scispace - formally typeset
Search or ask a question
Institution

University of Modena and Reggio Emilia

EducationModena, Italy
About: University of Modena and Reggio Emilia is a education organization based out in Modena, Italy. It is known for research contribution in the topics: Population & Medicine. The organization has 8179 authors who have published 22418 publications receiving 671337 citations. The organization is also known as: Università degli Studi di Modena e Reggio Emilia & Universita degli Studi di Modena e Reggio Emilia.


Papers
More filters
Journal ArticleDOI
TL;DR: The aim of this study was to determine the prevalence, characteristics and outcomes of patients with unclassifiable interstitial lung disease (ILD) and to develop a simple method of predicting disease behaviour and to identify subgroups with distinct disease behaviour.
Abstract: The aim of this study was to determine the prevalence, characteristics and outcomes of patients with unclassifiable interstitial lung disease (ILD) and to develop a simple method of predicting disease behaviour. Unclassifiable ILD patients were identified from an ongoing longitudinal cohort. Unclassifiable ILD was diagnosed after a multidisciplinary review did not secure a specific ILD diagnosis. Clinical characteristics and outcomes were compared with idiopathic pulmonary fibrosis (IPF) and non-IPF ILDs. Independent predictors of mortality were determined using Cox proportional-hazards analysis to identify subgroups with distinct disease behaviour. Unclassifiable ILD was diagnosed in 10% of the ILD cohort (132 out of 1370 patients). The most common reason for being unclassifiable was missing histopathological assessment due to a high risk of surgical lung biopsy. Demographic and physiological features of unclassifiable ILD were intermediate between IPF and non-IPF disease controls. Unclassifiable ILD had longer survival rates when compared to IPF on adjusted analysis (hazard ratio 0.62, p = 0.04) and similar survival compared to non-IPF ILDs (hazard ratio 1.54, p = 0.12). Independent predictors of survival in unclassifiable ILD included diffusion capacity of the lung for carbon monoxide (p = 0.001) and a radiological fibrosis score (p = 0.02). Unclassifiable ILD represents approximately 10% of ILD cases and has a heterogeneous clinical course, which can be predicted using clinical and radiological variables.

216 citations

Journal ArticleDOI
Abstract: Robustness and flexibility constitute the main advantages of multiple-robot systems with respect to single-robot ones as per the recent literature. The use of multiple unmanned aerial vehicles (UAVs) combines these benefits with the agility and pervasiveness of aerial platforms [1], [2]. The degree of autonomy of the multi-UAV system should be tuned according to the specificities of the situation under consideration. For regular missions, fully autonomous UAV systems are often appropriate, but, in general, the use of semiautonomous groups of UAVs, supervised or partially controlled by one or more human operators, is the only viable solution to deal with the complexity and unpredictability of real-world scenarios as in, e.g., the case of search and rescue missions or exploration of large/cluttered environments [3]. In addition, the human presence is also mandatory for taking the responsibility of critical decisions in high-risk situations [4].

216 citations

Journal ArticleDOI
19 Jul 2012-Nature
TL;DR: ShARP1 determines the intrinsic instability of HIF proteins to act in parallel to, and cooperate with, oxygen levels, which sheds light on the mechanisms and pathways by which TNBC acquires invasiveness and metastatic propensity.
Abstract: The molecular determinants of malignant cell behaviours in breast cancer remain only partially understood. Here we show that SHARP1 (also known as BHLHE41 or DEC2) is a crucial regulator of the invasive and metastatic phenotype in triple-negative breast cancer (TNBC), one of the most aggressive types of breast cancer. SHARP1 is regulated by the p63 metastasis suppressor and inhibits TNBC aggressiveness through inhibition of hypoxia-inducible factor 1α (HIF-1α) and HIF-2α (HIFs). SHARP1 opposes HIF-dependent TNBC cell migration in vitro, and invasive or metastatic behaviours in vivo. SHARP1 is required, and sufficient, to limit expression of HIF-target genes. In primary TNBC, endogenous SHARP1 levels are inversely correlated with those of HIF targets. Mechanistically, SHARP1 binds to HIFs and promotes HIF proteasomal degradation by serving as the HIF-presenting factor to the proteasome. This process is independent of pVHL (von Hippel-Lindau tumour suppressor), hypoxia and the ubiquitination machinery. SHARP1 therefore determines the intrinsic instability of HIF proteins to act in parallel to, and cooperate with, oxygen levels. This work sheds light on the mechanisms and pathways by which TNBC acquires invasiveness and metastatic propensity.

216 citations

Journal ArticleDOI
TL;DR: Two fundamental topics are dedicated to, which are essential to benefit from the use of FGMs for orthopedic applications, namely the computational tools for materials design and geometry optimization and the manufacturing techniques currently available to produce FGM-based grafts.

216 citations


Authors

Showing all 8322 results

NameH-indexPapersCitations
Carlo M. Croce1981135189007
Gregory Y.H. Lip1693159171742
Geoffrey Burnstock141148899525
Peter M. Rothwell13477967382
Claudio Franceschi12085659868
Lorenzo Galluzzi11847771436
Leonardo M. Fabbri10956660838
David N. Reinhoudt107108248814
Stefano Pileri10063543369
Andrea Bizzeti99116846880
Brian K. Shoichet9828140313
Dante Gatteschi9772748729
Roberta Sessoli9542441458
Thomas A. Buchholz9349433409
Pier Luigi Zinzani9285735476
Network Information
Related Institutions (5)
University of Bologna
115.1K papers, 3.4M citations

97% related

Sapienza University of Rome
155.4K papers, 4.3M citations

97% related

University of Padua
114.8K papers, 3.6M citations

97% related

University of Milan
139.7K papers, 4.6M citations

95% related

Katholieke Universiteit Leuven
176.5K papers, 6.2M citations

93% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202376
2022230
20212,354
20202,083
20191,633
20181,450