Biomedical subjects

H Eugene Stanley

Publications and source records attributed to H Eugene Stanley.

At least 19 recordsLinked to original sources

PubMed2006

Percolation model for growth rates of aggregates and its application for business firm growth.

Motivated by recent empirical studies of business firm growth, we develop a dynamic percolation model which captures some of the features of the economical system--i.e., merging and splitting of business firms--represented as aggregates on a d-dimensional lattice. We find the steady-state distribution of the aggregate size and explore how this distribution depends on the model parameters. We find that at the critical threshold, the standard deviation of the aggregate growth rates, sigma, increases with aggregate size S as sigma approximately S(beta), where beta can be explained in terms of the connectedness length exponent nu and the fractal dimension d(f), with beta=1(2nud(f)) approximately 0.20 for d=2 and 0.125 for d-->infinity. The distributions of aggregate growth rates have a sharp peak at the center and pronounced wings extending over many standard deviations, giving the distribution a tent-shape form--the Laplace distribution. The distributions for different aggregate sizes scaled by their standard deviations collapse onto the same curve.

Journal Article↗

PubMed2006

Preferential attachment and growth dynamics in complex systems.

Complex systems can be characterized by classes of equivalency of their elements defined according to system specific rules. We propose a generalized preferential attachment model to describe the class size distribution. The model postulates preferential growth of the existing classes and the steady influx of new classes. According to the model, the distribution changes from a pure exponential form for zero influx of new classes to a power law with an exponential cut-off form when the influx of new classes is substantial. Predictions of the model are tested through the analysis of a unique industrial database, which covers both elementary units (products) and classes (markets, firms) in a given industry (pharmaceuticals), covering the entire size distribution. The model's predictions are in good agreement with the data. The paper sheds light on the emergence of the exponent tau approximately 2 observed as a universal feature of many biological, social and economic problems.

Journal Article↗

PubMed2006

Thermodynamics and dynamics of the two-scale spherically symmetric Jagla ramp model of anomalous liquids.

Using molecular dynamics simulations, we study the Jagla model of a liquid which consists of particles interacting via a spherically symmetric two-scale potential with both repulsive and attractive ramps. This potential displays anomalies similar to those found in liquid water, namely expansion upon cooling and an increase of diffusivity upon compression, as well as a liquid-liquid (LL) phase transition in the region of the phase diagram accessible to simulations. The LL coexistence line, unlike in tetrahedrally coordinated liquids, has a positive slope, because of the Clapeyron relation, corresponding to the fact that the high density phase (HDL) is more ordered than low density phase (LDL). When we cool the system at constant pressure above the critical pressure, the thermodynamic properties rapidly change from those of LDL-like to those of HDL-like upon crossing the Widom line. The temperature dependence of the diffusivity also changes rapidly in the vicinity of the Widom line, namely the slope of the Arrhenius plot sharply increases upon entering the HDL domain. The properties of the glass transition are different in the two phases, suggesting that the less ordered phase is fragile, while the more ordered phase is strong, which is consistent with the behavior of tetrahedrally coordinated liquids such as water silica, silicon, and BeF2.

Journal Article↗

PubMed2006

Optimization of the robustness of multimodal networks.

We investigate the robustness against both random and targeted node removal of networks in which P(k), the distribution of nodes with degree k, is a multimodal distribution, [formula--see text] with k(i) proportional to b -(i-1) and Dirac's delta function delta (x). We refer to this type of network as a scale-free multimodal network. For m=2, the network is a bimodal network; in the limit m approaches infinity, the network models a scale-free network. We calculate and optimize the robustness for given values of the number of modes m, the total number of nodes N, and the average degree , using analytical formulas for the random and targeted node removal thresholds for network collapse. We find, when N>>1, that (i) the robustness against random and targeted node removal for this multimodal network is controlled by a single combination of variables, N(1/m-1), (ii) the robustness of the multimodal network against targeted node removal decreases rapidly when the number of modes becomes larger than a critical value that is of the order of 1n N, and (iii) the values of exponent lambda(opt) that characterizes the scale-free degree distribution of the multimodal network that maximize the robustness against both random and targeted node removal fall between 2.5 and 3.

