Avaliação da correlação entre peroxidação lipídica e o perfil de marcadores inflamatórios em pacientes com Diabetes mellitus tipo 2, dislipidemia e periodontite crônica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Cálculo de equivalentes dinâmicos de sistema de potência usando algoritmos genéticos

Esta dissertação apresenta um método baseado em algoritmos genéticos para cálculo de equivalentes dinâmicos de sistemas de potência visando representar partes de um sistema para estudos de análise de estabilidade transitória. O modelo do equivalente dinâmico é obtido por meio da identificação de parâmetros de geradores síncronos, localizados nas barras de fronteira entre o sistema externo e o subsistema em estudo. Um indicie é usado para avaliar a proximidade entre as simulações realizadas usando o modelo completo e o modelo reduzido, após serem submetidos a grandes distúrbios no subsistema em estudo. Diferentes condições operacionais foram levadas em conta. As simulações foram realizadas usando os softwares GAOT “The Genetic Algorithm Optimization Toolbox”, ANAREDE e ANATEM. Esse método foi testado no sistema teste duas áreas do Kundur e no Sistema Interligado Nacional (SIN). Os resultados validaram a eficácia do método desenvolvido para o cálculo de equivalentes dinâmicos robustos.

Projeto de conjunto redutor de velocidade utilizando engrenagem sem-fim

This work is initially based in give a solution to a problem consisting of lifting a load in a warehouse focusing specifically on the solution´s project and comparison of the results obtained following the sequence of the book and comparing these results with the finite elements simulation based on the 3D components modeling. Starting from that was realized the project of the worm gear reducer to solve the problem and makes the work easier. The project consisted basically of the study, project itself and simulation by software of a worm gear reducer and projects steps, starting with the initial problem conditions (to lifting a load up to an specific height at a given time) following all the reducer project sequence, starting by the preliminary draft and electric motor selection using iterative process, material selection, worm gear dimensioning, axles, keyways, bearings and coupling. After that was performed the three dimensional modeling of the components using SolidWorks software and simulating these components using Ansys software. The results show the importance of the CAD in terms of improving project development speed and reducing costs with prototypes

Sistema biométrico de identificação de pessoas utilizando poros e minúcias de impressões digitais

The use of physical characteristics for human identification is known as biometrics. Among the many biometrics traits available, the fingerprint is the most widely used. The fingerprint identification is based on the impression patterns, as the pattern of ridges and minutiae, characteristics of first and second levels respectively. The current identification systems use these two levels of fingerprint features due to the low cost of the sensors. However, the recent advances in sensor technology, became possible to use third level features present within the ridges, such as the perspiration pores. Recent studies show that the use of third-level features can increase security and fraud protection in biometric systems, since they are difficult to reproduce. In addition, recent researches have also focused on multibiometrics recognition due to its many advantages. The goal of this research project was to apply fusion techniques for fingerprint recognition in order to combine minutia, ridges and pore-based methods and, thus, provide more robust biometrics recognition systems, and also to develop an automated fingerprint identification system using these three methods of recognition. We evaluated isotropic-based and adaptive-based automatic pore extraction methods, and the fusion of pore-based method with the identification methods based on minutiae and ridges. The experiments were performed on the public database PolyUHRF and showed a reduction of approximately 16% in the EER compared to the best results obtained by the methods individually

Physical and chemical matrix effects in soil carbon quantification using laser-induced breakdown spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Procedimentos para o dimensionamento de reservatório de água pluvial para residências unifamiliares: viabilidade e aprimoramento metodológico

This paper focus to apply, to discuss and to propose the Maximum Harvesting Method improvement, regarding the method application, for household rainwater harvesting systems. For this purpose, the rainwater was considered to supply the flush toilet demand in a household for 3, 4, and 5 inhabitants. The 80, 120 and 200m2 catchments areas and the 0, 1, 2 and 4mm first flushes discharges were also considered. Further, the improvement suggestions for cistern volume calculus and volume/level dynamics variation in a period were presented and the results were compared applying the Simulation Analyses Method. The results indicate that the Maximum Harvesting Method could be applied and that the improvement proposal can be used to determinate the cistern volume as well to analyze the dynamic behavior of volume/level, constituting by itself a single tool to assist rainwater harvesting systems designers.

