Characterization of dynamic solid phase DNA extraction from blood with magnetically controlled silica beads

A novel solid phase extraction technique is described where DNA is bound and eluted from magnetic silica beads in a manner where efficiency is dependent on the magnetic manipulation of the beads and not on the flow of solution through a packed bed. The utility of this technique in the isolation of reasonably pure, PCR-amplifiable DNA from complex samples is shown by isolating DNA from whole human blood, and subsequently amplifying a fragment of the beta-globin gene. By effectively controlling the movement of the solid phase in the presence of a static sample, the issues associated with reproducibly packing a solid phase in a microchannel and maintaining consistent flow rates are eliminated. The technique described here is rapid, simple, and efficient, allowing for recovery of more than 60% of DNA from 0.6 mu L of blood at a concentration which is suitable for PCR amplification. In addition, the technique presented here requires inexpensive, common laboratory equipment, making it easily adopted for both clinical point-of-care applications and on-site forensic sample analysis.

Dynamic light scattering and optical absorption spectroscopy study of pH and temperature stabilities of the extracellular hemoglobin of Glossoscolex paulistus

The extracellular hemoglobin of Glossoscolex paulistus (HbGp) is constituted of subunits containing heme groups, monomers and trimers, and nonheme structures, called linkers, and the whole protein has a minimum molecular mass near 3.1 x 10(6) Da. This and other proteins of the same family are useful model systems for developing blood substitutes due to their extracellular nature, large size, and resistance to oxidation. HbGp samples were studied by dynamic light scattering (DLS). In the pH range 6.0-8.0, HbGp is stable and has a monodisperse size distribution with a z-average hydrodynamic diameter (D-h) of 27 +/- 1 nm. A more alkaline pH induced an irreversible dissociation process, resulting in a smaller D-h of 10 +/- 1 nm. The decrease in D-h suggests a complete hemoglobin dissociation. Gel filtration chromatography was used to show unequivocally the oligomeric dissociation observed at alkaline pH. At pH 9.0, the dissociation kinetics is slow, taking a minimum of 24 h to be completed. Dissociation rate constants progressively increase at higher pH, becoming, at pH 10.5, not detectable by DILS. Protein temperature stability was also pH-dependent. Melting curves for HbGp showed oligomeric dissociation and protein denaturation as a function of pH. Dissociation temperatures were lower at higher pH. Kinetic studies were also performed using ultraviolet-visible absorption at the Soret band. Optical absorption monitors the hemoglobin autoxidation while DLS gives information regarding particle size changes in the process of protein dissociation. Absorption was analyzed at different pH values in the range 9.0-9.8 and at two temperatures, 25 degrees C and 38 degrees C. At 25 degrees C, for pH 9.0 and 9.3, the kinetics monitored by ultraviolet-visible absorption presents a monoexponential behavior, whereas for pH 9.6 and 9.8, a biexponential behavior was observed, consistent with heme heterogeneity at more alkaline pH. The kinetics at 38 degrees C is faster than that at 25 degrees C and is biexponential in the whole pH range. DLS dissociation rates are faster than the autoxidation dissociation rates at 25 degrees C. Autoxiclation and dissociation processes are intimately related, so that oligomeric protein dissociation promotes the increase of autoxidation rate and vice versa. The effect of dissociation is to change the kinetic character of the autoxidation of hemes from monoexponential to biexponential, whereas the reverse change is not as effective. This work shows that DLS can be used to follow, quantitatively and in real time, the kinetics of changes in the oligomerization of biologic complex supramolecular systems. Such information is relevant for the development of mimetic systems to be used as blood substitutes.

