MODELING SPORADIC TUMOR FORMATION DRIVEN BY TELOMERE DYSFUNCTION IN THE GASTROINTESTINAL TRACT

Colorectal cancer is a complex disease that is thought to arise when cells accumulate mutations that allow for uncontrolled growth. There are several recognized mechanisms for generating such mutations in sporadic colon cancer; one of which is chromosomal instability (CIN). One hypothesized driver of CIN in cancer is the improper repair of dysfunctional telomeres. Telomeres comprise the linear ends of chromosomes and play a dual role in cancer. Its length is maintained by the ribonucleoprotein, telomerase, which is not a normally expressed in somatic cells and as cells divide, telomeres continuously shorten. Critically shortened telomeres are considered dysfunctional as they are recognized as sites of DNA damage and cells respond by entering into replicative senescence or apoptosis, a process that is p53-dependent and the mechanism for telomere-induced tumor suppression. Loss of this checkpoint and improper repair of dysfunctional telomeres can initiate a cycle of fusion, bridge and breakage that can lead to chromosomal changes and genomic instability, a process that can lead to transformation of normal cells to cancer cells. Mouse models of telomere dysfunction are currently based on knocking out the telomerase protein or RNA component; however, the naturally long telomeres of mice require multiple generational crosses of telomerase null mice to achieve critically short telomeres. Shelterin is a complex of six core proteins that bind to telomeres specifically. Pot1a is a highly conserved member of this complex that specifically binds to the telomeric single-stranded 3’ G-rich overhang. Previous work in our lab has shown that Pot1a is essential for chromosomal end protection as deletion of Pot1a in murine embryonic fibroblasts (MEFs) leads to open telomere ends that initiate a DNA damage response mediated by ATR, resulting in p53-dependent cellular senescence. Loss of Pot1a in the background of p53 deficiency results in increased aberrant homologous recombination at telomeres and elevated genomic instability, which allows Pot1a-/-, p53-/- MEFs to form tumors when injected into SCID mice. These phenotypes are similar to those seen in cells with critically shortened telomeres. In this work, we created a mouse model of telomere ysfunction in the gastrointestinal tract through the conditional deletion of Pot1a that recapitulates the microscopic features seen in severe telomere attrition. Combined intestinal loss of Pot1a and p53 lead to formation of invasive adenocarcinomas in the small and large intestines. The tumors formed with long latency, low multiplicity and had complex genomes due to chromosomal instability, features similar to those seen in sporadic human colorectal cancers. Taken together, we have developed a novel mouse model of intestinal tumorigenesis based on genomic instability driven by telomere dysfunction.

Adolescent Sexual Behavior: Examining Data from Texas and the US

Background: The US has higher rates of teen births and sexually transmitted infections (STI) than other developed countries. Texas youth are disproportionately impacted. Purpose: To review local, state, and national data on teens’ engagement in sexual risk behaviors to inform policy and practice related to teen sexual health. Methods: 2009 middle school and high school Youth Risk Behavior Survey (YRBS) data, and data from All About Youth, a middle school study conducted in a large urban school district in Texas, were analyzed to assess the prevalence of sexual initiation, including the initiation of non-coital sex, and the prevalence of sexual risk behaviors among Texas and US youth. Results: A substantial proportion of middle and high school students are having sex. Sexual initiation begins as early as 6th grade and increases steadily through 12th grade with almost two-thirds of high school seniors being sexually experienced. Many teens are not protecting themselves from unintended pregnancy or STIs – nationally, 80% and 39% of high school students did not use birth control pills or a condom respectively the last time they had sex. Many middle and high school students are engaging in oral and anal sex, two behaviors which increase the risk of contracting an STI and HIV. In Texas, an estimated 689,512 out of 1,327,815 public high school students are sexually experienced – over half (52%) of the total high school population. Texas students surpass their US peers in several sexual risk behaviors including number of lifetime sexual partners, being currently sexually active, and not using effective methods of birth control or dual protection when having sex. They are also less likely to receive HIV/AIDS education in school. Conclusion: Changes in policy and practice, including implementation of evidence-based sex education programs in middle and high schools and increased access to integrated, teen-friendly sexual and reproductive health services, are urgently needed at the state and national levels to address these issues effectively.