Dynamic Traffic Grooming Algorithms for Reconfigurable SONET Over WDM Networks

The emergence of wavelength-division multiplexing (WDM) technology provides the capability for increasing the bandwidth of synchronous optical network (SONET) rings by grooming low-speed traffic streams onto different high-speed wavelength channels. Since the cost of SONET add–drop multiplexers (SADM) at each node dominates the total cost of these networks, how to assign the wavelength, groom the traffic, and bypass the traffic through the intermediate nodes has received a lot of attention from researchers recently. Moreover, the traffic pattern of the optical network changes from time to time. How to develop dynamic reconfiguration algorithms for traffic grooming is an important issue. In this paper, two cases (best fit and full fit) for handling reconfigurable SONET over WDM networks are proposed. For each approach, an integer linear programming model and heuristic algorithms (TS-1 and TS-2, based on the tabu search method) are given. The results demonstrate that the TS-1 algorithm can yield better solutions but has a greater running time than the greedy algorithm for the best fit case. For the full fit case, the tabu search heuristic yields competitive results compared with an earlier simulated annealing based method and it is more stable for the dynamic case.

MOLECULAR DYNAMICS STUDIES OF SIMPLE MODEL FLUIDS AND WATER CONFINED IN CARBON NANOTUBE

Molecular Dynamics (MD) simulation is one of the most important computational techniques with broad applications in physics, chemistry, chemical engineering, materials design and biological science. Traditional computational chemistry refers to quantum calculations based on solving Schrodinger equations. Later developed Density Functional Theory (DFT) based on solving Kohn-Sham equations became the more popular ab initio calculation technique which could deal with ~1000 atoms by explicitly considering electron interactions. In contrast, MD simulation based on solving classical mechanics equations of motion is a totally different technique in the field of computational chemistry. Electron interactions were implicitly included in the empirical atom-based potential functions and the system size to be investigated can be extended to ~106 atoms. The thermodynamic properties of model fluids are mainly determined by macroscopic quantities, like temperature, pressure, density. The quantum effects on thermodynamic properties like melting point, surface tension are not dominant. In this work, we mainly investigated the melting point, surface tension (liquid-vapor and liquid-solid) of model fluids including Lennard-Jones model, Stockmayer model and a couple of water models (TIP4P/Ew, TIP5P/Ew) by means of MD simulation. In addition, some new structures of water confined in carbon nanotube were discovered and transport behaviors of water and ions through nano-channels were also revealed.

Detection Methods for the Genus Lysobacter and the Species Lysobacter enzymogenes

Strains of Lysobacter enzymogenes, a bacterial species with biocontrol activity, have been detected via 16S rDNA sequences in soil in different parts of the world. In most instances, however, their occurrence could not be confirmed by isolation, presumably because the species occurred in low numbers relative to faster-growing species of Bacillus or Pseudomonas. In this study, we developed DNA-based detection and enrichment culturing methods for Lysobacter spp. and L. enzymogenes specifically. In the DNA-based method, a region of 16S rDNA conserved among Lysobacter spp. (L4: GAG CCG ACG TCG GAT TAG CTA GTT), was used as the forward primer in PCR amplification. When L4 and universal bacterial primer 1525R were used to amplify DNA from various bacterial species, an 1100-bp product was found in Lysobacter spp. exclusively. The enrichment culturing method involved culturing soils for 3 days in a chitin-containing broth amended with antibiotics. Bacterial strains in the enrichment culture were isolated on yeast-cell agar and then identified by 16S rDNA sequence analysis. A strain of L. enzymogenes added to soils was detected at populations as low as 102 and 104 CFU/g soil by PCR amplification and enrichment culturing, respectively. In a survey of 58 soil samples, Lysobacter was detected in 41 samples by PCR and enrichment culture, out of which 6 yielded strains of Lysobacter spp. by enrichment culture. Among isolated strains, all were identified to be L. enzymogenes, with the exception of a strain of L. antibioticus. Although neither method alone is completely effective at detecting L. enzymogenes, they are complementary when used together and may provide new information on the spatial distribution of the species in soil.

