Comunidades microbianas possuem papéis importantes em processos que ocorrem em diversos ambientes, tais como solos, oceanos e o trato gastrointestinal dos seres humanos. Portanto, é de interesse a compreensão da estrutura e do funcionamento dessas comunidades. A estrutura dessas comunidades, em termos de organismos componentes, pode ser determinada com o uso do sequenciamento de nova geração em conjunto com as técnicas meta-ômicas e pela análise taxonômica das sequências obtidas com programas de classificação taxonômica. Se por um lado diversos programas estão disponíveis, por outro lado eles cometem erros, como a identificação parcial dos organismos presentes na amostra e a identificação de organismos que não estão presentes na amostra (os falsos positivos - FPs). Algumas abordagens foram propostas para a melhoria das classificações taxonômicas obtidas por esses programas com a redução desses FPs, porém elas abordam apenas um tipo de meta-ômica, a metagenômica. Neste trabalho, propomos uma nova abordagem através da integração de diferentes meta-ômicas - metagenômicas shotgun e de amplicons de 16S, e metatranscritômica. Exploramos os resultados de classificações de dados simulados e mocks para a extração de variáveis e desenvolvemos modelos de classificação para discriminação de predições de espécies de bactérias classificadas como corretas ou incorretas. Comparamos o desempenho dos resultados obtidos entre as meta-ômicas individuais e os obtidos através da integração observando o balanceamento entre a precisão e a sensibilidade. De acordo com as medidas calculadas com nossos conjuntos de dados, nossa abordagem demonstrou melhorias na classificação com a redução de FPs e aumentos para a medida F1, quando comparada com abordagens não integrativas, inclusive com o uso de métodos de combinação de classificadores. Para facilitar seu uso, desenvolvemos o Gunga, uma ferramenta que incorpora a abordagem desenvolvida em formato de pacote do R, com funcionalidades para a integração de dados de classificação taxonômica com diferentes meta-ômicas e a classificação das predições incorretas. / Microbial communities play important roles in processes that occur in diverse environments, such as soils, oceans, and the gastrointestinal tract of humans. Therefore, it is of interest to understand the structure and functioning of these communities. The structure of these communities, in terms of component organisms, can be determined by the use of the next generation sequencing in conjunction with the meta-omics techniques and by the taxonomic analysis of the sequences obtained with taxonomic classification programs. If on the one hand several programs are available, on the other hand they make mistakes, such as the partial identification of the organisms present in the sample and the identification of organisms that are not present in the sample (the false positives - FPs). Some approaches have been proposed to improve the taxonomic classifications obtained by these programs with the reduction of these FPs, but they address only one type of meta-omics, the metagenomics. In this work, we propose a new approach by integrating different meta-omics - shotgun and 16S amplicon metagenomics, and metatranscriptomics. We explored the classifications results of simulated data and mocks for variable extraction and developed classification models for discriminating predictions of bacterial species classified as correct or incorrect. We compared the performance of the results obtained between the individual meta-omics and the obtained through the integration observing the balance between precision and sensitivity. According to the measures calculated with our data sets, our approach has shown improvements in the classification with the reduction of the FPs and increases for the F1 measure, when compared to non-integrative approaches, including the use of classifiers combination methods. To facilitate its use, we developed the Gunga, a tool that incorporates the developed approach in R package format, with features for the integration of taxonomic classification data with different meta-omics and the classification of the incorrect predictions.

