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Comparison of [ 11 C]TZ1964B and [ 18 F]MNI659 for PET imaging brain PDE10A in nonhuman primates
Abstract Phosphodiesterase 10A ( PDE 10A) inhibitors show therapeutic effects for diseases with striatal pathology. PET radiotracers have been developed to quantify in vivo PDE 10A levels and target engagement for therapeutic interventions. The aim of this study was to compare two potent and selective PDE 10A radiotracers, [ 11 C] TZ 1964B and [ 18 F] MNI 659 in the nonhuman primate ( NHP ) brain. Double scans in the same cynomolgus monkey on the same day were performed after injection of [ 11 C] TZ 1964B and [ 18 F] MNI 659. Specific uptake was determined in two ways: nondisplaceable binding potential ( BP ND ) was calculated using cerebellum as the reference region and the PDE ‐10A enriched striatum as the target region of interest ( ROI ); the area under the time–activity curve ( AUC ) for the striatum to cerebellum ratio was also calculated. High‐performance liquid chromatography ( HPLC ) analysis of solvent‐extracted NHP plasma identified the percentage of intact tracer versus radiolabeled metabolites samples post injection of each radiotracer. Both radiotracers showed high specific accumulation in NHP striatum. [ 11 C] TZ 1964B has higher striatal retention and lower specific striatal uptake than [ 18 F] MNI 659. The BP ND estimates of [ 11 C] TZ 1964B were 3.72 by Logan Reference model (Logan REF ) and 4.39 by simplified reference tissue model ( SRTM ); the BP ND estimates for [ 18 F] MNI 659 were 5.08 (Logan REF ) and 5.33 ( SRTM ). AUC ratios were 5.87 for [ 11 C] TZ 1964B and 7.60 for [ 18 F] MNI 659. Based on BP ND values in NHP striatum, coefficients of variation were ~10% for [ 11 C] TZ 1964B and ~30% for [ 18 F] MNI 659. Moreover, the metabolism study showed the percentage of parent compounds were ~70% for [ 11 C] TZ 1964B and ~50% for [ 18 F] MNI 659 60 min post injection. These data indicate that either [ 11 C] TZ 1964B or [ 18 F] MNI 659 could serve as suitable PDE 10A PET radiotracers with distinguishing features for particular clinical application.
Kinetic modeling of [ 18 F]V AT , a novel radioligand for positron emission tomography imaging vesicular acetylcholine transporter in non‐human primate brain
Abstract Molecular imaging of vesicular acetylcholine transporter ( VACh T) in the brain provides an important cholinergic biomarker for the pathophysiology and treatment of dementias including Alzheimer's disease. In this study, kinetics modeling methods were applied and compared for quantifying regional brain uptake of the VACh T‐specific positron emission tomography radiotracer, ((−)‐(1‐(‐8‐(2‐fluoroethoxy)‐3‐hydroxy‐1,2,3,4‐tetrahydronaphthalen‐2‐yl)piperidin‐4‐yl)(4‐fluorophenyl)‐methanone) ([ 18 F]V AT ) in macaques. Total volume distribution ( V T ) estimates were compared for one‐tissue compartment model (1 TCM ), two‐tissue compartment model (2 TCM ), Logan graphic analysis (LoganA IF ) and multiple linear analysis (M A 1) with arterial blood input function using data from three macaques. Using the cerebellum‐hemispheres as the reference region with data from seven macaques, three additional models were compared: reference tissue model ( RTM ), simplified RTM ( SRTM ), and Logan graphic analysis (Logan REF ). Model selection criterion indicated that a) 2 TCM and SRTM were the most appropriate kinetics models for [ 18 F]V AT ; and b) S RTM was strongly correlated with 2 TCM (Pearson's coefficients r > 0.93, p < 0.05). Test–retest studies demonstrated that [ 18 F]V AT has good reproducibility and reliability ( TRV < 10%, ICC > 0.72). These studies demonstrate [ 18 F]V AT is a promising VACh T positron emission tomography tracer for quantitative assessment of VACh T levels in the brain of living subjects. image
Mesoscale to Microscale Coupling for a Wind Ramp Case over Complex Terrain
Within the wind energy community, it has become increasingly important to simulate realistic weather events at high fidelity in order to improve wind turbine design, wind farm efficiency, and power forecasting. One of the major difficulties in simulating atmospheric events with numerical models at high fidelity is in accurately transitioning from the mesoscale to the microscale. The mesoscale flow, when input into the large-eddy simulation (LES) domain, will be free of resolved turbulence; needing sufficient time and space (known as fetch) for resolved-scale turbulence to develop. In order to reduce this fetch, several methods exist in which the temperature field, wind field, or both, are stochastically perturbed in order to accelerate the generation of turbulence. However, for cases involving complex terrain, it remains unclear if these perturbation processes are necessary, and if the interaction of the flow over the terrain, alone, is sufficient to generate adequate turbulence. In this study, a wind ramp event observed at the National Wind Technology Center (NWTC) outside of Boulder, CO is simulated first with a mesoscale model and then, using the simulated