Transdural motor cortex stimulation reverses neuropathic pain in rats: A profile of neuronal activation

Motor cortex stimulation (MCS) has been used to treat patients with neuropathic pain resistant to other therapeutic approaches; however, the mechanisms of pain control by MCS are still not clearly understood. We have demonstrated that MCS increases the nociceptive threshold of naive conscious rats, with opioid participation. In the present study, the effect of transdural MCS on neuropathic pain in rats subjected to chronic constriction injury of the sciatic nerve was investigated. In addition, the pattern of neuronal activation, evaluated by Fos and Zif268 immunolabel, was performed in the spinal cord and brain sites associated with the modulation of persistent pain. MCS reversed the mechanical hyperalgesia and allodynia induced by peripheral neuropathy. After stimulation, Fos immunoreactivity (Fos-IR) decreased in the dorsal horn of the spinal cord and in the ventral posterior lateral and medial nuclei of the thalamus, when compared to animals with neuropathic pain. Furthermore, the MCS increased the Fos-IR in the periaqueductal gray, the anterior cingulate cortex and the central and basolateral amygdaloid nuclei. Zif268 results were similar to those obtained for Fos, although no changes were observed for Zif268 in the anterior cingulate cortex and the central amygdaloid nucleus after MCS. The present findings suggest that MCS reverts neuropathic pain phenomena in rats, mimicking the effect observed in humans, through activation of the limbic and descending pain inhibitory systems. Further investigation of the mechanisms involved in this effect may contribute to the improvement of the clinical treatment of persistent pain. (c) 2010 European Federation of International Association for the Study of Pain Chapters. Published by Elsevier Ltd. All rights reserved.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

Fragment-guided approach to incorporating structural information into a CoMFA study: BACE-1 as an example

Alzheimer`s disease is an ultimately fatal neurodegenerative disease, and BACE-1 has become an attractive validated target for its therapy, with more than a hundred crystal structures deposited in the PDB. In the present study, we present a new methodology that integrates ligand-based methods with structural information derived from the receptor. 128 BACE-1 inhibitors recently disclosed by GlaxoSmithKline R&D were selected specifically because the crystal structures of 9 of these compounds complexed to BACE-1, as well as five closely related analogs, have been made available. A new fragment-guided approach was designed to incorporate this wealth of structural information into a CoMFA study, and the methodology was systematically compared to other popular approaches, such as docking, for generating a molecular alignment. The influence of the partial charges calculation method was also analyzed. Several consistent and predictive models are reported, including one with r (2) = 0.88, q (2) = 0.69 and r (pred) (2) = 0.72. The models obtained with the new methodology performed consistently better than those obtained by other methodologies, particularly in terms of external predictive power. The visual analyses of the contour maps in the context of the enzyme drew attention to a number of possible opportunities for the development of analogs with improved potency. These results suggest that 3D-QSAR studies may benefit from the additional structural information added by the presented methodology.

Functional analysis of a novel missense NBC1 mutation and of other mutations causing proximal renal tubular acidosis

Mutations in the Na+-HCO3- cotransporter NBC1 cause severe proximal tubular acidosis (pRTA) associated with ocular abnormalities. Recent studies have suggested that at least some NBC1 mutants show abnormal trafficking in the polarized cells. This study identified a new homozygous NBC1 mutation (G486R) in a patient with severe pRTA. Functional analysis in Xenopus oocytes failed to detect the G486R activity due to poor surface expression. In ECV304 cells, however, G486R showed the efficient membrane expression, and its transport activity corresponded to approximately 50% of wild-type (WT) activity. In Madin-Darby canine kidney (MDCK) cells, G486R was predominantly expressed in the basolateral membrane domain as observed for WT. Among the previously identified NBC1 mutants that showed poor surface expression in oocytes, T485S showed the predominant basolateral expression in MDCK cells. On the other hand, L522P was exclusively retained in the cytoplasm in ECV304 and MDCK cells, and functional analysis in ECV304 cells failed to detect its transport activity. These results indicate that G486R, like T485S, is a partial loss of function mutation without major trafficking abnormalities, while L522P causes the clinical phenotypes mainly through its inability to reach the plasma membranes. Multiple experimental approaches would be required to elucidate potential disease mechanism by NBC1 mutations.

