No abstract

Our aim was to prospectively ascertain the incidence of first-ever stroke and ischaemic stroke subtypes, mortality, functional outcome and recurrence in Northern Italy. We identified all possible cases of stroke (1st January 2004 and 31st December 2008). Multiple overlapping sources were used. Standard definitions for incident cases, pathological types and infarction subtypes were used. Patient characteristics were identified and analysed, case-fatality was ascertained from administrative databases, and outcome was assessed in all surviving patients by modified Rankin Scale. We identified 1,326 incident strokes. The pathological diagnosis was confirmed in 94 % of cases. The incidence of first-ever stroke was 80.2 per 100,000 (95 % CI 73–87) when adjusted to world population. The incidence of embolic stroke was significantly greater in women than in men (p < 0.001) whereas the incidence of atherothrombotic stroke was significantly greater in men than in women (p < 0.001). The case-fatality of incident strokes was 9.5 % at 7 day, 16.1 % at 28 day, and 29.9 % at 1 year. Case-fatality of ischaemic stroke was lower than that of other pathological types (p < 0.0001). Hypertension was the most important risk factor, and atrial fibrillation was the most common in embolic stroke. Increasing age, female gender and embolic stroke subtypes were associated with an adverse outcome. Data on stroke incidence and case-fatality were similar to those of other high-income countries. However, differences were found in the distribution of risk factors and prognosis across the stroke types and ischaemic stroke subtypes. Gender differences in long-term functional outcomes were significant.

Background and Purpose: We sought to determine the incidence rate, risk factors, and prognosis of stroke in Valle d'Aosta, Italy, to provide information for planning regional health-care facilities.Methods: We undertook a prospective study of all new cases of stroke in the geographically defined population of 114,325 residents of Valle d'Aosta in northern Italy.Results: In the first year of the study (January 1-December 31, 1989), 254 cases of first stroke were registered. The crude annual incidence rate was 2.23/1,000,1.98/1,000 for men and 2.46/1,000 for women. After adjustment to the 1988 Italian population, the incidence rate for first stroke was 2.15/1,000 per year, 2.48/1,000 per year for men and 1.99/1,000 per year for women. The pathological diagnosis was cerebral infarction in 67%, intracranial hemorrhage in 15%, and unknown in 18%. The overall 30-day case-fatality rate was 31%. In survivors, Barthel Index Score recorded at 30 days from stroke onset showed that 100 patients (62%) were dependent in activities of daily living.

Human malignant mesothelioma (HMM) is an aggressive malignancy mainly caused by exposure to asbestos fibers. Here we investigated tumor suppressor genes in mesothelioma cells from tumoral ascites developed in mice exposed to asbestos (asb) fibers and in 12 HMM cell cultures. Mutations in Nf2, p16/Cdkn2a, p19/Arf and Trp53 genes and protein expression of p15/Cdkn2b and Cdk4 were analyzed in 12 cultures from mice hemizygous for Nf2 (asb-Nf2(KO3/+)) and 4 wild type counterparts (asb-Nf2(+/+)). We have found frequent inactivations of p16/Cdkn2a, p19/Arf (or P14/ARF) and p15/Cdkn2b, coinactivation of p16/Cdkn2a and p15/Cdkn2b and low rate of Trp53 mutations in both asb-Nf2(KO3/+) and asb-Nf2(+/+) mesothelioma cells. In both mouse and human mesothelioma cells, inactivation of the hortologous genes p16/Cdkn2a or P16/CDKN2A was due to deletions at the Ink4/Arf locus encompassing p19/Arf or P14/ARF, respectively. Loss of heterozygosity at the Nf2 locus was detected in 10 of 11 asb-Nf2(KO3/+) cultures and Nf2 gene rearrangement in one asb-Nf2(+/+) culture. These data show that the profile of TSG alterations in asbestos-induced mesothelioma is similar in mice and humans. Thus, the mouse mesothelioma model could be useful for human risk assessment, taking into account interindividual variations in genetic sensitivity to carcinogens.

Neural networks are a central technique in machine learning. Recent years have seen a wave of interest in applying neural networks to physical systems for which the governing dynamics are known and expressed through differential equations. Two fundamental challenges facing the development of neural networks in physics applications is their lack of interpretability and their physics-agnostic design. The focus of the present work is to embed physical constraints into the structure of the neural network to address the second fundamental challenge. By constraining tunable parameters (such as weights and biases) and adding special layers to the network, the desired constraints are guaranteed to be satisfied without the need for explicit regularization terms. This is demonstrated on supervised and unsupervised networks for two basic symmetries: even/odd symmetry of a function and energy conservation. In the supervised case, the network with embedded constraints is shown to perform well on regression problems while simultaneously obeying the desired constraints whereas a traditional network fits the data but violates the underlying constraints. Finally, a new unsupervised neural network is proposed that guarantees energy conservation through an embedded symplectic structure. The symplectic neural network is used to solve a system of energy-conserving differential equations and outperforms an unsupervised, non-symplectic neural network.