small matrices while maintaining high phylogenetic resolution. The web server is available at http://sing-group.org/p4p.Spanish ‘Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad’ [AGL2013-44039R]; Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020[POCI-01-0145-FEDER-006684];INOU16-05project from the University of Vigo; Fundación AECC. Funding for open access charge: Spanish ‘Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad’ [AGL2013-44039R].info:eu-repo/semantics/publishedVersio

In silico prediction reveals the existence of potential bioactive neuropeptides produced by the human gut microbiota

This work reports on a large-scale potential neuropeptide activity screening in human gut microbiomes deposited in public databases. In our experimental approach, the sequences of the bioactive peptides collected in the MAHMI database, mainly predicted as immunomodulatory or antitumoral, were crossed with those of the neuroactive/digestive peptides. From 91,325,790 potential bioactive peptides, only 581 returned a match when crossed against the 5949 neuroactive peptides from the NeuroPep database and the 15 digestive hormones. Relevant bacterial taxa, such as Ruminococcus sp., Clostridium sp. were found among the main producers of the matching sequences, and many of the matches corresponded to adiponectin and the hormone produced by adipocites, which is involved in glucose homeostasis. These results show, for the first time, the presence of potentially bioactive peptides produced by gut microbiota members over the nervous cells, most notably, peptides with already predicted immunomodulatory or anti-inflammatory activity. Classical (Lactobacillus sp.) and next-generation (Faecalibacterium sp.) probiotics are shown to produce these peptides, which are proposed as a potential mechanism of action of psychobiotics. Our previous experimental results showed that many of these peptides were active when incubated with immune cells, such as dendritic cells, so their effect over the nervous system innervating the gut mucosa holds significant potential and should be explored.Spanish “Programa Estatal de Investigación, Desarrollo e Inovación Orientada a los Retos de la Sociedad” (Grant AGL2016-78311-R); the Asociación Española Contra el Cancer (“Obtención de péptidos bioactivos contra el Cáncer Colo-Rectal a partir de secuencias genéticas de microbiomas intestinales”, grant PS-2016). This study was also supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER006684). SING group thanks CITI (Centro de Investigación, Transferencia e Innovación) from University of Vigo for hosting its IT infrastructure. This work was partially supported by the Asturias Regional Plan I+D+i for research groups (FYCYT-IDI/2018/000236) and by the Consellería de Educación, Universidades e Formación Profesional (Xunta de Galicia) under the scope of the strategic funding of ED431C2018/55-GRC Competitive Reference Groupinfo:eu-repo/semantics/publishedVersio

Computational prediction of the bioactivity potential of proteomes based on expert knowledge

Advances in the field of genome sequencing have enabled a comprehensive analysis and annotation of the dynamics of the protein inventory of cells. This has been proven particularly rewarding for microbial cells, for which the majority of proteins are already accessible to analysis through automatic metagenome annotation. The large-scale in silico screening of proteomes and metaproteomes is key to uncover bioactivities of translational, clinical and biotechnological interest, and to help assign functions to certain proteins, such as those predicted as hypothetical. This work introduces a new method for the prediction of the bioactivity potential of proteomes/metaproteomes, supporting the discovery of functionally relevant proteins based on prior knowledge. This methodology complements functional annotation enrichment methods by allowing the assignment of functions to proteins annotated as hypothetical/putative/uncharacterised, as well as and enabling the detection of specific bioactivities and the recovery of proteins from defined taxa. This work shows how the new method can be applied to screen proteome and metaproteome sets to obtain predictions of clinical or biotechnological interest based on reference datasets. Notably, with this methodology, the large information files obtained after DNA sequencing or protein identification experiments can be associated for translational purposes that, in cases such as antibiotic-resistance pathogens or foodborne diseases, may represent changes in how these important and global health burdens are approached in the clinical practice. Finally, the Sequence-based Expert-driven pRoteome bioactivity Prediction EnvironmENT, a public Web service implemented in Scala functional programming style, is introduced as means to ensure broad access to the method as well as to discuss main implementation issues, such as modularity, extensibility and interoperability.This work was supported by the Spanish “Programa Estatal de Investigación, Desarrollo e Inovación Orientada a los Retos de la Sociedad” (grant AGL2013-44039R); the Asociación Española Contra el Cancer (“Obtención de péptidos bioactivos contra el Cáncer Colo-Rectal a partir de secuencias genéticas de microbiomas intestinales”, grant PS2016). This study was also supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145- FEDER006684). SING group thanks CITI (Centro de Investigación, Transferencia e Innovación) from University of Vigo for hosting its IT infrastructure.info:eu-repo/semantics/publishedVersio