998 resultados para Diffusion times


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This article describes the first steps toward comprehensive characterization of molecular transport within scaffolds for tissue engineering. The scaffolds were fabricated using a novel melt electrospinning technique capable of constructing 3D lattices of layered polymer fibers with well - defined internal microarchitectures. The general morphology and structure order was then determined using T 2 - weighted magnetic resonance imaging and X - ray microcomputed tomography. Diffusion tensor microimaging was used to measure the time - dependent diffusivity and diffusion anisotropy within the scaffolds. The measured diffusion tensors were anisotropic and consistent with the cross - hatched geometry of the scaffolds: diffusion was least restricted in the direction perpendicular to the fiber layers. The results demonstrate that the cross - hatched scaffold structure preferentially promotes molecular transport vertically through the layers ( z - axis), with more restricted diffusion in the directions of the fiber layers ( x – y plane). Diffusivity in the x – y plane was observed to be invariant to the fiber thickness. The characteristic pore size of the fiber scaffolds can be probed by sampling the diffusion tensor at multiple diffusion times. Prospective application of diffusion tensor imaging for the real - time monitoring of tissue maturation and nutrient transport pathways within tissue engineering scaffolds is discussed.

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Part of the optical clearing study in biological tissues concerns the determination of the diffusion characteristics of water and optical clearing agents in the subject tissue. Such information is sufficient to characterize the time dependence of the optical clearing mechanisms—tissue dehydration and refractive index (RI) matching. We have used a simple method based on collimated optical transmittance measurements made from muscle samples under treatment with aqueous solutions containing different concentrations of ethylene glycol (EG), to determine the diffusion time values of water and EG in skeletal muscle. By representing the estimated mean diffusion time values from each treatment as a function of agent concentration in solution, we could identify the real diffusion times for water and agent. These values allowed for the calculation of the correspondent diffusion coefficients for those fluids. With these results, we have demonstrated that the dehydration mechanism is the one that dominates optical clearing in the first minute of treatment, while the RI matching takes over the optical clearing operations after that and remains for a longer time of treatment up to about 10 min, as we could see for EG and thin tissue samples of 0.5 mm.

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Stochastic Diffusion Search is an efficient probabilistic bestfit search technique, capable of transformation invariant pattern matching. Although inherently parallel in operation it is difficult to implement efficiently in hardware as it requires full inter-agent connectivity. This paper describes a lattice implementation, which, while qualitatively retaining the properties of the original algorithm, restricts connectivity, enabling simpler implementation on parallel hardware. Diffusion times are examined for different network topologies, ranging from ordered lattices, over small-world networks to random graphs.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Although magnetic resonance spectroscopy can be used as a unique tool to study molecular diffusion, it is rarely used to measure the diffusion properties of intramyocellular and extramyocellular lipids. Lipids have very low apparent diffusion coefficients (ADCs), which make these measurements difficult and necessitate strong diffusion gradients and long diffusion times. Consequence is that these measurements have inherently low signal-to-noise ratio and are prone to artifacts. The addition of physiological triggering and individual storage and processing of the spectra is seen to be a possible approach to maximize signal intensity and achieve high reproducibility of the experiments. Thus, the optimized measurement protocol was used to investigate the diffusion properties of lipids in human skeletal muscle in vivo. At a diffusion time of about 110 ms, intramyocellular lipids show a significantly lower ADC (2.0 × 10(-6) mm(2)/s, 95% confidence interval 1.10 × 10(-6) to 2.94 × 10(-6) mm(2)/s) than extramyocellular lipids (1.58 × 10(-5) mm(2)/s, 95% confidence interval 1.41 × 10(-5) to 1.75 × 10(-5) mm(2)/s). Because the chemical properties of both lipid pools can be assumed to be similar, the difference can only be attributed to restricted or severely hindered diffusion in the intramyocellular droplets.

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The main objective of this work was to develop an application capable of determining the diffusion times and diffusion coefficients of optical clearing agents and water inside a known type of muscle. Different types of chemical agents can also be used with the method implemented, such as medications or metabolic products. Since the diffusion times can be calculated, it is possible to describe the dehydration mechanism that occurs in the muscle. The calculation of the diffusion time of an optical clearing agent allows to characterize the refractive index matching mechanism of optical clearing. By using both the diffusion times and diffusion of water and clearing agents not only the optical clearing mechanisms are characterized, but also information about optical clearing effect duration and magnitude is obtained. Such information is crucial to plan a clinical intervention in cooperation with optical clearing. The experimental method and equations implemented in the developed application are described in throughout this document, demonstrating its effectiveness. The application was developed in MATLAB code, but the method was personalized so it better fits the application needs. This process significantly improved the processing efficiency, reduced the time to obtain he results, multiple validations prevents common errors and some extra functionalities were added such as saving application progress or export information in different formats. Tests were made using glucose measurements in muscle. Some of the data, for testing purposes, was also intentionally changed in order to obtain different simulations and results from the application. The entire project was validated by comparing the calculated results with the ones found in literature, which are also described in this document.

