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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Quantitative analysis for assessing regional function of liver by using 99m Tc-GSA SPECT

Le, Thang Tran, Kobayashi, Hideaki, Tkai, Katsufumi, Kato, Katsuhiko, Ishigaki, Takeo 05 1900 (has links)
No description available.
2

The Relationship Between School Type and Mental Health of Lesbian, Gay, Bisexual, Transgender, and Questioning Young Adults

Spencer, Steven Vincente 01 January 2016 (has links)
Gay-straight alliance (GSA) clubs may positively affect mental health for lesbian, gay, bisexual, transgender, and questioning (LGBT) students, but little research has studied schools that primarily enroll LGBT students. Guided by neofunctional and sexual stigma theory, the purpose of this study was to determine if graduates of LGBT high schools have better mental health than LGBT and heterosexual graduates of mainstream high schools. A snow ball sample, of 183 graduates of high schools in the United States and 95 graduates from high schools in other countries, 80% who identified as LGBT, completed an online survey consisting of 5 short mental health assessments, measuring anxiety, depression, self-esteem, internalized homophobia, and life satisfaction. Including demographic variables as covariates, ANCOVA was used to test for significant difference in the mental health of former students who have attended high schools with GSAs (GSA+) compared with graduates of high schools without GSAs (GSA-). Research results found that U.S. graduates of GSA+ high schools had significantly higher self-esteem (p = .034) and life satisfaction (p = .026) than U.S. graduates of GSA- high schools. Graduates of non U.S. GSA+ high schools had significantly lower levels of depression (p =.016) than graduates of U.S. GSA- high schools. Students who identified as gender conforming had significantly higher levels of self-esteem (p =.004) and significantly lower levels of depression (p = .000) than students identifying as nongender conforming. The social change implications of these findings include urging school administrations across the country to support GSAs as they may improve the mental health of students who identify as LGBT or nongender conforming.
3

Generalized Simulated Annealing Parameter Sweeping Applied to the Protein Folding Problem / Mapeamento de Parâmetros do Simulated Annealing Generalizado aplicado ao problema do Enovelamento de Proteínas

Flavia Paiva Agostini 06 June 2009 (has links)
Com os rápidos avanços no seqüenciamento do genoma, a compreensão da estrutura de proteínas torna-se uma extensão crucial a esses progressos. Apesar dos significativos avanços tecnológicos recentes, a determinação experimental da estrutura terciária de proteínas ainda é muito lenta se comparada com a taxa de acúmulo de dados das seqüências de aminoácidos. Isto torna o enovelamento de proteínas um problema central para o desenvolvimento da biologia pós-genômica. Em nosso trabalho, fazemos uso de um método de otimização, o Generalized Simulated Annealing (GSA), baseado na termoestatística generalizada por Tsallis. Embora o GSA seja um procedimento geral, sua eficiência depende não apenas da escolha apropriada de parâmetros, mas também das características topológicas da hiper--superfície de energia da função custo. Com o mapeamento dos parâmetros necessários à aplicação do GSA, pode-se reduzir significativamente o número de escolhas, além de tornar possível uma análise do efeito dos parâmetros no comportamento do algoritmo. Como passo inicial, usamos estruturas conhecidas, com as quais os resultados obtidos com o GSA possam ser comparados, como é o caso das polialaninas. Além disso, aplicamos, o GSA a três peptídeos de proteínas ribossomais da família P, de considerável importância no estudo da doença de Chagas. Cada um possui 13 aminoácidos, diferindo em apenas uma mutação não conservativa no terceiro aminoácido. Como os peptídeos não possuem estrutura experimentalmente resolvida, analisamos os resultados obtidos com GSA seguidos por simulações de Dinâmica Molecular. A validade destes resultados é estudada, de forma que, no futuro, estruturas desconhecidas possam ser determinadas com certo grau de confiabilidade. / As the genome sequencing advances, the comprehension of protein structures becomes a crucial extension to these progresses. In spite of the numerous recent technological advances, experimental determination of protein terciary structures is still very slow compared to the accumulated data from amino acid sequences. That is what makes the protein folding a central problem to the development of the pots-genomic era. In this work we use an optimization method, the Generalized Simulated Annealing (GSA), which is based on Tsallis' generalized thermostatistics, to investigate the protein folding problem. Although GSA is a generic procedure, its efficiency depends not only on the appropriate choice of parameters, but also on topological characteristics of the energy hypersurface. By mapping all the GSA parameters, it can be possible to reduce the number of possible choices of them. That also allows an analysis of its effects on the algorithm behavior. As a initial step, we apply GSA to known structures, such as polyalanines. In sequence, we also apply GSA to three more peptides of ribosomal P proteins, which are of considerable importance on the comprehension of Chagas' heart disease. Each one contains 13 amino acids and differ only on the third residue by a non-conservative mutation. As these peptides do not have experimentally resolved structure, we analyze results obtained from GSA followed by Molecular Dynamics simulations. Validity of these results is studied such that, in the future, unknown structures can be determined by this technique with a higher degree of confidence.
4