Journal Article↗

PubMed2006

Spurious detection of phase synchronization in coupled nonlinear oscillators.

Coupled nonlinear systems under certain conditions exhibit phase synchronization, which may change for different frequency bands or with the presence of additive system noise. In both cases, Fourier filtering is traditionally used to preprocess data. We investigate to what extent the phase synchronization of two coupled Rössler oscillators depends on (1) the broadness of their power spectrum, (2) the width of the bandpass filter, and (3) the level of added noise. We find that for identical coupling strengths, oscillators with broader power spectra exhibit weaker synchronization. Further, we find that within a broad bandwidth range, bandpass filtering reduces the effect of noise but can lead to a spurious increase in the degree of phase synchronization with narrowing bandwidth, even when the coupling between the two oscillators remains the same.

Biophysics↗

PubMed2006

Thermodynamic and dynamic anomalies for dumbbell molecules interacting with a repulsive ramplike potential.

Using collision driven discrete molecular dynamics, we investigate the thermodynamics and dynamics of systems of 500 dumbbell molecules interacting by a purely repulsive ramplike discretized potential, consisting of n steps of equal size. We compare the behavior of the two systems, with n=18 and n=144 steps. Each system exhibits both thermodynamic and dynamic anomalies, a density maximum and the translational and rotational mobilities show anomalous behavior. Starting with very dense systems and decreasing the density, both mobilities first increase, reach a maximum, then decrease, reach a minimum, and finally increase; this behavior is similar to the behavior of SPC/E (Simple Point Charge-Extended) water. The regions in the pressure-temperature plane of translational and rotational mobility anomalies depend strongly on n. The product of the translational diffusion coefficient and the orientational correlation time increases with temperature, in contrast with the behavior of most liquids.

Journal Article↗

PubMed2006

Family of tunable spherically symmetric potentials that span the range from hard spheres to waterlike behavior.

We investigate the equation of state, diffusion coefficient, and structural order of a family of spherically symmetric potentials consisting of a hard core and a linear repulsive ramp. This generic potential has two characteristic length scales: the hard and soft core diameters. The family of potentials is generated by varying their ratio, lambda. We find negative thermal expansion (thermodynamic anomaly) and an increase of the diffusion coefficient upon isothermal compression (dynamic anomaly) for 0< or =lambda<6/7. As in water, the regions where these anomalies occur are nested domes in the (T, p) or (T, P) planes , with the thermodynamic anomaly dome contained entirely within the dynamic anomaly dome. We calculate translational and orientational order parameters (t and Q6), and project equilibrium state points onto the (t, Q6) plane, or order map. The order map evolves from waterlike behavior to hard-sphere-like behavior upon varying lambda between 4/7 and 6/7. Thus, we traverse the range of liquid behavior encompassed by hard spheres (lanbda=1) and waterlike (lambda approximately 4/7) with a family of tunable spherically symmetric potentials by simply varying the ratio of hard to soft-core diameters. Although dynamic and thermodynamic anomalies occur almost across the entire range 0< or=lambda< or=1, waterlike structural anomalies (i.e., decrease in both t and Q6 upon compression and strictly correlated T and Q6 in the anomalous region) occur only around lambda=4/7. Waterlike anomalies in structure, dynamics and thermodynamics arise solely due to the existence of two length scales, with their ratio lambda being the single control parameter, orientation-dependent interactions being absent by design.

Journal Article↗

PubMed2006

Transport in weighted networks: partition into superhighways and roads.