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 and validation of a LIBS method for the determination of macro and micronutrients in sugar cane leaves

Laser induced breakdown spectrometry (LIBS) was applied for the determination of macro (P, K, Ca, Mg) and micronutrients (B, Cu, Fe, Mn and Zn) in sugar cane leaves, which is one of the most economically important crops in Brazil. Operational conditions were previously optimized by a neuro-genetic approach, by using a laser Nd:YAG at 1064 nm with 110 mJ per pulse focused on a pellet surface prepared with ground plant samples. Emission intensities were measured after 2.0 mu s delay time, with 4.5 mu s integration time gate and 25 accumulated laser pulses. Measurements of LIBS spectra were based on triplicate and each replicate consisted of an average of ten spectra collected in different sites (craters) of the pellet. Quantitative determinations were carried out by using univariate calibration and chemometric methods, such as PLSR and iPLS. The calibration models were obtained by using 26 laboratory samples and the validation was carried out by using 15 test samples. For comparative purpose, these samples were also microwave-assisted digested and further analyzed by ICP OES. In general, most results obtained by LIBS did not differ significantly from ICP OES data by applying a t-test at 95% confidence level. Both LIBS multivariate and univariate calibration methods produced similar results, except for Fe where better results were achieved by the multivariate approach. Repeatability precision varied from 0.7 to 15% and 1.3 to 20% from measurements obtained by multivariate and univariate calibration, respectively. It is demonstrated that LIBS is a powerful tool for analysis of pellets of plant materials for determination of macro and micronutrients by choosing calibration and validation samples with similar matrix composition.

Exercise intensity optimization for men with high cardiorespiratory fitness

Exercise intensity is a key parameter for exercise prescription but the optimal range for individuals with high cardiorespiratory fitness is unknown. The aims of this study were (1) to determine optimal heart rate ranges for men with high cardiorespiratory fitness based on percentages of maximal oxygen consumption (%VO(2max)) and reserve oxygen consumption (%VO(2reserve)) corresponding to the ventilatory threshold and respiratory compensation point, and ( 2) to verify the effect of advancing age on the exercise intensities. Maximal cardiorespiratory testing was performed on 210 trained men. Linear regression equations were calculated using paired data points between percentage of maximal heart rate (%HR(max)) and %VO(2max) and between percentage of heart rate reserve (%HRR) and %VO(2reserve) attained at each minute during the test. Values of %VO(2max) and %VO(2reserve) at the ventilatory threshold and respiratory compensation point were used to calculate the corresponding values of %HRmax and %HRR, respectively. The ranges of exercise intensity in relation to the ventilatory threshold and respiratory compensation point were achieved at 78-93% of HR(max) and 70-93% of HRR, respectively. Although absolute heart rate decreased with advancing age, there were no age-related differences in %HR(max) and %HRR at the ventilatory thresholds. Thus, in men with high cardiorespiratory fitness, the ranges of exercise intensity based on %HR(max) and %HRR regarding ventilatory threshold were 78-93% and 70-93% respectively, and were not influenced by advancing age.

Atenolol blunts blood pressure increase during dynamic resistance exercise in hypertensives

center dot Dynamic resistance exercise promotes a sizeable increase in blood pressure during its execution in non medicated hypertensives. WHAT THIS STUDY ADDS center dot Atenolol not only decreases blood pressure level but also mitigates the increase of blood pressure during dynamic resistance exercise in hypertensive patients. An increase in blood pressure during resistance exercise might be at least in part attributed to an increase in cardiac output. AIMS This study was conducted to determine whether atenolol was able to decrease BP level and mitigate BP increase during dynamic resistance exercise performed at three different intensities in hypertensives. METHODS Ten essential hypertensives (systolic/diastolic BP between 140/90 and 160/105 mmHg) were blindly studied after 6 weeks of placebo and atenolol. In each phase, volunteers executed, in a random order, three protocols of knee-extension exercises to fatigue: (i) one set at 100% of 1 RM; (ii) three sets at 80% of 1 RM; and (iii) three sets at 40% of 1 RM. Intra-arterial radial blood pressure was measured throughout the protocols. RESULTS Atenolol decreased systolic BP maximum values achieved during the three exercise protocols (100% = 186 +/- 4 vs. 215 +/- 7, 80% = 224 +/- 7 vs. 247 +/- 9 and 40% = 223 +/- 7 vs. 252 +/- 16 mmHg, P < 0.05). Atenolol also mitigated an increase in systolic BP in the first set of exercises (100% = +38 +/- 5 vs. +54 +/- 9; 80% = +68 +/- 11 vs. +84 +/- 13 and 40% = +69 +/- 7 vs. +84 +/- 14, mmHg, P < 0.05). Atenolol decreased diastolic BP values and mitigated its increase during exercise performed at 100% of 1 RM (126 +/- 6 vs. 145 +/- 6 and +41 +/- 6 vs. +52 +/- 6, mmHg, P < 0.05), but not at the other exercise intensities. CONCLUSIONS Atenolol was effective in both reducing systolic BP maximum values and mitigating BP increase during resistance exercise performed at different intensities in hypertensive subjects.