Volcanic forcing for climate modeling: a new microphysics-based data set covering years 1600–present

As the understanding and representation of the impacts of volcanic eruptions on climate have improved in the last decades, uncertainties in the stratospheric aerosol forcing from large eruptions are now linked not only to visible optical depth estimates on a global scale but also to details on the size, latitude and altitude distributions of the stratospheric aerosols. Based on our understanding of these uncertainties, we propose a new model-based approach to generating a volcanic forcing for general circulation model (GCM) and chemistry–climate model (CCM) simulations. This new volcanic forcing, covering the 1600–present period, uses an aerosol microphysical model to provide a realistic, physically consistent treatment of the stratospheric sulfate aerosols. Twenty-six eruptions were modeled individually using the latest available ice cores aerosol mass estimates and historical data on the latitude and date of eruptions. The evolution of aerosol spatial and size distribution after the sulfur dioxide discharge are hence characterized for each volcanic eruption. Large variations are seen in hemispheric partitioning and size distributions in relation to location/date of eruptions and injected SO2 masses. Results for recent eruptions show reasonable agreement with observations. By providing these new estimates of spatial distributions of shortwave and long-wave radiative perturbations, this volcanic forcing may help to better constrain the climate model responses to volcanic eruptions in the 1600–present period. The final data set consists of 3-D values (with constant longitude) of spectrally resolved extinction coefficients, single scattering albedos and asymmetry factors calculated for different wavelength bands upon request. Surface area densities for heterogeneous chemistry are also provided.

Modeling Englacial Radar Attenuation at Siple Dome, West Antarctica, Using Ice Chemistry and Temperature Data

The radar reflectivity of an ice-sheet bed is a primary measurement for discriminating between thawed and frozen beds. Uncertainty in englacial radar attenuation and its spatial variation introduces corresponding uncertainty in estimates of basal reflectivity. Radar attenuation is proportional to ice conductivity, which depends on the concentrations of acid and sea-salt chloride and the temperature of the ice. We synthesize published conductivity measurements to specify an ice-conductivity model and find that some of the dielectric properties of ice at radar frequencies are not yet well constrained. Using depth profiles of ice-core chemistry and borehole temperature and an average of the experimental values for the dielectric properties, we calculate an attenuation rate profile for Siple Dome, West Antarctica. The depth-averaged modeled attenuation rate at Siple Dome (20.0 +/- 5.7 dB km(-1)) is somewhat lower than the value derived from radar profiles (25.3 +/- 1.1 dB km(-1)). Pending more experimental data on the dielectric properties of ice, we can match the modeled and radar-derived attenuation rates by an adjustment to the value for the pure ice conductivity that is within the range of reported values. Alternatively, using the pure ice dielectric properties derived from the most extensive single data set, the modeled depth-averaged attenuation rate is 24.0 +/- 2.2 dB km(-1). This work shows how to calculate englacial radar attenuation using ice chemistry and temperature data and establishes a basis for mapping spatial variations in radar attenuation across an ice sheet.

Experimental, theoretical and numerical investigation of the nonlinear micromechanical properties of bone

