VCD to determine absolute configuration of natural product molecules: secolignans from Peperomia blanda

The absolute configuration and solution-state conformers of three peperomin-type secolignans isolated from Peperomia blanda (Piperaceae) are unambiguously determined by using vibrational circular dichroism (VCD) spectroscopy associated with density functional theory (DFT) calculations. Advantages of VCD over the electronic form of CD for the analysis of diastereomers are also discussed. This work extends our growing knowledge about secondary metabolites within the Piperaceae family species while providing a definitive and straightforward method to assess the absolute stereochemistry of secolignans.

Effect of a propeller duct on AUV maneuverability

A number of autonomous underwater vehicles, AUV, are equipped with commercial ducted propellers, most of them produced originally for the remote operated vehicle, ROV, industry. However, AUVs and ROVs are supposed to work quite differently since the ROV operates in almost the bollard pull condition, while the AUV works at larger cruising speeds. Moreover, they can have an influence in the maneuverability of AUV due to the lift the duct generates in the most distant place of the vehicle's center of mass. In this work, it is proposed the modeling of the hydrodynamic forces and moment on a duct propeller according to a numerical (CFD) simulation, and analytical and semi-empirical, ASE, approaches. Predicted values are compared to experimental results produced in a towing tank. Results confirm the advantages of the symbiosis between CFD and ASE methods for modeling the influence of the propeller duct in the AUV maneuverability. (C) 2012 Elsevier Ltd. All rights reserved.

Validation and comparison of two soil-vegetation-atmosphere transfer models for tropical Africa

This study aims to compare and validate two soil-vegetation-atmosphere-transfer (SVAT) schemes: TERRA-ML and the Community Land Model (CLM). Both SVAT schemes are run in standalone mode (decoupled from an atmospheric model) and forced with meteorological in-situ measurements obtained at several tropical African sites. Model performance is quantified by comparing simulated sensible and latent heat fluxes with eddy-covariance measurements. Our analysis indicates that the Community Land Model corresponds more closely to the micrometeorological observations, reflecting the advantages of the higher model complexity and physical realism. Deficiencies in TERRA-ML are addressed and its performance is improved: (1) adjusting input data (root depth) to region-specific values (tropical evergreen forest) resolves dry-season underestimation of evapotranspiration; (2) adjusting the leaf area index and albedo (depending on hard-coded model constants) resolves overestimations of both latent and sensible heat fluxes; and (3) an unrealistic flux partitioning caused by overestimated superficial water contents is reduced by adjusting the hydraulic conductivity parameterization. CLM is by default more versatile in its global application on different vegetation types and climates. On the other hand, with its lower degree of complexity, TERRA-ML is much less computationally demanding, which leads to faster calculation times in a coupled climate simulation.

Multidimensional Projections for Visual Analysis of Social Networks

Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context. Context, in its turn, is given by attributes associated with graph elements, such as individual nodes, edges, and groups of edges, as well as by the nature of the connections between individuals. In most systems, attributes of individuals and communities are not taken into consideration during graph layout, except to derive weights for force-based placement strategies. This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings. These properties are employed to layout nodes on the plane via multidimensional projection techniques. For the attribute mapping, we show that node proximity in the layout corresponds to similarity in attribute, leading to easiness in locating similar groups of nodes. The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm, reaching a meaningful layout in one pass. When a force algorithm is then applied to this initial mapping, the final layout presents better properties than conventional force-based approaches. Numerical evaluations show a number of advantages of pre-mapping points via projections. User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone. In order to allow better space usage for complex networks, a graph mapping on the surface of a sphere is also implemented.