Influência da Hiperglicemia sobre os Perfis de Expressão Transcricional de mRNAs e microRNAs em Linfócitos de Pacientes com Diabetes Mellitus tipo 2 / Influence of Hyperglycemia in the Transcriptional Expression Profiles of mRNAs and microRNAs in Lymphocytes of Patients with Type 2 Diabetes Mellitus

Danilo Jordão Xavier 14 June 2013 (has links)
O Diabetes Mellitus é uma das maiores causas de morte no mundo. O desenvolvimento do Diabetes Mellitus tipo 2 (DM2) está relacionado com uma série de fatores genéticos e ambientais, culminando com o desenvolvimento do DM2. Já a hiperglicemia, característica marcante da doença, está associada a uma série de complicações metabólicas e comorbidades. No entanto, nào se sabe a influência de um controle apropriado da doença, com menores níveis glicêmicos. No presente trabalho, foi utilizada a técnica de microarrays para comparar os perfis transcricionais (mRNA e microRNA) de células mononucleares de sangue periférico (PBMCs) em três grupos distintos: um grupo de pacientes DM2 descompensados (DM2-D, n=13); um grupo de pacientes DM2 compensados (DM2-C, n=14), e um grupo controle (n=10). Os dados foram analisados por meio de duas linguagens de programação: R e PERL. Após a extração dos dados utilizando-se o software Feature Extraction, versão 10.7 (Agilent Techonologies), foram realizadas correção do background, exclusão dos outliers, normalização dos dados pelo método quantile e, por fim, o ajuste de variações nãobiológicas. Os dados foram então submetidos a análise estatística rank products, sendo identificados 415 mRNAs diferencialmente expressos no grupo DM2-C relativamente aos controles, 285 no grupo DM2-D em comparação aos controles e 478 em pacientes DM2-D comparados aos DM2-C. Posteriormente, os genes diferencialmente expressos foram submetidos à analise de enriquecimento funcional (DAVID). Foram encontrados 22 e 56 termos biológicos enriquecidos (p-corrigido Benjamini-Hochberg < 0,05) para as comparações DM2-C versus controle e pacientes DM2-D versus DM2-C, respectivamente. Em ambas as comparações, um processo biológico foi considerado de interesse para o presente trabalho: resposta inflamatória. Na análise por GSEA e GSA, foram identificados 110 grupos gênicos diferencialmente expressos na comparação DM2-C versus controle. Já para a comparação DM2-D versus controles foram encontrados 297 grupos gênicos diferencialmente expressos, enquanto que na comparação DM2-D versus DM2-C, 161 grupos gênicos diferencialmente expressos. Dentre os grupos gênicos diferencialmente expressos, três merecem destaque: regulação do reparo do DNA (GO: 0006282), resposta ao superóxido (GO: 0000303) e resposta ao estresse do retículo endoplasmático (GO: 0034976). Ainda, 97 microRNAs foram diferencialmente expressos na comparação DM2-C versus controles, 54 na comparação DM2-D versus controles e 101 na comparação DM2-D versus DM2-C. Assim, diferentes grupos gênicos