CREACIÓN DE UNA COMUNIDAD VIRTUAL DE APRENDIZAJE PARA LA MAESTRÍA PEDAGOGÍA PROFESIONAL DE LA UNIVERSIDAD DE HOLGUÍN

Postgraduate education is a priority for Cuban higher education. In the current times, the international tendency of this modality has been to incorporate elements of Educational Technology to favor the processes of continuous training with the influence of Information and Communication Technologies. In particular, the use of Virtual Environments of Teaching Learning facilitates the organization, conservation and control of information through the design and implementation of virtual courses. The present work, based on a research developed in the University of Holguín, makes use of the Moodle platform in order to favor the interaction between students and professors of the Master’s degree Professional Pedagogy to contribute to the permanent formation. The objective of this paper is to present the results of the creation of a Virtual Learning Community for this Master's degree. With 15 courses mounted, this Virtual Learning Community has an average quality of 38.1%. For the analysis of the results, 1 course was taken as a reference, with a total of 24 female teachers enrolled, where a total of 7 activities and 10 resources were used. The impact study was obtained through observation and the application of surveys and interviews. In addition, the calculation of relative frequency or percentage and frequency distribution was used.La educación de postgrado constituye una prioridad para la educación superior cubana. El uso de la tecnología educativa en función de su perfeccionamiento, ha ocupado protagonismo en los últimos años. El uso de Ambientes Virtuales de Enseñanza Aprendizaje facilita la organización, conservación y control de la información a través del diseño e implementación de cursos virtuales. La presente investigación, desarrollada en la Universidad de Holguín, hace uso de la plataforma Moodle en función de cómo favorecer la creación de una Comunidad Virtual de Aprendizaje en la maestría Pedagogía Profesional para contribuir a la formación permanente de un profesional competente. El objetivo del artículo es la presentación de los resultados de la creación de una Comunidad Virtual de Aprendizaje en Moodle para la maestría Pedagogía Profesional. Los principales resultados se obtuvieron a través de la observación y la aplicación de encuestas y entrevistas. Además, se utilizó el cálculo de frecuencia relativa o porcentaje y la distribución de frecuencias. Con 15 cursos montados, la comunidad virtual en cuestión cuenta con un promedio de calidad de un 38.1%. Para el análisis de los resultados se tomó 1 curso como referencia, con un total de 24 maestrantes matriculados, donde se utilizaron un total de 7 actividades y 10 recursos

Fusobacterium Is Associated with Colorectal Adenomas

The human gut microbiota is increasingly recognized as a player in colorectal cancer (CRC). While particular imbalances in the gut microbiota have been linked to colorectal adenomas and cancer, no specific bacterium has been identified as a risk factor. Recent studies have reported a high abundance of Fusobacterium in CRC subjects compared to normal subjects, but this observation has not been reported for adenomas, CRC precursors. We assessed the abundance of Fusobacterium species in the normal rectal mucosa of subjects with (n = 48) and without adenomas (n = 67). We also confirmed previous reports on Fusobacterium and CRC in 10 CRC tumor tissues and 9 matching normal tissues by pyrosequencing. We extracted DNA from rectal mucosal biopsies and measured bacterial levels by quantitative PCR of the 16S ribosomal RNA gene. Local cytokine gene expression was also determined in mucosal biopsies from adenoma cases and controls by quantitative PCR. The mean log abundance of Fusobacterium or cytokine gene expression between cases and controls was compared by t-test. Logistic regression was used to compare tertiles of Fusobacterium abundance. Adenoma subjects had a significantly higher abundance of Fusobacterium species compared to controls (p = 0.01). Compared to the lowest tertile, subjects with high abundance of Fusobacterium were significantly more likely to have adenomas (OR 3.66, 95% CI 1.37–9.74, p-trend 0.005). Cases but not controls had a significant positive correlation between local cytokine gene expression and Fusobacterium abundance. Among cases, the correlation for local TNF-α and Fusobacterium was r = 0.33, p = 0.06 while it was 0.44, p = 0.01 for Fusobacterium and IL-10. These results support a link between the abundance of Fusobacterium in colonic mucosa and adenomas and suggest a possible role for mucosal inflammation in this process

La lección del Nunca Más. Una aproximación interdisciplinar al contenido y alcance jurídico internacional de la obligación estatal de garantizar la no repetición a través de la educación en memoria. Informe Final

Conceptualmente, el proyecto giró en torno a las garantías de no repetición, es decir: medidas orientadas a evitar futuros incumplimientos del Derecho internacional, de muy diversa naturaleza, pues virtualmente pueden consistir en cualquier cosa (siempre que no resulte abusiva), aunque las más habituales en la práctica internacional son la adopción/derogación/reforma de legislación o de medidas administrativas y las medidas de carácter institucional (relativas a la existencia, organización o funcionamiento de órganos del Estado). Cuando un Estado incumple una obligación internacional –y, por tanto, comete un hecho internacionalmente ilícito–, la principal consecuencia que surge para él es la obligación de reparar, en cualquier de sus tres formas –restitución (o, en su caso, compensación por equivalencia), indemnización o satisfacción (reparación moral)–. Además, en circunstancias excepcionales, tendría también la obligación de ofrecer garantías de no repetición1. Esas “circunstancias excepcionales” vienen en esencia delimitadas por la existencia de violaciones graves de normas imperativas de Derecho internacional, como ocurre cuando se lesionan de manera flagrante o sistemática derechos humanos fundamentales, prácticas que a su vez están tipificadas como crímenes internacionales (genocidio o crímenes contra la humanidad). Por tanto, cuando en el interior de un Estado se cometen atrocidades de esa naturaleza, bien por parte de las propias autoridades estatales, bien por parte de actores no estatales cuyo comportamiento no ha sido prevenido o reprimido por el Estado, surgiría para este la obligación de ofrecer garantías de no repetición

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Additional file 2: of Early-life skin microbiota in hospitalized preterm and full-term infants

Figure S1. Contaminant OTUs identified in extraction control samples. A. Relative abundance of bacterial taxa in extraction control samples. B. OTUs with greater than 1% relative abundance in extraction controls. These OTUs were excluded from subsequent analyses as they were presumed to be contaminants, except the highlighted Staphylococcus OTU that was found to be the dominant Staphylococcus OTU in the biological samples. C. Relative abundance of the contaminant OTUs (in aggregate) that were excluded from subsequent analyses within each sample site. The contaminant OTUs contributed to a minority of the total OTU abundance in each of the sample sites. OTU = operational taxonomic unit. (PPTX 264 kb

Additional file 8: of Early-life skin microbiota in hospitalized preterm and full-term infants

Figure S4. The environmental microbiota of preterm and full-term infants. A. Relative abundance of the top genera in the hospital environment. B. Generalized UniFrac distances between infant body sites and their corresponding environmental samples. Median distances were lower among preterm infants. *p < 0.05. (PPTX 118 kb