The relationship between leaf nitrogen, nitrogen metabolites and herbivory in two species of Nyctaginaceae from the Brazilian Cerrado

Guapira graciliflora and Neea theifera are taxonomically related species of the tribe Pisoneae. Both species are found in the same environment, the Brazilian Cerrado, and therefore, are subjected to similar selective pressures. These species occur in oligotrophic environments, yet contain high concentrations of nitrogen in their leaves. The present study was carried out to investigate the ecological role of nitrogen in herbivory on these species. The differences in the N content, compositions of secondary N-metabolites, mechanical resistance, and water content between their leaves indicate that these species have different adaptations as defense mechanisms. In both species, their high nitrogen content seems to promote herbivory. The presence of secondary nitrogen metabolites does not prevent the species from suffering intense damage by herbivores on their early leaves. The herbivory rates observed were lower for mature leaves of both species than for young leaves. In G. graciliflora, nutritional content and leaf hardness are the most important variables correlated with reduction of herbivory rates, whereas in N. theifera, N compounds are also correlated with herbivory rates. Despite the differences in the strategies of these two species, they exhibit a similar efficiency of protection against natural enemies because their total herbivory rates are similar. The difference in their N defense allocation may imply benefits for survival under Cerrado conditions. We briefly discuss the oligotrophic habitat conditions of the studied plants and possible advantages of their strategies of N accumulation and metabolic uses. (C) 2011 Elsevier B.V. All rights reserved.

Emergence of sensory selection mechanisms in Artificial Life simulations

Background The evolutionary advantages of selective attention are unclear. Since the study of selective attention began, it has been suggested that the nervous system only processes the most relevant stimuli because of its limited capacity [1]. An alternative proposal is that action planning requires the inhibition of irrelevant stimuli, which forces the nervous system to limit its processing [2]. An evolutionary approach might provide additional clues to clarify the role of selective attention. Methods We developed Artificial Life simulations wherein animals were repeatedly presented two objects, "left" and "right", each of which could be "food" or "non-food." The animals' neural networks (multilayer perceptrons) had two input nodes, one for each object, and two output nodes to determine if the animal ate each of the objects. The neural networks also had a variable number of hidden nodes, which determined whether or not it had enough capacity to process both stimuli (Table 1). The evolutionary relevance of the left and the right food objects could also vary depending on how much the animal's fitness was increased when ingesting them (Table 1). We compared sensory processing in animals with or without limited capacity, which evolved in simulations in which the objects had the same or different relevances. Table 1. Nine sets of simulations were performed, varying the values of food objects and the number of hidden nodes in the neural networks. The values of left and right food were swapped during the second half of the simulations. Non-food objects were always worth -3. The evolution of neural networks was simulated by a simple genetic algorithm. Fitness was a function of the number of food and non-food objects each animal ate and the chromosomes determined the node biases and synaptic weights. During each simulation, 10 populations of 20 individuals each evolved in parallel for 20,000 generations, then the relevance of food objects was swapped and the simulation was run again for another 20,000 generations. The neural networks were evaluated by their ability to identify the two objects correctly. The detectability (d') for the left and the right objects was calculated using Signal Detection Theory [3]. Results and conclusion When both stimuli were equally relevant, networks with two hidden nodes only processed one stimulus and ignored the other. With four or eight hidden nodes, they could correctly identify both stimuli. When the stimuli had different relevances, the d' for the most relevant stimulus was higher than the d' for the least relevant stimulus, even when the networks had four or eight hidden nodes. We conclude that selection mechanisms arose in our simulations depending not only on the size of the neuron networks but also on the stimuli's relevance for action.

Narrowing the gap of personalized medicine in emerging countries: the case of multiple endocrine neoplasias in Brazil

The finished version of the human genome sequence was completed in 2003, and this event initiated a revolution in medical practice, which is usually referred to as the age of genomic or personalized medicine. Genomic medicine aims to be predictive, personalized, preventive, and also participative (4Ps). It offers a new approach to several pathological conditions, although its impact so far has been more evident in mendelian diseases. This article briefly reviews the potential advantages of this approach, and also some issues that may arise in the attempt to apply the accumulated knowledge from genomic medicine to clinical practice in emerging countries. The advantages of applying genomic medicine into clinical practice are obvious, enabling prediction, prevention, and early diagnosis and treatment of several genetic disorders. However, there are also some issues, such as those related to: (a) the need for approval of a law equivalent to the Genetic Information Nondiscrimination Act, which was approved in 2008 in the USA; (b) the need for private and public funding for genetics and genomics; (c) the need for development of innovative healthcare systems that may substantially cut costs (e.g. costs of periodic medical followup); (d) the need for new graduate and postgraduate curricula in which genomic medicine is emphasized; and (e) the need to adequately inform the population and possible consumers of genetic testing, with reference to the basic aspects of genomic medicine.

