Estudo da descelularização tecidual na produção de arcabouços biológicos para enxertos

The regeneration of bone defects with loss of substance remains as a therapeutic challenge in the medical field. There are basically four types of grafts: autologous, allogenic, xenogenic and isogenic. It is a consensus that autologous bone is the most suitable material for this purpose, but there are limitations to its use, especially the insufficient amount in the donor. Surveys show that the components of the extracellular matrix (ECM) are generally conserved between different species and are well tolerated even in xenogenic recipient. Thus, several studies have been conducted in the search for a replacement for autogenous bone scaffold using the technique of decellularization. To obtain these scaffolds, tissue must undergo a process of cell removal that causes minimal adverse effects on the composition, biological activity and mechanical integrity of the remaining extracellular matrix. There is not, however, a conformity among researchers about the best protocol for decellularization, since each of these treatments interfere differently in biochemical composition, ultrastructure and mechanical properties of the extracellular matrix, affecting the type of immune response to the material. Further down the arsenal of research involving decellularization bone tissue represents another obstacle to the arrival of a consensus protocol. The present study aimed to evaluate the influence of decellularization methods in the production of biological scaffolds from skeletal organs of mice, for their use for grafting. This was a laboratory study, sequenced in two distinct stages. In the first phase 12 mice hemi-calvariae were evaluated, divided into three groups (n = 4) and submitted to three different decellularization protocols (SDS [group I], trypsin [Group II], Triton X-100 [Group III]). We tried to identify the one that promotes most efficient cell removal, simultaneously to the best structural preservation of the bone extracellular matrix. Therefore, we performed quantitative analysis of the number of remaining cells and descriptive analysis of the scaffolds, made possible by microscopy. In the second stage, a study was conducted to evaluate the in vitro adhesion of mice bone marrow mesenchymal cells, cultured on these scaffolds, previously decellularized. Through manual counting of cells on scaffolds there was a complete cell removal in Group II, Group I showed a practically complete cell removal, and Group III displayed cell remains. The findings allowed us to observe a significant difference only between Groups II and III (p = 0.042). Better maintenance of the collagen structure was obtained with Triton X-100, whereas the decellularization with Trypsin was responsible for the major structural changes in the scaffolds. After culture, the adhesion of mesenchymal cells was only observed in specimens deccelularized with Trypsin. Due to the potential for total removal of cells and the ability to allow adherence of these, the protocol based on the use of Trypsin (Group II) was considered the most suitable for use in future experiments involving bone grafting decellularized scaffolds

Perfil de mortalidade de idosos no Rio Grande do Norte: estudo comparativo entre duas faixas etárias e fatores relacionados

Measures of mortality represent one of the most important indicators of health conditions. For comprising the larger rate of deaths, the study of mortality in the elderly population is regarded as essential to understand the health situation. In this sense, the present study aims to analyze the mortality profile of the population from 60 to 69 (young elders) and older than 80 years old (oldest old) in the Rio Grande do Norte state (Brazil) in the period 2001 to 2011, and to identify the association with contextual factors and variables about the quality of the Mortality Information System (SIM). For this purpose, Mortality Proportional (MP) was calculated for the state and Specific Mortality Rate by Age (CMId) , according to chapters of ICD- 10, to the municipalities of Rio Grande do Norte , through data from the Mortality Information System (SIM) and the Brazilian Institute of Geography and Statistics (IGBE). In order to identify groups of municipalities with similar mortality profiles, Nonhierarchical Clustering K-means method was applied and the Factor Analysis by the Principal Components Analysis was resort to reduce contextual variables. The spatial distribution of these groups and the factors were visualized using the Spatial Analysis Areas technique. During the period investigated, 21,813 younger elders deaths were recorded , with a predominance of deaths from circulatory diseases (32.75%) and neoplasms (22.9 %) . Among the oldest old, 50,637 deaths were observed, which 35.26% occurred because of cardiovascular diseases and 17.27% of ill-defined causes. Clustering Analysis produced three clusters to the two age groups and Factor Analysis reduced the contextual variables into three factors, also the sum of the factor scores was considered. Among the younger elders, the groups are called misinformation profile, development profile and development paradox, which showed a statistically significant association with education and poverty and extreme poverty factors, factorial sum and the variable related to underreporting of deaths. Misinformation profile remained in the oldest old group, accompanied by the epidemiological transition profile and the epidemiological paradox, that were statistically associated with the development and health factor, as well as with the variables that indicate the SIM quality: proportion of blank fields about the schooling and underreporting. It proposed that the mortality profiles of the younger elders and oldest old differ on the importance of the basic causes and that are influenced by different contextual aspects , observing that 60 to 69 years group is more affected by such aspects. Health inequalities can be reduced by measures aimed to improve levels of education and poverty, especially in younger elders, and by optimizing the use of health services, which is more associated to the oldest old health situation. Furthermore, it is important to improve the quality of information for the two age groups

Algoritmos de agrupamento aplicados a dados de expressão gênica de câncer: um estudo comparativo

The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using classic clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context. This work presents the first large-scale analysis of seven different clustering methods and four proximity measures for the analysis of 35 cancer gene expression data sets. Results reveal that the finite mixture of Gaussians, followed closely by k-means, exhibited the best performance in terms of recovering the true structure of the data sets. These methods also exhibited, on average, the smallest difference between the actual number of classes in the data sets and the best number of clusters as indicated by our validation criteria. Furthermore, hierarchical methods, which have been widely used by the medical community, exhibited a poorer recovery performance than that of the other methods evaluated. Moreover, as a stable basis for the assessment and comparison of different clustering methods for cancer gene expression data, this study provides a common group of data sets (benchmark data sets) to be shared among researchers and used for comparisons with new methods