1000 resultados para Lurie, Ranan R., 1932-


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Rare germline mutations in TP53 (17p13.1) cause a highly penetrant predisposition to a specific spectrum of early cancers, defining the Li-Fraumeni Syndrome (LFS). A germline mutation at codon 337 (p.Arg337His, c1010G>A) is found in about 0.3% of the population of Southern Brazil. This mutation is associated with partially penetrant LFS traits and is found in the germline of patients with early cancers of the LFS spectrum unselected for familial his- tory. To characterize the extended haplotypes carrying the mutation, we have genotyped 9 short tandem repeats on chromosome 17p in 12 trios of Brazilian p.Arg337His carriers. Results confirm that all share a common ancestor haplotype of Caucasian/Portuguese-Ibe- ric origin, distant in about 72–84 generations (2000 years assuming a 25 years intergenera- tional distance) and thus pre-dating European migration to Brazil. So far, the founder p. Arg337His haplotype has not been detected outside Brazil, with the exception of two resi- dents of Portugal, one of them of Brazilian origin. On the other hand, increased meiotic recombination in p.Arg337His carriers may account for higher than expected haplotype diversity. Further studies comparing haplotypes in populations of Brazil and of other areas of Portuguese migration are needed to understand the historical context of this mutation in Brazil.

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BACKGROUND: The Cervical Cancer Database of the Brazilian National Health Service (SISCOLO) contains information regarding all cervical cytological tests and, if properly explored, can be used as a tool for monitoring and managing the cervical cancer screening program. The aim of this study was to perform a historical analysis of the cervical cancer screening program in Brazil from 2006 to 2013. MATERIAL AND METHODS: The data necessary to calculate quality indicators were obtained from the SISCOLO, a Brazilian health system tool. Joinpoint analysis was used to calculate the annual percentage change. RESULTS: We observed important trends showing decreased rates of low-grade squamous intraepithelial lesions (LSIL) and high-grade squamous intraepithelial lesions (HSIL) and an increased rate of rejected exams from 2009 to 2013. The index of positivity was maintained at levels below those indicated by international standards; very low frequencies of unsatisfactory cases were observed over the study period, which partially contradicts the low rate of positive cases. The number of positive cytological diagnoses was below that expected, considering that developed countries with low frequencies of cervical cancer detect more lesions annually. CONCLUSIONS: The evolution of indicators from 2006 to 2013 suggests that actions must be taken to improve the effectiveness of cervical cancer control in Brazil.

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The present study aimed to investigate the effect of structure (design and porosity) on the matrix stiffness and osteogenic activity of stem cells cultured on poly(ester-urethane) (PEU) scaffolds. Different three-dimensional (3D) forms of scaffold were prepared from lysine-based PEU using traditional salt-leaching and advanced bioplotting techniques. The resulting scaffolds were characterized by differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), mercury porosimetry and mechanical testing. The scaffolds had various pore sizes with different designs, and all were thermally stable up to 300â °C. In vitrotests, carried out using rat bone marrow stem cells (BMSCs) for bone tissue engineering, demonstrated better viability and higher cell proliferation on bioplotted scaffolds compared to salt-leached ones, most probably due to their larger and interconnected pores and stiffer nature, as shown by higher compressive moduli, which were measured by compression testing. Similarly, SEM, von Kossa staining and EDX analyses indicated higher amounts of calcium deposition on bioplotted scaffolds during cell culture. It was concluded that the design with larger interconnected porosity and stiffness has an effect on the osteogenic activity of the stem cells.

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Due to the limited self-repair capacity of cartilage, regenerative medicine therapies for the treatment of cartilage defects must use a significant amount of cells, preferably applied using a hydrogel system that can promise their delivery and functionality at the specific site. This paper discusses the potential use of k-carrageenan hydrogels for the delivery of stem cells obt ained from adipose tissue in the treatment of cartilage tissue defects. The developed hydrogels were produced by an ionotropic gelation met hod and human adipose stem cells (hASCs) were encapsulated in 1.5% w/v k-carrageenan solution at a cell density of 5  10 6 cells/ml. The results from the analysis of the cell-encapsulating hydrogels, cultured for up to 21 days, indicated that k-carrageenan hydrogels support the viability, proliferation and chondrogenic differentiation of hASCs. Additionally, the mec hanical analysis demonstrated an increase in stiffness and viscoelastic properties of k-carrageenan gels with their encapsulated cells with increasing time in culture with chondrogenic medium. These results allowed the conclusion that k-carrageenan exhibits properties t hat enable the in vitro functionality of encapsulated hASCs and thus may provide the basis for new successful approaches for the treatment of cartilage defects.

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Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.