Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Michela Bonomo"'
Autor:
Kim Clarke, Sara Ricciardi, Tim Pearson, Izwan Bharudin, Peter K. Davidsen, Michela Bonomo, Daniela Brina, Alessandra Scagliola, Deborah M. Simpson, Robert J. Beynon, Farhat Khanim, John Ankers, Mark A. Sarzynski, Sujoy Ghosh, Addolorata Pisconti, Jan Rozman, Martin Hrabe de Angelis, Chris Bunce, Claire Stewart, Stuart Egginton, Mark Caddick, Malcolm Jackson, Claude Bouchard, Stefano Biffo, Francesco Falciani
Publikováno v:
Cell Reports, Vol 21, Iss 6, Pp 1507-1520 (2017)
Summary: Regular endurance training improves muscle oxidative capacity and reduces the risk of age-related disorders. Understanding the molecular networks underlying this phenomenon is crucial. Here, by exploiting the power of computational modeling,
Externí odkaz:
https://doaj.org/article/56b43239ccf74aeabfd363d761f08299
Autor:
Francesca Baldini, Adriana Voci, Gianluca Damonte, Patrizia Gena, Michela Bonomo, Elena Grasselli, Piero Portincasa, Nadia Serale, Marilina Florio, Laura Vergani, Giuseppe Calamita, Annalisa Salis
Hepatic steatosis is the hallmark of non-alcoholic fatty liver disease (NAFLD), the hepatic manifestation of the metabolic syndrome and insulin resistance with potential evolution towards non-alcoholic steatohepatitis (NASH), cirrhosis and hepatocell
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17cbf04e0a5f87b65eb7cdcd6b19facd
http://hdl.handle.net/11567/999908
http://hdl.handle.net/11567/999908
Autor:
Angelo Galiano, Roberto Ria, Domenico Scarafile, Assunta Melaccio, Michela Bonomo, Anna Gallone, Antonella Frassanito, Angelo Vacca, Alessandro Massaro, Giuseppe Calamita, Francesca Vacca, Filippo Attivissimo, Antonio Giovanni Solimando
Publikováno v:
MeMeA
The proposed work describes preliminary results of a research project based on the realization of a Decision Support System -DSS- platform embedding medical and artificial intelligence -AI- algorithms. Specifically the telemedicine platform is suitab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4dcce6c7dd08c785894c6fdbd0e700d2
http://hdl.handle.net/11589/202080
http://hdl.handle.net/11589/202080
Autor:
Martin Hrabé de Angelis, Claude Bouchard, Deborah M. Simpson, Peter K. Davidsen, Alessandra Scagliola, Izwan Bharudin, Robert J. Beynon, Addolorata Pisconti, Francesco Falciani, Jan Rozman, Farhat L. Khanim, Claire E. Stewart, Mark X. Caddick, Malcolm J. Jackson, Michela Bonomo, Stefano Biffo, Mark A. Sarzynski, Sujoy Ghosh, Kim Clarke, Daniela Brina, Stuart Egginton, John M. Ankers, Timothy Pearson, Christopher M. Bunce, Sara Ricciardi
Publikováno v:
Cell Reports, Vol 21, Iss 6, Pp 1507-1520 (2017)
Cell Reports
Cell Rep. 21, 1507-1520 (2017)
Cell Reports
Cell Rep. 21, 1507-1520 (2017)
Summary Regular endurance training improves muscle oxidative capacity and reduces the risk of age-related disorders. Understanding the molecular networks underlying this phenomenon is crucial. Here, by exploiting the power of computational modeling,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::870b163f71546054e9beacf4f22cc6b9