Unconventional neurotransmitters, neurodegeneration and neuroprotection

Neurotransmitters are also involved in functions other than conventional signal transfer between nerve cells, such as development, plasticity, neurodegeneration, and neuroprotection. For example, there is a considerable amount of data indicating developmental roles for the glutamatergic, cholinergic, dopaminergic, GABA-ergic, and ATP/adenosine systems. In this review, we discuss the existing literature on these "new" functions of neurotransmitters in relation to some unconventional neurotransmitters, such as the endocannabinoids and nitric oxide. Data indicating both transcriptional and post-transcriptional modulation of endocannabinoid and nitrinergic systems after neural lesions are discussed in relation to the non-conventional roles of these neurotransmitters. Knowledge of the roles of neurotransmitters in brain functions other than information transfer is critical for a more complete understanding of the functional organization of the brain and to provide more opportunities for the development of therapeutical tools aimed at minimizing neuronal death.

Complex networks: the key to systems biology

Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.

Pulsar binary systems in a nonsymmetric theory of gravitation II. Dipole radiation

This paper deals with the emission of gravitational radiation in the context of a previously studied metric nonsymmetric theory of gravitation. The part coming from the symmetric part of the metric coincides with the mass quadrupole moment result of general relativity. The one associated to the antisymmetric part of the metric involves the dipole moment of the fermionic charge of the system. The results are applied to binary star systems and the decrease of the period of the elliptical motion is calculated.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Learning processes and the neural analysis of conditioning

Classical and operant conditioning principles, such as the behavioral discrepancy-derived assumption that reinforcement always selects antecedent stimulus and response relations, have been studied at the neural level, mainly by observing the strengthening of neuronal responses or synaptic connections. A review of the literature on the neural basis of behavior provided extensive scientific data that indicate a synthesis between the two conditioning processes based mainly on stimulus control in learning tasks. The resulting analysis revealed the following aspects. Dopamine acts as a behavioral discrepancy signal in the midbrain pathway of positive reinforcement, leading toward the nucleus accumbens. Dopamine modulates both types of conditioning in the Aplysia mollusk and in mammals. In vivo and in vitro mollusk preparations show convergence of both types of conditioning in the same motor neuron. Frontal cortical neurons are involved in behavioral discrimination in reversal and extinction procedures, and these neurons preferentially deliver glutamate through conditioned stimulus or discriminative stimulus pathways. Discriminative neural responses can reliably precede operant movements and can also be common to stimuli that share complex symbolic relations. The present article discusses convergent and divergent points between conditioning paradigms at the neural level of analysis to advance our knowledge on reinforcement.

The effect of using mixed initiator systems on the efficiency of photopolymerization of dental resins

A study was performed in order to determine the efficiency of the simultaneous use of the photoinitiators phenylpropanedione (PPD) and camphorquinone (CQ) in the polymerization of acrylic polymers and evaluate possible mechanisms leading to synergism or antagonism. It was found that efficiencies of both initiators taken individually are higher than that of their mixture, indicating that when both dyes are used simultaneously there will be an energy transfer from the more efficient initiator (CQ) to the less efficient one (PPD). Also, there was no proof of any reaction between the amine present in the CQ formulation and the PPD excited state.

Morpho-anatomical features of underground systems in six Asteraceae species from the Brazilian Cerrado

In the Brazilian Cerrado (neotropical savanna), the development of bud-bearing underground systems as adaptive structures to fire and dry periods can comprise an important source of buds for this ecosystem, as already demonstrated in the Brazilian Campos grasslands and North American prairies. Asteraceae species from both woody and herbaceous strata have subterranean organs that accumulate carbohydrates, reinforcing the adaptive strategy of these plants to different environmental conditions. This study aims to analyse the morpho-anatomy of underground systems of six species of Asteraceae (Mikania cordifolia L.f. Willd., Mikania sessilifolia DC, Trixis nobilis (Vell.) Katinas, Pterocaulon alopecuroides (Lam.) DC., Vernonia elegans Gardner and Vernonia megapotamica Spreng.), to describe these structures and to verify the occurrence and origin of shoot buds, and to analyse the presence of reserve substances. Individuals sampled in Cerrado areas in São Paulo State showed thick underground bud-bearing organs, with adventitious or lateral roots and presence of fructans. Xylopodium was found in all studied species, except for Trixis nobilis, which had stem tuber. The presence of fructans as reserve, and the capacity of structures in the formation of buds indicate the potential of herbaceous species of Asteraceae in forming a viable bud bank for vegetation regeneration in the Brazilian Cerrado.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Prediction of good glass formers in the Al-Ni-La and Al-Ni-Gd systems using topological instability and electronegativity

