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.

MRI and the diagnosis of multiple sclerosis: expanding the concept of "no better explanation".

Abstract: Although the diagnosis of multiple sclerosis relies on the demonstration of disease dissemination in space and time, the exclusion of other neurological disorders is also essential. The limited specificity of abnormalities disclosed by MRI may increase the likelihood of diagnosis of multiple sclerosis in patients affected by other disorders. The available criteria for diagnosis of multiple sclerosis have not taken advantage of the potential of MRI to detect features "not suggestive" of multiple sclerosis. Recognition of such features in the work-up of patients suspected of having multiple sclerosis may reduce the likelihood of a false positive diagnosis of the disorder in some, while suggesting the correct alternative diagnosis in other patients. On the basis of this, a workshop of the European MAGNIMS (Magnetic Resonance Network in Multiple Sclerosis) was held to define a series of MRI red flags in the setting of clinically suspected multiple sclerosis that is derived from evidence-based findings and educated guesses. The presence of such red flags should alert clinicians to reconsider the differential diagnosis more extensively. In this review we will report on the conclusions of this international consensus, which should represent a first step beyond the concept of "no better explanation", and inform future diagnostic criteria for multiple sclerosis.

Delayed risk stratification, to include the response to initial treatment (surgery and radioiodine ablation), has better outcome predictivity in differentiated thyroid cancer patients

Abstract: Introduction: After initial treatment, differentiated thyroid cancer (DTC) patients are stratified as low and high risk based on clinical/pathological features. Recently, a risk stratification based on additional clinical data accumulated during follow-up has been proposed. Objective: To evaluate the predictive value of delayed risk stratification (DRS) obtained at the time of the first diagnostic control (8‐12 months after initial treatment). Methods: We reviewed 512 patients with DTC whose risk assessment was initially defined according to the American (ATA) and European Thyroid Association (ETA) guidelines. At the time of the first control, 8‐12 months after initial treatment, patients were re-stratified according to their clinical status: DRS. Results: Using DRS, about 50% of ATA/ETA intermediate/high-risk patients moved to DRS low-risk category, while about 10% of ATA/ETA low-risk patients moved to DRS high-risk category. The ability of the DRS to predict the final outcome was superior to that of ATA and ETA. Positive and negative predictive values for both ATA (39.2 and 90.6% respectively) and ETA (38.4 and 91.3% respectively) were significantly lower than that observed with the DRS (72.8 and 96.3% respectively, P!0.05). The observed variance in predicting final outcome was 25.4% for ATA, 19.1% for ETA, and 62.1% for DRS. Conclusions: Delaying the risk stratification of DTC patients at a time when the response to surgery and radioiodine ablation is evident allows to better define individual risk and to better modulate the subsequent follow-up.

Corticospinal Excitability Modulation to Hand Muscles During Movement Imagery

Abstract: Motor evoked potentials (MEPs) to magnetic transcranial stimulation (TCS) were recorded from right abductor digiti minimi (ADM) and first dorsal interosseous (FDI) muscles, sharing the same peripheral innervation but engaged in two different motor demands. In seven healthy and trained subjects, the latencies, amplitudes and variability of MEPs were investigated under the following, randomly intermingled, conditions: full muscular and mental relaxation; mental simulation of selective index finger or little finger abduction; mental non-motor activity (arithmetical calculation); and real motor task (little and index finger abduction). The whole procedure was performed by continuous audiovisual monitoring of electromyographic 'silence' in the tested muscles. The maximal facilitatory effects (= latency shortening and amplitude increase) on MEPs were induced by the real motor task. An amplitude potentiation of MEPs in both tested muscles was present during non-motor mental activity, in comparison to basal values. A further amplitude potentiation, without latency shifts, was confined to the muscle acting as 'prime mover' for the mentally simulated movement, according to the motor program dispatched but not executed by the subject. Similar results were also found in the F-wave, showing that mental simulation affects spinal motoneuronal excitability as well, although -- due to the lack of MEP and F-wave latency shift -- the main effect takes place at cortical level. The study shows that movement imagery can focus specific facilitation on the prime-mover muscle for the mentally simulated movement. This is mainly evident on FDI muscle, which controls fingers (i.e. the index) with highly corticalized motor representation.

Search for gravitational waves from low mass compact binary coalescence in LIGO's sixth science run and Virgo's science runs 2 and 3

Abstract: We report on a search for gravitational waves from coalescing compact binaries using LIGO and Virgo observations between July 7, 2009, and October 20, 2010. We searched for signals from binaries with total mass between 2 and 25M(circle dot); this includes binary neutron stars, binary black holes, and binaries consisting of a black hole and neutron star. The detectors were sensitive to systems up to 40 Mpc distant for binary neutron stars, and further for higher mass systems. No gravitational-wave signals were detected. We report upper limits on the rate of compact binary coalescence as a function of total mass, including the results from previous LIGO and Virgo observations. The cumulative 90% confidence rate upper limits of the binary coalescence of binary neutron star, neutron star-black hole, and binary black hole systems are 1.3 x 10(-4), 3.1 x 10(-5), and 6.4 x 10(-6) Mpc(-3) yr(-1), respectively. These upper limits are up to a factor 1.4 lower than previously derived limits. We also report on results from a blind injection challenge.