Mathematical modelling and numerical simulation of the morphological development of neurons

Background

The morphological development of neurons is a very complex process involving both genetic and environmental components. Mathematical modelling and numerical simulation are valuable tools in helping us unravel particular aspects of how individual neurons grow their characteristic morphologies and eventually form appropriate networks with each other.

Methods

A variety of mathematical models that consider (1) neurite initiation (2) neurite elongation (3) axon pathfinding, and (4) neurite branching and dendritic shape formation are reviewed. The different mathematical techniques employed are also described.

Results

Some comparison of modelling results with experimental data is made. A critique of different modelling techniques is given, leading to a proposal for a unified modelling environment for models of neuronal development.

Conclusion

A unified mathematical and numerical simulation framework should lead to an expansion of work on models of neuronal development, as has occurred with compartmental models of neuronal electrical activity.

     

Thermodynamic non-additivity in disordered systems with extended phase space

Non-additivity effects in coupled dynamic-stochastic systems are investigated. It is shown that there is a mapping of the replica approach to disordered systems with finite replica indexn on Tsallis non-extensive statistics, if the average thermodynamic entropy of the dynamic subsystem differs from the information entropy for the probability distribution in the stochastic subsystem. The entropic indexq is determined by the entropy difference ΔS. In the case of incomplete information, the entropic indexq=1−n is shown to be related to the degree of lost information.     

Turbulent flame visualization using direct numerical simulation

Combustion phenomena are of high scientific and technological interest, in particular for energy generation and transportation systems. Direct Numerical Simulations (DNS) have become an essential and well established research tool to investigate the structure of turbulent flames, since they do not rely on any approximate turbulence models. In this work two complementary DNS codes are employed to investigate different types of fuels and flame configurations. The code is π³ is a 3-dimensional DNS code using a low-Mach number approximation. Chemistry is described through a tabulation, using two coordinates to enter a database constructed for example with 29 species and 141 reactions for methane combustion. It is used here to investigate the growth of a turbulent premixed flame in a methane-air mixture (Case 1). The second code,Sider is an explicit three-dimensional DNS code solving the fully compressible reactive Navier-Stokes equations, where the chemical processes are computed using a complete reaction scheme, taking into account accurate diffusion properties. It is used here to compute a hydrogen/air turbulent diffusion flame (Case 2), considering 9 chemical species and 38 chemical reactions.     

Sensitization of spinal cord nociceptive neurons with a conjugate of substance P and cholera toxin

Background  

Several investigators have coupled toxins to neuropeptides for the purpose of lesioning specific neurons in the central nervous system. By producing deficits in function these toxin conjugates have yielded valuable information about the role of these cells. In an effort to specifically stimulate cells rather than kill them we have conjugated the neuropeptide substance P to the catalytic subunit of cholera toxin (SP-CTA). This conjugate should be taken up selectively by neurokinin receptor expressing neurons resulting in enhanced adenylate cyclase activity and neuronal firing.     

A 100 kHz Narrow-Pulse-Width Mid-Infrared Optical Parametric Oscillator Based on PPMgLN Crystal

We report a narrow pulse width optical parametric oscillator based on periodically poled MgO:LiNbO₃ (PPMgLN) with a high repetition rate under quasi-phase matched conditions. When the maximum pumping power of the 1,064-nm laser was 14.57 W, the acousto-optical (A-O) Q-switch repetition rate was 100 kHz, and the PPMgLN crystal grating period was 29.5 μm. A 1,474-nm signal light output power of 4.21 W and a 3,828 nm idler light output power of 1.547 W were obtained, corresponding to a pulse width of 9.52 ns and 9.65 ns, respectively. The overall optical–optical conversion efficiency was 39.5%. Additionally, by changing the temperature from 25°C to 150°C, a tunable signal wavelength of 1,474–1,499 nm and idler wavelength at 3,676–3,828 nm of the output laser were achieved.     

Analysis of Asymmetric Long-Range Surface-Plasmon Waveguide with High-Confinement Mode

We model and study the asymmetric long-range surface-plasmon waveguides using the finite-element method. We introduce two types of asymmetric structures and discuss their modal properties compared to traditional long-range surface-plasmon waveguides. Although the propagation distance is decreased, the energy-confinement capability is improved for asymmetric long-range waveguiding structures when the geometrical parameters are properly selected. Our simulation result offers guidance for tuning properties of plasmonic waveguides and providing ways for enhancing electromagnetic energy confinement in long-range surface-plasmon waveguides.     

