Human neural stem cell transplantation in ALS: initial results from a phase I trial

We report the initial results from a phase I clinical trial for ALS. We transplanted GMP-grade, fetal human neural stem cells from natural in utero death (hNSCs) into the anterior horns of the spinal cord to test for the safety of both cells and neurosurgical procedures in these patients. The trial was approved by the Istituto Superiore di Sanit\ue0 and the competent Ethics Committees and was monitored by an external Safety Board

Validating spatiotemporal predictions of western corn rootworm at the regional scale (Tuscany, central Italy)

New invasive pest species are dif!cult to manage, because researchers, advisors, and farmers in the newly invaded areas lack advanced understanding in how and when managing them. The aim of this study was to test selected models that could reliably predict the phenology of Diabrotica virgifera virgifera (LeConte), an important insect pest of maize. We compared the results of three years monitoring activity in three areas of Tuscany with the output of two different models, in order to predict adult emergence from air temperature measurements. The best results were achieved with the model that utilized the date of maize planting as starting date for the accumulation of degree-days, con!rming a strict connection between crop and pest phenology. Model output for the predicted day of the year for start and peak of the pest cumulative emergence was mapped over the administrative boundaries of Tuscany with a regression model run with temperatures derived from WorldClim on-line database. These results will be integrated in a Decision Support System for containment and management strategies of maize pests in Tuscany

Towards understanding temporal and spatial dynamics of Bactrocera oleae (Rossi) infestations using decade-long agrometeorological time series

Insect dynamics depend on temperature patterns, and therefore, global warming may lead to increasing frequencies and intensities of insect outbreaks. The aim of this work was to analyze the dynamics of the olive fruit fly, Bactrocera oleae (Rossi), in Tuscany (Italy). We profited from long-term records of insect infestation and weather data available from the regional database and agrometeorological network. We tested whether the analysis of 13 years of monitoring campaigns can be used as basis for prediction models of B. oleae infestation. We related the percentage of infestation observed in the first part of the host-pest interaction and throughout the whole year to agrometeorological indices formulated for different time periods. A two-step approach was adopted to inspect the effect of weather on infestation: generalized linear model with a binomial error distribution and principal component regression to reduce the number of the agrometeorological factors and remove their collinearity. We found a consistent relationship between the degree of infestation and the temperature-based indices calculated for the previous period. The relationship was stronger with the minimum temperature of winter season. Higher infestation was observed in years following warmer winters. The temperature of the previous winter and spring explained 66 % of variance of early-season infestation. The temperature of previous winter and spring, and current summer, explained 72 % of variance of total annual infestation. These results highlight the importance of multiannual monitoring activity to fully understand the dynamics of B. oleae populations at a regional scale