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Distribution of different fibre types in human skeletal muscles. A statistical and computational model for the study of fibre type grouping and early diagnosis of skeletal muscle fibre denervation and reinnervation.

To define fibre type grouping in terms of random and non-random arrangements of the two fibre types, type 1 (ST) and type 2 (FT), we adopted the measure of counting the number of "enclosed fibres". The statistical properties of the number of enclosed fibres, and the number and size of groups of enclosed fibres were studied in computer-simulated muscle cross-sections, using a model based upon hexagonal-shaped fibres. The effects on the results of differences in the sizes of the muscle fibres were considered. The applicability of the model, and the derived results and methods of analysis were tested on 10 samples from a cross-section of a whole human muscle. The results show that the model can be applied to various shapes and sizes of muscle samples and various sizes of muscle fibres. The number of enclosed fibres within a muscle sample is the best of the three measures of non-randomness considered. A test is also described for assessing whether or not the observed number of enclosed fibres is random at a given significance level.

Biopsy, Needle↗
PubMed2006

Mesoscale computer modeling of lipid-DNA complexes for gene therapy.

We report on a molecular simulation method, which captures the self-assembly of cationic lipid-DNA (CL-DNA) gene delivery complexes. Computational efficiency required for large length- and time-scale simulations is achieved through a coarse-grained representation of the intramolecular details and via intermolecular potentials, which effectively mimic the hydrophobic effect without an explicit solvent. The broad utility of the model is illustrated by demonstrating excellent agreement with x-ray diffraction experimental data for the dependence of the spacing between DNA chains on the concentration of CLs. At high concentrations, the large electrostatic pressure induces the formation of pores in the membranes through which the DNA molecules may escape the complex. We relate this observation to the origin of recently observed enhanced transfection efficiency of lamellar CL-DNA complexes at high charge densities.

Computer Simulation↗
PubMed2001

Entrainment by an extracellular AC stimulus in a computational model of cardiac tissue.

INTRODUCTION: Cardiac tissue can be entrained when subjected to sinusoidal stimuli, often responding with action potentials sustained for the duration of the stimulus. To investigate mechanisms responsible for both entrainment and extended action potential duration, computer simulations of a two-dimensional grid of cardiac cells subjected to sinusoidal extracellular stimulation were performed. METHODS AND RESULTS: The tissue is represented as a bidomain with unequal anisotropy ratios. Cardiac membrane dynamics are governed by a modified Beeler-Reuter model. The stimulus, delivered by a bipolar electrode, has a duration of 750 to 1,000 msec, an amplitude range of 800 to 3,200 microA/cm, and a frequency range of 10 to 60 Hz. The applied stimuli create virtual electrode polarization (VEP) throughout the sheet. The simulations demonstrate that periodic extracellular stimulation results in entrainment of the tissue. This phase-locking of the membrane potential to the stimulus is dependent on the location in the sheet and the magnitude of the stimulus. Near the electrodes, the oscillations are 1:1 or 1:2 phase-locked; at the middle of the sheet, the oscillations are 1:2 or 1:4 phase-locked and occur on the extended plateau of an action potential. The 1:2 behavior near the electrodes is due to periodic change in the voltage gradient between VEP of opposite polarity; at the middle of the sheet, it is due to spread of electrotonic current following the collision of a propagating wave with refractory tissue. CONCLUSION: The simulations suggest that formation of VEP in cardiac tissue subjected to periodic extracellular stimulation is of paramount importance to tissue entrainment and formation of an extended oscillatory action potential plateau.

Action Potentials↗
PubMed2003

Computational model of the migrating motor complex of the small intestine.

The migrating motor complex (MMC) is a cyclic motor pattern with several phases enacted over the entire length of the small intestine. This motor pattern is initiated and coordinated by the enteric nervous system and modulated by extrinsic factors. Because in vitro preparations of the MMC do not exist, it has not been possible to determine the intrinsic nerve circuits that manage this motor pattern. We have used computer simulation to explore the possibility that the controlling circuit is the network of AH/Dogiel type II (AH) neurons. The basis of the model is that recurrent connections between AH neurons cause local circuits to enter a high-firing-rate state that provides the maximal motor drive observed in phase III of the MMC. This also drives adjacent segments of the network causing slow migration. Delayed negative feedback within the circuit, provided by activity-dependent synaptic depression, forces the network to return to rest after passage of phase III. The anal direction of propagation is a result of slight anal bias observed in projections of AH neurons. The model relates properties of neurons to properties of the MMC cycle: phase III migration speed is governed by neuron excitability, MMC cycle length is governed by the rate of recovery of synaptic efficacy, and phase III duration is governed by duration of slow excitatory postsynaptic potentials in AH neurons. In addition, the model makes experimental predictions that can be tested using standard techniques.

Algorithms↗
PubMed2004

Computational modeling of di-transition-metal-substituted gamma-keggin polyoxometalate anions. Structural refinement of the protonated divacant lacunary silicodecatungstate.

