Molecular modeling studies and in vitro bioactivity evaluation of a set of novel 5-nitro-heterocyclic derivatives as anti-T. cruzi agents

In this study, in vitro anti-T. cruzi activity assays of nifuroxazide (NX) analogues, such as 5-nitro-2-furfuryliden and 5-nitro-2-theniliden derivatives, were performed. A molecular modeling approach was also carried out to relate the lipophilicity potential ( LP) property and biological activity data. The majority of the NX derivatives showed increased anti-T. cruzi activity in comparison to the reference drug, benznidazole (BZN). Additionally, the 5-nitro-2-furfuryliden derivatives presented better pharmacological profile than the 5-nitro-2-theniliden analogues. The LP maps and corresponding ClogP values indicate that there is an optimum lipophilicity value, which must be observed in the design of new potential anti-T. cruzi agents. (c) 2009 Elsevier Ltd. All rights reserved.

Synthesis, antichagasic in vitro evaluation, cytotoxicity assays, molecular modeling and SAR/QSAR studies of a 2-phenyl-3-(1-phenyl-1H-pyrazol-4-yl)-acrylic acid benzylidene-carbohydrazide series

Chagas disease (American trypanosomiasis) is one of the most important parasitic diseases with serious social and economic impacts mainly on Latin America. This work reports the synthesis, in vitro trypanocidal evaluation, cytotoxicity assays, and molecular modeling and SAR/QSAR studies of a new series of N-phenylpyrazole benzylidene-carbohydrazides. The results pointed 6k (X = H, Y = p-NO(2), pIC(50) = 4.55 M) and 6l (X = F, Y = p-CN, pIC(50) = 4.27 M) as the most potent derivatives compared to crystal violet (pIC(50) = 3.77 M). The halogen-benzylidene-carbohydrazide presented the lowest potency whereas 6l showed the most promising pro. le with low toxicity (0% of cell death). The best equation from the 4D-QSAR analysis (Model 1) was able to explain 85% of the activity variability. The QSAR graphical representation revealed that bulky X-substituents decreased the potency whereas hydrophobic and hydrogen bond acceptor Y-substituents increased it. (C) 2008 Elsevier Ltd. All rights reserved.

Towards realistic simulations of lava dome growth using the level set method

The level set method has been implemented in a computational volcanology context. New techniques are presented to solve the advection equation and the reinitialisation equation. These techniques are based upon an algorithm developed in the finite difference context, but are modified to take advantage of the robustness of the finite element method. The resulting algorithm is tested on a well documented Rayleigh–Taylor instability benchmark [19], and on an axisymmetric problem where the analytical solution is known. Finally, the algorithm is applied to a basic study of lava dome growth.

Governing coordination: Behavioural principles and neural correlates

The coordination of movement is governed by a coalition of constraints. The expression of these constraints ranges from the concrete—the restricted range of motion offered by the mechanical configuration of our muscles and joints; to the abstract—the difficulty that we experience in combining simple movements into complex rhythms. We seek to illustrate that the various constraints on coordination are complementary and inclusive, and the means by which their expression and interaction are mediated systematically by the integrative action of the central nervous system (CNS). Beyond identifying the general principles at the behavioural level that govern the mutual interplay of constraints, we attempt to demonstrate that these principles have as their foundation specific functional properties of the cortical motor systems. We propose that regions of the brain upstream of the motor cortex may play a significant role in mediating interactions between the functional representations of muscles engaged in sensorimotor coordination tasks. We also argue that activity in these ldquosupramotorrdquo regions may mediate the stabilising role of augmented sensory feedback.

