Physical and functional mapping of a novel tumor suppressor locus for prostate cancer within chromosome 10p12.31-q11

Prostate cancer remains the second leading cause of male cancer deaths in the United States, yet the molecular mechanisms underlying this disease remain largely unknown. Cytogenetic and molecular analyses of prostate tumors suggest a consistent association with the loss of chromosome 10. Previously, we have defined a novel tumor suppressor locus PAC-1 within chromosome 10pter-q11. Introduction of the short arm of chromosome 10 into a prostatic adenocarcinoma cell line PC-3H resulted in dramatic tumor suppression and restoration of a programmed cell death pathway. Using a combined approach of comparative genomic hybridization and microsatellite analysis of PC-3H, I have identified a region of hemizygosity within 10p12-p15. This region has been shown to be involved in frequent loss of heterozygosity in gliomas and melanoma. To functionally dissect the region within chromosome 10p containing PAC-1, we developed a strategy of serial microcell fusion, a technique that allows the transfer of defined fragments of chromosome 10p into PC-3H. Serial microcell fusion was used to transfer defined 10p fragments into a mouse A9 fibrosarcoma cell line. Once characterized by FISH and microsatellite analyses, the 10p fragments were subsequently transferred into PC-3H to generate a panel of microcell hybrid clones containing overlapping deletions of chromosome 10p. In vivo and microsatellite analyses of these PC hybrids identified a small chromosome 10p fragment (an estimated 31 Mb in size inclusive of the centromere) that when transferred into the PC-3H background, resulted in significant tumor suppression and limited a region of functional tumor suppressor activity to chromosome 10p12.31-q11. This region coincides with a region of LOH demonstrated in prostate cancer. These studies demonstrate the utility of this approach as a powerful tool to limit regions of functional tumor suppressor activity. Furthermore, these data used in conjunction with data generated by the Human Genome Project lent a focused approach to identify candidate tumor suppressor genes involved in prostate cancer. ^

A Bayesian analysis for spatial processes with application to mapping

In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease etiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. Empirical Bayesian (EB) methods have been used to spatially smooth the estimates by permitting an area estimate to "borrow strength" from its neighbors. Such EB methods include the use of a Gamma model, of a James-Stein estimator, and of a conditional autoregressive (CAR) process. A fully Bayesian analysis of the CAR process is proposed. One advantage of this fully Bayesian analysis is that it can be implemented simply by using repeated sampling from the posterior densities. Use of a Markov chain Monte Carlo technique such as Gibbs sampler was not necessary. Direct resampling from the posterior densities provides exact small sample inferences instead of the approximate asymptotic analyses of maximum likelihood methods (Clayton & Kaldor, 1987). Further, the proposed CAR model provides for covariates to be included in the model. A simulation demonstrates the effect of sample size on the fully Bayesian analysis of the CAR process. The methods are applied to lip cancer data from Scotland, and the results are compared. ^

Mapping wide row crops with video sequences acquired from a tractor moving at treatment speed

This paper presents a mapping method for wide row crop fields. The resulting map shows the crop rows and weeds present in the inter-row spacing. Because field videos are acquired with a camera mounted on top of an agricultural vehicle, a method for image sequence stabilization was needed and consequently designed and developed. The proposed stabilization method uses the centers of some crop rows in the image sequence as features to be tracked, which compensates for the lateral movement (sway) of the camera and leaves the pitch unchanged. A region of interest is selected using the tracked features, and an inverse perspective technique transforms the selected region into a bird’s-eye view that is centered on the image and that enables map generation. The algorithm developed has been tested on several video sequences of different fields recorded at different times and under different lighting conditions, with good initial results. Indeed, lateral displacements of up to 66% of the inter-row spacing were suppressed through the stabilization process, and crop rows in the resulting maps appear straight

Mapping variability of soil water content and flux across 1¿1000 m scales using the actively heated fiber optic method

