Shock waves on complex networks

Power grids, road maps, and river streams are examples of infrastructural networks which are highly vulnerable to external perturbations. An abrupt local change of load (voltage, traffic density, or water level) might propagate in a cascading way and affect a significant fraction of the network. Almost discontinuous perturbations can be modeled by shock waves which can eventually interfere constructively and endanger the normal functionality of the infrastructure. We study their dynamics by solving the Burgers equation under random perturbations on several real and artificial directed graphs. Even for graphs with a narrow distribution of node properties (e.g., degree or betweenness), a steady state is reached exhibiting a heterogeneous load distribution, having a difference of one order of magnitude between the highest and average loads. Unexpectedly we find for the European power grid and for finite Watts-Strogatz networks a broad pronounced bimodal distribution for the loads. To identify the most vulnerable nodes, we introduce the concept of node-basin size, a purely topological property which we show to be strongly correlated to the average load of a node

A Systems Biology Interpretation of Array Comparative Genomic Hybridization (aCGH) Data through Phylogenetics

Array Comparative Genomic Hybridization (aCGH) is a rapid screening technique to detect gene deletions and duplications, providing an overview of chromosomal aberrations throughout the entire genome of a tumor, without the need for cell culturing. However, the heterogeneity of aCGH data obfuscates existing methods of data analysis. Analysis of aCGH data from a systems biology perspective or in the context of total aberrations is largely absent in the published literature. We present here a novel alternative to the functional analysis of aCGH data using the phylogenetic paradigm that is well-suited to high dimensional datasets of heterogeneous nature, but has not been widely adapted to aCGH data. Maximum parsimony phylogenetic analysis sorts out genetic data through the simplest presentation of the data on a cladogram, a graphical evolutionary tree, thus providing a powerful and efficient method for aCGH data analysis. For example, the cladogram models the multiphasic changes in the cancer genome and identifies shared early mutations in the disease progression, providing a simple yet powerful means of aCGH data interpretation. As such, applying maximum parsimony phylogenetic analysis to aCGH results allows for the differentiation between drivers and passenger genes aberrations in cancer specimens. In addition to offering a novel methodology to analyze aCGH results, we present here a crucial software suite that we wrote to carry out the analysis. In a broader context, we wish to underscore that phylogenetic analysis of aCGH data is a non-parametric method that circumvents the pitfalls and frustrations of standard analytical techniques that rely on parametric statistics. Organizing the data in a cladogram as explained in this research article provides insights into the disease common aberrations, as well as the disease subtypes and their shared aberrations (the synapomorphies) of each subtype. Hence, we report the method and make the software suite publicly and freely available at http://software.phylomcs.com so that researchers can test alternative and innovative approaches to the analysis of aCGH data

Large random correlations in individual mean field spin glass samples

We argue that complex systems must possess long range correlations and illustrate this idea on the example of the mean field spin glass model. Defined on the complete graph, this model has no genuine concept of distance, but the long range character of correlations is translated into a broad distribution of the spin-spin correlation coefficients for almost all realizations of the random couplings. When we sample the whole phase space we find that this distribution is so broad indeed that at low temperatures it essentially becomes uniform, with all possible correlation values appearing with the same probability. The distribution of correlations inside a single phase space valley is also studied and found to be much narrower.Comment: Added a few references and a comment phras

Epithelial 3D-spheroids as a tool to study air pollutant-induced lung pathology

Cigarette smoke (CS) and air pollutants (AP) activate pathological processes in bronchial epithelial cells resulting in lung function decline which severely impacts human health. Knowledge about the molecular mechanism(s) by which CS and AP induce pathology is limited. Our previous studies in 2D cultures of human bronchial epithelial (BEAS-2B) cells showed that CS exposure activates transforming growth factor-β1 (TGF-β1) release and signaling. Furthermore, CS exposure reduced the expression of E-cadherin, which was prevented by applying a TGF-β1 neutralizing antibody. Exposure of BEAS-2B cells cultured in 2D to diesel exhaust particles (DEP) increased TGF-β1 protein expression and reduced the expression of epithelial cell markers, whereas mesenchymal markers are upregulated. Conventional 2D cell culture may, however, not fully reflect the physiology of bronchial epithelial cells in vivo. To simulate the in vivo situation more closely we cultured the bronchial epithelial cells in a 3D environment in the current study. Treatment of epithelial spheroids with TGF-β resulted in reduced E-cadherin and increased collagen I expression, indicating the activation of epithelial-to-mesenchymal transition (EMT). Similarly, exposure of spheroids to DEP induced and EMT-like phenotype. Collectively, our data indicate AP induces an EMT-like phenotype of BEAS-2B cells in 3D spheroid cultures. This opens new avenues for drug development for the treatment of lung diseases induced by AP. The 3D spheroid cell culture is a novel, innovative and physiologically relevant model for culturing a variety of cells. It is a versatile tool for both high-throughput studies and for identifying molecular mechanisms involved in bronchial epithelial cell (patho)physiology

Citizens’ Food Habit Behavior and Food Waste Consequences during the First COVID-19 Lockdown in Spain

During the first COVID-19 wave in Spain, confining the population at home was seen as an effective way to prevent the disease from spreading. This limited mobility affected citizens’ routines at homes because it influenced their life habits, including food management. The main objective of this paper was to understand citizens’ food waste (FW) behavior during the first COVID-19 lockdown in Spain by understanding related food practices that could have influenced FW generation. An online survey was conducted from 14 May to 11 June, 2020; 6293 valid responses were collected and analyzed, and 95% of the participants declared not wasting more food than usual. On average, they reported wasting 234 g per household per week, which equals 88 g per capita. We found significant differences in the reported FW generation between participants regarding their age, gender, household composition, and employment status due to COVID-19. In addition, food-related behaviors such as buying more food than usual due to fear or anxiety, storing more food than before the lockdown, and improvising when buying groceries seemed to affect the FW reported by the participants. The paper ends by comparing the conclusions drawn by different works conducted in other countries for a similar purpose

Effect of correlations on network controllability

A dynamical system is controllable if by imposing appropriate external signals on a subset of its nodes, it can be driven from any initial state to any desired state in finite time. Here we study the impact of various network characteristics on the minimal number of driver nodes required to control a network. We find that clustering and modularity have no discernible impact, but the symmetries of the underlying matching problem can produce linear, quadratic or no dependence on degree correlation coefficients, depending on the nature of the underlying correlations. The results are supported by numerical simulations and help narrow the observed gap between the predicted and the observed number of driver nodes in real networks

Individualized Stabilization Criteria–Driven Ranibizumab versus Laser in Branch Retinal Vein Occlusion

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Injection into coal seams for simultaneous CO{sub 2} mitigation and enhanced recovery of coalbed methane. Topical report, March 1995--March 1996

The overall objective of this task is to test the technical viability of injecting CO{sub 2} into the Fruitland Coal to displace methane from the coal and to mitigate CO{sub 2} emissions that are a consequence of primary coalbed methane production from surrounding wells in the area. To evaluate this technical viability, a field test was conducted and the test is being interpreted using data measured in WRI`s laboratory, as well as using Amoco`s state-of-the-art coalbed methane simulator. Also, a second pilot of the process is being evaluated using the simulator. Ultimately, the technology developed will be applied to a Wyoming coal

Individualized Ranibizumab Regimen Driven by Stabilization Criteria for Central Retinal Vein Occlusion

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