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1.
Raquel Alves dos Santos Teresinha Rosa Cabral Isabel Rosa Cabral Lusania Maria Greggi Antunes Cristiane Pontes Andrade Plínio Cerqueira dos Santos Cardoso Marcelo de Oliveira Bahia Claudia Pessoa José Luis Martins do Nascimento Rommel Rodríguez Burbano Catarina Satie Takahashi 《Biocell》2008,32(2):195-200
Physalis angulata L (Solanaceae) is a medicinal plant from North of Brazil, whose different extracts and infusions are commonly used in the popular medicine for the treatment of malaria, asthma, hepatitis, dermatitis and rheumatism. However, the genotoxic effects of P. angulata on human cells is not well known. The main purpose of the present study was to evaluate the in vitro genotoxic effects of aqueous extract of P. angulata using the comet assay and the micronucleus assay in human lymphocytes provided from 6 healthy donors. Treatments with P. angulata extracts were performed in vitro in order to access the extent of DNA damage. The comet assay has shown that treatments with P. angulata at 0.5, 1.0, 2.0, 3.0 and 6.0 microg/mL in culture medium were genotoxic. Lymphocytes treated with P. angulata at the concentrations of 3.0 and 6.0 microg/mL in culture medium showed a statistically significant increase in the frequency of micronucleus (p<0.05), however, the cytokinesis blocked proliferation index (CBPI) was not decreased after P. angulata treatment. In conclusion, the present work demonstrated the genotoxic effects of P. angulata extract on human lymphocytes in vitro. 相似文献
2.
Olga Azevedo Filipa Cordeiro Miguel Fernandes Gago Gabriel Miltenberger-Miltenyi Catarina Ferreira Nuno Sousa Damio Cunha 《International journal of molecular sciences》2021,22(9)
Fabry disease (FD) is an X-linked lysosomal storage disorder caused by mutations of the GLA gene that result in a deficiency of the enzymatic activity of α-galactosidase A and consequent accumulation of glycosphingolipids in body fluids and lysosomes of the cells throughout the body. GB3 accumulation occurs in virtually all cardiac cells (cardiomyocytes, conduction system cells, fibroblasts, and endothelial and smooth muscle vascular cells), ultimately leading to ventricular hypertrophy and fibrosis, heart failure, valve disease, angina, dysrhythmias, cardiac conduction abnormalities, and sudden death. Despite available therapies and supportive treatment, cardiac involvement carries a major prognostic impact, representing the main cause of death in FD. In the last years, knowledge has substantially evolved on the pathophysiological mechanisms leading to cardiac damage, the natural history of cardiac manifestations, the late-onset phenotypes with predominant cardiac involvement, the early markers of cardiac damage, the role of multimodality cardiac imaging on the diagnosis, management and follow-up of Fabry patients, and the cardiac efficacy of available therapies. Herein, we provide a comprehensive and integrated review on the cardiac involvement of FD, at the pathophysiological, anatomopathological, laboratory, imaging, and clinical levels, as well as on the diagnosis and management of cardiac manifestations, their supportive treatment, and the cardiac efficacy of specific therapies, such as enzyme replacement therapy and migalastat. 相似文献
3.
Expert finding is an information retrieval task that is concerned with the search for the most knowledgeable people with respect to a specific topic, and the search is based on documents that describe people's activities. The task involves taking a user query as input and returning a list of people who are sorted by their level of expertise with respect to the user query. Despite recent interest in the area, the current state‐of‐the‐art techniques lack in principled approaches for optimally combining different sources of evidence. This article proposes two frameworks for combining multiple estimators of expertise. These estimators are derived from textual contents, from graph‐structure of the citation patterns for the community of experts and from profile information about the experts. More specifically, this article explores the use of supervised learning to rank methods, as well as rank aggregation approaches, for combining all of the estimators of expertise. Several supervised learning algorithms, which are representative of the pointwise, pairwise and listwise approaches, were tested, and various state‐of‐the‐art data fusion techniques were also explored for the rank aggregation framework. Experiments that were performed on a dataset of academic publications from the Computer Science domain attest the adequacy of the proposed approaches. 相似文献
4.
Sebastiano Battiato Giovanni Maria Farinella Giovanni Giuffrida Catarina Sismeiro Giuseppe Tribulato 《Multimedia Tools and Applications》2009,42(1):5-30
Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audience.
Companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect
to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing
process is simple and widely used, recently the industry has been under increased pressure to further optimize learning, in
particular when facing severe time and learning space constraints. The main contribution of the present work is to demonstrate
that direct marketing firms can exploit the information on visual content to optimize the learning phase. This paper proposes
a two-phase learning strategy based on a cascade of regression methods that takes advantage of the visual and text features
to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS)
show the effectiveness of the proposed methods and a significant improvement over traditional learning techniques. The proposed
approach can be used in any multimedia direct marketing domain in which offers comprise both a visual and text component.
Sebastiano Battiato was born in Catania, Italy, in 1972. He received the degree in Computer Science (summa cum laude) in 1995 and his Ph.D in Computer Science and Applied Mathematics in 1999. From 1999 to 2003 he has lead the “Imaging” team c/o STMicroelectronics in Catania. Since 2004 he works as a Researcher at Department of Mathematics and Computer Science of the University of Catania. His research interests include image enhancement and processing, image coding and camera imaging technology. He published more than 90 papers in international journals, conference proceedings and book chapters. He is co-inventor of about 15 international patents. He is reviewer for several international journals and he has been regularly a member of numerous international conference committees. He has participated in many international and national research projects. He is an Associate Editor of the SPIE Journal of Electronic Imaging (Specialty: digital photography and image compression). He is director of ICVSS (International Computer Vision Summer School). He is a Senior Member of the IEEE. Giovanni Maria Farinella is currently contract researcher at Dipartimento di Matematica e Informatica, University of Catania, Italy (IPLAB research group). He is also associate member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006. His research interests lie in the fields of computer vision, pattern recognition and machine learning. In 2004 he received his degree in Computer Science (egregia cum laude) from University of Catania. He was awarded a Ph.D. (Computer Vision) from the University of Catania in 2008. He has co-authored several papers in international journals and conferences proceedings. He also serves as reviewer numerous international journals and conferences. He is currently the co-director of the International Summer School on Computer Vision (ICVSS). Giovanni Giuffrida is an assistant professor at University of Catania, Italy. He received a degree in Computer Science from the University of Pisa, Italy in 1988 (summa cum laude), a Master of Science in Computer Science from the University of Houston, Texas, in 1992, and a Ph.D. in Computer Science, from the University of California in Los Angeles (UCLA) in 2001. He has an extensive experience in both the industrial and academic world. He served as CTO and CEO in the industry and served as consultant for various organizations. His research interest is on optimizing content delivery on new media such as Internet, mobile phones, and digital tv. He published several papers on data mining and its applications. He is a member of ACM and IEEE. Catarina Sismeiro is a senior lecturer at Imperial College Business School, Imperial College London. She received her Ph.D. in Marketing from the University of California, Los Angeles, and her Licenciatura in Management from the University of Porto, Portugal. Before joining Imperial College Catarina had been and assistant professor at Marshall School of Business, University of Southern California. Her primary research interests include studying pharmaceutical markets, modeling consumer behavior in interactive environments, and modeling spatial dependencies. Other areas of interest are decision theory, econometric methods, and the use of image and text features to predict the effectiveness of marketing communications tools. Catarina’s work has appeared in innumerous marketing and management science conferences. Her research has also been published in the Journal of Marketing Research, Management Science, Marketing Letters, Journal of Interactive Marketing, and International Journal of Research in Marketing. She received the 2003 Paul Green Award and was the finalist of the 2007 and 2008 O’Dell Awards. Catarina was also a 2007 Marketing Science Institute Young Scholar, and she received the D. Antonia Adelaide Ferreira award and the ADMES/MARKTEST award for scientific excellence. Catarina is currently on the editorial boards of the Marketing Science journal and the International Journal of Research in Marketing. Giuseppe Tribulato was born in Messina, Italy, in 1979. He received the degree in Computer Science (summa cum laude) in 2004 and his Ph.D in Computer Science in 2008. From 2005 he has lead the research team at Neodata Group. His research interests include data mining techniques, recommendation systems and customer targeting. 相似文献
Giuseppe TribulatoEmail: |