A new criterion has been recently proposed combining the topological instability (lambda criterion) and the average electronegativity difference (Delta e) among the elements of an alloy to predict and select new glass-forming compositions. In the present work, this criterion (lambda.Delta e) is applied to the Al-Ni-La and Al-Ni-Gd ternary systems and its predictability is validated using literature data for both systems and additionally, using own experimental data for the Al-La-Ni system. The compositions with a high lambda.Delta e value found in each ternary system exhibit a very good correlation with the glass-forming ability of different alloys as indicated by their supercooled liquid regions (Delta T(x)) and their critical casting thicknesses. In the case of the Al-La-Ni system, the alloy with the largest lambda.Delta e value, La(56)Al(26.5)Ni(17.5), exhibits the highest glass-forming ability verified for this system. Therefore, the combined lambda.Delta e criterion is a simple and efficient tool to select new glass-forming compositions in Al-Ni-RE systems. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3563099]

Modified Steels for Cold-Forming U-Bolts Used In Leaf Springs Systems

In this work, a low alloy steel and a fabrication process were developed to produce U-Bolts for commercial vehicles. Thus, initially five types of no-heat treated steel were developed with different additions of chrome, nickel, and silicon to produce strain hardening effect during cold-forming processing of the U-Bolts, assuring the required mechanical properties. The new materials exhibited a fine perlite and ferrite microstructure due to aluminum and vanadium additions, well known as grain size refiners. The mechanical properties were evaluated in a servo-hydraulic test machine system-MTS 810 according to ASTM A370-03; E739 and E08m-00 standards. The microstructure and fractography analyses of the cold-formed steels were performed by using optical and scanning electronic microscope techniques. To evaluate the performance of the steels and the production process, fatigue tests were carried out under load control (tensile-tensile), R = 0.1 and f = 30 Hz. The Weibull statistic methodology was used for the analysis of the fatigue results. At the end of this work the 0.21% chrome content steel, Alloy 2, presented the best fatigue performance.

On the energy harvesting potential of piezoaeroelastic systems

This paper investigates the concept of piezoaeroelasticity for energy harvesting. The focus is placed on mathematical modeling and experimental validations of the problem of generating electricity at the flutter boundary of a piezoaeroelastic airfoil. An electrical power output of 10.7 mW is delivered to a 100 k load at the linear flutter speed of 9.30 m/s (which is 5.1% larger than the short-circuit flutter speed). The effect of piezoelectric power generation on the linear flutter speed is also discussed and a useful consequence of having nonlinearities in the system is addressed. (C) 2010 American Institute of Physics. [doi:10.1063/1.3427405]

Cooperation, interaction and learning in local production systems: Evidence in Brazilian firms

In a local production system (LPS), besides external economies, the interaction, cooperation, and learning are indicated by the literature as complementary ways of enhancing the LPS's competitiveness and gains. In Brazil, the greater part of LPSs, mostly composed by small enterprises, displays incipient relationships and low levels of interaction and cooperation among their actors. The size of the participating enterprises itself for specificities that engender organizational constraints, which, in turn, can have a considerable impact on their relationships and learning dynamics. For that reason, it is the purpose of this article to present an analysis of interaction, cooperation, and learning relationships among several types of actors pertaining to an LPS in the farming equipment and machinery sector, bearing in mind the specificities of small enterprises. To this end, the fieldwork carried out in this study aimed at: (i) investigating external and internal knowledge sources conducive to learning and (ii) identifying and analyzing motivating and inhibiting factors related to specificities of small enterprises in order to bring the LPS members closer together and increase their cooperation and interaction. Empirical evidence shows that internal aspects of the enterprises, related to management and infrastructure, can have a strong bearing on their joint actions, interaction and learning processes.

Diffusive Synchronization of Hyperchaotic Lorenz Systems

The synchronizing properties of two diffusively coupled hyperchaotic Lorenz 4D systems are investigated by calculating the transverse Lyapunov exponents and by observing the phase space trajectories near the synchronization hyperplane. The effect of parameter mismatch is also observed. A simple electrical circuit described by the Lorenz 4D equations is proposed. Some results from laboratory experiments with two coupled circuits are presented. Copyright (C) 2009 Ruy Barboza.

Trajectory Sensitivity Method and Master-Slave Synchronization to Estimate Parameters of Nonlinear Systems

A combination of trajectory sensitivity method and master-slave synchronization was proposed to parameter estimation of nonlinear systems. It was shown that master-slave coupling increases the robustness of the trajectory sensitivity algorithm with respect to the initial guess of parameters. Since synchronization is not a guarantee that the estimation process converges to the correct parameters, a conditional test that guarantees that the new combined methodology estimates the true values of parameters was proposed. This conditional test was successfully applied to Lorenz's and Chua's systems, and the proposed parameter estimation algorithm has shown to be very robust with respect to parameter initial guesses and measurement noise for these examples. Copyright (C) 2009 Elmer P. T. Cari et al.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.