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At least 127 records · Page 7Linked to original sources
PubMed1999

The Macromolecular Route to Chiral Amplification.

Cooperative phenomena, described by one-dimensional statistical physical methods, are observed between the enantiomeric characteristics of monomeric materials and the polymers they produce. The effect of minute energies associated with this amplified chirality, although currently not interpretable, can be easily measured. Nonlinear relationships between enantiomeric excess or enantiomeric content and polymer properties may offer the possibility of developing chiral catalysts and chiral chromatographic materials in which the burden of large enantiomeric excess or content may be considerably alleviated. New approaches to information and sensor technology may become possible.

Journal Article↗
PubMed2002

Electrophoresis of randomly charged particles.

The technique of "rotational electrophoresis" has been developed recently to measure the charge nonuniformity on Brownian particles in a suspension. Measurements of the angular velocity in electrophoresis are interpreted with electrokinetic theory to give a standard deviation of zeta potential among N regions on a particle. A key question is how various molecular mechanisms of charging could lead to charge nonuniformity on a length scale of O (100 nm). Simple statistical physics is used to show that although Poisson charging with univalent charges cannot explain recent measurements showing significant charge nonuniformity, random charging with multivalent charges can better explain the data. In addition, the result shows that a small number of charged "visualization" molecules can be adsorbed to a particle without impacting the experimental technique of rotational electrophoresis.

Colloids↗
PubMed1996

Quantifying biological specificity: the statistical mechanics of molecular recognition.

The Random Energy Model of statistical physics is applied to the problem of the specificity of recognition between two biological (macro)molecules forming a non-covalent complex. In this model, the native mode of association is separated by an energy gap from a large body of non-native modes. Whereas the native mode is unique, the non-native modes form an energy spectrum which is approximated by a gaussian distribution. Specificity can then be estimated by writing the partition function and calculating the ratio r of non-native to native modes at thermodynamic equilibrium. We examine three situations: (i) recognition in the absence of a competitor; (ii) recognition in the presence of a competing ligand; (iii) recognition in a heterogeneous mixture. We derive the dependence of the ratio r on temperature and on the concentration of competing ligands, and we estimate the effect of a local perturbation such as can result from a point mutation. Cases (i) and (iii) are modeled by docking experiments in the computer. In case (iii), which is representative of a wide variety of biological situations, we show that increasing the heterogeneity of a mixture affects the specificity of recognition, even when the concentration of competing species is kept constant.

Binding Sites↗
PubMed1988

Analysis of cell locomotion. Contact guidance of human polymorphonuclear leukocytes.

The methods of statistical physics have been applied to the analysis of cell movement. Human polymorphonuclear leukocytes were exposed to different surfaces possessing parallel oriented physical structures (scratched glass surface, machine drilled aluminum surface, optical grid and stretched polyethylene foil) and cell migration was observed using time-lapse photography. We demonstrate that in cell migration along physical structures, referred to as contact guidance, two subgroups can be distinguished: 1) The nematic type where the cell size is large in relation to the grid distance of the undulate surface. 2) The smectic type where the cell size is small in relation to the grid distance of the substrate. Nematic contact guidance is characterized by an anisotropic random walk. In all substrates investigated the diffusion process parallel to the lines was faster than the diffusion process perpendicular to them. The angular dependent diffusion coefficient was described by an ellipse. Deviation from a circle defined an apolar order parameter, whose value was about 0.3. The amount of information which the cells collected from, the undulate surface was very low, between 0.1 and 0.2 bits. We demonstrate that cells do not recognize all the details of their surroundings and that their migration can be compared to the "groping around" of a short sighted man. The blurred environment can be described by a mean field whose strength is proportional to the apolar order parameter. It is argued that the anisotropic surface tension is the basic source for nematic contact guidance. Smectic contact guidance is characterized by an anisotropic random walk and is quantified by a density order parameter which is 0.28 in the case of the scratched glass surface of a Neubauer counting chamber. The information which the cells collect from their environment is very low (0.03 bits). The lines seen by the cell can be described by a mean field whose strength is proportional to the density oder parameter. Finally, we demonstrate that the locomotion of granulocytes is governed by an internal clock and internal programs. After migrating for a certain time (32 s) in a particular direction, a new direction of locomotion is determined by an internal program. The cell decides basically between left or right, thereby preferring a turn angle such that the cell migrates either parallel or perpendicular to the lines. The angles are nearly equally probable but the cell moves, in the case of nematic guidance, with different velocities in the + or - direction. The cell also has directional memories with characteristic times of 32 s and greater than 100 s.

