Using multidimensional projection techniques for reaching a high distinguishing ability in biosensing

Recent advances in the control of molecular engineering architectures have allowed unprecedented ability of molecular recognition in biosensing, with a promising impact for clinical diagnosis and environment control. The availability of large amounts of data from electrical, optical, or electrochemical measurements requires, however, sophisticated data treatment in order to optimize sensing performance. In this study, we show how an information visualization system based on projections, referred to as Projection Explorer (PEx), can be used to achieve high performance for biosensors made with nanostructured films containing immobilized antigens. As a proof of concept, various visualizations were obtained with impedance spectroscopy data from an array of sensors whose electrical response could be specific toward a given antibody (analyte) owing to molecular recognition processes. In addition to discussing the distinct methods for projection and normalization of the data, we demonstrate that an excellent distinction can be made between real samples tested positive for Chagas disease and Leishmaniasis, which could not be achieved with conventional statistical methods. Such high performance probably arose from the possibility of treating the data in the whole frequency range. Through a systematic analysis, it was inferred that Sammon`s mapping with standardization to normalize the data gives the best results, where distinction could be made of blood serum samples containing 10(-7) mg/mL of the antibody. The method inherent in PEx and the procedures for analyzing the impedance data are entirely generic and can be extended to optimize any type of sensor or biosensor.

An environmentally friendly triphasic catalytic system: Mn(salen) occluded in membranes based on PDMS/PVA

The commercially available Jacobsen catalyst, Mn(salen), was occluded in hybrid polymeric membranes based on poly(dimethylsiloxane) (PDMS) and poly(vinyl alcohol) (PVA). The obtained systems were characterized by UV-vis spectroscopy and SEM techniques. The membranes were used as a catalytic barrier between two different phases: an organic substrate phase (cyclooctene or styrene) in the absence of solvent, and an aqueous solution of either t-BuOOH or H(2)O(2). Membranes containing different percentages of PVA were prepared, in order to modulate their hydrophilic/hydrophobic swelling properties. The occluded complex proved to be an efficient catalyst for the oxidation of alkenes. The new triphasic system containing a cheap and easily available catalyst allowed substrate oxidation and easy product separation using ""green"" oxidants. (C) 2010 Elsevier B.V. All rights reserved.

EEG-based Brain-Computer Interfaces: An Overview of Basic Concepts and Clinical Applications in Neurorehabilitation

Some patients are no longer able to communicate effectively or even interact with the outside world in ways that most of us take for granted. In the most severe cases, tetraplegic or post-stroke patients are literally `locked in` their bodies, unable to exert any motor control after, for example, a spinal cord injury or a brainstem stroke, requiring alternative methods of communication and control. But we suggest that, in the near future, their brains may offer them a way out. Non-invasive electroencephalogram (EEG)-based brain-computer interfaces (BCD can be characterized by the technique used to measure brain activity and by the way that different brain signals are translated into commands that control an effector (e.g., controlling a computer cursor for word processing and accessing the internet). This review focuses on the basic concepts of EEG-based BC!, the main advances in communication, motor control restoration and the down-regulation of cortical activity, and the mirror neuron system (MNS) in the context of BCI. The latter appears to be relevant for clinical applications in the coming years, particularly for severely limited patients. Hypothetically, MNS could provide a robust way to map neural activity to behavior, representing the high-level information about goals and intentions of these patients. Non-invasive EEG-based BCIs allow brain-derived communication in patients with amyotrophic lateral sclerosis and motor control restoration in patients after spinal cord injury and stroke. Epilepsy and attention deficit and hyperactive disorder patients were able to down-regulate their cortical activity. Given the rapid progression of EEG-based BCI research over the last few years and the swift ascent of computer processing speeds and signal analysis techniques, we suggest that emerging ideas (e.g., MNS in the context of BC!) related to clinical neuro-rehabilitation of severely limited patients will generate viable clinical applications in the near future.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

Inflammatory Cytokines during Liver Transplantation: Prospective Randomized Trial Comparing Conventional and Piggyback Techniques

Background/Aims: Cytokines have a significant role in the response to injury following liver transplantation, but the origin and course of such molecules are not completely known. The aim of this study was to evaluate the production and liver metabolism of the inflammatory cytokines interleukin (IL)-1 beta, IL-6, IL-8, interferon (IFN)-Y and tumor necrosis factor (TNF)-alpha in orthotopic liver transplantation (OLT), comparing the conventional and the piggyback methods. Methodology: We performed a study of 30 patients who underwent elective OLT and were randomized for the conventional or piggyback techniques at the beginning of the operation. The amount of cytokines and their hepatic metabolism were calculated based on plasma concentrations and vascular blood flow at 2, 5, 10, 15, 30, 60, 90, and 120 minutes after revascularization. Results: The amount of IL-1 beta in portal blood was higher in patients who underwent surgery using the conventional technique (estimate interest = 63,783.9 +/- 16,586.1 pg/min, versus 11,979.6 +/- 16,585.7 pg/min in the piggyback group, p=0.035). There were no significant differences between the two operative`s methods for IL-6, IL-8, IFN-Y and TNF-alpha production. The hepatic metabolism of cytokines was not different between groups. Although all the curves showed higher amounts of cytokines with the conventional technique, these were not statistically significant. Conclusion: The study shows the similarity between the two techniques concerning the stimuli for the production of inflammatory molecules.