THE CO-INFLUENCE OF THE SEA BREEZE AND THE COASTAL UPWELLING AT CABO FRIO: A NUMERICAL INVESTIGATION USING COUPLED MODELS

A coupled atmospheric-oceanic model was used to investigate whether there is a positive feedback between the coastal upwelling and the sea breeze at Cabo Frio - RJ (Brazil). Two experiments were performed to ascertain the influence of the sea breeze on the coastal upwelling: the first one used the coupled model forced with synoptic NE winds of 8 m s(-1) and the sign of the sea breeze circulation was set by the atmospheric model; the second experiment used only the oceanic model with constant 8 m s(-1) NE winds. Then, to study the influence of the coastal upwelling on the sea breeze, two more experiments were performed: one using a coastal upwelling representative SST initial field and the other one using a constant and homogeneous SST field of 26 degrees C. Finally, two more experiments were conducted to verify the influence of the topography and the spatial distribution of the sea surface temperature on the previous results. The results showed that the sea breeze can intensify the coastal upwelling, but the coastal upwelling does not intensify the sea breeze circulation, suggesting that there is no positive feedback between these two phenomena at Cabo Frio.

A numerical investigation of the atmosphere-ocean thermal contrast over the coastal upwelling region of Cabo Frio, Brazil

An one-dimensional atmospheric second order closure model, coupled to an oceanic mixed layer model, is used to investigate the short term variation of the atmospheric and oceanic boundary layers in the coastal upwelling area of Cabo Frio, Brazil (23 degrees S, 42 degrees 08`W). The numerical simulations were carried out to evaluate the impact caused by the thermal contrast between atmosphere and ocean on the vertical extent and other properties of both atmospheric and oceanic boundary layers. The numerical simulations were designed taking as reference the observations carried out during the passage of a cold front that disrupted the upwelling regime in Cabo Frio in July of 1992. The simulations indicated that in 10 hours the mechanical mixing, sustained by a constant background flow of 10 in s(-1), increases the atmospheric boundary layer in 214 in when the atmosphere is initially 2 K warmer than the ocean (positive thermal contrast observed during upwelling regime). For an atmosphere initially -2 K colder than the ocean (negative thermal contrast observed during passage of the cold front), the incipient thermal convection intensifies the mechanical mixing increasing the vertical extent of the atmospheric boundary layer in 360 in. The vertical evolution of the atmospheric boundary layer is consistent with the observations carried out in Cabo Frio during upwelling condition. When the upwelling is disrupted, the discrepancy between the simulated and observed atmospheric boundary layer heights in Cabo Frio during July of 1992 increases considerably. During the period of 10 hours, the simulated oceanic mixed layer deepens 2 in and 5.4 in for positive and negative thermal contrasts of 2 K and -2 K, respectively. In the latter case, the larger vertical extent of the oceanic mixed layer is due to the presence of thermal convection in the atmospheric boundary layer, which in turn is associated to the absence of upwelling caused by the passage of cold fronts in Cabo Frio.

