Evolving Clustered Random Networks

We propose a Markov chain simulation method to generate simple connected random graphs with a specified degree sequence and level of clustering. The networks generated by our algorithm are random in all other respects and can thus serve as generic models for studying the impacts of degree distributions and clustering on dynamical processes as well as null models for detecting other structural properties in empirical networks

3D time series analysis of cell shape using Laplacian approaches

Background: Fundamental cellular processes such as cell movement, division or food uptake critically depend on cells being able to change shape. Fast acquisition of three-dimensional image time series has now become possible, but we lack efficient tools for analysing shape deformations in order to understand the real three-dimensional nature of shape changes. Results: We present a framework for 3D+time cell shape analysis. The main contribution is three-fold: First, we develop a fast, automatic random walker method for cell segmentation. Second, a novel topology fixing method is proposed to fix segmented binary volumes without spherical topology. Third, we show that algorithms used for each individual step of the analysis pipeline (cell segmentation, topology fixing, spherical parameterization, and shape representation) are closely related to the Laplacian operator. The framework is applied to the shape analysis of neutrophil cells. Conclusions: The method we propose for cell segmentation is faster than the traditional random walker method or the level set method, and performs better on 3D time-series of neutrophil cells, which are comparatively noisy as stacks have to be acquired fast enough to account for cell motion. Our method for topology fixing outperforms the tools provided by SPHARM-MAT and SPHARM-PDM in terms of their successful fixing rates. The different tasks in the presented pipeline for 3D+time shape analysis of cells can be solved using Laplacian approaches, opening the possibility of eventually combining individual steps in order to speed up computations

Crystallization of strongly interacting photons in a nonlinear optical fiber

Understanding strongly correlated quantum systems is a central problem in many areas of physics. The collective behavior of interacting particles gives rise to diverse fundamental phenomena such as confinement in quantum chromodynamics, phase transitions, and electron fractionalization in the quantum Hall regime. While such systems typically involve massive particles, optical photons can also interact with each other in a nonlinear medium. In practice, however, such interactions are often very weak. Here we describe a novel technique that allows the creation of a strongly correlated quantum gas of photons using one-dimensional optical systems with tight field confinement and coherent photon trapping techniques. The confinement enables the generation of large, tunable optical nonlinearities via the interaction of photons with a nearby cold atomic gas. In its extreme, we show that a quantum light field can undergo fermionization in such one-dimensional media, which can be probed via standard photon correlation measurements

Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells

available in PMC 2011 November 01.Cellular RNA levels are determined by the interplay of RNA production, processing and degradation. However, because most studies of RNA regulation do not distinguish the separate contributions of these processes, little is known about how they are temporally integrated. Here we combine metabolic labeling of RNA at high temporal resolution with advanced RNA quantification and computational modeling to estimate RNA transcription and degradation rates during the response of mouse dendritic cells to lipopolysaccharide. We find that changes in transcription rates determine the majority of temporal changes in RNA levels, but that changes in degradation rates are important for shaping sharp 'peaked' responses. We used sequencing of the newly transcribed RNA population to estimate temporally constant RNA processing and degradation rates genome wide. Degradation rates vary significantly between genes and contribute to the observed differences in the dynamic response. Certain transcripts, including those encoding cytokines and transcription factors, mature faster. Our study provides a quantitative approach to study the integrative process of RNA regulation.Human Frontier Science Program (Strasbourg, France)Howard Hughes Medical InstituteBurroughs Wellcome Fund (Career Award at the Scientific Interface

The Hubbard model within the equations of motion approach

The Hubbard model has a special role in Condensed Matter Theory as it is considered as the simplest Hamiltonian model one can write in order to describe anomalous physical properties of some class of real materials. Unfortunately, this model is not exactly solved except for some limits and therefore one should resort to analytical methods, like the Equations of Motion Approach, or to numerical techniques in order to attain a description of its relevant features in the whole range of physical parameters (interaction, filling and temperature). In this manuscript, the Composite Operator Method, which exploits the above mentioned analytical technique, is presented and systematically applied in order to get information about the behavior of all relevant properties of the model (local, thermodynamic, single- and two- particle ones) in comparison with many other analytical techniques, the above cited known limits and numerical simulations. Within this approach, the Hubbard model is shown to be also capable to describe some anomalous behaviors of the cuprate superconductors.Comment: 232 pages, more than 300 figures, more than 500 reference