De acuerdo con la literatura científica, la frecuencia del acortamiento de los isquiotibiales, está relacionado con factores genéticos, hábitos diarios y actividades deportivas. Sin embargo, con las numerosas metodologías de tratamiento propuestas en la literatura se hace difícil establecer cuál de ellas resulta ser la más efectiva. En este trabajo se llevó a cabo meta-análisis sobre la eficacia de los tratamientos para la ganancia de flexibilidad en los músculos isquiotibiales. La búsqueda de la literatura permitió identificar 41 estudios, 39 publicados y 2 no publicados, entre 1930 y 2007, que cumplieron con los criterios de inclusión, totalizando 85 comparaciones entre grupo tratado y control. El índice del tamaño del efecto utilizado fue la diferencia de medias estandarizada. Los tratamientos obtuvieron una efectividad estadísticamente significativa (d+ = 1,054). El estiramiento muscular, más la combinación de estiramiento más calentamiento resultaron ser los tratamientos más efectivos. La relación entre el tamaño del efecto con las demás variables de tratamiento, de sujeto, metodológicas y extrínsecas, también fueron examinadas. El sesgo de publicación no fue una amenaza contra la validez de los resultados. Los tratamientos son más eficaces cuando: son empleados en sujetos del género femenino; cuanto más jóvenes sean los sujetos; y cuando se utiliza un número mayor de semanas de tratamiento. / According to the scientific literature, the frequency of the shortened hamstring, is related to genetic factors, daily habits and sports activities. In spite of the found treatment methodologies diversity is difficult to establish which of them is more effective. In this paper we carried out a meta-analysis about the efficacy of the treatment for the increase the flexibility in the hamstring muscle. The searched of the literature enabled us identify 41 studies, 39 published and 2 no published, between 1930 and 2007, that fulfilled our the selection criteria, giving a total 85 comparisons between a treated an a control group. The effect size index was the standardized mean difference in the posttest. The treatments obtained a statistically significant effectiveness (d+ = 1,054). The stretching and stretching plus warming -up resulted to be the treatment more effective. The relationship of others treatment, subjects, methodological and extrinsic variables with the effect size were also examined. The publication bias was not a threat against the validity of the results. The treatments are more efficient when: they are applied in subjects of the feminine gender; the more young be the subjects and when a greater number of weeks of treatment are utilized

To understand the etiology of psychopathic personality traits and thus in the long run to be able to develop successful prevention, a first step is to find out what role genetic and environmental effects play. A meta-review of 15 twin studies (N=26, 981), was conducted to estimate the magnitude of genetic and environmental influences on psychopathic personality traits. The results show that additive genetic (heritable) factors and non-shared environmental factors each explain 50% of the variance in psychopathic personality traits, while shared environmental factors were of no importance. Measure, informant, age, and sex were investigated as potential moderators showing that informant had an impact on the findings. This meta-analysis provides a structured synthesis of the relative genetic and environmental contributions in psychopathic personality traits through various stages of development and across sex. / För att förstå etiologin av psykopatiska personlighetsdrag och därmed i det långa loppet kunna utveckla framgångsrik prevention, är ett första steg att klargöra vilken roll genetiska och miljömässiga effekter spelar. En meta-översikt på 15 tvillingstudier (N=26,981), genomfördes för att uppskatta i vilken grad genetiska och miljömässiga faktorer påverkar psykopatiska personlighetsdrag. Resultaten visade att additiva genetiska (ärftliga) och unika miljömässiga faktorer förklarar 50% var av variansen i psykopatiska personlighetsdrag, medan delade miljömässiga faktorer inte var av betydelse. Mått, informant, ålder och kön undersöktes som potentiella moderatorer och visade att informant påverkade resultaten. Denna meta-analys ger en strukturerad syntes av de relativa genetiska och miljömässiga bidrag som påverkar psykopatiska personlighetsdrag genom olika utvecklingsstadier och mellan könen.

Interactions between cyanobacteria and herbivorous grazers play an important role in mediating the responses of freshwater phytoplankton assemblages to nutrient enrichment and top-down manipulation. Negative consequences associated with these interactions include dangerous blooms of harmful blue-green algae that have been implicated in the sickness and death of fishes, livestock, and, in extreme cases, humans. Frequently cited mechanisms influencing the interactions between grazers and cyanobacteria include cyanobacterial toxicity and morphology. To tease apart the importance of these mechanisms, I used meta-analysis to quantitatively synthesize the available literature on this topic. In addition, I conducted several experiments using novel techniques to determine the effect that cyanobacterial secondary metabolites from the bloom-forming cyanobacterium,

<p>VizzAnalyzer is a program analysis tool that can be used for analyzing software programs. It relies on so called Front-Ends for information extraction from various sources like C or Java source code. It allows analyzing different source code by mapping the language specific front-end meta-model onto a common meta-model, on which analysis are defined. Right now we use the Eclipse Parser for parsing Java source code. This requires an Eclipse installation involving a large number of dependencies in order to work with Java source code. Yet, this is not always feasible; we want to be independent from Eclipse using an alternative parser.</p><p>Recoder is a Java meta-programming application program interface (API) that can be used to write Java programs that manipulate and analyze other Java programs. The Recoder framework provides over an application programming interface detailed access to the source code in form of an abstract syntax tree (AST). It has a small footprint and no external dependencies.</p><p>We create the Recoder Front-End as alternative to the existing Eclipse front-end. This includes the definition of a mapping between Recoder Front-End Meta-Model to Common Meta-Model. The mapping result will be used by VizzAnalyzer to do further analysis work. This Bachelor thesis documents relevant theory regarding Recoder Front-End and discusses its development and implementation.</p>

