Mapping the intrinsic curvature and flexibility along the DNA chain

The energy of DNA deformation plays a crucial and active role in its packaging and its function in the cell. Considerable effort has gone into developing methodologies capable of evaluating the local sequence-directed curvature and flexibility of a DNA chain. These studies thus far have focused on DNA constructs expressly tailored either with anomalous flexibility or curvature tracts. Here we demonstrate that these two structural properties can be mapped also along the chain of a “natural” DNA with any sequence on the basis of its scanning force microscope (SFM) images. To know the orientation of the sequence of the investigated DNA molecules in their SFM images, we prepared a palindromic dimer of the long DNA molecule under study. The palindromic symmetry also acted as an internal gauge of the statistical significance of the analysis carried out on the SFM images of the dimer molecules. It was found that although the curvature modulus is not efficient in separating static and dynamic contributions to the curvature of the population of molecules, the curvature taken with its direction (its sign in two dimensions) permits the direct separation of the intrinsic curvature from the flexibility contributions. The sequence-dependent flexibility seems to vary monotonically with the chain's intrinsic curvature; the chain rigidity was found to modulate as its local thermodynamic stability and does not correlate with the dinucleotide chain rigidities evaluation made from x-ray data by other authors.

Mapping the protein regions responsible for the functional specificities of the Arabidopsis MADS domain organ-identity proteins.

The Arabidopsis MADS domain proteins AP1, AP3, PI, and AG specify floral organ identity. All of these proteins contain a MADS domain required for DNA binding and dimerization; a region termed L (linker between MADS domain and K domain), which plays an important role in dimerization specificity; the K domain, named for its similarity to the coiled-coil domain of keratin; and a C-terminal region of unknown function. To determine which regions of these proteins are responsible for their abilities to specify different organs, we have made a number of chimeric MADS box genes. The in vivo function of these chimeric genes was investigated by ectopic expression in transgenic Arabidopsis plants. The four proteins fall into two classes on the basis of regions responsible for their functional specificities. The L region and K domain define the functional specificities of AP3 and PI, while the MADS domain and L region define the functional specificities of AP1 and AG.

cDNA cloning and gene mapping of a candidate human cell cycle checkpoint protein.

A family of proteins involved in cell cycle progression, DNA recombination, and the detection of DNA damage has been recently identified. One of the members of this family, human ATM, is defective in the cells of patients with ataxia telangiectasia and is involved in detection and response of cells to damaged DNA. Other members include Mei-41 (Drosophila melanogaster), Mec1p (Saccharomyces cerevisiae), and Rad3 (Schizosaccharomyces pombe), which are required for the S and G2/M checkpoints, as well as FRAP (Homo sapiens) and Torl/2p (S. cerevisiae), which are involved in a rapamycin-sensitive pathway leading to G1 cell cycle progression. We report here the cloning of a human cDNA encoding a protein with significant homology to members of this family. Three overlapping clones isolated from a Jurkat T-cell cDNA library revealed a 7.9-kb open reading frame encoding a protein that we have named FRP1 (FRAP-related protein) with 2644 amino acids and a predicted molecular mass of 301 kDa. Using fluorescence in situ hybridization and a full-length cDNA FRP1 clone, the FRP1 gene has been mapped to the chromosomal locus 3q22-q24. FRP1 is most closely related to three of the PIK-related kinase family members involved in checkpoint function--Mei-41, Mec1p, and Rad3--and as such may be the functional human counterpart of these proteins.

The specificity of emotion inferences as a function of emotional contextual support

Research on emotion inferences has shown that readers include a representation of the main character's emotional state in their mental representations of the text. We examined the specificity of emotion representations as a function of the emotion content of short narratives, in terms of the quantity and quality of emotion components included in the narratives, based on the GRID instrument (Fontaine et al., 2013). In a self-paced reading task, target sentences that only moderately matched the emotional context were read faster than target sentences that strongly matched the emotional context of the narratives. In a “makes sense” judgment task, we showed that this result was not driven by a mapping difficulty and, in a memory task, we provided some evidence that these effects reflected integration processes. We suggest that readers can integrate specific emotions into their mental representations, but only if provided with the appropriate emotional contextual support.

Mapping the determinants in owl monkey CD4 and CCR5 that allow entry of early-stage HIV-1 Env variants

Thesis (Master's)--University of Washington, 2016-06

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.