THREE-DIMENSIONAL NUMERICAL SIMULATIONS OF MAGNETIZED WINDS OF SOLAR-LIKE STARS

By means of self-consistent three-dimensional magnetohydrodynamics (MHD) numerical simulations, we analyze magnetized solar-like stellar winds and their dependence on the plasma-beta parameter (the ratio between thermal and magnetic energy densities). This is the first study to perform such analysis solving the fully ideal three-dimensional MHD equations. We adopt in our simulations a heating parameter described by gamma, which is responsible for the thermal acceleration of the wind. We analyze winds with polar magnetic field intensities ranging from 1 to 20 G. We show that the wind structure presents characteristics that are similar to the solar coronal wind. The steady-state magnetic field topology for all cases is similar, presenting a configuration of helmet streamer-type, with zones of closed field lines and open field lines coexisting. Higher magnetic field intensities lead to faster and hotter winds. For the maximum magnetic intensity simulated of 20 G and solar coronal base density, the wind velocity reaches values of similar to 1000 km s(-1) at r similar to 20r(0) and a maximum temperature of similar to 6 x 10(6) K at r similar to 6r(0). The increase of the field intensity generates a larger ""dead zone"" in the wind, i.e., the closed loops that inhibit matter to escape from latitudes lower than similar to 45 degrees extend farther away from the star. The Lorentz force leads naturally to a latitude-dependent wind. We show that by increasing the density and maintaining B(0) = 20 G the system recover back to slower and cooler winds. For a fixed gamma, we show that the key parameter in determining the wind velocity profile is the beta-parameter at the coronal base. Therefore, there is a group of magnetized flows that would present the same terminal velocity despite its thermal and magnetic energy densities, as long as the plasma-beta parameter is the same. This degeneracy, however, can be removed if we compare other physical parameters of the wind, such as the mass-loss rate. We analyze the influence of gamma in our results and we show that it is also important in determining the wind structure.

Infeasibility handling in genetic algorithm using nested domains for production planning

In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.

Numerical analysis of an incremented statistical sampling procedure in MCNP

MCNP has stood so far as one of the main Monte Carlo radiation transport codes. Its use, as any other Monte Carlo based code, has increased as computers perform calculations faster and become more affordable along time. However, the use of Monte Carlo method to tally events in volumes which represent a small fraction of the whole system may turn to be unfeasible, if a straight analogue transport procedure (no use of variance reduction techniques) is employed and precise results are demanded. Calculations of reaction rates in activation foils placed in critical systems turn to be one of the mentioned cases. The present work takes advantage of the fixed source representation from MCNP to perform the above mentioned task in a more effective sampling way (characterizing neutron population in the vicinity of the tallying region and using it in a geometric reduced coupled simulation). An extended analysis of source dependent parameters is studied in order to understand their influence on simulation performance and on validity of results. Although discrepant results have been observed for small enveloping regions, the procedure presents itself as very efficient, giving adequate and precise results in shorter times than the standard analogue procedure. (C) 2007 Elsevier Ltd. All rights reserved.

Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization

Augmented Lagrangian methods for large-scale optimization usually require efficient algorithms for minimization with box constraints. On the other hand, active-set box-constraint methods employ unconstrained optimization algorithms for minimization inside the faces of the box. Several approaches may be employed for computing internal search directions in the large-scale case. In this paper a minimal-memory quasi-Newton approach with secant preconditioners is proposed, taking into account the structure of Augmented Lagrangians that come from the popular Powell-Hestenes-Rockafellar scheme. A combined algorithm, that uses the quasi-Newton formula or a truncated-Newton procedure, depending on the presence of active constraints in the penalty-Lagrangian function, is also suggested. Numerical experiments using the Cute collection are presented.

Design of novel antituberculosis compounds using graph-theoretical and substructural approaches

The increasing resistance of Mycobacterium tuberculosis to the existing drugs has alarmed the worldwide scientific community. In an attempt to overcome this problem, two models for the design and prediction of new antituberculosis agents were obtained. The first used a mixed approach, containing descriptors based on fragments and the topological substructural molecular design approach (TOPS-MODE) descriptors. The other model used a combination of two-dimensional (2D) and three-dimensional (3D) descriptors. A data set of 167 compounds with great structural variability, 72 of them antituberculosis agents and 95 compounds belonging to other pharmaceutical categories, was analyzed. The first model showed sensitivity, specificity, and accuracy values above 80% and the second one showed values higher than 75% for these statistical indices. Subsequently, 12 structures of imidazoles not included in this study were designed, taking into account the two models. In both cases accuracy was 100%, showing that the methodology in silico developed by us is promising for the rational design of antituberculosis drugs.