University of Perugia

About: University of Perugia is a education organization based out in Perugia, Umbria, Italy. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 13365 authors who have published 39516 publications receiving 1265601 citations. The organization is also known as: Universitá degli Studi di Perugia & Universita degli Studi di Perugia.

AddNeuroMed—The European Collaboration for the Discovery of Novel Biomarkers for Alzheimer's Disease

Abstract: There is an urgent need for Alzheimer's disease (AD) biomarkers-especially in the context of clinical trials. Biomarkers for early diagnosis, disease progression, and prediction are most critical, and disease-modification therapy development may depend on the discovery and validation of such markers. AddNeuroMed is a cross European, public/private consortium developed for AD biomarker discovery. We report here the development and design of AddNeuroMed and the progress toward the development of plasma markers. Despite the obstacles to such markers, we have identified a range of markers including CFH and A2M, both of which have been independently replicated. The experience of AddNeuroMed leads us to three overall conclusions. First, collaboration is essential. Second, design is paramount and combining modalities, such as imaging and proteomics, may be informative. Third, animal models are valuable in biomarker research. Most importantly, we have learned that plasma markers are feasible.

The L3 silicon microvertex detector

Abstract: The design and construction of the silicon strip microvertex detector (SMD) of the L3 experiment at LEP are described. We present the sensors, readout electronics, data acquisition system, mechanical assembly and support, displacement monitoring systems and radiation monitoring system of the recently installed double-sided, double-layered SMD. This detector utilizes novel and sophisticated techniques for its readout.

Plasma proteins predict conversion to dementia from prodromal disease

Abstract: Background The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia. Methods Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays. Results Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%). Conclusions We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.

A model‐free version of the fundamental theorem of asset pricing and the super‐replication theorem

Abstract: We propose a Fundamental Theorem of Asset Pricing and a Super-Replication Theorem in a model-independent framework. We prove these theorems in the setting of finite, discrete time and a market consisting of a risky asset S as well as options written on this risky asset. As a technical condition, we assume the existence of a traded option with a superlinearly growing payoff-function, e.g., a power option. This condition is not needed when sufficiently many vanilla options maturing at the horizon T are traded in the market.