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PubMed2005

Direct measurement of single and ensemble average particle-surface potential energy profiles.

This work involves the development of a novel technique that integrates total internal reflection and video microscopy methods to simultaneously measure single particle and ensemble average particle-surface interactions. For the 2 mum silica colloids and glass coverslip used in this study, particle size polydispersity is found to be a dominant factor in determining the distribution of single particle profiles about ensemble average profiles. In conjunction with this observation, chemical and physical nonuniformity are not evident in any of our measurements even with sensitivity to interactions on the order of kT. One advantage of using ensemble averaging in conjunction with time averaging is the ability to dramatically decrease the time required to measure average particle-wall interactions which scales inversely with interfacial particle concentration. A number of experimental issues are addressed in the development of this technique including (1) combining single particle distribution functions, (2) statistical sampling of distribution functions using both time and ensemble averaging, and (3) correcting overlapping scattering signals between adjacent particles. The capabilities of the ensemble averaging technique are also demonstrated to provide unique measurements of particle-surface interactions in metastable systems by selecting only height excursions of levitated particles when calculating potentials. Ultimately, this new technique provides several important advantages over single particle measurements, which provides a foundation for measuring interactions in increasingly complex interfacial systems.

Journal Article↗
PubMed2004

Phase separation in mixtures of Yukawa and charged Yukawa particles from Gibbs ensemble Monte Carlo simulations and the mean spherical approximation.

The phase equilibrium of mixtures of Yukawa and charged Yukawa particles is studied by means of Gibbs ensemble Monte Carlo (GEMC) simulation method and the mean spherical approximation (MSA). The strength of the Coulomb energy compared to that of the Yukawa attraction is characterized by a coupling constant. For low coupling constants a classical vapor--liquid phase separation appears with a good agreement between GEMC and the MSA. For high coupling constant, a phase separation between a salt poor and a salt rich phase occurs that resembles the phase equilibrium behavior of the solvent primitive model.

Journal Article↗
PubMed2004

Genetic networks with canalyzing Boolean rules are always stable.

We determine stability and attractor properties of random Boolean genetic network models with canalyzing rules for a variety of architectures. For all power law, exponential, and flat in-degree distributions, we find that the networks are dynamically stable. Furthermore, for architectures with few inputs per node, the dynamics of the networks is close to critical. In addition, the fraction of genes that are active decreases with the number of inputs per node. These results are based upon investigating ensembles of networks using analytical methods. Also, for different in-degree distributions, the numbers of fixed points and cycles are calculated, with results intuitively consistent with stability analysis; fewer inputs per node implies more cycles, and vice versa. There are hints that genetic networks acquire broader degree distributions with evolution, and hence our results indicate that for single cells, the dynamics should become more stable with evolution. However, such an effect is very likely compensated for by multicellular dynamics, because one expects less stability when interactions among cells are included. We verify this by simulations of a simple model for interactions among cells.

Animals↗
PubMed2003

Self-consistent determination of the transition state for protein folding: application to a fibronectin type III domain.

We present a general approach in which theory and experiments are combined in an iterative manner to provide a detailed description of the transition state ensemble (TSE) for folding. The method is illustrated by applying it to TNfn3, a fibronectin type III domain protein. In the first iteration, a coarse-grained determination of the TSE is carried out by using a limited set of experimental phi values as constraints in a molecular dynamics sampling simulation. The resulting model of the TSE is used to determine the additional residues whose phi value measurement would provide the most information for refining the TSE. Successive iterations with an increasing number of phi value measurements are carried out until no further changes in the properties of the TSE are detected or there are no additional residues whose phi values can be measured. In the study of TNfn3 three iterations were necessary to achieve self-consistency. A retrospective application of the method can be used to determine the accuracy of the TSE results and to find "key residues" for folding, i.e., those that are most important for the formation of the TSE. The approach reported here is an efficient method for finding the structures that make up the TSEs for protein folding. Its use will improve future efforts for their experimental determination and refinement.

Fibronectins↗
PubMed2004

Quantitative proteomic analysis of sokotrasterol sulfate-stimulated primary human endothelial cells.

