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Francesca Giuffrida Pierre‐Alain Golay Frdric Destaillats Bernadette Hug Fabiola Dionisi 《European Journal of Lipid Science and Technology》2005,107(11):792-798
Lipid oxidation has great impact on the quality of food products through flavor and taste deterioration, reduction in nutritive value, and potential toxicity of the oxidized food components. Flavor and taste deterioration can be easily perceived and it represents one of the major causes of consumer complaints in the food industry. The deterioration of sensory properties is due to the decomposition products of hydroperoxides that easily isomerize and degrade into volatile compounds. Volatile products are responsible for flavor and taste deterioration. In this study, we present the development of the solid‐phase microextraction gas chromatography‐mass spectrometry (SPME‐GC‐MS) technique to quantify low amounts (μg/g range) of secondary oxidation products, i.e. hexanal. The optimization of SPME parameters is a difficult task because of the possibility of further formation of volatile products during analysis. Different parameters such as type of fiber, exposure time of the fiber to the sample headspace and the optimal temperature of absorption have also been investigated. The complete validation of the method was achieved by the determination of linearity, limits of detection and quantification and repeatability. We demonstrated that the SPME method is a valuable tool for the quantification of low amounts of secondary oxidation products such as hexanal. Therefore, this technique can be used to detect early formation of volatiles. 相似文献
3.
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
4.
Domenica Mangraviti Jessica Maria Abbate Carmelo Iaria Francesca Rigano Luigi Mondello Marco Quartuccio Fabio Marino 《International journal of molecular sciences》2022,23(18)
The present work proposes the use of a fast analytical platform for the mass spectrometric (MS) profiling of canine mammary tissues in their native form for the building of a predictive statistical model. The latter could be used as a novel diagnostic tool for the real-time identification of different cellular alterations in order to improve tissue resection during veterinary surgery, as previously validated in human oncology. Specifically, Rapid Evaporative Ionization Mass Spectrometry (REIMS) coupled with surgical electrocautery (intelligent knife—iKnife) was used to collect MS data from histologically processed mammary samples, classified into healthy, hyperplastic/dysplastic, mastitis and tumors. Differences in the lipid composition enabled tissue discrimination with an accuracy greater than 90%. The recognition capability of REIMS was tested on unknown mammary samples, and all of them were correctly identified with a correctness score of 98–100%. Triglyceride identification was increased in healthy mammary tissues, while the abundance of phospholipids was observed in altered tissues, reflecting morpho-functional changes in cell membranes, and oxidized species were also tentatively identified as discriminant features. The obtained lipidomic profiles represented unique fingerprints of the samples, suggesting that the iKnife technique is capable of differentiating mammary tissues following chemical changes in cellular metabolism. 相似文献
5.
Lucia Micale Carmela Fusco Grazia Nardella Orazio Palmieri Tiziana Latiano Domenica Gioffreda Francesca Tavano Anna Panza Antonio Merla Giuseppe Biscaglia Marco Gentile Antonello Cuttitta Marco Castori Francesco Perri Anna Latiano 《International journal of molecular sciences》2023,24(1)
Achalasia is an esophageal smooth muscle motility disorder with unknown pathogenesis. Taking into account our previous results on the downexpression of miR-200c-3p in tissues of patients with achalasia correlated with an increased expression of PRKG1, SULF1, and SYDE1 genes, our aim was to explore the unknown biological interaction between these genes and human miR-200c-3p and if this relation could unravel their functional role in the etiology of achalasia. To search for putative miR-200c-3p binding sites in the 3′-UTR of PRKG1, SULF1 and SYDE1, a bioinformatics tool was used. To test whether PRKG1, SULF1, and SYDE1 are targeted by miR-200c-3p, a dual-luciferase reporter assay and quantitative PCR on HEK293 and fibroblast cell lines were performed. To explore the biological correlation between PRKG1 and miR-200c-3p, an immunoblot analysis was carried out. The overexpression of miR-200c-3p reduced the luciferase activity in cells transfected with a luciferase reporter containing a fragment of the 3′-UTR regions of PRKG1, SULF1, and SYDE1 which included the miR-200c-3p seed sequence. The deletion of the miR-200c-3p seed sequence from the 3′-UTR fragments abrogated this reduction. A negative correlation between miR-200c-3p and PRKG1, SULF1, and SYDE1 expression levels was observed. Finally, a reduction of the endogenous level of PRKG1 in cells overexpressing miR-200c-3p was detected. Our study provides, for the first time, functional evidence about the PRKG1 gene as a direct target and SULF1 and SYDE1 as potential indirect substrates of miR-200c-3p and suggests the involvement of NO/cGMP/PKG signaling in the pathogenesis of achalasia. 相似文献
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7.
Giuseppe Spoto Silvia Bordiga Domenica Scarano Adriano Zecchina 《Catalysis Letters》1992,13(1-2):39-44
In this note an exchange procedure of the acidic protons of H-ZSM5 by CuI ions through reaction with CuCl in the gas phase is described. In the so obtained CuI-ZSM5 exchanged zeolite the CuI ions are in well defined configuration and form with NO mono and di-nitrosyl complexes of high structural and spectroscopic quality. The CuI(NO)2 species are transformed at RT into CuII(NO)X (X=O– and/or NO
2
–
) species which could represent an intermediate in NO decomposition. 相似文献
8.
Newton K. Amaglo Richard N. Bennett Rosario B. Lo Curto Eduardo A.S. Rosa Vincenzo Lo Turco Angela Giuffrida Alberto Lo Curto Francesco Crea Gladys M. Timpo 《Food chemistry》2010
The purpose of this new study was to determine the types and levels of major phytochemicals (non-nutrients) and nutrients in the different tissues from vegetative and flowering Moringa oleifera L. an important multipurpose crop. Rhamnose and acetyl-rhamnose-substituted glucosinolates were found in all of the M. oleifera tissues with different profiles depending on the tissue. In addition the tissues of M. oleifera had a relatively complex flavonoid profile consisting of glucosides, rutinosides, malonylglucosides and traces of acetylglucosides of kaempferol, quercetin and isorhamnetin. Fatty acid profiling of the different tissues showed that leaves were rich in palmitic (16:0) and linolenic (18:3) acid whereas seeds were predominated by oleic acid (18:1). Roots were rich in palmitic and oleic acid, whereas stems and twigs predominately contained palmitic acid. Potassium, magnesium and calcium were the predominant minerals in all of the tissues. Low levels of selenium were detected only in whole seeds. 相似文献
9.
Gaiaschi A Beretta B Poiesi C Conti A Giuffrida MG Galli CL Restani P 《Journal of dairy science》2000,83(12):2733-2739
Since casein proteolysis has a critical role in defining the typical characteristics of Grana Padano cheese, we evaluated the hydrolysis of alphas-casein during the ripening process. Thanks to the high specificity of the anti-alphas((alphas1 + alphas2)-casein monoclonal antibody and amino acid sequence determination, it was possible to identify three main alphas-casein-derived polypeptides in cheese: alphaa, alphab, and alphac. Their production by the three enzymes most involved in cheese proteolysis (pepsin, chymosin, and plasmin) was evaluated by performing in vitro digestions. Data showed that alphaa was released in cheese mainly by the chymosin attack, while alphab and alphac were due to the action of plasmin. A significant correlation between the abundance of some polypeptides and ripening process was shown. 相似文献
10.