Institution
University of Siena
Education•Siena, Italy•
About: University of Siena is a education organization based out in Siena, Italy. It is known for research contribution in the topics: Population & Cancer. The organization has 12179 authors who have published 33334 publications receiving 1008287 citations. The organization is also known as: Università degli studi di Siena & Universita degli studi di Siena.
Papers published on a yearly basis
Papers
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London School of Economics and Political Science1, Museum of Science2, University of Siena3, University of Zurich4, Mid Sweden University5, University of Twente6, Roskilde University7, University of Jena8, Eindhoven University of Technology9, University of Oslo10, Adam Mickiewicz University in Poznań11, University of Eastern Finland12, Austrian Academy of Sciences13, Johannes Kepler University of Linz14
TL;DR: The latest European sample survey of public perceptions of biotechnology reveals widespread opposition to genetically modified (GM) food in much of Europe, but public attitudes to medical and environmental applications remain positive.
Abstract: The latest European sample survey of public perceptions of biotechnology reveals widespread opposition to genetically modified (GM) food in much of Europe, but public attitudes to medical and environmental applications remain positive.
416 citations
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TL;DR: In this article, the authors survey macroeconomic issues that marked the transition from planned to market economy in Central and Eastern European and former Soviet Union countries, and discuss explanations for the initial output fall, and mediumterm issues such as optimal speed of transition, disorganization, institutions and sectoral reallocation as source of output dynamics.
Abstract: This essay surveys macroeconomic issues that marked the transition from planned to market economy in Central and Eastern European and former Soviet Union countries. We first establish stylized facts of the transition so far. We then critically survey the theoretical literature on transition, discussing explanations for the initial output fall, and mediumterm issues such as optimal speed of transition, disorganization, institutions and sectoral reallocation as source of output dynamics. We review the empirical literature to assess how well it translates the theoretical models and explains the stylized facts. We conclude with suggestions for future research.
416 citations
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TL;DR: Recommendations on how and when to use MRI for disease monitoring are presented, and some promising MRI approaches that may be introduced into clinical practice in the near future are discussed.
Abstract: The role of MRI in the assessment of multiple sclerosis (MS) goes far beyond the diagnostic process. MRI techniques can be used as regular monitoring to help stage patients with MS and measure disease progression. MRI can also be used to measure lesion burden, thus providing useful information for the prediction of long-term disability. With the introduction of a new generation of immunomodulatory and/or immunosuppressive drugs for the treatment of MS, MRI also makes an important contribution to the monitoring of treatment, and can be used to determine baseline tissue damage and detect subsequent repair. This use of MRI can help predict treatment response and assess the efficacy and safety of new therapies. In the second part of the MAGNIMS (Magnetic Resonance Imaging in MS) network's guidelines on the use of MRI in MS, we focus on the implementation of this technique in prognostic and monitoring tasks. We present recommendations on how and when to use MRI for disease monitoring, and discuss some promising MRI approaches that may be introduced into clinical practice in the near future.
411 citations
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TL;DR: It is proposed that, in addition to biomarker measurements on samples obtained from organisms at field sites, biomarker screening tests should be initiated in the laboratory with a range of new chemicals and organisms relevant to the field sites thought to be at risk to establish links between laboratory-based testing and adverse effects in situ.
Abstract: The potential use of biomarkers in ecological risk assessment is explored. The biomarker concept, initially developed to form a basis for studies at the individual/population level, is extended to include community and ecosystem level studies. A strategy is outlined in which biomarkers might be used to assess chemical exposureand the cumulative, adverse effects of toxicants on biotain situ. Protocols for identifying communities, species and populations most at risk are described. The role of biomarkers in the evaluation of the effectiveness of remedial action to alleviate pollution is discussed. It is proposed that, in addition to biomarker measurements on samples obtained from organisms at field sites, biomarker screening tests should be initiated in the laboratory with a range of new chemicals and organisms relevant to the field sites thought to be at risk. This will help to establish links between laboratory-based testing and adverse effectsin situ.
409 citations
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University of Insubria1, University of Pavia2, University of Eastern Piedmont3, University of Bologna4, University of Verona5, Humanitas University6, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico7, University of Milan8, University of Genoa9, University of Catania10, University of Parma11, University of Pisa12, University of Turin13, University of Perugia14, Sapienza University of Rome15, University of Padua16, University of Brescia17, University of Modena and Reggio Emilia18, University of Siena19, University of Udine20, Università Campus Bio-Medico21, Catholic University of the Sacred Heart22
TL;DR: This study adds to the evidence that patients with haematological malignancies have worse outcomes and the general Italian population with COVID-19 has high mortality, by calculating standardised mortality ratios between observed death in the study cohort and expected death by applying stratum-specific mortality rates.
408 citations
Authors
Showing all 12352 results
Name | H-index | Papers | Citations |
---|---|---|---|
Johan Auwerx | 158 | 653 | 95779 |
I. V. Gorelov | 139 | 1916 | 103133 |
Roberto Tenchini | 133 | 1390 | 94541 |
Francesco Fabozzi | 133 | 1561 | 93364 |
M. Davier | 132 | 1449 | 107642 |
Roberto Dell'Orso | 132 | 1412 | 92792 |
Rino Rappuoli | 132 | 816 | 64660 |
Teimuraz Lomtadze | 129 | 893 | 80314 |
Manas Maity | 129 | 1309 | 87465 |
Dezso Horvath | 128 | 1283 | 88111 |
Paolo Azzurri | 126 | 1058 | 81651 |
Vincenzo Di Marzo | 126 | 659 | 60240 |
Igor Katkov | 125 | 972 | 71845 |
Ying Lu | 123 | 708 | 62645 |
Thomas Schwarz | 123 | 701 | 54560 |