9 research outputs found

    General analysis of the governmental perceptions and policies in Latin America and the Caribbean

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    El estudio proporciona un análisis de las percepciones de los gobiernos sobre la situación demográfica y de las políticas gubernamentales implementadas por los países de América Latina y el Caribe en el campo de la población. El énfasis se sitúa en el crecimiento demográfico, a nivel de la mortalidad y acceso a servicios anticonceptivos. Previo la descripción de la situación regional , el análisis releva la evolución de las percepciones y políticas entre 1980 y 1991, incluyendo una discusión detenida tanto de las variables objeto de políticas como de la demografía de los países de la región

    Comprehensive genomic profiling of glioblastoma tumors, BTICs, and xenografts reveals stability and adaptation to growth environments

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    Glioblastoma multiforme (GBM) is the most deadly brain tumor, and currently lacks effective treatment options. Brain tumor-initiating cells (BTICs) and orthotopic xenografts are widely used in investigating GBM biology and new therapies for this aggressive disease. However, the genomic characteristics and molecular resemblance of these models to GBM tumors remain undetermined. We used massively parallel sequencing technology to decode the genomes and transcriptomes of BTICs and xenografts and their matched tumors in order to delineate the potential impacts of the distinct growth environments. Using data generated from whole-genome sequencing of 201 samples and RNA sequencing of 118 samples, we show that BTICs and xenografts resemble their parental tumor at the genomic level but differ at the mRNA expression and epigenomic levels, likely due to the different growth environment for each sample type. These findings suggest that a comprehensive genomic understanding of in vitro and in vivo GBM model systems is crucial for interpreting data from drug screens, and can help control for biases introduced by cell-culture conditions and the microenvironment in mouse models. We also found that lack of MGMT expression in pretreated GBM is linked to hypermutation, which in turn contributes to increased genomic heterogeneity and requires new strategies for GBM treatment
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