Regional lung perfusion estimated by electrical impedance tomography in a piglet model of lung collapse

Borges JB, Suarez-Sipmann F, Bohm SH, Tusman G, Melo A, Maripuu E, Sandstrom M, Park M, Costa EL, Hedenstierna G, Amato M. Regional lung perfusion estimated by electrical impedance tomography in a piglet model of lung collapse. J Appl Physiol 112: 225-236, 2012. First published September 29, 2011; doi: 10.1152/japplphysiol.01090.2010.-The assessment of the regional match between alveolar ventilation and perfusion in critically ill patients requires simultaneous measurements of both parameters. Ideally, assessment of lung perfusion should be performed in real-time with an imaging technology that provides, through fast acquisition of sequential images, information about the regional dynamics or regional kinetics of an appropriate tracer. We present a novel electrical impedance tomography (EIT)-based method that quantitatively estimates regional lung perfusion based on first-pass kinetics of a bolus of hypertonic saline contrast. Pulmonary blood flow was measured in six piglets during control and unilateral or bilateral lung collapse conditions. The first-pass kinetics method showed good agreement with the estimates obtained by single-photon-emission computerized tomography (SPECT). The mean difference (SPECT minus EIT) between fractional blood flow to lung areas suffering atelectasis was -0.6%, with a SD of 2.9%. This method outperformed the estimates of lung perfusion based on impedance pulsatility. In conclusion, we describe a novel method based on EIT for estimating regional lung perfusion at the bedside. In both healthy and injured lung conditions, the distribution of pulmonary blood flow as assessed by EIT agreed well with the one obtained by SPECT. The method proposed in this study has the potential to contribute to a better understanding of the behavior of regional perfusion under different lung and therapeutic conditions.

The juvenile three-spined stickleback : model organism for the study of estrogenic and androgenic endocrine disruption in laboratory and field

Industrial and domestic sewage effluents have been found to cause reproductive disorders in wild fish, often as a result of the interference of compounds in the effluents with the endocrine system. This thesis describes laboratory-based exposure experiments and a field survey that were conducted with juveniles of the three-spined stickleback, Gasterosteus aculeatus. This small teleost is a common fish in Swedish coastal waters and was chosen as an alternative to non-native test species commonly used in endocrine disruption studies, which allows the comparison of field data with results from laboratory experiments. The aim of this thesis was to elucidate 1) if genetic sex determination and differentiation can be disturbed by natural and synthetic steroid hormones and 2) whether this provides an endpoint for the detection of endocrine disruption, 3) to evaluate the applicability of specific estrogen- and androgen-inducible marker proteins in juvenile three-spined sticklebacks, 4) to investigate whether estrogenic and/or androgenic endocrine disrupting activity can be detected in effluents from Swedish pulp mills and domestic sewage treatment plants and 5) whether such activity can be detected in coastal waters receiving these effluents. Laboratory exposure experiments found juvenile three-spined sticklebacks to be sensitive to water-borne estrogenic and androgenic steroid substances. Intersex – the co-occurrence of ovarian and testicular tissue in gonads – was induced by 17β-estradiol (E2), 17α-ethinylestradiol (EE2), 17α-methyltestosterone (MT) and 5α-dihydrotestosterone (DHT). The first two weeks after hatching was the phase of highest sensitivity. MT was ambivalent by simultaneously eliciting masculinizing and feminizing effects. When applying a DNA-based method for genetic sex identification, it was found that application of MT only during the first two weeks after hatching caused total and apparently irreversible development of testis in genetic females. E2 caused gonad type reversal from male to female. E2 and EE2 induced vitellogenin - the estrogen-responsive yolk precursor protein, while DHT and MT induced spiggin – the androgen-responsive glue protein of the stickleback. None of the effluents from two pulp mills and two domestic sewage treatment plants had any estrogenic or androgenic activity. Juvenile three-spined sticklebacks were collected during four subsequent summers at the Swedish Baltic Sea coast in recipients of effluents from pulp mills and a domestic sewage treatment plant as well as remote reference sites. No sings of endocrine disruption were observed at any site, when studying gonad development or marker proteins, except for a deviation of sex ratios at a reference site. The three-spined stickleback – with focus on the juvenile stage – was found to be a sensitive species suitable for the study of estrogenic and androgenic endocrine disruption.

Dense disparity map estimation respecting image discontinuities

[EN] We present an energy based approach to estimate a dense disparity map from a set of two weakly calibrated stereoscopic images while preserving its discontinuities resulting from image boundaries. We first derive a simplified expression for the disparity that allows us to estimate it from a stereo pair of images using an energy minimization approach. We assume that the epipolar geometry is known, and we include this information in the energy model. Discontinuities are preserved by means of a regularization term based on the Nagel-Enkelmann operator. We investigate the associated Euler-Lagrange equation of the energy functional, and we approach the solution of the underlying partial differential equation (PDE) using a gradient descent method The resulting parabolic problem has a unique solution. In order to reduce the risk to be trapped within some irrelevant local minima during the iterations, we use a focusing strategy based on a linear scalespace. Experimental results on both synthetic and real images arere presented to illustrate the capabilities of this PDE and scale-space based method.