Vitamin K has a negligible effect on bone mineral density (BMD) and a large but uncertain effect on fractures. The three studies in the thesis explored uncertainty about the effect of vitamin K on fractures using the methods of economic evaluation and Bayesian meta-analysis. In study 1, a Markov probabilistic microsimulation model was developed for a hypothetical cohort of 50-year-old postmenopausal women without osteoporosis. This was a fracture incidence-based model, populated with data from the literature. It was used to examine the cost-effectiveness of two supplementation strategies over a lifetime horizon. We compared vitamin K2 (or vitamin K1) concurrent with vitamin D3 and calcium versus vitamin D3 and calcium alone. Study 2 included a systematic review, and classical and Bayesian univariate meta-analyses to determine the efficacies of the K vitamins on BMD or fractures in current and future trials. Study 3 used Bayesian bivariate random-effects meta-analysis to jointly model the treatment effects on two correlated bone outcomes. We compared the estimates from the univariate and bivariate meta-analyses and explored how these results would change the conclusions of the cost-effectiveness analysis. The strategies including vitamin K were highly cost-effective at willingness-to-pay of $50,000/QALY (quality-adjusted life year); however, the results were most sensitive to changes in the efficacy of vitamin K. The univariate meta-analyses showed large uncertainties in the anti-fracture effects of vitamin K2 in current and future trials. The bivariate 95% credible intervals were considerably narrower than those from the univariate meta-analyses. Using future odds ratios from the bivariate meta-analyses, vitamin K2 cost more than $100,000/QALY while vitamin K1 was cost-saving. Our analyses found substantial uncertainty around the estimates of the vitamin K effect on fractures. We recommend against routine use of vitamin K for fracture prevention. Bayesian bivariate meta-analysis accounts for all available information and should be considered when the treatment effects are measured on two correlated outcomes.

Vitamin K has a negligible effect on bone mineral density (BMD) and a large but uncertain effect on fractures. The three studies in the thesis explored uncertainty about the effect of vitamin K on fractures using the methods of economic evaluation and Bayesian meta-analysis. In study 1, a Markov probabilistic microsimulation model was developed for a hypothetical cohort of 50-year-old postmenopausal women without osteoporosis. This was a fracture incidence-based model, populated with data from the literature. It was used to examine the cost-effectiveness of two supplementation strategies over a lifetime horizon. We compared vitamin K2 (or vitamin K1) concurrent with vitamin D3 and calcium versus vitamin D3 and calcium alone. Study 2 included a systematic review, and classical and Bayesian univariate meta-analyses to determine the efficacies of the K vitamins on BMD or fractures in current and future trials. Study 3 used Bayesian bivariate random-effects meta-analysis to jointly model the treatment effects on two correlated bone outcomes. We compared the estimates from the univariate and bivariate meta-analyses and explored how these results would change the conclusions of the cost-effectiveness analysis. The strategies including vitamin K were highly cost-effective at willingness-to-pay of $50,000/QALY (quality-adjusted life year); however, the results were most sensitive to changes in the efficacy of vitamin K. The univariate meta-analyses showed large uncertainties in the anti-fracture effects of vitamin K2 in current and future trials. The bivariate 95% credible intervals were considerably narrower than those from the univariate meta-analyses. Using future odds ratios from the bivariate meta-analyses, vitamin K2 cost more than $100,000/QALY while vitamin K1 was cost-saving. Our analyses found substantial uncertainty around the estimates of the vitamin K effect on fractures. We recommend against routine use of vitamin K for fracture prevention. Bayesian bivariate meta-analysis accounts for all available information and should be considered when the treatment effects are measured on two correlated outcomes.

In this thesis we will be concerned with a particular type of architecture for reasoning systems, known as meta-level architectures. After presenting the arguments for such architectures (chapter 1), we discuss a number of systems in the literature that provide an explicit meta-level architecture (chapter 2), and these systems are compared on the basis of a number of distinguishing characteristics. This leads to a classification of meta-level architectures (chapter 3). Within this classification we compare the different types of architectures, and argue that one of these types, called bilingual meta-level inference systems, has a number of advantages over the other types. We study the general structure of bilingual meta-level inference architectures (chapter 4), and we discuss the details of a system that we implemented which has this architecture (chapter 5). One of the problems that this type of system suffers from is the overhead that is incurred by the meta-level effort. We give a theoretical model of this problem, and we perform measurements which show that this problem is indeed a significant one (chapter 6). Chapter 7 discusses partial evaluation, the main technique available in the literature to reduce the meta-level overhead. This technique, although useful, suffers from a number of serious problems. We propose two further techniques, partial reflection and many-sorted logic (chapters 8 and 9), which can be used to reduce the problem of meta-level overhead without suffering from these problems.