Kinetics of elimination and distribution in blood and liver of biocompatible ferrofluids based on Fe(3)O(4) nanoparticles: An EPR and XRF study

In this study, we evaluated the biodistribution and the elimination kinetics of a biocompatible magnetic fluid, Endorem (TM), based on dextrancoated Fe(3)O(4) nanoparticles endovenously injected into Winstar rats. The iron content in blood and liver samples was recorded using electron paramagnetic resonance (EPR) and X-ray fluorescence (XRF) techniques. The EPR line intensity at g=2.1 was found to be proportional to the concentration of magnetic nanoparticles and the best temperature for spectra acquisition was 298 K. Both EPR and XRF analysis indicated that the maximum concentration of iron in the liver occurred 95 min after the ferrofluid administration. The half-life of the magnetic nanoparticles (MNP) in the blood was (11.6 +/- 0.6) min measured by EPR and (12.6 +/- 0.6) min determined by XRF. These results indicate that both EPR and XRF are very useful and appropriate techniques for the study of kinetics of ferrofluid elimination and biodistribution after its administration into the organism. (c) 2007 Elsevier B.V. All rights reserved.

Magnetic characterization by SQUID and FMR of a biocompatible ferrofluid based on Fe(3)O(4)

Biocompatible superparamagnetic iron oxide nanoparticles of magnetite coated with dextran were magnetically characterized using the techniques of SQUID (superconducting quantum interference device) magnetometry and ferromagnetic resonance (FMR). The SQUID magnetometry characterization was performed by isothermal measurements under applied magnetic field using the methods of zero-field-cooling (ZFC) and field-cooling (FC). The magnetic behavior of the nanoparticles indicated their superparamagnetic nature and it was assumed that they consisted exclusively of monodomains. The transition to a blocked state was observed at the temperature T(B) = (43 +/- 1) K for frozen ferrofluid and at (52 +/- 1) K for the lyophilized ferrofluid samples. The FMR analysis showed that the derivative peak-to-peak linewidth (Delta H(PP)), gyromagnetic factor (g), number of spins (N(S)), and spin-spin relaxation time (T(2)) were strongly dependent on both temperature and super-exchange interaction. This information is important for possible nanotechnological applications, mainly those which are strongly dependent on the magnetic parameters.

Diagnostic model based on Raman spectra of normal, hyperplasia and prostate adenocarcinoma tissues in vitro

This study evaluated the use of Raman spectroscopy to identify the spectral differences between normal (N), benign hyperplasia (BPH) and adenocarcinoma (CaP) in fragments of prostate biopsies in vitro with the aim of developing a spectral diagnostic model for tissue classification. A dispersive Raman spectrometer was used with 830 nm wavelength and 80 mW excitation. Following Raman data collection and tissue histopathology (48 fragments diagnosed as N, 43 as BPH and 14 as CaP), two diagnostic models were developed in order to extract diagnostic information: the first using PCA and Mahalanobis analysis techniques and the second one a simplified biochemical model based on spectral features of cholesterol, collagen, smooth muscle cell and adipocyte. Spectral differences between N, BPH and CaP tissues, were observed mainly in the Raman bands associated with proteins, lipids, nucleic and amino acids. The PCA diagnostic model showed a sensitivity and specificity of 100%, which indicates the ability of PCA and Mahalanobis distance techniques to classify tissue changes in vitro. Also, it was found that the relative amount of collagen decreased while the amount of cholesterol and adipocyte increased with severity of the disease. Smooth muscle cell increased in BPH tissue. These characteristics were used for diagnostic purposes.

