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PubMed2005

Magnetic levitation-based Martian and Lunar gravity simulator.

Missions to Mars will subject living specimens to a range of low gravity environments. Deleterious biological effects of prolonged exposure to Martian gravity (0.38 g), Lunar gravity (0.17 g), and microgravity are expected, but the mechanisms involved and potential for remedies are unknown. We are proposing the development of a facility that provides a simulated Martian and Lunar gravity environment for experiments on biological systems in a well controlled laboratory setting. The magnetic adjustable gravity simulator will employ intense, inhomogeneous magnetic fields to exert magnetic body forces on a specimen that oppose the body force of gravity. By adjusting the magnetic field, it is possible to continuously adjust the total body force acting on a specimen. The simulator system considered consists of a superconducting solenoid with a room temperature bore sufficiently large to accommodate small whole organisms, cell cultures, and gravity sensitive bio-molecular solutions. It will have good optical access so that the organisms can be viewed in situ. This facility will be valuable for experimental observations and public demonstrations of systems in simulated reduced gravity.

Animals↗
PubMed2002

De novo design of biocatalysts.

The challenging field of de novo enzyme design is beginning to produce exciting results. The application of powerful computational methods to functional protein design has recently succeeded at engineering target activities. In addition, efforts in directed evolution continue to expand the transformations that can be accomplished by existing enzymes. The engineering of completely novel catalytic activity requires traversing inactive sequence space in a fitness landscape, a feat that is better suited to computational design. Optimizing activity, which can include subtle alterations in backbone conformation and protein motion, is better suited to directed evolution, which is highly effective at scaling fitness landscapes towards maxima. Improved rational design efforts coupled with directed evolution should dramatically improve the scope of de novo enzyme design.

Antibodies, Catalytic↗
PubMed2005

Impact seeding and reseeding in the inner solar system.

Assuming that asteroidal and cometary impacts onto Earth can liberate material containing viable microorganisms, we studied the subsequent distribution of the escaping impact ejecta throughout the inner Solar System on time scales of 30,000 years. Our calculations of the delivery rates of this terrestrial material to Mars and Venus, as well as back to Earth, indicate that transport to great heliocentric distances may occur in just a few years and that the departure speed is significant. This material would have been efficiently and quickly dispersed throughout the Solar System. Our study considers the fate of all the ejected mass (not just the slowly moving material), and tabulates impact rates onto Venus and Mars in addition to Earth itself. Expressed as a fraction of the ejected particles, roughly 0.1% and 0.001% of the ejecta particles would have reached Venus and Mars, respectively, in 30,000 years, making the biological seeding of those planets viable if the target planet supported a receptive environment at the time. In terms of possibly safeguarding terrestrial life by allowing its survival in space while our planet cools after a major killing thermal pulse, we show via our 30,000- year integrations that efficient return to Earth continues for this duration. Our calculations indicate that roughly 1% of the launched mass returns to Earth after a major impact regardless of the impactor speed; although a larger mass is ejected following impacts at higher speeds, a smaller fraction of these ejecta is returned. Early bacterial life on Earth could have been safeguarded from any purported impact-induced extinction by temporary refuge in space.

Earth, Planet↗
PubMed2005

Learning invariant object recognition in the visual system with continuous transformations.

The cerebral cortex utilizes spatiotemporal continuity in the world to help build invariant representations. In vision, these might be representations of objects. The temporal continuity typical of objects has been used in an associative learning rule with a short-term memory trace to help build invariant object representations. In this paper, we show that spatial continuity can also provide a basis for helping a system to self-organize invariant representations. We introduce a new learning paradigm "continuous transformation learning" which operates by mapping spatially similar input patterns to the same postsynaptic neurons in a competitive learning system. As the inputs move through the space of possible continuous transforms (e.g. translation, rotation, etc.), the active synapses are modified onto the set of postsynaptic neurons. Because other transforms of the same stimulus overlap with previously learned exemplars, a common set of postsynaptic neurons is activated by the new transforms, and learning of the new active inputs onto the same postsynaptic neurons is facilitated. We demonstrate that a hierarchical model of cortical processing in the ventral visual system can be trained with continuous transform learning, and highlight differences in the learning of invariant representations to those achieved by trace learning.