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.

Optimization of Heat Treatment Profiles Applied to Nanometric-Scale Nb(3)Sn Wires With Cu-Sn Artificial Pinning Centers

Nb(3)Sn is one of the most used superconducting materials for applications in high magnetic fields. The improvement of the critical current densities (J(c)) is important, and must be analyzed together with the optimization of the flux pinning acting in the material. For Nb(3)Sn, it is known that the grain boundaries are the most effective pinning centers. However, the introduction of artificial pinning centers (APCs) with different superconducting properties has been proved to be beneficial for J(c). As these APCs are normally in the nanometric-scale, the conventional heat treatment profiles used for Nb(3)Sn wires cannot be directly applied, leading to excessive grain growth and/or increase of the APCs cross sections. In this work, the heat treatment profiles for Nb(3)Sn superconductor wires with Cu(Sn) artificial pinning centers in nanometric-scale were analyzed in an attempt to improve J(c) . It is described a methodology to optimize the heat treatment profiles in respect to diffusion, reaction and formation of the superconducting phases. Microstructural, transport and magnetic characterization were performed in an attempt to find the pinning mechanisms acting in the samples. It was concluded that the maximum current densities were found when normal phases (due to the introduction of the APCs) are acting as main pinning centers in the global behavior of the Nb(3)Sn superconducting wire.

Improved xylitol production in media containing phenolic aldehydes: application of response surface methodology for optimization and modeling of bioprocess

BACKGROUND: The combined effects of vanillin and syringaldehyde on xylitol production by Candida guilliermondii using response surface methodology (RSM) have been studied. A 2(2) full-factorial central composite design was employed for experimental design and analysis of the results. RESULTS: Maximum xylitol productivities (Q(p) = 0.74 g L(-1) h(-1)) and yields (Y(P/S) = 0.81 g g(-1)) can be attained by adding only vanillin at 2.0 g L(-1) to the fermentation medium. These data were closely correlated with the experimental results obtained (0.69 +/- 0.04 g L(-1) h(-1) and 0.77 +/- 0.01 g g(-1)) indicating a good agreement with the predicted value. C. guilliermondii was able to convert vanillin completely after 24 h of fermentation with 94% yield of vanillyl alcohol. CONCLUSIONS: The bioconversion of xylose into xylitol by C. guilliermondii is strongly dependent on the combination of aldehydes and phenolics in the fermentation medium. Vanillin is a source of phenolic compound able to improve xylitol production by yeast. The conversion of vanillin to alcohol vanilyl reveals the potential of this yeast for medium detoxification. (C) 2009 Society of Chemical Industry

Flux Pinning Optimization of MgB(2) Bulk Samples Prepared Using High-Energy Ball Milling and Addition of TaB(2)

