Search

Your search keyword '"Clemente G."' showing total 34 results
Start Over Author "Clemente G." Journal journal of hepatology
34 results on '"Clemente G."'

16. 496 Increased intrahepatic cyclooxygenase-2 and metalloproteinase-2 and -9 expression associates with advanced liver disease in chronic hepatitis C virus infection: Role of viral core and NS5A proteins

Author

Nunez, O., primary, Fernandez-Martinez, A., additional, Apolinario, A., additional, Lorente, R., additional, Bosca, L., additional, de la Cruz, G., additional, Clemente, G., additional, Martin-Sanz, P., additional, and Garcia-Monzon, C., additional

Published
2004
Full Text
View/download PDF

33. Use of artificial intelligence as an innovative donor-recipient matching model for liver transplantation: results from a multicenter Spanish study.

Author

Briceño J, Cruz-Ramírez M, Prieto M, Navasa M, Ortiz de Urbina J, Orti R, Gómez-Bravo MÁ, Otero A, Varo E, Tomé S, Clemente G, Bañares R, Bárcena R, Cuervas-Mons V, Solórzano G, Vinaixa C, Rubín A, Colmenero J, Valdivieso A, Ciria R, Hervás-Martínez C, and de la Mata M

Subjects
Adolescent, Adult, Aged, Algorithms, Decision Making, Computer-Assisted, Female, Graft Survival, Humans, Male, Middle Aged, Models, Statistical, Multivariate Analysis, Neural Networks, Computer, Prognosis, Spain, Transplant Recipients, Young Adult, Artificial Intelligence, Liver Transplantation statistics & numerical data, Tissue Donors
Abstract

Background & Aims: There is an increasing discrepancy between the number of potential liver graft recipients and the number of organs available. Organ allocation should follow the concept of benefit of survival, avoiding human-innate subjectivity. The aim of this study is to use artificial-neural-networks (ANNs) for donor-recipient (D-R) matching in liver transplantation (LT) and to compare its accuracy with validated scores (MELD, D-MELD, DRI, P-SOFT, SOFT, and BAR) of graft survival., Methods: 64 donor and recipient variables from a set of 1003 LTs from a multicenter study including 11 Spanish centres were included. For each D-R pair, common statistics (simple and multiple regression models) and ANN formulae for two non-complementary probability-models of 3-month graft-survival and -loss were calculated: a positive-survival (NN-CCR) and a negative-loss (NN-MS) model. The NN models were obtained by using the Neural Net Evolutionary Programming (NNEP) algorithm. Additionally, receiver-operating-curves (ROC) were performed to validate ANNs against other scores., Results: Optimal results for NN-CCR and NN-MS models were obtained, with the best performance in predicting the probability of graft-survival (90.79%) and -loss (71.42%) for each D-R pair, significantly improving results from multiple regressions. ROC curves for 3-months graft-survival and -loss predictions were significantly more accurate for ANN than for other scores in both NN-CCR (AUROC-ANN=0.80 vs. -MELD=0.50; -D-MELD=0.54; -P-SOFT=0.54; -SOFT=0.55; -BAR=0.67 and -DRI=0.42) and NN-MS (AUROC-ANN=0.82 vs. -MELD=0.41; -D-MELD=0.47; -P-SOFT=0.43; -SOFT=0.57, -BAR=0.61 and -DRI=0.48)., Conclusions: ANNs may be considered a powerful decision-making technology for this dataset, optimizing the principles of justice, efficiency and equity. This may be a useful tool for predicting the 3-month outcome and a potential research area for future D-R matching models., (Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

Published
2014
Full Text
View/download PDF

34. Differential contribution of hepatitis C virus NS5A and core proteins to the induction of oxidative and nitrosative stress in human hepatocyte-derived cells.

Author

García-Mediavilla MV, Sánchez-Campos S, González-Pérez P, Gómez-Gonzalo M, Majano PL, López-Cabrera M, Clemente G, García-Monzón C, and González-Gallego J

Subjects
Cell Line, Flow Cytometry, Genes, Reporter, Humans, Inflammation, Luciferases analysis, Luciferases genetics, Models, Biological, Nitrogen Compounds, Polymerase Chain Reaction, Reactive Oxygen Species, Transfection, Hepacivirus physiology, Hepatocytes physiology, Hepatocytes virology, Nitrates metabolism, Oxidative Stress, Viral Core Proteins physiology
Abstract

Background/aims: We aimed to explore the effects of hepatitis C virus (HCV) core and NS5A proteins on reactive oxygen (ROS) and nitrogen species (RNS) formation and on gene expression profile of iNOS in human hepatocyte-derived cells., Methods: Production of ROS and RNS and nitrotyrosine residues accumulation were determined by flow cytometry and fluorescent microscopy as well as by Western blot, respectively, in NS5A- and core-transfected cells. Northern blot, Western blot, real-time PCR, and luciferase assays were used to assess iNOS gene expression in both transfectants., Results: Cytokine-activated NS5A- and core-transfected cells induced ROS and RNS production but an earlier and more marked increase was observed in NS5A-expressing cells. Superoxide production was also augmented, showing a similar temporal pattern of appearance in both NS5A- and core-transfected cells. Although both NS5A and core HCV proteins were able to up-regulate iNOS gene expression, accompanied by a nitrotyrosine-containing proteins accumulation, an earlier iNOS overexpression was observed in NS5A-expressing cells, suggesting a different time course of iNOS activation pattern for core and NS5A HCV proteins., Conclusions: Our results indicate a differential contribution of both HCV proteins to oxidative and nitrosative stress generation.

Published
2005
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results