A contribution for developing more efficient dynamic modelling algorithms of parallel robots

Parallel kinematic structures are considered very adequate architectures for positioning and orienti ng the tools of robotic mechanisms. However, developing dynamic models for this kind of systems is sometimes a difficult task. In fact, the direct application of traditional methods of robotics, for modelling and analysing such systems, usually does not lead to efficient and systematic algorithms. This work addre sses this issue: to present a modular approach to generate the dynamic model and through some convenient modifications, how we can make these methods more applicable to parallel structures as well. Kane’s formulati on to obtain the dynamic equations is shown to be one of the easiest ways to deal with redundant coordinates and kinematic constraints, so that a suitable c hoice of a set of coordinates allows the remaining of the modelling procedure to be computer aided. The advantages of this approach are discussed in the modelling of a 3-dof parallel asymmetric mechanisms.

Electrogeneration of platinum nanoparticles in a matrix of dendrimer-carbon nanotubes

Hybrid materials with enhanced properties can now be obtained by combining nanomaterials such as carbon nanotubes and metallic nanoparticles, where the main challenge is to control fabrication conditions. In this study, we demonstrate that platinum nanoparticles (PtNps) can be electrogenerated within layer-by-layer (LbL) films of polyamidoamine (PAMAM) dendrimers and single-walled carbon nanotubes (SWCNTs), which serve as stabilizing matrices. The advantages of the possible control through electrogeneration were demonstrated with a homogeneous distribution of PtNps over the entire surface of the PAMAM/SWCNT LbL films, whose electroactive sites could be mapped using magnetic force microscopy. The Pt-containing films were used as catalysts for hydrogen peroxide reduction, with a decrease in the reduction potential of 60 mV compared to a Pt film deposited onto bare ITO. By analyzing the mechanisms responsible for hydrogen peroxide reduction, we ascribed the enhanced catalytic activity to synergistic effects between platinum and carbon in the LbL films, which are promising for sensing and fuel cell applications.

Improved ground motion intensity measures for reliability-based demand analysis of structures

In Performance-Based Earthquake Engineering (PBEE), evaluating the seismic performance (or seismic risk) of a structure at a designed site has gained major attention, especially in the past decade. One of the objectives in PBEE is to quantify the seismic reliability of a structure (due to the future random earthquakes) at a site. For that purpose, Probabilistic Seismic Demand Analysis (PSDA) is utilized as a tool to estimate the Mean Annual Frequency (MAF) of exceeding a specified value of a structural Engineering Demand Parameter (EDP). This dissertation focuses mainly on applying an average of a certain number of spectral acceleration ordinates in a certain interval of periods, Sa,avg (T1,…,Tn), as scalar ground motion Intensity Measure (IM) when assessing the seismic performance of inelastic structures. Since the interval of periods where computing Sa,avg is related to the more or less influence of higher vibration modes on the inelastic response, it is appropriate to speak about improved IMs. The results using these improved IMs are compared with a conventional elastic-based scalar IMs (e.g., pseudo spectral acceleration, Sa ( T(¹)), or peak ground acceleration, PGA) and the advanced inelastic-based scalar IM (i.e., inelastic spectral displacement, Sdi). The advantages of applying improved IMs are: (i ) "computability" of the seismic hazard according to traditional Probabilistic Seismic Hazard Analysis (PSHA), because ground motion prediction models are already available for Sa (Ti), and hence it is possibile to employ existing models to assess hazard in terms of Sa,avg, and (ii ) "efficiency" or smaller variability of structural response, which was minimized to assess the optimal range to compute Sa,avg. More work is needed to assess also "sufficiency" and "scaling robustness" desirable properties, which are disregarded in this dissertation. However, for ordinary records (i.e., with no pulse like effects), using the improved IMs is found to be more accurate than using the elastic- and inelastic-based IMs. For structural demands that are dominated by the first mode of vibration, using Sa,avg can be negligible relative to the conventionally-used Sa (T(¹)) and the advanced Sdi. For structural demands with sign.cant higher-mode contribution, an improved scalar IM that incorporates higher modes needs to be utilized. In order to fully understand the influence of the IM on the seismis risk, a simplified closed-form expression for the probability of exceeding a limit state capacity was chosen as a reliability measure under seismic excitations and implemented for Reinforced Concrete (RC) frame structures. This closed-form expression is partuclarly useful for seismic assessment and design of structures, taking into account the uncertainty in the generic variables, structural "demand" and "capacity" as well as the uncertainty in seismic excitations. The assumed framework employs nonlinear Incremental Dynamic Analysis (IDA) procedures in order to estimate variability in the response of the structure (demand) to seismic excitations, conditioned to IM. The estimation of the seismic risk using the simplified closed-form expression is affected by IM, because the final seismic risk is not constant, but with the same order of magnitude. Possible reasons concern the non-linear model assumed, or the insufficiency of the selected IM. Since it is impossibile to state what is the "real" probability of exceeding a limit state looking the total risk, the only way is represented by the optimization of the desirable properties of an IM.

