Electrochemical response of 70Co-30Ni highly branched 3D-dendritic structures for charge storage electrodes

A 70Co-30Ni dendritic alloy was produced on stainless steel by pulse electrodeposition in the cathodic domain, and oxidized by potential cycling. X-ray diffraction (XRD) identified the presence of two phases and scanning electron microscopy (SEM) evidenced an open 3D highly branched dendritic morphology. After potential cycling in 1 M KOH, SEM and X-ray photoelectron spectroscopy (XPS) revealed, respectively, the presence of thin nanoplates, composed of Co and Ni oxi-hydroxides and hydroxides over the original dendritic film. Cyclic voltammetry tests showd the presence of redox peaks assigned to the oxidation and reduction of Ni and Co centres in the surface film. Charge/discharge measurements revealed capacity values of 121 mAh g(1) at 1 mA cm(2). The capacity retention under 8000 cycles was above 70%, stating the good reversibility of these redox materials and its suitability to be used as charge storage electrodes. Electrochemical impedance spectroscopy (EIS) spectra, taken under different applied bias, showed that the capacitance increased when the electrode was fully oxidized and decreased when the electrode was reduced, reflecting different states-of-charge of the electrode. (C) 2015 Elsevier Ltd. All rights reserved.

Reinforcement learning in dendritic structures

The discovery of binary dendritic events such as local NMDA spikes in dendritic subbranches led to the suggestion that dendritic trees could be computationally equivalent to a 2-layer network of point neurons, with a single output unit represented by the soma, and input units represented by the dendritic branches. Although this interpretation endows a neuron with a high computational power, it is functionally not clear why nature would have preferred the dendritic solution with a single but complex neuron, as opposed to the network solution with many but simple units. We show that the dendritic solution has a distinguished advantage over the network solution when considering different learning tasks. Its key property is that the dendritic branches receive an immediate feedback from the somatic output spike, while in the corresponding network architecture the feedback would require additional backpropagating connections to the input units. Assuming a reinforcement learning scenario we formally derive a learning rule for the synaptic contacts on the individual dendritic trees which depends on the presynaptic activity, the local NMDA spikes, the somatic action potential, and a delayed reinforcement signal. We test the model for two scenarios: the learning of binary classifications and of precise spike timings. We show that the immediate feedback represented by the backpropagating action potential supplies the individual dendritic branches with enough information to efficiently adapt their synapses and to speed up the learning process.

Reinforcement learning in dendritic structures

The discovery of binary dendritic events such as local NMDA spikes in dendritic subbranches led to the suggestion that dendritic trees could be computationally equivalent to a 2-layer network of point neurons, with a single output unit represented by the soma, and input units represented by the dendritic branches. Although this interpretation endows a neuron with a high computational power, it is functionally not clear why nature would have preferred the dendritic solution with a single but complex neuron, as opposed to the network solution with many but simple units. We show that the dendritic solution has a distinguished advantage over the network solution when considering different learning tasks. Its key property is that the dendritic branches receive an immediate feedback from the somatic output spike, while in the corresponding network architecture the feedback would require additional backpropagating connections to the input units. Assuming a reinforcement learning scenario we formally derive a learning rule for the synaptic contacts on the individual dendritic trees which depends on the presynaptic activity, the local NMDA spikes, the somatic action potential, and a delayed reinforcement signal. We test the model for two scenarios: the learning of binary classifications and of precise spike timings. We show that the immediate feedback represented by the backpropagating action potential supplies the individual dendritic branches with enough information to efficiently adapt their synapses and to speed up the learning process.

Conception, synthèse et caractérisation de nouvelles macromolécules branchées biocompatibles pour encapsuler des principes actifs hydrophobes

