The effect of fluoride on enamel and dentin formation in the uremic rat incisor

Renal impairment in children is associated with tooth defects that include enamel pitting and hypoplasia. However, the specific effects of uremia on tooth formation are not known. In this study, we used rat mandibular incisors, which continuously erupt and contain all stages of tooth formation, to characterize the effects of uremia on tooth formation. We also tested the hypothesis that uremia aggravates the fluoride (F)-induced changes in developing teeth. Rats were subjected to a two-stage 5/6 nephrectomy or sham operation and then exposed to 0 (control) or 50 ppm NaF in drinking water for 14 days. The effects of these treatments on food intake, body growth rate, and biochemical serum parameters for renal function and calcium metabolism were monitored. Nephrectomy reduced food intake and weight gain. Intake of F by nephrectomized rats increased plasma F levels twofold and further decreased food intake and body weight gain. Uremia affected formation of dentin and enamel and was more extensive than the effect of F alone. Uremia also significantly increased predentin width and induced deposition of large amounts of osteodentin-like matrix-containing cells in the pulp chamber. In enamel formation, the cells most sensitive to uremia were the transitional-stage ameloblasts. These data demonstrate that intake of F by rats with reduced renal function impairs F clearance from the plasma and aggravates the already negative effects of uremia on incisor tooth development

The National Atmospheric Release Advisory Center (NARAC) Modeling and Decision Support System for Radiological and Nuclear Emergency Preparedness and Response

This paper describes the tools and services provided by the National Atmospheric Release Advisory Center (NARAC) at Lawrence Livermore National Laboratory (LLNL) for modeling the impacts of airborne hazardous materials. NARAC provides atmospheric plume modeling tools and services for chemical, biological, radiological, and nuclear airborne hazards. NARAC can simulate downwind effects from a variety of scenarios, including fires, industrial and transportation accidents, radiation dispersal device explosions, hazardous material spills, sprayers, nuclear power plant accidents, and nuclear detonations. NARAC collaborates with several government agencies and laboratories in order to accomplish its mission. The NARAC suite of software tools include simple stand-alone, local-scale plume modeling tools for end-user's computers, and Web- and Internet-based software to access advanced modeling tools and expert analyses from the national center at LLNL. Initial automated, 3-D predictions of plume exposure limits and protective action guidelines for emergency responders and managers are available from the center in 5-10 minutes. These can be followed immediately by quality-assured, refined analyses by 24 x 7 on-duty or on-call NARAC staff. NARAC continues to refine calculations using updated on-scene information, including measurements, until all airborne releases have stopped and the hazardous threats are mapped and impacts assessed. Model predictions include the 3-D spatial and time-varying effects of weather, land use, and terrain, on scales from the local to regional to global. Real-time meteorological data and forecasts are provided by redundant communications links to the U.S. National Oceanic and Atmospheric Administration (NOAA), U.S. Navy, and U.S. Air Force, as well as an in-house mesoscale numerical weather prediction model. NARAC provides an easy-to-use Geographical Information System (GIS) for display of plume predictions with affected population counts and detailed maps, and the ability to export plume predictions to other standard GIS capabilities. Data collection and product distribution is provided through a variety of communication methods, including dial-up, satellite, and wired and wireless networks

ARAC-3, A New Generation Emergency Response Modeling System

A description of the new ARAC-3 (Atmospheric Release Advisory Capability) modeling system is presented. Among the major new capabilities are a prognostic forecast model and entirely new diagnostic and dispersion models. Various components of the system are being tested to determine their performance both individually and within an integrated setting. When completed in 1999, ARAC-3 will contain all the features of the current ARAC-2 system as well as new capabilities that will enable ARAC to function as a state-of-the-art emergency response system well into the next decade

An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences

First look at the new ARAC dispersion model

We describe a new atmospheric dispersion model being developed for the emergency response system of the US Department of Energy`s Atmospheric Release Advisory Capability (ARAC). This model solves the turbulent, advection-diffusion equation via a Lagrangian particle, Monte-Carlo method. Within a simulation, particles representing the pollutant are moved through the domain using a random displacement method to model the turbulent diffusion and a Runge-Kutta method to model the advection. The bottom boundary in the new model is a union of bilinear surfaces between gridded terrain data rather than the discontinuous `stair step` representation of terrain used previously in the ARAC. The new model accepts winds on (x,y,o) grids that can be horizontally and vertically graded and nested in the horizontal