Short-term Osteoclastic Activity Induced by Locally High Concentrations of Recombinant Human Bone Morphogenetic Protein–2 in a Cancellous Bone Environment

Study Design. An experimental study investigating osteoclastic activity induced by rhBMP-2 in sheep. Objective. To examine the effects of increasing local rhBMP-2 concentration on osteoclastic response and peri-implant bone resorption. Summary of Background Data. Level I clinical studies have established the safe and effective volume and concentration of rhBMP-2 delivered on an absorbable collagen sponge. However, peri-implant bone resorption appearing as decreased mineral density has been observed radiographically in rare instances after implantation of rhBMP-2 on an absorbable collagen sponge (rhBMP-2/ACS). Methods. Bilateral corticocancellous defects were created in the distal femora of 30 adult sheep. Combinations of rhBMP-2/ACS implant volume (V) (1V = normal fill or 2V = overfilled) and rhBMP-2 solution concentration (⤫) (1 ⤫ normal concentration or 3.5 ⤫ = hyperconcentrated) resulted in local rhBMP-2 concentrations of 0⤫, 1⤫, 2⤫, 3.5⤫, and 7⤫ the estimated effective concentration for this model. Faxitron radiography, quantitative CT, histology, and quantitative histomorphometry were conducted in a blinded fashion to analyze the effect of the treatments. Results. At 1 week, the normal fill-normal concentration implants (1⤫) produced the least transient osteoclastic activity resulting in limited peri-implant resorption. Overfilledhyperconcentrated implants (2⤫, 3.5⤫) demonstrated moderate resorption zones. Overfilled-hyperconcentrated implants (7⤫) demonstrated extensive osteoclastic activity and marked resorption. Results at 4 and 8 weeks revealed dense osteoid and bone in the voids with progressive bony healing. Control defects showed no osteoclastic activity with little to no bony healing. Conclusion. Increasing the local rhBMP-2 concentration by overfilling the defect with rhBMP-2/ACS or hyper-concentrating the rhBMP-2 solution on the absorbable collagen sponge led to a concentration-dependent osteoclastic resorption of peri-implant bone. The osteoclastic effect was transient, and progressive healing took place over the 8-week survival period

EMELI 1.0: An Experimental Smart Modeling Framework For Automatic Coupling Of Self-Describing Models

EMELI (Experimental Modeling Environment for Linking and Interoperability) is a modeling framework written in Python that was designed to explore the possibility of smart modeling frameworks. As defined here, a smart modeling framework is one that makes it easy for users to couple reusable component models to create new, composite models through the use of a standardized model interface and standardized model metadata. Users make selections from a repository of component models that each provide a CSDMS Basic Model Interface (BMI) for self-description and model control. EMELI then (1) creates a framework object that serves as a container for the component models, (2) instantiates the selected component models as objects in the framework, (3) checks whether the chosen component models are compatible and together provide a complete composite model (i.e. whether every component model can get the variables it needs from one of the other models in the selected set) and then (4) runs the model, automatically passing required variables (or references) between the coupled components as necessary and automatically adjusting for differences between the component models, such as time-stepping scheme and units. EMELI demonstrates an attractive mechanism for coupling heterogeneous models after they have undergone a relatively small amount of additional preparation while also helping to prevent inappropriate couplings

Stochastic geometry with applications to river networks

Empirical observations have established connections between river network geometry and various hydrophysical quantities of interest. Since rivers can be decomposed into basic components known as links, one would like to understand the physical processes at work in link formation and maintenance. The author develops a natural stochastic geometric model for this problem, for the particular type of link known as exterior links. In the model, the distribution of distance from a uniformly distributed point to a fixed graph is computed. This model yields an approximate expression for the distribution of length of exterior links that incorporates junction angles and drainage density, and compares favorably with observed length distributions. The author goes on to investigate related mathematical questions of independent interest, such as the case where the previously mentioned graph is itself a realization of a random process, and in so doing derives a formula for the first contact distribution of a general random Voronoi tesselation (also associated with the names of Dirichlet and Thiessen). Since this random tesselation is a natural starting point for modelling spatial processes in a wide variety of fields, these results should find immediate applications. It is also shown how these results can be interpreted as a generalization of a classical problem considered by Buffon

