Submitted by MARCEL PRATAVIEIRA null (marcelprata93@hotmail.com) on 2016-03-07T15:52:49Z No. of bitstreams: 1 Dissertação - Marcel Pratavieira - 2016.pdf: 8130455 bytes, checksum: a459e73ed4ef0757431f12802bc7f15b (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-03-07T19:51:13Z (GMT) No. of bitstreams: 1 pratavieira_m_me_rcla.pdf: 8130455 bytes, checksum: a459e73ed4ef0757431f12802bc7f15b (MD5) / Made available in DSpace on 2016-03-07T19:51:13Z (GMT). No. of bitstreams: 1 pratavieira_m_me_rcla.pdf: 8130455 bytes, checksum: a459e73ed4ef0757431f12802bc7f15b (MD5) Previous issue date: 2016-02-23 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / As abelhas têm sido utilizadas como modelos robustos e influentes para o estudo de memória e aprendizagem, contribuindo para o melhor entendimento das bases da cognição. Nesse contexto, diferentes metabólitos foram caracterizados por desempenharem funções distintas no processo de aprendizagem e formação de memória em insetos. Considerando que pouco se sabe sobre os metabólitos em relação ao desenvolvimento das habilidades cognitivas em A. mellifera, ou mesmo em relação aos comportamentos reflexos (condicionados e/ou não condicionados), o presente estudo teve como objetivo a análise metabolômica do cérebro de abelhas submetidas ao ensaio comportamental de reflexo de extensão de probóscide (REP). Para isto, foi padronizada a técnica de análise metabolômica com o uso do sistema LC-ESI- MS e MSn, construindo-se inicialmente uma biblioteca de compostos característicos de cérebro de abelhas (neurotransmissores, aminoácidos livres, poliaminas, nucleotídeos, nucleosídeos, ácidos orgânicos, etc). Nesta primeira abordagem, dentre os 112 compostos da biblioteca, 48 foram identificados e quantificados; alguns destes compostos foram únicos para o grupo controle (cadaverina, espermina, glicose, uracila e n-acetil-L-glutamato 5-semialdeido), enquanto que outros foram únicos para o grupo REP (fenilalanina, betaína, espermidina, serina e creatina). Dentre os compostos identificados em ambos os grupos, apenas 5 compostos apresentaram diferenças quantitativas estatisticamente significantes (arginina, asparagina, guanosina monofosfato, putrescina e 4-guanitinobutanoato). Visando o estudo dos perfis metabólicos regionais (em cada região do cérebro), foi também padronizado o protocolo experimental utilizando-se a estratégia MALDI Spectral Imaging e o desenvolvimento de um método semi-quantitativo de metabólitos. Esta estratégia permitiu o mapeamento e o estudo da distribuição espacial dos metabólitos identificados em cortes de cérebro de abelhas, bem como uma melhor compreensão da distribuição dessas moléculas nas diferentes estruturas do cérebro e sua correlação com o comportamento ensaiado. As duas estratégias aplicadas mostraram-se complementares e fundamentais para a compreensão da cognição em abelhas. De modo geral, o ensaio de REP parece estimular intensa atividade cerebral, alto gasto energético, intensa sinalização química e a ativação de algumas cascatas metabólicas específicas, tais como a rota metabólica da prolina e arginina. Nos indivíduos do grupo REP a arginina provavelmente foi catabolizada nas sínteses de creatina, 4-guanidinobutanoato, putrescina e espermidina. Esses processos bioquímicos provavelmente foram importantes para coordenar o reconhecimento da molécula de sacarose, e associar esse odor com um comportamento reflexo para a extensão da probóscide (estímulo não condicionado). / The honeybee Apis mellifera has long served as an invertebrate model organism for learning and memory research, contributing to a better understanding of cognition bases. In this context, different metabolites (especially neurotransmitters) were characterized by play distinct roles in learning process and in memory formation in insects. Whereas little is known about the metabolites in relation to the development of cognitive skills in A. mellifera, the present study aims to perform a metabolomic analysis of the honeybee brains submitted to the behavioral test of proboscis extension reflex (PER). For this, has been standardized a metabolomic analysis technique through the use of LC-ESI-MS and MSn system. Initially a low molecular weight compounds library was created, containing characteristic compounds of bee brain (neurotransmitters, free amino acids, polyamines, nucleotides, nucleosides, organic acids, etc.). In this first approach, from the library of 112 compounds, 48 compounds were identified and quantified; some of these compounds were only identified in the control group (cadaverine, spermine, glucose, uracil and N-acetyl-L-glutamate 5- semialdehyde), while others were only identified in PER group (phenylalanine, betaine, spermidine, serine and creatine). Among the compounds identified in both groups, only five compounds showed statistically significant differences in quantitative results (arginine, asparagine, guanosine monophosphate, putrescine and 4-guanidinebutanoate). In order to study the metabolic profiles by regions (within each brain region) it was also standardized an experimental protocol using a novel semi-quantitative method of MALDI Spectral Imaging strategy. This strategy allowed the study and the mapping of the spatial distribution of metabolites identified in honeybee brain sections, as well as a better understanding of the distribution of molecules in the different brain structures and their correlation with the behavior tested. Both strategies applied proved to be complementary and essential to the understanding of cognition in bees. Overall, in this study the PER test seems to stimulate intense brain activity, high energy expenditure, intense chemical signaling and activation of some specific metabolic pathways, such the arginine and proline metabolic pathway. In individuals of PER group arginine was probably catabolized in the synthesis of creatine, 4-guanidinobutanoato, putrescine and spermidine. This biochemical process were probably important to coordinate the recognition of sucrose molecule and associate this odor with a reflex behavior for the proboscis extension (unconditioned stimulus). / FAPESP: 2014/05376-1

