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Institution

University of Siena

EducationSiena, 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
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Journal ArticleDOI
TL;DR: Evidence of increasing concentrations in mercury in some biota in Arctic Canada and Greenland is therefore a concern with respect to ecosystem health.

295 citations

Journal ArticleDOI
TL;DR: Semaglutide 1.0mg was superior to exenatide ER 2.0 mg in improving glycemic control and reducing body weight after 56 weeks of treatment; the drugs had comparable safety profiles, indicating that semaglUTide treatment is highly effective for subjects with type 2 diabetes who are inadequately controlled on oral antidiabetic drugs.
Abstract: OBJECTIVE To compare the efficacy and safety of once-weekly semaglutide 1.0 mg s.c. with exenatide extended release (ER) 2.0 mg s.c. in subjects with type 2 diabetes. RESEARCH DESIGN AND METHODS In this phase 3a, open-label, parallel-group, randomized controlled trial, 813 subjects with type 2 diabetes taking oral antidiabetic drugs were randomized (1:1) to semaglutide 1.0 mg or exenatide ER 2.0 mg for 56 weeks. The primary end point was change from baseline in HbA 1c at week 56. RESULTS Mean HbA 1c (8.3% [67.7 mmol/mol] at baseline) was reduced by 1.5% (16.8 mmol/mol) with semaglutide and 0.9% (10.0 mmol/mol) with exenatide ER (estimated treatment difference vs. exenatide ER [ETD] –0.62% [95% CI –0.80, –0.44] [–6.78 mmol/mol (95% CI –8.70, –4.86)]; P P 1c CONCLUSIONS Semaglutide 1.0 mg was superior to exenatide ER 2.0 mg in improving glycemic control and reducing body weight after 56 weeks of treatment; the drugs had comparable safety profiles. These results indicate that semaglutide treatment is highly effective for subjects with type 2 diabetes who are inadequately controlled on oral antidiabetic drugs.

295 citations

Journal ArticleDOI
TL;DR: Refilling the lesions with intensities matching the surrounding normal‐appearing WM ensured accurate tissue‐class measurements and thus represents a promising approach for accurate tissue classification and brain volume measurements.
Abstract: MR-based measurements of brain volumes may be affected by the presence of white matter (WM) lesions Here, we assessed how and to what extent this may happen for WM lesions of various sizes and intensities After inserting WM lesions of different sizes and intensities into T1-W brain images of healthy subjects, we assessed the effect on two widely used automatic methods for brain volume measurement such as SIENAX (segmentation-based) and SIENA (registration-based) To explore the relevance of partial volume (PV) estimation, we performed the experiments with two different PV models, implemented by the same segmentation algorithm (FAST) of SIENAX and SIENA Finally, we tested potential solutions to this issue The presence of WM lesions did not bias measurements for registration-based method such as SIENA By contrast, the presence of WM lesions affected segmentation-based brain volume measurements such as SIENAx The misclassification of both gray matter (GM) and WM volumes varied considerably with lesion size and intensity, especially when the lesion intensity was similar to that of the GM/WM interface The extent to which the presence of WM lesions could affect tissue-class measures was clearly driven by the PV modeling used, with the mixel-type PV model giving a lower error in the presence of WM lesions The tissue misclassification due to WM lesions was still present when they were masked out By contrast, refilling the lesions with intensities matching the surrounding normal-appearing WM ensured accurate tissue-class measurements and thus represents a promising approach for accurate tissue classification and brain volume measurements

295 citations

Journal ArticleDOI
TL;DR: Pecourt et al. as discussed by the authors presented a theoretical study of isolated cytosine, the chromophore of cytidine, and showed that there must be an ultrafast decay channel for this species.
Abstract: Singlet fluorescence lifetimes of adenosine, cytidine, guanosine, and thymidine, determined by femtosecond pump−probe spectroscopy (Pecourt, J.-M. L.; Peon, J.; Kohler, B. J. Am. Chem. Soc. 2000, 122, 9348. Pecourt, J.-M. L.; Peon, J.; Kohler, B. J. Am. Chem. Soc. 2001, 123, 10370), show that the excited states produced by 263 nm light in these nucleosides decay in the subpicosecond range (290−720 fs). Ultrafast radiationless decay to the ground state greatly reduces the probability of photochemical damage. In this work we present a theoretical study of isolated cytosine, the chromophore of cytidine. The experimental lifetime of 720 fs indicates that there must be an ultrafast decay channel for this species. We have documented the possible decay channels and approximate energetics, using a valence-bond derived analysis to rationalize the structural details of the paths. The mechanism favored by our calculations and the experimental data involves (1) a two-mode decay coordinate composed of initial bond len...

294 citations

Journal ArticleDOI
01 Aug 2007-Energy
TL;DR: In this article, the results of a thorough energy and life cycle assessment (LIA) of CdTe and CIS photovoltaic modules are presented, making it one of the very first of its kind to be presented to the scientific community, and therefore especially worthy of attention as a preliminary indication of the future environmental impact that the up-scaling of thin film module production may entail.

293 citations


Authors

Showing all 12352 results

NameH-indexPapersCitations
Johan Auwerx15865395779
I. V. Gorelov1391916103133
Roberto Tenchini133139094541
Francesco Fabozzi133156193364
M. Davier1321449107642
Roberto Dell'Orso132141292792
Rino Rappuoli13281664660
Teimuraz Lomtadze12989380314
Manas Maity129130987465
Dezso Horvath128128388111
Paolo Azzurri126105881651
Vincenzo Di Marzo12665960240
Igor Katkov12597271845
Ying Lu12370862645
Thomas Schwarz12370154560
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202391
2022221
20211,870
20201,979
20191,639
20181,523