Computer Simulation↗
PubMed1998

Simulating energy flow in biomolecules: application to tuna cytochrome c.

By constructing a continuity equation of energy flow, one can utilize results from a molecular dynamics simulation to calculate the energy flux or flow in different parts of a biomolecule. Such calculations can yield useful insights into the pathways of energy flow in biomolecules. The method was first tested on a small system of a cluster of 13 argon atoms and then applied to the study of the pathways of energy flow after a tuna ferrocytochrome c molecule was oxidized. Initially, energy propagated faster along the direction perpendicular to the heme plane. This was due to an efficient through-bond mechanism, because the heme iron in cytochrome c was covalently bonded to a cysteine and a histidine. For the oxidation of cytochrome c, electrostatic interactions also facilitated a long-range through-space mechanism of energy flow. As a result, polar or charged groups that were further away from the oxidation site could receive energy earlier than nonpolar groups closer to the site. Another bridging mechanism facilitating efficient long-range responses to cytochrome c oxidation involved the coupling of far-off atoms with atoms that were nearer to, and interacted directly with, the oxidation site. The different characteristics of these energy transfer mechanisms defied a simple correlation between the time that the excess energy of the oxidation site first dissipated to an atom and the distance of the atom from the oxidation site. For tuna cytochrome c, all of the atoms of the protein had sensed the effects of the oxidation within approximately 40 fs. For the length scale of energy transfer considered in this study, the speed of the energy propagation in the protein was on the order of 10(5) m/s.

Animals↗
PubMed2003

Arterial pulsation-driven cerebrospinal fluid flow in the perivascular space: a computational model.

This study was conducted to determine whether local arterial pulsations are sufficient to cause cerebrospinal fluid (CSF) flow along perivascular spaces (PVS) within the spinal cord. A theoretical model of the perivascular space surrounding a "typical" small artery was analysed using computational fluid dynamics. Systolic pulsations were modelled as travelling waves on the arterial wall. The effects of wave geometry and variable pressure conditions on fluid flow were investigated. Arterial pulsations induce fluid movement in the PVS in the direction of arterial wave travel. Perivascular flow continues even in the presence of adverse pressure gradients of a few kilopascals. Flow rates are greater with increasing pulse wave velocities and arterial deformation, as both an absolute amplitude and as a proportion of the PVS. The model suggests that arterial pulsations are sufficient to cause fluid flow in the perivascular space even against modest adverse pressure gradients. Local increases in flow in this perivascular pumping mechanism or reduction in outflow may be important in the etiology of syringomyelia.

Arteries↗
PubMed2004

Prediction of a global climate change on Jupiter.

Jupiter's atmosphere, as observed in the 1979 Voyager space craft images, is characterized by 12 zonal jet streams and about 80 vortices, the largest of which are the Great Red Spot and three White Ovals that had formed in the 1930s. The Great Red Spot has been observed continuously since 1665 and, given the dynamical similarities between the Great Red Spot and the White Ovals, the disappearance of two White Ovals in 1997-2000 was unexpected. Their longevity and sudden demise has been explained however, by the trapping of anticyclonic vortices in the troughs of Rossby waves, forcing them to merge. Here I propose that the disappearance of the White Ovals was not an isolated event, but part of a recurring climate cycle which will cause most of Jupiter's vortices to disappear within the next decade. In my numerical simulations, the loss of the vortices results in a global temperature change of about 10 K, which destabilizes the atmosphere and thereby leads to the formation of new vortices. After formation, the large vortices are eroded by turbulence over a time of approximately 60 years--consistent with observations of the White Ovals-until they disappear and the cycle begins again.