provavelmente foram modulados pela hiperglicemia, além de terem sido descobertos novos microRNAs relacionados a altos níveis de glicose. / Diabetes mellitus is a major cause of death worldwide. The development of type 2 Diabetes Mellitus (T2D) is associated with a number of genetic and environmental factors, culminating in the development of T2D. Hyperglycemia, a hallmark of the disease, is associated with a number of metabolic complications and comorbidities. However, the influence of a proper control of the disease, with lower glucose levels is unknown. In this study, we used the microarrays technique to compare the transcriptional profiles (mRNA and microRNA) of peripheral blood mononuclear cells (PBMCs) in three distinct groups: a group of patients with uncontrolled T2D patients (T2D-U, n = 13) a group of controlled T2D patients (T2D-C, n = 14) and control group (n = 10). Data were analyzed using two programming languages: R and PERL. After extracting the data using the Feature Extraction software, version 10.7 (Agilent Technologies), background correction, outliers exclusion, data normalization by quantile and adjustmesnt of non-biological variations were performed. The data were then statistically analyzed by the rank products test, which identified 415 differentially expressed mRNAs in T2D-C group compared to controls, 285 in group T2D-U in comparison with controls and 478 when T2D-U and T2D-C are compared. Thereafter, the differentially expressed genes were subjected to functional enrichment analysis (DAVID). 22 and 56 biologically enriched terms were found (Benjamini-Hochberg-corrected p value<0.05), when comparing T2D-C with controls and T2D-U with T2D-C, respectively. In both comparisons, inflammatory response was selected as a biological process of interest. The analysis by GSEA and GSA identified 110 differentially expressed gene sets in comparison T2D-C versus control. As for the comparison T2D-U versus control, 297 gene sets were found differentially expressed, whereas in comparison T2D-U versus T2D-C, 161 differentially expressed gene sets were found. Among the differentially expressed gene sets, three stand out: regulation of DNA repair (GO: 0006282), superoxide response (GO: 0000303) and response to endoplasmic reticulum stress (GO: 0034976). Still, 97 microRNAs were differentially expressed in the T2D-C versus controls comparison, 54 when comparing T2D-U versus controls and 101 in the comparison of T2D-U versus T2D-C. Thus, different gene sets were probably modulated by hyperglycemia, and new microRNAs related to high levels of glucose were discovered.
5

Identificação de cascatas gênicas com base na modulação transcricional de células sanguíneas mononucleares periféricas de pacientes com diabetes mellitus do tipo 1 / Identification of gene cascades based on the transcriptional modulation of peripheral blood mononuclear cells from type 1 diabetes mellitus patients.

