Piezoelectric biosensors for real-time monitoring of hybridization and detection of hepatitis C virus

The piezoelectric quartz crystal resonators modified with oligonucleotide probes were used for detection of hepatitis C virus (HCV) in serum. The gold electrodes on either rough or smooth surface crystals were modified with a self-assembled monolayer of cystamine. After activation with glutaraldehyde, either avidin or streptavidin were immobilized and used for attachment of biotinylated DNA probes (four different sequences). Piezoelectric biosensors were used in a flow-through setup for direct monitoring of DNA resulting from the reverse transcriptase-linked polymerase chain reaction (RT-PCR) amplification of the original viral RNA. The samples of patients with hepatitis C were analyzed and the results were compared with the standard RT-PCR procedure (Amplicor test kit of Roche, microwell format with spectrophotometric evaluation). The piezoelectric hybridization assay was completed in 10 min and the same sensing surface was suitable for repeated use. (C) 2004 Elsevier B.V. All rights reserved.

Adsorption and detection of DNA dendrimers at carbon electrodes

Dendritic nucleic acids are highly branched and ordered molecular structures, possessing numerous single-stranded oligonucleotide arms, which hold great promise for enhancing the sensitivity of DNA biosensors. This article evaluates the interfacial behavior and redox activity of nucleic acid dendrimers at carbon paste electrodes, in comparison to DNA. Factors influencing the adsorption behavior, including the adsorption potential and time, solution conditions, or dendrimer concentration, are explored. The strong adsorption at the anodically pretreated carbon surface is exploited for an effective preconcentration step prior to the chronopotentiometric measurement of the surface species. Coupled with the numerous guanine oxidation sites, such stripping protocol offers remarkably low detection limits (e.g., 3 pM or 2.4 femtomole of the I-layer dendrimer following a 15 min accumulation). The new observations bear important implications upon future biosensing applications of nucleic dendrimers.

Non-destructive evaluation tool for monitoring and detection of structural damage by using neural network.

This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

Occurrence of coagulase-positive Staphylococcus in various food products commercialized in Botucatu, SP, Brazil and detection of toxins from food and isolated strains

The aim of this work was to assess the microbiological quality of commercialized desserts, sandwiches and finger food in Botucatu, SP, for human consumption. A total of 172 food samples were analyzed for fecal coliforms and coagulase-positive Staphylococcus and 69 (40.1%) were in disagreement with the standards established by Decree No. 12 (Brazilian Food Sanitation Standard, 2001). Coagulase-positive Staplylococcus was isolated from 26 (15.1%) samples. Toxins were not isolated directly from foods but 27 (54%) coagulase-positive Staphylococcus strains were enterotoxigenic, and toxin type C was the most frequently detected. These results suggest that these products may act as an important vehicle of transmission for well-established pathogens. (c) 2006 Elsevier Ltd. All rights reserved.

Histopathological findings and detection of parasites in the eyes of dogs infected naturally with Leishmania chagasi

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

So(2,1) Lie algebra and the Green's functions for the conditionally exactly solvable potentials

The Green's functions of the recently discovered conditionally exactly solvable potentials are computed. This is done through the use of a second-order differential realization of the so(2,1) Lie algebra. So we present the dynamical symmetry underlying the solvability of such potentials and show that they belong to a general class of solvable and partially solvable potentials. © 1994 The American Physical Society.

Harmonics filtering and detection of disturbances using wavelets

Traditional mathematical tools, like Fourier Analysis, have proven to be efficient when analyzing steady-state distortions; however, the growing utilization of electronically controlled loads and the generation of a new dynamics in industrial environments signals have suggested the need of a powerful tool to perform the analysis of non-stationary distortions, overcoming limitations of frequency techniques. Wavelet Theory provides a new approach to harmonic analysis, focusing the decomposition of a signal into non-sinusoidal components, which are translated and scaled in time, generating a time-frequency basis. The correct choice of the waveshape to be used in decomposition is very important and discussed in this work. A brief theoretical introduction on Wavelet Transform is presented and some cases (practical and simulated) are discussed. Distortions commonly found in industrial environments, such as the current waveform of a Switched-Mode Power Supply and the input phase voltage waveform of motor fed by inverter are analyzed using Wavelet Theory. Applications such as extracting the fundamental frequency of a non-sinusoidal current signal, or using the ability of compact representation to detect non-repetitive disturbances are presented.

