Non-equilibrium Dynamics of O(N) Nonlinear Sigma models: a Large-N approach

We study the time evolution of the mass gap of the O(N) non-linear sigma model in 2+1 dimensions due to a time-dependent coupling in the large-$N$ limit. Using the Schwinger-Keldysh approach, we derive a set of equations at large $N$ which determine the time dependent gap in terms of the coupling. These equations lead to a criterion for the breakdown of adiabaticity for slow variation of the coupling leading to a Kibble-Zurek scaling law. We describe a self-consistent numerical procedure to solve these large-$N$ equations and provide explicit numerical solutions for a coupling which starts deep in the gapped phase at early times and approaches the zero temperature equilibrium critical point $g_c$ in a linear fashion. We demonstrate that for such a protocol there is a value of the coupling $g= g_c^{\rm dyn}> g_c$ where the gap function vanishes, possibly indicating a dynamical instability. We study the dependence of $g_c^{\rm dyn}$ on both the rate of change of the coupling and the initial temperature. We also verify, by studying the evolution of the mass gap subsequent to a sudden change in $g$, that the model does not display thermalization within a finite time interval $t_0$ and discuss the implications of this observation for its conjectured gravitational dual as a higher spin theory in $AdS_4$.Comment: 22 pages, 9 figures. Typos corrected, references rearranged and added.v3 : sections rearranged, abstract modified, comment about Kibble-Zurek scaling correcte

Artificial Neural Network Inference (ANNI): A Study on Gene-Gene Interaction for Biomarkers in Childhood Sarcomas

Objective: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI). Method: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. Results: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. Conclusions: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas

Selective Enhancement of Insulin Sensitivity in the Endothelium In Vivo Reveals a Novel Proatherosclerotic Signaling Loop

Rationale: In the endothelium, insulin stimulates endothelial NO synthase (eNOS) to generate the antiatherosclerotic signaling radical NO. Insulin-resistant type 2 diabetes mellitus is associated with reduced NO availability and accelerated atherosclerosis. The effect of enhancing endothelial insulin sensitivity on NO availability is unclear. Objective: To answer this question, we generated a mouse with endothelial cell (EC)–specific overexpression of the human insulin receptor (hIRECO) using the Tie2 promoter–enhancer. Methods and Results: hIRECO demonstrated significant endothelial dysfunction measured by blunted endothelium-dependent vasorelaxation to acetylcholine, which was normalized by a specific Nox2 NADPH oxidase inhibitor. Insulin-stimulated phosphorylation of protein kinase B was increased in hIRECO EC as was Nox2 NADPH oxidase–dependent generation of superoxide, whereas insulin-stimulated and shear stress–stimulated eNOS activations were blunted. Phosphorylation at the inhibitory residue Y657 of eNOS and expression of proline-rich tyrosine kinase 2 that phosphorylates this residue were significantly higher in hIRECO EC. Inhibition of proline-rich tyrosine kinase 2 improved insulin-induced and shear stress–induced eNOS activation in hIRECO EC. Conclusions: Enhancing insulin sensitivity specifically in EC leads to a paradoxical decline in endothelial function, mediated by increased tyrosine phosphorylation of eNOS and excess Nox2-derived superoxide. Increased EC insulin sensitivity leads to a proatherosclerotic imbalance between NO and superoxide. Inhibition of proline-rich tyrosine kinase 2 restores insulin-induced and shear stress–induced NO production. This study demonstrates for the first time that increased endothelial insulin sensitivity leads to a proatherosclerotic imbalance between NO and superoxide

Discovering study-specific gene regulatory networks

This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets

Visualization of the intracavitary blood flow in systemic ventricles of Fontan patients by contrast echocardiography using particle image velocimetry

<p>Abstract</p> <p>Background</p> <p>Flow patterns in univentricular hearts may have clinical value. Therefore, it is our objective to asses and characterize vortex flow patterns with Fontan circulation in comparison with healthy controls.</p> <p>Methods</p> <p>Twenty-three patients (8 Fontan and 15 normal patients) underwent echocardiography with intravenous contrast agent (Sonovue^®) administration. Dedicated software was used to perform particle image velocimetry (PIV) and to visualize intracavitary flow in the systemic ventricles of the patients. Vortex parameters including vortex depth, length, width, and sphericity index were measured. Vortex pulsatility parameters including relative strength, vortex relative strength, and vortex pulsation correlation were also measured.</p> <p>Results</p> <p>The data from this study show that it is feasible to perform particle velocimetry in Fontan patients. Vortex length (VL) was significantly lower (0.51 ± 0.09 vs 0.65 ± 0.12, <it>P </it>= 0.010) and vortex width (VW) (0.32 ± 0.06 vs 0.27 ± 0.04, <it>p </it>= 0.014), vortex pulsation correlation (VPC) (0.26 ± 0.25 vs -0.22 ± 0.87, <it>p </it>= 0.05) were significantly higher in Fontan patients. Sphericity index (SI) (1.66 ± 0.48 vs 2.42 ± 0.62, <it>p </it>= 0.005), relative strength (RS) (0.77 ± 0.33 vs 1.90 ± 0.47, <it>p </it>= 0.0001), vortex relative strength (VRS) (0.18 ± 0.13 vs 0.43 ± 0.14, <it>p </it>= 0.0001) were significantly lower in the Fontan patients group.</p> <p>Conclusions</p> <p>PIV using contrast echocardiography is feasible in Fontan patients. Fontan patients had aberrant flow patterns as compared to normal hearts in terms of position, shape and sphericity of the main vortices. The vortex from the Fontan group was consistently shorter, wider and rounder than in controls. Whether vortex characteristics are related with clinical outcome is subject to further investigation.</p

