Estudo das características físico-químicas e biológicas pela adesão de osteoblastos em superfícies de titânio modificadas pela nitretação em plasma

SILVA, J. S. P. Estudo das características físico-químicas e biológicas pela adesão de osteoblastos em superfícies de titânio modificadas pela nitretação em plasma. 2008. 119 f. Tese (Doutorado) - Faculdade de Medicina, Universidade de São Paulo. São Paulo, 2008.

Análise metagenômica da microbiota de ambientes aquáticos do estado do Rio Grande do Norte - Brasil

The screening for genes in metagenomic libraries from soil creates opportunities to explore the enormous genetic and metabolic diversity of microorganisms. Rivers are ecosystems with high biological diversity, but few were examined using the metagenomic approach. With this objective, a metagenomic library was constructed from DNA soil samples collected at three different points along the Jundiaí-river (Rio Grande do Norte-Brazil). The points sampled are from open area, rough terrain and with the direct incidence of sunlight. This library was analyzed functionally and based in sequence. For functional analysis Luria-Bertani solid medium (LB) with NaCl concentration varied from 0.17M to 0.85M was used for functional analysis. Positives clones resistant to hypersaline medium were obtained. The recombinant DNAs were extracted and transformed into Escherichia coli strain DH10B and survival curves were obtained for quantification of abiotic stress resistance. The sequences of clones were obtained and submitted to the BLASTX tool. Some clones were found to hypothetical proteins of microorganisms from both Archaea and Bacteria division. One of the clones showed a complete ORF with high similarity to glucose-6-phosphate isomerase which participates in the synthesis of glycerol pathway and serves as a compatible solute to balance the osmotic pressure inside and outside of cells. Subsequently, in order to identify genes encoding osmolytes or enzymes related halotolerance, environmental DNA samples from the river soil, from the water column of the estuary and ocean were collected and pyrosequenced. Sequences of osmolytes and enzymes of different microorganisms were obtained from the UniProt and used as RefSeqs for homology identification (TBLASTN) in metagenomic databases. The sequences were submitted to HMMER for the functional domains identification. Some enzymes were identified: alpha-trehalose-phosphate synthase, L-ectoina synthase (EctC), transaminase L-2 ,4-diaminobutyric acid (EctB), L-2 ,4-diaminobutyric acetyltransferase (EctA), L-threonine 3 dehydrogenase (sorbitol pathway), glycerol-3-phosphate dehydrogenase, inositol 3-phosphate dehydrogenase, chaperones, L-proline, glycine betaine binding ABC transporter, myo-inositol-1-phosphate synthase protein of proline simportadora / PutP sodium-and trehalose-6-phosphate phosphatase These proteins are commonly related to saline environments, however the identification of them in river environment is justified by the high salt concentration in the soil during prolonged dry seasons this river. Regarding the richness of the microbiota the river substrate has an abundance of halobacteria similar to the sea and more than the estuary. These data confirm the existence of a specialized response against salt stress by microorganisms in the environment of the Jundiaí river

Máquina de vetores-suporte intervalar

The Support Vector Machines (SVM) has attracted increasing attention in machine learning area, particularly on classification and patterns recognition. However, in some cases it is not easy to determinate accurately the class which given pattern belongs. This thesis involves the construction of a intervalar pattern classifier using SVM in association with intervalar theory, in order to model the separation of a pattern set between distinct classes with precision, aiming to obtain an optimized separation capable to treat imprecisions contained in the initial data and generated during the computational processing. The SVM is a linear machine. In order to allow it to solve real-world problems (usually nonlinear problems), it is necessary to treat the pattern set, know as input set, transforming from nonlinear nature to linear problem. The kernel machines are responsible to do this mapping. To create the intervalar extension of SVM, both for linear and nonlinear problems, it was necessary define intervalar kernel and the Mercer s theorem (which caracterize a kernel function) to intervalar function