Efeitos do diabetes gestacional moderado e da reposição com insulina na lactação sobre a próstata ventral do rato Wistar

Pós-graduação em Biologia Geral e Aplicada - IBB

Efeito da infecção pelo vírus da febre amarela no mecanismo de splicing celular

Pós-graduação em Microbiologia - IBILCE

Um algoritmo de busca tabu para problemas de localização não capacitados

In this work, a tabu search algorithm for solving uncapacitated location problems is presented. The uncapacitated location problem is a classic problem of localization and occurs in many practical situations. The problem consists in determining in a network, at the minimum possible cost, the better localization, in a network, for the installation of facilities in order to attend the customers' associated demands, at the minimum possible cost. One admits that there exists a cost associated with the opening of a facility and a cost of attendance of each customer by any open facilities. In the particular case of the uncapacitated location problem there is no capacity limitation to attend the customers’ demands. There are some parameters in the algorithm that influence the solution’s quality. These parameters were tested and optimal values for them were obtained. The results show that the proposed algorithm is able to find the optimal solution for all small tested problems keeping the compromise between solution’s quality and computational time. However, to solve bigger problems, the structure of the algorithm must be changed in its structure. The implemented algorithm is integrated to a computational platform for solution of logistic problems

Método de Taguchi aplicado a um processo de corte por fusão de um tecido sintético

A company must have full knowledge and control of its operations so as to meet the market requirements and meet their production goals. Thus this paper uses the Taguchi method to extend the operational control of a cutting process by fusion of a synthetic fabric in the longitudinal direction. For process analysis and tracking of possible causes of the problem techniques of Production Engineering as the cause and effect diagram, also known as Ishikawa diagram, and design of experiments were used, the last one was applied to the design techniques of Taguchi. Finally the preparation method of understanding and design of experiment was due to the use of the software MINITAB v15 ®, which showed that the speed of rolling the fabric after cutting is crucial for controlling the entire operation

A matemática dos sistemas de localização por satélites

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Expressão imuno-histoquímica de KI-67, COX-2, MMP-9 e P53 nos tumores testiculares caninos

Pós-graduação em Ciência Animal - FMVA

Inovação tecnológica de boas práticas agrícolas e a informática na gestão agropecuária

This study aims to develop innovative proposals for production agriculture management and plans to build a participatory model, through the digital inclusion of members of the family farm gathered in a cooperative venture seeking to establish new environmental management efficiency for household production. The first part of the hypothesis assumes that a major obstacle to the insertion of small family farms into the markets is skilled labor, human capital. A training model has been developed for traceability and tracking activities on family farms, based on the atemoya culture. The second hypothesis predicts that it is possible to create a model that is scientifically supported by widely accepted rules derived from GlobalGAP standard certification, a global benchmark for good agricultural practices. Using these rules the model seeks to achieve the traceability of agricultural products and operations from the preservation of identity information within the production chain. The results obtained by the computerized system confirmed the presented hypotheses by demonstrating that technological innovation through intensive communication and information technologies education as well as other associated forms are important drivers of regional development, especially if implemented through a digital inclusion project using the state program Infocentros Access São Paulo.

A new HPLC-DAD-MS/MS method for the simultaneous determination of major compounds in the crude extract of Lychnophora salicifolia Mart. (Brazilian arnicao) leaves: Application to chemical variability evaluation

Lychnophora salicifolia Mart., which occurs in the Brazilian Cerrado in the states of Bahia and Minas Gerais as well as in the southeast of the state of Goias, is the most widely distributed and also the most polymorphic species of the genus. This plant is popularly known to have anti-inflammatory and analgesic activities. In this work, we have studied the variation in terms of polar metabolites of ninety-three Lychnophora salicifolia Mart, specimens collected from different regions of the Brazilian Cerrado. Identification of the constituents of this mixture was carried out by analysis of the UV spectra and MS data after chromatographic separation. Twenty substances were identified, including chlorogenic acid derivatives, a flavonoid C-glucoside, and other sesquiterpenes. The analytical method was validated, and the reliability and credibility of the results was ensured for the purposes of this study. The concentration range required for analysis of content variability within the analyzed group of specimens was covered with appropriate values of limits of detection and quantitation, as well as satisfactory precision and recovery. A quantitative variability was observed among specimens collected from the same location, but on average they were similar from a chemical viewpoint. In relation to the study involving specimens from different locations, there were both qualitative and quantitative differences among plants collected from different regions of Brazil. Statistical analysis revealed that there is a correlation between geographical localization and polar metabolites profile for specimens collected from different locations. This is evidence that the pattern of metabolites concentration depends on the geographical distribution of the specimens. (C) 2012 Elsevier B.V. All rights reserved.

