<p>The aim of this pro ject was to evaluate the use of SIMD array architectures in radar </p><p>signal processing. This has been done by implementing one of the most demanding parts </p><p>of the radar signal processing chain for airborne radar on the CSX600 architecture devel- </p><p>oped by Clearspeed Technologies. The CSX600 architecture is a SIMD processor with 96 </p><p>processing elements which can be arranged either as a linera array or as a ring. The QR- </p><p>decomposition, which was the part chosen for implementation, is the most performance </p><p>demanding part of the STAP stage. In order to create a relevant test case the well known </p><p>RT STAP benchmark from Mitre Corporation has been used. Two different algorithms </p><p>for performing QR-decompositions have been implemented and verified. In both cases </p><p>it has been concluded that either longer (> </p><p>≈256) or shorter (< ≈32) processor array </p><p>lengths would, in general, yield a higher utilization ratio. The FLOP count and utiliza- </p><p>tion has been measured for both algorithms, and it has been concluded that at least eight </p><p>CSX600 processors are needed to meet the real-time demand of the benchmark.</p>

Thesis (Ph.D.)--University of Missouri-Columbia, 2006. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (April 26, 2007) Vita. Includes bibliographical references.

We use seismic array methods (semblance analysis) to image areas of seismic energy release in the Sunda Arc region and world-wide. Broadband seismograms at teleseismic distances (30° ≤ Δ ≤ 100°) are compared at several subarrays. Semblance maps of different subarrays are multiplied. High semblance tracked over long time (10s of second to minutes) and long distances indicate locations of earthquakes. The method allows resolution of rupture characteristics important for tsunami early warning: start and duration, velocity and direction, length and area. The method has been successfully applied to recent and historic events (M>6.5) and is now operational in real time. Results are obtained shortly after source time, see http://www.geo.uni-potsdam.de/Forschung/Geophysik/GITEWS/tsunami.htm). Comparison of manual and automatic processing are in good agreement. Computational effort is small. Automatic results may be obtained within 15 - 20 minutes after event occurrence.

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In chronic lymphocytic leukemia (CLL), the presence of multiple subsets expressing ‘stereotyped’ B-cell receptors (BCRs) has implicated antigen(s) in leukemogenesis. These stereotyped subsets display similar immunoglobulin (IG) gene usage, almost identical complementarity determining region 3’s and may share clinical features. For instance, subsets #1 (IGHV1/5/7/IGKV1-39) and #2 (IGHV3-21/IGLV3-21) have inferior outcome compared to non-subset patients, whereas subset #4 (IGHV4-34/IGKV2-30) display a favourable prognosis. The aim of this thesis was to investigate genomic aberrations, gene expression patterns and methylation profiles in stereotyped subsets and compare epigenetic profiles in CLL and mantle cell lymphoma (MCL). In paper I, we investigated genomic aberrations in subsets #2, #4 and #16 and in non-stereotyped samples (n=101) using high-density 250K SNP arrays. Subset #2 and non-subset #2 IGHV3-21 cases displayed a higher frequency of aberrations than subset #4 cases. The high incidence of del(11q) in both subset #2/non-subset #2 may reflect the adverse survival reported for IGHV3-21 patients. In contrast, the lower frequency of genetic events and lack of poor-prognostic aberrations in subset #4 may partially explain their indolent disease. In paper II, we analysed the global RNA expression in subset #4, #16 and non-subset IGHV4-34 CLL patients (n=25). Subsets #4 and 16 showed distinct gene expression profiles, where genes involved in cell regulatory pathways were significantly lower expressed in subset #4, in line with their low-proliferative disease. In paper III, a genome-wide methylation array was applied to investigate methylation profiles in subsets #1, #2 and #4 (n=39). We identified differential methylation patterns for all subsets and found affected genes to be involved in e.g. apoptosis and therapy resistance. When performing functional annotation, a clear enrichment of genes involved in adaptive immunity was observed. These genes were preferentially methylated in subset #1 when compared to either subset #2 or #4, possibly due to different antigen responses. In paper IV, the genome-wide methylation profiles for 30 CLL and 20 MCL patients were investigated. Distinct methylation profiles were observed, where MCL displayed a more homogeneous profile. Homeobox transcription factor genes showed a higher degree of methylation in MCL, while apoptosis-related genes and proliferation-associated genes were methylated in CLL. In summary, this thesis demonstrates that stereotyped CLL subsets display differences in gene expression profiles, genetic aberrations and methylation patterns, underscoring the functional relevance of subgrouping according to BCR stereotypy. The distinct methylation profiles of CLL and MCL suggests that different epigenetic mechanisms are involved in the pathogenesis of these B-cell malignancies.

