Global organization of metabolic fluxes in the bacterium Escherichia coli.

Cellular metabolism, the integrated interconversion of thousands of metabolic substrates through enzyme-catalysed biochemical reactions, is the most investigated complex intracellular web of molecular interactions. Although the topological organization of individual reactions into metabolic networks is well understood, the principles that govern their global functional use under different growth conditions raise many unanswered questions. By implementing a flux balance analysis of the metabolism of Escherichia coli strain MG1655, here we show that network use is highly uneven. Whereas most metabolic reactions have low fluxes, the overall activity of the metabolism is dominated by several reactions with very high fluxes. E. coli responds to changes in growth conditions by reorganizing the rates of selected fluxes predominantly within this high-flux backbone. This behaviour probably represents a universal feature of metabolic activity in all cells, with potential implications for metabolic engineering.

Freezing by heating in a driven mesoscopic system

We investigate a simple model corresponding to particles driven in opposite directions and interacting via a repulsive potential. The particles move off-lattice on a periodic strip and are subject to random forces as well. We show that this model-which can be considered as a continuum version of some driven diffusive systems-exhibits a paradoxical, new kind of transition called here "freezing by heating." One interesting feature of this transition is that a crystallized state with a higher total energy is obtained from a fluid state by increasing the amount of fluctuations.

Jamming and fluctuations in granular drag

We investigate the dynamic evolution of jamming in granular media through fluctuations in the granular drag force. The successive collapse and formation of jammed states give a stick-slip nature to the fluctuations which is independent of the contact surface between the grains and the dragged object, thus implying that the stress-induced collapse is nucleated in the bulk of the granular sample. We also find that while the fluctuations are periodic at small depths, they become "stepped" at large depths, a transition which we interpret as a consequence of the long-range nature of the force chains.

Locomotion and proliferation of glioblastoma cells in vitro: statistical evaluation of videomicroscopic observations.

OBJECT: The motility and doubling of human glioblastoma cells were investigated by means of statistical evaluation of large sets of data obtained using computer-aided videomicroscopy. METHODS: Data were obtained on cells in four established glioblastoma cell lines and also on primary tumor cells cultured from fresh surgical samples. Growth rates and cell cycle times were measured in individual microscopic fields. The averages of cell cycle time and the duplication time for the recorded cell populations were 26.2 +/- 5.6 hours and 38 +/- 4 hours, respectively. With these parameters, no significant differences among the cell lines were revealed. Also, there was no correlation in the cell cycle time of a parent cell and its progeny in any of the cultures. Statistical analysis of cell locomotion revealed an exponential distribution of cell velocities and strong fluctuations in individual cell velocities across time. The average velocity values ranged from 4.2 to 27.9 micro/hour. In spite of the uniform histopathological classification of the four tumors, each cell line produced by these tumors displayed distinct velocity distribution profiles and characteristic average velocity values. A comparison of recently established primary cultures with cell lines that had propagated multiple times indicated that cells derived from different tumors sustain their characteristic locomotor activity after several passages. CONCLUSIONS: It can be inferred from the data that statistical evaluation of physical parameters of cell locomotion can provide additional tools for tumor diagnosis.

Theory of periodic swarming of bacteria: application to Proteus mirabilis.

The periodic swarming of bacteria is one of the simplest examples for pattern formation produced by the self-organized collective behavior of a large number of organisms. In the spectacular colonies of Proteus mirabilis (the most common species exhibiting this type of growth), a series of concentric rings are developed as the bacteria multiply and swarm following a scenario that periodically repeats itself. We have developed a theoretical description for this process in order to obtain a deeper insight into some of the typical processes governing the phenomena in systems of many interacting living units. Our approach is based on simple assumptions directly related to the latest experimental observations on colony formation under various conditions. The corresponding one-dimensional model consists of two coupled differential equations investigated here both by numerical integrations and by analyzing the various expressions obtained from these equations using a few natural assumptions about the parameters of the model. We determine the phase diagram corresponding to systems exhibiting periodic swarming, and discuss in detail how the various stages of the colony development can be interpreted in our framework. We point out that all of our theoretical results are in excellent agreement with the complete set of available observations. Thus the present study represents one of the few examples where self-organized biological pattern formation is understood within a relatively simple theoretical approach, leading to results and predictions fully compatible with experiments.

Development of correlations in the dynamics of wet granular avalanches.

