ASL expression in ALDH1A1+ neurons in the substantia nigra metabolically contributes to neurodegenerative phenotype

Argininosuccinate lyase (ASL) is essential for the NO-dependent regulation of tyrosine hydroxylase (TH) and thus for catecholamine production. Using a conditional mouse model with loss of ASL in catecholamine neurons, we demonstrate that ASL is expressed in dopaminergic neurons in the substantia nigra pars compacta, including the ALDH1A1 + subpopulation that is pivotal for the pathogenesis of Parkinson disease (PD). Neuronal loss of ASL results in catecholamine deficiency, in accumulation and formation of tyrosine aggregates, in elevation of α-synuclein, and phenotypically in motor and cognitive deficits. NO supplementation rescues the formation of aggregates as well as the motor deficiencies. Our data point to a potential metabolic link between accumulations of tyrosine and seeding of pathological aggregates in neurons as initiators for the pathological processes involved in neurodegeneration. Hence, interventions in tyrosine metabolism via regulation of NO levels may be therapeutic beneficial for the treatment of catecholamine-related neurodegenerative disorders

A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment

The aim of this work is to report on an activity carried out during the 2010 Recognized Environmental Picture experiment, held in the Ligurian Sea during summer 2010. The activity was the first at-sea test of the recently developed decision support system (DSS) for operation planning, which had previously been tested in an artificial experiment. The DSS assesses the impact of both environmental conditions (meteorological and oceanographic) and non-environmental conditions (such as traffic density maps) on people and assets involved in the operation and helps in deciding a course of action that allows safer operation. More precisely, the environmental variables (such as wind speed, current speed and significant wave height) taken as input by the DSS are the ones forecasted by a super-ensemble model, which fuses the forecasts provided by multiple forecasting centres. The uncertainties associated with the DSS's inputs (generally due to disagreement between forecasts) are propagated through the DSS's output by using the unscented transform. In this way, the system is not only able to provide a traffic light map (run/not run the operation), but also to specify the confidence level associated with each action. This feature was tested on a particular type of operation with underwater gliders: the glider surfacing for data transmission. It is also shown how the availability of a glider path prediction tool provides surfacing options along the predicted path. The applicability to different operations is demonstrated by applying the same system to support diver operations