Gold electrode modified by self-assembled monolayers of thiols to determine DNA sequences hybridization

The process of immobilization of biological molecules is one of the most important steps in the construction of a biosensor. In the case of DNA, the way it exposes its bases can result in electrochemical signals to acceptable levels. The use of self-assembled monolayer that allows a connection to the gold thiol group and DNA binding to an aldehydic ligand resulted in the possibility of determining DNA hybridization. Immobilized single strand of DNA (ssDNA) from calf thymus pre-formed from alkanethiol film was formed by incubating a solution of 2-aminoethanothiol (Cys) followed by glutaraldehyde (Glu). Cyclic voltammetry (CV) was used to characterize the self-assembled monolayer on the gold electrode and, also, to study the immobilization of ssDNA probe and hybridization with the complementary sequence (target ssDNA). The ssDNA probe presents a well-defined oxidation peak at +0.158 V. When the hybridization occurs, this peak disappears which confirms the efficacy of the annealing and the DNA double helix performing without the presence of electroactive indicators. The use of SAM resulted in a stable immobilization of the ssDNA probe, enabling the hybridization detection without labels. This study represents a promising approach for molecular biosensor with sensible and reproducible results.

Iron oxide/gold core/shell nanomagnetic probes and CdS biolabels for amplified electrochemical immunosensing of Salmonella typhimurium

There is an imminent need for rapid methods to detect and determine pathogenic bacteria in food products as alternatives to the laborious and time-consuming culture procedures. In this work, an electrochemical immunoassay using iron/gold core/shell nanoparticles (Fe@Au) conjugated with anti-Salmonella antibodies was developed. The chemical synthesis and functionalization of magnetic and gold-coated magnetic nanoparticles is reported. Fe@Au nanoparticles were functionalized with different self-assembled monolayers and characterized using ultraviolet-visible spectrometry, transmission electron microscopy, and voltammetric techniques. The determination of Salmonella typhimurium, on screen-printed carbon electrodes, was performed by square-wave anodic stripping voltammetry through the use of CdS nanocrystals. The calibration curve was established between 1×101 and 1×106 cells/mL and the limit of detection was 13 cells/mL. The developed method showed that it is possible to determine the bacteria in milk at low concentrations and is suitable for the rapid (less than 1 h) and sensitive detection of S. typhimurium in real samples. Therefore, the developed methodology could contribute to the improvement of the quality control of food samples.

Electroanalysis of urinary L-dopa using tyrosinase immobilized on gold nanoelectrode ensembles

The performance of an amperometric biosensor constructed by associating tyrosinase (Tyr) enzyme with the advantages of a 3D gold nanoelectrode ensemble (GNEE) is evaluated in a flow-injection analysis (FIA) system for the analysis of l-dopa. GNEEs were fabricated by electroless deposition of the metal within the pores of polycarbonate track-etched membranes. A simple solvent etching procedure based on the solubility of polycarbonate membranes is adopted for the fabrication of the 3D GNEE. Afterward, enzyme was immobilized onto preformed self-assembled monolayers of cysteamine on the 3D GNEEs (GNEE-Tyr) via cross-linking with glutaraldehyde. The experimental conditions of the FIA system, such as the detection potential (−0.200 V vs. Ag/AgCl) and flow rates (1.0 mL min−1) were optimized. Analytical responses for l-dopa were obtained in a wide concentration range between 1 × 10−8 mol L−1 and 1 × 10−2 mol L−1. The limit of quantification was found to be 1 × 10−8 mol L−1 with a resultant % RSD of 7.23% (n = 5). The limit of detection was found to be 1 × 10−9 mol L−1 (S/N = 3). The common interfering compounds, namely glucose (10 mmol L−1), ascorbic acid (10 mmol L−1), and urea (10 mmol L−1), were studied. The recovery of l-dopa (1 × 10−7 mol L−1) from spiked urine samples was found to be 96%. Therefore, the developed method is adequate to be applied in the clinical analysis.

