Acute and chronic electrical activation of baroreceptor afferents in awake and anesthetized subjects

Electrical stimulation of baroreceptor afferents was used in the 1960's in several species, including human beings, for the treatment of refractory hypertension. This approach bypasses the site of baroreceptor mechanosensory transduction. Chronic electrical stimulation of arterial baroreceptors, particularly of the carotid sinus nerve (Hering's nerve), was proposed as an ultimate effort to treat refractory hypertension and angina pectoris due to the limited nature of pharmacological therapy available at that time. Nevertheless, this approach was abandoned in the early 1970's due to technical limitations of implantable devices and to the development of better-tolerated antihypertensive medications. More recently, our laboratory developed the technique of electrical stimulation of the aortic depressor nerve in conscious rats, enabling access to hemodynamic responses without the undesirable effect of anesthesia. In addition, electrical stimulation of the aortic depressor nerve allows assessment of the hemodynamic responses and the sympathovagal balance of the heart in hypertensive rats, which exhibit a well-known decrease in baroreflex sensitivity, usually attributed to baroreceptor ending dysfunction. Recently, there has been renewed interest in using electrical stimulation of the carotid sinus, but not the carotid sinus nerve, to lower blood pressure in conscious hypertensive dogs as well as in hypertensive patients. Notably, previous undesirable technical outcomes associated with electrical stimulation of the carotid sinus nerve observed in the 1960's and 1970's have been overcome. Furthermore, promising data have been recently reported from clinical trials that evaluated the efficacy of carotid sinus stimulation in hypertensive patients with drug resistant hypertension.FAPESPCNPqCoordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES

A Reassessment of North American River Basin Cool-Season Precipitation: Developments From a New Mountain Climatology Data Set

Characterizing hydrological processes on large scales is challenging due to limitations of observational networks, remoting sensing platforms, and modeling techniques. Water balances have larger uncertainties in mountain regions, where orographic processes produce high spatial variability in precipitation patterns and snow accumulation. Recent work suggests current water budgets underestimate mountain snow water storage, perhaps indicating biases in modeled precipitation. We assess whether global hydroclimate data sets underestimate precipitation for six North American watersheds, ranging from 3–70% mountainous. By selecting a single representative year for each watershed, we compare relatively high-resolution precipitation estimates from the Weather Research and Forecasting (WRF) regional climate model with four global products: Modern-Era Retrospective Analysis for Research and Applications, version 2, the Global Land Data Assimilation System, the Global Precipitation Climatology Project, and the Climate Research Unit's climate data set. Comparisons to WRF precipitation suggest that observation-based gridded data products do not produce reasonable estimates of watershed-scale cool-season precipitation, underestimating by 1–69%. The Global Precipitation Climatology Project and the Climate Research Unit data set have average biases of −26% and −38%, respectively. The Modern-Era Retrospective Analysis for Research and Applications version 2 and the Global Land Data Assimilation System show smaller underestimates relative to WRF (−17% and −21%, respectively), with nearly all mean bias from the mountains (underestimated by 27% and 39%) rather than the topographically simpler lowlands (underestimated by 5% and 2%). We suggest global products fail to capture orographic enhancement of precipitation, resulting in large underestimates of precipitation, snowfall, and snow water storage in mountains of selected North American watersheds, which highlights the need for more accurate precipitation estimates to accurately assess spatiotemporal variations in the water cycle

Characterizing Biases in Mountain Snow Accumulation From Global Data Sets

Mountain snow has a fundamental role in regional water budgets through its seasonal accumulation, storage, and melt. However, characterizing snow accumulation over large regions remains difficult because of limited observational networks and the inability of available satellite instruments to remotely sense snow depth or water equivalent in mountains. Models offer some ability to estimate snow water storage (SWS) on mountain range to continental scales. Here we compare four commonly used global data sets to understand whether there is a consensus regarding mountain SWS estimates among them. The data sets—European Centre for Medium-Range Weather Forecasts Reanalysis-Interim, Global Land Data Assimilation System, Modern-Era Retrospective Analysis for Research and Applications version 2, and Variable Infiltration Capacity—agree to within ±36% of the four–data set average for total global SWS. When mountain areas are extracted using a new seasonal mountain snow classification data set, the four data products have more agreement, where all are within ±21% of the seasonal SWS for mountain regions. However, when compared to high-resolution (9 km) simulations of SWS from the Weather Research and Forecasting (WRF) regional model, the four global products differ from WRF-estimated North American mountain snow accumulation by 40–66%, with a negative bias up to 651 km3, comparable to the annual streamflow of the Mississippi River. If we extend the North America SWS bias to global mountains, the global data sets may miss as much as 1,500 km3 of SWS, equivalent to 4% of the flow in all the world's rivers. The potential difference of SWS suggests more work must be done to characterize water resources in snow-dominated regions, particularly in mountains