Sebastiano Battiato was born in Catania, Italy, in 1972. He received the degree in Computer Science (summa cum laude) in 1995 and his Ph.D in Computer Science and Applied Mathematics in 1999. From 1999 to 2003 he has lead the “Imaging” team c/o STMicroelectronics in Catania. Since 2004 he works as a Researcher at Department of Mathematics and Computer Science of the University of Catania. His research interests include image enhancement and processing, image coding and camera imaging technology. He published more than 90 papers in international journals, conference proceedings and book chapters. He is co-inventor of about 15 international patents. He is reviewer for several international journals and he has been regularly a member of numerous international conference committees. He has participated in many international and national research projects. He is an Associate Editor of the SPIE Journal of Electronic Imaging (Specialty: digital photography and image compression). He is director of ICVSS (International Computer Vision Summer School). He is a Senior Member of the IEEE. Giovanni Maria Farinella is currently contract researcher at Dipartimento di Matematica e Informatica, University of Catania, Italy (IPLAB research group). He is also associate member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006. His research interests lie in the fields of computer vision, pattern recognition and machine learning. In 2004 he received his degree in Computer Science (egregia cum laude) from University of Catania. He was awarded a Ph.D. (Computer Vision) from the University of Catania in 2008. He has co-authored several papers in international journals and conferences proceedings. He also serves as reviewer numerous international journals and conferences. He is currently the co-director of the International Summer School on Computer Vision (ICVSS). Giovanni Giuffrida is an assistant professor at University of Catania, Italy. He received a degree in Computer Science from the University of Pisa, Italy in 1988 (summa cum laude), a Master of Science in Computer Science from the University of Houston, Texas, in 1992, and a Ph.D. in Computer Science, from the University of California in Los Angeles (UCLA) in 2001. He has an extensive experience in both the industrial and academic world. He served as CTO and CEO in the industry and served as consultant for various organizations. His research interest is on optimizing content delivery on new media such as Internet, mobile phones, and digital tv. He published several papers on data mining and its applications. He is a member of ACM and IEEE. Catarina Sismeiro is a senior lecturer at Imperial College Business School, Imperial College London. She received her Ph.D. in Marketing from the University of California, Los Angeles, and her Licenciatura in Management from the University of Porto, Portugal. Before joining Imperial College Catarina had been and assistant professor at Marshall School of Business, University of Southern California. Her primary research interests include studying pharmaceutical markets, modeling consumer behavior in interactive environments, and modeling spatial dependencies. Other areas of interest are decision theory, econometric methods, and the use of image and text features to predict the effectiveness of marketing communications tools. Catarina’s work has appeared in innumerous marketing and management science conferences. Her research has also been published in the Journal of Marketing Research, Management Science, Marketing Letters, Journal of Interactive Marketing, and International Journal of Research in Marketing. She received the 2003 Paul Green Award and was the finalist of the 2007 and 2008 O’Dell Awards. Catarina was also a 2007 Marketing Science Institute Young Scholar, and she received the D. Antonia Adelaide Ferreira award and the ADMES/MARKTEST award for scientific excellence. Catarina is currently on the editorial boards of the Marketing Science journal and the International Journal of Research in Marketing. Giuseppe Tribulato was born in Messina, Italy, in 1979. He received the degree in Computer Science (summa cum laude) in 2004 and his Ph.D in Computer Science in 2008. From 2005 he has lead the research team at Neodata Group. His research interests include data mining techniques, recommendation systems and customer targeting. 相似文献
5.
A method for analyzing production systems by applying multi-objective optimization and data mining techniques on discrete-event simulation models, the so-called Simulation-based Innovization (SBI) is presented in this paper. The aim of the SBI analysis is to reveal insight on the parameters that affect the performance measures as well as to gain deeper understanding of the problem, through post-optimality analysis of the solutions acquired from multi-objective optimization. This paper provides empirical results from an industrial case study, carried out on an automotive machining line, in order to explain the SBI procedure. The SBI method has been found to be particularly suitable in this case study as the three objectives under study, namely total tardiness, makespan and average work-in-process, are in conflict with each other. Depending on the system load of the line, different decision variables have been found to be influencing. How the SBI method is used to find important patterns in the explored solution set and how it can be valuable to support decision making in order to improve the scheduling under different system loadings in the machining line are addressed. 相似文献
6.
Characterization of a water-based paint for corrosion protection 总被引:1,自引:0,他引:1
Paula Dias Catarina Carneiro Luísa Andrade José Sousa João Machado Adélio Mendes 《Journal of Coatings Technology and Research》2012,9(3):365-374
Corrosion of steel rebars in reinforced concrete is one of the major problems in the construction industry. Carbonation reactions
of concrete with carbon dioxide and, mainly, the chloride salts action are the main causes responsible for concrete degradation.