Comparison of the meccano method with standard mesh generation techniques

[EN]The meccano method is a novel and promising mesh generation technique for simultaneously creating adaptive tetrahedral meshes and volume parameterizations of a complex solid. The method combines several former procedures: a mapping from the meccano boundary to the solid surface, a 3-D local refinement algorithm and a simultaneous mesh untangling and smoothing. In this paper we present the main advantages of our method against other standard mesh generation techniques. We show that our method constructs meshes that can be locally refined by using the Kossaczky bisection rule and maintaining a high mesh quality. Finally, we generate volume T-mesh for isogeometric analysis, based on the volume parameterization obtained by the method…

Analytical challenges in the fields of Nanobioscience and Nanobiotecnology: integrated methods for separation and characterization

Nano(bio)science and nano(bio)technology play a growing and tremendous interest both on academic and industrial aspects. They are undergoing rapid developments on many fronts such as genomics, proteomics, system biology, and medical applications. However, the lack of characterization tools for nano(bio)systems is currently considered as a major limiting factor to the final establishment of nano(bio)technologies. Flow Field-Flow Fractionation (FlFFF) is a separation technique that is definitely emerging in the bioanalytical field, and the number of applications on nano(bio)analytes such as high molar-mass proteins and protein complexes, sub-cellular units, viruses, and functionalized nanoparticles is constantly increasing. This can be ascribed to the intrinsic advantages of FlFFF for the separation of nano(bio)analytes. FlFFF is ideally suited to separate particles over a broad size range (1 nm-1 μm) according to their hydrodynamic radius (rh). The fractionation is carried out in an empty channel by a flow stream of a mobile phase of any composition. For these reasons, fractionation is developed without surface interaction of the analyte with packing or gel media, and there is no stationary phase able to induce mechanical or shear stress on nanosized analytes, which are for these reasons kept in their native state. Characterization of nano(bio)analytes is made possible after fractionation by interfacing the FlFFF system with detection techniques for morphological, optical or mass characterization. For instance, FlFFF coupling with multi-angle light scattering (MALS) detection allows for absolute molecular weight and size determination, and mass spectrometry has made FlFFF enter the field of proteomics. Potentialities of FlFFF couplings with multi-detection systems are discussed in the first section of this dissertation. The second and the third sections are dedicated to new methods that have been developed for the analysis and characterization of different samples of interest in the fields of diagnostics, pharmaceutics, and nanomedicine. The second section focuses on biological samples such as protein complexes and protein aggregates. In particular it focuses on FlFFF methods developed to give new insights into: a) chemical composition and morphological features of blood serum lipoprotein classes, b) time-dependent aggregation pattern of the amyloid protein Aβ1-42, and c) aggregation state of antibody therapeutics in their formulation buffers. The third section is dedicated to the analysis and characterization of structured nanoparticles designed for nanomedicine applications. The discussed results indicate that FlFFF with on-line MALS and fluorescence detection (FD) may become the unparallel methodology for the analysis and characterization of new, structured, fluorescent nanomaterials.