Thais Cristine Arns 15 March 2013 (has links)
O diabetes mellitus do tipo 1 (DM1) é uma doença autoimune crônica, durante a qual as células beta pancreáticas, responsáveis pela secreção de insulina, são seletivamente destruídas. O desenvolvimento desta doença é uma consequência da predisposição genética combinada a fatores ambientais largamente desconhecidos e eventos estocásticos. Neste trabalho foi proposta a comparação da expressão gênica transcricional em grande escala (transcriptoma) entre amostras de pacientes de DM1 e controles, obtidas a partir de células mononucleares do sangue periférico (PBMCs). As alterações resultantes na expressão gênica causada pela doença podem ser amostradas em PBMCs, uma vez que as células imunes efetoras estão presumivelmente em equilíbrio com a população celular circulante. A fim de identificar alterações na expressão gênica, foram utilizados métodos analíticos como a tecnologia de microarrays e o cálculo do coeficiente de correlação de Pearson, sendo possível observar aumento ou diminuição na expressão gênica e também a magnitude desta mudança. Além disso, foi realizada análise de grupos gênicos (gene sets ou GSA), método baseado na significância de conjuntos gênicos pré-definidos, ao invés de genes individuais. Este procedimento é mais adequado para análise de uma doença poligênica, tal como o DM1. A análise de GSA possibilitou a seleção de genes envolvidos, por exemplo, nas seguintes vias: cascata de I-kappaB kinase/NF-kappaB, regulação da via de sinalização do receptor de TGF-ß, regulação da cascata de JAK-STAT e via de sinalização mediada por citocinas e quimiocinas, das quais podem ser identificados marcadores transcricionais. A análise imparcial do transcriptoma de PBMCs permitiu a identificação de gene sets e genes associados ao DM1, seu perfil de expressão preferencial em tipos celulares do sistema imune e seus padrões de modulação. / Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease, in which the pancreatic beta cells responsible for secretion of insulin are selectively destroyed. The development of this disease is a result of genetic predisposition combined with largely unknown environmental factors and stochastic events. In this work it was proposed to compare the large scale transcriptional gene expression (transcriptome) between samples obtained from T1DM patients and healthy controls, obtained from peripheral blood mononuclear cells (PBMCs). The resulting changes in gene expression caused by the disease can be sampled in PBMCs, as immune effector cells are presumably in equilibrium with the circulating cell population. In order to identify changes in gene expression, we used analytical methods such as microarray technology and calculating the Pearson correlation coefficient, where it was possible to observe increases or decreases in gene expression and also the magnitude of change. Furthermore, we performed a gene set analysis (GSA) method based on the significance of predefined gene sets instead of individual genes. This procedure is more suitable for analyzing a polygenic disease such as T1DM. GSA analysis enabled the selection of genes involved for example, in the following pathways: I-kappaB kinase/NF-kappaB cascade, regulation of TGF-ß receptor signaling pathway, regulation of JAK-STAT cascade and cytokine and chemokine mediated signaling pathway, from which transcriptional markers can be identified. An unbiased transcriptome analysis of PBMCs allowed the identification of gene sets and genes associated with T1DM, its preferential expression profile in cell types of the immune system and its modulation patterns.
6

Mapeamento de Parâmetros do Simulated Annealing Generalizado aplicado ao problema do Enovelamento de Proteínas / Generalized Simulated Annealing Parameter Sweeping Applied to the Protein Folding Problem

