Validation of an experimental polyurethane model for biomechanical studies on implant-supported prosthesis: compression tests

OBJECTIVES: The complexity and heterogeneity of human bone, as well as ethical issues, most always hinder the performance of clinical trials. Thus, in vitro studies become an important source of information for the understanding of biomechanical events on implant-supported prostheses, although study results cannot be considered reliable unless validation studies are conducted. The purpose of this work was to validate an artificial experimental model based on its modulus of elasticity, to simulate the performance of human bone in vivo in biomechanical studies of implant-supported prostheses. MATERIAL AND METHODS: In this study, fast-curing polyurethane (F16 polyurethane, Axson) was used to build 40 specimens that were divided into five groups. The following reagent ratios (part A/part B) were used: Group A (0.5/1.0), Group B (0.8/1.0), Group C (1.0/1.0), Group D (1.2/1.0), and Group E (1.5/1.0). A universal testing machine (Kratos model K - 2000 MP) was used to measure modulus of elasticity values by compression. RESULTS: Mean modulus of elasticity values were: Group A - 389.72 MPa, Group B - 529.19 MPa, Group C - 571.11 MPa, Group D - 470.35 MPa, Group E - 437.36 MPa. CONCLUSION: The best mechanical characteristics and modulus of elasticity value comparable to that of human trabecular bone were obtained when A/B ratio was 1:1.

Lesion of the subthalamic nucleus reverses motor deficits but not death of nigrostriatal dopaminergic neurons in a rat 6-hydroxydopamine-lesion model of Parkinson's disease

The objective of the present study was to determine whether lesion of the subthalamic nucleus (STN) promoted by N-methyl-D-aspartate (NMDA) would rescue nigrostriatal dopaminergic neurons after unilateral 6-hydroxydopamine (6-OHDA) injection into the medial forebrain bundle (MFB). Initially, 16 mg 6-OHDA (6-OHDA group) or vehicle (artificial cerebrospinal fluid - aCSF; Sham group) was infused into the right MFB of adult male Wistar rats. Fifteen days after surgery, the 6-OHDA and SHAM groups were randomly subdivided and received ipsilateral injection of either 60 mM NMDA or aCSF in the right STN. Additionally, a control group was not submitted to stereotaxic surgery. Five groups of rats were studied: 6-OHDA/NMDA, 6-OHDA/Sham, Sham/NMDA, Sham/Sham, and Control. Fourteen days after injection of 6-OHDA, rats were submitted to the rotational test induced by apomorphine (0.1 mg/kg, ip) and to the open-field test. The same tests were performed again 14 days after NMDA-induced lesion of the STN. The STN lesion reduced the contralateral turns induced by apomorphine and blocked the progression of motor impairment in the open-field test in 6-OHDA-treated rats. However, lesion of the STN did not prevent the reduction of striatal concentrations of dopamine and metabolites or the number of nigrostriatal dopaminergic neurons after 6-OHDA lesion. Therefore, STN lesion is able to reverse motor deficits after severe 6-OHDA-induced lesion of the nigrostriatal pathway, but does not protect or rescue dopaminergic neurons in the substantia nigra pars compacta.