Development of muliplexed analytical methods based on bioluminescent whole-cell biosensors

The subject of this Ph.D. research thesis is the development and application of multiplexed analytical methods based on bioluminescent whole-cell biosensors. One of the main goals of analytical chemistry is multianalyte testing in which two or more analytes are measured simultaneously in a single assay. The advantages of multianalyte testing are work simplification, high throughput, and reduction in the overall cost per test. The availability of multiplexed portable analytical systems is of particular interest for on-field analysis of clinical, environmental or food samples as well as for the drug discovery process. To allow highly sensitive and selective analysis, these devices should combine biospecific molecular recognition with ultrasensitive detection systems. To address the current need for rapid, highly sensitive and inexpensive devices for obtaining more data from each sample,genetically engineered whole-cell biosensors as biospecific recognition element were combined with ultrasensitive bioluminescence detection techniques. Genetically engineered cell-based sensing systems were obtained by introducing into bacterial, yeast or mammalian cells a vector expressing a reporter protein whose expression is controlled by regulatory proteins and promoter sequences. The regulatory protein is able to recognize the presence of the analyte (e.g., compounds with hormone-like activity, heavy metals…) and to consequently activate the expression of the reporter protein that can be readily measured and directly related to the analyte bioavailable concentration in the sample. Bioluminescence represents the ideal detection principle for miniaturized analytical devices and multiplexed assays thanks to high detectability in small sample volumes allowing an accurate signal localization and quantification. In the first chapter of this dissertation is discussed the obtainment of improved bioluminescent proteins emitting at different wavelenghts, in term of increased thermostability, enhanced emission decay kinetic and spectral resolution. The second chapter is mainly focused on the use of these proteins in the development of whole-cell based assay with improved analytical performance. In particular since the main drawback of whole-cell biosensors is the high variability of their analyte specific response mainly caused by variations in cell viability due to aspecific effects of the sample’s matrix, an additional bioluminescent reporter has been introduced to correct the analytical response thus increasing the robustness of the bioassays. The feasibility of using a combination of two or more bioluminescent proteins for obtaining biosensors with internal signal correction or for the simultaneous detection of multiple analytes has been demonstrated by developing a dual reporter yeast based biosensor for androgenic activity measurement and a triple reporter mammalian cell-based biosensor for the simultaneous monitoring of two CYP450 enzymes activation, involved in cholesterol degradation, with the use of two spectrally resolved intracellular luciferases and a secreted luciferase as a control for cells viability. In the third chapter is presented the development of a portable multianalyte detection system. In order to develop a portable system that can be used also outside the laboratory environment even by non skilled personnel, cells have been immobilized into a new biocompatible and transparent polymeric matrix within a modified clear bottom black 384 -well microtiter plate to obtain a bioluminescent cell array. The cell array was placed in contact with a portable charge-coupled device (CCD) light sensor able to localize and quantify the luminescent signal produced by different bioluminescent whole-cell biosensors. This multiplexed biosensing platform containing whole-cell biosensors was successfully used to measure the overall toxicity of a given sample as well as to obtain dose response curves for heavy metals and to detect hormonal activity in clinical samples (PCT/IB2010/050625: “Portable device based on immobilized cells for the detection of analytes.” Michelini E, Roda A, Dolci LS, Mezzanotte L, Cevenini L , 2010). At the end of the dissertation some future development steps are also discussed in order to develop a point of care (POCT) device that combine portability, minimum sample pre-treatment and highly sensitive multiplexed assays in a short assay time. In this POCT perspective, field-flow fractionation (FFF) techniques, in particular gravitational variant (GrFFF) that exploit the earth gravitational field to structure the separation, have been investigated for cells fractionation, characterization and isolation. Thanks to the simplicity of its equipment, amenable to miniaturization, the GrFFF techniques appears to be particularly suited for its implementation in POCT devices and may be used as pre-analytical integrated module to be applied directly to drive target analytes of raw samples to the modules where biospecifc recognition reactions based on ultrasensitive bioluminescence detection occurs, providing an increase in overall analytical output.

