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Institution

University of Milano-Bicocca

EducationMilan, Italy
About: University of Milano-Bicocca is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Population & Blood pressure. The organization has 8972 authors who have published 22322 publications receiving 620484 citations. The organization is also known as: Università degli Studi di Milano-Bicocca & Universita degli Studi di Milano-Bicocca.


Papers
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Journal ArticleDOI
TL;DR: In this study, different global measures of classification performances are compared by means of results achieved on an extended set of real multivariate datasets and a set of benchmark values based on different random classification scenarios are introduced.

173 citations

Journal ArticleDOI
TL;DR: In males, hypertension is characterized by a higher prevalence of increased iron stores and metabolic abnormalities that are part of theIRHIO syndrome, which may have clinical implications due to the increased risk of IRHIO patients to develop hepatic cirrhosis and also for the role of iron in early atherogenesis.
Abstract: Objectives Insulin-resistance-associated hepatic iron overload syndrome (IRHIO) is characterized by high serum ferritin and presence of metabolic alterations that are part of insulin-resistance syndrome (IRS). Thus, clinical conditions characterized by a high prevalence of IRS may also be characteri

172 citations

Journal ArticleDOI
TL;DR: The role of anti–amyloid β (Aβ) autoantibodies in the acute and remission phases of cerebral amyloid angiopathy–related inflammation is investigated.
Abstract: Objective Cerebral amyloid angiopathy–related inflammation (CAA-ri) is characterized by vasogenic edema and multiple cortical/subcortical microbleeds, sharing several aspects with the recently defined amyloid-related imaging abnormalities (ARIA) reported in Alzheimer's disease (AD) passive immunization therapies. Herein, we investigated the role of anti–amyloid β (Aβ) autoantibodies in the acute and remission phases of CAA-ri. Methods We used a novel ultrasensitive technique on patients from a retrospective multicenter case–control study, and evaluated the anti-Aβ autoantibody concentration in the cerebrospinal fluid (CSF) of 10 CAA-ri, 8 CAA, 14 multiple sclerosis, and 25 control subjects. Levels of soluble Aβ40, Aβ42, tau, P-181 tau, and APOE genotype were also investigated. Results During the acute phase of CAA-ri, anti-Aβ autoantibodies were specifically increased and directly correlated with Aβ mobilization, together with augmented tau and P-181 tau. Following clinical and radiological remission, autoantibodies progressively returned to control levels, and both soluble Aβ and axonal degeneration markers decreased in parallel. Interpretation Our data support the hypothesis that the pathogenesis of CAA-ri may be mediated by a selective autoimmune reaction against cerebrovascular Aβ, directly related to autoantibody concentration and soluble Aβ. The CSF dosage of anti-Aβ autoantibodies with the technique here described can thus be proposed as a valid alternative tool for the diagnosis of CAA-ri. Moreover, given the similarities between ARIA developing spontaneously and those observed during immunization trials, anti-Aβ autoantibodies can be considered as novel potential biomarkers in future amyloid-modifying therapies for the treatment of AD and CAA. Ann Neurol 2013;73:449–458

172 citations

Journal ArticleDOI
TL;DR: This research presents a novel probabilistic approach that allows us to assess the importance of knowing the carrier and removal status of canine coronavirus, as a source of infection for other animals.
Abstract: Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of "modifiable risk factors", measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details.

172 citations

Journal ArticleDOI
TL;DR: In this article, the authors present and discuss an inventory map of deep seated gravitational slope deformations (DSGSD) at the scale of the entire European Alps, in order to review existing knowledge and investigate general controls on these phenomena.

172 citations


Authors

Showing all 9226 results

NameH-indexPapersCitations
Carlo Rovelli1461502103550
Giuseppe Mancia1451369139692
Marco Bersanelli142526105135
Teruki Kamon1422034115633
Marco Colonna13951271166
M. I. Martínez134125179885
A. Mennella13246393236
Roberto Salerno132119783409
Federico Ferri132137689337
Marco Paganoni132143888482
Arabella Martelli131131884029
Sandra Malvezzi129132684401
Andrea Massironi129111578457
Marco Pieri129128582914
Cristina Riccardi129162791452
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023173
2022349
20212,468
20202,253
20191,905
20181,706