The Actively Heated Fiber Optic (AHFO) method is shown to be capable of measuring soil water content several times per hour at 0.25 m spacing along cables of multiple kilometers in length. AHFO is based on distributed temperature sensing (DTS) observation of the heating and cooling of a buried fiber-optic cable resulting from an electrical impulse of energy delivered from the steel cable jacket. The results presented were collected from 750 m of cable buried in three 240 m colocated transects at 30, 60, and 90 cm depths in an agricultural field under center pivot irrigation. The calibration curve relating soil water content to the thermal response of the soil to a heat pulse of 10 W m−1 for 1 min duration was developed in the lab. This calibration was found applicable to the 30 and 60 cm depth cables, while the 90 cm depth cable illustrated the challenges presented by soil heterogeneity for this technique. This method was used to map with high resolution the variability of soil water content and fluxes induced by the nonuniformity of water application at the surface.

Mapping strain exerted on blood vessel walls using deuterium double-quantum-filtered MRI

A technique is described for displaying distinct tissue layers of large blood vessel walls as well as measuring their mechanical strain. The technique is based on deuterium double-quantum-filtered (DQF) spectroscopic imaging. The effectiveness of the double-quantum filtration in suppressing the signal of bulk water is demonstrated on a phantom consisting of rat tail tendon fibers. Only intrafibrillar water is displayed, excluding all other signals of water molecules that reorient isotropically. One- and two-dimensional spectroscopic imaging of bovine aorta and coronary arteries show the characteristic DQF spectrum of each of the tissue layers. This property is used to obtain separate images of the outer layer, the tunica adventitia, or the intermediate layer, the tunica media, or both. To visualize the effect of elongation, the average residual quadrupole splitting <Δνq> is calculated for each pixel. Two-dimensional deuterium quadrupolar splitting images are obtained for a fully relaxed and a 55% elongated sample of bovine coronary artery. These images indicate that the strong effect of strain is associated with water molecules in the tunica adventitia whereas the DQF NMR signal of water in the tunica media is apparently strain-insensitive. After appropriate calibration, these average quadrupolar splitting images can be interpreted as strain maps.

Nondestructive, in situ, cellular-scale mapping of elemental abundances including organic carbon in permineralized fossils

The electron microprobe allows elemental abundances to be mapped at the μm scale, but until now high resolution mapping of light elements has been challenging. Modifications of electron microprobe procedure permit fine-scale mapping of carbon. When applied to permineralized fossils, this technique allows simultaneous mapping of organic material, major matrix-forming elements, and trace elements with μm-scale resolution. The resulting data make it possible to test taphonomic hypotheses for the formation of anatomically preserved silicified fossils, including the role of trace elements in the initiation of silica precipitation and in the prevention of organic degradation. The technique allows one to understand the localization of preserved organic matter before undertaking destructive chemical analyses and, because it is nondestructive, offers a potentially important tool for astrobiological investigations of samples returned from Mars or other solar system bodies.

Metaphase and interphase fluorescence in situ hybridization mapping of the rice genome with bacterial artificial chromosomes.

Fluorescence in situ hybridization (FISH) is a powerful tool for physical mapping in human and other mammalian species. However, application of the FISH technique has been limited in plant species, especially for mapping single- or low-copy DNA sequences, due to inconsistent signal production in plant chromosome preparations. Here we demonstrate that bacterial artificial chromosome (BAC) clones can be mapped readily on rice (Oryza sativa L.) chromosomes by FISH. Repetitive DNA sequences in BAC clones can be suppressed efficiently by using rice genomic DNA as a competitor in the hybridization mixture. BAC clones as small as 40 kb were successfully mapped. To demonstrate the application of the FISH technique in physical mapping of plant genomes, both anonymous BAC clones and clones closely linked to a rice bacterial blight-resistance locus, Xa21, were chosen for analysis. The physical location of Xa21 and the relationships among the linked clones were established, thus demonstrating the utility of FISH in plant genome analysis.

Radiomic Texture Analysis Mapping Predicts Areas of True Functional MRI Activity.