The endothelium forms a continuous monolayer at the interface between blood and tissue and contributes significantly to the sensing and transducing of signals between blood and tissue. New blood vessel formation, or angiogenesis, is initiated by the activation of endothelial cells and is an important process required for various pathological and physiological situations. This study used cleavable isotope-coded affinity tag reagents combined with mass spectrometry to investigate the molecular basis of a recently discovered angiogenesis-promoting steroid, sokotrasterol sulfate. Changes in the relative abundances of over 1000 proteins within human endothelial cells treated with sokotrasterol sulfate and vehicle-treated cells were identified and quantitated using this technique. A method that examines the entire ensemble of quantitative measurements was developed to identify proteins that showed a statistically significant change in relative abundance resulting from treatment with sokotrasterol sulfate. A total of 93 proteins was significantly up-regulated, and 37 were down-regulated in response to sokotrasterol sulfate stimulation of endothelial cells. Among the up-regulated proteins, several were identified that are novel to endothelial cells and are likely involved in cell communication and morphogenesis. These findings are consistent with a role for sokotrasterol sulfate in endothelial sprouting.

Cations↗
PubMed1977

Echo structure in medical ultrasonic pulse-echo scanning.

The factors contributing to the structure (i.e. amplitude and shape) of echoes from major reflecting boundaries in tissues are reviewed. It is shown that the pulsed nature of a scanner's emitted sound field introduces complex variations in echo shape which are not usually taken into account. Moreover, echo structure is strongly modified by the geometry of the interface and not only by the physical composition of the adjacent materials. These effects are shown to be characteristic of the basic reflection process with pulsed fields. The influence of some receiver transfer properties on the displayed echo is also indicated. It is suggested that the analysis of sound fields scattered from small-scale internal structures (echo ensemble analysis) is a preferred method of tissue characterization.

Ultrasonics↗
PubMed2006

Neural populations can induce reliable postsynaptic currents without observable spike rate changes or precise spike timing.

Fine temporal patterns of firing in much of the brain are highly irregular. In some circuits, the precise pattern of irregularity contains information beyond that contained in mean firing rates. However, the capacity of neural circuits to use this additional information for computational purposes is not well understood. Here we employ computational methods to show that an ensemble of neurons firing at a constant mean rate can induce arbitrarily chosen temporal current patterns in postsynaptic cells. If the presynaptic neurons fire with nearly uniform interspike intervals, then current patterns are sensitive to variations in spike timing. But irregular, Poisson-like firing can drive current patterns robustly, even if spike timing varies by tens of milliseconds from trial to trial. Notably, irregular firing patterns can drive useful patterns of current even if they are so variable that several hundred repeated experimental trials would be needed to distinguish them from random firing. Together, these results describe an unrestrictive set of conditions in which postsynaptic cells might exploit virtually any information contained in spike timing. We speculate as to how this capability may underlie an extension of population coding to the temporal domain.

Algorithms↗
PubMed1989

A Bayesian methodology for scaling radiation studies from animals to man.

This paper describes a Bayesian methodology for integrating studies in experimental animals and humans to obtain a risk estimate for a radionuclide for which no data or very limited human data are available. The method is quite general and is not limited to radiation studies. In fact, it was first developed for chemical toxicants. The methodology is illustrated using studies with rats, beagles, and humans exposed to isotopes of Ra and Pu. The goal is a quantitative risk estimate for bone cancer in humans exposed to internally deposited Pu. The choice of bone cancer as an end point and of Pu as the source of exposure was made partially because of its inherent interest but also because of issues of data availability and suitability. We performed Poisson regression analyses on 13 of 15 data sets. These analyses form the basis for the unifying method of interpreting the entire ensemble of studies. Each of the studies is summarized by the estimated dose-response slope and its estimated standard error. These summary statistics are combined with other available biological and physical information about species differences, physical and metabolic characteristics of isotopes, disease mechanisms, and the like. This information enters the analysis in the form of prior assumptions about the parameters of the Bayesian model combining the studies. The posterior distribution for the bone cancer rate in man from the Bayesian analysis of the 13 studies is updated with the limited data on Pu in humans. This update gives the final probability density for the bone cancer rate in humans exposed to internally deposited Pu. This density has a median of about three cancers per 100 Gy and has a 95% probability interval from 0.8 to 11 bone cancers per 100 Gy.

