It is evident that the study of proteins is crucial for a deeper understanding of how drug treatments affect the body. However, differential protein expression analysis, which can be described as the method of finding which proteins are affected by a treatment, faces some major challenges. First of all, because proteomics data typically comprise several thousand different proteins for just a small number of biological tissues, there are both problems concerning multiple comparisons and low statistical power. Secondly, proteomics data are prone to suffer high rates of missing values, which could bias the results. One approach to handle these issues, which is gaining popularity, is to apply Bayesian hierarchical modeling in order to pool information from the complete dataset of all proteins when making inferences for each protein individually. Yet, in practice, there seems to be essentially only one Bayesian hierarchical model that currently is being employed, which uses a conjugate prior for the error variances but has no prior for the coefficients or the missing values. Given this, the aim of the thesis is to investigate how the model can be improved by adding priors for the coefficients and the missing values. The results show that by adding a hierarchical prior for the coefficients prediction accuracy may be increased. Furthermore, the results show that by adding a prior for the missing values differently expressed proteins can be detected that otherwise would have been overlooked.

No description available.

No description available.

No description available.

No description available.

No description available.

1. O manejo da vida silvestre em matrizes antropizadas, fora de reservas naturais, é importante para melhorar a eficácia de esforços conservacionistas que visam proteger e restaurar a biodiversidade. Desta forma, é fundamental entender as características da matriz que aumentam a adequabilidade do habitat para as espécies remanescentes e também avaliar as respostas das espécies à práticas de manejo alternativas. 2. Neste estudo utilizamos uma abordagem de modelagem hierárquica, que leva em conta o efeito de falhas de detectabilidade das espécies, para estimar o efeito de práticas de manejo adotadas dentro de talhões de plantios de Eucalyptus sobre a ocupação de aves. Nossos modelos incorporam características sítio-específicas, como tipo de prática de manejo e o contexto da paisagem em que se inserem cada unidade amostral. Também incorpora características espécie-específicas, em particular à sensibilidade das espécies aos distúrbios e estrato de forrageio. 3. O principal fator associado a diferenças na ocupação de aves dentro de nossa área de estudo é o tipo de pratica de manejo. A presença de árvores nativas dispersas e de sub-bosque em estágio inicial de sucessão dentro dos talhões está associada com um aumento na proporção de espécies do pool regional capaz de ocupar a matriz silvicultural. O contexto da paisagem teve um efeito relativamente menor sobre a ocupação de aves na área de estudo. 4. Síntese e Aplicação. A ocupação de aves está associada positivamente ao aumento da complexidade estrutural dentro dos talhões de eucalipto, as espécies respondem a retenção de árvores nativas dispersas e a presença de sub-bosque. Gerenciadores interessados em aumentar o valor conservacionista de plantios de Eucalyptus para as aves deveriam preservar as arvores maduras e adotar práticas que estimulem a regeneração do sub-bosque durante o preparo do local e rotação do plantio. / 1. Managing for wildlife in human-dominated matrices outside natural reserves has great importance to improve the efficacy of conservation efforts aiming to protect and restore biodiversity. As such, it is critical to understand which features of the matrix that enhance habitat suitability to the remaining species and also to evaluate species responses to alternative management practices. 2. We used hierarchical modeling to estimate the effect of stand level management practices adopted in Eucalyptus plantations on bird occupancy while accounting for species detection failure. Our models incorporate site- specific traits, such as management practice type and the landscape context of each sampling unit. It also incorporates species specific-traits, particularly species sensitivity to disturbance and species foraging stratum. 3. The major factor associated with differences in bird occupancy within our study site is the management practice type. Scattered native trees and early successional stage understory within mature stands was associated with an increase in the proportion of bird species from the regional pool that was able to occupy the silvicultural matrix. Landscape context had a relatively minor effect on bird occupancy in our study area. 4. Synthesis and applications. Bird occupancy is positively associated with increasing spatial heterogeneity within eucalyptus stands with species responding to the retention of native scattered trees and understory presence. Managers interested in improving the conservation value of Eucalyptus plantations to birds should preserve some existing trees and adopt practices that trigger understory regeneration during site preparation and stand rotation.