Transport in weighted networks is dominated by the minimum spanning tree (MST), the tree connecting all nodes with the minimum total weight. We find that the MST can be partitioned into two distinct components, having significantly different transport properties, characterized by centrality--the number of times a node (or link) is used by transport paths. One component, superhighways, is the infinite incipient percolation cluster, for which we find that nodes (or links) with high centrality dominate. For the other component, roads, which includes the remaining nodes, low centrality nodes dominate. We find also that the distribution of the centrality for the infinite incipient percolation cluster satisfies a power law, with an exponent smaller than that for the entire MST. The significance of this finding is that one can improve significantly the global transport by improving a tiny fraction of the network, the superhighways.

Computer Simulation↗

PubMed2006

Molecular dynamics study of orientational cooperativity in water.

Recent experiments on liquid water show collective dipole orientation fluctuations dramatically slower than expected (with relaxation time > 50 ns) [D.P. Shelton, Phys. Rev. B 72, 020201(R) (2005)]. Molecular dynamics simulations of extended simple point charge (SPC/E) water show a large vortexlike structure of the dipole field at ambient conditions surviving over [J. Higo, Proc. Natl. Acad. Sci. U.S.A. 98, 5961 (2001)]. Both results disagree with previous results on water dipoles in similar conditions, for which autocorrelation times are a few picoseconds. Motivated by these recent results, we study the water dipole reorientation using molecular dynamics simulations of the SPC/E model in bulk water for temperatures ranging from ambient 300 K down to the deep supercooled region of the phase diagram at 210 K. First, we calculate the dipole autocorrelation function and find that our simulations are well described by a stretched exponential decay, from which we calculate the orientational autocorrelation time t(alpha). Second, we define a second characteristic time, namely, the time required for the randomization of molecular dipole orientation, the self-dipole randomization time t(r), which is an upper limit on t(alpha); we find that t(r) is approximately equal to 5t(alpha). Third, to check if there are correlated domains of dipoles in water which have large relaxation times compared to the individual dipoles, we calculate the randomization time t(box) of the site-dipole field, the net dipole moment formed by a set of molecules belonging to a box of edge L(box). We find that the site-dipole randomization time t(box) is approximately equal to 2.5t(alpha) for L(box) approximately equal to 3 A, i.e., it is shorter than the same quantity calculated for the self-dipole. Finally, we find that the orientational correlation length is short even at low T.

Journal Article↗

PubMed2006

Optimal paths in strong and weak disorder: a unified approach.

We present a unified scaling theory for the optimal path connecting opposite edges of a disordered lattice of size L. Each bond of the lattice is assigned a cost exp(ar), where r is a uniformly distributed random variable and a is disorder strength. The optimal path minimizes the sum of the costs of the bonds along the path. We argue that for L>>a(nu) , where nu is the correlation exponent of percolation, the path becomes equivalent to a directed polymer on an effective lattice consisting of blobs of size xi=a(nu). It is self-affined and characterized by the roughness exponent of directed polymers chi. For L<<a(nu), or on the length scales below the blob size xi, the path behaves as an optimal path in the strong disorder limit. It has a self-similar fractal shape with fractal dimension d(opt). We derived the scaling relations for the length of the path, its transversal displacement, the average cost and its fluctuation. We test our scaling theoretical predictions by numerical simulations on a square lattice.

Journal Article↗

PubMed2006

Cross-correlation of instantaneous phase increments in pressure-flow fluctuations: applications to cerebral autoregulation.

