Construção de um biossensor para o doseamento de ureia baseado na inibição enzimática da amidase de pseudomonas aeruginosa com recurso a um eléctrodo selectivo de iões amónio

Era objectivo do presente trabalho o desenvolvimento de um biossensor baseado na inibição da amidase de Pseudomonas aeruginosa para a quantificação de ureia em diversas amostras com recurso a um eléctrodo selectivo de iões amónio (ISE). A ureia é um poderoso inibidor do centro activo da amidase (Acilamida hidrolase EC 3.5.1.4) de Pseudomonas aeruginosa a qual catalisa a hidrólise de amidas alifáticas produzindo o ácido correspondente e amónia. O extracto celular de Pseudomonas aeruginosa L10 contendo actividade de amidase foi imobilizado em membranas de poliétersulfona modificadas (PES) e em membranas de nylon Porablot NY Plus na presença de gelatina e de glutaraldeído (GA) como agente bifuncional. Estas membranas foram posteriormente utilizadas na construção do biossensor baseado no ISE, utilizando acetamida como substrato, a reacção enzimática foi seguida medindo os iões amónio produzidos pela hidrólise da amida alifática, e a resposta do biossensor apresentada como a velocidade inicial da reacção (mV.min-1). A optimização dos parâmetros de imobilização foi efectuada de acordo com a metodologia ANOVA. Assim, a mistura de 30μL extracto celular, 2μL GA (5%) e 10 μL Gelatina 15% (p/v) foi a que conduziu a uma melhor resposta do biossensor. Efectuou-se ainda o estudo de optimização de alguns parâmetros experimentais pH e tempo de incubação em ureia, este conduziu ao valor pH=7,2 como pH óptimo de resposta do biossensor e 20 min como tempo óptimo de incubação das membranas nas soluções de ureia, sendo neste caso a resposta do biossensor dada pela diferença das respostas do biossensor antes e após incubação. A calibração do biossensor foi efectuada em soluções contendo concentrações conhecidas de ureia preparadas em tampão Tris, leite e vinho caseiro, exibindo um limite de detecção de 2,0 ×10-6 M de ureia. A incubação das membranas em hidroxilamina 2M por um período de 2h permitiu a recuperação de 70% da actividade enzimática da membrana. O biossensor apresentou uma elevada estabilidade de armazenamento por um período de 55 dias revelando uma perda de apenas 15% da sua resposta. O biossensor desenvolvido apresenta uma sensibilidade de 58,245 mV.min-1 e um tempo de resposta de aproximadamente 20s. A resposta do biossensor foi linear para concentrações de ureia presentes no vinho na gama de 4-10 μM de ureia.

Study of the Saldanha Massif (MAR, 36 degrees 34 ' N): Constrains from rock magnetic and geophysical data

We present a study of the magnetic properties of a group of basalt samples from the Saldanha Massif (Mid-Atlantic Ridge - MAR - 36degrees 33' 54" N, 33degrees 26' W), and we set out to interpret these properties in the tectono-magmatic framework of this sector of the MAR. Most samples have low magnetic anisotropy and magnetic minerals of single domain grain size, typical of rapid cooling. The thermomagnetic study mostly shows two different susceptibility peaks. The high temperature peak is related to mineralogical alteration due to heating. The low temperature peak shows a distinction between three different stages of low temperature oxidation: the presence of titanomagnetite, titanomagnetite and titanomaghemite, and exclusively of titanomaghemite. Based on established empirical relationships between Curie temperature and degree of oxidation, the latter is tentatively deduced for all samples. Finally, swath bathymetry and sidescan sonar data combined with dive observations show that the Saldanha Massif is located over an exposed section of upper mantle rocks interpreted to be the result of detachment tectonics. Basalt samples inside the detachment zone often have higher than expected oxidation rates; this effect can be explained by the higher permeability caused by the detachment fault activity.

Feature Discretization with Relevance and Mutual Information Criteria

Feature discretization (FD) techniques often yield adequate and compact representations of the data, suitable for machine learning and pattern recognition problems. These representations usually decrease the training time, yielding higher classification accuracy while allowing for humans to better understand and visualize the data, as compared to the use of the original features. This paper proposes two new FD techniques. The first one is based on the well-known Linde-Buzo-Gray quantization algorithm, coupled with a relevance criterion, being able perform unsupervised, supervised, or semi-supervised discretization. The second technique works in supervised mode, being based on the maximization of the mutual information between each discrete feature and the class label. Our experimental results on standard benchmark datasets show that these techniques scale up to high-dimensional data, attaining in many cases better accuracy than existing unsupervised and supervised FD approaches, while using fewer discretization intervals.

A MAP approach to evidence accumulation clustering

The Evidence Accumulation Clustering (EAC) paradigm is a clustering ensemble method which derives a consensus partition from a collection of base clusterings obtained using different algorithms. It collects from the partitions in the ensemble a set of pairwise observations about the co-occurrence of objects in a same cluster and it uses these co-occurrence statistics to derive a similarity matrix, referred to as co-association matrix. The Probabilistic Evidence Accumulation for Clustering Ensembles (PEACE) algorithm is a principled approach for the extraction of a consensus clustering from the observations encoded in the co-association matrix based on a probabilistic model for the co-association matrix parameterized by the unknown assignments of objects to clusters. In this paper we extend the PEACE algorithm by deriving a consensus solution according to a MAP approach with Dirichlet priors defined for the unknown probabilistic cluster assignments. In particular, we study the positive regularization effect of Dirichlet priors on the final consensus solution with both synthetic and real benchmark data.

Off-the-person electrocardiography: performance assessment and clinical correlation

Previous work by our group introduced a novel concept and sensor design for “off-the-person” ECG, for which evidence on how it compares against standard clinical-grade equipment has been largely missing. Our objectives with this work are to characterise the off-the-person approach in light of the current ECG systems landscape, and assess how the signals acquired using this simplified setup compare with clinical-grade recordings. Empirical tests have been performed with real-world data collected from a population of 38 control subjects, to analyze the correlation between both approaches. Results show off-the-person data to be correlated with clinical-grade data, demonstrating the viability of this approach to potentially extend preventive medicine practices by enabling the integration of ECG monitoring into multiple dimensions of people’s everyday lives. © 2015, IUPESM and Springer-Verlag Berlin Heidelberg.