Sarcosine oxidase composite screen-printed electrode for sarcosine determination in biological samples

As the prostate cancer (PCa) progresses, sarcosine levels increase both in tumor cells and urine samples, suggesting that this metabolite measurements can help in the creation of non-invasive diagnostic methods for this disease. In this work, a biosensor device was developed for the quantification of sarcosine via electrochemical detection of H2O2 (at 0.6 V) generated from the catalyzed oxidation of sarcosine. The detection was carried out after the modification of carbon screen printed electrodes (SPEs) by immobilization of sarcosine oxidase (SOX) on the electrode surface. The strategies used herein included the activation of the carbon films by an electrochemical step and the formation of an NHS/EDAC layer to bond the enzyme to the electrode, the use of metallic or semiconductor nanoparticles layer previously or during the enzyme immobilization. In order to improve the sensor stability and selectivity a polymeric layer with extra enzyme content was further added. The proposed methodology for the detection of sarcosine allowed obtaining a limit of detection (LOD) of 16 nM, using a linear concentration range between 10 and 100 nM. The biosensor was successfully applied to the analysis of sarcosine in urine samples.

Sarcosine oxidase composite screen-printed electrode for sarcosine determination in biological samples

XIX Meeting of the Portuguese Electrochemical Society - XVI Iberic Meeting of Electrochemistry

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamical Analysis and Visualization of Tornadoes Time Series

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Multidimensional Scaling Visualization using Parametric Similarity Indices

In this paper, we apply multidimensional scaling (MDS) and parametric similarity indices (PSI) in the analysis of complex systems (CS). Each CS is viewed as a dynamical system, exhibiting an output time-series to be interpreted as a manifestation of its behavior. We start by adopting a sliding window to sample the original data into several consecutive time periods. Second, we define a given PSI for tracking pieces of data. We then compare the windows for different values of the parameter, and we generate the corresponding MDS maps of ‘points’. Third, we use Procrustes analysis to linearly transform the MDS charts for maximum superposition and to build a global MDS map of “shapes”. This final plot captures the time evolution of the phenomena and is sensitive to the PSI adopted. The generalized correlation, the Minkowski distance and four entropy-based indices are tested. The proposed approach is applied to the Dow Jones Industrial Average stock market index and the Europe Brent Spot Price FOB time-series.

Characterization and Biological Activities of Ocellatin Peptides from the Skin Secretion of the Frog Leptodactylus pustulatus

Eight new peptides were isolated from the skin secretion of the frog Leptodactylus pustulatus and their amino acid sequences determined by de novo sequencing and by cDNA cloning. Structural similarities between them and other antimicrobial peptides from the skin secretion of Leptodactylus genus frogs were found. Ocellatins-PT1 to -PT5 (25 amino acid residues) are amidated at the C-terminus, while ocellatins-PT6 to -PT8 (32 amino acid residues) have free carboxylates. Antimicrobial activity, hemolytic tests, and cytotoxicity against a murine fibroblast cell line were investigated. All peptides, except for ocellatin-PT2, have antimicrobial activity against at least one Gram negative strain. Ocellatin-PT8 inhibited the growth of Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Salmonella choleraesuis strains with MICs in the 60−240 μM range. No significant effect was observed in human erythrocytes and in a murine fibroblast cell line after exposure to the peptides at MICs. A comparison between sequences obtained by both direct HPLC-MS de novo sequencing and cDNA cloning demonstrates the secretion of mature peptides derived from a pre-pro-peptide structure.

(Un)suitability of the use of pH buffers in biological, biochemical and environmental studies and their interaction with metal ions – a review

The use of buffers to maintain the pH within a desired range is a very common practice in chemical, biochemical and biological studies. Among them, zwitterionic N-substituted aminosulfonic acids, usually known as Good’s buffers, although widely used, can complex metals and interact with biological systems. The present work reviews, discusses and updates the metal complexation characteristics of thirty one commercially available buffers. In addition, their impact on biological systems is also presented. The influences of these buffers on the results obtained in biological, biochemical and environmental studies, with special focus on their interaction with metal ions, are highlighted and critically reviewed. Using chemical speciation simulations, based on the current knowledge of the metal–buffer stability constants, a proposal of the most adequate buffer to employ for a given metal ion is presented.

Software development for estimation of optical clearing agent’s diffusion coefficients in biological tissues

The study of chemical diffusion in biological tissues is a research field of high importance and with application in many clinical, research and industrial areas. The evaluation of diffusion and viscosity properties of chemicals in tissues is necessary to characterize treatments or inclusion of preservatives in tissues or organs for low temperature conservation. Recently, we have demonstrated experimentally that the diffusion properties and dynamic viscosity of sugars and alcohols can be evaluated from optical measurements. Our studies were performed in skeletal muscle, but our results have revealed that the same methodology can be used with other tissues and different chemicals. Considering the significant number of studies that can be made with this method, it becomes necessary to turn data processing and calculation easier. With this objective, we have developed a software application that integrates all processing and calculations, turning the researcher work easier and faster. Using the same experimental data that previously was used to estimate the diffusion and viscosity of glucose in skeletal muscle, we have repeated the calculations with the new application. Comparing between the results obtained with the new application and with previous independent routines we have demonstrated great similarity and consequently validated the application. This new tool is now available to be used in similar research to obtain the diffusion properties of other chemicals in different tissues or organs.