Oestrogen receptor beta in adenoid cystic carcinoma of salivary glands

Aims: This study aimed to describe the expression of oestrogen receptor (ER)alpha, ER beta and aromatase in salivary gland adenoid cystic carcinoma (ACC). Methods and results: ER alpha, ER beta and aromatase expression was analysed by immunohistochemistry in tissue microarray blocks from 38 cases of ACC and seven normal salivary glands. The intracellular localization and amount of total protein expression were investigated by immunofluorescence and western blotting in an ACC cell line. Western blotting analysis showed overexpression of ER alpha, ER beta and aromatase in the ACC cell line; however, with immunofluorescence, only ER beta was shown to be expressed in the nucleus. Immunohistochemistry revealed positive nuclear expression of ER beta, positive cytoplasmic expression of aromatase and a lack of ER alpha expression as compared with normal salivary glands. Conclusions: The nuclear expression of ER beta indicates that oestrogen may be active in ACC and possibly able to mediate E2-targeted gene transcription. This study strongly suggests that ER beta may be involved in tumour progression, playing a role in tumour development, and thus corroborating the indication for ER antagonists in the clinical control of ACC. This study opens a new perspective on the potential use of anti-oestrogens and aromatase inhibitors as therapeutic agents against ACC.

Assessment of cumulative damage by using ultrasonic C-scan on carbon fiber/epoxy composites under thermal cycling

In recent years, structural composites manufactured by carbon fiber/epoxy laminates have been employed in large scale in aircraft industries. These structures require high strength under severe temperature changes of -56° until 80 °C. Regarding this scenario, the aim of this research was to reproduce thermal stress in the laminate plate developed by temperature changes and tracking possible cumulative damages on the laminate using ultrasonic C-scan inspection. The evaluation was based on attenuation signals and the C-scan map of the composite plate. The carbon fiber/epoxy plain weave laminate underwent temperatures of -60° to 80 °C, kept during 10 minutes and repeated for 1000, 2000, 3000 and 4000 times. After 1000 cycles, the specimens were inspected by C-scanning. A few changes in the laminate were observed using the inspection methodology only in specimens cycled 3000 times, or so. According to the found results, the used temperature range did not present enough conditions to cumulative damage in this type of laminate, which is in agreement with the macro - and micromechanical theory.

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

Reconstruction of CNGS neutrino events in the emulsions of the OPERA experiment

The OPERA experiment aims at the direct observation of ν_mu -> ν_tau oscillations in the CNGS (CERN Neutrinos to Gran Sasso) neutrino beam produced at CERN; since the ν_e contamination in the CNGS beam is low, OPERA will also be able to study the sub-dominant oscillation channel ν_mu -> ν_e. OPERA is a large scale hybrid apparatus divided in two supermodules, each equipped with electronic detectors, an iron spectrometer and a highly segmented ~0.7 kton target section made of Emulsion Cloud Chamber (ECC) units. During my research work in the Bologna Lab. I have taken part to the set-up of the automatic scanning microscopes studying and tuning the scanning system performances and efficiencies with emulsions exposed to a test beam at CERN in 2007. Once the triggered bricks were distributed to the collaboration laboratories, my work was centered on the procedure used for the localization and the reconstruction of neutrino events.