Journal Article↗
PubMed2000

Anomalous burning rates of flamelets induced by self-similar multiple scale (fractal and spiral) initial fields

In contrast to the classical problem of a single idealized flamelet (which is described by a nonlinear reaction-diffusion equation of motion) which propagates at a constant burning rate, self-similar multiple scale fields, whether fractal or nonfractal, induce anomalous rates of burning determined by the space-filling properties of the initial field. We compare the regimes induced by (line-cuts through) three specific geometries with distinct space-filling characteristics: (1) an algebraic spiral which has capacity (box-counting dimension) D(k)>0, and fractal dimension H=0; (2) an exponential spiral which has D(k)=0 and H=0, and geometric ratio R>1; (3) a fractal Cantor dust which has D(k)=H>0. The (nondimensional) burning rate U(B) induced by all three geometries takes the general form U(B) approximately F(tau(-zeta)), where F is a function whose form depends on the specific geometry, zeta is an exponent that contains the space-filling characteristic of the geometry, and tau is a nondimensional time. (1) For the algebraic spiral, F(x)=1(x), and zeta=D(k); F is continuous. (2) For the exponential spiral, F(x)=ln(x), and zeta=1/(R-1); F is continuous. (3) For the fractal Cantor dust, F(u)(x)=1(x), and zeta=H (for the envelope); F itself is a step-like discontinuous function. Thus, as D(k)-->0, or as H-->0, or as R-->infinity, then zeta-->0 and U(B)-->const; and as D(k)-->1, or as H-->1, (space filling) then zeta-->1; and as R-->1 (space filling) then zeta-->infinity. Two numerical methods, a fundamental (Eulerian) solution to the equation of motion and a Lagrangian model for flamelet propagation, confirm these theoretical predictions. The Lagrangian model is based on the idealized flamelet as a "point" with finite flame thickness Delta(L), (which is determined by the two-flamelet collision process), propagating with a given flame speed U(L). The Lagrangian model allows simulations in parameter ranges not easily accessible by the fundamental method (such as the case for the fractal Cantor dust). Interestingly, the linear regime of scalar diffusion in an algebraic spiral field displays the same dependence on D(k) as in the present reaction-diffusion case. The nonlinear regime of advection-diffusion (Burger turbulence) shows a different dependence on D(k).

Journal Article↗
PubMed2005

Computational analysis of tumor angiogenesis patterns using a two-dimensional model.

Tumor angiogenesis was simulated using a two-dimensional computational model. The equation that governed angiogenesis comprised a tumor angiogenesis factor (TAF) conservation equation in time and space, which was solved numerically using the Galerkin finite element method. The time derivative in the equation was approximated by a forward Euler scheme. A stochastic process model was used to simulate vessel formation and vessel elongation towards a paracrine site, i.e., tumor-secreted basic fibroblast growth factor (bFGF). In this study, we assumed a two-dimensional model that represented a thin (1.0 mm) slice of the tumor. The growth of the tumor over time was modeled according to the dynamic value of bFGF secreted within the tumor. The data used for the model were based on a previously reported model of a brain tumor in which four distinct stages (multicellular spherical, first detectable lesion, diagnosis, and death of the virtual patient) were modeled. In our study, computation was not continued beyond the 'diagnosis' time point to avoid the computational complexity of analyzing numerous vascular branches. The numerical solutions revealed that no bFGF remained within the region in which vessels developed, owing to the uptake of bFGF by endothelial cells. Consequently, a sharp declining gradient of bFGF existed near the surface of the tumor. The vascular architecture developed numerous branches close to the tumor surface (the brush-border effect). Asymmetrical tumor growth was associated with a greater degree of branching at the tumor surface.

Computer Simulation↗
PubMed2001

Entropy generation method to quantify thermal comfort.

The present paper presents a thermodynamic approach to assess the quality of human-thermal environment interaction and quantify thermal comfort. The approach involves development of entropy generation term by applying second law of thermodynamics to the combined human-environment system. The entropy generation term combines both human thermal physiological responses and thermal environmental variables to provide an objective measure of thermal comfort. The original concepts and definitions form the basis for establishing the mathematical relationship between thermal comfort and entropy generation term. As a result of logic and deterministic approach, an Objective Thermal Comfort Index (OTCI) is defined and established as a function of entropy generation. In order to verify the entropy-based thermal comfort model, human thermal physiological responses due to changes in ambient conditions are simulated using a well established and validated human thermal model developed at the Institute of Environmental Research of Kansas State University (KSU). The finite element based KSU human thermal computer model is being utilized as a "Computational Environmental Chamber" to conduct series of simulations to examine the human thermal responses to different environmental conditions. The output from the simulation, which include human thermal responses and input data consisting of environmental conditions are fed into the thermal comfort model. Continuous monitoring of thermal comfort in comfortable and extreme environmental conditions is demonstrated. The Objective Thermal Comfort values obtained from the entropy-based model are validated against regression based Predicted Mean Vote (PMV) values. Using the corresponding air temperatures and vapor pressures that were used in the computer simulation in the regression equation generates the PMV values. The preliminary results indicate that the OTCI and PMV values correlate well under ideal conditions. However, an experimental study is needed in the future to fully establish the validity of the OTCI formula and the model. One of the practical applications of this index is that could it be integrated in thermal control systems to develop human-centered environmental control systems for potential use in aircraft, mass transit vehicles, intelligent building systems, and space vehicles.