Surface-enhanced Raman scattering (SERS) applied to cancer diagnosis and detection of pesticides, explosives, and drugs

The inelastic scattering of light, Raman scattering, presents a very low cross section. However, the signal can be amplified by several orders of magnitude, leading to the so-called surface-enhanced Raman scattering (SERS) phenomenon. Basically, the SERS effect is achieved when the target molecule (analyte) is adsorbed onto metallic nanoparticles, usually noble metals. This article presents an overview of the applications of SERS to cancer diagnosis and the detection of pesticides, explosives, and drugs (illicit and pharmacological). SERS is routinely applied nowadays to detect and identify analytes at very low concentrations, including for single-molecule detection. However, the application of SERS as an analytical tool requires reliable and reproducible SERS substrates, in terms of enhancement factors, which depends on the size, shape, and aggregation of the metallic nanoparticles. Therefore, the production of reliable and reproducible SERS substrates is a challenge in the field. Besides, the metallic nanoparticles can also induce changes in the system by possible interactions with the analyte under investigation, which must be taken into account. This review will present work in which, under certain specific experimental conditions, SERS has been analytically applied.

Controllability of control systems on complex simple lie groups and the topology of flag manifolds

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multiseries Lie groups and asymptotic modules for characterizing and solving integrable models

A multiseries integrable model (MSIM) is defined as a family of compatible flows on an infinite-dimensional Lie group of N-tuples of formal series around N given poles on the Riemann sphere. Broad classes of solutions to a MSIM are characterized through modules over rings of rational functions, called asymptotic modules. Possible ways for constructing asymptotic modules are Riemann-Hilbert and ∂̄ problems. When MSIM's are written in terms of the group coordinates, some of them can be contracted into standard integrable models involving a small number of scalar functions only. Simple contractible MSIM's corresponding to one pole, yield the Ablowitz-Kaup-Newell-Segur (AKNS) hierarchy. Two-pole contractible MSIM's are exhibited, which lead to a hierarchy of solvable systems of nonlinear differential equations consisting of (2 + 1) -dimensional evolution equations and of quite strong differential constraints. © 1989 American Institute of Physics.

Staphylococcal enterotoxins: molecular aspects and detection methods

Members of the Staphylococcus genus, especially Staphylococcus aureus, are the most common pathogens found in hospitals and in community-acquired infections. Some of their pathogenicity is associated with enzyme and toxin production. Until recently, S. aureus was the most studied species in the genus; however, in last few years, the rise of infections caused by coagulase-negative staphylococci has pointed out the need for further studies on virulence factors that have not yet been completely elucidated so as to better characterize the pathogenic potential of this group of microorganisms. Several staphylococcal species produce enterotoxins, a family of related proteins responsible for many diseases, such as the toxic-shock syndrome, septicemia and food poisoning. To this date, 23 different enterotoxin types have been identified besides toxic-shock syndrome toxin-1 (TSST-1), and they can be divided into five phylogenetic groups. The mechanism of action of these toxins includes superantigen activity and emetic properties, which can lead to biological effects of infection. Various methods can detect genes that encode enterotoxins and their production. Molecular methods are the most frequently used at present. This review article has the objective to describe aspects related to the classification, structure and regulation of enterotoxins and toxic-shock syndrome toxin-1 detection methods.

Border detection in digital images: An approach by fuzzy numbers

The purpose of this paper is to introduce a new approach for edge detection in gray shaded images. The proposed approach is based on the fuzzy number theory. The idea is to deal with the uncertainties concerning the gray shades making up the image, and thus calculate the appropriateness of the pixels in relation to an homogeneous region around them. The pixels not belonging to the region are then classified as border pixels. The results have shown that the technique is simple, computationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors. © 2007 IEEE.

Edge detection in digital images using fuzzy numbers

The purpose of this paper is to introduce a new approach for edge detection in grey shaded images. The proposed approach is based on the fuzzy number theory. The idea is to deal with the uncertainties concerning the grey shades making up the image and, thus, calculate the appropriateness of the pixels in relation to a homogeneous region around them. The pixels not belonging to the region are then classified as border pixels. The results have shown that the technique is simple, computationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors. Copyright © 2009, Inderscience Publishers.

A malware detection system inspired on the human immune system

Malicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.