Studio della trasduzione del Segnale Nucleare Inositide-Dipendente: identificazione di eEF1A2 come nuovo Fosfosubstrato di PKC βI

Introduction Phospholipase Cb1 (PLC-β1) is a key player in the regulation of nuclear inositol lipid signaling and of a wide range of cellular functions, such as proliferation and differentiation (1,2,3). PLCb1 signaling depends on the cleavage of phosphatidylinositol 4,5-bisphosphate and the formation of the second messengers diacylglycerol and Inositol tris-phosphate which activate canonical protein kinase C (cPKC) isoforms. Here we describe a proteomic approach to find out a potential effector of nuclear PLC-b1 dependent signaling during insulin stimulated myogenic differentiation. Methods Nuclear lysates obtained from insulin induced C2C12 myoblasts were immunoprecipitated with anti-phospho-substrate cPKC antibody. Proteins, stained with Comassie blue, were excised, digested and subsequently analysed in LC-MS/MS. For peptide sequence searching, the mass spectra were processed and analyzed using the Mascot MS/MS ion search program with the NCBI database. Western blotting, GST-pull down and co-immunoprecipitation were performed to study the interaction between eEF1A2 and cPKCs. Site direct mutagenesis was performed to confirm the phosphorylated motif recognized by the antibody. Immunofluorescence analysis, GFP-tagged eEF1A2 vector and subcellular fractionation were performed to study nuclear localization and relative distribution of eEF1A2. Results We have previously shown that PLC-β1 is greatly increased at the nuclear level during insulin-induced myoblasts differentiation and that this nuclear localization is essential for induction of differentiation. Thus, nuclear proteins of insulin stimulated C2C12 myoblasts, were immunoprecipitated with an anti-phospho-substrate cPKC antibody. After Electrophoretic gel separation of proteins immunoprecipitated, several molecules were identified by LC-MS/MS. Among these most relevant and unexpected was eukaryotic elongation factor 1 alpha 2 (eEF1A2). We found that eEF1A2 is phosphorylated by PKCb1 and that these two molecules coimmunolocalized at the nucleolar level. eEF1A2 could be phosphorylated in many sites among which both threonine and serine residues. By site direct mutagenesis we demonstrated that it is the serine residue of the motif recognized by the antibody that is specifically phosphorylated by PKCb1. The silencing of PLCb1 gives rise to a reduction of expression and phosphorylation levels of eEF1A2 indicating this molecule as a target of nuclear PLCb1 regulatory network during myoblasts differentiation.

Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins

The goal of this thesis work is to develop a computational method based on machine learning techniques for predicting disulfide-bonding states of cysteine residues in proteins, which is a sub-problem of a bigger and yet unsolved problem of protein structure prediction. Improvement in the prediction of disulfide bonding states of cysteine residues will help in putting a constraint in the three dimensional (3D) space of the respective protein structure, and thus will eventually help in the prediction of 3D structure of proteins. Results of this work will have direct implications in site-directed mutational studies of proteins, proteins engineering and the problem of protein folding. We have used a combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM), the so-called Hidden Neural Network (HNN) as a machine learning technique to develop our prediction method. By using different global and local features of proteins (specifically profiles, parity of cysteine residues, average cysteine conservation, correlated mutation, sub-cellular localization, and signal peptide) as inputs and considering Eukaryotes and Prokaryotes separately we have reached to a remarkable accuracy of 94% on cysteine basis for both Eukaryotic and Prokaryotic datasets, and an accuracy of 90% and 93% on protein basis for Eukaryotic dataset and Prokaryotic dataset respectively. These accuracies are best so far ever reached by any existing prediction methods, and thus our prediction method has outperformed all the previously developed approaches and therefore is more reliable. Most interesting part of this thesis work is the differences in the prediction performances of Eukaryotes and Prokaryotes at the basic level of input coding when ‘profile’ information was given as input to our prediction method. And one of the reasons for this we discover is the difference in the amino acid composition of the local environment of bonded and free cysteine residues in Eukaryotes and Prokaryotes. Eukaryotic bonded cysteine examples have a ‘symmetric-cysteine-rich’ environment, where as Prokaryotic bonded examples lack it.