Outlier detection with partial information:Application to emergency mapping

This paper, addresses the problem of novelty detection in the case that the observed data is a mixture of a known 'background' process contaminated with an unknown other process, which generates the outliers, or novel observations. The framework we describe here is quite general, employing univariate classification with incomplete information, based on knowledge of the distribution (the 'probability density function', 'pdf') of the data generated by the 'background' process. The relative proportion of this 'background' component (the 'prior' 'background' 'probability), the 'pdf' and the 'prior' probabilities of all other components are all assumed unknown. The main contribution is a new classification scheme that identifies the maximum proportion of observed data following the known 'background' distribution. The method exploits the Kolmogorov-Smirnov test to estimate the proportions, and afterwards data are Bayes optimally separated. Results, demonstrated with synthetic data, show that this approach can produce more reliable results than a standard novelty detection scheme. The classification algorithm is then applied to the problem of identifying outliers in the SIC2004 data set, in order to detect the radioactive release simulated in the 'oker' data set. We propose this method as a reliable means of novelty detection in the emergency situation which can also be used to identify outliers prior to the application of a more general automatic mapping algorithm. © Springer-Verlag 2007.

Robust automatic mapping algorithms in a network monitoring scenario

Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.

The effect of nutritional supplementation on visual function

The aim of this research was to determine the effect of a lutein-based nutritional supplemented on measures of visual function in normal and ARMD-affected eyes. Thirty participants were recruited to the ARMD cohort (aged between 55 and 82 years, mean ± SD: 69.2 ± 7.8) and 46 were recruited into the normal cohort (aged between 22 and 73 years, mean ± SD: 50.0 ± 15.9). Outcome measures were distance (DVA) and near (NVA) visual acuity, contrast sensitivity (CS), photostress recovery time measured with the Eger Macular Stressometer (EMS), central visual function assessed with the Macular Mapping test (MMT), and fundus photography. Reliability studies were carried out for the EMS and the MMT. A change of 14 s is required to indicate a clinically significant change in EMS time, and a change of 14 MMT points is required to indicate a clinically significant change in MMT score. Sample sizes were sufficient for the trial to have 80% power to detect a significant clinical effect at the 5% significance level for all outcome measures in the normal cohort, and for CS in the ARMD cohort. The study demonstrated that a nutritional supplement containing 6mg lutein, 750 mg vitamin A, 250 mg vitamin C, 34 mg vitamin E, 10 mg zinc, and 0.5 mg copper had no effect on the outcome measures over nine or 18 months in normal or ARMD affected participants. The finding that nine months of antioxidant supplementation, in this case, has no significant effect on CS in ARMD-affected participants adds to the literature, and contrasts with previous RCTs, the AREDS and the LAST. This project has added to the debate about the use of nutritional supplementation prior to the onset of ARMD.

Importance of storm events in controlling ecosystem structure and function in a Florida gulf coast estuary

From 8/95 to 2/01, we investigated the ecological effects of intra- and inter-annual variability in freshwater flow through Taylor Creek in southeastern Everglades National Park. Continuous monitoring and intensive sampling studies overlapped with an array of pulsed weather events that impacted physical, chemical, and biological attributes of this region. We quantified the effects of three events representing a range of characteristics (duration, amount of precipitation, storm intensity, wind direction) on the hydraulic connectivity, nutrient and sediment dynamics, and vegetation structure of the SE Everglades estuarine ecotone. These events included a strong winter storm in November 1996, Tropical Storm Harvey in September 1999, and Hurricane Irene in October 1999. Continuous hydrologic and daily water sample data were used to examine the effects of these events on the physical forcing and quality of water in Taylor Creek. A high resolution, flow-through sampling and mapping approach was used to characterize water quality in the adjacent bay. To understand the effects of these events on vegetation communities, we measured mangrove litter production and estimated seagrass cover in the bay at monthly intervals. We also quantified sediment deposition associated with Hurricane Irene's flood surge along the Buttonwood Ridge. These three events resulted in dramatic changes in surface water movement and chemistry in Taylor Creek and adjacent regions of Florida Bay as well as increased mangrove litterfall and flood surge scouring of seagrass beds. Up to 5 cm of bay-derived mud was deposited along the ridge adjacent to the creek in this single pulsed event. These short-term events can account for a substantial proportion of the annual flux of freshwater and materials between the mangrove zone and Florida Bay. Our findings shed light on the capacity of these storm events, especially when in succession, to have far reaching and long lasting effects on coastal ecosystems such as the estuarine ecotone of the SE Everglades.

