Background: The use of meta-analysis to combine the results of observational studies is controversial. Despite its common use, methodological work in this area is lacking. Because of the diversity of study designs, exposure and outcome measures, and differential adjustment for confounding variables, the identification of sources of heterogeneity among study effect estimates is particularly important when combining data from observational studies. This thesis presents the results of a study that examines the relative ability of individual participant data (IPD) meta-analysis (which was considered a “gold standard”) and traditional aggregate data (AD) meta-analysis to identify sources of heterogeneity among studies examining mechanical exposure and low back pain (LBP) in workers. Materials and Methods: A systematic literature search was conducted to identify relevant articles. The corresponding author of each article was contacted to request their individual-level data. Because the outcome definitions and exposure measures were not uniform across studies, two sub-studies were conducted 1) to identify sets of outcome definitions that could be combined in a meta-analysis and 2) to develop methods to translate mechanical exposure onto a common metric. IPD analyses were conducted using generalized estimating equation (GEE) regression to identify variables that acted as strong confounders and effect modifiers. Traditional AD meta-analysis was also conducted and potential sources of heterogeneity were tested using meta-regression. Key Findings: (1) Overall, we found an association between both forces and postures on LBP, although the magnitude varied depending on the exposure-outcome combination. Among the outcomes, the ORs tended to be highest for sick leave due to LBP. (2) There was very little evidence of strong confounders in the relationship between mechanical exposure and LBP; thus differential adjustment for confounders in studies would not likely be an important source of heterogeneity in an AD meta-analysis. (3) AD meta-analysis was able to identify the same study-level effect modifiers as IPD meta-analysis, but did not consistently identify individual-level effect modifiers. Both individual-level characteristics (older age and being male), and study-level characteristics (population-based studies and self-reported mechanical exposure), were associated with an increased OR for many of the LBP outcome and mechanical exposure combinations. Conclusion: AD meta-analysis is likely sufficient to detect heterogeneity for study-level factors but is not sufficient to identify individual-level effect modifiers. When the primary source of evidence in a research area is observational studies and when there is controversy despite several systematic reviews, IPD meta-analysis can be used to better understand sources of heterogeneity and provide context

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Cells are complex biological units with advanced signalling systems, a dynamic capacity to adapt to its environment, and the ability to divide and grow. In fact, they are of such high level of complexity that it has deemed extremely difficult or even impossible to completely understand cells as complete units. The search for comprehending the cell has instead been divided into small, relatively isolated research fields, in which simplified models are used to explain cell biology. The result produced through these reductionistic investigations is integral for our current description of biology. However, there comes a time when it is possible to go beyond such simplifications and investigate cell biology at a higher level of complexity. That time is now. This thesis describes the development of mathematical tools to investigate intricate biological systems, with focus on heterogeneous protein interactions. By the use of simulations, real-time measurements and kinetic fits, standard assays for specificity measurements and receptor quantification were scrutinized in order to find optimal experimental settings and reduce labour time as well as reagent cost. A novel analysis platform, called Interaction Map, was characterized and applied on several types of interactions. Interaction Map decomposes a time-resolved binding curve and presents information on the kinetics and magnitude of each interaction that contributed to the curve. This provides a greater understanding of parallel interactions involved in the same biological system, such as a cell. The heterogeneity of the epidermal growth factor receptor (EGFR) system was investigated with Interaction Map applied on data from the instrument LigandTracer, together with complementing manual assays. By further introducing disturbances to the system, such as tyrosine kinase inhibitors and variation in temperature, information was obtained about dimerization, internalization and degradation rates. In the long term, analysis of binding kinetics and combinations of parallel interactions can improve the understanding of complex biomolecular mechanisms in cells and may explain some of the differences observed between cell lines, medical treatments and groups of patients.

Although considerable research has been invested in disentangling the factors limiting species’ ranges at local and continental spatial scales, less attention has been granted to the relationship between species’ spatial distributions and landscape attributes at intermediate spatial scales. This research investigates the spatial relationship between avian species’ distributions (Ontario Breeding Bird Atlas [2001-2005] data) and landcover heterogeneity (Ontario Land Cover [1991-1998] data) in terms of their respective boundary locations (i.e., high rates of change in landcover composition and avian species turnover) in a vulnerable transitional zone in southern Ontario. Significant spatial overlap was found between landcover and avian boundaries. Given that land management decisions are most often made at the regional or landscape scales, this positive spatial relationship has important implications for conservation efforts. Future research should focus on assessing the spatial relationship between landcover heterogeneity and avian species’ distributions for different functional and taxonomic groups.