Algorithms↗
PubMed2026

FIERCE: reconstructing dynamic trajectories from the differentiation potency of single cells.

MOTIVATION: Since the introduction of single-cell RNA sequencing (scRNA-seq), numerous computational approaches have been developed to reconstruct dynamic cellular processes from static transcriptional profiles. These methods order cells along continuous trajectories by assessing their similarity in the gene-expression space. However, they rely on several assumptions, such as prior knowledge of the structure and directionality of the expected genealogy. These assumptions can limit their application to complex cellular systems with poorly understood developmental paths. RESULTS: To address this challenge, we introduce FIERCE (Framework for InfERence of the veloCity of Entropy), a novel computational pipeline designed to predict the changes in the differentiation potency of single cells during dynamic processes. Through a fully unsupervised approach, FIERCE enables the inference of cell lineages directly on the differentiation landscape of the biological system, thus eliminating the need for prior specification of developmental parameters. We demonstrate the efficacy of FIERCE by reconstructing three well-known mouse differentiation systems and by quantifying its accuracy on simulated data. AVAILABILITY AND IMPLEMENTATION: The FIERCE R package is available on GitHub at https://github.com/bicciatolab/FIERCE.

Cell Differentiation↗
PubMed2004

Colour constancy in context: roles for local adaptation and levels of reference.

By determining the locations of boundaries between colour categories, we measured changes in the colour appearance of test-reflectances as a function of the simulated illumination. Test-reflectances were displayed against a variegated background of reflectance samples. Under prolonged adaptation to each illuminant, observers demonstrated a high degree of appearance-based colour constancy. By using backgrounds that consisted of chromatically biased sets of reflectances, we tested whether this stability depends on estimates of the illuminant's cone-coordinates based on simple scene statistics. The chromatic bias of the background had only a small effect on the classification of test materials. To compare the roles of spatially local and spatially extended estimation processes, we then (unknown to the observer) simulated different illuminants on the test and on the background. Observers continued to demonstrate reasonable colour constancy. To examine the relative roles of automatic adaptation and perceptual strategies, we reduced the duration of exposure to the test compared to exposure to the background (under the conflicting illuminant). The results suggest that mechanisms that preserve information across successive test-presentations (e.g. spatially local adaptation with a time course of a few seconds, and perceptual adjustments to levels of reference) are key determinants of the stability of colour appearance.

Adaptation, Ocular↗
PubMed2006

Quasi Monte Carlo-based isotropic distribution of gradient directions for improved reconstruction quality of 3D EPR imaging.

In continuous wave (CW) electron paramagnetic resonance imaging (EPRI), high quality of reconstructed image along with fast and reliable data acquisition is highly desirable for many biological applications. An accurate representation of uniform distribution of projection data is necessary to ensure high reconstruction quality. The current techniques for data acquisition suffer from nonuniformities or local anisotropies in the distribution of projection data and present a poor approximation of a true uniform and isotropic distribution. In this work, we have implemented a technique based on Quasi-Monte Carlo method to acquire projections with more uniform and isotropic distribution of data over a 3D acquisition space. The proposed technique exhibits improvements in the reconstruction quality in terms of both mean-square-error and visual judgment. The effectiveness of the suggested technique is demonstrated using computer simulations and 3D EPRI experiments. The technique is robust and exhibits consistent performance for different object configurations and orientations.

Algorithms↗
PubMed2004

Effects of relief space and escape holes on pressure characteristics of maxillary edentulous impressions.