Aging societies suffer from an increasing incidence of bone fractures. Bone strength depends on the amount of mineral measured by clinical densitometry, but also on the micromechanical properties of the bone hierarchical organization. A good understanding has been reached for elastic properties on several length scales, but up to now there is a lack of reliable postyield data on the lower length scales. In order to be able to describe the behavior of bone at the microscale, an anisotropic elastic-viscoplastic damage model was developed using an eccentric generalized Hill criterion and nonlinear isotropic hardening. The model was implemented as a user subroutine in Abaqus and verified using single element tests. A FE simulation of microindentation in lamellar bone was finally performed show-ing that the new constitutive model can capture the main characteristics of the indentation response of bone. As the generalized Hill criterion is limited to elliptical and cylindrical yield surfaces and the correct shape for bone is not known, a new yield surface was developed that takes any convex quadratic shape. The main advantage is that in the case of material identification the shape of the yield surface does not have to be anticipated but a minimization results in the optimal shape among all convex quadrics. The generality of the formulation was demonstrated by showing its degeneration to classical yield surfaces. Also, existing yield criteria for bone at multiple length scales were converted to the quadric formulation. Then, a computational study to determine the influence of yield surface shape and damage on the in-dentation response of bone using spherical and conical tips was performed. The constitutive model was adapted to the quadric criterion and yield surface shape and critical damage were varied. They were shown to have a major impact on the indentation curves. Their influence on indentation modulus, hardness, their ratio as well as the elastic to total work ratio were found to be very well described by multilinear regressions for both tip shapes. For conical tips, indentation depth was not a significant fac-tor, while for spherical tips damage was insignificant. All inverse methods based on microindentation suffer from a lack of uniqueness of the found material properties in the case of nonlinear material behavior. Therefore, monotonic and cyclic micropillar com-pression tests in a scanning electron microscope allowing a straightforward interpretation comple-mented by microindentation and macroscopic uniaxial compression tests were performed on dry ovine bone to identify modulus, yield stress, plastic deformation, damage accumulation and failure mecha-nisms. While the elastic properties were highly consistent, the postyield deformation and failure mech-anisms differed between the two length scales. A majority of the micropillars showed a ductile behavior with strain hardening until failure by localization in a slip plane, while the macroscopic samples failed in a quasi-brittle fashion with microcracks coalescing into macroscopic failure surfaces. In agreement with a proposed rheological model, these experiments illustrate a transition from a ductile mechanical behavior of bone at the microscale to a quasi-brittle response driven by the growth of preexisting cracks along interfaces or in the vicinity of pores at the macroscale. Subsequently, a study was undertaken to quantify the topological variability of indentations in bone and examine its relationship with mechanical properties. Indentations were performed in dry human and ovine bone in axial and transverse directions and their topography measured by AFM. Statistical shape modeling of the residual imprint allowed to define a mean shape and describe the variability with 21 principal components related to imprint depth, surface curvature and roughness. The indentation profile of bone was highly consistent and free of any pile up. A few of the topological parameters, in particular depth, showed significant correlations to variations in mechanical properties, but the cor-relations were not very strong or consistent. We could thus verify that bone is rather homogeneous in its micromechanical properties and that indentation results are not strongly influenced by small de-viations from the ideal case. As the uniaxial properties measured by micropillar compression are in conflict with the current literature on bone indentation, another dissipative mechanism has to be present. The elastic-viscoplastic damage model was therefore extended to viscoelasticity. The viscoelastic properties were identified from macroscopic experiments, while the quasistatic postelastic properties were extracted from micropillar data. It was found that viscoelasticity governed by macroscale properties has very little influence on the indentation curve and results in a clear underestimation of the creep deformation. Adding viscoplasticity leads to increased creep, but hardness is still highly overestimated. It was possible to obtain a reasonable fit with experimental indentation curves for both Berkovich and spherical indenta-tion when abandoning the assumption of shear strength being governed by an isotropy condition. These results remain to be verified by independent tests probing the micromechanical strength prop-erties in tension and shear. In conclusion, in this thesis several tools were developed to describe the complex behavior of bone on the microscale and experiments were performed to identify its material properties. Micropillar com-pression highlighted a size effect in bone due to the presence of preexisting cracks and pores or inter-faces like cement lines. It was possible to get a reasonable fit between experimental indentation curves using different tips and simulations using the constitutive model and uniaxial properties measured by micropillar compression. Additional experimental work is necessary to identify the exact nature of the size effect and the mechanical role of interfaces in bone. Deciphering the micromechanical behavior of lamellar bone and its evolution with age, disease and treatment and its failure mechanisms on several length scales will help preventing fractures in the elderly in the future.

Resolving diffusion in clay minerals at different time scales: Combination of experimental and modeling approaches

Since no single experimental or modeling technique provides data that allow a description of transport processes in clays and clay minerals at all relevant scales, several complementary approaches have to be combined to understand and explain the interplay between transport relevant phenomena. In this paper molecular dynamics simulations (MD) were used to investigate the mobility of water in the interlayer of montmorillonite (Mt), and to estimate the influence of mineral surfaces and interlayer ions on the water diffusion. Random Walk (RW) simulations based on a simplified representation of pore space in Mt were used to estimate and understand the effect of the arrangement of Mt particles on the meso- to macroscopic diffusivity of water. These theoretical calculations were complemented with quasielastic neutron scattering (QENS) measurements of aqueous diffusion in Mt with two pseudo-layers of water performed at four significantly different energy resolutions (i.e. observation times). The size of the interlayer and the size of Mt particles are two characteristic dimensions which determine the time dependent behavior of water diffusion in Mt. MD simulations show that at very short time scales water dynamics has the characteristic features of an oscillatory motion in the cage formed by neighbors in the first coordination shell. At longer time scales, the interaction of water with the surface determines the water dynamics, and the effect of confinement on the overall water mobility within the interlayer becomes evident. At time scales corresponding to an average water displacement equivalent to the average size of Mt particles, the effects of tortuosity are observed in the meso- to macroscopic pore scale simulations. Consistent with the picture obtained in the simulations, the QENS data can be described using a (local) 3D diffusion at short observation times, whereas at sufficiently long observation times a 2D diffusive motion is clearly observed. The effects of tortuosity measured in macroscopic tracer diffusion experiments are in qualitative agreement with RW simulations. By using experimental data to calibrate molecular and mesoscopic theoretical models, a consistent description of water mobility in clay minerals from the molecular to the macroscopic scale can be achieved. In turn, simulations help in choosing optimal conditions for the experimental measurements and the data interpretation. (C) 2014 Elsevier B.V. All rights reserved.