A fuzzy reed-frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization

Risk optimization of a steel frame communications tower subject to tornado winds

The structural engineering community in Brazil faces new challenges with the recent occurrence of high intensity tornados. Satellite surveillance data shows that the area covering the south-east of Brazil, Uruguay and some of Argentina is one of the world most tornado-prone areas, second only to the infamous tornado alley in central United States. The design of structures subject to tornado winds is a typical example of decision making in the presence of uncertainty. Structural design involves finding a good balance between the competing goals of safety and economy. This paper presents a methodology to find the optimum balance between these goals in the presence of uncertainty. In this paper, reliability-based risk optimization is used to find the optimal safety coefficient that minimizes the total expected cost of a steel frame communications tower, subject to extreme storm and tornado wind loads. The technique is not new, but it is applied to a practical problem of increasing interest to Brazilian structural engineers. The problem is formulated in the partial safety factor format used in current design codes, with all additional partial factor introduced to serve as optimization variable. The expected cost of failure (or risk) is defined as the product of a. limit state exceedance probability by a limit state exceedance cost. These costs include costs of repairing, rebuilding, and paying compensation for injury and loss of life. The total expected failure cost is the sum of individual expected costs over all failure modes. The steel frame communications, tower subject of this study has become very common in Brazil due to increasing mobile phone coverage. The study shows that optimum reliability is strongly dependent on the cost (or consequences) of failure. Since failure consequences depend oil actual tower location, it turn,,; out that different optimum designs should be used in different locations. Failure consequences are also different for the different parties involved in the design, construction and operation of the tower. Hence, it is important that risk is well understood by the parties involved, so that proper contracts call be made. The investigation shows that when non-structural terms dominate design costs (e.g, in residential or office buildings) it is not too costly to over-design; this observation is in agreement with the observed practice for non-optimized structural systems. In this situation, is much easier to loose money by under-design. When by under-design. When structural material cost is a significant part of design cost (e.g. concrete dam or bridge), one is likely to lose significantmoney by over-design. In this situation, a cost-risk-benefit optimization analysis is highly recommended. Finally, the study also shows that under time-varying loads like tornados, the optimum reliability is strongly dependent on the selected design life.

Parametric model for the analysis of concrete expansion due to alkali-aggregate reaction

The alkali-aggregate reaction (AAR) is a chemical reaction that provokes a heterogeneous expansion of concrete and reduces important properties such as Young's modulus, leading to a reduction in the structure's useful life. In this study, a parametric model is employed to determine the spatial distribution of the concrete expansion, combining normalized factors that influence the reaction through an AAR expansion law. Optimization techniques were employed to adjust the numerical results and observations in a real structure. A three-dimensional version of the model has been implemented in a finite element commercial package (ANSYS(C)) and verified in the analysis of an accelerated mortar test. Comparisons were made between two AAR mathematical descriptions for the mechanical phenomenon, using the same methodology, and an expansion curve obtained from experiment. Some parametric studies are also presented. The numerical results compared very well with the experimental data validating the proposed method.

Contribution margin model applied to the marketing planning of a container liner carrier

The implementation of confidential contracts between a container liner carrier and its customers, because of the Ocean Shipping Reform Act (OSRA) 1998, demands a revision in the methodology applied in the carrier's planning of marketing and sales. The marketing and sales planning process should be more scientific and with a better use of operational research tools considering the selection of the customers under contracts, the duration of the contracts, the freight, and the container imbalances of these contracts are basic factors for the carrier's yield. This work aims to develop a decision support system based on a linear programming model to generate the business plan for a container liner carrier, maximizing the contribution margin of its freight.

Immunomodulatory effects of recombinant BCG expressing pertussis toxin on TNF-alpha and IL-10 in a bladder cancer model

Background: Since successful treatment of superficial bladder cancer with BCG requires proper induction of Th1 immunity, we have developed a rBCG-S1PT strain that induced a stronger cellular immune response than BCG. This preclinical study was designed to compare the modulatory effects of BCG and rBCG-S1PT on bladder TNF-alpha and IL-10 expression and to evaluate antitumour activity. Methods: For Experiment I, the MB49 bladder cancer cell line was used in C57BL/6 mice. Chemical cauterization of the bladder was performed to promote intravesical tumor implantation. Mice were treated by intravesical instillation with BCG, rBCG-S1PT or PBS once a week for four weeks. After 35 days the bladders were removed and weighed. TNF-group. There were increases in TNF-alpha in the BCG-treated group, as well as increases in TNF-alpha and IL-10 mRNA in the rBCG-S1PT group. Conclusion: These data indicate a significant reduction of bladder tumor volume for the rBCG group, compared to the BCG and PBS groups. This suggests that rBCG could be a useful substitute for wild-type BCG and that the potential modulation between TNF-alpha and IL-10 cytokine productions may have therapeutic value.