Agostini, Flavia Paiva 06 June 2009 (has links)
Made available in DSpace on 2015-03-04T18:51:09Z (GMT). No. of bitstreams: 1 TeseFlavia.pdf: 12428230 bytes, checksum: 6fb8e9ea53da0aa51093c702fb32bc4a (MD5) Previous issue date: 2009-06-06 / Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior / As the genome sequencing advances, the comprehension of protein structures becomes a crucial extension to these progresses. In spite of the numerous recent technological advances, experimental determination of protein terciary structures is still very slow compared to the accumulated data from amino acid sequences. That is what makes the protein folding a central problem to the development of the pots-genomic era. In this work we use an optimization method, the Generalized Simulated Annealing (GSA), which is based on Tsallis' generalized thermostatistics, to investigate the protein folding problem. Although GSA is a generic procedure, its efficiency depends not only on the appropriate choice of parameters, but also on topological characteristics of the energy hypersurface. By mapping all the GSA parameters, it can be possible to reduce the number of possible choices of them. That also allows an analysis of its effects on the algorithm behavior. As a initial step, we apply GSA to known structures, such as polyalanines. In sequence, we also apply GSA to three more peptides of ribosomal P proteins, which are of considerable importance on the comprehension of Chagas' heart disease. Each one contains 13 amino acids and differ only on the third residue by a non-conservative mutation. As these peptides do not have experimentally resolved structure, we analyze results obtained from GSA followed by Molecular Dynamics simulations. Validity of these results is studied such that, in the future, unknown structures can be determined by this technique with a higher degree of confidence. / Com os rápidos avanços no seqüenciamento do genoma, a compreensão da estrutura de proteínas torna-se uma extensão crucial a esses progressos. Apesar dos significativos avanços tecnológicos recentes, a determinação experimental da estrutura terciária de proteínas ainda é muito lenta se comparada com a taxa de acúmulo de dados das seqüências de aminoácidos. Isto torna o enovelamento de proteínas um problema central para o desenvolvimento da biologia pós-genômica. Em nosso trabalho, fazemos uso de um método de otimização, o Generalized Simulated Annealing (GSA), baseado na termoestatística generalizada por Tsallis. Embora o GSA seja um procedimento geral, sua eficiência depende não apenas da escolha apropriada de parâmetros, mas também das características topológicas da hiper--superfície de energia da função custo. Com o mapeamento dos parâmetros necessários à aplicação do GSA, pode-se reduzir significativamente o número de escolhas, além de tornar possível uma análise do efeito dos parâmetros no comportamento do algoritmo. Como passo inicial, usamos estruturas conhecidas, com as quais os resultados obtidos com o GSA possam ser comparados, como é o caso das polialaninas. Além disso, aplicamos, o GSA a três peptídeos de proteínas ribossomais da família P, de considerável importância no estudo da doença de Chagas. Cada um possui 13 aminoácidos, diferindo em apenas uma mutação não conservativa no terceiro aminoácido. Como os peptídeos não possuem estrutura experimentalmente resolvida, analisamos os resultados obtidos com GSA seguidos por simulações de Dinâmica Molecular. A validade destes resultados é estudada, de forma que, no futuro, estruturas desconhecidas possam ser determinadas com certo grau de confiabilidade.
7

Identificação de cascatas gênicas com base na modulação transcricional de células sanguíneas mononucleares periféricas de pacientes com diabetes mellitus do tipo 1 / Identification of gene cascades based on the transcriptional modulation of peripheral blood mononuclear cells from type 1 diabetes mellitus patients.