MgB(2) is considered to be an important conductor for applications. Optimizing flux pinning in these conductors can improve their critical currents. Doping can influence flux pinning efficiency and grain connectivity, and also affect the resistivity, upper critical field and critical temperature. This study was designed to attempt the doping of MgB(2) on the Mg sites with metal-diborides using high-energy ball milling. MgB(2) samples were prepared by milling pre-reacted MgB(2) and TaB(2) powders using a Spex 8000M mill with WC jars and balls in a nitrogen-filled glove box. The mixing concentration in (Mg(1-x)Ta(x))B(2) was up to x = 0.10. Samples were removed from the WC jars after milling times up to 4000 minutes and formed into pellets using cold isostatic pressing. The pellets were heat treated in a hot isostatic press (HIP) at 1000 degrees C under a pressure of 30 kpsi for 24 hours. The influence that milling time and TaB(2) addition had on the microstructure and the resulting superconducting properties of TaB(2)-added MgB(2) is discussed. Improvement J(c) of at high magnetic fields and of pinning could be obtained in milled samples with added TaB(2) The sample with added 5at.% TaB(2) and milled for 300 minutes showed values of J(c) similar to 7 x 10(5) A/cm(2) and F(p) similar to 14 GN/m(3) at 2T, 4.2 K. The milled and TaB(2)-mixed samples showed higher values of mu(0)H(irr) than the unmilled-unmixed sample.

Total Soluble Solids from Banana: Evaluation and Optimization of Extraction Parameters

Banana, an important component in the diet of the global population, is one of the most consumed fruits in the world. This fruit is also very favorable to industry processes (e. g., fermented beverages) due to its rich content on soluble solids and minerals, with low acidity. The main objective of this work was to evaluate the influence of factors such as banana weight and extraction time during a hot aqueous extraction process on the total soluble solids content of banana. The extract is to be used by the food and beverage industries. The experiments were performed with 105 mL of water, considering the moisture of the ripe banana (65%). Total sugar concentrations were obtained in a beer analyzer and the result expressed in degrees Plato (degrees P, which is the weight of the extract or the sugar equivalent in 100 g solution at 20 degrees C), aiming at facilitating the use of these results by the beverage industries. After previous studies of characterization of the fruit and of ripening performance, a 2(2) full-factorial star design was carried out, and a model was developed to describe the behavior of the dependent variable (total soluble solids) as a function of the factors (banana weight and extraction time), indicating as optimum conditions for extraction 38.5 g of banana at 39.7 min.

Gait Pattern Adaptation for an Active Lower-Limb Orthosis Based on Neural Networks

This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis-patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis-patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle-foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern. (C) Koninklijke Brill NV, Leiden, 2011

A novel multiobjective optimization algorithm based on bacterial chemotaxis

In this article a novel algorithm based on the chemotaxis process of Echerichia coil is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO. (C) 2009 Elsevier Ltd. All rights reserved.

Optimization of modal filters based on arrays of piezoelectric sensors

Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

Effective Electromechanical Coupling Coefficients of Piezoelectric Adaptive Structures: Critical Evaluation and Optimization

This work presents a critical analysis of methodologies to evaluate the effective (or generalized) electromechanical coupling coefficient (EMCC) for structures with piezoelectric elements. First, a review of several existing methodologies to evaluate material and effective EMCC is presented. To illustrate the methodologies, a comparison is made between numerical, analytical and experimental results for two simple structures: a cantilever beam with bonded extension piezoelectric patches and a simply-supported sandwich beam with an embedded shear piezoceramic. An analysis of the electric charge cancelation effect on the effective EMCC observed in long piezoelectric patches is performed. It confirms the importance of reinforcing the electrodes equipotentiality condition in the finite element model. Its results indicate also that smaller (segmented) and independent piezoelectric patches could be more interesting for energy conversion efficiency. Then, parametric analyses and optimization are performed for a cantilever sandwich beam with several embedded shear piezoceramic patches. Results indicate that to fully benefit from the higher material coupling of shear piezoceramic patches, attention must be paid to the configuration design so that the shear strains in the patches are maximized. In particular, effective square EMCC values higher than 1% were obtained embedding nine well-spaced short piezoceramic patches in an aluminum/foam/aluminum sandwich beam.