A Novel Method for the Detection of Trace Gases Based on Photo-Acoustic Spectroscopy

We study quartz tuning fork (QTF) characteristics using a 532 nm semiconductor laser with a power of 39 mW and calculate QTF vibrations caused by thermal noise and disturbance of the air using the equipartition theorem; the vibration value is about 1.152 Pm. The signal-to-noise ratio and QTF resonance amplitude acquired experimentally are 104.56 and 214.75 Pm, respectively. In addition, we develop a new photo-acoustic spectroscopic system for detection of trace acetylene using a CW diode laser source with distributed feedback operating near 1,532 nm, measure the absorption spectrum of acetylene employing this system, and show that the method elaborated is more sensitive than photoelectric detectors that provides new directions for research in photo-acoustic spectroscopy.     

Modeling the deformation behavior of nanocrystalline alloy with hierarchical microstructures

A mechanism-based plasticity model based on dislocation theory is developed to describe the mechanical behavior of the hierarchical nanocrystalline alloys. The stress–strain relationship is derived by invoking the impeding effect of the intra-granular solute clusters and the inter-granular nanostructures on the dislocation movements along the sliding path. We found that the interaction between dislocations and the hierarchical microstructures contributes to the strain hardening property and greatly influence the ductility of nanocrystalline metals. The analysis indicates that the proposed model can successfully describe the enhanced strength of the nanocrystalline hierarchical alloy. Moreover, the strain hardening rate is sensitive to the volume fraction of the hierarchical microstructures. The present model provides a new perspective to design the microstructures for optimizing the mechanical properties in nanostructural metals.     

Synthesis and characterization of nanostructured iron compounds prepared from the decomposition of iron pentacarbonyl dispersed into carbon materials with varying porosities

This work describes the production and characterization of carbon-iron nanocomposites obtained from the decomposition of iron pentacarbonyl (Fe(CO)₅) mixed with different carbon materials: a high surface area activated carbon (AC), powdered graphite (G), milled graphite (MG), and carbon black (CB). The nanocomposites were prepared either under argon or in ambient atmosphere, with a fixed ratio of Fe(CO)₅ (4.0 mL) to carbon precursor (2.0 g). The images of scanning electron microscopy and the analysis of textural properties indicated the presence of nanostructured Fe compounds homogeneously dispersed into the different classes of pores of the carbon matrices. The elemental Fe content was always larger for samples prepared in ambient atmosphere, reaching values in the range of 20–32 wt%. On the other hand, samples prepared under argon showed reduced Fe content, with values in the range 5–10 wt% for samples prepared from precursors with low surface area (G, MG, and CB) and a much higher value (~19 wt%) for samples prepared from the precursor of high surface area (AC). Mössbauer spectroscopy and X-ray diffractometry showed that the nanoparticles were mostly composed of iron oxides in the case of the samples prepared in oxygen-rich ambient atmosphere and also for the AC-derived nanocomposite prepared under argon, which is consistent with the large oxygen content of this precursor. For the other precursors, with reduced or no oxygen content, metallic iron and iron carbides were found to be the dominant phases in samples prepared under oxygen-free atmosphere. The samples prepared in ambient atmosphere and the AC-derived sample prepared under argon exhibited superparamagnetic behavior at room temperature, as revealed by temperature-dependent magnetization curves and Mössbauer spectroscopy.     

Automated determination of size and morphology information from soot transmission electron microscope (TEM)-generated images

The thermophoretic sampling of particulates from hot media, coupled with transmission electron microscope (TEM) imaging, is a combined approach that is widely used to derive morphological information. The identification and the measurement of the particulates, however, can be complex when the TEM images are of low contrast, noisy, and have non-uniform background signal level. The image processing method can also be challenging and time consuming, when the samples collected have large variability in shape and size, or have some degree of overlapping. In this work, a three-stage image processing sequence is presented to facilitate time-efficient automated identification and measurement of particulates from the TEM grids. The proposed processing sequence is first applied to soot samples that were thermophoretically sampled from a laminar non-premixed ethylene-air flame. The parameter values that are required to be set to facilitate the automated process are identified, and sensitivity of the results to these parameters is assessed. The same analysis process is also applied to soot samples that were acquired from an externally irradiated laminar non-premixed ethylene-air flame, which have different geometrical characteristics, to assess the morphological dependence of the proposed image processing sequence. Using the optimized parameter values, statistical assessments of the automated results reveal that the largest discrepancies that are associated with the estimated values of primary particle diameter, fractal dimension, and prefactor values of the aggregates for the tested cases, are approximately 3, 1, and 10 %, respectively, when compared with the manual measurements.