ICF components of corresponding outcome measures in flexor tendon rehabilitation – a systematic review

<p>Abstract</p> <p>Background</p> <p>The International Classification of Functioning, Disability and Health (ICF) delivers a holistic approach to health conditions. The objective of the present study is to provide an overview of flexor tendon rehabilitation outcome measures with respect to ICF components. Furthermore, it aims to investigate to which extent current assessments measure aspects of health according to these components primarily focussing on <it>activity </it>and <it>participation</it>.</p> <p>Methods</p> <p>A systematic literature review was conducted to identify all studies meeting the inclusion criteria. Studies were only included if they assessed more than <it>body function and body structure </it>and referred to the ICF components <it>activity </it>and <it>participation</it>. The outcome measures were analysed and their linkage to the ICF components were investigated to examine to which degree aspects of health outcome as defined by the ICF were considered.</p> <p>Results</p> <p>As anticipated, the application of outcome measures after flexor tendon repair is non conform. In many studies the emphasis still lies on physical impairment neglecting activity limitations and participation restrictions.</p> <p>Aspects of health after flexor tendon repair could be assessed more adequately and cover patients' needs more sufficiently by choosing outcome measures which refer to all aspects of functioning.</p> <p>Conclusion</p> <p>The ICF can help to identify aspects of health which are not being considered. The ICF can help promote further development of adequate outcome measures including activity limitation and participation restrictions by targeting patient centred goals and respecting patients' needs.</p

Piccolo genotype modulates neural correlates of emotion processing but not executive functioning

Major depressive disorder (MDD) is characterized by affective symptoms and cognitive impairments, which have been associated with changes in limbic and prefrontal activity as well as with monoaminergic neurotransmission. A genome-wide association study implicated the polymorphism rs2522833 in the piccolo (PCLO) gene—involved in monoaminergic neurotransmission—as a risk factor for MDD. However, the role of the PCLO risk allele in emotion processing and executive function or its effect on their neural substrate has never been studied. We used functional magnetic resonance imaging (fMRI) to investigate PCLO risk allele carriers vs noncarriers during an emotional face processing task and a visuospatial planning task in 159 current MDD patients and healthy controls. In PCLO risk allele carriers, we found increased activity in the left amygdala during processing of angry and sad faces compared with noncarriers, independent of psychopathological status. During processing of fearful faces, the PCLO risk allele was associated with increased amygdala activation in MDD patients only. During the visuospatial planning task, we found no genotype effect on performance or on BOLD signal in our predefined areas as a function of increasing task load. The PCLO risk allele was found to be specifically associated with altered emotion processing, but not with executive dysfunction. Moreover, the PCLO risk allele appears to modulate amygdala function during fearful facial processing in MDD and may constitute a possible link between genotype and susceptibility for depression via altered processing of fearful stimuli. The current results may therefore aid in better understanding underlying neurobiological mechanisms in MDD

CAGO: A Software Tool for Dynamic Visual Comparison and Correlation Measurement of Genome Organization

CAGO (Comparative Analysis of Genome Organization) is developed to address two critical shortcomings of conventional genome atlas plotters: lack of dynamic exploratory functions and absence of signal analysis for genomic properties. With dynamic exploratory functions, users can directly manipulate chromosome tracks of a genome atlas and intuitively identify distinct genomic signals by visual comparison. Signal analysis of genomic properties can further detect inconspicuous patterns from noisy genomic properties and calculate correlations between genomic properties across various genomes. To implement dynamic exploratory functions, CAGO presents each genome atlas in Scalable Vector Graphics (SVG) format and allows users to interact with it using a SVG viewer through JavaScript. Signal analysis functions are implemented using R statistical software and a discrete wavelet transformation package waveslim. CAGO is not only a plotter for generating complex genome atlases, but also a platform for exploring genome atlases with dynamic exploratory functions for visual comparison and with signal analysis for comparing genomic properties across multiple organisms. The web-based application of CAGO, its source code, user guides, video demos, and live examples are publicly available and can be accessed at http://cbs.ym.edu.tw/cago

