Extracellular matrix regulates force transduction at VE-cadherin junctions.

Increased tension on VE-cadherin (VE-cad) complexes activates adaptive cell stiffening and local cytoskeletal reinforcement--two key signatures of intercellular mechanotransduction. Here we demonstrate that tugging on VE-cad receptors initiates a cascade that results in downstream integrin activation. The formation of new integrin adhesions potentiates vinculin and actin recruitment to mechanically reinforce stressed cadherin adhesions. This cascade differs from documented antagonistic effects of integrins on intercellular junctions. We identify focal adhesion kinase, Abl kinase, and RhoA GTPase as key components of the positive feedback loop. Results further show that a consequence of integrin involvement is the sensitization of intercellular force transduction to the extracellular matrix (ECM) not by regulating junctional tension but by altering signal cascades that reinforce cell-cell adhesions. On type 1 collagen or fibronectin substrates, integrin subtypes α2ß1 and α5ß1, respectively, differentially control actin remodeling at VE-cad adhesions. Specifically, ECM-dependent differences in VE-cad force transduction mirror differences in the rigidity sensing mechanisms of α2ß1 and α5ß1 integrins. The findings verify the role of integrins in VE-cad force transduction and uncover a previously unappreciated mechanism by which the ECM impacts the mechanical reinforcement of interendothelial junctions.

Noninflammatory Stress-Induced Remodeling of Mandibular Bone: Impact of Age and Pregnancy.

PURPOSE: The impact of noninflammatory stress, such as aging and pregnancy, on human long bone remodeling is well-established, but little is known about the impact of these stressors on oral bones, including the mandibular bone. To begin to fill this gap in our knowledge, we utilized a mouse mandibular model to evaluate the impact of noninflammatory simple stressors, ie, aging and pregnancy, on bone mandibular architecture and bone density in the mandible using micro-CT. MATERIALS AND METHODS: For the present study, mandibles were obtained from both aged and pregnant C57BL/6 mice and analyzed using micro-CT technology. Micro-CT metrics included bone volume fraction (BVF), total volume (TV), tissue density, and apparent density in the mandible on the mandibular area of compact and trabecular bone, in which the teeth are embedded. All bone-related metrics data from aged and pregnant mice were analyzed using ANOVA analysis and visualized in boxplots. RESULTS: Age-dependent bone remodeling occurred over 4 to 18 weeks of age, ie, increases in BVF, TV, BV/TV, as well as tissue and bone density. Evaluation of bone remodeling in breeder mice (repeated pregnancy model) and virgin mice (age-matched controls) at 37 weeks of age demonstrated that breeder mice had a dramatic decline in all bone metrics measured. CONCLUSIONS: This study underscores the need for more research on noninflammatory stress-related mandibular bone remodeling (eg, age and pregnancy), which compromises bone strength and tooth anchoring. The data also underscores loss of alveolar bone height, as in periodontitis, is an important metric for a more complete assessment of bone loss. This report on mice provides essential data that can be applied for oral-maxillofacial surgeons and periodontists when planning for dental implants in patients with such stressors. Periodontitis related bone loss occurs independent of skeletal homeostasis, although osteoporosis may adversely affect alveolar bone height in humans.

Thresholds of lake and reservoir connectivity in river networks control nitrogen removal.

Lakes, reservoirs, and other ponded waters are ubiquitous features of the aquatic landscape, yet their cumulative role in nitrogen removal in large river basins is often unclear. Here we use predictive modeling, together with comprehensive river water quality, land use, and hydrography datasets, to examine and explain the influences of more than 18,000 ponded waters on nitrogen removal through river networks of the Northeastern United States. Thresholds in pond density where ponded waters become important features to regional nitrogen removal are identified and shown to vary according to a ponded waters' relative size, network position, and degree of connectivity to the river network, which suggests worldwide importance of these new metrics. Consideration of the interacting physical and biological factors, along with thresholds in connectivity, reveal where, why, and how much ponded waters function differently than streams in removing nitrogen, what regional water quality outcomes may result, and in what capacity management strategies could most effectively achieve desired nitrogen loading reduction.

A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA.

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50ppb and probability of dissolved oxygen concentration to be below 0.5ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971-2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative impact on nitrate predictions. Three-dimensional visualization indicates that nitrate predictions depend on the probability of anoxic conditions and other factors, and that nitrate predictions generally decreased with increasing groundwater age.

Regional Effects of Agricultural Conservation Practices on Nutrient Transport in the Upper Mississippi River Basin.

