Supramolecular Approach to Gold Nanoparticle/Triruthenium Cluster Hybrid Materials and Interfaces

A systematic and comprehensive study of the interaction of citrate-stabilized gold nanoparticles with triruthenium cluster complexes of general formula [Ru(3)(CH(3)COO)(6)(L)](+) [L = 4-cyanopyridine (4-CNpy), 4,4`-bipyridine (4,4`-bpy) or 4,4`-bis(pyridyl)ethylene (bpe)] has been carried out. The cluster-nanoparticle interaction in solution and the construction of thin films of the hybrid materials were investigated in detail by electronic and surface plasmon resonance (SPR) spectroscopy, Raman scattering spectroscopy and scanning electron microscopy (SEM). Citrate-stabilized gold nanoparticles readily interacted with [Ru(3)O(CH(3)COO)(6)(L)(3)](+) complexes to generate functionalized nanoparticles that tend to aggregate according to rates and extents that depend on the bond strength defined by the characteristics of the cluster L ligands following the sequence bpe > 4,4`-bpy >> 4-CNpy. The formation of compact thin films of hybrid AuNP/[Ru(3)O(CH(3)COO)(6)(L)(3)](+) derivatives with L = bpe and 4,4`-bpy indicated that the stability/lability of AuNP-cluster bonds as well as their solubility are important parameters that influence the film contruction process. Fluorine-doped tin oxide electrodes modified with thin films of these nanomaterials exhibited similar electrocatalytic activity but much higher sensitivity than a conventional gold electrode in the oxidation of nitrite ion to nitrate depending on the bridging cluster complex, demonstrating the high potential for the development of amperometric sensors.

Micro/nanostructured carbon composite modified with a hybrid redox mediator and enzymes as a glucose biosensor

A carbon micro/nanostructured composite based on cup-stacked carbon nanotubes (CSCNTs) grown onto a carbon felt has been found to be an efficient matrix for enzyme immobilization and chemical signal transduction. The obtained CSCNT/felt was modified with a copper hexacyanoferrate/polypyrrole (CuHCNFe/Ppy) hybrid mediator, and the resulting composite electrode was applied to H(2)O(2) detection, achieving a sensitivity of 194 +/- 15 mu A mmol(-1) L. The results showed that the CSCNT/felt matrix significantly increased the sensitivity of CuHCNFe/Ppy-based sensors compared to those prepared on a felt unrecovered by CSCNTs. Our data revealed that the improved sensitivity of the as-prepared CuHCNFe/Ppy-CSCNT/felt composite electrode can be attributed to the electronic interactions taking place among the CuHCNFe nanocrystals, Ppy layer and CSCNTs. In addition, the presence of CSCNTs also seemed to favor the dispersion of CuHCNFe nanocrystals over the Ppy matrix, even though the CSCNTs were buried under the conducting polymer layer. The CSCNT/felt matrix also enabled the preparation of a glucose biosensor whose sensitivity could be tuned as a function of the number of glucose oxidase (GOx) layers deposited through a Layer-by-Layer technique with an sensitivity of 11 +/- 2 mu A mmol(-1) L achieved at 15 poly(diallyldimethylammoniumchloride)/GOx bilayers. (C) 2011 Elsevier Ltd. All rights reserved.

A hybrid case adaptation approach for case-based reasoning

Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.

Carbon nanotubes in nanostructured films: Potential application as amperometric and potentiometric field-effect (bio-)chemical sensors

The assembly of carbon nanotubes (CNTs) into nanostructured films is attractive for producing functionalized hybrid materials and (bio-)chemical sensors, but this requires experimental methods that allow for control of molecular architecturcs. In this study, we exploit the layer-by-layer (LbL) technique to obtain two types of sensors incorporating CNTs. In the first, LbL films of alternating layers of multi-walled carbon nanotubes (MWNTs) dispersed in polyarninoamide (PAMAM) dendrimers and nickel phthalocyanine (NiTsPc) were used in amperometric detection of the neurotransmitter dopamine (DA). The electrochemical properties evaluated with cyclic voltammetry indicated that the incorporation of MWNTs in the PAMAM-NT/NiTsPc LbL films led to a 3-fold increase in the peak current, in addition to a decrease of 50 mV in the oxidation potential of DA. The latter allowed detection of DA even in the presence of ascorbic acid (AA), a typical interferent for DA. Another LbL film was obtained with layers of PAMAM and single-walled carbon nanotubes (SWNTs) employed in field-effect-devices using a capacitive electrolyte-insulator-semiconductor structure (EIS). The adsorption of the film components was monitored by measuring the flat-band voltage shift in capacitance-voltage (C-P) curves, caused by the charges from the components. Constant capacitance (ConCap) measurements showed that the EISPAMAM/SWNT film displayed a high pH sensitivity (ca. 54.5 mV/pH), being capable of detecting penicillin G between 10(-4) mol L(-1) and 10(-2) mol L-1, when a layer of penicillinase was adsorbed atop the PAMAM/SWNT film. (C) 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cell-cell signal-dependent dynamic interactions between HD-GYP and GGDEF domain proteins mediate virulence in Xanthomonas campestris

RpfG is a paradigm for a class of widespread bacterial two-component regulators with a CheY-like receiver domain attached to a histidine-aspartic acid-glycine-tyrosine-proline (HD-GYP) cyclic di-GMP phosphodiesterase domain. In the plant pathogen Xanthomonas campestris pv. campestris (Xcc), a two-component system comprising RpfG and the complex sensor kinase RpfC is implicated in sensing and responding to the diffusible signaling factor (DSF), which is essential for cell-cell signaling. RpfF is involved in synthesizing DSF, and mutations of rpfF, rpfG, or rpfC lead to a coordinate reduction in the synthesis of virulence factors such as extracellular enzymes, biofilm structure, and motility. Using yeast two-hybrid analysis and fluorescence resonance energy transfer experiments in Xcc, we show that the physical interaction of RpfG with two proteins with diguanylate cyclase (GGDEF) domains controls a subset of RpfG-regulated virulence functions. RpfG interactions were abolished by alanine substitutions of the three residues of the conserved GYP motif in the HD-GYP domain. Changing the GYP motif or deletion of the two GGDEF-domain proteins reduced Xcc motility but not the synthesis of extracellular enzymes or biofilm formation. RpfG-GGDEF interactions are dynamic and depend on DSF signaling, being reduced in the rpfF mutant but restored by DSF addition. The results are consistent with a model in which DSF signal transduction controlling motility depends on a highly regulated, dynamic interaction of proteins that influence the localized expression of cyclic di-GMP.