RNA Interference and cyclooxygenase-2 (COX-2) regulation in colon cancer cells

Despite new methods and combined strategies, conventional cancer chemotherapy still lacks specificity and induces drug resistance. Gene therapy can offer the potential to obtain the success in the clinical treatment of cancer and this can be achieved by replacing mutated tumour suppressor genes, inhibiting gene transcription, introducing new genes encoding for therapeutic products, or specifically silencing any given target gene. Concerning gene silencing, attention has recently shifted onto the RNA interference (RNAi) phenomenon. Gene silencing mediated by RNAi machinery is based on short RNA molecules, small interfering RNAs (siRNAs) and microRNAs (miRNAs), that are fully o partially homologous to the mRNA of the genes being silenced, respectively. On one hand, synthetic siRNAs appear as an important research tool to understand the function of a gene and the prospect of using siRNAs as potent and specific inhibitors of any target gene provides a new therapeutical approach for many untreatable diseases, particularly cancer. On the other hand, the discovery of the gene regulatory pathways mediated by miRNAs, offered to the research community new important perspectives for the comprehension of the physiological and, above all, the pathological mechanisms underlying the gene regulation. Indeed, changes in miRNAs expression have been identified in several types of neoplasia and it has also been proposed that the overexpression of genes in cancer cells may be due to the disruption of a control network in which relevant miRNA are implicated. For these reasons, I focused my research on a possible link between RNAi and the enzyme cyclooxygenase-2 (COX-2) in the field of colorectal cancer (CRC), since it has been established that the transition adenoma-adenocarcinoma and the progression of CRC depend on aberrant constitutive expression of COX-2 gene. In fact, overexpressed COX-2 is involved in the block of apoptosis, the stimulation of tumor-angiogenesis and promotes cell invasion, tumour growth and metastatization. On the basis of data reported in the literature, the first aim of my research was to develop an innovative and effective tool, based on the RNAi mechanism, able to silence strongly and specifically COX-2 expression in human colorectal cancer cell lines. In this study, I firstly show that an siRNA sequence directed against COX-2 mRNA (siCOX-2), potently downregulated COX-2 gene expression in human umbilical vein endothelial cells (HUVEC) and inhibited PMA-induced angiogenesis in vitro in a specific, non-toxic manner. Moreover, I found that the insertion of a specific cassette carrying anti-COX-2 shRNA sequence (shCOX-2, the precursor of siCOX-2 previously tested) into a viral vector (pSUPER.retro) greatly increased silencing potency in a colon cancer cell line (HT-29) without activating any interferon response. Phenotypically, COX-2 deficient HT-29 cells showed a significant impairment of their in vitro malignant behaviour. Thus, results reported here indicate an easy-to-use, powerful and high selective virus-based method to knockdown COX-2 gene in a stable and long-lasting manner, in colon cancer cells. Furthermore, they open up the possibility of an in vivo application of this anti-COX-2 retroviral vector, as therapeutic agent for human cancers overexpressing COX-2. In order to improve the tumour selectivity, pSUPER.retro vector was modified for the shCOX-2 expression cassette. The aim was to obtain a strong, specific transcription of shCOX-2 followed by COX-2 silencing mediated by siCOX-2 only in cancer cells. For this reason, H1 promoter in basic pSUPER.retro vector [pS(H1)] was substituted with the human Cox-2 promoter [pS(COX2)] and with a promoter containing repeated copies of the TCF binding element (TBE) [pS(TBE)]. These promoters were choosen because they are partculary activated in colon cancer cells. COX-2 was effectively silenced in HT-29 and HCA-7 colon cancer cells by using enhanced pS(COX2) and pS(TBE) vectors. In particular, an higher siCOX-2 production followed by a stronger inhibition of Cox-2 gene were achieved by using pS(TBE) vector, that represents not only the most effective, but also the most specific system to downregulate COX-2 in colon cancer cells. Because of the many limits that a retroviral therapy could have in a possible in vivo treatment of CRC, the next goal was to render the enhanced RNAi-mediate COX-2 silencing more suitable for this kind of application. Xiang and et al. (2006) demonstrated that it is possible to induce RNAi in mammalian cells after infection with engineered E. Coli strains expressing Inv and HlyA genes, which encode for two bacterial factors needed for successful transfer of shRNA in mammalian cells. This system, called “trans-kingdom” RNAi (tkRNAi) could represent an optimal approach for the treatment of colorectal cancer, since E. Coli in normally resident in human intestinal flora and could easily vehicled to the tumor tissue. For this reason, I tested the improved COX-2 silencing mediated by pS(COX2) and pS(TBE) vectors by using tkRNAi system. Results obtained in HT-29 and HCA-7 cell lines were in high agreement with data previously collected after the transfection of pS(COX2) and pS(TBE) vectors in the same cell lines. These findings suggest that tkRNAi system for COX-2 silencing, in particular mediated by pS(TBE) vector, could represent a promising tool for the treatment of colorectal cancer. Flanking the studies addressed to the setting-up of a RNAi-mediated therapeutical strategy, I proposed to get ahead with the comprehension of new molecular basis of human colorectal cancer. In particular, it is known that components of the miRNA/RNAi pathway may be altered during the progressive development of colorectal cancer (CRC), and it has been already demonstrated that some miRNAs work as tumor suppressors or oncomiRs in colon cancer. Thus, my hypothesis was that overexpressed COX-2 protein in colon cancer could be the result of decreased levels of one or more tumor suppressor miRNAs. In this thesis, I clearly show an inverse correlation between COX-2 expression and the human miR- 101(1) levels in colon cancer cell lines, tissues and metastases. I also demonstrate that the in vitro modulating of miR-101(1) expression in colon cancer cell lines leads to significant variations in COX-2 expression, and this phenomenon is based on a direct interaction between miR-101(1) and COX-2 mRNA. Moreover, I started to investigate miR-101(1) regulation in the hypoxic environment since adaptation to hypoxia is critical for tumor cell growth and survival and it is known that COX-2 can be induced directly by hypoxia-inducible factor 1 (HIF-1). Surprisingly, I observed that COX-2 overexpression induced by hypoxia is always coupled to a significant decrease of miR-101(1) levels in colon cancer cell lines, suggesting that miR-101(1) regulation could be involved in the adaption of cancer cells to the hypoxic environment that strongly characterize CRC tissues.