Although considerable research has been invested in disentangling the factors limiting species’ ranges at local and continental spatial scales, less attention has been granted to the relationship between species’ spatial distributions and landscape attributes at intermediate spatial scales. This research investigates the spatial relationship between avian species’ distributions (Ontario Breeding Bird Atlas [2001-2005] data) and landcover heterogeneity (Ontario Land Cover [1991-1998] data) in terms of their respective boundary locations (i.e., high rates of change in landcover composition and avian species turnover) in a vulnerable transitional zone in southern Ontario. Significant spatial overlap was found between landcover and avian boundaries. Given that land management decisions are most often made at the regional or landscape scales, this positive spatial relationship has important implications for conservation efforts. Future research should focus on assessing the spatial relationship between landcover heterogeneity and avian species’ distributions for different functional and taxonomic groups.

To recover oil remaining in petroleum reservoirs after waterflooding, the gravitationally stable mode of gas injection is recognized as a promising tertiary oil recovery process. Understanding the phenomena occurring over the course of the gravity-assisted inert gas injection (GAIGI) process is thus important. Extensive studies on both secondary and tertiary modes of gravity drainage have shown promising results in recovering oil from homogeneous water-wet glass bead packs, sand packs, and sandstone cores, respectively. However, it is not realistic to anticipate similar flow mechanisms and recovery results in all types of reservoirs because the natural hydrocarbon reservoirs are all heterogeneous in terms of their permeability, porosity, and wettability. Such heterogeneities cause irregular displacement patterns, and nonuniform fluid distribution. The impact of heterogeneity of the porous media on the GAIGI process has not been fully addressed in the experimental studies carried out to date; therefore, this thesis aims to fill in the gap of knowledge on this area. The impact of reservoir wettability and pore structure heterogeneities at the macroscopic scale on the recovery efficiency of the GAIGI process was investigated through a systematic experimental study for tertiary recovery of waterflood residual oil. To obtain heterogeneous (in terms of wettability) packings, isolated inclusions of oil-wet consolidated glass beads were embedded in a continuum of unconsolidated water-wet glass beads. Similarly, the heterogeneous porous media exhibiting permeability heterogeneity consisted of large-pore-size isolated regions randomly distributed in a small-pore-size continuum. Upon waterflooding, significantly higher waterflood residual oil saturation was established in both cases of heterogeneous media in comparison to water-wet homogeneous porous media. The amount of waterflood residual oil varied linearly with the volume fraction of heterogeneities in the packings. Experimental results obtained from tertiary gravity drainage experiments demonstrated that the continuity of water-wet portions of the heterogeneous porous media facilitates the residual oil recovery through the film flow mechanism, provided that the oil spreading coefficient is positive. In addition, owing to the high waterflood residual oil content of the heterogeneous media tested, the oil bank formation occurred earlier and grew faster than that in homogeneous media, resulting in a higher oil recovery factor. However, the favorable wettability conditions in both the homogeneous and heterogeneous porous media exhibiting permeability heterogeneity resulted in slightly lower reduced residual oil saturation after the GAIGI process compared to that in the heterogeneous media with wettability heterogeneity under the same condition of withdrawal rate. In addition, the oil recovery factor at gas breakthrough was found to be inversely related to the production rate due to the functionality of gravity and viscous forces over the course of gravity drainage. These two forces were combined into a dimensionless form, defined as the gravity number (Ngv=Kogg/oVpg). It was discovered that there is a correlation between the oil recovery factor at gas breakthrough and the gravity number for both the heterogeneous and homogeneous media. The correlation of recovery factor at gas breakthrough versus the gravity number in heterogeneous media followed a similar trend as that found for homogeneous water-wet porous media. However, at a given gravity number, the recovery factor in heterogeneous media was greater than that in the homogeneous media. This implies that heterogeneous media will be better target reservoirs for applying the GAIGI process compared to the homogeneous reservoirs.

Background: The use of meta-analysis to combine the results of observational studies is controversial. Despite its common use, methodological work in this area is lacking. Because of the diversity of study designs, exposure and outcome measures, and differential adjustment for confounding variables, the identification of sources of heterogeneity among study effect estimates is particularly important when combining data from observational studies. This thesis presents the results of a study that examines the relative ability of individual participant data (IPD) meta-analysis (which was considered a “gold standard”) and traditional aggregate data (AD) meta-analysis to identify sources of heterogeneity among studies examining mechanical exposure and low back pain (LBP) in workers. Materials and Methods: A systematic literature search was conducted to identify relevant articles. The corresponding author of each article was contacted to request their individual-level data. Because the outcome definitions and exposure measures were not uniform across studies, two sub-studies were conducted 1) to identify sets of outcome definitions that could be combined in a meta-analysis and 2) to develop methods to translate mechanical exposure onto a common metric. IPD analyses were conducted using generalized estimating equation (GEE) regression to identify variables that acted as strong confounders and effect modifiers. Traditional AD meta-analysis was also conducted and potential sources of heterogeneity were tested using meta-regression. Key Findings: (1) Overall, we found an association between both forces and postures on LBP, although the magnitude varied depending on the exposure-outcome combination. Among the outcomes, the ORs tended to be highest for sick leave due to LBP. (2) There was very little evidence of strong confounders in the relationship between mechanical exposure and LBP; thus differential adjustment for confounders in studies would not likely be an important source of heterogeneity in an AD meta-analysis. (3) AD meta-analysis was able to identify the same study-level effect modifiers as IPD meta-analysis, but did not consistently identify individual-level effect modifiers. Both individual-level characteristics (older age and being male), and study-level characteristics (population-based studies and self-reported mechanical exposure), were associated with an increased OR for many of the LBP outcome and mechanical exposure combinations. Conclusion: AD meta-analysis is likely sufficient to detect heterogeneity for study-level factors but is not sufficient to identify individual-level effect modifiers. When the primary source of evidence in a research area is observational studies and when there is controversy despite several systematic reviews, IPD meta-analysis can be used to better understand sources of heterogeneity and provide context