Effect of Different Stages of Tensile Deformation on Magnetic Barkhausen Emission in High Strength Low Alloy Steel

Micromagnetic techniques have been considered as a potential non-destructive evaluation (NDE) method for microstructural characterization and stress/strain measurements in ferritic steels [1–14]. The effect of tensile deformation on micromagnetic parameters has been studied by many researchers [8–14]. Most of these studies have been done only in the elastic region and the obtained relation between magnetic parameters and the applied stress has been used to determine the residual stresses, considering that the residual stress level will not exceed the yield stress of the material. These studies have not taken into account the microstructural changes due to dislocations generation by the plastic deformation.</p

The what and where of adding channel noise to the Hodgkin-Huxley equations

One of the most celebrated successes in computational biology is the Hodgkin-Huxley framework for modeling electrically active cells. This framework, expressed through a set of differential equations, synthesizes the impact of ionic currents on a cell's voltage -- and the highly nonlinear impact of that voltage back on the currents themselves -- into the rapid push and pull of the action potential. Latter studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the Hodgkin-Huxley equations. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic Hodgkin-Huxley equations. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly Matlab simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html.Comment: 14 pages, 3 figures, review articl

Identification of a novel zinc metalloprotease through a global analysis of clostridium difficile extracellular proteins

Clostridium difficile is a major cause of infectious diarrhea worldwide. Although the cell surface proteins are recognized to be important in clostridial pathogenesis, biological functions of only a few are known. Also, apart from the toxins, proteins exported by C. difficile into the extracellular milieu have been poorly studied. In order to identify novel extracellular factors of C. difficile, we analyzed bacterial culture supernatants prepared from clinical isolates, 630 and R20291, using liquid chromatography-tandem mass spectrometry. The majority of the proteins identified were non-canonical extracellular proteins. These could be largely classified into proteins associated to the cell wall (including CWPs and extracellular hydrolases), transporters and flagellar proteins. Seven unknown hypothetical proteins were also identified. One of these proteins, CD630_28300, shared sequence similarity with the anthrax lethal factor, a known zinc metallopeptidase. We demonstrated that CD630_28300 (named Zmp1) binds zinc and is able to cleave fibronectin and fibrinogen in vitro in a zinc-dependent manner. Using site-directed mutagenesis, we identified residues important in zinc binding and enzymatic activity. Furthermore, we demonstrated that Zmp1 destabilizes the fibronectin network produced by human fibroblasts. Thus, by analyzing the exoproteome of C. difficile, we identified a novel extracellular metalloprotease that may be important in key steps of clostridial pathogenesis

Cardiac MR Elastography: Comparison with left ventricular pressure measurement

Purpose of the Study: To compare magnetic resonance elastography (MRE) with ventricular pressure changes in an animal model. Methods: Three pigs of different cardiac physiology (weight, 25 to 53 kg; heart rate, 61 to 93 bpm; left ventricular [LV] end-diastolic volume, 35 to 70 ml) were subjected to invasive LV pressure measurement by catheter and noninvasive cardiac MRE. Cardiac MRE was performed in a short-axis view of the heart and applying a 48.3-Hz shear-wave stimulus. Relative changes in LV-shear wave amplitudes during the cardiac cycle were analyzed. Correlation coefficients between wave amplitudes and LV pressure as well as between wave amplitudes and LV diameter were determined. Results: A relationship between MRE and LV pressure was observed in all three animals (R-square [greater than or equal to] 0.76). No correlation was observed between MRE and LV diameter (R-square [less than or equal to] 0.15). Instead, shear wave amplitudes decreased 102 +/- 58 ms earlier than LV diameters at systole and amplitudes increased 175 +/- 40 ms before LV dilatation at diastole. Amplitude ratios between diastole and systole ranged from 2.0 to 2.8, corresponding to LV pressure differences of 60 to 73 mmHg. Conclusion: Externally induced shear waves provide information reflecting intraventricular pressure changes which, if substantiated in further experiments, has potential to make cardiac MRE a unique noninvasive imaging modality for measuring pressure-volume function of the heart

Mathematical model of a telomerase transcriptional regulatory network developed by cell-based screening: analysis of inhibitor effects and telomerase expression mechanisms

Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability