3 resultados para Intensity classes
em Reposit
Resumo:
Introdução – Os benefícios do exercício físico em sobreviventes de cancro da mama têm sido reportados; contudo, a sua prática permanece baixa, tornando importante o conhecimento dos fatores que promovam a motivação e adesão ao exercício nesta população. Objetivos – Identificar as preferências quanto à programação e aconselhamento do exercício físico de uma amostra da população de mulheres portuguesas sobreviventes de cancro da mama e averiguar a influência das variáveis demográficas e médicas nestas preferências. Método – Foi aplicado um questionário a uma amostra não probabilística sequencial de 26 mulheres sobreviventes de cancro da mama. Resultados – A amostra era maioritariamente constituída por mulheres entre os 45 e os 62 anos, casadas ou em união de facto, com ensino básico, empregadas e com Índice de Massa Corporal (IMC) > 24,4. Maioritariamente tinham realizado cirurgia radical há um mês ou mais, apresentavam estadio I do tumor, efetuavam quimioterapia como tratamento adjuvante e algumas realizavam classes de fisioterapia. A maioria das participantes demonstrava interesse em receber aconselhamento, sentia-se apta a participar num programa de exercício, preferia receber aconselhamento face-a-face no hospital e acompanhada por outros doentes oncológicos. O exercício deveria ser supervisionado e com intensidade moderada, sendo as caminhadas o tipo de exercício preferido. Não foi estatisticamente possível realizar a associação entre as variáveis demográficas e médicas e as preferências. Conclusão – Alguns resultados obtidos estão em concordância com estudos prévios; contudo, outros divergem destes. Os resultados obtidos podem fornecer informações importantes para a construção futura de programas de exercício para esta população. ABSTRACT - Introduction – The benefits of physical exercise in cancer survivors have been reported, although it’s practice remains low, becoming important the acknowledgement of the factors that promote the motivation and adhesion of physical exercise in this population. Objectives – To identify the preferences about programming and counseling of physical exercise inside a population-based sample of Portuguese women who have survived breast cancer. We also intend to investigate the influence of demographic and medical variables in those preferences. Method – A questionnaire was applied to a non-probabilistic sequential sample of 26 women that have survived breast cancer. Results – Our sample was mainly composed by women aged between 45 and 62, married or in a cohabitation state, with basic instruction, employed and with a Body Mass Index (BMI)> 24.4. Most of them have had radical mastectomy for at least one month, had the Stage I of the tumor, and had done chemotherapy as an adjuvant treatment and some of them were practicing post-surgery physical therapy. The majority of participants showed interest in receiving counseling, felt able to participate in an exercise program, preferred receiving face-to-face counseling, at the hospital and with other cancer patients. The exercise should be supervised and with a moderate intensity. Walking was their preferred choice of exercise. It was not statistically possible to establish the relationship between demographic and medical variables and those preferences. Conclusion – Some results are in agreement with previous studies; however, others diverge from these. The results obtained can provide important information for future construction of exercise programs for this population.
Resumo:
Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.
Resumo:
Dissertação apresentada à Escola Superior de Educação de Lisboa para a obtenção de grau de mestre em Ciências da Educação -Especialidade Educação Especial