La vectorisation des médicaments est une approche très prometteuse tant sur le plan médical qu’économique pour la livraison des substances actives ayant une faible biodisponibilité. Dans ce contexte, les polymères en étoile et les dendrimères, macromolécules symétriques et branchées, semblent être les solutions de vectorisation les plus attrayantes. En effet, ces structures peuvent combiner efficacement une stabilité élevée dans les milieux biologiques à une capacité d’encapsulation des principes actifs. Grâce à leur architecture bien définie, ils permettent d’atteindre un très haut niveau de reproductibilité de résultats, tout en évitant le problème de polydispersité. Bien que des nombreuses structures dendritiques aient été proposées ces dernières années, il est cependant à noter que la conception de nouveaux nanovecteurs dendritiques efficaces est toujours d’actualité. Ceci s’explique par des nombreuses raisons telles que celles liées à la biocompatibilité, l’efficacité d’encapsulation des agents thérapeutiques, ainsi que par des raisons économiques. Dans ce projet, de nouvelles macromolécules branchées biocompatibles ont été conçues, synthétisées et évaluées. Pour augmenter leur efficacité en tant qu’agents d’encapsulations des principes actifs hydrophobes, les structures de ces macromolécules incluent un coeur central hydrophobe à base de porphyrine, décanediol ou trioléine modifié et, également, une couche externe hydrophile à base d’acide succinique et de polyéthylène glycol. Le choix des éléments structuraux de futures dendrimères a été basé sur les données de biocompatibilité, les résultats de nos travaux de synthèse préliminaires, ainsi que les résultats de simulation in silico réalisée par une méthode de mécanique moléculaire. Ces travaux ont permis de choisir des composés les plus prometteurs pour former efficacement et d’une manière bien contrôlable des macromolécules polyesters. Ils ont aussi permis d’évaluer au préalable la capacité de futurs dendrimères de capter une molécule médicamenteuse (itraconazole). Durant cette étape, plusieurs nouveaux composés intermédiaires ont été obtenus. L’optimisation des conditions menant à des rendements réactionnels élevés a été réalisée. En se basant sur les travaux préliminaires, l’assemblage de nouveaux dendrimères de première et de deuxième génération a été effectué, en utilisant les approches de synthèse divergente et convergente. La structure de nouveaux composés a été prouvée par les techniques RMN du proton et du carbone 13C, spectroscopie FTIR, UV-Vis, analyse élémentaire, spectrométrie de masse et GPC. La biocompatibilité de produits a été évaluée par les tests de cytotoxicité avec le MTT sur les macrophages murins RAW-262.7. La capacité d’encapsuler les principes actifs hydrophobes a été étudiée par les tests avec l’itraconazole, un antifongique puissant mais peu biodisponible. La taille de nanoparticules formées dans les solutions aqueuses a été mesurée par la technique DLS. Ces mesures ont montré que toutes les structures dendritiques ont tendance à former des micelles, ce qui exclue leurs applications en tant que nanocapsules unimoléculaires. L’activité antifongique des formulations d’itraconazole encapsulé avec les dendrimères a été étudiée sur une espèce d’un champignon pathogène Candida albicans. Ces tests ont permis de conclure que pour assurer l’efficacité du traitement, un meilleur contrôle sur le relargage du principe actif était nécessaire.

Computer generation and quantitative morphometric analysis of virtual neurons

An important goal in computational neuroanatomy is the complete and accurate simulation of neuronal morphology. We are developing computational tools to model three-dimensional dendritic structures based on sets of stochastic rules. This paper reports an extensive, quantitative anatomical characterization of simulated motoneurons and Purkinje cells. We used several local and global algorithms implemented in the L-Neuron and ArborVitae programs to generate sets of virtual neurons. Parameters statistics for all algorithms were measured from experimental data, thus providing a compact and consistent description of these morphological classes. We compared the emergent anatomical features of each group of virtual neurons with those of the experimental database in order to gain insights on the plausibility of the model assumptions, potential improvements to the algorithms, and non-trivial relations among morphological parameters. Algorithms mainly based on local constraints (e.g., branch diameter) were successful in reproducing many morphological properties of both motoneurons and Purkinje cells (e.g. total length, asymmetry, number of bifurcations). The addition of global constraints (e.g., trophic factors) improved the angle-dependent emergent characteristics (average Euclidean distance from the soma to the dendritic terminations, dendritic spread). Virtual neurons systematically displayed greater anatomical variability than real cells, suggesting the need for additional constraints in the models. For several emergent anatomical properties, a specific algorithm reproduced the experimental statistics better than the others did. However, relative performances were often reversed for different anatomical properties and/or morphological classes. Thus, combining the strengths of alternative generative models could lead to comprehensive algorithms for the complete and accurate simulation of dendritic morphology.

Estudo sobre a redução aluminotérmica de Ta2O5 e TiO2 usando descarga de cátodo oco

In this study it was used two metallic oxides, Ta2O5 and TiO2, in order to obtain metallic powders of Ta and Ti through aluminothermic reduction ignited by plasma. Ta2O5 and TiO2 powders were mixed with Al in a planetary mill, using different milling times. A thermal analysis study (DTA and TG) was carried out, in order to know the temperature to react both the mixtures. Then, these mixtures were submitted to a hollow cathode discharge, where they were reacted using aluminothermic reduction ignited by plasma. The product obtained was characterized by XRD and SEM, where it was proven the possibility of producing these metallic particles, different from the conventional process, where metallic ingots are obtained. It was verified that the aluminothermic reduction ignited by plasma is able to produce metallic powders of Ta and Ti, and a higher efficiency was observed to the process with Ta2O5-Al mixtures. Among different microstructural aspects observed, it can be noted the presence of metallic nanoparticles trapped into an Al2O3 matrix, besides acicular structures (titanium) and dendritic structures (tantalum), which are a product characteristic from a fast cooling

