Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Sequential updating via dynamic hierarchical models: A Bayesian approach to longitudinal data analysis

Most statistical analysis, theory and practice, is concerned with static models; models with a proposed set of parameters whose values are fixed across observational units. Static models implicitly assume that the quantified relationships remain the same across the design space of the data. While this is reasonable under many circumstances this can be a dangerous assumption when dealing with sequentially ordered data. The mere passage of time always brings fresh considerations and the interrelationships among parameters, or subsets of parameters, may need to be continually revised. ^ When data are gathered sequentially dynamic interim monitoring may be useful as new subject-specific parameters are introduced with each new observational unit. Sequential imputation via dynamic hierarchical models is an efficient strategy for handling missing data and analyzing longitudinal studies. Dynamic conditional independence models offers a flexible framework that exploits the Bayesian updating scheme for capturing the evolution of both the population and individual effects over time. While static models often describe aggregate information well they often do not reflect conflicts in the information at the individual level. Dynamic models prove advantageous over static models in capturing both individual and aggregate trends. Computations for such models can be carried out via the Gibbs sampler. An application using a small sample repeated measures normally distributed growth curve data is presented. ^

Improved Techniques for Acquisition and Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Detecting Vascular Permeability in the Central Nervous System

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive technique for quantitative assessment of the integrity of blood-brain barrier and blood-spinal cord barrier (BSCB) in the presence of central nervous system pathologies. However, the results of DCE-MRI show substantial variability. The high variability can be caused by a number of factors including inaccurate T1 estimation, insufficient temporal resolution and poor contrast-to-noise ratio. My thesis work is to develop improved methods to reduce the variability of DCE-MRI results. To obtain fast and accurate T1 map, the Look-Locker acquisition technique was implemented with a novel and truly centric k-space segmentation scheme. In addition, an original multi-step curve fitting procedure was developed to increase the accuracy of T1 estimation. A view sharing acquisition method was implemented to increase temporal resolution, and a novel normalization method was introduced to reduce image artifacts. Finally, a new clustering algorithm was developed to reduce apparent noise in the DCE-MRI data. The performance of these proposed methods was verified by simulations and phantom studies. As part of this work, the proposed techniques were applied to an in vivo DCE-MRI study of experimental spinal cord injury (SCI). These methods have shown robust results and allow quantitative assessment of regions with very low vascular permeability. In conclusion, applications of the improved DCE-MRI acquisition and analysis methods developed in this thesis work can improve the accuracy of the DCE-MRI results.

Dynamic Chemical Shift Imaging for Image-Guided Thermal Therapy

Magnetic resonance temperature imaging (MRTI) is recognized as a noninvasive means to provide temperature imaging for guidance in thermal therapies. The most common method of estimating temperature changes in the body using MR is by measuring the water proton resonant frequency (PRF) shift. Calculation of the complex phase difference (CPD) is the method of choice for measuring the PRF indirectly since it facilitates temperature mapping with high spatiotemporal resolution. Chemical shift imaging (CSI) techniques can provide the PRF directly with high sensitivity to temperature changes while minimizing artifacts commonly seen in CPD techniques. However, CSI techniques are currently limited by poor spatiotemporal resolution. This research intends to develop and validate a CSI-based MRTI technique with intentional spectral undersampling which allows relaxed parameters to improve spatiotemporal resolution. An algorithm based on autoregressive moving average (ARMA) modeling is developed and validated to help overcome limitations of Fourier-based analysis allowing highly accurate and precise PRF estimates. From the determined acquisition parameters and ARMA modeling, robust maps of temperature using the k-means algorithm are generated and validated in laser treatments in ex vivo tissue. The use of non-PRF based measurements provided by the technique is also investigated to aid in the validation of thermal damage predicted by an Arrhenius rate dose model.