Objectives: The aim of this dissertation was to examine bias in randomized controlled trials (RCTs) and non-randomized studies (NRS) in surgery using the literature evaluating laparoscopy and conventional (i.e. open) surgery for the treatment of colon cancer as a case study. The objectives were 1) to develop a conceptual framework for bias in comparative NRS; 2) to compare effect estimates from NRS with those from RCTs at low risk of bias; 3) to explore the impact of NRS-design attributes on estimates of treatment effect. Methods: The methods included a modified framework synthesis, systematic review of the literature, random-effects meta-analyses, and frequentist and Bayesian meta-regression. The Cochrane Risk of Bias Tool was used to classify trials as Strong RCTs (i.e. low risk of bias) or Typical RCTs (i.e. unclear or high risk of bias). Results: A conceptual framework for bias in comparative NRS was developed and it contains 37 individual sources of bias or “items”. These items were organized within 6 overarching “domains”: selection bias, information bias, performance bias, detection bias, attrition bias, and selective reporting bias. Our analyses revealed that NRS were associated with more extreme estimates of benefit for laparoscopy than Strong RCTs when examining subjective outcomes. The odds ratios from NRS were 36% smaller (i.e. demonstrating more benefit for laparoscopy) than those from Strong RCTs for the outcome post-operative complications (Ratio of Odds Ratios, ROR 0.64, [0.42, 0.97], p=0.04). Similar exaggerated benefit was seen among NRS when assessing length of stay, (Difference in Mean Differences, -2.15 days, [-4.08, -0.21], p=0.03). This pattern was not observed with the objective outcomes peri-operative mortality and number of lymph nodes harvested. Analyses adjusted for period effects and between-study case-mix yielded similar findings. Finally, effect estimates in NRS did not consistently vary according to the presence or absence of nine design characteristics identified from the conceptual framework. Conclusions: We have demonstrated that the results of surgical NRS can be significantly biased as compared with those of low risk of bias RCTs when evaluating subjective outcomes. However, none of the nine NRS-design characteristics examined was consistently associated with biased effect estimates.

Objectives: The aim of this dissertation was to examine bias in randomized controlled trials (RCTs) and non-randomized studies (NRS) in surgery using the literature evaluating laparoscopy and conventional (i.e. open) surgery for the treatment of colon cancer as a case study. The objectives were 1) to develop a conceptual framework for bias in comparative NRS; 2) to compare effect estimates from NRS with those from RCTs at low risk of bias; 3) to explore the impact of NRS-design attributes on estimates of treatment effect. Methods: The methods included a modified framework synthesis, systematic review of the literature, random-effects meta-analyses, and frequentist and Bayesian meta-regression. The Cochrane Risk of Bias Tool was used to classify trials as Strong RCTs (i.e. low risk of bias) or Typical RCTs (i.e. unclear or high risk of bias). Results: A conceptual framework for bias in comparative NRS was developed and it contains 37 individual sources of bias or “items”. These items were organized within 6 overarching “domains”: selection bias, information bias, performance bias, detection bias, attrition bias, and selective reporting bias. Our analyses revealed that NRS were associated with more extreme estimates of benefit for laparoscopy than Strong RCTs when examining subjective outcomes. The odds ratios from NRS were 36% smaller (i.e. demonstrating more benefit for laparoscopy) than those from Strong RCTs for the outcome post-operative complications (Ratio of Odds Ratios, ROR 0.64, [0.42, 0.97], p=0.04). Similar exaggerated benefit was seen among NRS when assessing length of stay, (Difference in Mean Differences, -2.15 days, [-4.08, -0.21], p=0.03). This pattern was not observed with the objective outcomes peri-operative mortality and number of lymph nodes harvested. Analyses adjusted for period effects and between-study case-mix yielded similar findings. Finally, effect estimates in NRS did not consistently vary according to the presence or absence of nine design characteristics identified from the conceptual framework. Conclusions: We have demonstrated that the results of surgical NRS can be significantly biased as compared with those of low risk of bias RCTs when evaluating subjective outcomes. However, none of the nine NRS-design characteristics examined was consistently associated with biased effect estimates.