Satellite-Based Management Tool for Oak Savanna Ecosystem Restoration

The structure and function of oak Quercus spp. savanna ecosystems in the North American Midwest were originally maintained by an active disturbance regime (often fire). Subsequent reductions in the frequency of disturbance after European settlement have facilitated rapid, regional conversion of these ecosystems to more closed-canopy forest. Hence, regional-scale management strategies are now needed to restore critical spatial gradients of light, temperature, soil moisture, and soil organic matter for recovery and sustenance of the unique mosaic of understory grass and forb species assemblages that define oak savannas. Tree species composition, distribution, mortality, basal area, and canopy cover are important forest structural parameters that are intrinsically linked to oak savanna restoration ecology. In this benchmark study, we seek to determine whether Landsat-based monitoring protocols can be developed as a tool to guide and monitor regional-scale restoration and management efforts. Using the Sherburne National Wildlife Refuge in central Minnesota as a test case, ground-based forest-structure data were collected and used with multitemporal Landsat sensor data and iterative exclusion partial least-squares regression to calibrate six predictive overstory structure models. Model calibrations produced moderate- to high-accuracy results with respective adjusted coefficient of determination and root mean-squared error values as follows: 0.859, 9.3% (canopy cover); 0.855, 2.95 m2 ha−1 (total basal area); 0.741, 11.6% (red oaks relative basal area); 0.781, 11.9% (bur oak relative basal area); 0.861, 3.20 m2 ha−1 (living oak basal area); and 0.833, 9.1% (dead oak relative basal area). We used the resulting structure models for the Sherburne test site to demonstrate how these data could be applied to help managers prioritize areas within management zones for restorative treatments. Although our Sherburne oak savanna test ecosystem is small (12,424 ha) compared with the size of a full Landsat scene (3.4 million ha), resulting structure models can be extended to the whole Landsat scene, which demonstrates how such modeling protocols can be used for repeated (e.g., annual to decadal), regional-scale analysis and assessment to improve management, planning, and implementation of oak savanna restoration efforts elsewhere

Evaluation of catastrophic musculoskeletal injuries in Thoroughbreds and Quarter Horses at three Midwestern racetracks

Objective—To determine the incidence of and compare the types of catastrophic musculoskeletal injuries (CMIs) sustained in Thoroughbreds and Quarter Horses during racing at 3 Midwestern racetracks from 2000 to 2006. Design—Retrospective cohort study. Animals—139 Thoroughbred and 50 Quarter Horse racehorses euthanized because of CMIs. Procedures—Veterinary officials from 3 Midwestern racing jurisdictions provided injury reports for Thoroughbreds and Quarter Horses that sustained CMIs (which required euthanasia) and the total number of race starts for each year. The number of CMIs/1,000 starts was determined for each racetrack. Past performance reports for each horse with a CMI were evaluated. Results—The total number of race starts (both breeds) at the 3 racetracks from 2000 through 2006 was 129,460, with an overall incidence of 1.46 CMIs/1,000 race starts. Incidences of CMIs among racetracks were similar. Of horses that sustained a CMI, the median age of Thoroughbreds at first race was 3 years, compared with a median age of 2 years for Quarter Horses. A larger proportion of Thoroughbreds sustained a CMI in a claiming race than did Quarter Horses, and a larger proportion of Quarter Horses sustained a CMI in a futurity trial than did Thoroughbreds. The most common site for CMIs in Thoroughbreds was the left forelimb (69/124 [55.6%]), whereas most CMIs in Quarter Horses involved the right forelimb (18/30 [60.0%]). Conclusions and Clinical Relevance—Differences identified between CMIs in Thoroughbred and Quarter Horse racehorses should allow veterinarians to focus on horses and anatomic regions of greatest risk of CMI during racing

The influence of droplet size and biodegradation on the transport of subsurface oil droplets during the Deepwater Horizon: a model sensitivity study

