Selection and Characterization of a DNA Aptamer Specifically Targeting Human HECT Ubiquitin Ligase WWP1

published_or_final_versio

Towards Intelligent Lower Limb Prostheses with Activity Recognition

User’s volitional control of lower limb prostheses is still challenging task despite technological advancements. There is still a need for amputees to impose their will upon the prosthesis to drive in an accurate and interactive fashion. This study represents a brief review on control strategies using different sensor modalities for the purpose of phases/events detection and activity recognition. The preliminary work that is associated with middle-level control shows a simple and reliable method for event detection in real-time using a single inertial measurement unit. The outcome shows promising results

Parametric study of EEG sensitivity to phase noise during face processing

<b>Background: </b> The present paper examines the visual processing speed of complex objects, here faces, by mapping the relationship between object physical properties and single-trial brain responses. Measuring visual processing speed is challenging because uncontrolled physical differences that co-vary with object categories might affect brain measurements, thus biasing our speed estimates. Recently, we demonstrated that early event-related potential (ERP) differences between faces and objects are preserved even when images differ only in phase information, and amplitude spectra are equated across image categories. Here, we use a parametric design to study how early ERP to faces are shaped by phase information. Subjects performed a two-alternative force choice discrimination between two faces (Experiment 1) or textures (two control experiments). All stimuli had the same amplitude spectrum and were presented at 11 phase noise levels, varying from 0% to 100% in 10% increments, using a linear phase interpolation technique. Single-trial ERP data from each subject were analysed using a multiple linear regression model. <b>Results: </b> Our results show that sensitivity to phase noise in faces emerges progressively in a short time window between the P1 and the N170 ERP visual components. The sensitivity to phase noise starts at about 120–130 ms after stimulus onset and continues for another 25–40 ms. This result was robust both within and across subjects. A control experiment using pink noise textures, which had the same second-order statistics as the faces used in Experiment 1, demonstrated that the sensitivity to phase noise observed for faces cannot be explained by the presence of global image structure alone. A second control experiment used wavelet textures that were matched to the face stimuli in terms of second- and higher-order image statistics. Results from this experiment suggest that higher-order statistics of faces are necessary but not sufficient to obtain the sensitivity to phase noise function observed in response to faces. <b>Conclusion: </b> Our results constitute the first quantitative assessment of the time course of phase information processing by the human visual brain. We interpret our results in a framework that focuses on image statistics and single-trial analyses

Assessing the psychometric and ecometric properties of neighborhood scales using adolescent survey data from urban and rural Scotland

This work was supported by NHS Health Scotland and the University of St Andrews.Background:  Despite the well-established need for specific measurement instruments to examine the relationship between neighborhood conditions and adolescent well-being outcomes, few studies have developed scales to measure features of the neighborhoods in which adolescents reside. Moreover, measures of neighborhood features may be operationalised differently by adolescents living in different levels of urban/rurality. This has not been addressed in previous studies. The objectives of this study were to: 1) establish instruments to measure adolescent neighborhood features at both the individual and neighborhood level, 2) assess their psychometric and ecometric properties, 3) test for invariance by urban/rurality, and 4) generate neighborhood level scores for use in further analysis. Methods:  Data were from the Scottish 2010 Health Behaviour in School-aged Children Survey, which included an over-sample of rural adolescents. The survey responses of interest came from questions designed to capture different facets of the local area in which each respondent resided. Intermediate data zones were used as proxies for neighborhoods. Internal consistency was evaluated by Cronbach’s alpha. Invariance was examined using confirmatory factor analysis. Multilevel models were used to estimate ecometric properties and generate neighborhood scores. Results:  Two constructs labeled neighborhood social cohesion and neighborhood disorder were identified. Adjustment was made to the originally specified model to improve model fit and measures of invariance. At the individual level, reliability was .760 for social cohesion and .765 for disorder, and between .524 and .571 for both constructs at the neighborhood level. Individuals in rural areas experienced greater neighborhood social cohesion and lower levels of neighborhood disorder compared with those in urban areas. Conclusions:  The scales are appropriate for measuring neighborhood characteristics experienced by adolescents across urban and rural Scotland, and can be used in future studies of neighborhoods and health. However, trade-offs between neighborhood sample size and reliability must be considered.Publisher PDFPeer reviewe

Age-related delay in information accrual for faces: Evidence from a parametric, single-trial EEG approach

Background: In this study, we quantified age-related changes in the time-course of face processing by means of an innovative single-trial ERP approach. Unlike analyses used in previous studies, our approach does not rely on peak measurements and can provide a more sensitive measure of processing delays. Young and old adults (mean ages 22 and 70 years) performed a non-speeded discrimination task between two faces. The phase spectrum of these faces was manipulated parametrically to create pictures that ranged between pure noise (0% phase information) and the undistorted signal (100% phase information), with five intermediate steps. Results: Behavioural 75% correct thresholds were on average lower, and maximum accuracy was higher, in younger than older observers. ERPs from each subject were entered into a single-trial general linear regression model to identify variations in neural activity statistically associated with changes in image structure. The earliest age-related ERP differences occurred in the time window of the N170. Older observers had a significantly stronger N170 in response to noise, but this age difference decreased with increasing phase information. Overall, manipulating image phase information had a greater effect on ERPs from younger observers, which was quantified using a hierarchical modelling approach. Importantly, visual activity was modulated by the same stimulus parameters in younger and older subjects. The fit of the model, indexed by R2, was computed at multiple post-stimulus time points. The time-course of the R2 function showed a significantly slower processing in older observers starting around 120 ms after stimulus onset. This age-related delay increased over time to reach a maximum around 190 ms, at which latency younger observers had around 50 ms time lead over older observers. Conclusion: Using a component-free ERP analysis that provides a precise timing of the visual system sensitivity to image structure, the current study demonstrates that older observers accumulate face information more slowly than younger subjects. Additionally, the N170 appears to be less face-sensitive in older observers