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We report extensive observational data for five of the lowest redshift Super-Luminous Type Ic Supernovae (SL-SNe Ic) discovered to date, namely, PTF10hgi, SN2011ke, PTF11rks, SN2011kf, and SN2012il. Photometric imaging of the transients at +50 to +230 days after peak combined with host galaxy subtraction reveals a luminous tail phase for four of these SL-SNe. A high-resolution, optical, and near-infrared spectrum from xshooter provides detection of a broad He I ?10830 emission line in the spectrum (+50 days) of SN2012il, revealing that at least some SL-SNe Ic are not completely helium-free. At first sight, the tail luminosity decline rates that we measure are consistent with the radioactive decay of 56Co, and would require 1-4 M ? of 56Ni to produce the luminosity. These 56Ni masses cannot be made consistent with the short diffusion times at peak, and indeed are insufficient to power the peak luminosity. We instead favor energy deposition by newborn magnetars as the power source for these objects. A semi-analytical diffusion model with energy input from the spin-down of a magnetar reproduces the extensive light curve data well. The model predictions of ejecta velocities and temperatures which are required are in reasonable agreement with those determined from our observations. We derive magnetar energies of 0.4 <~ E(1051 erg) lsim 6.9 and ejecta masses of 2.3 <~ M ej(M ?) lsim 8.6. The sample of five SL-SNe Ic presented here, combined with SN 2010gx—the best sampled SL-SNe Ic so far—points toward an explosion driven by a magnetar as a viable explanation for all SL-SNe Ic.

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This study evaluated the effect of physical and chemical activation on the speed of penetration of hydrogen peroxide bleaching agents present in different concentrations through the enamel and dentin. One hundred and twenty bovine incisors were used, which were obtained enamel/dentin discs of the buccal surface, with 6 mm in diameter. The samples were divided into six groups: G1 - Hydrogen Peroxide Gel 20%, G2 - Hydrogen Peroxide Gel 20% with light activation, G3 - Hydrogen Peroxide Gel 20% with Manganese Gluconate; G4 - Hydrogen Peroxide Gel 35%; G5 - Hydrogen Peroxide Gel 35% with the light activation and G6 - Hydrogen Peroxide Gel 35% with Manganese Gluconate. The specimens were placed in a transparent support on which there was a substance sensitive to hydrogen peroxide immediately below and in contact with the specimen. After the procedures for applying the gel for each group, one video camera was positioned and operated to monitor the time of penetration of peroxide in each specimen. The recording ended after changing the color of the fluid revealed in all specimens and times were noted for comparison. ANOVA analysis showed that concentration and type of activation of bleaching gel significantly influenced the diffusion time of hydrogen peroxide (P 0.05). 35% hydrogen peroxide showed the lowest diffusion times compared to the groups with 20% hydrogen peroxide gel. The light activation of hydrogen peroxide decrease significantly the diffusion time compared to chemical activation. The highest diffusion time was obtained with 20% hydrogen peroxide chemically activated. The diffusion time of hydrogen peroxide was dependent on activation and concentration of hydrogen peroxide. The higher concentration of hydrogen peroxide diffused through dental tissues more quickly

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In a recent paper, Gordon, Muratov, and Shvartsman studied a partial differential equation (PDE) model describing radially symmetric diffusion and degradation in two and three dimensions. They paid particular attention to the local accumulation time (LAT), also known in the literature as the mean action time, which is a spatially dependent timescale that can be used to provide an estimate of the time required for the transient solution to effectively reach steady state. They presented exact results for three-dimensional applications and gave approximate results for the two-dimensional analogue. Here we make two generalizations of Gordon, Muratov, and Shvartsman’s work: (i) we present an exact expression for the LAT in any dimension and (ii) we present an exact expression for the variance of the distribution. The variance provides useful information regarding the spread about the mean that is not captured by the LAT. We conclude by describing further extensions of the model that were not considered by Gordon,Muratov, and Shvartsman. We have found that exact expressions for the LAT can also be derived for these important extensions...