We investigate the relationship between the blood flow velocities (BFV) in the middle cerebral arteries and beat-to-beat blood pressure (BP) recorded from a finger in healthy and post-stroke subjects during the quasisteady state after perturbation for four different physiologic conditions: supine rest, head-up tilt, hyperventilation, and CO2 rebreathing in upright position. To evaluate whether instantaneous BP changes in the steady state are coupled with instantaneous changes in the BFV, we compare dynamical patterns in the instantaneous phases of these signals, obtained from the Hilbert transform, as a function of time. We find that in post-stroke subjects the instantaneous phase increments of BP and BFV exhibit well-pronounced patterns that remain stable in time for all four physiologic conditions, while in healthy subjects these patterns are different, less pronounced, and more variable. We propose an approach based on the cross-correlation of the instantaneous phase increments to quantify the coupling between BP and BFV signals. We find that the maximum correlation strength is different for the two groups and for the different conditions. For healthy subjects the amplitude of the cross-correlation between the instantaneous phase increments of BP and BFV is small and attenuates within 3-5 heartbeats. In contrast, for post-stroke subjects, this amplitude is significantly larger and cross-correlations persist up to 20 heartbeats. Further, we show that the instantaneous phase increments of BP and BFV are cross-correlated even within a single heartbeat cycle. We compare the results of our approach with three complementary methods: direct BP-BFV cross-correlation, transfer function analysis, and phase synchronization analysis. Our findings provide insight into the mechanism of cerebral vascular control in healthy subjects, suggesting that this control mechanism may involve rapid adjustments (within a heartbeat) of the cerebral vessels, so that BFV remains steady in response to changes in peripheral BP.

Blood Flow Velocity↗

PubMed2006

Scaling and memory of intraday volatility return intervals in stock markets.

We study the return interval tau between price volatilities that are above a certain threshold q for 31 intraday data sets, including the Standard and Poor's 500 index and the 30 stocks that form the Dow Jones Industrial index. For different threshold q, the probability density function Pq(tau)scales with the mean interval tau as [Formula: see text], similar to that found in daily volatilities. Since the intraday records have significantly more data points compared to the daily records, we could probe for much higher thresholds and still obtain good statistics. We find that the scaling function f(x)is consistent for all 31 intraday data sets in various time resolutions, and the function is well-approximated by the stretched exponential, f(x) similar to e(-ax)(gamma), with gamma=0.38+/-0.05 and a=3.9+/-0.5, which indicates the existence of correlations. We analyze the conditional probability distribution Pq(tau/tau0) for tau following a certain interval tau0, and find Pq(tau/tau0) depends on tau0, which demonstrates memory in intraday return intervals. Also, we find that the mean conditional interval (tau/tau0) increases with tau0, consistent with the memory found for Pq(tau/tau0). Moreover, we find that return interval records, in addition to having short-term correlations as demonstrated by Pq(tau/tau0), have long-term correlations with correlation exponents similar to that of volatility records.

Journal Article↗

PubMed2006

Universal behavior of optimal paths in weighted networks with general disorder.

We study the statistics of the optimal path in both random and scale-free networks, where weights are taken from a general distribution P(w). We find that different types of disorder lead to the same universal behavior. Specifically, we find that a single parameter (S defined as AL(-1/v) for d-dimensional lattices, and S defined as AN(-1/3) for random networks) determines the distributions of the optimal path length, including both strong and weak disorder regimes. Here v is the percolation connectivity exponent, and A depends on the percolation threshold and P(w). We show that for a uniform P(w), Poisson or Gaussian, the crossover from weak to strong does not occur, and only weak disorder exists.

Journal Article↗

PubMed2006

Scale-free networks emerging from weighted random graphs.

We study Erdös-Rényi random graphs with random weights associated with each link. We generate a "supernode network" by merging all nodes connected by links having weights below the percolation threshold (percolation clusters) into a single node. We show that this network is scale-free, i.e., the degree distribution is P(k) approximately k(-lambda) with lambda=2.5. Our results imply that the minimum spanning tree in random graphs is composed of percolation clusters, which are interconnected by a set of links that create a scale-free tree with lambda=2.5. We suggest that optimization causes the percolation threshold to emerge spontaneously, thus creating naturally a scale-free supernode network. We discuss the possibility that this phenomenon is related to the evolution of several real world scale-free networks.

Journal Article↗

PubMed2006

Relation between rotational and translational dynamic heterogeneities in water.