Individual analysis of functional Magnetic Resonance Imaging (fMRI) scans requires user-adjustment of the statistical threshold in order to maximize true functional activity and eliminate false positives. In this study, we propose a novel technique that uses radiomic texture analysis (TA) features associated with heterogeneity to predict areas of true functional activity. Scans of 15 right-handed healthy volunteers were analyzed using SPM8. The resulting functional maps were thresholded to optimize visualization of language areas, resulting in 116 regions of interests (ROIs). A board-certified neuroradiologist classified different ROIs into Expected (E) and Non-Expected (NE) based on their anatomical locations. TA was performed using the mean Echo-Planner Imaging (EPI) volume, and 20 rotation-invariant texture features were obtained for each ROI. Using forward stepwise logistic regression, we built a predictive model that discriminated between E and NE areas of functional activity, with a cross-validation AUC and success rate of 79.84% and 80.19% respectively (specificity/sensitivity of 78.34%/82.61%). This study found that radiomic TA of fMRI scans may allow for determination of areas of true functional activity, and thus eliminate clinician bias.

A Way of Doing Things: Exploring and Applying the Alexander Technique for Choral Conductors

Thesis (D.M.A.)--University of Washington, 2016-06

Neutron-mapping polymer flow: Scattering, flow visualization, and molecular theory

Flows of complex fluids need to be understood at both macroscopic and molecular scales, because it is the macroscopic response that controls the fluid behavior, but the molecular scale that ultimately gives rise to rheological and solid-state properties. Here the flow field of an entangled polymer melt through an extended contraction, typical of many polymer processes, is imaged optically and by small-angle neutron scattering. The dual-probe technique samples both the macroscopic stress field in the flow and the microscopic configuration of the polymer molecules at selected points. The results are compared with a recent tube model molecular theory of entangled melt flow that is able to calculate both the stress and the single-chain structure factor from first principles. The combined action of the three fundamental entangled processes of reptation, contour length fluctuation, and convective constraint release is essential to account quantitatively for the rich rheological behavior. The multiscale approach unearths a new feature: Orientation at the length scale of the entire chain decays considerably more slowly than at the smaller entanglement length.

Fine mapping of the tomato I-3 gene for fusarium wilt resistance and elimination of a co-segregating resistance gene analogue as a candidate for I-3

The I-3 gene from the wild tomato species Lycopersicon pennellii confers resistance to race 3 of the devastating vascular wilt pathogen Fusarium oxysporum f. sp. lycopersici. As an initial step in a positional cloning strategy for the isolation of I-3, we converted restriction fragment length polymorphism and conserved orthologue set markers, known genes and a resistance gene analogue (RGA) mapping to the I-3 region into PCR-based sequence characterised amplified region (SCAR) and cleaved amplified polymorphic sequence (CAPS) markers. Additional PCR-based markers in the I-3 region were generated using the randomly amplified DNA fingerprinting (RAF) technique. SCAR, CAPS and RAF markers were used for high-resolution mapping around the I-3 locus. The I-3 gene was localised to a 0.3-cM region containing a RAF marker, eO6, and an RGA, RGA332. RGA332 was cloned and found to correspond to a putative pseudogene with at least two loss-of-function mutations. The predicted pseudogene belongs to the Toll interleukin-1 receptor-nucleotide-binding site-leucine-rich-repeat sub-class of plant disease resistance genes. Despite the presence of two RGA332 homologues in L. esculentum, DNA gel blot and PCR analysis suggests that no other homologues are present in lines carrying I-3 that could be alternative candidates for the gene.