Ultrasensitive detection of ovarian cancer marker using immunoliposomes and gold nanoelectrodes

Mucin-16 (MUC16) is the established ovarian cancer marker used to follow the disease during or after treatment for epithelial ovarian cancer. The emerging science of cancer markers also demands for the new sensitive detection methods. In this work, we have developed an electrochemical immunosensor for antigen MUC16 using gold nanoelectrode ensemble (GNEE) and ferrocene carboxylic acid encapsulated liposomes tethered with monoclonal anti-Mucin-16 antibodies ( MUC16). GNEEs were fabricated by electroless deposition of the gold within the pores of polycarbonate track-etched membranes. Afterwards, MUC16 were immobilized on preformed self-assembled monolayer of cysteamine on the GNEE via cross-linking with EDC-Sulfo-NHS. A sandwich immunoassay was performed on MUC16 functionalized GNEE with MUC16 and immunoliposomes. The differential pulse voltammetry was employed to quantify the faradic redox response of ferrocene carboxylic acid released from immunoliposomes. The dose–response curve for MUC16 concentration was found between the range of 0.001–300 U mL−1. The lowest detection limit was found to be 5 × 10−4 U mL−1 (S/N = 3). We evaluated the performance of this developed immunosensor with commercial ELISA assay by comparing results obtained from spiked serum samples and real blood serum samples from volunteers.

Novel biosensing device for point-of-care applications with plastic antibodies grown on Au-Screen Printed Electrodes

A gold screen printed electrode (Au-SPE) was modified by merging Molecular Imprinting and Self-Assembly Monolayer techniques for fast screening cardiac biomarkers in point-of-care (POC). For this purpose, Myoglobin (Myo) was selected as target analyte and its plastic antibody imprinted over a glutaraldehyde (Glu)/cysteamine (Cys) layer on the gold-surface. The imprinting effect was produced by growing a reticulated polymer of acrylamide (AAM) and N,N′-methylenebisacrylamide (NNMBA) around the Myo template, covalently attached to the biosensing surface. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) studies were carried out in all chemical modification steps to confirm the surface changes in the Au-SPE. The analytical features of the resulting biosensor were studied by different electrochemical techniques, including EIS, square wave voltammetry (SWV) and potentiometry. The limits of detection ranged from 0.13 to 8 μg/mL. Only potentiometry assays showed limits of detection including the cut-off Myo levels. Quantitative information was also produced for Myo concentrations ≥0.2 μg/mL. The linear response of the biosensing device showed an anionic slope of ~70 mV per decade molar concentration up to 0.3 μg/mL. The interference of coexisting species was tested and good selectivity was observed. The biosensor was successfully applied to biological fluids.

Myoglobin-biomimetic electroactive materials made by surface molecular imprinting on silica beads and their use as ionophores in polymeric membranes for potentiometric transduction

Myoglobin (Mb) is among the cardiac biomarkers playing a major role in urgent diagnosis of cardiovascular diseases. Its monitoring in point-of-care is therefore fundamental. Pursuing this goal, a novel biomimetic ionophore for the potentiometric transduction of Mb is presented. It was synthesized by surface molecular imprinting (SMI) with the purpose of developing highly efficient sensor layers for near-stereochemical recognition of Mb. The template (Mb) was imprinted on a silane surface that was covalently attached to silica beads by means of self-assembled monolayers. First the silica was modified with an external layer of aldehyde groups. Then, Mb was attached by reaction with its amine groups (on the external surface) and subsequent formation of imine bonds. The vacant places surrounding Mb were filled by polymerization of the silane monomers 3-aminopropyltrimethoxysilane (APTMS) and propyltrimethoxysilane (PTMS). Finally, the template was removed by imine cleavage after treatment with oxalic acid. The results materials were finely dispersed in plasticized PVC selective membranes and used as ionophores in potentiometric transduction. The best analytical features were found in HEPES buffer of pH 4. Under this condition, the limits of detection were of 1.3 × 10−6 mol/L for a linear response after 8.0 × 10−7 mol/L with an anionic slope of −65.9 mV/decade. The imprinting effect was tested by preparing non-imprinted (NI) particles and employing these materials as ionophores. The resulting membranes showed no ability to detect Mb. Good selectivity was observed towards creatinine, sacarose, fructose, galactose, sodium glutamate, and alanine. The analytical application was conducted successfully and showed accurate and precise results.