A better understanding of oil droplet formation, degradation, and dispersal in deep waters is needed to enhance prediction of the fate and transport of subsurface oil spills. This research evaluates the influence of initial droplet size and rates of biodegradation on the subsurface transport of oil droplets, specifically those from the Deepwater Horizon oil spill. A three-dimensional coupled model was employed with components that included analytical multiphase plume, hydrodynamic and Lagrangian models. Oil droplet biodegradation was simulated based on first order decay rates of alkanes. The initial diameter of droplets (10–300 μm) spanned a range of sizes expected from dispersant-treated oil. Results indicate that model predictions are sensitive to biodegradation processes, with depth distributions deepening by hundreds of meters, horizontal distributions decreasing by hundreds to thousands of kilometers, and mass decreasing by 92–99% when biodegradation is applied compared to simulations without biodegradation. In addition, there are two- to four-fold changes in the area of the seafloor contacted by oil droplets among scenarios with different biodegradation rates. The spatial distributions of hydrocarbons predicted by the model with biodegradation are similar to those observed in the sediment and water column, although the model predicts hydrocarbons to the northeast and east of the well where no observations were made. This study indicates that improvement in knowledge of droplet sizes and biodegradation processes is important for accurate prediction of subsurface oil spills.National Science Foundation (U.S.) (RAPID: Deepwater Horizon Grant OCE-1048630)National Science Foundation (U.S.) (RAPID: Deepwater Horizon Grant OCE-1044573)National Science Foundation (U.S.) (RAPID: Deepwater Horizon Grant CBET-1045831)Gulf of Mexico Research Initiativ

Water and Land-surface Feedbacks in a Polygonal Tundra Environment

The Arctic, including Alaska, is currently experiencing an unprecedented degree of environmental change with increases in both the mean annual surface temperature and precipitation. These observed changes in the climate regime has resulted in a permafrost condition that is particularly sensitive to changes in both Changes in the surface energy balance and water balances and is susceptible to degradation. Thermokarst topography forms whenever ice-rich permafrost thaws and the ground subsides into the resulting voids. Extensive areas of thermokarst activity are currently being observed throughout the arctic and sub-arctic environments. The important processes involved with thermokarsting include surface ponding, surface subsidence, changes in drainage patterns, and related erosion. In this research, we are applying the land-surface evolution model, ERODE (http://csdms.colorado.edu/wiki/Model:Erode), to an area dominated by low- center, ice-wedge polygons. We are modifying the ERODE model to include land surface subsistence in areas where the maximum active layer depth exceeds the protective layer – the layer of soil above ice-rich soils that acts as a buffer to surface energy processes. The goal of this modeling study is to better understand and quantify the development of thermokarst features in the polygonal tundra environment, emphasizing the resulting feedbacks and connections between hydrologic processes and a dynamic surface topography. Further, we are working on understanding the balance between thermal and mechanical processes with regard to thermokarst processes. This unique application of a landscape evolution model may provide valuable insight related to the rates and spatial extent of thermokarst development and the subsequent hydrologic responses to degrading permafrost in a changing climate.Office of Biological and Environmental Research, Department of Energy Office of Science, Alaska Climate Science Cente

Understanding the experience of initiating community-based group physical activity by people with serious mental illness: a systematic review using a meta-ethnographic approach

Background People living with serious mental illness (SMI) experience debilitating symptoms that worsen their physical health and quality of life. Regular physical activity (PA) may bring symptomatic improvements and enhance wellbeing. When undertaken in community-based group settings, PA may yield additional benefits such as reduced isolation. Initiating PA can be difficult for people with SMI and so PA engagement is commonly low. Designing acceptable and effective PA programmes requires a better understanding of the lived experiences of PA initiation among people with SMI. Methods This systematic review of qualitative studies used the meta-ethnography approach by Noblit and Hare (1988). Electronic databases were searched from inception to November 2017. Eligible studies used qualitative methodology; involved adults (≥18 years) with schizophrenia, bipolar affective disorder, major depressive disorder or psychosis; reported community-based group PA; and captured the experience of PA initiation, including key features of social support. Study selection and quality assessment was performed by four reviewers. Results Sixteen studies were included in the review. We identified a ‘journey' that depicted a long sequence of phases involved in initiating PA. The journey demonstrated the thought processes, expectations, barriers and support needs of people with SMI. In particular, social support from a trusted source played an important role in getting people to the activity, both physically and emotionally. Discussion The journey illustrated that initiation of PA for people with SMI is a long complex transition. This complex process needs to be understood before ongoing participation in PA can be addressed

An intelligent interface for integrating climate, hydrology, agriculture, and socioeconomic models

Understanding the interactions between natural processes and human activities poses major challenges as it requires the integration of models and data across disparate disciplines. It typically takes many months and even years to create valid end-to-end simulations as different models need to be configured in consistent ways and generate data that is usable by other models. MINT is a novel framework for model integration that captures extensive knowledge about models and data and aims to automatically compose them together. MINT guides a user to pose a well-formed modeling question, select and configure appropriate models, find and prepare appropriate datasets, compose data and models into end-to-end workflows, run the simulations, and visualize the results. MINT currently includes hydrology, agriculture, and socioeconomic models.Office of the VP for Researc