Tissue-specific silencing of homoeologs in natural populations of the recent allopolyploid Tragopogon mirus

The definitive version is available at www3.interscience.wiley.com http://dx.doi.org/10.1111/j.1469-8137.2010.03205.

Magnetic Resonance Imaging-Based Assessment of Breast Cancer-Related Lymphoedema Tissue Composition.

OBJECTIVES: The aim of this study was to propose a magnetic resonance imaging acquisition and analysis protocol that uses image segmentation to measure and depict fluid, fat, and muscle volumes in breast cancer-related lymphoedema (BCRL). This study also aims to compare affected and control (unaffected) arms of patients with diagnosed BCRL, providing an analysis of both the volume and the distribution of the different tissue components. MATERIALS AND METHODS: The entire arm was imaged with a fluid-sensitive STIR and a 2-point 3-dimensional T1W gradient-echo-based Dixon sequences, acquired in sagittal orientation and covering the same imaging volume. An automated image postprocessing procedure was developed to simultaneously (1) contour the external volume of the arm and the muscle fascia, allowing separation of the epifacial and subfascial volumes; and to (2) separate the voxels belonging to the muscle, fat, and fluid components. The total, subfascial, epifascial, muscle (subfascial), fluid (epifascial), and fat (epifascial) volumes were measured in 13 patients with unilateral BCRL. Affected versus unaffected volumes were compared using a 2-tailed paired t test; a value of P < 0.05 was considered to be significant. Pearson correlation was used to investigate the linear relationship between fat and fluid excess volumes. The distribution of fluid, fat, and epifascial excess volumes (affected minus unaffected) along the arm was also evaluated using dedicated tissue composition maps. RESULTS: Total arm, epifascial, epifascial fluid, and epifascial fat volumes were significantly different (P < 0.0005), with greater volume in the affected arms. The increase in epifascial volume (globally, 94% of the excess volume) constituted the bulk of the lymphoedematous swelling, with fat comprising the main component. The total fat excess volume summed over all patients was 2.1 times that of fluid. Furthermore, fat and fluid excess volumes were linearly correlated (Pearson r = 0.75), with the fat excess volume being greater than the fluid in 11 subjects. Differences in muscle compartment volume between affected and unaffected arms were not statistically significant, and contributed only 6% to the total excess volume. Considering the distribution of the different tissue excess volumes, fluid accumulated prevalently around the elbow, with substantial involvement of the upper arm in only 3 cases. Fat excess volume was generally greater in the upper arm; however, the relative increase in epifascial volume, which considers the total swelling relative to the original size of the arm, was in 9 cases maximal within the forearm. CONCLUSIONS: Our measurements indicate that excess of fat within the epifascial layer was the main contributor to the swelling, even when a substantial accumulation of fluid was present. The proposed approach could be used to monitor how the internal components of BCRL evolve after presentation, to stratify patients for treatment, and to objectively assess treatment response. This methodology provides quantitative metrics not currently available during the standard clinical assessment of BCRL and shows potential for implementation in clinical practice

Stable Word-Clouds for Visualising Text-Changes Over Time

Word-clouds are a useful tool for providing overviews over texts, visualising relevant words. Multiple word-clouds can also be used to visualise changes over time in a text. This requires that the words in the individual word-clouds have stable positions, as otherwise it is very difficult so see what changed between two consecutive word-clouds. Existing approaches have used coordinated positioning algorithms, which do not allow for their use in an online, dynamic context. In this paper we present a fast word-cloud algorithm that uses word orthogonality to determine which words can share the same space in the word-clouds combined with a simple, but fast spiral-based layout algorithm. The evaluation shows that the algorithm achieves its goal of creating series of word-clouds fast enough to enable use in an online, dynamic context