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We recorded miniature endplate currents (mEPCs) using simultaneous voltage clamp and extracellular methods, allowing correction for time course measurement errors. We obtained a 20-80% rise time (tr) of approximately 80 micros at 22 degrees C, shorter than any previously reported values, and tr variability (SD) with an upper limit of 25-30 micros. Extracellular electrode pressure can increase tr and its variability by 2- to 3-fold. Using Monte Carlo simulations, we modeled passive acetylcholine diffusion through a vesicle fusion pore expanding radially at 25 nm x ms(-1) (rapid, from endplate omega figure appearance) or 0.275 nm x ms(-1) (slow, from mast cell exocytosis). Simulated mEPCs obtained with rapid expansion reproduced tr and the overall shape of our experimental mEPCs, and were similar to simulated mEPCs obtained with instant acetylcholine release. We conclude that passive transmitter diffusion, coupled with rapid expansion of the fusion pore, is sufficient to explain the time course of experimentally measured synaptic currents with trs of less than 100 micros.

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In 2010 Berezhkovskii and coworkers introduced the concept of local accumulation time (LAT) as a finite measure of the time required for the transient solution of a reaction diffusion equation to effectively reach steady state(Biophys J. 99, L59 (2010); Phys Rev E. 83, 051906 (2011)). Berezhkovskii’s approach is a particular application of the concept of mean action time (MAT) that was introduced previously by McNabb (IMA J Appl Math. 47, 193 (1991)). Here, we generalize these previous results by presenting a framework to calculate the MAT, as well as the higher moments, which we call the moments of action. The second moment is the variance of action time; the third moment is related to the skew of action time, and so on. We consider a general transition from some initial condition to an associated steady state for a one–dimensional linear advection–diffusion–reaction partial differential equation(PDE). Our results indicate that it is possible to solve for the moments of action exactly without requiring the transient solution of the PDE. We present specific examples that highlight potential weaknesses of previous studies that have considered the MAT alone without considering higher moments. Finally, we also provide a meaningful interpretation of the moments of action by presenting simulation results from a discrete random walk model together with some analysis of the particle lifetime distribution. This work shows that the moments of action are identical to the moments of the particle lifetime distribution for certain transitions.

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The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.

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High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

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We show that data from recent experiments carried out on the kinetics of DNA escape from alpha-hemolysin nanopores [M. Wiggin, C. Tropini, C. T. Cossa, N. N. Jetha, and A. Marziali, Biophys. J. 95, 5317 (2008)] may be rationalized by a model of chain dynamics based on the anomalous diffusion of a particle moving in a harmonic well in the presence of a delta function sink. The experiments of Wiggin found, among other things, that the occasional occurrence of unusually long escape times in the distribution of chain trapping events led to nonexponential decays in the survival probability, S(t), of the DNA molecules within the nanopore. Wiggin ascribed this nonexponentiality to the existence of a distribution of trapping potentials, which they suggested was theresult of stochastic interactions between the bases of the DNA and the amino acids located on the surface of the nanopore. Based on this idea, they showed that the experimentally determined S(t) could be well fit in both the short and long time regimes by a function of the form (1+t/tau)(-alpha) (the so called Becquerel function). In our model, S(t) is found to be given by a Mittag-Leffler function at short times and by a generalized Mittag-Leffler function at long times. By suitable choice of certain parameter values, these functions are found to fit the experimental S(t) even better than the Becquerel function. Anomalous diffusion of DNA within the trap prior to escape over a barrier of fixed height may therefore provide a second, plausible explanation of the data, and may offer fresh perspectives on similar trapping and escape problems.

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Barrierless chemical reactions have often been modeled as a Brownian motion on a one-dimensional harmonic potential energy surface with a position-dependent reaction sink or window located near the minimum of the surface. This simple (but highly successful) description leads to a nonexponential survival probability only at small to intermediate times but exponential decay in the long-time limit. However, in several reactive events involving proteins and glasses, the reactions are found to exhibit a strongly nonexponential (power law) decay kinetics even in the long time. In order to address such reactions, here, we introduce a model of barrierless chemical reaction where the motion along the reaction coordinate sustains dispersive diffusion. A complete analytical solution of the model can be obtained only in the frequency domain, but an asymptotic solution is obtained in the limit of long time. In this case, the asymptotic long-time decay of the survival probability is a power law of the Mittag−Leffler functional form. When the barrier height is increased, the decay of the survival probability still remains nonexponential, in contrast to the ordinary Brownian motion case where the rate is given by the Smoluchowski limit of the well-known Kramers' expression. Interestingly, the reaction under dispersive diffusion is shown to exhibit strong dependence on the initial state of the system, thus predicting a strong dependence on the excitation wavelength for photoisomerization reactions in a dispersive medium. The theory also predicts a fractional viscosity dependence of the rate, which is often observed in the reactions occurring in complex environments.