Arns, Thais Cristine 15 March 2013 (has links)
O diabetes mellitus do tipo 1 (DM1) é uma doença autoimune crônica, durante a qual as células beta pancreáticas, responsáveis pela secreção de insulina, são seletivamente destruídas. O desenvolvimento desta doença é uma consequência da predisposição genética combinada a fatores ambientais largamente desconhecidos e eventos estocásticos. Neste trabalho foi proposta a comparação da expressão gênica transcricional em grande escala (transcriptoma) entre amostras de pacientes de DM1 e controles, obtidas a partir de células mononucleares do sangue periférico (PBMCs). As alterações resultantes na expressão gênica causada pela doença podem ser amostradas em PBMCs, uma vez que as células imunes efetoras estão presumivelmente em equilíbrio com a população celular circulante. A fim de identificar alterações na expressão gênica, foram utilizados métodos analíticos como a tecnologia de microarrays e o cálculo do coeficiente de correlação de Pearson, sendo possível observar aumento ou diminuição na expressão gênica e também a magnitude desta mudança. Além disso, foi realizada análise de grupos gênicos (gene sets ou GSA), método baseado na significância de conjuntos gênicos pré-definidos, ao invés de genes individuais. Este procedimento é mais adequado para análise de uma doença poligênica, tal como o DM1. A análise de GSA possibilitou a seleção de genes envolvidos, por exemplo, nas seguintes vias: cascata de I-kappaB kinase/NF-kappaB, regulação da via de sinalização do receptor de TGF-ß, regulação da cascata de JAK-STAT e via de sinalização mediada por citocinas e quimiocinas, das quais podem ser identificados marcadores transcricionais. A análise imparcial do transcriptoma de PBMCs permitiu a identificação de gene sets e genes associados ao DM1, seu perfil de expressão preferencial em tipos celulares do sistema imune e seus padrões de modulação. / Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease, in which the pancreatic beta cells responsible for secretion of insulin are selectively destroyed. The development of this disease is a result of genetic predisposition combined with largely unknown environmental factors and stochastic events. In this work it was proposed to compare the large scale transcriptional gene expression (transcriptome) between samples obtained from T1DM patients and healthy controls, obtained from peripheral blood mononuclear cells (PBMCs). The resulting changes in gene expression caused by the disease can be sampled in PBMCs, as immune effector cells are presumably in equilibrium with the circulating cell population. In order to identify changes in gene expression, we used analytical methods such as microarray technology and calculating the Pearson correlation coefficient, where it was possible to observe increases or decreases in gene expression and also the magnitude of change. Furthermore, we performed a gene set analysis (GSA) method based on the significance of predefined gene sets instead of individual genes. This procedure is more suitable for analyzing a polygenic disease such as T1DM. GSA analysis enabled the selection of genes involved for example, in the following pathways: I-kappaB kinase/NF-kappaB cascade, regulation of TGF-ß receptor signaling pathway, regulation of JAK-STAT cascade and cytokine and chemokine mediated signaling pathway, from which transcriptional markers can be identified. An unbiased transcriptome analysis of PBMCs allowed the identification of gene sets and genes associated with T1DM, its preferential expression profile in cell types of the immune system and its modulation patterns.
8