Despite progress in the implementation of conservation practices, related improvements in water quality have been challenging to measure in larger river systems. In this paper we quantify these downstream effects by applying the empirical U.S. Geological Survey water-quality model SPARROW to investigate whether spatial differences in conservation intensity were statistically correlated with variations in nutrient loads. In contrast to other forms of water quality data analysis, the application of SPARROW controls for confounding factors such as hydrologic variability, multiple sources and environmental processes. A measure of conservation intensity was derived from the USDA-CEAP regional assessment of the Upper Mississippi River and used as an explanatory variable in a model of the Upper Midwest. The spatial pattern of conservation intensity was negatively correlated (p = 0.003) with the total nitrogen loads in streams in the basin. Total phosphorus loads were weakly negatively correlated with conservation (p = 0.25). Regional nitrogen reductions were estimated to range from 5 to 34% and phosphorus reductions from 1 to 10% in major river basins of the Upper Mississippi region. The statistical associations between conservation and nutrient loads are consistent with hydrological and biogeochemical processes such as denitrification. The results provide empirical evidence at the regional scale that conservation practices have had a larger statistically detectable effect on nitrogen than on phosphorus loadings in streams and rivers of the Upper Mississippi Basin.

Tuned critical avalanche scaling in bulk metallic glasses.

Ingots of the bulk metallic glass (BMG), Zr64.13Cu15.75Ni10.12Al10 in atomic percent (at. %), are compressed at slow strain rates. The deformation behavior is characterized by discrete, jerky stress-drop bursts (serrations). Here we present a quantitative theory for the serration behavior of BMGs, which is a critical issue for the understanding of the deformation characteristics of BMGs. The mean-field interaction model predicts the scaling behavior of the distribution, D(S), of avalanche sizes, S, in the experiments. D(S) follows a power law multiplied by an exponentially-decaying scaling function. The size of the largest observed avalanche depends on experimental tuning-parameters, such as either imposed strain rate or stress. Similar to crystalline materials, the plasticity of BMGs reflects tuned criticality showing remarkable quantitative agreement with the slip statistics of slowly-compressed nanocrystals. The results imply that material-evaluation methods based on slip statistics apply to both crystalline and BMG materials.

Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States.

We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models - 6 for total nitrogen and 6 for total phosphorus - all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long-term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.

A Multi-Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models.

Stream-loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long-term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water-quality model, the flow-bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water-quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.

The Regionalization of National-Scale SPARROW Models for Stream Nutrients.

This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national-scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national-scale and regional-scale information to estimate a hybrid model that imposes cross-region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ±100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models.

Incorporating Uncertainty Into the Ranking of SPARROW Model Nutrient Yields From Mississippi/Atchafalaya River Basin Watersheds.

Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying "high priority" areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient-reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight-digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.

Differences in phosphorus and nitrogen delivery to the Gulf of Mexico from the Mississippi River Basin.

Seasonal hypoxia in the northern Gulf of Mexico has been linked to increased nitrogen fluxes from the Mississippi and Atchafalaya River Basins, though recent evidence shows that phosphorus also influences productivity in the Gulf. We developed a spatially explicit and structurally detailed SPARROW water-quality model that reveals important differences in the sources and transport processes that control nitrogen (N) and phosphorus (P) delivery to the Gulf. Our model simulations indicate that agricultural sources in the watersheds contribute more than 70% of the delivered N and P. However, corn and soybean cultivation is the largest contributor of N (52%), followed by atmospheric deposition sources (16%); whereas P originates primarily from animal manure on pasture and rangelands (37%), followed by corn and soybeans (25%), other crops (18%), and urban sources (12%). The fraction of in-stream P and N load delivered to the Gulf increases with stream size, but reservoir trapping of P causes large local- and regional-scale differences in delivery. Our results indicate the diversity of management approaches required to achieve efficient control of nutrient loads to the Gulf. These include recognition of important differences in the agricultural sources of N and P, the role of atmospheric N, attention to P sources downstream from reservoirs, and better control of both N and P in close proximity to large rivers.

Optomechanical integration method for finite integrals.

We present, for the first time to our knowledge, an optomechanical integration method for finite functions. This technique allows for the integration of any finite function by combining optical and mechanical principals. The integrated function can then be determined using curve fitting methods. Furthermore, the original function can be reproduced through numerical or analytical integration.

The Role of Headwater Streams in Downstream Water Quality.

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth- and higher-order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water-resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters.

Natural background concentrations of nutrients in streams and rivers of the conterminous United States.

Determining natural background concentrations of nutrients in watersheds in the developed world has been hampered by a lack of pristine sampling sites covering a range of climatic conditions and basin sizes. Using data from 63 minimally impacted U.S. Geological Survey reference basins, we developed empirical models of the background yield of total nitrogen (TN) and total phosphorus (TP) from small watersheds as functions of annual runoff, basin size, atmospheric nitrogen deposition rate, and region-specific factors. We applied previously estimated in-stream loss rates to yields from the small watershed models to obtain estimates of background TN and TP yield and concentration throughout the stream/river network in 14 ecoregions of the conterminous United States. Background TN concentration varies from less than 0.02 mg L(-1) in the xeric west to more than 0.5 mg L(-1) along the southeastern coastal plain. Background TP concentration varies from less than 0.006 mg L-(1) in the xeric west to more than 0.08 mg L(-1) in the great plains. TN concentrations in U.S. streams and rivers currently exceed natural background levels by a much larger factor (6.4) than do TP concentrations (2.0). Because of local variation in runoff and other factors, the range of background nutrient concentrations is very large within some nutrient ecoregions. It is likely that background concentrations in some streams in these regions exceed proposed nutrient criteria.