In Vitro Activity of the Antifungal Plant Defensin RsAFP2 against Candida Isolates and Its In Vivo Efficacy in Prophylactic Murine Models of Candidiasis

We show that RsAFP2, a plant defensin that interacts with fungal glucosylceramides, is active against Candida albicans, inhibits to a lesser extent other Candida species, and is nontoxic to mammalian cells. Moreover, glucosylceramide levels in Candida species correlate with RsAFP2 sensitivity. We found RsAFP2 prophylactically effective against murine candidiasis.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

Approach to Equilibrium for a Class of Random Quantum Models of Infinite Range

We consider random generalizations of a quantum model of infinite range introduced by Emch and Radin. The generalizations allow a neat extension from the class l (1) of absolutely summable lattice potentials to the optimal class l (2) of square summable potentials first considered by Khanin and Sinai and generalised by van Enter and van Hemmen. The approach to equilibrium in the case of a Gaussian distribution is proved to be faster than for a Bernoulli distribution for both short-range and long-range lattice potentials. While exponential decay to equilibrium is excluded in the nonrandom l (1) case, it is proved to occur for both short and long range potentials for Gaussian distributions, and for potentials of class l (2) in the Bernoulli case. Open problems are discussed.

Renormalization of the S parameter in holographic models of electroweak symmetry breaking

We show that the S parameter is not finite in theories of electroweak symmetry breaking in a slice of anti-de Sitter five-dimensional space, with the light fermions localized in the ultraviolet. We compute the one-loop contributions to S from the Higgs sector and show that they are logarithmically dependent on the cutoff of the theory. We discuss the renormalization of S, as well as the implications for bounds from electroweak precision measurements on these models. We argue that, although in principle the choice of renormalization condition could eliminate the S parameter constraint, a more consistent condition would still result in a large and positive S. On the other hand, we show that the dependence on the Higgs mass in S can be entirely eliminated by the renormalization procedure, making it impossible in these theories to extract a Higgs mass bound from electroweak precision constraints.

Comparative study of dental arch width in plaster models, photocopies and digitized images

The aim of this study was to comparatively assess dental arch width, in the canine and molar regions, by means of direct measurements from plaster models, photocopies and digitized images of the models. The sample consisted of 130 pairs of plaster models, photocopies and digitized images of the models of white patients (n = 65), both genders, with Class I and Class II Division 1 malocclusions, treated by standard Edgewise mechanics and extraction of the four first premolars. Maxillary and mandibular intercanine and intermolar widths were measured by a calibrated examiner, prior to and after orthodontic treatment, using the three modes of reproduction of the dental arches. Dispersion of the data relative to pre- and posttreatment intra-arch linear measurements (mm) was represented as box plots. The three measuring methods were compared by one-way ANOVA for repeated measurements (α = 0.05). Initial / final mean values varied as follows: 33.94 to 34.29 mm / 34.49 to 34.66 mm (maxillary intercanine width); 26.23 to 26.26 mm / 26.77 to 26.84 mm (mandibular intercanine width); 49.55 to 49.66 mm / 47.28 to 47.45 mm (maxillary intermolar width) and 43.28 to 43.41 mm / 40.29 to 40.46 mm (mandibular intermolar width). There were no statistically significant differences between mean dental arch widths estimated by the three studied methods, prior to and after orthodontic treatment. It may be concluded that photocopies and digitized images of the plaster models provided reliable reproductions of the dental arches for obtaining transversal intra-arch measurements.

Comparison of some theoretical models for fittings of the temperature dependence of the fundamental energy gap in GaAs

In this work we report on a comparison of some theoretical models usually used to fit the dependence on temperature of the fundamental energy gap of semiconductor materials. We used in our investigations the theoretical models of Viña, Pässler-p and Pässler-ρ to fit several sets of experimental data, available in the literature for the energy gap of GaAs in the temperature range from 12 to 974 K. Performing several fittings for different values of the upper limit of the analyzed temperature range (Tmax), we were able to follow in a systematic way the evolution of the fitting parameters up to the limit of high temperatures and make a comparison between the zero-point values obtained from the different models by extrapolating the linear dependence of the gaps at high T to T = 0 K and that determined by the dependence of the gap on isotope mass. Using experimental data measured by absorption spectroscopy, we observed the non-linear behavior of Eg(T) of GaAs for T > ΘD.