Self-mated tribological systems based on multilayer micro/nanocrystalline CVD diamond coatings

The tribological response of multilayer micro/nanocrystalline diamond coatings grown by the hot filament CVD technique is investigated. These multigrade systems were tailored to comprise a starting microcrystalline diamond (MCD) layer with high adhesion to a silicon nitride (Si3N4) ceramic substrate, and a top nanocrystalline diamond (NCD) layer with reduced surface roughness. Tribological tests were carried out with a reciprocating sliding configuration without lubrication. Such composite coatings exhibit a superior critical load before delamination (130–200 N), when compared to the mono- (60–100 N) and bilayer coatings (110 N), considering ∼10 µm thick films. Regarding the friction behaviour, a short-lived initial high friction coefficient was followed by low friction regimes (friction coefficients between 0.02 and 0.09) as a result of the polished surfaces tailored by the tribological solicitation. Very mild to mild wear regimes (wear coefficient values between 4.1×10−8 and 7.7×10−7 mm3 N−1 m−1) governed the wear performance of the self-mated multilayer coatings when subjected to high-load short-term tests (60–200 N; 2 h; 86 m) and medium-load endurance tests (60 N; 16 h; 691 m).

Programas de self-management em pacientes com DPOC: uma revisão sistemática

Introdução: Programas de self-management têm como objectivo habilitar os pacientes com estratégias necessárias para levar a cabo procedimentos específicos para a patologia. A última revisão sistemática sobre selfmanagament em DPOC foi realizada em 2007, concluindo-se que ainda não era possível fornecer dados claros e suficientes acerca de recomendações sobre a estrutura e conteúdo de programas de self-managament na DPOC. A presente revisão tem o intuito de complementar a análise da revisão anterior, numa tentativa de inferir a influência do ensino do self-management na DPOC. Objectivos: verificar a influência dos programas de self-management na DPOC, em diversos indicadores relacionados com o estado de saúde do paciente e na sua utilização dos serviços de saúde. Estratégia de busca: pesquisa efectuada nas bases de dados PubMed e Cochrane Collaboration (01/01/2007 – 31/08/2010). Palavras-chave: selfmanagement education, self-management program, COPD e pulmonary rehabilitation. Critérios de Selecção: estudos randomizados sobre programas de selfmanagement na DPOC. Extracção e Análise dos Dados: 2 investigadores realizaram, independentemente, a avaliação e extracção de dados de cada artigo. Resultados: foram considerados 4 estudos randomizados em selfmanagement na DPOC nos quais se verificaram benefícios destes programas em diversas variáveis: qualidade de vida a curto e médio prazo, utilização dos diferentes recursos de saúde, adesões a medicação de rotina, controle das exacerbações e diminuição da sintomatologia. Parece não ocorrer alteração na função pulmonar e no uso de medicação de emergência, sendo inconclusivo o seu efeito na capacidade de realização de exercício. Conclusões: programas de self-management aparentam ter impacto positivo na qualidade de vida, recurso a serviços de saúde, adesão à medicação, planos de acção e níveis de conhecimento da DPOC. Discrepâncias nos critérios de selecção das amostras utilizadas, períodos de seguimento desiguais, consistência das variáveis mensuradas, condicionam a informação disponibilizada sobre este assunto.

Self-optimization module for scheduling using case-based reasoning

Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.

Meta-heuristics self-configuration for scheduling

Scheduling resolution requires the intervention of highly skilled human problemsolvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. This paper addresses the resolution of complex scheduling problems using cooperative negotiation. A Multi-Agent Autonomic and Meta-heuristics based framework with self-configuring capabilities is proposed.

Self-optimization for dynamic scheduling in manufacturing systems

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

Case-based reasoning for meta-heuristics self-parameterization in a multi-agent scheduling system

A novel agent-based approach to Meta-Heuristics self-configuration is proposed in this work. Meta-heuristics are examples of algorithms where parameters need to be set up as efficient as possible in order to unsure its performance. This paper presents a learning module for self-parameterization of Meta-heuristics (MHs) in a Multi-Agent System (MAS) for resolution of scheduling problems. The learning is based on Case-based Reasoning (CBR) and two different integration approaches are proposed. A computational study is made for comparing the two CBR integration perspectives. In the end, some conclusions are reached and future work outlined.

Negotiation mechanism for self-organized scheduling system

This paper presents a negotiation mechanism for Dynamic Scheduling based on Swarm Intelligence (SI). Under the new negotiation mechanism, agents must compete to obtain a global schedule. SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviors of insects and other animals. This work is concerned with negotiation, the process through which multiple selfinterested agents can reach agreement over the exchange of operations on competitive resources.

Self-organization for scheduling in agile manufacturing

Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.