Global sensitivity analysis on vibro-acoustic composite materials with parametric dependency / L'analyse de sensibilité globale sur matériaux composites vibroacoustiques avec la dépendance paramétrique

Chai, Wenqi 30 November 2018 (has links)
Avec le développement rapide des modèles mathématiques et des outils de simulation, le besoin des processus de quantification des incertitudes a été bien augmenté. L'incertitude paramétrique et la groupe des nombreux décisions sont aujourd’hui les deux barrières principales dans la résolution des grandes problèmes systématiques.Capable de proportionner l'incertitude de la sortie sur celle des entrées, l’Analyse de Sensibilité Globale (GSA) est une solution fiable pour la quantification de l’incertitude. Parmi plusieurs algorithmes de GSA, Fourier Amplitude Sensitivity Analysis (FAST) est l’un des choix les plus populaires des chercheurs. Basé sur ANOVA-HDMR (ANalysis Of VAriance - High Dimensional Model Representation), il est solide en mathématique est efficace en calcul.Malheureusement, la décomposition unique d’ANOVA-HDMR se dépend sur l’indépendance des entrées. À cause de cela, il y a pas mal de cas industriels qui ne peut pas se traiter par FAST, particulièrement pour ceux qui donnent uniquement les échantillons mais sans lois de distribution. Sous cette demande, deux méthode extensifs de FAST avec design de corrélation sont proposées et étudiées dans la recherche. Parmi les deux méthodes, FAST-c s’est basé sur les distributions et FAST-orig s’est basé sur les échantillons.Comme applications et validations, multiples problèmes vibroacoustiques se sont traités dans la recherche. Les matériaux acoustiques avec soustructures, sont des candidats parfaits pour tester FAST-c et FAST-orig. Deux application sont présentées dans la première partie de la thèse, après l’état de l’arts. Les modèles choisis sont matérial poroélastique et structures composite sandwich, dont les propriétés mécaniques sont tous fortement influencées par les paramètres géométriques microscopique ou mesoscopique. D’avoir la méthode de FAST originale comparée avec les deux nouvelles, on trouve bien plus d’information sur la performance vibroacoustique de ces matériaux.Déjà répondu à la demande de GSA sur les modèles avecs les variables dépendantes, la deuxième partie de la thèse contient plus de recherches reliées avec FAST. D’abord FAST est pris en comparaison avec Random Forest, une algorithme bien connu de data-mining. Leurs erreurs potentiels et la possibilité de fonctioner ensemble sont discutés. Et dans les chapitres suivies, plus d’application de FAST sont présentées. Les méthodes sont appliquées sous plusieurs différente conditions. Une modèle de structure périodique qui contient des corrélation parmi les unités nous a en plus forcé à développer une nouvelle FAST-pe méthode. Dans ces applications, les designs des processus préliminaires et les stratégies d’échantillonages sont des essences à présenter. / With rapid development of mathematical models and simulation tools, the need of uncertainty quantification process has grown higher than ever before. Parametric uncertainties and overall decision stacks are nowadays the two main barriers in solving large scale systematic problem.Global Sensitivity Analysis (GSA) is one reliable solution for uncertainty quantification which is capable to assess the uncertainty of model output on its inputs’. Among several GSA algorithms, Fourier Amplitude Sensitivity Test (FAST) is one of the most popular choices of researchers. Based on ANOVA-HDMR (ANalysis Of VAriance - High Dimensional Model Representation), it is both mathematically solid and computationally efficient.One unfortunate fact is that the uniqueness of ANOVA-HDMR relies on the independency of input variables. It makes FAST unable to treat many industrial cases especially for those with only datasets but not distribution functions to be found. To answer the needs, two extended FAST methods with correlation design are proposed and further studied in this research. Among them FAST-c is distribution-based and FAST-orig is data-based.As a frame of validation and application, a number of vibroacoustic problems are dealt with in this research. Vibroacoustic materials with substructures, are perfect test candidates for FAST-c and FAST-orig. Two application cases are presented in the first part of this thesis, following the literature review. The models chosen here are poroelastic material and sandwich composite structures, both having their mechanical properties hugely influenced by their microscopic and mesoscopic geometric parameters. Getting the original FAST method compared to the two with correlation design, many different features on materials’ vibroacoustic performance are latter discovered.Having got an answer for GSA on models with dependent variables, the second part of this thesis contains more extended researches related to FAST. It is taken into comparison with Random Forest, a well-known data-mining algorithm. The potential error of both algorithms are analyzed and the possibility of joint application is discussed. In the following chapters, more applications of FAST-series methods are reported. They are applied under various conditions where another improved version named FAST-pe is developed to treat a model of periodic structures with correlation among each units. Upon these FAST application cases, the design of preliminary process and the sampling strategies is the core part to be introduced.
9

