Numerical simulation of gel electrophoresis of DNA knots in weak and strong electric fields.

Gel electrophoresis allows one to separate knotted DNA (nicked circular) of equal length according to the knot type. At low electric fields, complex knots, being more compact, drift faster than simpler knots. Recent experiments have shown that the drift velocity dependence on the knot type is inverted when changing from low to high electric fields. We present a computer simulation on a lattice of a closed, knotted, charged DNA chain drifting in an external electric field in a topologically restricted medium. Using a Monte Carlo algorithm, the dependence of the electrophoretic migration of the DNA molecules on the knot type and on the electric field intensity is investigated. The results are in qualitative and quantitative agreement with electrophoretic experiments done under conditions of low and high electric fields.

Prediction of Infant Drug Exposure Through Breastfeeding: Population PK Modeling and Simulation of Fluoxetine Exposure.

The likelihood of significant exposure to drugs in infants through breast milk is poorly defined, given the difficulties of conducting pharmacokinetics (PK) studies. Using fluoxetine (FX) as an example, we conducted a proof-of-principle study applying population PK (popPK) modeling and simulation to estimate drug exposure in infants through breast milk. We simulated data for 1,000 mother-infant pairs, assuming conservatively that the FX clearance in an infant is 20% of the allometrically adjusted value in adults. The model-generated estimate of the milk-to-plasma ratio for FX (mean: 0.59) was consistent with those reported in other studies. The median infant-to-mother ratio of FX steady-state plasma concentrations predicted by the simulation was 8.5%. Although the disposition of the active metabolite, norfluoxetine, could not be modeled, popPK-informed simulation may be valid for other drugs, particularly those without active metabolites, thereby providing a practical alternative to conventional PK studies for exposure risk assessment in this population.

Accurate and efficient simulation of multiphase flow in a heterogeneous reservoir by using error estimate and control in the multiscale finite-volume framework

The multiscale finite-volume (MSFV) method is designed to reduce the computational cost of elliptic and parabolic problems with highly heterogeneous anisotropic coefficients. The reduction is achieved by splitting the original global problem into a set of local problems (with approximate local boundary conditions) coupled by a coarse global problem. It has been shown recently that the numerical errors in MSFV results can be reduced systematically with an iterative procedure that provides a conservative velocity field after any iteration step. The iterative MSFV (i-MSFV) method can be obtained with an improved (smoothed) multiscale solution to enhance the localization conditions, with a Krylov subspace method [e.g., the generalized-minimal-residual (GMRES) algorithm] preconditioned by the MSFV system, or with a combination of both. In a multiphase-flow system, a balance between accuracy and computational efficiency should be achieved by finding a minimum number of i-MSFV iterations (on pressure), which is necessary to achieve the desired accuracy in the saturation solution. In this work, we extend the i-MSFV method to sequential implicit simulation of time-dependent problems. To control the error of the coupled saturation/pressure system, we analyze the transport error caused by an approximate velocity field. We then propose an error-control strategy on the basis of the residual of the pressure equation. At the beginning of simulation, the pressure solution is iterated until a specified accuracy is achieved. To minimize the number of iterations in a multiphase-flow problem, the solution at the previous timestep is used to improve the localization assumption at the current timestep. Additional iterations are used only when the residual becomes larger than a specified threshold value. Numerical results show that only a few iterations on average are necessary to improve the MSFV results significantly, even for very challenging problems. Therefore, the proposed adaptive strategy yields efficient and accurate simulation of multiphase flow in heterogeneous porous media.

Dynamic, auxin-responsive plasma membrane-to-nucleus movement of Arabidopsis BRX.

In Arabidopsis, interplay between nuclear auxin perception and trans-cellular polar auxin transport determines the transcriptional auxin response. In brevis radix (brx) mutants, this response is impaired, probably indirectly because of disturbed crosstalk between the auxin and brassinosteroid pathways. Here we provide evidence that BRX protein is plasma membrane-associated, but translocates to the nucleus upon auxin treatment to modulate cellular growth, possibly in conjunction with NGATHA class B3 domain-type transcription factors. Application of the polar auxin transport inhibitor naphthalene phthalamic acid (NPA) resulted in increased BRX abundance at the plasma membrane. Thus, nuclear translocation of BRX could depend on cellular auxin concentration or on auxin flux. Supporting this idea, NPA treatment of wild-type roots phenocopied the brx root meristem phenotype. Moreover, BRX is constitutively turned over by the proteasome pathway in the nucleus. However, a stabilized C-terminal BRX fragment significantly rescued the brx root growth phenotype and triggered a hypocotyl gain-of-function phenotype, similar to strong overexpressors of full length BRX. Therefore, although BRX activity is required in the nucleus, excess activity interferes with normal development. Finally, similar to the PIN-FORMED 1 (PIN1) auxin efflux carrier, BRX is polarly localized in vascular cells and subject to endocytic recycling. Expression of BRX under control of the PIN1 promoter fully rescued the brx short root phenotype, suggesting that the two genes act in the same tissues. Collectively, our results suggest that BRX might provide a contextual readout to synchronize cellular growth with the auxin concentration gradient across the root tip.