Animals↗
PubMed1999

Critical behavior of the two-dimensional spin-diluted Ising model via the equilibrium ensemble approach.

The equilibrium ensemble approach to disordered systems is used to investigate the critical behavior of the two-dimensional Ising model in the presence of quenched random site dilution. The numerical transfer matrix technique in semi-infinite strips of finite width, together with phenomenological renormalization and conformal invariance, is particularly suited to putting the equilibrium ensemble approach to work. A method by which to extract with great precision the critical temperature of the model is proposed and applied. A more systematic finite-size scaling analysis than in previous numerical studies has been performed. A parallel investigation, along the lines of the two main scenarios currently under discussion, namely, the logarithmic corrections scenario (with critical exponents fixed in the Ising universality class) versus the weak universality scenario (critical exponents varying with the degree of disorder), is carried out. In interpreting our data, maximum care is constantly taken to be open to both possibilities. A critical discussion shows that an unambiguous discrimination between the two scenarios is still not possible on the basis of the available finite-size data.

Journal Article↗
PubMed2002

Higher-order correlations for fluctuations in the presence of fields.

The higher-order moments of the fluctuations for thermodynamic systems in the presence of fields are investigated in the framework of a theoretical method. The method uses a generalized statistical ensemble consistent with an adequate expression for the internal energy. The applications refer to the case of a system in a magnetoquasistatic field. In the case of linear magnetic media, one finds that, for the description of the magnetic induction fluctuations, the Gaussian approximation is satisfactory. For nonlinear media, the corresponding fluctuations are non-Gaussian, having a non-null asymmetry. Furthermore, the respective fluctuations have characteristics of leptokurtic, mesokurtic and platykurtic type, depending on the value of the magnetic field strength as compared with a scaling factor of the magnetization curve.

Journal Article↗
PubMed2003

Wetting behavior of associating binary mixtures at attractive walls: a lattice Monte Carlo study.

The lattice gas model is used to study the effects of molecular association on the wettability of surfaces with attractive walls by binary symmetric associating mixtures. The model assumes that the adsorbate particles occupy a regular cubic lattice of sites and that the interactions between adsorbate particles involve only the first nearest neighbors. The energies of interaction between the pairs of like particles are the same, while the only interaction between a pair of unlike particles is due to association. Only the formation of dimers is allowed and the energy of association is finite. The particles are subject to the surface, van der Waals-like potential, assumed to be the same for both components. The model is studied with the help of the Monte Carlo simulation method in the grand canonical ensemble. Only the ground state properties are treated analytically. It is demonstrated that, in general, molecular association hinders wetting. In particular, in the systems with nonzero wetting temperature, the increase of the association energy leads to the increase of the wetting temperature and for sufficiently high energy of association the mixture does not wet the surface at all. When the system is expected to exhibit complete wetting at the ground state, the film formed by strongly associating mixtures wets the surface only at sufficiently low temperatures, below the dewetting temperature. It is demonstrated that the dewetting temperature increases with the strength of the surface potential as well as with the increase of the association energy.

Journal Article↗
PubMed2006

Time scale for magnetic reversal and the topological nonconnectivity threshold.

Anisotropic classical Heisenberg models with all-to-all spin coupling display a topological nonconnectivity threshold (TNT) for any number N of spins. Below this threshold, the energy surface is disconnected in two components with positive and negative total magnetizations, respectively, so that magnetization cannot reverse its sign and ergodicity is broken, even at finite N. Here, we solve the model in the microcanonical ensemble, using a recently developed method based on large deviation techniques, and show that a phase transition is present at an energy higher than the TNT energy. In the energy range between the TNT energy and the phase transition, magnetization changes sign stochastically and its behavior can be fully characterized by an average magnetization reversal time. The time scale for magnetic reversal can be computed analytically, using statistical mechanics. Numerical simulations confirm this calculation and further show that the magnetic reversal time diverges with a power law at the TNT threshold, with a size-dependent exponent. This exponent can be computed in the thermodynamic limit N-->(infinity), by the knowledge of entropy as a function of magnetization, and turns out to be in reasonable agreement with finite numerical simulations. We finally generalize our results to other models: Heisenberg chains with distance-dependent coupling, small 3D clusters with nearest-neighbor interactions, metastable states. We conjecture that the power-law divergence of the magnetic reversal time scale might be a universal signature of the presence of a TNT.