Comparison of methods to estimate snow water equivalent at the mountain range scale: A case study of the California Sierra Nevada

Despite the importance of snow in global water and energy budgets, estimates of global mountain snow water equivalent (SWE) are not well constrained. Two approaches for estimating total range-wide SWE over Sierra Nevada, California, are assessed: 1) global/hemispherical models and remote sensing and models available for continental United States (CONUS) plus southern Canada (CONUS+) available to the scientific community and 2) regional climate model simulations via the Weather Research and Forecasting (WRF) Model run at 3, 9, and 27 km. As no truth dataset provides total mountain range SWE, these two approaches are compared to a "reference" SWE consisting of three published, independent datasets that utilize/validate against in situ SWE measurements. Model outputs are compared with the reference datasets for three water years: 2005 (high snow accumulation), 2009 (average), and 2014 (low). There is a distinctive difference between the reference/WRF datasets and the global/CONUS+ daily estimates of SWE, with the former suggesting up to an order of magnitude more snow. Results are qualitatively similar for peak SWE and 1 April SWE for all three years. Analysis of SWE time series indicates that lower SWE for global and CONUS+ datasets is likely due to precipitation, rain/snow partitioning, and ablation parameterization differences. It is found that WRF produces reasonable (within 50%) estimates of total mountain range SWE in the Sierra Nevada, while the global and CONUS+ datasets underestimate SWE

The Surface Water and Ocean Topography (SWOT) Mission River Database (SWORD): A Global River Network for Satellite Data Products

The upcoming Surface Water and Ocean Topography (SWOT) satellite mission, planned to launch in 2022, is the first mission to focus on measuring hydrological processes in Earth's surface water. As such, SWOT will vastly expand observations of global rivers ≥100 m wide. SWOT will provide a variety of data products, including a global vector river product containing water surface elevation (WSE), width, slope, and estimated discharge. Practical application and consistency of the SWOT vector products requires a prior global river network database divided into reaches. Here, we introduce the SWOT River Database (SWORD). SWORD will serve as the framework for the SWOT river vector products consisting of river reaches (∼10 km long) and nodes (∼200 m spacing). We generate SWORD by combining several global river- and satellite-related data sets into one congruent product. When defining river reaches, we incorporate natural and human-created river obstructions, basin boundaries, tributary junctions, and SWOT orbit track information. SWORD contains a total of 213,485 reaches and 10.7 million nodes. Globally, 77.3% of river reach lengths are between 10 and 20 km with a median reach length of 10.5 km. 95% of river reaches ≥10 km will have sufficient SWOT observations to provide discharge estimates at least once per orbit cycle. SWORD also contains many useful hydrologic and morphological attributes and is designed to be expandable in the future. Even before the launch of SWOT, it can serve as a framework for global hydrologic analyses using models, in situ measurements, and additional satellite observations

A New Estimate of North American Mountain Snow Accumulation From Regional Climate Model Simulations

Despite the importance of mountain snowpack to understanding the water and energy cycles in North America's montane regions, no reliable mountain snow climatology exists for the entire continent. We present a new estimate of mountain snow water equivalent (SWE) for North America from regional climate model simulations. Climatological peak SWE in North America mountains is 1,006 km3, 2.94 times larger than previous estimates from reanalyses. By combining this mountain SWE value with the best available global product in nonmountain areas, we estimate peak North America SWE of 1,684 km3, 55% greater than previous estimates. In our simulations, the date of maximum SWE varies widely by mountain range, from early March to mid-April. Though mountains comprise 24% of the continent's land area, we estimate that they contain ~60% of North American SWE. This new estimate is a suitable benchmark for continental- and global-scale water and energy budget studies

Elastase-2, a tissue alternative pathway for angiotensin II generation, plays a role in circulatory sympathovagal balance in mice

