Long term survival of mature autotransplanted teeth: A retrospective single center analysis

Objective: The replacement of an irremediably compromised tooth requires an implant rehabilitation or a traditional fixed partial denture. In well-selected cases, a further therapeutic possibility is represented by tooth autotransplantation. Although dental transplants are poorly understood and practiced, the international literature agrees that it is considered the first choice when applicable. The advantages of this technique are numerous: use of an autologous element, maintenance of tissue trophism, aesthetic and functional restoration, costs reduction. Although autotransplantation is often performed with immature teeth, even mature teeth with fully formed apex can be used as donors. The aim of the present work was to analyze consecutive cases of completely formed donor teeth autotransplantations performed from 2005 to 2011 in 21 patients for evaluating the survival and success rate. Materials and methods: The medical records of patients who underwent transplantation in a specialized center in Rimini (Italy) from 2005 to 2011 were checked. Only transplants of mature donor molars were considered. Patients were called up to evaluate the survival rate and success rate. Results: The mean age at the time of the surgery was 33,6 \ub1 7,4; mean follow up was 11,9 years \ub11,9. Success rate at the time of latest recall visit was 80 % and survival 95 % of the analyzed cases. Conclusions: The survival and success rate are in complete agreement with the most recent literature and confirm that the technique of autotransplantation is reliable when indications and protocols are rigidly followed, also using mature teeth as donors

Equilibrium responses of global net primary production and carbon storage to doubled atmospheric carbon dioxide: sensitivity to changes in vegetation nitrogen concentration

We ran the terrestrial ecosystem model (TEM) for the globe at 0.5° resolution for atmospheric CO2 concentrations of 340 and 680 parts per million by volume (ppmv) to evaluate global and regional responses of net primary production (NPP) and carbon storage to elevated CO2 for their sensitivity to changes in vegetation nitrogen concentration. At 340 ppmv, TEM estimated global NPP of 49.0 1015 g (Pg) C yr−1 and global total carbon storage of 1701.8 Pg C; the estimate of total carbon storage does not include the carbon content of inert soil organic matter. For the reference simulation in which doubled atmospheric CO2 was accompanied with no change in vegetation nitrogen concentration, global NPP increased 4.1 Pg C yr−1 (8.3%), and global total carbon storage increased 114.2 Pg C. To examine sensitivity in the global responses of NPP and carbon storage to decreases in the nitrogen concentration of vegetation, we compared doubled CO2 responses of the reference TEM to simulations in which the vegetation nitrogen concentration was reduced without influencing decomposition dynamics (“lower N” simulations) and to simulations in which reductions in vegetation nitrogen concentration influence decomposition dynamics (“lower N+D” simulations). We conducted three lower N simulations and three lower N+D simulations in which we reduced the nitrogen concentration of vegetation by 7.5, 15.0, and 22.5%. In the lower N simulations, the response of global NPP to doubled atmospheric CO2 increased approximately 2 Pg C yr−1 for each incremental 7.5% reduction in vegetation nitrogen concentration, and vegetation carbon increased approximately an additional 40 Pg C, and soil carbon increased an additional 30 Pg C, for a total carbon storage increase of approximately 70 Pg C. In the lower N+D simulations, the responses of NPP and vegetation carbon storage were relatively insensitive to differences in the reduction of nitrogen concentration, but soil carbon storage showed a large change. The insensitivity of NPP in the N+D simulations occurred because potential enhancements in NPP associated with reduced vegetation nitrogen concentration were approximately offset by lower nitrogen availability associated with the decomposition dynamics of reduced litter nitrogen concentration. For each 7.5% reduction in vegetation nitrogen concentration, soil carbon increased approximately an additional 60 Pg C, while vegetation carbon storage increased by only approximately 5 Pg C. As the reduction in vegetation nitrogen concentration gets greater in the lower N+D simulations, more of the additional carbon storage tends to become concentrated in the north temperate-boreal region in comparison to the tropics. Other studies with TEM show that elevated CO2 more than offsets the effects of climate change to cause increased carbon storage. The results of this study indicate that carbon storage would be enhanced by the influence of changes in plant nitrogen concentration on carbon assimilation and decomposition rates. Thus changes in vegetation nitrogen concentration may have important implications for the ability of the terrestrial biosphere to mitigate increases in the atmospheric concentration of CO2 and climate changes associated with the increases

Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America

We use the terrestrial ecosystem model (TEM), a process-based model, to investigate how interactions between carbon (C) and nitrogen (N) dynamics affect predictions of net primary productivity (NPP) for potential vegetation in North America. Data on pool sizes and fluxes of C and N from intensively studied field sites are used to calibrate the model for each of 17 non-wetland vegetation types. We use information on climate, soils, and vegetation to make estimates for each of 11,299 non-wetland, 0.5° latitude × 0.5° longitude, grid cells in North America. The potential annual NPP and net N mineralization (NETNMIN) of North America are estimated to be 7.032 × 1015 g C yr−1 and 104.6 × 1012 g N yr−1, respectively. Both NPP and NETNMIN increase along gradients of increasing temperature and moisture in northern and temperate regions of the continent, respectively. Nitrogen limitation of productivity is weak in tropical forests, increasingly stronger in temperate and boreal forests, and very strong in tundra ecosystems. The degree to which productivity is limited by the availability of N also varies within ecosystems. Thus spatial resolution in estimating exchanges of C between the atmosphere and the terrestrial biosphere is improved by modeling the linkage between C and N dynamics. We also perform a factorial experiment with TEM on temperate mixed forest in North America to evaluate the importance of considering interactions between C and N dynamics in the response of NPP to an elevated temperature of 2°C. With the C cycle uncoupled from the N cycle, NPP decreases primarily because of higher plant respiration. However, with the C and N cycles coupled, NPP increases because productivity that is due to increased N availability more than offsets the higher costs of plant respiration. Thus, to investigate how global change will affect biosphere-atmosphere interactions, process-based models need to consider linkages between the C and N cycles

Collective behaviour without collective order in wild swarms of midges

Collective behaviour is a widespread phenomenon in biology, cutting through a huge span of scales, from cell colonies up to bird flocks and fish schools. The most prominent trait of collective behaviour is the emergence of global order: individuals synchronize their states, giving the stunning impression that the group behaves as one. In many biological systems, though, it is unclear whether global order is present. A paradigmatic case is that of insect swarms, whose erratic movements seem to suggest that group formation is a mere epiphenomenon of the independent interaction of each individual with an external landmark. In these cases, whether or not the group behaves truly collectively is debated. Here, we experimentally study swarms of midges in the field and measure how much the change of direction of one midge affects that of other individuals. We discover that, despite the lack of collective order, swarms display very strong correlations, totally incompatible with models of noninteracting particles. We find that correlation increases sharply with the swarm's density, indicating that the interaction between midges is based on a metric perception mechanism. By means of numerical simulations we demonstrate that such growing correlation is typical of a system close to an ordering transition. Our findings suggest that correlation, rather than order, is the true hallmark of collective behaviour in biological systems.Comment: The original version has been split into two parts. This first part focuses on order vs. correlation. The second part, about finite-size scaling, will be included in a separate paper. 15 pages, 6 figures, 1 table, 5 video

Finite-size scaling as a way to probe near-criticality in natural swarms

Collective behaviour in biological systems is often accompanied by strong correlations. The question has therefore arisen of whether correlation is amplified by the vicinity to some critical point in the parameters space. Biological systems, though, are typically quite far from the thermodynamic limit, so that the value of the control parameter at which correlation and susceptibility peak depend on size. Hence, a system would need to readjust its control parameter according to its size in order to be maximally correlated. This readjustment, though, has never been observed experimentally. By gathering three-dimensional data on swarms of midges in the field we find that swarms tune their control parameter and size so as to maintain a scaling behaviour of the correlation function. As a consequence, correlation length and susceptibility scale with the system's size and swarms exhibit a near-maximal degree of correlation at all sizes.Comment: Selected for Viewpoint in Physics; PRL Editor's Suggestio

how far are we from the use of satellite rainfall products in landslide forecasting

