Browsing by Author "Rocha, T."
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- Comparison of different methods of measuring similarity in physiologic time seriesPublication . Kianimajd, A.; Ruano, M G; Carvalho, P.; Henriques, J.; Rocha, T.; Paredes, S.; Ruano, AntonioSearching for similarity between time series plays an important role when large amounts of information need to be clustered to integrate intelligent supported personal health care diagnosis systems. The performance of classification, clustering and disease prediction are influenced by the prior stage where similarity between time series is performed. Physiologic signals vary even within the same patient, so an analysis of their possible variation without affecting future clustering accuracy is hereby addressed. Commonly employed methods of measuring similarity between time series were tested on longer data segments than the typical cardiac cycle envisaging its use integrated on personalized health care cardiovascular diagnosis systems. Euclidean distance, Discrete Wavelet Transform, Discrete Fourier Transform, Correlation Coefficient, Mahalanobis distance, Minkowski Distance, and Dynamic Time Warping Distance were compared when 20 levels of small variations in amplitude scaling and shift, time scaling and shift, baseline variance and additive Gaussian noise are forced to the tested time series. Concentrating on the performance of the similarity methods in terms of their insensibility to small data variations results demonstrate that the time domain Correlation Coefficient is the most robust method while the Discrete Wavelet Transform is the elected one between the transform-based methods tested. Selection of a similarity method to be applied should also take into account implementation issues, namely need of data reduction to avoid computational burden, and in this case transform-based methods should be elected. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
- Ecotoxicological assessment of the anticancer drug cisplatin in the the polychaete Nereis diversicolorPublication . Aureliano, M.; Bebianno, Maria João; Abessa, D. M. S.; Rocha, T.; FONSECA, TAINÁAnticancer drugs are designed to inhibit tumor cell proliferation by interacting with DNA and altering cellular growth factors. When released into the waterbodies of municipal and hospital effluents these pharmaceutical compounds may pose a risk to non-target aquatic organisms, due to their mode of action (cytotoxic, genotoxic, mutagenic and teratogenic). The present study aimed to assess the ecotoxicological potential of the alkylating agent cisplatin (CisPt) to the polychaete Nereis diversicolor, at a range of relevant environmental concentrations (i.e. 0.1, 10 and 100 ng Pt L−1 ). Behavioural impairment (burrowing kinetic impairment), ion pump effects (SR Ca2+-ATPase), neurotoxicity (AChE activity), oxidative stress (SOD, CAT and GPXs activities), metal exposure (metallothionein-like proteins - MTLP), biotransformation (GST), oxidative damage (LPO) and genotoxicity (DNA damage), were selected as endpoints to evaluate the sublethal responses of the ragworms after 14-days of exposure in a water-sediment system. Significant burrowing impairment occurred in worms exposed to the highest CisPt concentration (100 ng Pt L−1 ) along with neurotoxic effects. The activity of antioxidant enzymes (SOD, CAT) and second phase biotransformation enzyme (GST) was inhibited but such effects were compensated by MTLP induction. Furthermore, LPO levels also increased. Results showed that the mode of action of cisplatin may pose a risk to this aquatic species even at the range of ng L−1
- A multibiomarker approach in the clam Ruditapes decussatus to assess the impact of pollution in the Ria Formosa lagoon, South Coast of PortugalPublication . Cravo, Alexandra; Pereira, C.; Gomes, Tânia; Cardoso, Cátia; Serafim, M.A.; Almeida, Cheila; Rocha, T.; Lopes, Belisandra; Company, Rui; Medeiros, A.; Norberto, R.; Pereira, R.; Araújo, O.; Bebianno, Maria JoãoThe Ria Formosa lagoon is an ecosystem whose water quality reflects the anthropogenic influence upon the surrounding areas. In this lagoon, the clam Ruditapes decussatus has a great economical importance and has been widely used as a biomonitor. A multibiomarker approach (d-aminolevulinic acid dehy- dratase, metallothionein, lipid peroxidation, acetylcholinesterase, alkali-labile phosphates, DNA damage) was applied to assess the environmental quality of this ecosystem and the accumulation of contaminants and their potential adverse effects on clams. Clams were sampled in different shellfish beds in the period between July 2007 and December 2008 and abiotic parameters (temperature, salinity, pH and dissolved oxygen of seawater and organic matter in the sediment), condition index, metals (Cd, Cu, Zn, Ni, Pb), TBTs and PAHs concentrations were measured in clam tissues. Data was integrated using Principal Component Analyses and biomarker indices: IBR (Integrated Biomarker Response) and HSI (Health Status Index). This multibiomarker approach enabled discrimination of a time and space trend between sites with different degrees of anthropogenic contamination, identifying one of them (site 2) as the most stressful and summer months as the most critical period for clams due to an increase of environmental stress (anthropogenic pressure along with extreme environmental conditions, e.g. temperature, dissolved oxygen, organic matter in the sediments, etc). The selected biomarkers provided an integrated response to assess the environmental quality of the system, proving to be a useful approach when complex mixtures of contaminants occur.
- Validation of a similarity measurement method for clustering cardiac signalsPublication . Kianimajd, A.; Graca Ruano, Maria; Carvalho, P.; Henriques, J.; Rocha, T.; Paredes, S.; Morgado, M.; Bernardes, R.; Amador, M.; Afonso, P. M.Development of personalized cardiovascular management systems involves automatic identification of the current data as normal or pathological; considering cardiac data as time-series, the illness identification may be performed by seeking similarity between the current patient's time-series data and a reference signal and then proceeding to illness stratification (clustering). Seven of the most common methods of time-series similarity measurement were assessed by imposing 6 types of distortions to the reference signal, considering for each distortion 20 possible variations. This study employed 10 seconds length records of arterial blood pressure signals of healthy subjects, collected from a public database. Then clustering using Partitioning Around Medoids was performed among pathological and non-pathological data considering 3 different clusters. Clustering results confirm usage of the reduced basis Discrete Wavelet Transform resulting from the combination of Haar wavelet decomposition with the Karhunen-Loeve transforms, presenting an accuracy ranging from 76% to 85% when partitioning around Medoids clustering is used.