The sites of neural adaptation induced by resistance training in humans

Although it has long been supposed that resistance training causes adaptive changes in the CNS, the sites and nature of these adaptations have not previously been identified. In order to determine whether the neural adaptations to resistance training occur to a greater extent at cortical or subcortical sites in the CNS, we compared the effects of resistance training on the electromyographic (EMG) responses to transcranial magnetic (TMS) and electrical (TES) stimulation. Motor evoked potentials (MEPs) were recorded from the first dorsal interosseous muscle of 16 individuals before and after 4 weeks of resistance training for the index finger abductors (n = 8), or training involving finger abduction-adduction without external resistance (n = 8). TMS was delivered at rest at intensities from 5 % below the passive threshold to the maximal output of the stimulator. TMS and TES were also delivered at the active threshold intensity while the participants exerted torques ranging from 5 to 60 % of their maximum voluntary contraction (MVC) torque. The average latency of MEPs elicited by TES was significantly shorter than that of TMS MEPs (TES latency = 21.5 ± 1.4 ms; TMS latency = 23.4 ± 1.4 ms; P < 0.05), which indicates that the site of activation differed between the two forms of stimulation. Training resulted in a significant increase in MVC torque for the resistance-training group, but not the control group. There were no statistically significant changes in the corticospinal properties measured at rest for either group. For the active trials involving both TMS and TES, however, the slope of the relationship between MEP size and the torque exerted was significantly lower after training for the resistance-training group (P < 0.05). Thus, for a specific level of muscle activity, the magnitude of the EMG responses to both forms of transcranial stimulation were smaller following resistance training. These results suggest that resistance training changes the functional properties of spinal cord circuitry in humans, but does not substantially affect the organisation of the motor cortex.

Using the level set method to model endogenous lava dome growth

Modeling volcanic phenomena is complicated by free-surfaces often supporting large rheological gradients. Analytical solutions and analogue models provide explanations for fundamental characteristics of lava flows. But more sophisticated models are needed, incorporating improved physics and rheology to capture realistic events. To advance our understanding of the flow dynamics of highly viscous lava in Peléean lava dome formation, axi-symmetrical Finite Element Method (FEM) models of generic endogenous dome growth have been developed. We use a novel technique, the level-set method, which tracks a moving interface, leaving the mesh unaltered. The model equations are formulated in an Eulerian framework. In this paper we test the quality of this technique in our numerical scheme by considering existing analytical and experimental models of lava dome growth which assume a constant Newtonian viscosity. We then compare our model against analytical solutions for real lava domes extruded on Soufrière, St. Vincent, W.I. in 1979 and Mount St. Helens, USA in October 1980 using an effective viscosity. The level-set method is found to be computationally light and robust enough to model the free-surface of a growing lava dome. Also, by modeling the extruded lava with a constant pressure head this naturally results in a drop in extrusion rate with increasing dome height, which can explain lava dome growth observables more appropriately than when using a fixed extrusion rate. From the modeling point of view, the level-set method will ultimately provide an opportunity to capture more of the physics while benefiting from the numerical robustness of regular grids.

Modeling control objectives for business process compliance

Business process design is primarily driven by process improvement objectives. However, the role of control objectives stemming from regulations and standards is becoming increasingly important for businesses in light of recent events that led to some of the largest scandals in corporate history. As organizations strive to meet compliance agendas, there is an evident need to provide systematic approaches that assist in the understanding of the interplay between (often conflicting) business and control objectives during business process design. In this paper, our objective is twofold. We will firstly present a research agenda in the space of business process compliance, identifying major technical and organizational challenges. We then tackle a part of the overall problem space, which deals with the effective modeling of control objectives and subsequently their propagation onto business process models. Control objective modeling is proposed through a specialized modal logic based on normative systems theory, and the visualization of control objectives on business process models is achieved procedurally. The proposed approach is demonstrated in the context of a purchase-to-pay scenario.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Modeling ex vivo hematopoiesis using chemical engineering metaphors

Ex vivo hematopoiesis is increasingly used for clinical applications. Models of ex vivo hematopoiesis are required to better understand the complex dynamics and to optimize hematopoietic culture processes. A general mathematical modeling framework is developed which uses traditional chemical engineering metaphors to describe the complex hematopoietic dynamics. Tanks and tubular reactors are used to describe the (pseudo-) stochastic and deterministic elements of hematopoiesis, respectively. Cells at any point in the differentiation process can belong to either an immobilized, inert phase (quiescent cells) or a mobile, active phase (cycling cells). The model describes five processes: (1) flow (differentiation), (2) autocatalytic formation (growth),(3) degradation (death), (4) phase transition from immobilized to mobile phase (quiescent to cycling transition), and (5) phase transition from mobile to immobilized phase (cycling to quiescent transition). The modeling framework is illustrated with an example concerning the effect of TGF-beta 1 on erythropoiesis. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