Effect of recasting procedure upon corrosion behavior and metallic ion release of Co-Cr-Mo dental alloy in physiological

Recasting process influence upon corrosion behavior of Co-Cr-Mo dental alloy in simulated physiological serum has been investigated using chemical and electrochemical techniques. Recast Co-Cr-Mo alloy by induction (IND) or by blowtorch (FLAME) has exhibited similar dendritic structures. Both IND and FLAME alloys have presented good corrosion resistance in physiological serum. Passivation process provides this corrosion resistance. Codissolution makes this process difficult. Passive films, formed on these alloys, have been analyzed as a dual layer consisting of an inner barrier and an outer porous layer. Passive film protective characteristics are higher in FLAME than in IND alloy. On this last alloy, the passive film is more porous due to a higher Codissolution. ©Carl Hanser Verlag, München.

Semisolid microstructural evolution of AlSi7Mg alloy during partial remelting

Different as-cast microstructures of an AlSi7Mg alloy were produced by controlling the solidification conditions. The as-cast grain size ranged from 1.4 mm to 160 mum and the morphology varied from dendritic to rosette-like to globular. The as-cast materials were then partially remelted and isothermally held at 580degreesC for microstructure evolution. The final microstructure depended on the initial as-cast microstructure and the isothermal holding time. After partial remelting and isothermal holding, coarse-grained dendritic structures were not able to evolve to a globular structure, while structures with medium sized dendritic grains evolved to a globular structure with a relatively large particle size after a long isothermal holding time. Fine-grained structures evolved to well-rounded globular grains within times ranging front 10 min to 5 min as the dendritic nature of the starting structure diminished. An empirical equation has been established to describe the relationship between the evolved microstructure and the as-cast microstructure. (C) 2003 Elsevier B.V. All rights reserved.

Estudo sobre a redução aluminotérmica de Ta2O5 e TiO2 usando descarga de cátodo oco

In this study it was used two metallic oxides, Ta2O5 and TiO2, in order to obtain metallic powders of Ta and Ti through aluminothermic reduction ignited by plasma. Ta2O5 and TiO2 powders were mixed with Al in a planetary mill, using different milling times. A thermal analysis study (DTA and TG) was carried out, in order to know the temperature to react both the mixtures. Then, these mixtures were submitted to a hollow cathode discharge, where they were reacted using aluminothermic reduction ignited by plasma. The product obtained was characterized by XRD and SEM, where it was proven the possibility of producing these metallic particles, different from the conventional process, where metallic ingots are obtained. It was verified that the aluminothermic reduction ignited by plasma is able to produce metallic powders of Ta and Ti, and a higher efficiency was observed to the process with Ta2O5-Al mixtures. Among different microstructural aspects observed, it can be noted the presence of metallic nanoparticles trapped into an Al2O3 matrix, besides acicular structures (titanium) and dendritic structures (tantalum), which are a product characteristic from a fast cooling

Die Isolierung und Aufreinigung der Metalloendopeptidase LysN und die Evaluierung der Spezifität der LysN E157D-Mutante und ihr Einsatz in der Proteomik und die Mechanismen der Bildung von “dendritic cell aggresome- like induced structures“ (DALIS)

Der proteolytische Verdau von Proteinen in Peptide ist ein wichtiger Schritt in der Tandem-Massenspektrometrie. Dabei werden Peptide fragmentiert und die sich ergebenden Fragmentionen geben Aufschluss über die Aminosäuresequenz des zu untersuchenden Proteins. Dabei sind für die Fragmentierung sowohl Länge und Sequenz, als auch der Ladungszustand des Peptids ungemein wichtig. Diese Parameter bedingen sich durch Endoproteasen, die für den proteolytischen Verdau eingesetzt werden. Eine Voraussetzung hierfür ist die Spezifität der Protease. Trypsin ist bei weitem die gebräuchlichste Protease zur massenspektrometrischen Probenvorbereitung. Allerdings bietet Trypsin keine Komplettlösung. Je nach Fragestellung und Applikation müssen weitere Proteasen eingesetzt werden, um eine komplette Sequenzabdeckung zu gewährleisten und möglichst alle posttranslationalen Modifikationen nachzuweisen, oder bestimmte Proteomklassen (z.B Phosphoproteom