Genome-Wide Assessment of AU-Rich Elements by the AREScore Algorithm

In mammalian cells, AU-rich elements (AREs) are well known regulatory sequences located in the 3′ untranslated region (UTR) of many short-lived mRNAs. AREs cause mRNAs to be degraded rapidly and thereby suppress gene expression at the posttranscriptional level. Based on the number of AUUUA pentamers, their proximity, and surrounding AU-rich regions, we generated an algorithm termed AREScore that identifies AREs and provides a numerical assessment of their strength. By analyzing the AREScore distribution in the transcriptomes of 14 metazoan species, we provide evidence that AREs were selected for in several vertebrates and Drosophila melanogaster. We then measured mRNA expression levels genome-wide to address the importance of AREs in SL2 cells derived from D. melanogaster hemocytes. Tis11, a zinc finger RNA–binding protein homologous to mammalian tristetraprolin, was found to target ARE–containing reporter mRNAs for rapid degradation in SL2 cells. Drosophila mRNAs whose expression is elevated upon knock down of Tis11 were found to have higher AREScores. Moreover high AREScores correlate with reduced mRNA expression levels on a genome-wide scale. The precise measurement of degradation rates for 26 Drosophila mRNAs revealed that the AREScore is a very good predictor of short-lived mRNAs. Taken together, this study introduces AREScore as a simple tool to identify ARE–containing mRNAs and provides compelling evidence that AREs are widespread regulatory elements in Drosophila

Highly variable response to cytotoxic chemotherapy in carcinoma-associated fibroblasts (CAFs) from lung and breast

<p>Abstract</p> <p>Background</p> <p>Carcinoma-associated fibroblasts (CAFs) can promote carcinogenesis and tumor progression. Only limited data on the response of CAFs to chemotherapy and their potential impact on therapy outcome are available. This study was undertaken to analyze the influence of chemotherapy on carcinoma-associated fibroblasts (CAFs) <it>in vitro </it>and <it>in vivo</it>.</p> <p>Methods</p> <p>The <it>in vivo </it>response of stromal cells to chemotherapy was investigated in 22 neoadjuvant treated breast tumors on tissue sections before and after chemotherapy. Response to chemotherapy was analyzed <it>in vitro </it>in primary cultures of isolated CAFs from 28 human lung and 9 breast cancer tissues. The response was correlated to <it>Mdm2</it>, <it>ERCC1 </it>and <it>TP53 </it>polymorphisms and <it>TP53 </it>mutation status. Additionally, the cytotoxic effects were evaluated in an <it>ex vivo </it>experiment using cultured tissue slices from 16 lung and 17 breast cancer specimens.</p> <p>Results</p> <p>Nine of 22 tumors showed a therapy-dependent reduction of stromal activity. Pathological response of tumor or stroma cells did not correlate with clinical response. Isolated CAFs showed little sensitivity to paclitaxel. In contrast, sensitivity of CAFs to cisplatinum was highly variable with a GI50 ranging from 2.8 to 29.0 μM which is comparable to the range observed in tumor cell lines. No somatic <it>TP53 </it>mutation was detected in any of the 28 CAFs from lung cancer tissue. In addition, response to cisplatinum was not significantly associated with the genotype of <it>TP53 </it>nor <it>Mdm2 </it>and <it>ERCC1 </it>polymorphisms. However, we observed a non-significant trend towards decreased sensitivity in the presence of <it>TP53 </it>variant genotype. In contrast to the results obtained in isolated cell culture, in tissue slice culture breast cancer CAFs responded to paclitaxel within their microenvironment in the majority of cases (9/14). The opposite was observed in lung cancer tissues: only few CAFs were sensitive to cisplatinum within their microenvironment (2/15) whereas a higher proportion responded to cisplatinum in isolated culture.</p> <p>Conclusion</p> <p>Similar to cancer cells, CAF response to chemotherapy is highly variable. Beside significant individual/intrinsic differences the sensitivity of CAFs seems to depend also on the cancer type as well as the microenvironment.</p