RESUMEN
Formative research is an important first step in the design and development of children's school-based physical activity (PA) interventions. Exploration of educator [headteacher and physical education (PE)-co-ordinator] perceptions toward the promotion of school-based PA, including PE delivery has however been limited. This study took a socio-ecological approach to explore the barriers and facilitators of children's school-based PA from the perspective of school educators. Interviews were conducted with headteachers (n = 4), PE-co-ordinators (n = 4) and a deputy headteacher (n = 1) and data thematically analysed using Nvivo software (version 10). Findings suggested that, at an organizational level headteachers were the predominant driving force in the promotion of PA opportunities, yet institutional barriers including low priority for PA and PE were perceived to negate delivery. At an interpersonal level, strategies to increase the delivery of school-based PA were developed, however poor teacher-coach relationships and significant others reduced PA promotion opportunities. Child PA was further negated through intrapersonal factors, including lack of PE-specific teacher training and varying teacher interest in PA and sport. To increase primary school children's school-based PA, barriers and facilitators at the organizational, interpersonal and intrapersonal level must be considered and targeted and researchers and schools should work in partnership to develop future interventions.
Asunto(s)
Personal Docente/psicología , Ejercicio Físico , Servicios de Salud Escolar/organización & administración , Adulto , Niño , Inglaterra , Femenino , Humanos , Masculino , Educación y Entrenamiento Físico/métodos , Educación y Entrenamiento Físico/organización & administración , Instituciones Académicas/organización & administración , Formación del ProfesoradoRESUMEN
Cancers arise owing to mutations in a subset of genes that confer growth advantage. The availability of the human genome sequence led us to propose that systematic resequencing of cancer genomes for mutations would lead to the discovery of many additional cancer genes. Here we report more than 1,000 somatic mutations found in 274 megabases (Mb) of DNA corresponding to the coding exons of 518 protein kinase genes in 210 diverse human cancers. There was substantial variation in the number and pattern of mutations in individual cancers reflecting different exposures, DNA repair defects and cellular origins. Most somatic mutations are likely to be 'passengers' that do not contribute to oncogenesis. However, there was evidence for 'driver' mutations contributing to the development of the cancers studied in approximately 120 genes. Systematic sequencing of cancer genomes therefore reveals the evolutionary diversity of cancers and implicates a larger repertoire of cancer genes than previously anticipated.
Asunto(s)
Genes Relacionados con las Neoplasias/genética , Genoma Humano/genética , Genómica , Mutación/genética , Neoplasias/genética , Secuencia de Aminoácidos , Análisis Mutacional de ADN , Humanos , Datos de Secuencia Molecular , Proteínas de Neoplasias/química , Proteínas de Neoplasias/genética , Proteínas Quinasas/química , Proteínas Quinasas/genéticaRESUMEN
The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.