Appraisal-driven somatovisceral response patterning: effects of intrinsic pleasantness and goal conduciveness.

Several componential emotion theories suggest that appraisal outcomes trigger characteristic somatovisceral changes that facilitate information processing and prepare the organism for adaptive behavior. The current study tested predictions derived from Scherer's Component Process Model. Participants viewed unpleasant and pleasant pictures (intrinsic pleasantness appraisal) and were asked to concurrently perform either an arm extension or an arm flexion, leading to an increase or a decrease in picture size. Increasing pleasant stimuli and decreasing unpleasant stimuli were considered goal conducive; decreasing pleasant stimuli and increasing unpleasant stimuli were considered goal obstructive (goal conduciveness appraisal). Both appraisals were marked by several somatovisceral changes (facial electromyogram, heart rate (HR)). As predicted, the changes induced by the two appraisals showed similar patterns. Furthermore, HR results, compared with data of earlier studies, suggest that the adaptive consequences of both appraisals may be mediated by stimulus proximity.

A fixed-links modeling approach to assess individual differences in the attentional blink: Analysis of behavioral and psychophysiological data

The attentional blink (AB) is a fundamental limitation of the ability to select relevant information from irrelevant information. It can be observed with the detection rate in an AB task as well as with the corresponding P300 amplitude of the event-related potential. In previous research, however, correlations between these two levels of observation were weak and rather inconsistent. A possible explanation of this finding might be that multiple processes underlie the AB and, thus, obscure a possible relationship between AB-related detection rate and the corresponding P300 amplitude. The present study investigated this assumption by applying a fixed-links modeling approach to represent behavioral individual differences in the AB as a latent variable. Concurrently, this approach enabled us to control for additional sources of variance in AB performance by deriving two additional latent variables. The correlation between the latent variable reflecting behavioral individual differences in AB magnitude and a corresponding latent variable derived from the P300 amplitude was high (r=.70). Furthermore, this correlation was considerably stronger than the correlations of other behavioral measures of the AB magnitude with their psychophysiological counterparts (all rs<.40). Our findings clearly indicate that the systematic disentangling of various sources of variance by utilizing the fixed-links modeling approach is a promising tool to investigate behavioral individual differences in the AB and possible psychophysiological correlates of these individual differences.

Modeling postglacial vegetation dynamics of temperate forests on the Olympic Peninsula (WA, USA) with special regard to snowpack

Past and future forest composition and distribution in temperate mountain ranges is strongly influenced by temperature and snowpack. We used LANDCLIM, a spatially explicit, dynamic vegetation model, to simulate forest dynamics for the last 16,000 years and compared the simulation results to pollen and macrofossil records at five sites on the Olympic Peninsula (Washington, USA). To address the hydrological effects of climate-driven variations in snowpack on simulated forest dynamics, we added a simple snow accumulation-and-melt module to the vegetation model and compared simulations with and without the module. LANDCLIM produced realistic present-day species composition with respect to elevation and precipitation gradients. Over the last 16,000 years, simulations driven by transient climate data from an atmosphere-ocean general circulation model (AOGCM) and by a chironomid-based temperature reconstruction captured Late-glacial to Late Holocene transitions in forest communities. Overall, the reconstruction-driven vegetation simulations matched observed vegetation changes better than the AOGCM-driven simulations. This study also indicates that forest composition is very sensitive to snowpack-mediated changes in soil moisture. Simulations without the snow module showed a strong effect of snowpack on key bioclimatic variables and species composition at higher elevations. A projected upward shift of the snow line and a decrease in snowpack might lead to drastic changes in mountain forests composition and even a shift to dry meadows due to insufficient moisture availability in shallow alpine soils.