The Cosmology of Composite Inelastic Dark Matter

Composite dark matter is a natural setting for implementing inelastic dark matter - the O(100 keV) mass splitting arises from spin-spin interactions of constituent fermions. In models where the constituents are charged under an axial U(1) gauge symmetry that also couples to the Standard Model quarks, dark matter scatters inelastically off Standard Model nuclei and can explain the DAMA/LIBRA annual modulation signal. This article describes the early Universe cosmology of a minimal implementation of a composite inelastic dark matter model where the dark matter is a meson composed of a light and a heavy quark. The synthesis of the constituent quarks into dark mesons and baryons results in several qualitatively different configurations of the resulting dark matter hadrons depending on the relative mass scales in the system.Comment: 31 pages, 4 figures; references added, typos correcte

Charged-Lepton Flavour Physics

This writeup of a talk at the 2011 Lepton-Photon symposium in Mumbai, India, summarises recent results in the charged-lepton flavour sector. I review searches for charged-lepton flavour violation, lepton electric dipole moments and flavour-conserving CP violation. I also discuss recent progress in tau-lepton physics and in the Standard Model prediction of the muon anomalous magnetic moment.Comment: Presented at Lepton-Photon 2011, Mumbai, India; 23 pages, 14 figure

Quantitative metric profiles capture three-dimensional temporospatial architecture to discriminate cellular functional states

<p>Abstract</p> <p>Background</p> <p>Computational analysis of tissue structure reveals sub-visual differences in tissue functional states by extracting quantitative signature features that establish a diagnostic profile. Incomplete and/or inaccurate profiles contribute to misdiagnosis.</p> <p>Methods</p> <p>In order to create more complete tissue structure profiles, we adapted our cell-graph method for extracting quantitative features from histopathology images to now capture temporospatial traits of three-dimensional collagen hydrogel cell cultures. Cell-graphs were proposed to characterize the spatial organization between the cells in tissues by exploiting graph theory wherein the nuclei of the cells constitute the <it>nodes </it>and the approximate adjacency of cells are represented with <it>edges</it>. We chose 11 different cell types representing non-tumorigenic, pre-cancerous, and malignant states from multiple tissue origins.</p> <p>Results</p> <p>We built cell-graphs from the cellular hydrogel images and computed a large set of features describing the structural characteristics captured by the graphs over time. Using three-mode tensor analysis, we identified the five most significant features (metrics) that capture the compactness, clustering, and spatial uniformity of the 3D architectural changes for each cell type throughout the time course. Importantly, four of these metrics are also the discriminative features for our histopathology data from our previous studies.</p> <p>Conclusions</p> <p>Together, these descriptive metrics provide rigorous quantitative representations of image information that other image analysis methods do not. Examining the changes in these five metrics allowed us to easily discriminate between all 11 cell types, whereas differences from visual examination of the images are not as apparent. These results demonstrate that application of the cell-graph technique to 3D image data yields discriminative metrics that have the potential to improve the accuracy of image-based tissue profiles, and thus improve the detection and diagnosis of disease.</p

Widespread Climate Change in the Himalayas and Associated Changes in Local Ecosystems

Background: Climate change in the Himalayas, a biodiversity hotspot, home of many sacred landscapes, and the source of eight largest rivers of Asia, is likely to impact the well-being of $\sim$20% of humanity. However, despite the extraordinary environmental, cultural, and socio-economic importance of the Himalayas, and despite their rapidly increasing ecological degradation, not much is known about actual changes in the two most critical climatic variables: temperature and rainfall. Nor do we know how changes in these parameters might impact the ecosystems including vegetation phenology. Methodology/Principal Findings: By analyzing temperature and rainfall data, and NDVI (Normalized Difference Vegetation Index) values from remotely sensed imagery, we report significant changes in temperature, rainfall, and vegetation phenology across the Himalayas between 1982 and 2006. The average annual mean temperature during the 25 year period has increased by 1.5$^\circ$C with an average increase of 0.06$^\circ$C yr$^{−1}$. The average annual precipitation has increased by 163 mm or 6.52 mmyr$^{−1}$. Since changes in temperature and precipitation are immediately manifested as changes in phenology of local ecosystems, we examined phenological changes in all major ecoregions. The average start of the growing season (SOS) seems to have advanced by 4.7 days or 0.19 days yr$^{−1}$ and the length of growing season (LOS) appears to have advanced by 4.7 days or 0.19 days yr$^{−1}$, but there has been no change in the end of the growing season (EOS). There is considerable spatial and seasonal variation in changes in climate and phenological parameters. Conclusions/Significance: This is the first time that large scale climatic and phenological changes at the landscape level have been documented for the Himalayas. The rate of warming in the Himalayas is greater than the global average, confirming that the Himalayas are among the regions most vulnerable to climate change