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Institution

University of Milan

EducationMilan, Italy
About: University of Milan is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Population & Transplantation. The organization has 58413 authors who have published 139784 publications receiving 4636354 citations. The organization is also known as: Università degli Studi di Milano & Statale.


Papers
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Journal ArticleDOI
TL;DR: In this paper, it is shown that the temperature of preparation affects the catalytic activity through the surface area and the chemical composition (non-stoichiometry), and the co-variation of these parameters is best followed in situ by voltammetric curves and point of zero charge measurements.

883 citations

Journal ArticleDOI
Jens Kattge1, Gerhard Bönisch2, Sandra Díaz3, Sandra Lavorel  +751 moreInstitutions (314)
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

882 citations

Journal ArticleDOI
A. A. Abdo1, A. A. Abdo2, Markus Ackermann3, Ivan Agudo4  +270 moreInstitutions (51)
Abstract: We have conducted a detailed investigation of the broadband spectral properties of the gamma-ray selected blazars of the Fermi LAT Bright AGN Sample (LBAS). By combining our accurately estimated Fermi gamma-ray spectra with Swift, radio, infra-red, optical, and other hard X-ray/gamma-ray data, collected within 3 months of the LBAS data taking period, we were able to assemble high-quality and quasi-simultaneous spectral energy distributions (SED) for 48 LBAS blazars. The SED of these gamma-ray sources is similar to that of blazars discovered at other wavelengths, clearly showing, in the usual log nu-log nu F-nu representation, the typical broadband spectral signatures normally attributed to a combination of low-energy synchrotron radiation followed by inverse Compton emission of one or more components. We have used these SED to characterize the peak intensity of both the low-and the high-energy components. The results have been used to derive empirical relationships that estimate the position of the two peaks from the broadband colors (i.e., the radio to optical, alpha(ro), and optical to X-ray, alpha(ox), spectral slopes) and from the gamma-ray spectral index. Our data show that the synchrotron peak frequency (nu(S)(peak)) is positioned between 10(12.5) and 10(14.5) Hz in broad-lined flat spectrum radio quasars (FSRQs) and between 10(13) and 10(17) Hz in featureless BL Lacertae objects. We find that the gamma-ray spectral slope is strongly correlated with the synchrotron peak energy and with the X-ray spectral index, as expected at first order in synchrotron-inverse Compton scenarios. However, simple homogeneous, one-zone, synchrotron self-Compton (SSC) models cannot explain most of our SED, especially in the case of FSRQs and low energy peaked (LBL) BL Lacs. More complex models involving external Compton radiation or multiple SSC components are required to reproduce the overall SED and the observed spectral variability. While more than 50% of known radio bright high energy peaked (HBL) BL Lacs are detected in the LBAS sample, only less than 13% of known bright FSRQs and LBL BL Lacs are included. This suggests that the latter sources, as a class, may be much fainter gamma-ray emitters than LBAS blazars, and could in fact radiate close to the expectations of simple SSC models. We categorized all our sources according to a new physical classification scheme based on the generally accepted paradigm for Active Galactic Nuclei and on the results of this SED study. Since the LAT detector is more sensitive to flat spectrum gamma-ray sources, the correlation between nu(S)(peak) and gamma-ray spectral index strongly favors the detection of high energy peaked blazars, thus explaining the Fermi overabundance of this type of sources compared to radio and EGRET samples. This selection effect is similar to that experienced in the soft X-ray band where HBL BL Lacs are the dominant type of blazars.

882 citations

Journal ArticleDOI
01 Aug 1999-Diabetes
TL;DR: 1H and 13C NMR spectroscopy revealed intramyocellular abnormalities of lipid metabolism associated with whole body insulin resistance in subjects at high risk of developing diabetes, and might be useful tools for noninvasively monitoring these alterations in diabetes and prediabetic states.
Abstract: Insulin resistance is the best prediction factor for the clinical onset of type 2 diabetes. It was suggested that intramuscular triglyceride store may be a primary pathogenic factor for its development. To test this hypothesis, 14 young lean offspring of type 2 diabetic parents, a model of in vivo insulin resistance with increased risk to develop diabetes, and 14 healthy subjects matched for anthropomorphic parameters and life habits were studied with 1) euglycemic-hyperinsulinemic clamp to assess whole body insulin sensitivity, 2) localized 1H nuclear magnetic resonance (NMR) spectroscopy of the soleus (higher content of fiber type I, insulin sensitive) and tibialis anterior (higher content of fiber type IIb, less insulin sensitive) muscles to assess intramyocellular triglyceride content, 3) 13C NMR of the calf subcutaneous adipose tissue to assess composition in saturated/unsaturated carbons of triglyceride fatty acid chains, and 4) dual X-ray energy absorption to assess body composition. Offspring of diabetic parents, notwithstanding normal fat content and distribution, were characterized by insulin resistance and increased intramyocellular triglyceride content in the soleus (P < 0.01) but not in the tibialis anterior (P = 0.19), but showed a normal content of saturated/unsaturated carbons in the fatty acid chain of subcutaneous adipocytes. Stepwise regression analysis selected intramyocellular triglyceride soleus content and plasma free fatty acid levels as the main predictors of whole body insulin sensitivity. In conclusion, 1H and 13C NMR spectroscopy revealed intramyocellular abnormalities of lipid metabolism associated with whole body insulin resistance in subjects at high risk of developing diabetes, and might be useful tools for noninvasively monitoring these alterations in diabetes and prediabetic states.

881 citations

Journal ArticleDOI
TL;DR: CE is an effective diagnostic tool for patients with obscure GI bleeding and if done early in the course of the workup, CE could shorten considerably the time to diagnosis, lead to definitive treatment in a relevant proportion of patients, and spare a number of alternative investigations with low diagnostic yield.

880 citations


Authors

Showing all 58902 results

NameH-indexPapersCitations
Yi Cui2201015199725
Peter J. Barnes1941530166618
Thomas C. Südhof191653118007
Charles A. Dinarello1901058139668
Alberto Mantovani1831397163826
John J.V. McMurray1781389184502
Giuseppe Remuzzi1721226160440
Russel J. Reiter1691646121010
Jean Louis Vincent1611667163721
Tobin J. Marks1591621111604
Tomas Hökfelt158103395979
José Baselga156707122498
Naveed Sattar1551326116368
Silvia Franceschi1551340112504
Frederik Barkhof1541449104982
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023240
2022777
20219,390
20209,000
20197,475
20186,804