Dioxins are environmental contaminants that raise concern because they are potent and persistent. The most potent dioxin congener, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), causes a wide variety of biochemical and toxic effects in laboratory animals and in humans. Major toxicities of TCDD are initiated by their binding to the AH receptor (AHR), a ligand-activated transcription factor that regulates expression of numerous genes. However, the specific genes whose dysregulation leads to major toxicities such as wasting, hepatotoxicity, and lethality are unknown. The objective of this thesis research was to identify the molecular mechanisms by which dioxins cause lethality. To this end, a powerful genetic rat model was utilized – the Han/Wistar (Kuopio) rat which is highly resistant to dioxin toxicity due to a major deletion in the AHR’s transactivation domain (TAD) leading to 3 potential AHR variant transcripts. We found that insertion-variant transcripts (IVs) are the dominant forms of AHR expressed in H/W rats, constitutively and after TCDD treatment. Gene expression array analysis revealed that the total number of TCDD-responsive genes in liver was significantly lower in H/W rats (that carry the TAD deletion) than in dioxin-sensitive rats (that carry wildtype AHR). Genes that are well-known to be AHR-regulated and dioxin-inducible  such as CYP1 transcripts  remained responsive to TCDD in H/W rats; thus the TAD deletion selectively interferes with expression of a subset of hepatic genes rather than abolishing global AHR-mediated responses. Genes that differed in response to TCDD between dioxin-sensitive rats and dioxin-resistant rats are integral parts of pathways known to be disrupted by dioxin treatment such as protein synthesis/degradation, fatty acid transport/metabolism, and apoptosis. These genes are worthy candidates for further mechanistic studies to test their role in major dioxin toxicities. Numerous differentially-regulated genes were downregulated; however, microRNAs, which downregulate mRNA levels in other systems, likely play no role in downregulation of mRNAs by dioxins in adult liver and are unlikely to be involved in hepatotoxicity. Findings in this research support the hypothesis that H/W rats are resistant to TCDD lethality because the TAD deletion prevents the AHR from dysregulating specific mRNA transcripts but not hepatic miRNAs.

As phosphorylation represents the pivotal mechanism for regulation of biological processes, kinases belong to one of the most biologically significant enzyme classes. The development of analytical techniques for characterization of kinase activity, in particular at a global scale, is a central priority for proteomic and cell biology researchers. In order to facilitate global analysis of cellular phosphorylation, a new paradigm of microarray technology which focuses on analysis of total cellular kinase activity, kinome, has emerged in the past few years. As the specificity of many kinases is dictated primarily by recognition of residues immediately surrounding the site of phosphorylation a logical methodology is to employ peptides representing these immediate sequences as experimental substrates. Microarray chips carrying hundreds of such substrate targets have been developed for human kinome analysis, however, lack of similar tools for species outside research mainstream has limited kinome analysis in these species.<p> Based on sequence alignment of orthologous phosphoproteins from mammalian species, conservation of amino acid identity is reported to be 80 %. Accordingly, the potential exists to utilize phosphorylation sequence databases to extrapolate phosphorylation sites in other species based on their genomic sequence information. Peptides representing these proposed phosphorylation sites can then be utilized as substrates to quantify the activity of the corresponding kinase. Based on these principles, a bovine microarray of 300 unique peptide targets was constructed. The bovine phosphorylation targets were selected to represent a spectrum of cellular events but with focus on processes related to innate immunity. Initial application and validation of the bovine peptide arrays was carried out for kinome analysis of bovine blood monocytes stimulated with either lipopolysaccharide (LPS) or CpG-ODNs; ligands for Toll-like receptors (TLR) 4 and 9, respectively. The arrays confirmed activation of the known TLR signaling pathway as well as identifying receptor-specific phosphorylation events. Phosphorylation events not previously attributed to TLR activation were also identified and validated by independent bioassays. This investigation offers insight into the complexity of TLR signaling and more importantly verifies the potential to use bioinformatics approaches to create tools for species-specific kinome analysis based on genomic information.