Dynamic identification of structures: experimental assessment of modal parameteres through methods in frequency domain, in time-frequency domain and model updating

Among the experimental methods commonly used to define the behaviour of a full scale system, dynamic tests are the most complete and efficient procedures. A dynamic test is an experimental process, which would define a set of characteristic parameters of the dynamic behaviour of the system, such as natural frequencies of the structure, mode shapes and the corresponding modal damping values associated. An assessment of these modal characteristics can be used both to verify the theoretical assumptions of the project, to monitor the performance of the structural system during its operational use. The thesis is structured in the following chapters: The first introductive chapter recalls some basic notions of dynamics of structure, focusing the discussion on the problem of systems with multiply degrees of freedom (MDOF), which can represent a generic real system under study, when it is excited with harmonic force or in free vibration. The second chapter is entirely centred on to the problem of dynamic identification process of a structure, if it is subjected to an experimental test in forced vibrations. It first describes the construction of FRF through classical FFT of the recorded signal. A different method, also in the frequency domain, is subsequently introduced; it allows accurately to compute the FRF using the geometric characteristics of the ellipse that represents the direct input-output comparison. The two methods are compared and then the attention is focused on some advantages of the proposed methodology. The third chapter focuses on the study of real structures when they are subjected to experimental test, where the force is not known, like in an ambient or impact test. In this analysis we decided to use the CWT, which allows a simultaneous investigation in the time and frequency domain of a generic signal x(t). The CWT is first introduced to process free oscillations, with excellent results both in terms of frequencies, dampings and vibration modes. The application in the case of ambient vibrations defines accurate modal parameters of the system, although on the damping some important observations should be made. The fourth chapter is still on the problem of post processing data acquired after a vibration test, but this time through the application of discrete wavelet transform (DWT). In the first part the results obtained by the DWT are compared with those obtained by the application of CWT. Particular attention is given to the use of DWT as a tool for filtering the recorded signal, in fact in case of ambient vibrations the signals are often affected by the presence of a significant level of noise. The fifth chapter focuses on another important aspect of the identification process: the model updating. In this chapter, starting from the modal parameters obtained from some environmental vibration tests, performed by the University of Porto in 2008 and the University of Sheffild on the Humber Bridge in England, a FE model of the bridge is defined, in order to define what type of model is able to capture more accurately the real dynamic behaviour of the bridge. The sixth chapter outlines the necessary conclusions of the presented research. They concern the application of a method in the frequency domain in order to evaluate the modal parameters of a structure and its advantages, the advantages in applying a procedure based on the use of wavelet transforms in the process of identification in tests with unknown input and finally the problem of 3D modeling of systems with many degrees of freedom and with different types of uncertainty.

A hybrid technology for parallel recording of single ion channels

Hybrid technologies, thanks to the convergence of integrated microelectronic devices and new class of microfluidic structures could open new perspectives to the way how nanoscale events are discovered, monitored and controlled. The key point of this thesis is to evaluate the impact of such an approach into applications of ion-channel High Throughput Screening (HTS)platforms. This approach offers promising opportunities for the development of new classes of sensitive, reliable and cheap sensors. There are numerous advantages of embedding microelectronic readout structures strictly coupled to sensing elements. On the one hand the signal-to-noise-ratio is increased as a result of scaling. On the other, the readout miniaturization allows organization of sensors into arrays, increasing the capability of the platform in terms of number of acquired data, as required in the HTS approach, to improve sensing accuracy and reliabiity. However, accurate interface design is required to establish efficient communication between ionic-based and electronic-based signals. The work made in this thesis will show a first example of a complete parallel readout system with single ion channel resolution, using a compact and scalable hybrid architecture suitable to be interfaced to large array of sensors, ensuring simultaneous signal recording and smart control of the signal-to-noise ratio and bandwidth trade off. More specifically, an array of microfluidic polymer structures, hosting artificial lipid bilayers blocks where single ion channel pores are embededed, is coupled with an array of ultra-low noise current amplifiers for signal amplification and data processing. As demonstrating working example, the platform was used to acquire ultra small currents derived by single non-covalent molecular binding between alpha-hemolysin pores and beta-cyclodextrin molecules in artificial lipid membranes.