Genetic Risk Factors for PTSD: A Gene-Set Analysis of Neurotransmitter Receptors

Lewis, Michael 08 July 2020 (has links)
PTSD is a moderately heritable disorder that causes intense and chronic suffering in many afflicted individuals. The pathogenesis of PTSD is not well understood, and genetic mechanisms are particularly elusive. Neurotransmitter systems are thought to contribute to PTSD etiology and are the targets of most pharmacotherapies used to treat PTSD, including the only two FDA approved options and a wide array of off-label options. However, the degree to which variation in genes which encode for and regulate neurotransmitter receptors increase risk of developing PTSD is unclear. Recently, large collaborative groups of PTSD genetics researchers have completed genome-wide association studies (GWAS) using massive sample sizes and have made summary statistics available for public use. In 2018, a new technique for high-powered analysis of GWAS summary statistics called GSA-SNP2 was introduced. In order to explore the relationship between PTSD and genetic variants in widely theorized molecular targets, this study applied GSA-SNP2 to manually curated neurotransmitter receptor gene-sets. Curated gene-sets included nine total "neurotransmitter receptor group" gene-sets and 45 total "receptor subtype" gene-sets. Each "neurotransmitter receptor group" gene-sets was designed to capture concentration of genetic risk factors for PTSD within genes which encode for all receptor subtypes that are activated by a given neurotransmitter. In contrast, "receptor subtype" gene-sets focused on specific subtypes and also accounted for intracellular signaling; each was designed to capture concentration of genetic risk factors for PTSD within genes which encode for specific receptor subtypes and the intracellular signaling proteins through which they exert their effects. Due to practical considerations, this work used summary statistics derived from a GWAS with far fewer participants (2,424 cases; 7,113 controls) than initially planned (23,212 cases; 151,447 controls). Prior to controlling for multiple comparisons, 7 of the investigated gene-sets reached statistical significance at the p ≤ .05 level. However, after controlling for multiple comparisons, none of the investigated gene-sets reached statistical significance. Due to limited statistical power of the current work, these results should be interpreted very cautiously. The current study is best interpreted as a preliminary study and is most informative in relation to refining study design. Implications for next steps are emphasized in discussion and nominally significant results are synthesized with the literature to demonstrate the types of research questions that might be addressed by applying a refined version of this study design to a larger sample. / Doctor of Philosophy / Though nearly all individuals will be exposed to a potentially traumatic event in their lifetime, only a small percentage will experience PTSD, which is a severe psychological disorder. Though genetics are known contribute to an individual's level of risk for developing PTSD, relatively little is known about which particular genetic differences are key. Neurotransmitter receptors are thought to contribute to the risk for PTSD and are a key aspect of medications for PTSD. However, little is known about whether genetic differences in neurotransmitter receptors contribute to risk for developing PTSD. Recently, large collaborative groups of PTSD genetics researchers have completed studies which investigate genetic risk factors from across the genome using massive sample sizes and have made the statistical output of these studies available to the public. In 2018, a new technique called GSA-SNP2 was created to help assist with efforts to analyze aspects of that statistical output that have not been previously analyzed. This study used GSA-SNP2 to analyze the degree to which groups of neurotransmitter receptor genes contribute to the risk of developing PTSD. Due to the coronavirus pandemic, the researcher did not have access to the computing power needed to analyze the initially planned data which included 23,212 individuals with PTSD and 151,447 individuals without PTSD. As a substitute, the current work is an analysis using statistical output data from a study which included 2,424 individuals with PTSD and 7,113 individuals without PTSD. Based on a level of statistical significance that is typically used in most psychological studies, seven of the investigated gene-sets contribute highly to the risk for PTSD. However, it was necessary to use a different threshold for statistical significance due to the testing of many different groups of genes. After making that adjustment, none of the investigated gene-sets reached statistical significance. Due to limited statistical power of the current work, these results should be interpreted very cautiously. The current study is best interpreted as a preliminary study and is most informative in relation to refining study design. Implications for next steps are emphasized in discussion and nominally significant results are synthesized with the literature to demonstrate the types of research questions that might be addressed by applying a refined version of this study design to a larger sample.
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Albright’s Hereditary Osteodystrophy Associated with Cerebellar Pilocytic Astrocytoma: Coincidence or Genetic Relationship?

Sobottka, Stephan B., Hübner, Angela, Haase, Markus, Ahrens, Wiebke, Rupprecht, Edgar, Schackert, Hans K., Schackert, Gabriele 20 February 2014 (has links) (PDF)
Albright’s hereditary osteodystrophy (AHO) is a rare inherited disease characterized by skeletal abnormalities, short stature, and, in some cases, resistance to parathyroid hormone, resulting in pseudohypoparathyroidism (PHP). Heterozygous inactivating mutations of the GNAS1 gene are responsible for reduced activity of the alpha subunit of the Gs protein (GSα), a protein that mediates hormone signal transduction across cell membranes. Gsα is also known to have oncogenic potentials, leading to the development of human pituitary tumors and Leydig cell tumors. Here, we report the 1st case, a 3.5-year-old girl, with classic AHO phenotype and PHP type 1A associated with a cerebellar pilocytic astrocytoma. Coincidence or genetic relationships of both diseases are discussed according to molecular findings and current literature. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

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