Journal Article↗
PubMed2006

Use of an induced fit receptor structure in virtual screening.

Structured-based drug design has traditionally relied on a single receptor structure as a target for docking and screening studies. However, it has become increasingly clear that in many cases where protein flexibility is an issue, it is critical to accurately model ligand-induced receptor movement in order to obtain high enrichment factors. We present a novel protein-ligand docking method that accounts for both ligand and receptor flexibility and accurately predicts the conformation of protein-ligand binding complexes. This method can generate viable receptor ensembles that can be used in virtual database screens.

Databases, Protein↗
PubMed1995

Effect of amplitude normalization on surface EMG linear envelopes of masticatory muscles during gum chewing.

Various amplitude normalization procedures for surface electromyographic (EMG) signals have been utilized to reduce the inter- and intrasubject variability of data collected on gait analysis. We examined two normalization methods (normalization to mean of ensemble average: NME, and normalization to peak of ensemble average: NPE) for intersubject variability and reproducibility surface EMG profiles for the masticatory muscles during unilateral gum chewing. The EMG profiles for the anterior temporal (Ta), posterior temporal (Tp), masseter (M) and anterior belly of the digastric (Da) muscles on the chewing side from five normal subjects were made at three different sessions. Coefficients of variation and intraclass correlation coefficients were used to assess variability and reproducibility. Each normalization procedure the intersubject variability of unnormalized EMG profiles for Ta, Tp and M. The NME procedure provided lower intersubject variability for Da. The reproducibility of unnormalized profiles for Ta, Tp and M was significantly improved by both procedures (p < 0.05). NME on Da was more effective in its reproducibility (p < 0.05). We found that the phasic characteristics of muscular activity influenced the outcome of amplitude normalization.

Adult↗
PubMed2026

Disagreement-informed arbitration for gene regulatory network inference: A score-level meta-classifier and a diagnostic typology of inter-method conflict.

Gene regulatory network inference methods routinely disagree about individual edges, and practitioners resolve those conflicts by choosing one method or averaging them all. We ask whether the conflict can instead be arbitrated per edge. A gradient-boosted classifier is trained on the raw scores that ten inference methods-correlation-based, information-theoretic, sparse-regression and tree-ensemble, including GENIE3, GRNBoost2, CLR and ARACNe-assign to each candidate regulator-target pair, so that the weight given to each method varies from edge to edge. Across six single-cell perturbation screens spanning four cell types, arbitration improves on mean ensembling by +0.056 AUROC on Adamson and +0.083 on Shifrut under target-grouped cross-validation. The evaluation protocol turns out to matter more than the model. Edge-level cross-validation, standard in this literature, inflates apparent gains by 0.060 AUROC through target-gene leakage-comparable to the entire honest improvement. The effect is far larger for methods that represent genes implicitly: a supervised graph-attention link predictor trained on identical folds scores AUROC 0.930 under edge-level cross-validation, better than anything else we evaluate, and 0.533 once target genes are held out. Any method that parameterises genes is exposed, which covers most graph- and embedding-based approaches. A five-category typology of inter-method conflict localises where arbitration pays off, with the largest gains on edges where the methods disagree and the smallest where they already agree, while adding nothing as model input; we therefore report it as a diagnostic instrument rather than a modelling contribution. We also characterise what the ground truth measures: most perturbed genes in widely used screens are not transcription factors, and a mediation screen bounds how much of the perturbation response can be direct.

Ensemble methods↗
PubMed1999

Independent component analyses for quantifying neuronal ensemble interactions.