Fast algorithms for automatic mapping with space-limited covariance functions

In this paper we discuss a fast Bayesian extension to kriging algorithms which has been used successfully for fast, automatic mapping in emergency conditions in the Spatial Interpolation Comparison 2004 (SIC2004) exercise. The application of kriging to automatic mapping raises several issues such as robustness, scalability, speed and parameter estimation. Various ad-hoc solutions have been proposed and used extensively but they lack a sound theoretical basis. In this paper we show how observations can be projected onto a representative subset of the data, without losing significant information. This allows the complexity of the algorithm to grow as O(n m 2), where n is the total number of observations and m is the size of the subset of the observations retained for prediction. The main contribution of this paper is to further extend this projective method through the application of space-limited covariance functions, which can be used as an alternative to the commonly used covariance models. In many real world applications the correlation between observations essentially vanishes beyond a certain separation distance. Thus it makes sense to use a covariance model that encompasses this belief since this leads to sparse covariance matrices for which optimised sparse matrix techniques can be used. In the presence of extreme values we show that space-limited covariance functions offer an additional benefit, they maintain the smoothness locally but at the same time lead to a more robust, and compact, global model. We show the performance of this technique coupled with the sparse extension to the kriging algorithm on synthetic data and outline a number of computational benefits such an approach brings. To test the relevance to automatic mapping we apply the method to the data used in a recent comparison of interpolation techniques (SIC2004) to map the levels of background ambient gamma radiation. © Springer-Verlag 2007.

The use of spot simulation imagery for forestry mapping and management

SPOT simulation imagery was acquired for a test site in the Forest of Dean in Gloucestershire, U.K. This data was qualitatively and quantitatively evaluated for its potential application in forest resource mapping and management. A variety of techniques are described for enhancing the image with the aim of providing species level discrimination within the forest. Visual interpretation of the imagery was more successful than automated classification. The heterogeneity within the forest classes, and in particular between the forest and urban class, resulted in poor discrimination using traditional `per-pixel' automated methods of classification. Different means of assessing classification accuracy are proposed. Two techniques for measuring textural variation were investigated in an attempt to improve classification accuracy. The first of these, a sequential segmentation method, was found to be beneficial. The second, a parallel segmentation method, resulted in little improvement though this may be related to a combination of resolution in size of the texture extraction area. The effect on classification accuracy of combining the SPOT simulation imagery with other data types is investigated. A grid cell encoding technique was selected as most appropriate for storing digitised topographic (elevation, slope) and ground truth data. Topographic data were shown to improve species-level classification, though with sixteen classes overall accuracies were consistently below 50%. Neither sub-division into age groups or the incorporation of principal components and a band ratio significantly improved classification accuracy. It is concluded that SPOT imagery will not permit species level classification within forested areas as diverse as the Forest of Dean. The imagery will be most useful as part of a multi-stage sampling scheme. The use of texture analysis is highly recommended for extracting maximum information content from the data. Incorporation of the imagery into a GIS will both aid discrimination and provide a useful management tool.

Data Assimilation Technique For Flood Monitoring and Prediction

This paper focuses on the development of methods and cascade of models for flood monitoring and forecasting and its implementation in Grid environment. The processing of satellite data for flood extent mapping is done using neural networks. For flood forecasting we use cascade of models: regional numerical weather prediction (NWP) model, hydrological model and hydraulic model. Implementation of developed methods and models in the Grid infrastructure and related projects are discussed.

Metal transfer mapping for FCAW process by using near-infrared filming

In the Flux Cored Arc Welding (FCAW) process, the transfer of filler metal (metal transfer modes) to the base material to accomplish the weld bead determines the weld quality and therefore studies of such phenomena is demanded. Thus, in this work, the metal transfer through the FCAW process is investigated by filming the phenomena with the assist of near infrared visualization. During the literature survey, it was found that this technic has not been used so far for analyzing the FCAW process. It must be pointed out that the radiation emitted from the weld arc, fumes and particles (spattering) in this process represent a barrier for these studies based in the process visualization. The monitoring of metal transfer for FCAW process was carried out within the operational envelope of voltage and wire feed speed with the electrode E71T-1 (1.2 mm diameter) and Ar+25%CO2 as a shielding gas. A local developed near infrared filming with frame rate of 300 Hz was employed for metal transfer visualization in order to contribute to a better understanding of this process and evaluating characteristics of metal transfer, unlike previous studies, which used shadowgraph technique. It can clearly be seen how the droplet is created and transferred in this process and also identify the different modes of metal transfer by changing the parameters of voltage and wire feed speed in metal transfer maps. The final result of this study is the metal transfer mode maps, which establish suitable conditions and provide the basis for developing arc control strategies for the FCAW process.