STATEMENT OF PROBLEM: The selective pressure technique has been recommended for making impressions of maxillary edentulous residual ridges. Although various methods for making impressions have been reported, a definitive procedure has not been clearly elucidated. PURPOSE: This in vitro study evaluated changes in impression pressure produced by different types of relief space and escape holes in the impression tray for making an impression of a simulated maxillary edentulous arch. MATERIAL AND METHODS: Silicone impression material (Exadenture) and a maxillary edentulous acrylic cast were used. A miniature pressure sensor was embedded at the mid-palatal suture (point-P) and at the left first molar area on the edentulous ridge (point-R). Three types of tray relief were used: no spacer (NS), a 0.36-mm-thick sheet of wax (SS), or a 1.40-mm-thick base plate wax (BS). Four types of escape holes were made: no hole (NH), or escape holes of 0.5, 1.0, or 2.0 mm in diameter (05H, 10H, and 20H, respectively) in the area opposing point-P. Twelve trays were formed using these relief space and escape hole combinations. The cast and tray were attached to a rheometer for applying a continuous isotonic force of 5.0 kgf and compressive speed of 120 mm/min. Impressions were made and measurement of pressure (kPa) began immediately prior to compression and continued until the materials had polymerized for 2 minutes, with a sampling time of 5 Hz. Measurements were performed 5 times for each tray. The data were analyzed using 3-way analysis of variance and the Bonferroni test (alpha=.05). RESULTS: At initial pressure, the data obtained at point-P showed significantly higher values for NSNH, NS05H, SSNH, and SS05H (range: 22.29 +/- 1.58 kPa to 29.96 +/- 1.41 kPa) than those at point-R (range: 18.61 +/- 1.12 kPa to 22.71 +/- 2.11 kPa). At end pressure, the data obtained from NSNH at point P showed a significantly higher value (25.36 +/- 1.69 kPa) than that of point-R (15.36 +/- 0.99 kPa) (P<.001), whereas data from NS10H and NS20H at point-P showed a significantly lower value (6.32 +/- 0.84 kPa and 4.50 +/- 0.42 kPa) than at point-R (15.50 +/- 0.49 kPa and 14.98 +/- 0.88 kPa) (P<.001). The data obtained from SS05H, SS10H, and NS20H at point-P showed significantly lower values (range: 3.72 +/- 0.44 kPa to 9.10 +/- 0.26 kPa) than those at point-R (range: 13.40 +/- 1.31 kPa to 14.40 +/- 0.98 kPa). Moreover, the data obtained from BSNH, BS05H, BS10H, and BS20H at point-P showed significantly lower values (range: 3.24 +/- 1.96 kPa to 10.20 +/- 1.84 kPa) than those of point-R (range: 11.69 +/- 1.01 kPa to 14.04 +/- 2.08 kPa). CONCLUSION: For making impressions of an edentulous maxilla, the data suggest that a tray with an escape hole 1.0 mm or larger or a spacer thickness of base plate wax (1.40 mm) be used.

Acrylic Resins↗
PubMed1990

Order-disorder phenomena in myelinated nerve sheaths. I. A physical model and its parametrization: exact and approximate determination of the parameters.

An algorithm is developed for the analysis of the X-ray scattering spectra of lamellar systems, by reference to a precise physical model. The model consists of identical planar lamellae (the motif), all parallel and stacked in a one-dimensional crystal with four types of defect: stacking disorder, finite size of the crystallites, and presence of diffuse and blank scattering. In addition, the spectra are distorted by collimation aberrations. In order to evaluate the effects of these distortions, the following assumptions are made: (1) beyond some point Slimit the intensity curve can be expressed as a function of a (small) number of parameters; (2) the blank scattering, restricted to very small angles, can be identified and eliminated; and (3) the diffuse scattering is entirely defined by the values of idiff(h/D) at the lattice Sh = h/D (h is a positive integer less than or equal to DSlimit). These assumptions lead to an expression of the whole of the intensity curve as a function of a finite number of parameters: the average D and the variance sigma 2D of the repeat distance, the average number [N] of lamellae per crystallite, the set [idiff(h/D)] and the set [imotif(k/2D)] (where k is a positive integer), which defines the structure of the motif. An algorithm is proposed to determine the value of the various parameters. The derivation of the algorithm involves several operations: construction in real space of periodic functions whose motifs are step-sections of the autocorrelation function; expression in reciprocal space, and in terms of the experimental scattering curves, of the Fourier transform of those periodic functions; analysis of the properties of the two functions. The algorithm is tested using a variety of simulated scattering curves whose parameters [imotif(k/2D)], [idiff(2/D)], D, sigma D, [N] (and collimation distortions) are within the range commonly encountered in experimental conditions. The results show that the values of the parameters retrieved by the algorithms are very close to those used in the simulation. The calculations are fast and easy to implement on a computer. The main virtues of the algorithm are (1) to determine the values of all the parameters at once, eliminating most of the intermediate (and questionable) manipulations (separation of signal from noise, discrimination of overlapping reflections, integration of the intensities) and (2) to yield the continuous intensity curve of a single motif.