Dynamic Remodeling of the Stressed Heart: Role of Protein Degradation Pathways

The heart is a remarkable organ. In order to maintain its function, it remodels in response to a variety of environmental stresses, including pressure overload, volume overload, mechanical or pharmacological unloading and hormonal or metabolic disturbances. All these responses are linked to the inherent capacity of the heart to rebuild itself. Particularly, cardiac pressure overload activates signaling pathways of both protein synthesis and degradation. While much is known about regulators of protein synthesis, little is known about regulators of protein degradation in hypertrophy. The ubiquitin-proteasome system (UPS) selectively degrades unused and abnormal intracellular proteins. I speculated that the UPS may play an important role in both qualitative and quantitative changes in the composition of heart muscle during hypertrophic remodeling. My study hypothesized that cardiac remodeling in response to hypertrophic stimuli is a dynamic process that requires activation of highly regulated mechanisms of protein degradation as much as it requires protein synthesis. My first aim was to adopt a model of left ventricular hypertrophy and determine its gene expression and structural changes. Male Sprague-Dawley rats were submitted to ascending aortic banding and sacrificed at 7 and 14 days after surgery. Sham operated animals served as controls. Effective aortic banding was confirmed by hemodynamic assessment by Doppler flow measurements in vivo. Banded rats showed a four-fold increase in peak stenotic jet velocities. Histomorphometric analysis revealed a significant increase in myocyte size as well as fibrosis in the banded animals. Transcript analysis showed that banded animals had reverted to the fetal gene program. My second aim was to assess if the UPS is increased and transcriptionally regulated in hypertrophic left ventricular remodeling. Protein extracts from the left ventricles of the banded and control animals were used to perform an in vitro peptidase assay to assess the overall catalytic activity of the UPS. The results showed no difference between hypertrophied and control animals. Transcript analysis revealed decreases in transcript levels of candidate UPS genes in the hypertrophied hearts at 7 days post-banding but not at 14 days. However, protein expression analysis showed no difference at either time point compared to controls. These findings indicate that elements of the UPS are downregulated in the early phase of hypertrophic remodeling and normalizes in a later phase. The results provide evidence in support of a dynamic transcriptional regulation of a major pathway of intracellular protein degradation in the heart. The discrepancy between transcript levels on the one hand and protein levels on the other hand supports post-transcriptional regulation of the UPS pathway in the hypertrophied heart. The exact mechanisms and the functional consequences remain to be elucidated.

Effect of VEGF treatment on the blood-spinal cord barrier permeability in experimental spinal cord injury: dynamic contrast-enhanced magnetic resonance imaging.

Compromised blood-spinal cord barrier (BSCB) is a factor in the outcome following traumatic spinal cord injury (SCI). Vascular endothelial growth factor (VEGF) is a potent stimulator of angiogenesis and vascular permeability. The role of VEGF in SCI is controversial. Relatively little is known about the spatial and temporal changes in the BSCB permeability following administration of VEGF in experimental SCI. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies were performed to noninvasively follow spatial and temporal changes in the BSCB permeability following acute administration of VEGF in experimental SCI over a post-injury period of 56 days. The DCE-MRI data was analyzed using a two-compartment pharmacokinetic model. Animals were assessed for open field locomotion using the Basso-Beattie-Bresnahan score. These studies demonstrate that the BSCB permeability was greater at all time points in the VEGF-treated animals compared to saline controls, most significantly in the epicenter region of injury. Although a significant temporal reduction in the BSCB permeability was observed in the VEGF-treated animals, BSCB permeability remained elevated even during the chronic phase. VEGF treatment resulted in earlier improvement in locomotor ability during the chronic phase of SCI. This study suggests a beneficial role of acutely administered VEGF in hastening neurobehavioral recovery after SCI.

Identification and analysis of novel mitotic inhibitors of the Caenorhabditis elegans Aurora B kinase

Proper execution of mitosis requires the accurate segregation of replicated DNA into each daughter cell. The highly conserved mitotic kinase AIR-2/Aurora B is a dynamic protein that interacts with subsets of cofactors and substrates to coordinate chromosome segregation and cytokinesis in Caenorhabdiris elegans. To identify components of the AIR-2 regulatory pathway, a genome-wide RNAi-based screen for suppressors of air-2 temperature-sensitive mutant lethality was conducted. Here, I present evidence that two classes of suppressors identified in this screen are bona fide regulators of the AIR-2 kinase. The strongest suppressor cdc-48.3, encodes an Afg2/Spaf-related Cdc48-like AAA+ ATPase that regulates AIR-2 kinase activity and stability during C. elegans embryogenesis. Loss of CDC-48.3 suppresses the lethality of air-2 mutant embryos, marked by the restoration of the dynamic behavior of AIR-2 and rescue of chromosome segregation and cytokinesis defects. Loss of CDC-48.3 leads to mitotic delays and abnormal accumulation of AIR-2 during late telophase/mitotic exit. In addition, AIR-2 kinase activity is significantly upregulated from metaphase through mitotic exit in CDC-48.3 depleted embryos. Inhibition of the AIR-2 kinase is dependent on (1) a direct physical interaction between CDC-48.3 and AIR-2, and (2) CDC-48.3 ATPase activity. Importantly, the increase in AIR-2 kinase activity does not correlate with the stabilization of AIR-2 in late mitosis. Hence, CDC-48.3 is a bi-functional inhibitor of AIR-2 that is likely to act via distinct mechanisms. The second class of suppressors consists of psy-2/smk-1 and pph-4.1, which encode two components of the conserved PP4 phosphatase complex that is essential for spindle assembly, chromosome segregation, and overall mitotic progression. AIR-2 and its substrates are likely to be targets of this complex since mitotic AIR-2 kinase activity is significantly increased during mitosis when either PSY-2/SMK-1 or PPH-4.l is depleted. Altogether, this study demonstrates that during the C. elegans embryonic cell cycle, regulators including the CDC-48.3 ATPase and PP4 phosphatase complex interact with and control the kinase activity, targeting behavior and protein stability of the Aurora B kinase to ensure accurate and timely progression of mitosis. ^