Cell Movement↗
PubMed1993

Quantitative assessment of the microstructure of rat behavior: I, f(d), the extension of the scaling hypothesis.

Previous studies demonstrated that drug effects on the movement sequences of rats in unconditioned motor activity paradigms can be quantified by scaling measures that describe the average relationship between a variable of interest and an experimental parameter. However, rats engage in a wide variety of geometrically distinct movements that can be influenced differentially by drugs. In this investigation, the extended scaling approach is presented to capture quantitatively the relative contributions of geometrically distinct movement sequences to the overall path structure. The calculation of the spectrum of local spatial scaling exponents, f(d), is based on ensemble methods used in statistical physics. Results of the f(d) analysis confirm that the amount of motor activity is not correlated with the geometrical structure of movement sequences. Changes in the average spatial scaling exponent, d, correspond to shifting the entire f(d) function, and indicate overall changes in path structure. With the extended scaling approach, straight movement sequences are assessed independently from highly circumscribed movements. Thus, the f(d) function identifies drug effects on particular ranges of movement sequences as defined by the geometrical structure of movements. More generally, the f(d) function quantifies the relationship between microscopically recorded variables, in this paradigm consecutive (x,y) locations, and the macroscopic behavioral patterns that constitute the animal's response topography.

Animals↗
PubMed1997

Aspects of human biometeorology in past, present and future.

Human biometeorology is quite an old science: during the times of Hippokrates in ancient Greece the influence of weather changes on physiological processes in the human body were considered to exist. However, not until the progress in modern statistics, physics and physiology in the course of this century provided quantitative methods did human-biometeorology become an acknowledged natural science. In the first half of this century primarily the explanation of the phenomena of reactions of the body to weather changes was the general objective. In the second half of this century quantitative descriptions of thermal interchanges between the human body and the environment by means of energy balance models of the human body have gained increasing importance. The methods of modern human biometeorology increasingly are acknowledged by workers in disciplines of potential application, such as urban or regional planners or air conditioning engineers. Human biometeorology tries to assess all atmospheric influences in its entirety, including the air pollution pattern. The discipline considers itself as branch of science which is tied closely to environmental meteorology and environmental medicine.

Body Temperature Regulation↗
PubMed2000

Switching characteristics of a model for biochemical-reaction networks describing autophosphorylation versus dephosphorylation of Ca2+/calmodulin-dependent protein kinase II.

Ca2+/calmodulin-dependent protein kinase II (CaMKII) has been suggested to participate in various cellular phenomena triggered by Ca2+ signalling. In the present study, we addressed the functional role of CaMKII in molecular-signal transduction in cells by mathematical modelling of putative biochemical-reaction networks thought to represent an essential part of molecular events responsible for CaMKII-related cellular phenomena. These networks include Ca2+/calmodulin-dependent threonine-286/287 (Thr286/287) autophosphorylation of CaMKII versus dephosphorylation of the enzyme. Computer simulation of the model was performed to examine the relation between the Ca2+-signalling pattern as an input and the resulting degree of Thr286/287 autophosphorylation (m) as an output. Under the simplified condition that the Ca2+ concentration during Ca2+ signalling was set to remain constant with time, the biochemical-reaction networks were shown to function as a switch. There is a threshold for gamma, a parameter representing the probability that the Thr286/287-dephosphorylated CaMKII subunit binds with the Ca2+/calmodulin complex; if gamma is above this threshold, m increases with time to a large degree (switch-on); otherwise, it remains near zero (switch-off). Mathematically, this sharp onset of m at the threshold can be accounted for by a change in the structure of the dynamic system describing the model, from bistability to monostability; this is analogous to the first-order phase transition in statistical physics. For the oscillatory time course of [Ca2+], switching characteristics were also shown with respect to the frequency and the maximum amplitude of the oscillation. These results suggest that graded information mediated by Ca2+ signalling is digitized into all-or-non information mediated by Thr286/287 autophosphorylation of CaMKII.

Animals↗
PubMed1989

Neuronal models of cognitive functions.

Understanding the neural bases of cognition has become a scientifically tractable problem, and neurally plausible models are proposed to establish a causal link between biological structure and cognitive function. To this end, levels of organization have to be defined within the functional architecture of neuronal systems. Transitions from any one of these interacting levels to the next are viewed in an evolutionary perspective. They are assumed to involve: (1) the production of multiple transient variations and (2) the selection of some of them by higher levels via the interaction with the outside world. The time-scale of these "evolutions" is expected to differ from one level to the other. In the course of development and in the adult this internal evolution is epigenetic and does not require alteration of the structure of the genome. A selective stabilization (and elimination) of synaptic connections by spontaneous and/or evoked activity in developing neuronal networks is postulated to contribute to the shaping of the adult connectivity within an envelope of genetically encoded forms. At a higher level, models of mental representations, as states of activity of defined populations of neurons, are discussed in terms of statistical physics, and their storage is viewed as a process of selection among variable and transient pre-representations. Theoretical models illustrate that cognitive functions such as short-term memory and handling of temporal sequences may be constrained by "microscopic" physical parameters. Finally, speculations are offered about plausible neuronal models and selectionist implementations of intentions.