We use molecular dynamics simulations to probe the rotational dynamics of the extended simple point charge model of water for a range of temperatures down to 200 K, 6 K above the mode coupling temperature. We find that rotational dynamics is spatially heterogeneous; i.e., there are clusters of molecules that rotate significantly more than the average for a given time interval, and we study the size and the temporal behavior of these clusters. We find that the position of a rotational heterogeneity is strongly correlated with the position of a translational heterogeneity, and that the fraction of molecules belonging to both kinds of heterogeneities increases with decreasing temperature. We further find that although the two types of heterogeneities are not identical, they are related to the same physical picture.

Computer Simulation↗

PubMed2006

Ab initio discrete molecular dynamics approach to protein folding and aggregation.

Understanding the toxicity of amyloidogenic protein aggregates and designing therapeutic approaches require the knowledge of their structure at atomic resolution. Although solid-state NMR, X-ray diffraction, and other experimental techniques are capable of discerning the protein fibrillar structure, determining the structures of early aggregates, called oligomers, is a challenging experimental task. Computational studies by all-atom molecular dynamics, which provides a complete description of a protein in the solvent, are typically limited to study folding of smaller protein or aggregation of a small number of short protein fragments. We review an efficient ab initio computer simulation approach to protein folding and aggregation using discrete molecular dynamics (DMD) in combination with several coarse-grained protein models and implicit solvent. This approach involves different complexity levels in both the protein model and the interparticle interactions. Starting from the simplest protein model with minimal interactions, and gradually increasing its complexity, while guided by in vitro findings, we can systematically select the key features of the protein model and interactions that drive protein folding and aggregation. Because the method used in this DMD approach does not require any knowledge of the native or any other state of the protein, it can be applied to study degenerative disorders associated with protein misfolding and aberrant protein aggregation. The choice of the coarse-grained model depends on the complexity of the protein and specific questions to be addressed, which are mostly suggested by in vitro findings. Thus, we illustrate our approach on amyloid beta-protein (Abeta) associated with Alzheimer's disease (AD). Despite the simplifications introduced in the DMD approach, the predicted Abeta conformations are in agreement with existing experimental data. The in silico findings also provide further insights into the structure and dynamics of Abeta folding and oligomer formation that are amenable to in vitro testing.

Amyloid beta-Peptides↗

PubMed2006

Elucidating amyloid beta-protein folding and assembly: A multidisciplinary approach.

Oligomeric, neurotoxic amyloid protein assemblies are thought to be causative agents in Alzheimer's and other neurodegenerative diseases. Development of oligomer-specific therapeutic agents requires a mechanistic understanding of the oligomerization process. This is a daunting task because amyloidogenic protein oligomers often are metastable and comprise structurally heterogeneous populations in equilibrium with monomers and fibrils. A single methodological approach cannot elucidate the entire protein assembly process. An integrated multidisciplinary program is required. We discuss here the synergistic application of in hydro, in vacuo, and in silico methods to the study of the amyloid beta-protein, the key pathogenetic agent in Alzheimer's disease.

Amino Acid Sequence↗

PubMed2006

Computer simulations of Alzheimer's amyloid beta-protein folding and assembly.

Pathological folding and aggregation of the amyloid beta-protein (Abeta) are widely perceived as central to understanding Alzheimer's disease (AD) at the molecular level. Experimental approaches to study Abeta self-assembly are limited, because most relevant aggregates are quasi-stable and inhomogeneous. In contrast, simulations can provide significant insights into the problem, including specific sites in the molecule that would be attractive for drug targeting and details of the assembly pathways leading to the production of toxic assemblies. Here we review computer simulation approaches to understanding the structural biology of Abeta. We discuss the ways in which these simulations help guide experimental work, and in turn, how experimental results guide the development of theoretical and simulation approaches that may be of general utility in understanding pathologic protein folding and assembly.

Alzheimer Disease↗