Development of muliplexed analytical methods based on bioluminescent whole-cell biosensors

The subject of this Ph.D. research thesis is the development and application of multiplexed analytical methods based on bioluminescent whole-cell biosensors. One of the main goals of analytical chemistry is multianalyte testing in which two or more analytes are measured simultaneously in a single assay. The advantages of multianalyte testing are work simplification, high throughput, and reduction in the overall cost per test. The availability of multiplexed portable analytical systems is of particular interest for on-field analysis of clinical, environmental or food samples as well as for the drug discovery process. To allow highly sensitive and selective analysis, these devices should combine biospecific molecular recognition with ultrasensitive detection systems. To address the current need for rapid, highly sensitive and inexpensive devices for obtaining more data from each sample,genetically engineered whole-cell biosensors as biospecific recognition element were combined with ultrasensitive bioluminescence detection techniques. Genetically engineered cell-based sensing systems were obtained by introducing into bacterial, yeast or mammalian cells a vector expressing a reporter protein whose expression is controlled by regulatory proteins and promoter sequences. The regulatory protein is able to recognize the presence of the analyte (e.g., compounds with hormone-like activity, heavy metals…) and to consequently activate the expression of the reporter protein that can be readily measured and directly related to the analyte bioavailable concentration in the sample. Bioluminescence represents the ideal detection principle for miniaturized analytical devices and multiplexed assays thanks to high detectability in small sample volumes allowing an accurate signal localization and quantification. In the first chapter of this dissertation is discussed the obtainment of improved bioluminescent proteins emitting at different wavelenghts, in term of increased thermostability, enhanced emission decay kinetic and spectral resolution. The second chapter is mainly focused on the use of these proteins in the development of whole-cell based assay with improved analytical performance. In particular since the main drawback of whole-cell biosensors is the high variability of their analyte specific response mainly caused by variations in cell viability due to aspecific effects of the sample’s matrix, an additional bioluminescent reporter has been introduced to correct the analytical response thus increasing the robustness of the bioassays. The feasibility of using a combination of two or more bioluminescent proteins for obtaining biosensors with internal signal correction or for the simultaneous detection of multiple analytes has been demonstrated by developing a dual reporter yeast based biosensor for androgenic activity measurement and a triple reporter mammalian cell-based biosensor for the simultaneous monitoring of two CYP450 enzymes activation, involved in cholesterol degradation, with the use of two spectrally resolved intracellular luciferases and a secreted luciferase as a control for cells viability. In the third chapter is presented the development of a portable multianalyte detection system. In order to develop a portable system that can be used also outside the laboratory environment even by non skilled personnel, cells have been immobilized into a new biocompatible and transparent polymeric matrix within a modified clear bottom black 384 -well microtiter plate to obtain a bioluminescent cell array. The cell array was placed in contact with a portable charge-coupled device (CCD) light sensor able to localize and quantify the luminescent signal produced by different bioluminescent whole-cell biosensors. This multiplexed biosensing platform containing whole-cell biosensors was successfully used to measure the overall toxicity of a given sample as well as to obtain dose response curves for heavy metals and to detect hormonal activity in clinical samples (PCT/IB2010/050625: “Portable device based on immobilized cells for the detection of analytes.” Michelini E, Roda A, Dolci LS, Mezzanotte L, Cevenini L , 2010). At the end of the dissertation some future development steps are also discussed in order to develop a point of care (POCT) device that combine portability, minimum sample pre-treatment and highly sensitive multiplexed assays in a short assay time. In this POCT perspective, field-flow fractionation (FFF) techniques, in particular gravitational variant (GrFFF) that exploit the earth gravitational field to structure the separation, have been investigated for cells fractionation, characterization and isolation. Thanks to the simplicity of its equipment, amenable to miniaturization, the GrFFF techniques appears to be particularly suited for its implementation in POCT devices and may be used as pre-analytical integrated module to be applied directly to drive target analytes of raw samples to the modules where biospecifc recognition reactions based on ultrasensitive bioluminescence detection occurs, providing an increase in overall analytical output.