NPAS2 as a transcriptional regulator of non-rapid eye movement sleep: genotype and sex interactions.

Because the transcription factor neuronal Per-Arnt-Sim-type signal-sensor protein-domain protein 2 (NPAS2) acts both as a sensor and an effector of intracellular energy balance, and because sleep is thought to correct an energy imbalance incurred during waking, we examined NPAS2's role in sleep homeostasis using npas2 knockout (npas2-/-) mice. We found that, under conditions of increased sleep need, i.e., at the end of the active period or after sleep deprivation (SD), NPAS2 allows for sleep to occur at times when mice are normally awake. Lack of npas2 affected electroencephalogram activity of thalamocortical origin; during non-rapid eye movement sleep (NREMS), activity in the spindle range (10-15 Hz) was reduced, and within the delta range (1-4 Hz), activity shifted toward faster frequencies. In addition, the increase in the cortical expression of the NPAS2 target gene period2 (per2) after SD was attenuated in npas2-/- mice. This implies that NPAS2 importantly contributes to the previously documented wake-dependent increase in cortical per2 expression. The data also revealed numerous sex differences in sleep; in females, sleep need accumulated at a slower rate, and REMS loss was not recovered after SD. In contrast, the rebound in NREMS time after SD was compromised only in npas2-/- males. We conclude that NPAS2 plays a role in sleep homeostasis, most likely at the level of the thalamus and cortex, where NPAS2 is abundantly expressed.

Monte Carlo simulation of a whole-body counter using IGOR phantoms.

Whole-body counting is a technique of choice for assessing the intake of gamma-emitting radionuclides. An appropriate calibration is necessary, which is done either by experimental measurement or by Monte Carlo (MC) calculation. The aim of this work was to validate a MC model for calibrating whole-body counters (WBCs) by comparing the results of computations with measurements performed on an anthropomorphic phantom and to investigate the effect of a change in phantom's position on the WBC counting sensitivity. GEANT MC code was used for the calculations, and an IGOR phantom loaded with several types of radionuclides was used for the experimental measurements. The results show a reasonable agreement between measurements and MC computation. A 1-cm error in phantom positioning changes the activity estimation by >2%. Considering that a 5-cm deviation of the positioning of the phantom may occur in a realistic counting scenario, this implies that the uncertainty of the activity measured by a WBC is ∼10-20%.

Simulation of interface dynamics across pore discontinuities

We study the dynamics of a water-oil meniscus moving from a smaller to a larger pore. The process is characterised by an abrupt change in the configuration, yielding a sudden energy release. A theoretic study for static conditions provides analytical solutions of the surface energy content of the system. Although the configuration after the sudden energy release is energetically more convenient, an energy barrier must be overcome before the process can happen spontaneously. The energy barrier depends on the system geometry and on the flow parameters. The analytical results are compared to numerical simulations that solve the full Navier-Stokes equation in the pore space and employ the Volume Of Fluid (VOF) method to track the evolution of the interface. First, the numerical simulations of a quasi-static process are validated by comparison with the analytical solutions for a static meniscus, then numerical simulations with varying injection velocity are used to investigate dynamic effects on the configuration change. During the sudden energy jump the system exhibits an oscillatory behaviour. Extension to more complex geometries might elucidate the mechanisms leading to a dynamic capillary pressure and to bifurcations in final distributions of fluid phases in porous

Mass movement characterization using a reflexion and refraction seismic survey with the sloping local base level concept

This study proposes a new concept for upscaling local information on failure surfaces derived from geophysical data, in order to develop the spatial information and quickly estimate the magnitude and intensity of a landslide. A new vision of seismic interpretation on landslides is also demonstrated by taking into account basic geomorphic information with a numeric method based on the Sloping Local Base Level (SLBL). The SLBL is a generalization of the base level defined in geomorphology applied to landslides, and allows the calculation of the potential geometry of the landslide failure surface. This approach was applied to a large scale landslide formed mainly in gypsum and situated in a former glacial valley along the Rhone within the Western European Alps. Previous studies identified the existence of two sliding surfaces that may continue below the level of the valley. In this study. seismic refraction-reflexion surveys were carried out to verify the existence of these failure surfaces. The analysis of the seismic data provides a four-layer model where three velocity layers (<1000 ms(-1), 1500 ms(-1) and 3000 ms(-1)) are interpreted as the mobilized mass at different weathering levels and compaction. The highest velocity layer (>4000 ms(-1)) with a maximum depth of similar to 58 m is interpreted as the stable anhydrite bedrock. Two failure surfaces were interpreted from the seismic surveys: an upper failure and a much deeper one (respectively 25 and 50 m deep). The upper failure surface depth deduced from geophysics is slightly different from the results obtained using the SLBL, and the deeper failure surface depth calculated with the SLBL method is underestimated in comparison with the geophysical interpretations. Optimal results were therefore obtained by including the seismic data in the SLBL calculations according to the geomorphic limits of the landslide (maximal volume of mobilized mass = 7.5 x 10(6) m(3)).

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.