Relatedness and HLA-DRB1 typing may discriminate the magnitude of the genetic susceptibility to tuberculosis using a household contact model

Background Tuberculosis clusters in families may be due to increased household exposure, shared genetic factors, or both. Household contact studies are useful to control exposure because socioeconomic and environmental conditions are similar to all subjects, allowing the evaluation of the contribution of relatedness to disease development. Methods In this study, the familial aggregation of tuberculosis using relatedness and a specific inherited marker (HLA-DRB1) was evaluated. Fifty families, which had at least two cases of tuberculosis diagnosed within the past 5 years, were selected from a cohort of tuberculosis carried out in Recife, Brazil. The first case diagnosed was considered to be a primary case. The secondary attack rate of tuberculosis in household contacts was estimated according to the degree of relatedness. The relative risk of having tuberculosis based on the degree of relatedness household and the population attributable fraction to relatedness were also estimated. HLA-DRB1 typing and attributable etiologic/preventive fractions were calculated among sick and healthy household contacts. Results Compared to unrelated contacts, the relative risk for tuberculosis adjusted for age was 1.38 (95% CI 0.86 to 2.21). Relatedness contributed 23% to the development of tuberculosis at the population levels. The HLA-DRB1*04 allele group (OR = 2.44; p =0.0324; etiologic fraction =0.15) was overrepresented and the DRB1*15 allele group (OR=0.48; p=0.0488; protective fraction=0.19) was underrepresented among household contacts exhibiting tuberculosis. The presence of DRB1 shared alleles between primary cases and their contacts was a risk factor for tuberculosis (p=0.0281). Conclusion This household contact model together with the utilisation of two genetic variables permitted the evaluation of genetic factors contributing towards tuberculosis development.

DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 <= r <= 21 (85.2%) and r >= 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 <= r <= 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (> 80%) while simultaneously achieving low contamination (similar to 2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 <= r <= 21.

Melatonin treatment decreases c-fos expression in a headache model induced by capsaicin

The aim of the present work was to analyze c-fos response within the trigeminal nucleus caudalis (TNC) of pinealectomized rats and animals that received intraperitoneal melatonin, after intracisternal infusion of capsaicin, used to induce intracranial trigeminovascular stimulation. Experimental groups consisted of animals that received vehicle solution (saline-ethanol-Tween 80, 8:1:1, diluted 1:50) only (VEI, n = 5); animals that received capsaicin solution (200 nM) only (CAP, n = 6); animals submitted to pinealectomy (PX, n = 5); sham-operated animals (SH, n = 5); animals submitted to pinealectomy followed by capsaicin stimulation (200 nM) after 15 days (PX + CAP, n = 7); and animals that received capsaicin solution (200 nM) and intraperitoneal melatonin (10 mg/kg) (CAP + MEL, n = 5). Control rats, receiving vehicle in the cisterna magna, showed a small number of c-fos-positive cells in the TNC (layer I/II) as well as the sham-operated and pinealectomized rats, when compared to animals stimulated by capsaicin. On the other hand, pinealectomized rats, which received capsaicin, presented the highest number of c-fos-positive cells. Animals receiving capsaicin and melatonin treatment had similar expression of the vehicle group. Our data provide experimental evidence to support the role of melatonin and pineal gland in the pathophysiology of neurovascular headaches.

Thermodynamic origin of cooperativity in actomyosin interactions: The coupling of short-range interactions with actin bending stiffness in an Ising-like model

We present Monte Carlo simulations for a molecular motor system found in virtually all eukaryotic cells, the acto-myosin motor system, composed of a group of organic macromolecules. Cell motors were mapped to an Ising-like model, where the interaction field is transmitted through a tropomyosin polymer chain. The presence of Ca(2+) induces tropomyosin to block or unblock binding sites of the myosin motor leading to its activation or deactivation. We used the Metropolis algorithm to find the transient and the equilibrium states of the acto-myosin system composed of solvent, actin, tropomyosin, troponin, Ca(2+), and myosin-S1 at a given temperature, including the spatial configuration of tropomyosin on the actin filament surface. Our model describes the short- and long-range cooperativity during actin-myosin binding which emerges from the bending stiffness of the tropomyosin complex. We found all transition rates between the states only using the interaction energy of the constituents. The agreement between our model and experimental data also supports the recent theory of flexible tropomyosin.