Activated epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations characterize molecular subgroups of non-small cell lung cancer (NSCLC) and have a strong predictive value for response to EGFR inhibitor therapy. Recently, EGFR mutation testing was included in the diagnostic algorithm of NSCLC. However, there is a controversy about the clonal stability of the mutation during the progression of the disease. The aim of this study was to analyze NSCLC tumor tissue for the presence of both EGFR and KRAS mutations in morphologically different parts of the primary tumor. Formaldehyd fixed and paraffin embedded lung cancer specimens from primary resected NSCLC patients were selected; five cases harboring EGFR and five with KRAS mutations. From each tumor, three morphologically different tumor sites were manually micro-dissected and analyzed for the presence of EGFR and KRAS mutations. Additionally, normal lung tissue at a distance from the primary tumor as well as in close vicinity was tested.The EGFR and KRAS status were consistent in the three different areas of the primary tumors of all ten cases. EGFR as well as KRAS mutations were as well detectable in close and in some distant normal lung parenchyma in 7 of 10 analyzed patient samples. In conclusion, we found consistent KRAS and EGFR mutation status in primary NSCLC tumors. This finding is of importance for clinical practice, because it indicates that any part of the tumor, independent of intratumoral histological pattern, is representative for EGFR and KRAS mutation testing.

<p>This dissertation considers the relationship between peer and individual student interaction. The central finding is that self reported friends play a crucial role in individual behaviors, a role that is more significant than other students in their school. Also, using the network of friendships within a school it is possible to construct new peer effect measures and account for endogenous peer group formation. It is however important to distinguish these peer measures from unobserved individual characteristics that may also influence behavior.</p><p>The first chapter examines the effect of potentially misidentifying the reference group on peer effect estimates. The differential impact of school, grade and friend level peer effects on student decisions to smoke and drink are calculated. Friendship nominations come from the Add Health dataset, where students can list up to 10 friends from the school. The bias due to endogenous peer group formation and simulteneity are considered using various instrumenting strategies. Peer effects are found to be large and significant at the friends level for both delinquency variables. It is possible to show that misidentifying the peer group can result in peer effect estimates that are understated by as much as 40\%.</p><p>The second chapter of the dissertation further examines the role of peer interactions, this time considering the effect of popularity on student academic achievement. Recent work has found a strong positive relationship between these variables. In this chapter I ascertain the robustness of these previous findings to controls for unobserved student heterogeneity using and instrumenting technique and a structural model. The results indicate that popularity influences academic achievement positively in the baseline model. However, instrumenting for popularity or including measures of unobserved student characteristics results in a large drop in the effect of popularity, and leads to a significantly negative coefficient in the majority of cases. Interestingly, popularity influences future earnings and attitudes positively, where this effect is robust to the inclusion of unobserved type. Policy simulations where students are redistributed based on race or income indicate that the predicted number of friendships and popularity fall but academic achievement increases. Since student popularity increases happiness and earnings, the overall effect of the redistribution policies have to be considered before implementation.</p> / Dissertation

Geotechnical properties vary in space. Statistical parameters such as mean, deviation, and correlation length are characteristics for each sediment and formation history. The effects of spatial variability on the macro-scale mechanical properties of soils are investigated using Monte Carlo non-linear finite element simulations. Boundary conditions include 1) isotropic loading, 2) zero-lateral strain loading, 3) drained and undrained deviatoric loading, and 4) small-strain wave propagation. Emphasis is placed on identifying the effects of spatial variability on the stiffness and strength of soils, recognizing emergent phenomena, and creating the background for new geotechnical design methods that take into consideration spatial variability. The arithmetic mean of soil properties cannot be used to estimate the stiffness or strength of heterogeneous soils. Greater deviation and longer relative correlation length in the spatial distribution of soil properties yield a softer and weaker mechanical response. Load transfer concentrates along stiffer zones, leading to stress-focusing and lower K0 values. Drained loading promotes internal homogenization. Undrained deviatoric loading can cause percolation of internal weakness and shear strain localization. Spatial heterogeneity adds complexity to elastic wave propagation. Heterogeneous soil mixtures can be engineered to attain unique macroscale behavior