<p>In type 2 diabetes the concentration of glucose in the blood is increased, and tissues like fat and musclebecome less sensitive to insulin. These two phenomena are interrelated, but since the glucose-insulininterplay is highly complex, many aspects are still not understood. Here, a model-based approachmight help. Nevertheless, also a model-based approach has a limited impact, unless models for thesub-systems can be combined into a model for the whole-body regulation. Such a multi-level,module-based model is referred to as a hierarchical model, and this thesis is a proof-of-principle studyfor the future development of such models.</p><p>We have extended one of the best available models for the whole-body regulations, to include azoomable module for the fat tissue. The first step was to implement the whole-body model in thesoftware MathModelica, which support hierarchical modeling. Second, the originally mergedinsulin-responding module was sub-divided, so that a fat tissue was singled out. Third, a model for theinput-output profile for the fat tissue was developed by combining mechanistic knowledge withexisting and novel data from human fat cells. Finally, this detailed model was fitted to the profile of theoriginal fat model, and inserted in the whole-body model, with negligible effect on the whole-bodysimulations.</p><p>The resulting model has the ability to translate mechanistically oriented simulations on the biochemicallevel, which is the level were drugs act, to the whole-body level, which is of clinical interest. This is aquantum leap forward for modeling, and understanding, glucose homeostasis and type 2 diabetes.</p>

<p>This dissertation examines issues concerning sap flux scaled estimates of the canopy-averaged transpiration rate of trees per unit leaf area (E_L) and stomatal conductance (G_S), as well as their implications in the water and carbon balance of individuals and stands, with the final goal of an integrated assessment of 11 years of such data from two species (<italic>Pinus taeda</italic> and <italic>Liquidambar styraciflua</italic>) at the Duke Free Air Carbon dioxide Enrichment (Duke FACE) facility. These issues include (1) the effects of allometric relationships and xylem characteristics on the gas phase transport of water from leaves and the hydraulic supply of it, (2) consideration of the hydraulic capacitance in the inference of stomatal behavior from sap flux data and (3) the dynamic modeling of stomatal conductance to environmental drivers using Bayesian techniques. It is shown that a) for resolution of sap flux in conifers at the scale of minutes under dynamic conditions, time constants for both stomatal responses and hydraulic capacitance of sapwood must be considered, (b) nighttime conductance can lead to large errors in rates of sap flux measured under some conditions, (c) variation in allometry between <italic>P. taeda</italic> individuals can lead to different rates of transpiration and carbon assimilation per unit leaf area and that (d) hydraulic time constants for the stems of mature <italic>P. taeda</italic> at Duke FACE trees varied by the stem length considered and were on the order of 30-45 minutes for a 10-m segment. An analysis incorporating all these elements leads to the conclusions that (e) both elevated CO₂ (eCO₂) and fertilization (FR) resulted in proportionally larger reductions in the E_L and G_S of P. taeda as soil moisture decreased with (f) eCO₂ having little to no effect in months of high soil moisture and (g) FR leading to ~14% reduction of GS under high soil moisture in absence of eCO₂, while (h) both eCO₂ and FR led to reduced E_L and G_S of <italic>L. styraciflua</italic> across soil moisture conditions.</p> / Dissertation

In type 2 diabetes the concentration of glucose in the blood is increased, and tissues like fat and musclebecome less sensitive to insulin. These two phenomena are interrelated, but since the glucose-insulininterplay is highly complex, many aspects are still not understood. Here, a model-based approachmight help. Nevertheless, also a model-based approach has a limited impact, unless models for thesub-systems can be combined into a model for the whole-body regulation. Such a multi-level,module-based model is referred to as a hierarchical model, and this thesis is a proof-of-principle studyfor the future development of such models. We have extended one of the best available models for the whole-body regulations, to include azoomable module for the fat tissue. The first step was to implement the whole-body model in thesoftware MathModelica, which support hierarchical modeling. Second, the originally mergedinsulin-responding module was sub-divided, so that a fat tissue was singled out. Third, a model for theinput-output profile for the fat tissue was developed by combining mechanistic knowledge withexisting and novel data from human fat cells. Finally, this detailed model was fitted to the profile of theoriginal fat model, and inserted in the whole-body model, with negligible effect on the whole-bodysimulations. The resulting model has the ability to translate mechanistically oriented simulations on the biochemicallevel, which is the level were drugs act, to the whole-body level, which is of clinical interest. This is aquantum leap forward for modeling, and understanding, glucose homeostasis and type 2 diabetes.