Animals↗
PubMedDate not supplied

Ca2+ imaging in single living cells: theoretical and practical issues.

The measurement of intracellular calcium ion concentrations [( Ca2+]i) in single living cells using quantitative fluorescence microscopy draws from a diverse set of disciplines, including cellular biology, optical physics, statistics and computer science. Over the last few years, we have devised and built a number of systems for measuring [Ca2+]i with Fura-2, and have applied them in the exploration of a wide range of biological processes controlled by Ca2+. In this report we discuss these systems and their advantages and limitations. We also describe the theoretical and practical problems associated with using Fura-2 to measure [Ca2+]i, and the solutions that we, and others, have developed to overcome them. The approaches described should provide useful guidance for others interested in imaging [Ca2+] distribution in living cells. The factors that limit current methods are discussed, and areas for future development are highlighted.

Animals↗
PubMedDate not supplied

Finding the biologically optimal alignment of multiple sequences.

OBJECTIVE: Deterministic annealing, which is derived from statistical physics, is a method for obtaining the global optimum in parameter space. During the annealing process, starting from high temperatures which are then lowered, deterministic annealing deterministically find the (global) optimum at each temperature. Thus, deterministic annealing is expected to be more computationally efficient than stochastic sampling strategies to obtain the global optimum. We propose to apply the deterministic annealing technique to the problem of efficiently finding the biologically optimal alignment of multiple sequences. METHODS AND MATERIAL: We take a strategy based on probabilistic models for aligning multiple sequences. That is, we train a probabilistic model using given training sequences and obtain their alignment by parsing, i.e. searching for the most likely parse of each sequence and gaps using the trained parameters of the model. In this scenario, we propose a new stochastic model, which is simple enough to be suited to multiple sequence alignment and, unlike existing stochastic models, say a profile hidden Markov model (HMM), allows us to use similarity scores between symbols (or a symbol and a gap). We further present a learning algorithm for our simple model by combining deterministic annealing with an expectation-maximization (EM) algorithm. We emphasize that our approach is time-efficient, even if the training is done through an annealing process. RESULTS: In our experiments, we used actual protein sequences whose three-dimensional (3D) structures are determined and which are all aligned based on their 3D structures. We compared the results obtained by our approach with those by other existing approaches. Experimental results clearly showed that our approach gave the best performance, in terms of the similarity to the structurally determined alignment, among the approaches tested. Experimental results further indicated that our approach was ten times more efficient in terms of actual computation time than a competing method.

Algorithms↗
PubMed2006

A free energy principle for the brain.

By formulating Helmholtz's ideas about perception, in terms of modern-day theories, one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts: using constructs from statistical physics, the problems of inferring the causes of sensory input and learning the causal structure of their generation can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on Empirical Bayes and hierarchical models of how sensory input is caused. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of cortical organisation and responses. In this paper, we show these perceptual processes are just one aspect of emergent behaviours of systems that conform to a free energy principle. The free energy considered here measures the difference between the probability distribution of environmental quantities that act on the system and an arbitrary distribution encoded by its configuration. The system can minimise free energy by changing its configuration to affect the way it samples the environment or change the distribution it encodes. These changes correspond to action and perception respectively and lead to an adaptive exchange with the environment that is characteristic of biological systems. This treatment assumes that the system's state and structure encode an implicit and probabilistic model of the environment. We will look at the models entailed by the brain and how minimisation of its free energy can explain its dynamics and structure.

Afferent Pathways↗
PubMed2004

SIS epidemics with household structure: the self-consistent field method.

We consider a stochastic SIS infection model for a population partitioned into m households assuming random mixing. We solve the model in the limit m --> infinity by using the self-consistent field method of statistical physics. We derive a number of explicit results, and give numerical illustrations. We then do numerical simulations of the model for finite m and without random mixing. We find in many of these cases that the self-consistent field method is a very good approximation.

Endemic Diseases↗
PubMed2003

Ising model of cardiac thin filament activation with nearest-neighbor cooperative interactions.