Hmx1 Function In Lateral Facial Development

Thesis (Master's)--University of Washington, 2016-08

Seeing Turkish state formation processes: Mapping language and education census data

Language provides an interesting lens to look at state-building processes because of its cross-cutting nature. For example, in addition to its symbolic value and appeal, a national language has other roles in the process, including: (a) becoming the primary medium of communication which permits the nation to function efficiently in its political and economic life, (b) promoting social cohesion, allowing the nation to develop a common culture, and (c) forming a primordial basis for self-determination. Moreover, because of its cross-cutting nature, language interventions are rarely isolated activities. Languages are adopted by speakers, taking root in and spreading between communities because they are legitimated by legislation, and then reproduced through institutions like the education and military systems. Pádraig Ó’ Riagáin (1997) makes a case for this observing that “Language policy is formulated, implemented, and accomplishes its results within a complex interrelated set of economic, social, and political processes which include, inter alia, the operation of other non-language state policies” (p. 45). In the Turkish case, its foundational role in the formation of the Turkish nation-state but its linkages to human rights issues raises interesting issues about how socio-cultural practices become reproduced through institutional infrastructure formation. This dissertation is a country-level case study looking at Turkey’s nation-state building process through the lens of its language and education policy development processes with a focus on the early years of the Republic between 1927 and 1970. This project examines how different groups self-identified or were self-identified (as the case may be) in official Turkish statistical publications (e.g., the Turkish annual statistical yearbooks and the population censuses) during that time period when language and ethnicity data was made publicly available. The overarching questions this dissertation explores include: 1.What were the geo-political conditions surrounding the development and influencing the Turkish government’s language and education policies? 2.Are there any observable patterns in the geo-spatial distribution of language, literacy, and education participation rates over time? In what ways, are these traditionally linked variables (language, literacy, education participation) problematic? 3.What do changes in population identifiers, e.g., language and ethnicity, suggest about the government’s approach towards nation-state building through the construction of a civic Turkish identity and institution building? Archival secondary source data was digitized, aggregated by categories relevant to this project at national and provincial levels and over the course of time (primarily between 1927 and 2000). The data was then re-aggregated into values that could be longitudinally compared and then layered on aspatial administrative maps. This dissertation contributes to existing body of social policy literature by taking an interdisciplinary approach in looking at the larger socio-economic contexts in which language and education policies are produced.

A Learning Function for Parameter Reduction in Spiking Neural Networks with Radial Basis Function

Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.

Optimal control of non-linear systems through hybrid cell-mapping/artificial-neural-networks techniques

In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

Mapping new non-genetic dependencies in malignant pleural mesothelioma

Malignant Pleural Mesothelioma (MPM) is a very aggressive cancer whose incidence is growing worldwide. MPM escapes the classical models of carcinogenesis and lacks a distinctive genetic fingerprint, keeping obscure the molecular events that lead to tumorigenesis. This severely impacts on the limited therapeutic options and on the lack of specific biomarkers, concurring to make MPM one of the deadliest cancers. Here we combined a functional genome-wide loss of function CRISPR/Cas9 screening with patients’ transcriptomic and clinical data, to identify genes essential for MPM progression. Besides, we explored the role of non-coding RNAs to MPM progression by analysing gene expression profiles and clinical data from the MESO-TCGA dataset. We identified TRIM28 and the lncRNA LINC00941 as new vulnerabilities of MPM, associated with disease aggressiveness and bad outcome of patients. TRIM28 is a multi-domain protein involved in many processes, including transcription regulation. We showed that TRIM28 silencing impairs MPM cells’ growth and clonogenicity by blocking cells in mitosis. RNA-seq profiling showed that TRIM28 loss abolished the expression of major mitotic players. Our data suggest that TRIM28 is part of the B-MYB/FOXM1-MuvB complex that specifically drives the activation of mitotic genes, keeping the time of mitosis. In parallel, we found LINC00941 as strongly associated with reduced survival probability in MPM patients. LINC00941 KD profoundly reduced MPM cells’ growth, migration and invasion. This is accompanied by changes in morphology, cytoskeleton organization and cell-cell adhesion properties. RNA-seq profiling showed that LINC00941 KD impacts crucial functions of MPM, including HIF1α signalling. Collectively these data provided new insights into MPM biology and demonstrated that the integration of functional screening with patients’ clinical data is a powerful tool to highlight new non-genetic cancer dependencies that associate to a bad outcome in vivo, paving the way to new MPM-oriented targeted strategies and prognostic tools to improve patients risk-based stratification.