University of Siena

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.

Assessing brain atrophy rates in a large population of untreated multiple sclerosis subtypes.

Abstract: Objective: To assess the time course of brain atrophy and the difference across clinical subtypes in multiple sclerosis (MS). Methods: The percent brain volume change (PBVC) was computed on existing longitudinal (2 time points) T1-weighted MRI from untreated (trial and nontrial) patients with MS. Patients (n = 963) were classified as clinically isolated syndromes suggestive of MS (CIS, 16%), relapsing-remitting (RR, 60%), secondary progressive (SP, 15%), and primary progressive (9%) MS. The median length of follow-up was 14 months (range 12–68). Results: There was marked heterogeneity of the annualized PBVC (PBVC/y) across MS subtypes ( p = 0.003), with higher PBVC/y in SP than in CIS ( p = 0.003). However, this heterogeneity disappeared when data were corrected for the baseline normalized brain volume. When the MS population was divided into trial and nontrial subjects, the heterogeneity of PBVC/y across MS subtypes was present only in the second group, due to the higher PBVC/y values found in trial data in CIS ( p = 0.01) and RR ( p Conclusions: This first large study in untreated patients with multiple sclerosis (MS) with different disease subtypes shows that brain atrophy proceeds relentlessly throughout the course of MS, with a rate that seems largely independent of the MS subtype, when adjusting for baseline brain volume.

Advantages and Limitations of Microarray Technology in Human Cancer

Abstract: Cancer is a highly variable disease with multiple heterogeneous genetic and epigenetic changes. Functional studies are essential to understanding the complexity and polymorphisms of cancer. The final deciphering of the complete human genome, together with the improvement of high throughput technologies, is causing a fundamental transformation in cancer research. Microarray is a new powerful tool for studying the molecular basis of interactions on a scale that is impossible using conventional analysis. This technique makes it possible to examine the expression of thousands of genes simultaneously. This technology promises to lead to improvements in developing rational approaches to therapy as well as to improvements in cancer diagnosis and prognosis, assuring its entry into clinical practice in specialist centers and hospitals within the next few years. Predicting who will develop cancer and how this disease will behave and respond to therapy after diagnosis will be one of the potential benefits of this technology within the next decade. In this review, we highlight some of the recent developments and results in microarray technology in cancer research, discuss potentially problematic areas associated with it, describe the eventual use of microarray technology for clinical applications and comment on future trends and issues.

VHE γ-Ray Observation of the Crab Nebula and its Pulsar with the MAGIC Telescope

Abstract: We report about very high energy (VHE) gamma-ray observations of the Crab Nebula with the MAGIC telescope. The gamma-ray flux from the nebula was measured between 60 GeV and 9 TeV. The energy spectrum can be described by a curved power law dF/dE = f(0)(E/300 GeV)([a+b log)((E/300 GeV)])(10) with a flux normalization f(0) of (6.0 +/- 0.2(stat)) x 10(-10) cm(-2) s(-1) TeV-1, a = 2.31 +/- 0.06(stat), and b = 0.26 +/- 0.07(stat). The peak in the spectral energy distribution is estimated at 77 +/- 35 GeV. Within the observation time and the experimental resolution of the telescope, the gamma-ray emission is steady and pointlike. The emission's center of gravity coincides with the position of the pulsar. Pulsed gamma-ray emission from the pulsar could not be detected. We constrain the cutoff energy of the pulsed spectrum to be less than 27 GeV, assuming that the differential energy spectrum has an exponential cutoff. For a superexponential shape, the cutoff energy can be as high as 60 GeV.