The New Legal Pluralism

Scholars studying interactions among multiple communities have often used the term legal pluralism to describe the inevitable intermingling of normative systems that results from these interactions. In recent years, a new application of pluralist insights has emerged in the international and transnational realm. This review aims to survey and help define this emerging field of global legal pluralism. I begin by briefly describing sites for pluralism research, both old and new. Then I discuss how pluralism has come to be seen as an attractive analytical framework for those interested in studying law on the world stage. Finally, I identify advantages of a pluralist approach and respond to criticisms, and I suggest ways in which pluralism can help both in reframing old conceptual debates and in generating useful normative insights for designing procedural mechanisms, institutions, and discursive practices for managing hybrid legal/cultural spaces

On instantons as Kaluza-Klein modes of M5-branes

Instantons and W-bosons in 5d maximally supersymmetric Yang-Mills theory arise from a circle compactification of the 6d (2,0) theory as Kaluza-Klein modes and winding self-dual strings, respectively. We study an index which counts BPS instantons with electric charges in Coulomb and symmetric phases. We first prove the existence of unique threshold bound state of (noncommutative) U(1) instantons for any instanton number, and also show that charged instantons in the Coulomb phase correctly give the degeneracy of SU(2) self-dual strings. By studying SU(N) self-dual strings in the Coulomb phase, we find novel momentum-carrying degrees on the worldsheet. The total number of these degrees equals the anomaly coefficient of SU(N) (2,0) theory. We finally show that our index can be used to study the symmetric phase of this theory, and provide an interpretation as the superconformal index of the sigma model on instanton moduli space.Comment: 54 pages, 2 figures. v2: references added, figure improved, added comments on self-dual string anomaly, added new materials on the symmetric phase index, other minor correction

Factors associated with nursing home placement of all patients admitted for inpatient rehabilitation in Singapore community hospitals from 1996 to 2005: A disease stratified analysis

10.1371/journal.pone.0082697PLoS ONE812-POLN

Early prediction of response to radiotherapy and androgen-deprivation therapy in prostate cancer by repeated functional MRI: a preclinical study

<p>Abstract</p> <p>Background</p> <p>In modern cancer medicine, morphological magnetic resonance imaging (MRI) is routinely used in diagnostics, treatment planning and assessment of therapeutic efficacy. During the past decade, functional imaging techniques like diffusion-weighted (DW) MRI and dynamic contrast-enhanced (DCE) MRI have increasingly been included into imaging protocols, allowing extraction of intratumoral information of underlying vascular, molecular and physiological mechanisms, not available in morphological images. Separately, pre-treatment and early changes in functional parameters obtained from DWMRI and DCEMRI have shown potential in predicting therapy response. We hypothesized that the combination of several functional parameters increased the predictive power.</p> <p>Methods</p> <p>We challenged this hypothesis by using an artificial neural network (ANN) approach, exploiting nonlinear relationships between individual variables, which is particularly suitable in treatment response prediction involving complex cancer data. A clinical scenario was elicited by using 32 mice with human prostate carcinoma xenografts receiving combinations of androgen-deprivation therapy and/or radiotherapy. Pre-radiation and on days 1 and 9 following radiation three repeated DWMRI and DCEMRI acquisitions enabled derivation of the apparent diffusion coefficient (ADC) and the vascular biomarker <it>K</it>^trans, which together with tumor volumes and the established biomarker prostate-specific antigen (PSA), were used as inputs to a back propagation neural network, independently and combined, in order to explore their feasibility of predicting individual treatment response measured as 30 days post-RT tumor volumes.</p> <p>Results</p> <p>ADC, volumes and PSA as inputs to the model revealed a correlation coefficient of 0.54 (p < 0.001) between predicted and measured treatment response, while <it>K</it>^trans, volumes and PSA gave a correlation coefficient of 0.66 (p < 0.001). The combination of all parameters (ADC, <it>K</it>^trans, volumes, PSA) successfully predicted treatment response with a correlation coefficient of 0.85 (p < 0.001).</p> <p>Conclusions</p> <p>We have in a preclinical investigation showed that the combination of early changes in several functional MRI parameters provides additional information about therapy response. If such an approach could be clinically validated, it may become a tool to help identifying non-responding patients early in treatment, allowing these patients to be considered for alternative treatment strategies, and, thus, providing a contribution to the development of individualized cancer therapy.</p