Equation of state for the magnetic-color-flavor-locked phase and its implications for compact star models

Using the solutions of the gap equations of the magnetic-color-flavor-locked (MCFL) phase of paired quark matter in a magnetic field, and taking into consideration the separation between the longitudinal and transverse pressures due to the field-induced breaking of the spatial rotational symmetry, the equation of state of the MCFL phase is self-consistently determined. This result is then used to investigate the possibility of absolute stability, which turns out to require a field-dependent ""bag constant"" to hold. That is, only if the bag constant varies with the magnetic field, there exists a window in the magnetic field vs bag constant plane for absolute stability of strange matter. Implications for stellar models of magnetized (self-bound) strange stars and hybrid (MCFL core) stars are calculated and discussed.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Remote control of CNC machines using the CyberOPC communication system over public networks

During the last few years, the evolution of fieldbus and computers networks allowed the integration of different communication systems involving both production single cells and production cells, as well as other systems for business intelligence, supervision and control. Several well-adopted communication technologies exist today for public and non-public networks. Since most of the industrial applications are time-critical, the requirements of communication systems for remote control differ from common applications for computer networks accessing the Internet, such as Web, e-mail and file transfer. The solution proposed and outlined in this work is called CyberOPC. It includes the study and the implementation of a new open communication system for remote control of industrial CNC machines, making the transmission delay for time-critical control data shorter than other OPC-based solutions, and fulfilling cyber security requirements.

Neurobiology of panic disorder: From animal models to brain neuroimaging

Evidence from animal models of anxiety has led to the hypothesis that serotonin enhances inhibitory avoidance (related to anxiety) in the forebrain, but inhibits one-way escape (panic) in the midbrain periaqueductal gray (PAG). Stressing the difference between these emotions, neuroendocrinological results indicate that the hypothalamic-pituitary-adrenal axis is activated by anticipatory anxiety, but not by panic attack nor by electrical stimulation of the rat PAG. Functional neuroimaging has shown activation of the insula and upper brain stem (including PAG), as well as deactivation of the anterior cingulated cortex (ACC) during experimental panic attacks. Voxel-based morphometric analysis of brain magnetic resonance images has shown a grey matter volume increase in the insula and upper brain stem, and a decrease in the ACC of panic patients at rest, as compared to healthy controls. The insula and the ACC detect interoceptive stimuli, which are overestimated by panic patients. It is suggested that these brain areas and the PAG are involved in the pathophysiology of panic disorder. (C) 2008 Elsevier Ltd. All rights reserved.

Single Intranasal Administration of 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine in C57BL/6 Mice Models Early Preclinical Phase of Parkinson`s Disease

Many studies have shown that deficits in olfactory and cognitive functions precede the classical motor symptoms seen in Parkinson`s disease (PD) and that olfactory testing may contribute to the early diagnosis of this disorder. Although the primary cause of PD is still unknown, epidemiological studies have revealed that its incidence is increased in consequence of exposure to certain environmental toxins. In this study, most of the impairments presented by C57BL/6 mice infused with a single intranasal (i.n.) administration of the proneurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) (1 mg/nostril) were similar to those observed during the early phase of PD, when a moderate loss of nigral dopamine neurons results in olfactory and memory deficits with no major motor impairments. Such infusion decreased the levels of the enzyme tyrosine hydroxylase in the olfactory bulb, striatum, and substantia nigra by means of apoptotic mechanisms, reducing dopamine concentration in different brain structures such as olfactory bulb, striatum, and prefrontal cortex, but not in the hippocampus. These findings reinforce the notion that the olfactory system represents a particularly sensitive route for the transport of neurotoxins into the central nervous system that may be related to the etiology of PD. These results also provide new insights in experimental models of PD, indicating that the i.n. administration of MPTP represents a valuable mouse model for the study of the early stages of PD and for testing new therapeutic strategies to restore sensorial and cognitive processes in PD.