An MRI-based approach for the measurement of the dorsolateral prefrontal cortex in humans

The dorsolateral prefrontal cortex (DLPFC) has been implicated in the pathophysiology of mental disorders. Previous region-of-interest MRI studies that attempted to delineate this region adopted various landmarks and measurement techniques, with inconsistent results. We developed a new region-of-interest measurement method to obtain morphometric data of this region from structural MRI scans, taking into account knowledge from cytoarchitectonic postmortem studies and the large inter-individual variability of this region. MRI scans of 10 subjects were obtained, and DLPFC tracing was performed in the coronal plane by two independent raters using the semi-automated software Brains2. The intra-class correlation coefficients between two independent raters were 0.94 for the left DLPFC and 0.93 for the right DLPFC. The mean +/- S.D. DLPFC volumes were 9.23 +/- 2.35 ml for the left hemisphere and 8.20 +/- 2.08 ml for the right hemisphere. Our proposed method has high inter-rater reliability and is easy to implement, permitting the standardized measurement of this region for clinical research applications. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Specification and Evaluation of Safety Properties in a Component-Based Software Engineering Process

Over the past years, component-based software engineering has become an established paradigm in the area of complex software intensive systems. However, many techniques for analyzing these systems for critical properties currently do not make use of the component orientation. In particular, safety analysis of component-based systems is an open field of research. In this chapter we investigate the problems arising and define a set of requirements that apply when adapting the analysis of safety properties to a component-based software engineering process. Based on these requirements some important component-oriented safety evaluation approaches are examined and compared.

A new wavelet-based method for the solution of the population balance equation

A new wavelet-based method for solving population balance equations with simultaneous nucleation, growth and agglomeration is proposed, which uses wavelets to express the functions. The technique is very general, powerful and overcomes the crucial problems of numerical diffusion and stability that often characterize previous techniques in this area. It is also applicable to an arbitrary grid to control resolution and computational efficiency. The proposed technique has been tested for pure agglomeration, simultaneous nucleation and growth, and simultaneous growth and agglomeration. In all cases, the predicted and analytical particle size distributions are in excellent agreement. The presence of moving sharp fronts can be addressed without the prior investigation of the characteristics of the processes. (C) 2001 Published by Elsevier Science Ltd.

Model based procedure for scale-up of wet overflow ball mills Part 1: Outline of the methodology

Bond's method for ball mill scale-up only gives the mill power draw for a given duty. This method is incompatible with computer modelling and simulation techniques. It might not be applicable for the design of fine grinding ball mills and ball mills preceded by autogenous and semi-autogenous grinding mills. Model-based ball mill scale-up methods have not been validated using a wide range of full-scale circuit data. Their accuracy is therefore questionable. Some of these methods also need expensive pilot testing. A new ball mill scale-up procedure is developed which does not have these limitations. This procedure uses data from two laboratory tests to determine the parameters of a ball mill model. A set of scale-up criteria then scales-up these parameters. The procedure uses the scaled-up parameters to simulate the steady state performance of full-scale mill circuits. At the end of the simulation, the scale-up procedure gives the size distribution, the volumetric flowrate and the mass flowrate of all the streams in the circuit, and the mill power draw.

Incremental parsing in language-based editors: user needs and how to meet them

Incremental parsing has long been recognized as a technique of great utility in the construction of language-based editors, and correspondingly, the area currently enjoys a mature theory. Unfortunately, many practical considerations have been largely overlooked in previously published algorithms. Many user requirements for an editing system necessarily impact on the design of its incremental parser, but most approaches focus only on one: response time. This paper details an incremental parser based on LR parsing techniques and designed for use in a modeless syntax recognition editor. The nature of this editor places significant demands on the structure and quality of the document representation it uses, and hence, on the parser. The strategy presented here is novel in that both the parser and the representation it constructs are tolerant of the inevitable and frequent syntax errors that arise during editing. This is achieved by a method that differs from conventional error repair techniques, and that is more appropriate for use in an interactive context. Furthermore, the parser aims to minimize disturbance to this representation, not only to ensure other system components can operate incrementally, but also to avoid unfortunate consequences for certain user-oriented services. The algorithm is augmented with a limited form of predictive tree-building, and a technique is presented for the determination of valid symbols for menu-based insertion. Copyright (C) 2001 John Wiley & Sons, Ltd.

Aluminophosphate-based mesoporous molecular sieves: Synthesis and characterization of TAPOs

Mesoporous Ti-substituted aluminophosphates (AlPOs) with a hexagonal, cubic and lamellar pore structure, characteristic of MCM-41, MCM-48, and MCM-50, respectively, were synthesized. The stability of these mesophases upon template removal was studied. The pore structures, surface properties, and local atom environments of Al, P, and Ti of the hexagonal and cubic Ti-containing mesoporous products were extensively characterized using X-ray diffraction, magic angle spinning nuclear magnetic resonance, AAS, XPS, ultraviolet–visible, and adsorption of nitrogen and water vapor techniques while the lamellar mesophase was not further characterized due to its very poor thermal stability. Ti-containing mesoporous AlPO materials show a reasonable thermal stability upon template removal, a hydrophilic surface property, and high porosity showing application potentials in catalytic oxidation of hydrocarbons.