Truncated human endothelin receptor A produced by alternative splicing and its expression in melanoma

In this study, reverse transcriptase polymerase chain reaction was used to amplify human endothelin receptor A (ETA) and ETB receptor mRNA. A truncated ETA receptor transcript with exons 3 and 4 skipped was found. The skipping of these two exons results in 109 amino acids being deleted from the receptor. The truncated receptor was expressed in all tissues and cells examined, but the level of expression varied. In melanoma cell lines and melanoma tissues, the truncated receptor gene was the major species, whereas the wild-type ETA was predominant in other tissues. A 1.9-kb ETA transcript was identified in melanoma cell lines by Northern blot, which was much smaller than the transcript in heart and in other tissues reported previously (4.3 kb). The cDNA coding regions of the truncated and wild-type ETA receptors were stably transfected into Chinese hamster ovary (CHO) cells. The truncated ETA receptor-transfected CHO cells did not show binding affinity to endothelin 1 (ET-1) or endothelin 3 (ET-3). The function and biological significance of this truncated ETA receptor is not clear, but it may have regulatory roles for cell responses to ETs

Visualizations relevant to the user by multi-view latent variable factorization

A main goal of data visualization is to find, from among all the available alternatives, mappings to the 2D/3D display which are relevant to the user. Assuming user interaction data, or other auxiliary data about the items or their relationships, the goal is to identify which aspects in the primary data support the user's input and, equally importantly, which aspects of the user's potentially noisy input have support in the primary data. For solving the problem, we introduce a multi-view embedding in which a latent factorization identifies which aspects in the two data views (primary data and user data) are related and which are specific to only one of them. The factorization is a generative model in which the display is parameterized as a part of the factorization and the other factors explain away the aspects not expressible in a two-dimensional display. Functioning of the model is demonstrated on several data sets

Temporoparietal encoding of space and time during vestibular-guided orientation

When we walk in our environment, we readily determine our travelled distance and location using visual cues. In the dark, estimating travelled distance uses a combination of somatosensory and vestibular (i.e., inertial) cues. The observed inability of patients with complete peripheral vestibular failure to update their angular travelled distance during active or passive turns in the dark implies a privileged role for vestibular cues during human angular orientation. As vestibular signals only provide inertial cues of self-motion (e.g., velocity, °/s), the brain must convert motion information to distance information (a process called 'path integration') to maintain our spatial orientation during self-motion in the dark. It is unknown, however, what brain areas are involved in converting vestibular-motion signals to those that enable such vestibular-spatial orientation. Hence, using voxel-based lesion-symptom mapping techniques, we explored the effect of acute right hemisphere lesions in 18 patients on perceived angular position, velocity and motion duration during whole-body angular rotations in the dark. First, compared to healthy controls' spatial orientation performance, we found that of the 18 acute stroke patients tested, only the four patients with damage to the temporoparietal junction showed impaired spatial orientation performance for leftward (contralesional) compared to rightward (ipsilesional) rotations. Second, only patients with temporoparietal junction damage showed a congruent underestimation in both their travelled distance (perceived as shorter) and motion duration (perceived as briefer) for leftward compared to rightward rotations. All 18 lesion patients tested showed normal self-motion perception. These data suggest that the cerebral cortical regions mediating vestibular-motion ('am I moving?') and vestibular-spatial perception ('where am I?') are distinct. Furthermore, the congruent contralesional deficit in time (motion duration) and position perception, seen only in temporoparietal junction patients, may reflect a common neural substrate in the temporoparietal junction that mediates the encoding of motion duration and travelled distance during vestibular-guided navigation. Alternatively, the deficits in timing and spatial orientation with temporoparietal junction lesions could be functionally linked, implying that the temporoparietal junction may act as a cortical temporal integrator, combining estimates of self-motion velocity over time to derive an estimate of travelled distance. This intriguing possibility predicts that timing abnormalities could lead to spatial disorientation

Bayesian exponential family projections for coupled data sources

Exponential family extensions of principal component analysis (EPCA) have received a considerable amount of attention in recent years, demonstrating the growing need for basic modeling tools that do not assume the squared loss or Gaussian distribution. We extend the EPCA model toolbox by presenting the first exponential family multi-view learning methods of the partial least squares and canonical correlation analysis, based on a unified representation of EPCA as matrix factorization of the natural parameters of exponential family. The models are based on a new family of priors that are generally usable for all such factorizations. We also introduce new inference strategies, and demonstrate how the methods outperform earlier ones when the Gaussianity assumption does not hold