Denna rapport beskriver Windows Installer och hur dess API kan användas för att generera MSI-paket. Det förklaras hur MSI-paket bör vara utformade och hur dessa kan användas. Projektet resulterade i en prototyp åt uppdragsgivaren Capitex AB. Prototypen kunde användas för att generera MSI-paket för applikationen Säljstöd.

La dégradation sélective des protéines par un mécanisme ubiquitine et protéasome 26S dépendant est conservée chez tous les eucaryotes. Les E3 ubiquitine ligases sont les derniers acteurs de la cascade d’ubiquitinylation et sont responsables de la sélection spécifique des protéines cibles pour leur dégradation. Les enzymes E3 de type CRL4 forment des complexes multiprotéiques dont les récepteurs de substrats sont appelés DCAF pour DDB1-CUL4 Associated Factor. Les études réalisées chez les mammifères et les levures ont permis d’identifier une signature spécifique des DCAF : le motif WDxR à la fin d’un domaine WD40. L’analyse bioinformatique a montré l’existence de plus de 85 DCAF potentielles chez Arabidopsis thaliana. Parmi ces récepteurs, nous nous sommes intéressés à une famille multigénique appelée MSI (Multicopy Suppressor of IRA1). Des études précédentes ont permis de montrer que MSI1 et MSI4 participaient chacune à un complexe CRL4 différent capable d’interagir fonctionnellement avec un complexe PRC2 (Polycomb Repressive Complex 2) pour moduler une régulation épigénétique.Les résultats obtenus et décrits dans ce manuscrit mettent en évidence une interaction physique entre les protéines MSI (2 ou 3) et DDB1a suggérant l’existence d’un complexe multimérique incluant CUL4. L’interrogation des données publiques confrontées à nos données expérimentales, nous a permis d’établir que l’expression des deux gènes était régulée de manière cycle cellulaire dépendante. De plus, un mutant perte de fonction msi3 présente un phénotype de retard de croissance suggérant une fonction de contrôle du cycle cellulaire. D’autre part, leur capacité d’interagir avec des régulateurs chromatiniens permet d’envisager une régulation par voie épigénétique. Toutefois, le rôle exact de ces protéines reste à déterminer. / Selective protein degradation by the UPS (Ubiquitin Proteasome System) is highly conserved in all eukaryotes. The E3 ubiquitin ligases are the last actors in the ubiquitylation pathway and target specifically the proteins for degradation. CRL4 E3 ligases form multiprotein complexes where the substrate receptors are called DCAFs for DDB1-CUL4 Associated Factor. Studies made in mammals and yeast allowed to highlight a characteristic signature for the DCAFs: the WDxR motif at the end of a WD40 domain. Bioinformatic studies could identify around 85 potential DCAFs in Arabidopsis thaliana. Among those receptors, we were interested in a small multigenic family called MSIs (Multicopy Suppressor of IRA1). Previous studies showed that MSI1 and MSI4 belong to different CRL4 complexes functionally connected to a PRC2 complex (Polycomb Repressive Complex 2). The results obtained and described in this manuscript highlight a physical interaction between MSI (2 or 3) and DDB1a suggesting the existence of a multimeric complex including CUL4. Furthermore, bioinformatic as well as experimental data, allowed us to establish that MSI2 and MSI3 gene expression are cell cycle regulated. Moreover, phenotypic analysis of an msi3 loss of function mutant showed a delayed growth implying a function as cell cycle regulator. On the other hand, the ability of MSI3 to interact with chromatin regulators points to an epigenetic regulatory pathway. However, the exact function of these proteins remains to be determined.