A detailed characterization of avalanche dynamics of wet granular media in a rotating drum apparatus is presented. The results confirm the existence of the three wetness regimes observed previously: the granular, the correlated, and the viscoplastic regime. These regimes show qualitatively different dynamic behaviors that are reflected in all the investigated quantities. We discuss the effect of interstitial liquid on the characteristic angles of the material and on the avalanche size distribution. These data also reveal logarithmic aging and allow us to map out the phase diagram of the dynamic behavior as a function of liquid content and flow rate. Via quantitative measurements of the flow velocity and the granular flux during avalanches, we characterize avalanche types unique to wet media. We also explore the details of viscoplastic flow (observed at the highest liquid contents) in which there are lasting contacts during flow, leading to coherence across the entire sample. This coherence leads to a velocity independent flow depth at high rotation rates and robust pattern formation in the granular surface.

Spectra of "real-world" graphs: beyond the semicircle law.

Many natural and social systems develop complex networks that are usually modeled as random graphs. The eigenvalue spectrum of these graphs provides information about their structural properties. While the semicircle law is known to describe the spectral densities of uncorrelated random graphs, much less is known about the spectra of real-world graphs, describing such complex systems as the Internet, metabolic pathways, networks of power stations, scientific collaborations, or movie actors, which are inherently correlated and usually very sparse. An important limitation in addressing the spectra of these systems is that the numerical determination of the spectra for systems with more than a few thousand nodes is prohibitively time and memory consuming. Making use of recent advances in algorithms for spectral characterization, here we develop methods to determine the eigenvalues of networks comparable in size to real systems, obtaining several surprising results on the spectra of adjacency matrices corresponding to models of real-world graphs. We find that when the number of links grows as the number of nodes, the spectral density of uncorrelated random matrices does not converge to the semicircle law. Furthermore, the spectra of real-world graphs have specific features, depending on the details of the corresponding models. In particular, scale-free graphs develop a trianglelike spectral density with a power-law tail, while small-world graphs have a complex spectral density consisting of several sharp peaks. These and further results indicate that the spectra of correlated graphs represent a practical tool for graph classification and can provide useful insight into the relevant structural properties of real networks.

Stick-slip fluctuations in granular drag.

We study fluctuations in the drag force experienced by an object moving through a granular medium. The successive formation and collapse of jammed states give a stick-slip nature to the fluctuations which are periodic at small depths but become "stepped" at large depths, a transition that we interpret as a consequence of the long-range nature of the force chains and the finite size of our experiment. Another important finding is that the mean force and the fluctuations appear to be independent of the properties of the contact surface between the grains and the dragged object. These results imply that the drag force originates in the bulk properties of the granular sample.

Collective transport in locally asymmetric periodic structures.

In this paper we give an overview of the cooperative effects in fluctuation driven transport arising from the interaction of a large number of particles. (i) First, we study a model with finite-sized, overdamped Brownian particles interacting via hard-core repulsion. Computer simulations and theoretical calculations reveal a number of novel cooperative transport phenomena in this system, including the reversal of direction of the net current as the particle density is increased, and a very strong and complex dependence of the average velocity on both the size and the average distance of the particles. (ii) Next, we consider the cooperation of a collection of motors rigidly attached to a backbone. This system possesses dynamical phase transition allowing spontaneous directed motion even if the system is spatially symmetric. (iii) Finally, we report on an experimental investigation exploring the horizontal transport of granular particles in a vertically vibrated system whose base has a sawtooth-shaped profile. The resulting material flow exhibits complex collective behavior, both as a function of the number of layers of particles and the driving frequency; in particular, under certain conditions, increasing the layer thickness leads to a reversal of the current, while the onset of transport as a function of frequency occurs gradually in a manner reminiscent of a phase transition. (c) 1998 American Institute of Physics.

The kinesin walk: a dynamic model with elastically coupled heads.

Recently individual two-headed kinesin molecules have been studied in in vitro motility assays revealing a number of their peculiar transport properties. In this paper we propose a simple and robust model for the kinesin stepping process with elastically coupled Brownian heads that show all of these properties. The analytic and numerical treatment of our model results in a very good fit to the experimental data and practically has no free parameters. Changing the values of the parameters in the restricted range allowed by the related experimental estimates has almost no effect on the shape of the curves and results mainly in a variation of the zero load velocity that can be directly fitted to the measured data. In addition, the model is consistent with the measured pathway of the kinesin ATPase.