Modeling the optical constants of GaP, InP, and InAs

An extension of the Adachi model with the adjustable broadening function, instead of the Lorentzian one, is employed to model the optical constants of GaP, InP, and InAs. Adjustable broadening is modeled by replacing the damping constant with the frequency-dependent expression. The improved flexibility of the model enables achieving an excellent agreement with the experimental data. The relative rms errors obtained for the refractive index equal 1.2% for GaP, 1.0% for InP, and 1.6% for InAs. (C) 1999 American Institute of Physics. [S0021-8979(99)05807-7].

Modeling the fluid-flow-induced stress and collapse in a dendritic network

An analytical approach to the stress development in the coherent dendritic network during solidification is proposed. Under the assumption that stresses are developed in the network as a result of the friction resisting shrinkage-induced interdendritic fluid flow, the model predicts the stresses in the solid. The calculations reflect the expected effects of postponed dendrite coherency, slower solidification conditions, and variations of eutectic volume fraction and shrinkage. Comparing the calculated stresses to the measured shear strength of equiaxed mushy zones shows that it is possible for the stresses to exceed the strength, thereby resulting in reorientation or collapse of the dendritic network.

Modeling the optical constants of AlxGa1-xAs alloys

The extension of Adachi's model with a Gaussian-like broadening function, in place of Lorentzian, is used to model the optical dielectric function of the alloy AlxGa1-xAs. Gaussian-like broadening is accomplished by replacing the damping constant in the Lorentzian line shape with a frequency dependent expression. In this way, the comparative simplicity of the analytic formulas of the model is preserved, while the accuracy becomes comparable to that of more intricate models, and/or models with significantly more parameters. The employed model accurately describes the optical dielectric function in the spectral range from 1.5 to 6.0 eV within the entire alloy composition range. The relative rms error obtained for the refractive index is below 2.2% for all compositions. (C) 1999 American Institute of Physics. [S0021-8979(99)00512-5].

Phase diagram of a Heisenberg spin-Peierls model with quantum phonons

Using a new version of the density-matrix renormalization group we determine the phase diagram of a model of an antiferromagnetic Heisenberg spin chain where the spins interact with quantum phonons. A quantum phase transition from a gapless spin-fluid state to a gapped dimerized phase occurs at a nonzero value of the spin-phonon coupling. The transition is in the same universality class as that of a frustrated spin chain, to which the model maps in the diabatic limit. We argue that realistic modeling of known spin-Peierls materials should include the effects of quantum phonons.

Designs for an asymmetric gradient set and a compact superconducting magnet for neural magnetic resonance imaging

Imaging of the head and neck is the most commonly performed clinical magnetic resonance imaging (MRI) examination [R. G. Evans and J. R. G. Evans, AJR 157, 603 (1991)]. This is usually undertaken in a generalist MRI instrument containing superconducting magnet system capable of imaging all organs. These generalist instruments are large, typically having a bore of 0.9-1.0 m and a length of 1.7-2.5 m and therefore are expensive to site, somewhat claustrophobic to the patient, and offer little access by attending physicians. In this article, we present the design of a compact, superconducting MRI magnet for head and neck imaging that is less than 0.8 m in length and discuss in detail the design of an asymmetric gradient coil set, tailored to the magnet profile. In particular, the introduction of a radio-frequency FM modulation scheme in concert with a gradient sequence allows the epoch of the linear region of the gradient set to be much closer to the end of the gradient structure than was previously possible. Images from a prototype gradient set demonstrate the effectiveness of the designs. (C) 1999 American Institute of Physics. [S0034-6748(99)04910-2].