In recent years, digitalization and computer-based technologies have greatly revolutionized the field of bioinformatics. Advance research and development of computer-based programs have enhanced various DNA sequencing technologies. This advancement has significantly broadened our understanding of genomic evolution and has widely contributed to the application of clinical genomics. Cancer has been one of the major causes of death across the world. Cancer is mainly caused due to the damage or changes in DNA that affect the function of genes which contain a set of instructions that control various functions of cells. This damage in genes that maintain DNA repair mechanism may lead towards genome instability allowing rapid growth of cancer.   Microsatellite instability (MSI) is one such condition characterized due to genomic alteration leading towards the failure of DNA repair mechanism in cancerous cells. MSI is found in various types of cancer but is most often found in colorectal cancer, gastric cancer, and endometrial cancer. Hence, detection of this MSI can greatly contribute towards cancer therapies and enable to plan for the best treatment. This study mainly focuses on evaluating the performance of MSI calling algorithms using targeted sequencing methods.   The literature provides a detailed outline of various topics related to MSI detection. Moreover, different computational methods like MSIsensor, MSIsensor-ct, MSIsensor-pro, MSings, MiMSI, and MSIsensor2 were used in this study for the detection of MSI in selected samples are thoroughly discussed in the methodology section. Finally, the findings of this study conclude that the MSI calling algorithms mentioned above provide accurate detection of MSI in the chosen samples. Also, these algorithms enable us to determine the MSI status of the chosen samples more precisely

No description available.

Despite the significant progress in medicine, infectious diseases are life-threatening thanks to an increasing number of multiresistant strains of microorganisms and late detection of pathological agents. An opportunistic fungus Aspergillus fumigatus cause respiratory system diseases called aspergillosis. The invasive pulmonary aspergillosis affects immunocompromised patients after inhalation of ubiquitous conidia of A. fumigatus and results in 450,000 deaths per year. The biofilm formation in the infected tissue protects A. fumigatus against antimicrobial drugs. Late therapy may not be effective. Infection of immunocompromised patients and biofilm formation is characteristic also for gram negative bacteria Pseudomonas aeruginosa, which is due to the production of many factors of virulence and multiresistance a dreaded opportunistic pathogen. Scanning electron microscopy (SEM) provides detail information about morphology of microorganisms with the resolution in range of tens of nanometers that allows to observe microorganisms in the infected tissue and its pathological changes. Mass spectrometry allows to detect infection and its course based on identification of characteristic microbial molecules. The aim of this study was to optimize sample preparation of tissues infected with A. fumigatus or P....

