From Sample Processing to Quantification: A Full Electrochemical Approach for Neutral Analyte Derivatization, Capillary Electrophoresis Separation, and Contactless Conductivity Detection

A thin-layer electrochemical flow cell coupled to capillary electrophoresis with contactless conductivity detection (EC-CE-(CD)-D-4) was applied for the first time to the derivatization and quantification of neutral species using aliphatic alcohols as model compounds. The simultaneous electrooxidation of four alcohols (ethanol, 1-propanol, 1-butanol, and 1-pentanol) to the corresponding carboxylates was carried out on a platinum working electrode in acid medium. The derivatization step required 1 min at 1.6 V vs. Ag/AgCl under stopped flow conditions, which was preceded by a 10 s activation at 0 V. The solution close to the electrode surface was then hydrodynamically injected into the capillary, and a 2.5 min electrophoretic separation was carried out. The fully automated flow system operated at a frequency of 12 analyses per hour. Simultaneous determination of the four alcohols presented detection limits of about 5 x 10(-5) mol As a practical application with a complex matrix, ethanol concentrations were determined in diluted pale lager beer and in nonalcoholic beer. No statistically significant difference was observed between the EC-CE-(CD)-D-4 and gas chromatography with flame ionization detection (GC-FID) results for these samples. The derivatization efficiency remained constant over several hours of continuous operation with lager beer samples (n = 40).

THE CARE NEEDS OF WOMEN INFECTED WITH THE HUMAN PAPILLOMA VIRUS: A COMPREHENSIVE APPROACH

This study is founded on the phenomenology of Martin Heidegger, with the objective to understand the care needs of women infected with the human papilloma virus. Participants were fourteen women who had been diagnosed with this infection. The guiding questions were: What is it like to have this diagnosis? Tell me your experience, from when you received your diagnosis until today. What has your health care been like? The questions revealed the theme - seeking care as solicitude - which showed the importance of the support of family and friends. The presence of the infection as the cause of marital conflicts and separation was another highlighted aspect. The statements showed that there was a sense of resignation after an unsuccessful attempt to find accurate and clear information in order to make assertive decisions. Health interventions for infected women must overcome the traditional models of care, including interventions for health promotion and prevention, with trained professionals who are sensitive to the subjective dimension.

Peptide fingerprinting of the neurotoxic fractions isolated from the secretions of sea anemones Stichodactyla helianthus and Bunodosoma granulifera. New members of the APETx-like family identified by a 454 pyrosequencing approach

Sea anemones are known to contain a wide diversity of biologically active peptides, mostly unexplored according to recent peptidomic and transcriptomic studies. In the present work, the neurotoxic fractions from the exudates of Stichodactyla helianthus and Bunodosoma granulifera were analyzed by reversed-phase chromatography and mass spectrometry. The first peptide fingerprints of these sea anemones were assessed, revealing the largest number of peptide components (156) so far found in sea anemone species, as well as the richer peptide diversity of B. granulifera in relation to S. helianthus. The transcriptomic analysis of B. granulifera, performed by massive cDNA sequencing with 454 pyrosequencing approach allowed the discovery of five new APETx-like peptides (U-AITX-Bg1a-e - including the full sequences of their precursors for four of them), which together with type 1 sea anemone sodium channel toxins constitute a very distinguishable feature of studied sea anemone species belonging to genus Bunodosoma. The molecular modeling of these new APETx-like peptides showed a distribution of positively charged and aromatic residues in putative contact surfaces as observed in other animal toxins. On the other hand, they also showed variable electrostatic potentials, thus suggesting a docking onto their targeted channels in different spatial orientations. Moreover several crab paralyzing toxins (other than U-AITX-Bg1a-e), which induce a variety of symptoms in crabs, were isolated. Some of them presumably belong to new classes of crab-paralyzing peptide toxins, especially those with molecular masses below 2 kDa, which represent the smallest peptide toxins found in sea anemones. (C) 2011 Elsevier Inc. All rights reserved.