The goal of this study was to compare how multivariate statistical methods for dimension reduction account for correlations between simultaneously recorded neurons. Here, we describe applications of principal component analysis (PCA) and independent component analysis (ICA) (Cardoso J-F, Souloumiac A. IEE-Proc F 1993;140:362-70; Hyvarinen A, Oja E. Neural Comput 1997;9:1483-92; Lee TW, Girolami M, Sejnowski TJ. Neural Comp 1999;11:417-41) to neuronal ensemble data. Simulated ensembles of neurons were used to compare how well the methods above could account for correlated neuronal firing. The simulations showed that 'population vectors' defined by PCA were broadly distributed over the neuronal ensembles; thus, PCA was unable to identify independent groupings of neurons that shared common sources of input. By contrast, the ICA methods were all able to identify groupings of neurons that emerged due to correlated firing. This result suggests that correlated neuronal firing is reflected in higher-order correlations between neurons and not simply in the neurons' covariance. To assess the significance of these methods for real neuronal ensembles, we analyzed data from populations of neurons recorded in the motor cortex of rats trained to perform a reaction-time task. Scores for PCA and ICA were reconstructed on a bin-by-bin basis for single trials. These data were then used to train an artificial neural network to discriminate between single trials with either short or long reaction-times. Classifications based on scores from the ICA-based methods were significantly better than those based on PCA. For example, scores for components defined with an ICA-based method, extended ICA (Lee et al., 1999), classified more trials correctly (80.58+/-1.25%) than PCA (73.14+/-0.84%) for an ensemble of 26 neurons recorded in the motor cortex (ANOVA: P < 0.005). This result suggests that behaviorally relevant information is represented in correlated neuronal firing and can be best detected when higher-order correlations between neurons are taken into account.

Action Potentials↗
PubMed2005

Clustering ensembles: models of consensus and weak partitions.

Clustering ensembles have emerged as a powerful method for improving both the robustness as well as the stability of unsupervised classification solutions. However, finding a consensus clustering from multiple partitions is a difficult problem that can be approached from graph-based, combinatorial, or statistical perspectives. This study extends previous research on clustering ensembles in several respects. First, we introduce a unified representation for multiple clusterings and formulate the corresponding categorical clustering problem. Second, we propose a probabilistic model of consensus using a finite mixture of multinomial distributions in a space of clusterings. A combined partition is found as a solution to the corresponding maximum-likelihood problem using the EM algorithm. Third, we define a new consensus function that is related to the classical intraclass variance criterion using the generalized mutual information definition. Finally, we demonstrate the efficacy of combining partitions generated by weak clustering algorithms that use data projections and random data splits. A simple explanatory model is offered for the behavior of combinations of such weak clustering components. Combination accuracy is analyzed as a function of several parameters that control the power and resolution of component partitions as well as the number of partitions. We also analyze clustering ensembles with incomplete information and the effect of missing cluster labels on the quality of overall consensus. Experimental results demonstrate the effectiveness of the proposed methods on several real-world data sets.

Algorithms↗
PubMed1985

The influence of clothing ensembles on the lower critical temperature.

This paper describes the effect of clothing insulation on the lower critical temperature (LCT). Twelve young adult females were exposed to a temperature of 10 degrees C for 2 1/2 h. LCT was estimated at five different clothing conditions according to the intersect method. The total weights of clothing ensembles (CW) of the five conditions were 0.45, 0.52, 0.82, 1.34, and 2.56 kg, and their thermal insulating values (I) were 0.44, 0.60, 0.77, 1.21, and 2.14 clo, respectively. LCT of the five clothing ensembles were estimated to be 26.4, 25.4, 23.5, 21.5, and 17.5 degrees C, respectively. The regression equation of the logarithm of LCT on CW was calculated as logLCT = 1.4469-0.08283 CW and that on I was log LCT = 1.4613-0.10526 I, respectively. The rate of changes in LCT is suggested to be dependent on the clothing conditions as for the following equations: dLCT/dCW = -5.34 exp(-0.1907 CW) or dLCT/dI = -7.01 exp(-0.2424 I).

Adolescent↗