Protective coatings help to improve the durability of concrete structures by acting as a physical barrier against the corrosion
agents. Waterborne paints are usually used for concrete protection rather than solvent-based paints since they are less pollutant.
The aim of this work is to investigate the influence of the pore size and porosity on the permeability of the paints films
toward sodium chloride. Three characterization methods from membrane science were implemented to characterize paint coatings.
The time-lag method was used to determine the permeability toward the sodium chloride and toward helium and argon, these for
approximately 100% relative humidity. From the seven waterborne paints formulated, only one was found to be suitable for surface
protection of reinforced concrete, since its permeability toward NaCl was smaller than 10−14 m2 s−1, the threshold value required by National Laboratory of Civil Engineering (LNEC) in Portugal. For the formulated paints,
it was observed that the average pore size correlates well with the permeability toward sodium chloride. This is an important
result since obtaining the permeability toward sodium chloride of corrosion protective paints is very time consuming, while
the average pore size can be obtained in a much shorter time. 相似文献
7.
Catarina Almeida-Ferreira Rafael Silva-Teixeira Ana Cristina Gonalves Carlos Miguel Marto Ana Bela Sarmento-Ribeiro Francisco Caramelo Maria Filomena Botelho Mafalda Laranjo 《International journal of molecular sciences》2022,23(3)
Breast cancer (BC) is a malignant neoplasia with the highest incidence and mortality rates in women worldwide. Currently, therapies include surgery, radiotherapy, and chemotherapy, including targeted therapies in some cases. However, treatments are often associated with serious adverse effects. Looking for new options in BC treatment, we evaluated the therapeutic potential of cold atmospheric plasma (CAP) in two cell lines (MCF7 and HCC1806) with distinct histological features. Apoptosis seemed to be the most prevalent type of death, as corroborated by several biochemical features, including phosphatidylserine exposure, the disruption of mitochondrial membrane potential, an increase in BAX/BCL2 ratio and procaspase 3 loss. Moreover, the accumulation of cells in the G2/M phase of the cell cycle points to the loss of replication ability and decreased survival. Despite reported toxic concentrations of peroxides in culture media exposed to plasma, intracellular peroxide concentration was overall decreased accompanying a reduction in GSH levels shortly after plasma exposure in both cell lines. In HCC1806, elevated nitric oxide (NO) concentration accompanied by reduced superoxide levels suggests that these cells are capable of converting plasma-derived nitrites into NO that competes with superoxide dismutase (SOD) for superoxide to form peroxinitrite. The concomitant inhibition of the antioxidative activity of cells during CAP treatment, particularly the inhibition of cytochrome c oxidase with sodium azide, synergistically increased plasma toxicity. Thus, this in vitro research enlightens the therapeutic potential of CAP in the treatment of breast cancer, elucidating its possible mechanisms of action. 相似文献
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10.
A. Catarina Guedes Luís A. Meireles Helena M. Amaro F. Xavier Malcata 《Journal of the American Oil Chemists' Society》2010,87(7):791-801
Aquaculture is a growing commercial activity worldwide, which resorts more and more often to microalgae as feed; the lipid composition of such microalgae is a critical factor with regard to the fish growth rate upon ingestion. The aim of this work was thus to study the influence of light intensity on the lipid profile of a known microalga, Pavlova lutheri. Several semi-continuous cultures were carried out, and biochemical parameters such as lipid, protein, carbohydrate, and chlorophyll contents were quantified. Lipids were specifically fractionated into classes by TLC, and those in each class were subjected to GC afterwards in an attempt to ascertain their fatty acid profile. Evidence was consequently provided which showed that cultures grown under low light intensity (9 W m−2) possess a higher fraction of eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids esterified in polar classes—which are those with a more favorable role in aquaculture. It was also demonstrated that intermediate levels of light intensity (19 W m−2) may be misleading in terms of favorable effects upon EPA and DHA contents—because there is an increase in their total yields and productivities, but they appear mostly esterified into triacylglycerols; this may be a favorable deed for production and purification, but is metabolically not so effective in aquaculture. The highest EPA and DHA productivities attained were 1.29 and 0.69 mg L−1 day−1, respectively, at intermediate levels of light intensity (19 W m−2). 相似文献