no / AQ4N (banoxatrone) (1,4-bis-{[2-(dimethylamino-N-oxide)ethyl]amino}-5,8-dihydroxyanthracene-9,10-dione) is an example of a bioreductive prodrug in clinical development. In hypoxic cells AQ4N is reduced to the topoisomerase II inhibitor AQ4 (1,4-bis- {[2-(dimethylamino)ethyl]amino}-5,8-dihydroxyanthracene-9,10-dione). By inhibition of topoisomerase II within these hypoxic areas, AQ4N has been shown to sensitise tumours to existing chemo- and radiotherapy treatments. In this study the distribution of AQ4N and AQ4 in treated H460 human tumour xenografts has been examined by imaging matrix-assisted laser desorption/ionisation mass spectrometry. Images of the distribution of AQ4N and AQ4 have been produced that show little overlap. The distribution of ATP in the tumour xenografts was also studied as an endogenous marker of regions of hypoxia since concentrations of ATP are known to be decreased in these regions. The distribution of ATP was similar to that of AQ4N, i.e. in regions of abundant ATP there was no evidence of conversion of AQ4N into AQ4. This indicates that the cytotoxic metabolite AQ4 is confined to hypoxic regions of the tumour as intended.

No description available.

Predicting divorce potential has been of interest to researchers and clinicians. The Marital Status Inventory (Weiss & Ceretto, 1980) was developed to provide information about clients' perceived divorce potential. The MSI has been widely used but there have been complaints about the negatively worded items from clients, therapists, and researchers. Therefore, this study compared a revised form of the MSI (MSI-R has no negatively worded items) with the original format. There were three purposes of the study. The first was to assess the reliability and validity of the MSI-R. The second purpose was to see if the MSI-R continued to distinguish between types of therapy couples attended (marital versus other therapy). The third and final purpose of the study was to assess the ability of the MSI-R to assess divorce potential with a remarital sample. It was found that the MSI-R is on face value equally as valid as the original MSI. There was a lack of support for discriminate validity. The MSI-R was found to be internally consistent (alpha = .83), therefore reliable. Clients found the revised items to be more easily understood and readable than the original items. The MSI and MSI-R were significantly correlated indicating that they apparently measure the same concepts. Results showed that both groups scored on the low end of the scale indicating that the sample was not a very divorce prone group. There did not appear to be any difference with regards to mean scores on the MSI and MSI-R between marital and remarital groups. While the MSI-R appears to be a promising replacement for the MSI, further research is warranted to provide sufficient evidence of validity.

Background: Genetic and environmental factors have been associated with colorectal cancer (CRC) risk. However, their association with prognosis has been less studied. Methods: Path analysis was employed to examine causal pathways from education to environmental (diet, alcohol, smoking, physical activity) and personal factors (screening), and then to obesity and ultimately to tumour characteristics (stage, grade, microsatellite instability (MSI), and site) that are associated with CRC prognosis. Data came from the Ontario Familial Colon Cancer Registry. Pathways were evaluated for effect modification by sex and two indicators of CRC genetic susceptibility (Bethesda criteria and newly identified familial cancer clusters). Results: Four food patterns (healthy foods, high-fat foods, sweet and processed foods, and oriental foods) and four nutrient patterns (total macronutrient, fat vs. carbohydrate, and micronutrients from supplements and from foods) were identified. Education was associated positively with healthy lifestyle factors (e.g. healthy foods factor) and negatively with unhealthy factors (e.g. smoking). As expected, high body mass index (BMI) was associated with lower physical activity and higher fat vs. carbohydrate factor. Unexpectedly, BMI was positively associated with the healthy foods factor among Bethesda positive patients and men. An association between education and BMI was mediated by the healthy foods factor and by physical activity. Important poor prognostic factors, higher grade and stage, were associated with smoking and not being screened. However, unexpected associations included a positive association of physical activity with tumour grade among Bethesda positive patients and a positive association of healthy foods with stage among Bethesda negative patients. Patients with right-sided tumours were more likely to receive micronutrients from supplements, and screening and less likely to smoke, and for men, to have a high BMI, high fat diet and healthy food diet. Conclusion: Some unhealthy lifestyle factors, such as smoking and a high fat food dietary pattern, are associated with adverse CRC tumour characteristics and so may affect the prognosis. Family history may modify some associations though the findings require independent confirmation.