370 research outputs found
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
Perineural resiniferatoxin selectively inhibits inflammatory hyperalgesia
Resiniferatoxin (RTX) is an ultrapotent capsaicin analog that binds to the transient receptor potential channel, vanilloid subfamily member 1 (TRPV1). There is a large body of evidence supporting a role for TRPV1 in noxious-mediated and inflammatory hyperalgesic responses. In this study, we evaluated low, graded, doses of perineural RTX as a method for regional pain control. We hypothesized that this approach can provide long-term, but reversible, blockade of a portion of nociceptive afferent fibers within peripheral nerves when given at a site remote from the neuronal perikarya in the dorsal root ganglia. Following perineural RTX application to the sciatic nerve, we demonstrated a significant inhibition of inflammatory nociception that was dose- and time-dependent. At the same time, treated animals maintained normal proprioceptive sensations and motor control, and other nociceptive responses were largely unaffected. Using a range of mechanical and thermal algesic tests, we found that the most sensitive measure following perineural RTX administration was inhibition of inflammatory hyperalgesia. Recovery studies showed that physiologic sensory function could return as early as two weeks post-RTX treatment, however, immunohistochemical examination of the DRG revealed a partial, but significant reduction in the number of the TRPV1-positive neurons. We propose that this method could represent a beneficial treatment for a range of chronic pain problems, including neuropathic and inflammatory pain not responding to other therapies
Responses of Multipotent Retinal Stem Cells to IL-1 β
Purpose. To investigate how multipotent retinal stem cells (RSCs) isolated from mice respond to the proinflammatory signaling molecules, IL-1β, IL-18, and IL-17A. Materials and Methods. RSCs were cultured in a specific culture medium and were treated with these cytokines. Cell viability was detected by MTT assay; ultrastructure was evaluated by transmission electron microscopy; expression of IL-17rc and proapoptotic proteins was detected by immunocytochemistry and expression of Il-6 and Il-17a was detected by quantitative RT-PCR. As a comparison, primary mouse retinal pigment epithelium (RPE) cells were also treated with IL-1β, IL-18, or IL-17A and analyzed for the expression of Il-6 and Il-17rc. Results. Treatment with IL-1β, IL-18, or IL-17A decreased RSC viability in a dose-dependent fashion and led to damage in cellular ultrastructure including pyroptotic and/or necroptotic cells. IL-1β and IL-18 could induce proapoptotic protein expression. All treatments induced significantly higher expression of Il-6 and Il-17rc in both cells. However, neither IL-1β nor IL-18 could induce Il-17a expression in RSCs. Conclusions. IL-1β, IL-18, and IL-17A induce retinal cell death via pyroptosis/necroptosis and apoptosis. They also provoke proinflammatory responses in RSCs. Though IL-1β and IL-18 could not induce Il-17a expression in RSCs, they both increase Il-17rc expression, which may mediate the effect of Il-17a
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
A Novel Paradigm Between Leukocytosis, G-CSF Secretion, Neutrophil-to-Lymphocyte Ratio, Myeloid-Derived Suppressor Cells, and Prognosis in Non-small Cell Lung Cancer
Leukocytosis is a common feature of malignancies. While controversial, there appears to be an association between the degree of tumor-related leukocytosis and prognosis. In this paper, we provide evidence supporting an untapped clinical paradigm linking G-CSF secretion to the induction of leukocytosis and expansion of myeloid-derived suppressor cells, providing an explanation for the association between leukocytosis, elevated neutrophil-to-lymphocyte ratios and prognosis in non-small cell lung cancer. Clinically validating this mechanism may identify MDSCs and G-CSF as dynamic markers of early disease progression and therapeutic response, and shed light onto novel therapeutic avenues for the treatment of patients with non-small cell lung cancer
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
A universal preconditioner for simulating condensed phase materials.
We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonstrate the gain in computational efficiency in a wide range of materials that include metals, insulators, and molecular solids. The simple structure of the preconditioner means that the gains can be realised in practice not only when using expensive electronic structure models but also for fast empirical potentials. Even for relatively small systems of a few hundred atoms, we observe speedups of a factor of two or more, and the gain grows with system size. An open source Python implementation within the Atomic Simulation Environment is available, offering interfaces to a wide range of atomistic codes
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