Design and implementation of bioinformatics tools for large scale genome annotation

The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe

Computational methods for genome screening

Motivation An actual issue of great interest, both under a theoretical and an applicative perspective, is the analysis of biological sequences for disclosing the information that they encode. The development of new technologies for genome sequencing in the last years, opened new fundamental problems since huge amounts of biological data still deserve an interpretation. Indeed, the sequencing is only the first step of the genome annotation process that consists in the assignment of biological information to each sequence. Hence given the large amount of available data, in silico methods became useful and necessary in order to extract relevant information from sequences. The availability of data from Genome Projects gave rise to new strategies for tackling the basic problems of computational biology such as the determination of the tridimensional structures of proteins, their biological function and their reciprocal interactions. Results The aim of this work has been the implementation of predictive methods that allow the extraction of information on the properties of genomes and proteins starting from the nucleotide and aminoacidic sequences, by taking advantage of the information provided by the comparison of the genome sequences from different species. In the first part of the work a comprehensive large scale genome comparison of 599 organisms is described. 2,6 million of sequences coming from 551 prokaryotic and 48 eukaryotic genomes were aligned and clustered on the basis of their sequence identity. This procedure led to the identification of classes of proteins that are peculiar to the different groups of organisms. Moreover the adopted similarity threshold produced clusters that are homogeneous on the structural point of view and that can be used for structural annotation of uncharacterized sequences. The second part of the work focuses on the characterization of thermostable proteins and on the development of tools able to predict the thermostability of a protein starting from its sequence. By means of Principal Component Analysis the codon composition of a non redundant database comprising 116 prokaryotic genomes has been analyzed and it has been showed that a cross genomic approach can allow the extraction of common determinants of thermostability at the genome level, leading to an overall accuracy in discriminating thermophilic coding sequences equal to 95%. This result outperform those obtained in previous studies. Moreover, we investigated the effect of multiple mutations on protein thermostability. This issue is of great importance in the field of protein engineering, since thermostable proteins are generally more suitable than their mesostable counterparts in technological applications. A Support Vector Machine based method has been trained to predict if a set of mutations can enhance the thermostability of a given protein sequence. The developed predictor achieves 88% accuracy.