A LAPLACE TRANSFORM PAIR MODEL TO DETERMINE BREMSSTRAHLUNG SPECTRA FROM ATTENUATION DATA (RADIATION, X-RAY, SPECTRAL MODELING)

Every x-ray attenuation curve inherently contains all the information necessary to extract the complete energy spectrum of a beam. To date, attempts to obtain accurate spectral information from attenuation data have been inadequate.^ This investigation presents a mathematical pair model, grounded in physical reality by the Laplace Transformation, to describe the attenuation of a photon beam and the corresponding bremsstrahlung spectral distribution. In addition the Laplace model has been mathematically extended to include characteristic radiation in a physically meaningful way. A method to determine the fraction of characteristic radiation in any diagnostic x-ray beam was introduced for use with the extended model.^ This work has examined the reconstructive capability of the Laplace pair model for a photon beam range of from 50 kVp to 25 MV, using both theoretical and experimental methods.^ In the diagnostic region, excellent agreement between a wide variety of experimental spectra and those reconstructed with the Laplace model was obtained when the atomic composition of the attenuators was accurately known. The model successfully reproduced a 2 MV spectrum but demonstrated difficulty in accurately reconstructing orthovoltage and 6 MV spectra. The 25 MV spectrum was successfully reconstructed although poor agreement with the spectrum obtained by Levy was found.^ The analysis of errors, performed with diagnostic energy data, demonstrated the relative insensitivity of the model to typical experimental errors and confirmed that the model can be successfully used to theoretically derive accurate spectral information from experimental attenuation data. ^

Bayesian joint modeling of longitudinal and survival data

The joint modeling of longitudinal and survival data is a new approach to many applications such as HIV, cancer vaccine trials and quality of life studies. There are recent developments of the methodologies with respect to each of the components of the joint model as well as statistical processes that link them together. Among these, second order polynomial random effect models and linear mixed effects models are the most commonly used for the longitudinal trajectory function. In this study, we first relax the parametric constraints for polynomial random effect models by using Dirichlet process priors, then three longitudinal markers rather than only one marker are considered in one joint model. Second, we use a linear mixed effect model for the longitudinal process in a joint model analyzing the three markers. In this research these methods were applied to the Primary Biliary Cirrhosis sequential data, which were collected from a clinical trial of primary biliary cirrhosis (PBC) of the liver. This trial was conducted between 1974 and 1984 at the Mayo Clinic. The effects of three longitudinal markers (1) Total Serum Bilirubin, (2) Serum Albumin and (3) Serum Glutamic-Oxaloacetic transaminase (SGOT) on patients' survival were investigated. Proportion of treatment effect will also be studied using the proposed joint modeling approaches. ^ Based on the results, we conclude that the proposed modeling approaches yield better fit to the data and give less biased parameter estimates for these trajectory functions than previous methods. Model fit is also improved after considering three longitudinal markers instead of one marker only. The results from analysis of proportion of treatment effects from these joint models indicate same conclusion as that from the final model of Fleming and Harrington (1991), which is Bilirubin and Albumin together has stronger impact in predicting patients' survival and as a surrogate endpoints for treatment. ^

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

Modeling the survival of T-cell lymphocytes using compound branching processes

Radiotherapy has been a method of choice in cancer treatment for a number of years. Mathematical modeling is an important tool in studying the survival behavior of any cell as well as its radiosensitivity. One particular cell under investigation is the normal T-cell, the radiosensitivity of which may be indicative to the patient's tolerance to radiation doses.^ The model derived is a compound branching process with a random initial population of T-cells that is assumed to have compound distribution. T-cells in any generation are assumed to double or die at random lengths of time. This population is assumed to undergo a random number of generations within a period of time. The model is then used to obtain an estimate for the survival probability of T-cells for the data under investigation. This estimate is derived iteratively by applying the likelihood principle. Further assessment of the validity of the model is performed by simulating a number of subjects under this model.^ This study shows that there is a great deal of variation in T-cells survival from one individual to another. These variations can be observed under normal conditions as well as under radiotherapy. The findings are in agreement with a recent study and show that genetic diversity plays a role in determining the survival of T-cells. ^

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^