An integrated approach to evaluate emerging contaminants in drinking water

The chemical stock of emerging contaminants in Brazilian drinking water is of great interest due to the poor water quality at surface water intakes. In addition, little is known about the effect of some contaminants, such as endocrine disrupting chemicals (EDCs), which may be present in both raw and treated water. The aim of this work was to evaluate selected emerging contaminants in Brazilian waters using both chemical and biological analyses. Sampling sites were established in different municipalities based upon raw water quality data. Estrone, 17 beta-estradiol, estriol, 17 alpha-ethinylestradiol, bisphenol A, 4-n-octylphenol and 4-n-nonylphenol were determined in the samples by liquid chromatography-tandem mass spectrometry. A yeast assay using a Saccharomyces cerevisiae bioluminescent bioreporter was used to evaluate the estrogenic activity of the water samples. The first integrated results revealed similarities between the two individual approaches, since higher values for the bioassay were accompanied by significant concentrations of some selected compounds in surface water samples. No estrogenicity was observed for drinking water samples. Our results also indicate that the usual paradigm of evaluating water quality by measuring selected EDCs in a given water sample via chemical analysis, needs to be reviewed since the observed estrogenicity of a water sample is now a better guiding parameter to the selection of samples and substances to be chemically investigated in further analysis. So far, the data bank produced in this work, i.e., the comparison between chemical burden and observed estrogenicity, is not yet sufficiently robust to fully guide this decision. (C) 2011 Elsevier B.V. All rights reserved.

Prediction of tolerance in children with IgE mediated cow's milk allergy by microarray profiling and chemometric approach

The sera of a retrospective cohort (n = 41) composed of children with well characterized cow's milk allergy collected from multiple visits were analyzed using a protein microarray system measuring four classes of immunoglobulins. The frequency of the visits, age and gender distribution reflected real situation faced by the clinicians at a pediatric reference center for food allergy in 530 Paulo, Brazil. The profiling array results have shown that total IgG and IgA share similar specificity whilst IgM and in particular IgE are distantly related. The correlation of specificity of IgE and IgA is variable amongst the patients and this relationship cannot be used to predict atopy or the onset of tolerance to milk. The array profiling technique has corroborated the clinical selection criteria for this cohort albeit it clearly suggested that 4 out of the 41 patients might have allergies other than milk origin. There was also a good correlation between the array data and ImmunoCAP results, casein in particular. By using qualitative and quantitative multivariate analysis routines it was possible to produce validated statistical models to predict with reasonable accuracy the onset of tolerance to milk proteins. If expanded to larger study groups, the array profiling in combination with the multivariate techniques show potential to improve the prognostic of milk allergic patients. (C) 2012 Elsevier B.V. All rights reserved.

A feature selection approach for identification of signature genes from SAGE data

Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS) or the recent Sequencing-By-Synthesis (SBS) technique. Some of such genes identified by the proposed method may be useful to generate classifiers.

Multiobjective engineering design optimization problems: a sensitivity analysis approach

This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimization problems whose performance functions are highly susceptible to small variations in the design variables and/or design environment parameters. In both methods, the less sensitive design alternatives are preferred over others during the multiobjective optimization process. While taking the first approach, the designer chooses the design variable and/or parameter that causes uncertainties. The designer then associates a robustness index with each design alternative and adds each index as an objective function in the optimization problem. For the second approach, the designer must know, a priori, the interval of variation in the design variables or in the design environment parameters, because the designer will be accepting the interval of variation in the objective functions. The second method does not require any law of probability distribution of uncontrollable variations. Finally, the authors give two illustrative examples to highlight the contributions of the paper.

A new approach for modeling and control of nonlinear systems via norm-bounded linear differential inclusions

A systematic approach to model nonlinear systems using norm-bounded linear differential inclusions (NLDIs) is proposed in this paper. The resulting NLDI model is suitable for the application of linear control design techniques and, therefore, it is possible to fulfill certain specifications for the underlying nonlinear system, within an operating region of interest in the state-space, using a linear controller designed for this NLDI model. Hence, a procedure to design a dynamic output feedback controller for the NLDI model is also proposed in this paper. One of the main contributions of the proposed modeling and control approach is the use of the mean-value theorem to represent the nonlinear system by a linear parameter-varying model, which is then mapped into a polytopic linear differential inclusion (PLDI) within the region of interest. To avoid the combinatorial problem that is inherent of polytopic models for medium- and large-sized systems, the PLDI is transformed into an NLDI, and the whole process is carried out ensuring that all trajectories of the underlying nonlinear system are also trajectories of the resulting NLDI within the operating region of interest. Furthermore, it is also possible to choose a particular structure for the NLDI parameters to reduce the conservatism in the representation of the nonlinear system by the NLDI model, and this feature is also one important contribution of this paper. Once the NLDI representation of the nonlinear system is obtained, the paper proposes the application of a linear control design method to this representation. The design is based on quadratic Lyapunov functions and formulated as search problem over a set of bilinear matrix inequalities (BMIs), which is solved using a two-step separation procedure that maps the BMIs into a set of corresponding linear matrix inequalities. Two numerical examples are given to demonstrate the effectiveness of the proposed approach.