Abstract Satellite rainfall products have been available for many years (since '90) with an increasing spatial/temporal resolution and accuracy. Their global scale coverage and near real-time products perfectly fit the need of an early warning landslide system. Notwithstanding these characteristics, the number of studies employing satellite rainfall estimates for predicting landslide events is quite limited. In this study, we propose a procedure that allows us to evaluate the capability of different rainfall products to forecast the spatial-temporal occurrence of rainfall-induced landslides using rainfall thresholds. Specifically, the assessment is carried out in terms of skill scores, and receiver operating characteristic (ROC) analysis. The procedure is applied to ground observations and four different satellite rainfall estimates: 1) the Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis, TMPA, real time product (3B42-RT), 2) the SM2RASC product obtained from the application of SM2RAIN algorithm to the Advanced SCATterometer (ASCAT) derived satellite soil moisture (SM) data, 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN), and 4) the Climate Prediction Center (CPC) Morphing Technique (CMORPH). As case study, we consider the Italian territory for which a catalogue listing 1414 rainfall-induced landslides in the period 2008–2014 is available. Results show that satellite products underestimate rainfall with respect to ground observations. However, by adjusting the rainfall thresholds, satellite products are able to identify landslide occurrence, even though with less accuracy than ground-based rainfall observations. Among the four satellite rainfall products, CMORPH and SM2RASC are performing the best, even though differences are small. This result is to be attributed to the high spatial/temporal resolution of CMORPH, and the good accuracy of SM2RSC. Overall, we believe that satellite rainfall estimates might be an important additional data source for developing continental or global landslide warning systems

Predicting the effects of climate change on water yield and forest production in the northeastern United States

Rapid and simultaneous changes in temperature, precipitation and the atmospheric concentration of CO2 are predicted to occur over the next century. Simple, well-validated models of ecosystem function are required to predict the effects of these changes. This paper describes an improved version of a forest carbon and water balance model (PnET-II) and the application of the model to predict stand- and regional-level effects of changes in temperature, precipitation and atmospheric CO2 concentration. PnET-II is a simple, generalized, monthly time-step model of water and carbon balances (gross and net) driven by nitrogen availability as expressed through foliar N concentration. Improvements from the original model include a complete carbon balance and improvements in the prediction of canopy phenology, as well as in the computation of canopy structure and photosynthesis. The model was parameterized and run for 4 forest/site combinations and validated against available data for water yield, gross and net carbon exchange and biomass production. The validation exercise suggests that the determination of actual water availability to stands and the occurrence or non-occurrence of soil-based water stress are critical to accurate modeling of forest net primary production (NPP) and net ecosystem production (NEP). The model was then run for the entire NewEngland/New York (USA) region using a 1 km resolution geographic information system. Predicted long-term NEP ranged from -85 to +275 g C m-2 yr-1 for the 4 forest/site combinations, and from -150 to 350 g C m-2 yr-1 for the region, with a regional average of 76 g C m-2 yr-1. A combination of increased temperature (+6*C), decreased precipitation (-15%) and increased water use efficiency (2x, due to doubling of CO2) resulted generally in increases in NPP and decreases in water yield over the region

The AMSC mobile satellite system

The American Mobile Satellite Consortium (AMSC) Mobile Satellite Service (MSS) system is described. AMSC will use three multi-beam satellites to provide L-band MSS coverage to the United States, Canada and Mexico. The AMSC MSS system will have several noteworthy features, including a priority assignment processor that will ensure preemptive access to emergency services, a flexible SCPC channel scheme that will support a wide diversity of services, enlarged system capacity through frequency and orbit reuse, and high effective satellite transmitted power. Each AMSC satellite will make use of 14 MHz (bi-directional) of L-band spectrum. The Ku-band will be used for feeder links

Aspirations and common tensions : larger lessons from the third US national climate assessment

Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Climatic Change 135 (2016): 187-201, doi:10.1007/s10584-015-1530-z.The Third US National Climate Assessment (NCA3) was produced by experts in response to the US Global Change Research Act of 1990. Based on lessons learned from previous domestic and international assessments, the NCA3 was designed to speak to a broad public and inform the concerns of policy- and decision-makers at different scales. The NCA3 was also intended to be the first step in an ongoing assessment process that would build the nation’s capacity to respond to climate change. This concluding paper draws larger lessons from the insights gained throughout the assessment process that are of significance to future US and international assessment designers. We bring attention to process and products delivered, communication and engagement efforts, and how they contributed to the sustained assessment. Based on areas where expectations were exceeded or not fully met, we address four common tensions that all assessment designers must confront and manage: between (1) core assessment ingredients (knowledge base, institutional set-up, principled process, and the people involved), (2) national scope and subnational adaptive management information needs, (3) scope, complexity, and manageability, and (4) deliberate evaluation and ongoing learning approaches. Managing these tensions, amidst the social and political contexts in which assessments are conducted, is critical to ensure that assessments are feasible and productive, while its outcomes are perceived as credible, salient, and legitimate