Algorithms↗
PubMed2004

Conformational sampling and dynamics of membrane proteins from 10-nanosecond computer simulations.

In the current report, we provide a quantitative analysis of the convergence of the sampling of conformational space accomplished in molecular dynamics simulations of membrane proteins of duration in the order of 10 nanoseconds. A set of proteins of diverse size and topology is considered, ranging from helical pores such as gramicidin and small beta-barrels such as OmpT, to larger and more complex structures such as rhodopsin and FepA. Principal component analysis of the C(alpha)-atom trajectories was employed to assess the convergence of the conformational sampling in both the transmembrane domains and the whole proteins, while the time-dependence of the average structure was analyzed to obtain single-domain information. The membrane-embedded regions, particularly those of small or structurally simple proteins, were found to achieve reasonable convergence. By contrast, extra-membranous domains lacking secondary structure are often markedly under-sampled, exhibiting a continuous structural drift. This drift results in a significant imprecision in the calculated B-factors, which detracts from any quantitative comparison to experimental data. In view of such limitations, we suggest that similar analyses may be valuable in simulation studies of membrane protein dynamics, in order to attach a level of confidence to any biologically relevant observations.

Computer Simulation↗
PubMed1996

Self-organizing multi-resolution grid for motion planning and control.

A fully self-organizing neural network approach to low-dimensional control problems is described. We consider the problem of learning to control an object and solving the path planning problem at the same time. Control is based on the path planning model that follows the gradient of the stationary solution of a diffusion process working in the state space. Previous works are extended by introducing a self-organizing multigrid-like discretizing structure to represent the external world. Diffusion is simulated within a recurrent neural network built on this multigrid system. The novelty of the approach is that the diffusion on the multigrid is fast. Moreover, the diffusion process on the multigrid fits well the requirements of the path planning: it accelerates the diffusion in large free space regions while still keeps the resolution in small bottleneck-like labyrinths along the path. Control is achieved in the usual way: associative learning identifies the inverse dynamics of the system in a direct fashion. To this end there are introduced interneurons between neighboring discretizing units that detect the strength of the steady-state diffusion and forward control commands to the control neurons via modifiable connections. This architecture forms the Multigrid Position-and-Direction-to-Action (MPDA) map. The architecture integrates reactive path planning and continuous motion control. It is also shown that the scheme leads to population coding for the actual command vector.

Algorithms↗
PubMed2006

Trainable fusion rules. I. Large sample size case.

A wide selection of standard statistical pattern classification algorithms can be applied as trainable fusion rules while designing neural network ensembles. A focus of the present two-part paper is finite sample effects: the complexity of base classifiers and fusion rules; the type of outputs provided by experts to the fusion rule; non-linearity of the fusion rule; degradation of experts and the fusion rule due to the lack of information in the design set; the adaptation of base classifiers to training set size, etc. In the first part of this paper, we consider arguments for utilizing continuous outputs of base classifiers versus categorical outputs and conclude: if one succeeds in having a small number of expert networks working perfectly in different parts of the input feature space, then crisp outputs may be preferable over continuous outputs. Afterwards, we oppose fixed fusion rules versus trainable ones and demonstrate situations where weighted average fusion can outperform simple average fusion. We present a review of statistical classification rules, paying special attention to these linear and non-linear rules, which are employed rarely but, according to our opinion, could be useful in neural network ensembles. We consider ideal and sample-based oracle decision rules and illustrate characteristic features of diverse fusion rules by considering an artificial two-dimensional (2D) example where the base classifiers perform well in different regions of input feature space.

Animals↗