The International Trade Network: weighted network analysis and modelling

Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN.Comment: 5 pages, 5 figure

A statistical model with a standard Gamma distribution

We study a statistical model consisting of $N$ basic units which interact with each other by exchanging a physical entity, according to a given microscopic random law, depending on a parameter $\lambda$. We focus on the equilibrium or stationary distribution of the entity exchanged and verify through numerical fitting of the simulation data that the final form of the equilibrium distribution is that of a standard Gamma distribution. The model can be interpreted as a simple closed economy in which economic agents trade money and a saving criterion is fixed by the saving propensity $\lambda$. Alternatively, from the nature of the equilibrium distribution, we show that the model can also be interpreted as a perfect gas at an effective temperature $T(\lambda)$, where particles exchange energy in a space with an effective dimension $D(\lambda)$.Comment: 5 pages, including 4 figures. Uses REVTeX styl

ColorPhylo: A Color Code to Accurately Display Taxonomic Classifications

Color may be very useful to visualise complex data. As far as taxonomy is concerned, color may help observing various species’ characteristics in correlation with classification. However, choosing the number of subclasses to display is often a complex task: on the one hand, assigning a limited number of colors to taxa of interest hides the structure imbedded in the subtrees of the taxonomy; on the other hand, differentiating a high number of taxa by giving them specific colors, without considering the underlying taxonomy, may lead to unreadable results since relationships between displayed taxa would not be supported by the color code. In the present paper, an automatic color coding scheme is proposed to visualise the levels of taxonomic relationships displayed as overlay on any kind of data plot. To achieve this goal, a dimensionality reduction method allows displaying taxonomic “distances” onto a Euclidean two-dimensional space. The resulting map is projected onto a 2D color space (the Hue, Saturation, Brightness colorimetric space with brightness set to 1). Proximity in the taxonomic classification corresponds to proximity on the map and is therefore materialised by color proximity. As a result, each species is related to a color code showing its position in the taxonomic tree. The so called ColorPhylo displays taxonomic relationships intuitively and can be combined with any biological result. A Matlab version of ColorPhylo is available at http://sy.lespi.free.fr/ColorPhylo-homepage.html. Meanwhile, an ad-hoc distance in case of taxonomy with unknown edge lengths is proposed

Generalizations of the clustering coefficient to weighted complex networks

The recent high level of interest in weighted complex networks gives rise to a need to develop new measures and to generalize existing ones to take the weights of links into account. Here we focus on various generalizations of the clustering coefficient, which is one of the central characteristics in the complex network theory. We present a comparative study of the several suggestions introduced in the literature, and point out their advantages and limitations. The concepts are illustrated by simple examples as well as by empirical data of the world trade and weighted coauthorship networks.Comment: 4 pages, 1 table, 3 figures; revised versio

Targeting T cells to treat atherosclerosis: Odyssey from bench to bedside

More than 150 years from the initial description of inflammation in atherosclerotic plaques, randomized clinical trials to test anti-inflammatory therapies in atherosclerosis have recently been initiated. Lymphocytes and macrophages are main participants in the inflammatory response in atherosclerosis. T lymphocytes operate mainly by exerting strong influences on the function of many cells in the immune system and beyond, and co-ordinating their interactions. Importantly, T lymphocytes are not a homogenous population, but include several subsets with specialized functions that can either promote or suppress inflammation. The interactions between these T-lymphocyte subsets have critical consequences on the course and outcome of inflammation. The complexity of the inflammatory response in atherosclerosis poses significant challenges on translating experimental findings into clinical therapies and makes the journey from bench to bedside an arduous one. Here, we summarize recent advances on the role of CD4 + T cells in the inflammatory process in atherosclerosis and discuss potential therapies to modulate these lymphocytes that may provide future breakthroughs in the treatment of atherosclerosis

Time-Varying Priority Queuing Models for Human Dynamics

Queuing models provide insight into the temporal inhomogeneity of human dynamics, characterized by the broad distribution of waiting times of individuals performing tasks. We study the queuing model of an agent trying to execute a task of interest, the priority of which may vary with time due to the agent's "state of mind." However, its execution is disrupted by other tasks of random priorities. By considering the priority of the task of interest either decreasing or increasing algebraically in time, we analytically obtain and numerically confirm the bimodal and unimodal waiting time distributions with power-law decaying tails, respectively. These results are also compared to the updating time distribution of papers in the arXiv.org and the processing time distribution of papers in Physical Review journals. Our analysis helps to understand human task execution in a more realistic scenario.Comment: 8 pages, 6 figure