In vitro and ex vivo experiments indicate that elastase-2 (ELA-2), a chymotrypsin-serine protease elastase family member 2A, is an alternative pathway for angiotensin II (Ang II) generation. However, the role played by ELA-2 in vivo is unclear. We examined ELA-2 knockout (ELA-2KO) mice compared to wild-type (WT) mice and determined whether ELA-2 played a role in hemodynamics [arterial pressure (AP) and heart rate (HR)], cardiocirculatory sympathovagal balance and baroreflex sensitivity. The variability of systolic arterial pressure (SAP) and pulse interval (PI) for evaluating autonomic modulation was examined for time and frequency domains (spectral analysis), whereas a symbolic analysis was also used to evaluate PI variability. In addition, baroreflex sensitivity was examined using the sequence method. Cardiac function was evaluated echocardiographically under anesthesia. The AP was normal whereas the HR was reduced in ELA-2KO mice (425 ± 17 vs. 512 ± 13 bpm from WT). SAP variability and baroreflex sensitivity were similar in both strains. The LF power from the PI spectrum (33.6 ± 5 vs. 51.8 ± 4.8 nu from WT) and the LF/HF ratio (0.60 ± 0.1 vs. 1.45 ± 0.3 from WT) were reduced, whereas the HF power was increased (66.4 ± 5 vs. 48.2 ± 4.8 nu from WT) in ELA-2KO mice, indicating a shift toward parasympathetic modulation of HR. Echocardiographic examination showed normal fractional shortening and an ejection fraction in ELA-2KO mice; however, the cardiac output, stroke volume, and ventricular size were reduced. These findings provide the first evidence that ELA-2 acts on the sympathovagal balance of the heart, as expressed by the reduced sympathetic modulation of HR in ELA-2KO mice

Colossal dielectric permittivity of BaTiO3-based nanocrystalline ceramics sintered by spark plasma sintering

In pursuit of high permittivity materials for electronic application, there has been a considerable interest recently in the dielectric properties of various perovskite oxides like calcium copper titanate or lanthanum doped barium titanate. When processed in a particular way, this later material present at ambient temperature and at f=1 kHz unusual interesting dielectric properties, a so called “colossal” permittivity value up to several 106 with relatively low dielectric losses. Moreover and contrary to what is classically expected and evidenced for this type of materials, no temperature dependence is observed. This behavior is observed in nanopowders based ceramics. An assumption to explain the observed properties is proposed. These results have important technological applications, since these nanoceramics open a new route to the fabrication of very thin dielectric films

Global Relationships Between River Width, Slope, Catchment Area, Meander Wavelength, Sinuosity, and Discharge

Using river centerlines created with Landsat images and the Shuttle Radar Topography Mission digital elevation model, we created spatially continuous maps of mean annual flow river width, slope, meander wavelength, sinuosity, and catchment area for all rivers wider than 90 m located between 60°N and 56°S. We analyzed the distributions of these properties, identified their typical ranges, and explored relationships between river planform and slope. We found width to be directly associated with the magnitude of meander wavelength and catchment area. Moreover, we found that narrower rivers show a larger range of slope and sinuosity values than wider rivers. Finally, by comparing simulated discharge from a water balance model with measured widths, we show that power laws between mean annual discharge and width can predict width typically to −35% to +81%, even when a single relationship is applied across all rivers with discharge ranging from 100 to 50,000 m3/s

Anticipated improvements to river surface elevation profiles from the surface water and ocean topography mission

Existing publicly available digital elevation models (DEMs) provide global-scale data but are often not precise enough for studying processes that depend on small-scale topographic features in rivers. For example, slope breaks and knickpoints in rivers can be important in understanding tectonic processes, and riffle-pool structures are important drivers of riverine ecology. More precise data (e.g., lidar) are available in some areas, but their spatial extent limits large-scale research. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission is planned to launch in 2021 and will provide measurements of elevation and inundation extent of surface waters between 78° north and south latitude on average twice every 21 days. We present a novel noise reduction method for multitemporal river water surface elevation (WSE) profiles from SWOT that combines a truncated singular value decomposition and a slope-constrained least-squares estimator. We use simulated SWOT data of 85–145 km sections of the Po, Sacramento, and Tanana Rivers to show that 3–12 months of simulated SWOT data can produce elevation profiles with mean absolute errors (MAEs) of 5.38–12.55 cm at 100–200 m along-stream resolution. MAEs can be reduced further to 4–11 cm by averaging all observations. The average profiles have errors much lower than existing DEMs, allowing new advances in riverine research globally. We consider two case studies in geomorphology and ecology that highlight the scientific value of the more accurate in-river DEMs expected from SWOT. Simulated SWOT elevation profiles for the Po reveal convexities in the river longitudinal profile that are spatially coincident with the upward projection of blind thrust faults that are buried beneath the Po Plain at the northern termination of the Apennine Mountains. Meanwhile, simulated SWOT data for the Sacramento River reveals locally steep sections of the river profile that represent important habitat for benthic invertebrates at a spatial scale previously unrecognizable in large-scale DEMs presently available for this river