We have developed a model of cardiac thin filament activation using an Ising model approach from equilibrium statistical physics. This model explicitly represents nearest-neighbor interactions between 26 troponin/tropomyosin units along a one-dimensional array that represents the cardiac thin filament. With transition rates chosen to match experimental data, the results show that the resulting force-pCa (F-pCa) relations are similar to Hill functions with asymmetries, as seen in experimental data. Specifically, Hill plots showing (log(F/(1-F)) vs. log [Ca]) reveal a steeper slope below the half activation point (Ca(50)) compared with above. Parameter variation studies show interplay of parameters that affect the apparent cooperativity and asymmetry in the F-pCa relations. The model also predicts that Ca binding is uncooperative for low [Ca], becomes steeper near Ca(50), and becomes uncooperative again at higher [Ca]. The steepness near Ca(50) mirrors the steep F-pCa as a result of thermodynamic considerations. The model also predicts that the correlation between troponin/tropomyosin units along the one-dimensional array quickly decays at high and low [Ca], but near Ca(50), high correlation occurs across the whole array. This work provides a simple model that can account for the steepness and shape of F-pCa relations that other models fail to reproduce.

Actin Cytoskeleton↗
PubMed1979

A simple tension-displacement model for hemoglobin cooperativity.

Based on the Perutz view of hemoglobin cooperativity and the methodology of statistical physics, a molecular model for heme-heme interactions is proposed. The motion of the iron atom with respect to the heme plane is assumed to be the important feature of the oxygenation step, and results in an expression for hemoglobin saturation as an explicit function of the internal tension of the hemoglobin molecule. Closure of the equation is obtained with the assumption of linearity between the internal tension and the displacement of the iron atom above the heme plane. All model parameters are physically realizable and are characteristic of the hemoglobin molecule. Finally, the model is capable of discriminating between positive and negative cooperativity.

Binding Sites↗
PubMed1993

Application of the one- and two-dimensional Ising models to studies of cooperativity between ion channels.

The Ising model of statistical physics provides a framework for studying systems of protomers in which nearest neighbors interact with each other. In this article, the Ising model is applied to the study of cooperative phenomena between ligand-gated ion channels. Expressions for the mean open channel probability, rho o, and the variance, sigma 2, are derived from the grand partition function. In the one-dimensional Ising model, interactions between neighboring open channels give rise to a sigmoidal rho o versus concentration curve and a nonquadratic relationship between sigma 2 and rho o. Positive cooperativity increases the slope at the midpoint of the rho o versus concentration curve, shifts the apparent binding affinity to lower concentrations, and increases the variance for a given rho o. Negative cooperativity has the opposite effects. Strong negative cooperativity results in a bimodal sigma 2 versus rho o curve. The slope of the rho o versus concentration curve increases linearly with the number of binding sites on a protomer, but the sigma 2 versus rho o relationship is independent of the number of ligand binding sites. Thus, the sigma 2 versus rho o curve provides unambiguous information about channel interactions. In the two-dimensional Ising model, rho o and sigma 2 are calculated numerically from a series expansion of the grand partition function appropriate for weak interactions. Virtually all of the features exhibited by the one-dimensional model are qualitatively present in the two-dimensional model. These models are also applicable to voltage-gated ion channels.

Animals↗
PubMed1997

Dynamics of pore growth in membranes and membrane stability.

Pores can form and grow in biomembranes because of factors such as thermal fluctuation, transmembrane electrical potential, and cellular environment. We propose a new statistical physics model of the pore growth treated as a non-Markovian stochastic process, with a free energy barrier and memory friction from the membrane matrix treated as a quasi-two-dimensional viscoelastic and dielectric fluid continuum. On the basis of the modern theory of activated barrier crossing, an analytical expression for membrane lifetime and the phase diagram for membrane stability are obtained. The memory effect due to membrane viscoelasticity and the elasticity due to cytoskeletal network are found to induce sharp transitions to membrane stability against pore growth and compete with other factors to manifest rich dynamic transitions over the membrane lifetime.

Biophysical Phenomena↗
PubMed1995

Fractal mechanisms and heart rate dynamics. Long-range correlations and their breakdown with disease.

Under healthy conditions, the normal cardiac (sinus) interbeat interval fluctuates in a complex manner. Quantitative analysis using techniques adapted from statistical physics reveals the presence of long-range power-law correlations extending over thousands of heartbeats. This scale-invariant (fractal) behavior suggests that the regulatory system generating these fluctuations is operating far from equilibrium. In contrast, it is found that for subjects at high risk of sudden death (e.g., congestive heart failure patients), these long-range correlations break down. Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as motivating development of novel physiologic models of systems that appear to be heterodynamic rather than homeostatic.

Adult↗