Social interaction as a heuristic for combinatorial optimization problems

We investigate the performance of a variant of Axelrod's model for dissemination of culture-the Adaptive Culture Heuristic (ACH)-on solving an NP-Complete optimization problem, namely, the classification of binary input patterns of size F by a Boolean Binary Perceptron. In this heuristic, N agents, characterized by binary strings of length F which represent possible solutions to the optimization problem, are fixed at the sites of a square lattice and interact with their nearest neighbors only. The interactions are such that the agents' strings (or cultures) become more similar to the low-cost strings of their neighbors resulting in the dissemination of these strings across the lattice. Eventually the dynamics freezes into a homogeneous absorbing configuration in which all agents exhibit identical solutions to the optimization problem. We find through extensive simulations that the probability of finding the optimal solution is a function of the reduced variable F/N(1/4) so that the number of agents must increase with the fourth power of the problem size, N proportional to F(4), to guarantee a fixed probability of success. In this case, we find that the relaxation time to reach an absorbing configuration scales with F(6) which can be interpreted as the overall computational cost of the ACH to find an optimal set of weights for a Boolean binary perceptron, given a fixed probability of success.

Simultaneous optimization by neuro-genetic approach for analysis of plant materials by laser induced breakdown spectroscopy

A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic, A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 mu s integration time gate, 1.1 mu s delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem. (C) 2009 Elsevier B.V. All rights reserved.

Optimization of the AZO dyes decoloration process through neural networks: Determination of the H2O2 addition critical point

The concentration of hydrogen peroxide is an important parameter in the azo dyes decoloration process through the utilization of advanced oxidizing processes, particularly by oxidizing via UV/H2O2. It is pointed out that, from a specific concentration, the hydrogen peroxide works as a hydroxyl radical self-consumer and thus a decrease of the system`s oxidizing power happens. The determination of the process critical point (maximum amount of hydrogen peroxide to be added) was performed through a ""thorough mapping"" or discretization of the target region, founded on the maximization of an objective function objective (constant of reaction kinetics of pseudo-first order). The discretization of the operational region occurred through a feedforward backpropagation neural model. The neural model obtained presented remarkable coefficient of correlation between real and predicted values for the absorbance variable, above 0.98. In the present work, the neural model had, as phenomenological basis the Acid Brown 75 dye decoloration process. The hydrogen peroxide addition critical point, represented by a value of mass relation (F) between the hydrogen peroxide mass and the dye mass, was established in the interval 50 < F < 60. (C) 2007 Elsevier B.V. All rights reserved.

Extending the kinetic solution of the classic Michaelis-Menten model of enzyme action

The principal aim of studies of enzyme-mediated reactions has been to provide comparative and quantitative information on enzyme-catalyzed reactions under distinct conditions. The classic Michaelis-Menten model (Biochem Zeit 49:333, 1913) for enzyme kinetic has been widely used to determine important parameters involved in enzyme catalysis, particularly the Michaelis-Menten constant (K (M) ) and the maximum velocity of reaction (V (max) ). Subsequently, a detailed treatment of the mechanisms of enzyme catalysis was undertaken by Briggs-Haldane (Biochem J 19:338, 1925). These authors proposed the steady-state treatment, since its applicability was constrained to this condition. The present work describes an extending solution of the Michaelis-Menten model without the need for such a steady-state restriction. We provide the first analysis of all of the individual reaction constants calculated analytically. Using this approach, it is possible to accurately predict the results under new experimental conditions and to characterize and optimize industrial processes in the fields of chemical and food engineering, pharmaceuticals and biotechnology.