Effect of sialic acid loss on dendritic cell maturation

Sialic acids are key structural determinants and contribute to the functionality of a number of immune cell receptors. Previously, we demonstrated that differentiation of human dendritic cells (DCs) is accompanied by an increased expression of sialylated cell surface structures, putatively through the activity of the ST3Gal.I and ST6Gal.I sialyltransferases. Furthermore, DC endocytosis was reduced upon removal of the cell surface sialic acid residues by neuraminidase. In the present work, we evaluate the contribution of the sialic acid modifications in DC maturation. We demonstrate that neuraminidase-treated human DCs have increased expression of major histocompatibility complex (MHC) and costimulatory molecules, increased gene expression of specific cytokines and induce a higher proliferative response of T lymphocytes. Together, the data suggest that clearance of cell surface sialic acids contributes to the development of a T helper type 1 proinflammatory response. This postulate is supported by mouse models, where elevated MHC class II and increased maturation of specific DC subsets were observed in DCs harvested from ST3Gal.I(-/-) and ST6Gal.I(-/-) mice. Moreover, important qualitative differences, particularly in the extent of reduced endocytosis and in the peripheral distribution of DC subsets, existed between the ST3Gal.I(-/-) and ST6Gal.I(-/-) strains. Together, the data strongly suggest not only a role of cell surface sialic acid modifications in maturation and functionality of DCs, but also that the sialic acid linkages created by different sialyltransferases are functionally distinct. Consequently, with particular relevance to DC-based therapies, cell surface sialylation, mediated by individual sialyltransferases, can influence the immunogenicity of DCs upon antigen loading.

Alum interaction with dendritic cell membrane lipids is essential for its adjuvanticity.

As an approved vaccine adjuvant for use in humans, alum has vast health implications, but, as it is a crystal, questions remain regarding its mechanism. Furthermore, little is known about the target cells, receptors, and signaling pathways engaged by alum. Here we report that, independent of inflammasome and membrane proteins, alum binds dendritic cell (DC) plasma membrane lipids with substantial force. Subsequent lipid sorting activates an abortive phagocytic response that leads to antigen uptake. Such activated DCs, without further association with alum, show high affinity and stable binding with CD4(+) T cells via the adhesion molecules intercellular adhesion molecule-1 (ICAM-1) and lymphocyte function-associated antigen-1 (LFA-1). We propose that alum triggers DC responses by altering membrane lipid structures. This study therefore suggests an unexpected mechanism for how this crystalline structure interacts with the immune system and how the DC plasma membrane may behave as a general sensor for solid structures.

Neutrophils activate plasmacytoid dendritic cells by releasing self-DNA-peptide complexes in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a severe and incurable autoimmune disease characterized by chronic activation of plasmacytoid dendritic cells (pDCs) and production of autoantibodies against nuclear self-antigens by hyperreactive B cells. Neutrophils are also implicated in disease pathogenesis; however, the mechanisms involved are unknown. Here, we identified in the sera of SLE patients immunogenic complexes composed of neutrophil-derived antimicrobial peptides and self-DNA. These complexes were produced by activated neutrophils in the form of web-like structures known as neutrophil extracellular traps (NETs) and efficiently triggered innate pDC activation via Toll-like receptor 9 (TLR9). SLE patients were found to develop autoantibodies to both the self-DNA and antimicrobial peptides in NETs, indicating that these complexes could also serve as autoantigens to trigger B cell activation. Circulating neutrophils from SLE patients released more NETs than those from healthy donors; this was further stimulated by the antimicrobial autoantibodies, suggesting a mechanism for the chronic release of immunogenic complexes in SLE. Our data establish a link between neutrophils, pDC activation, and autoimmunity in SLE, providing new potential targets for the treatment of this devastating disease.

Self-organisation in the assembly of gels from mixtures of different dendritic peptide building blocks

This paper investigates dendritic peptides capable of assembling into nanostructured gels, and explores the effect on self-assembly of mixing different molecular building blocks. Thermal measurements, small angle Xray scattering (SAXS) and circular dichroism (CD) spectroscopy are used to probe these materials on macroscopic, nanoscopic and molecular length scales. The results from these investigations demonstrate that in this case, systems with different "size" and "chirality" factors can self-organise, whilst systems with different "shape" factors cannot. The "size" and "chirality" factors are directly connected with the molecular information programmed into the dendritic peptides, whilst the shape factor depends on the group linking these peptides together-this is consistent with molecular recognition hydrogen bond pathways between the peptidic building blocks controlling the ability of these systems to self-recognise. These results demonstrate that mixtures of relatively complex peptides, with only subtle differences on the molecular scale, can self-organise into nanoscale structures, an important step in the spontaneous assembly of ordered systems from complex mixtures.