The B3LYP density functional method has been validated for the di-Mn-substituted gamma-Keggin polyoxometalate (POM) anion, [(SiO4)MnIII2(OH)2W10O32]4-, and for the divacant lacunary silicodecatungastate, gamma-[(SiO4)W10O32]8-. This approach was shown to adequately describe the geometries of [(SiO4)MnIII2(OH)2W10O32]4- and gamma-[(SiO4)W10O32]8. Three different geometrical models, "full", "medium", and "small", for Mn2-gamma-Keggin have also been validated. It was shown that the medium [(SiO4)MnIII2(OH)2W6O24H8]4- model, as well as small [(SiO4)MnIII2(OH)2W4O18H10]2- model, preserves structural features of the full system, [(SiO4)MnIII2(OH)2W10O32]4-. However, the small model distorts the charge distribution at the "active site" of the system and should be used with caution. The same computational approach was employed to elucidate the structure of the di-Fe-substituted gamma-Keggin POM. The structure of the acidic (tetra-protonated form) of lacunary POM, gamma-[(SiO4)W10O32H4]4-, was shown to be gamma-[(SiO4)W10O28(OH)4]4- with four terminal hydroxo ligands, rather than gamma-[(SiO4)W10O30(H2O)2]4- with two aqua and two oxo(terminal) ligands as reported by Mizuno and co-workers (Science 2003, 300, 964). The observed and calculated asymmetry in the W-O(terminal) bond distances of gamma-[(SiO4)W10O32H4]4- is explained in terms of the existence of O1H1...O2H2 and O4H4...O3H3 hydrogen-bonding patterns in the gamma-[(SiO4)W10O28(OH)4]4- structure.

Journal Article↗
PubMed2003

He and N encapsulations in small cages: model computations for possible nanotechnology systems.

Endohedral cage compounds have been considered as possible candidate species for molecular memories. In this report, computations are carried out on four hypothetical He-containing endohedral systems, He@C14H16 (isogarudane and garudane cages) and He@C36 (D6h and D2d cages), and two hypothetical N-containing endohedral systems, N@C36 (D6h and D2d cages). Geometry optimizations are followed by vibrational analysis in some cases. The geometry optimizations can indeed produce local energy minima for the endohedral systems. While in N@C36 D6h the nitrogen atom has a central location, in N@C36 D2d it exhibits a bonding pattern. Thermodynamic and kinetic stability aspects are also discussed.

Computer Simulation↗
PubMed1997

A computational model for blood flow through highly curved arteries with asymmetric stenoses.

In this paper, we develop a three dimensional model of blood flow through curved arteries with asymmetric stenoses. Firstly, the Navier-Stokes equations representing Newtonian flow are solved using PHOENICS, a computational fluid dynamics package which utilises the Finite Volume method of solution. The severity of the stenoses considered in this study vary from about 40% to about 70%. Subsequently, the model is solved for Reynolds numbers ranging from 100 to 1200. The pressure drop results show good agreement with published results. The results also show that stenoses on a bent artery has a significant effect on blood flow characteristics.

Arteries↗
PubMed2005

The identification of apoptosis-related residues in human thymosin beta-10 by mutational analysis and computational modeling.

Thymosin beta-10 (TB10) is an actin monomer-sequestering peptide that consists of 43 amino acid residues and that tends to form alpha-helical structures. Previously, we showed that the overexpression of TB10 dramatically increases the frequency of apoptosis in human ovarian cancer cells. To identify the critical residues responsible for TB10-mediated apoptosis, we used a series of computational methods. First, a three-dimensional structure of human TB10 was constructed using the homology modeling method with the calf thymosin beta-9 NMR structure as a template. Although the sequences of both of these structures are almost identical, 200-ps molecular dynamics simulation results showed that their secondary structures differ. Analyses of molecular dynamics snapshot structures suggested that the TB10 structure is conformationally more complicated than the TB9 structure. The conserved 17LKKTET(22 motif region of TB10 was tested by Ala and Ser scanning mutagenesis using computational and biochemical methods, and 12 mutants were transfected into cancer cell lines and tested for their effects on growth arrest. Of the 12 mutants examined, only the Thr20 to Ser20 mutation showed reduced growth arrest. These results strongly suggest that Thr20 is specifically required for actin sequestration by TB10 in ovarian cancer cells. These results may provide useful information for the development of a new ovarian cancer therapy.

Actins↗
PubMed1999

Potentiation of Ca2+ influx through NMDA channels by action potentials: a computer model.

In pyramidal cells, somatic action potentials can propagate actively back into the apical dendrites and potentiate calcium influx at simultaneously activated glutamatergic synapses, presumably by relieving the voltage-dependent block of NMDA channels. We have used computer simulations to investigate the conditions under which this potentiation will be optimal. We find that a spike with a long duration and limited amplitude (peak of approximately -10 mV) will be most effective. A back-propagating action potential will achieve this form if the dendritic membrane has a low K+ channel density and a modest Na+ channel density (30-70 pS/microm2, similar to experimentally observed densities). The relative increase in calcium due to the backpropagating spike will be small, however, unless the accumulated calcium is rapidly removed.

Action Potentials↗
PubMed1995

A new computational model for protein folding based on atomic solvation.

A new model for calculating the solvation energy of proteins is developed and tested for its ability to identify the native conformation as the global energy minimum among a group of thousands of computationally generated compact non-native conformations for a series of globular proteins. In the model (called the WZS model), solvation preferences for a set of 17 chemically derived molecular fragments of the 20 amino acids are learned by a training algorithm based on maximizing the solvation energy difference between native and non-native conformations for a training set of proteins. The performance of the WZS model confirms the success of this learning approach; the WZS model misrecognizes (as more stable than native) only 7 of 8,200 non-native structures. Possible applications of this model to the prediction of protein structure from sequence are discussed.

Algorithms↗