The use of parallel imaging techniques for image acceleration is now common in clinical magnetic resonance imaging (MRI). There has been limited work, however, in translating the parallel imaging techniques to routine animal imaging. This dissertation describes foundational level work to enable parallel imaging of mice on a 4.7 Tesla/40 cm bore research scanner. Reducing the size of the hardware setup associated with typical parallel imaging was an integral part of achieving the work, as animal scanners are typically small-bore systems. To that end, an array element design is described that inherently decouples from a homogenous transmit field, potentially allowing for elimination of typically necessary active detuning switches. The unbalanced feed of this "dual-plane pair" element also eliminates the need for baluns in this case. The use of the element design in a 10-channel adjustable array coil for mouse imaging is presented, styled as a human cardiac top-bottom half-rack design. The design and construction of the homogenous transmit birdcage coil used is also described, one of the necessary components to eliminating the active detuning networks on the array elements. In addition, the design of a compact, modular multi-channel isolation preamplifier board is described, removing the preamplifiers from the elements and saving space in the bore. Several additions/improvements to existing laboratory infrastructure needed for parallel imaging of live mice are also described, including readying an animal preparation area and developing the ability to maintain isoflurane anesthesia delivery during scanning. In addition, the ability to trigger the MRI scanner to the ECG and respiratory signals from the mouse in order to achieve images free from physiological motion artifacts is described. The imaging results from the compact 10-channel mouse array coils are presented, and the challenges associated with the work are described, including difficulty achieving sample-loss dominance and signal-to-noise ratio (SNR) limitations. In conclusion, in vivo imaging of mice with cardiac and respiratory gating has been demonstrated. Compact array coils tailored for mice have been studied and potential future work and design improvements for our lab in this area are discussed.

Dioxins are environmental contaminants that raise concern because they are potent and persistent. The most potent dioxin congener, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), causes a wide variety of biochemical and toxic effects in laboratory animals and in humans. Major toxicities of TCDD are initiated by their binding to the AH receptor (AHR), a ligand-activated transcription factor that regulates expression of numerous genes. However, the specific genes whose dysregulation leads to major toxicities such as wasting, hepatotoxicity, and lethality are unknown. The objective of this thesis research was to identify the molecular mechanisms by which dioxins cause lethality. To this end, a powerful genetic rat model was utilized – the Han/Wistar (Kuopio) rat which is highly resistant to dioxin toxicity due to a major deletion in the AHR’s transactivation domain (TAD) leading to 3 potential AHR variant transcripts. We found that insertion-variant transcripts (IVs) are the dominant forms of AHR expressed in H/W rats, constitutively and after TCDD treatment. Gene expression array analysis revealed that the total number of TCDD-responsive genes in liver was significantly lower in H/W rats (that carry the TAD deletion) than in dioxin-sensitive rats (that carry wildtype AHR). Genes that are well-known to be AHR-regulated and dioxin-inducible  such as CYP1 transcripts  remained responsive to TCDD in H/W rats; thus the TAD deletion selectively interferes with expression of a subset of hepatic genes rather than abolishing global AHR-mediated responses. Genes that differed in response to TCDD between dioxin-sensitive rats and dioxin-resistant rats are integral parts of pathways known to be disrupted by dioxin treatment such as protein synthesis/degradation, fatty acid transport/metabolism, and apoptosis. These genes are worthy candidates for further mechanistic studies to test their role in major dioxin toxicities. Numerous differentially-regulated genes were downregulated; however, microRNAs, which downregulate mRNA levels in other systems, likely play no role in downregulation of mRNAs by dioxins in adult liver and are unlikely to be involved in hepatotoxicity. Findings in this research support the hypothesis that H/W rats are resistant to TCDD lethality because the TAD deletion prevents the AHR from dysregulating specific mRNA transcripts but not hepatic miRNAs.

DNA copy number alterations (CNAs) are genetic changes that can produce adverse effects in numerous human diseases, including cancer. CNAs are segments of DNA that have been deleted or amplified and can range in size from one kilobases to whole chromosome arms. Development of array comparative genomic hybridization (aCGH) technology enables CNAs to be measured at sub-megabase resolution using tens of thousands of probes. However, aCGH data are noisy and result in continuous valued measurements of the discrete CNAs. Consequently, the data must be processed through algorithmic and statistical techniques in order to derive meaningful biological insights. We introduce model-based approaches to analysis of aCGH data and develop state-of-the-art solutions to three distinct analytical problems. In the simplest scenario, the task is to infer CNAs from a single aCGH experiment. We apply a hidden Markov model (HMM) to accurately identify CNAs from aCGH data. We show that borrowing statistical strength across chromosomes and explicitly modeling outliers in the data, improves on baseline models. In the second scenario, we wish to identify recurrent CNAs in a set of aCGH data derived from a patient cohort. These are locations in the genome altered in many patients, providing evidence for CNAs that may be playing important molecular roles in the disease. We develop a novel hierarchical HMM profiling method that explicitly models both statistical and biological noise in the data and is capable of producing a representative profile for a set of aCGH experiments. We demonstrate that our method is more accurate than simpler baselines on synthetic data, and show our model produces output that is more interpretable than other methods. Finally, we develop a model based clustering framework to stratify a patient cohort, expected to be composed of a fixed set of molecular subtypes. We introduce a model that jointly infers CNAs, assigns patients to subgroups and infers the profiles that represent each subgroup. We show our model to be more accurate on synthetic data, and show in two patient cohorts how the model discovers putative novel subtypes and clinically relevant subgroups.