mesoscale solution as initial and boundary conditions, within a microscale LES solver. The mesoscale solution generated by the Weather Research and Forecasting (WRF) model accurately captures the wind ramp event with only a slight temporal shift and a small temperature bias when compared to the meteorological towers in the NWTC site. This information is then taken as the initial and boundary conditions within the Simulator for Wind Farm Applications (SOWFA) microscale LES model with varying terrain inputs. These inputs include the high-resolution (roughly 30 m grid spacing) terrain data from the Shuttle Radar Topography Mission (SRTM) (Figure 1a), as well as, three intermediate terrain resolution data sets produced by applying a uniform convolution window to the SRTM data with varying window sizes (Figure 1b-d). These are compared to the WRF terrain data interpolated to the high-resolution microscale grid (Figure 1e) in order to determine the impact of low-resolution (about 1 km grid spacing) terrain data on turbulence generation. The wind field is compared at several heights and distances along the dominant wind flow axis between each of the terrain cases. It is found that the development of turbulence across the domain is accelerated as terrain information increases in fidelity. Further, because this ramp event at the location of interest is largely influenced by the interaction of the short-wave trough with the terrain, as the topographic information decreases in fidelity the accuracy of the ramp event is decreased. To make generalizations and describe the benefits and shortcomings of this approach, several of the existing perturbation techniques are employed and compared to that of turbulence generation through topographic features.
Global River Topology (GRIT): A Bifurcating River Hydrography
Existing global river networks underpin a wide range of hydrological applications but do not represent channels with divergent river flows (bifurcations, multi‐threaded channels, canals), as these features defy the convergent flow assumption that elevation‐derived networks (e.g., HydroSHEDS, MERIT Hydro) are based on. Yet, bifurcations are important features of the global river drainage system, especially on large floodplains and river deltas, and are also often found in densely populated regions. Here we developed the first raster and vector‐based Global RIver Topology that not only represents the tributaries of the global drainage network but also the distributaries, including multi‐threaded rivers, canals and deltas. We achieve this by merging a 30 m Landsat‐based river mask with elevation‐generated streams to ensure a homogeneous drainage density outside of the river mask for rivers narrower than approximately 30 m. Crucially, we employ the new 30 m digital terrain model, FABDEM, based on TanDEM‐X, which shows greater accuracy over the traditionally used SRTM derivatives. After vectorization and pruning, directionality is assigned by a series of elevation, flow angle and continuity approaches. The new global network and its attributes are validated using gauging stations, comparison with existing networks, and randomized manual checks. The new network represents 19.6 million km of streams and rivers with drainage areas greater than 50 km 2 and includes 67,495 bifurcations. With the advent of hyper‐resolution modeling and artificial intelligence, GRIT is expected to greatly improve the accuracy of many river‐based applications such as flood forecasting, water availability and quality simulations, or riverine habitat mapping.
Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya
The sensitive ecosystem of the central Himalayan (CH) region, which is experiencing enhanced stress from anthropogenic forcing, requires adequate atmospheric observations and an improved representation of the Himalaya in the models. However, the accuracy of atmospheric models remains limited in this region due to highly complex mountainous topography. This article delineates the effects of spatial resolution on the modeled meteorology and dynamics over the CH by utilizing the Weather Research and Forecasting (WRF) model extensively evaluated against the Ganges Valley Aerosol Experiment (GVAX) observations during the summer monsoon. The WRF simulation is performed over a domain (d01) encompassing northern India at 15 km x 15 km resolution and two nests (d02 at 5 km x 5 km and d03 at 1 km x 1 km) centered over the CH, with boundary conditions from the respective parent domains. WRF simulations reveal higher variability in meteorology, e.g., relative humidity (RH = 70.3%-96.1%) and wind speed (WS = 1.1-4.2m s(-1)), compared to the ERA-Interim reanalysis (RH D 80.0%-85.0%, WS D 1.2-2.3m s(-1)) over northern India owing to the higher resolution. WRF-simulated temporal evolution of meteorological variables is found to agree with balloon-borne measurements, with stronger correlations aloft (r = 0.44-0.92) than those in the lower troposphere (r = 0.18-0.48). The model overestimates temperature (warm bias by 2.8 degrees C) and underestimates RH (dry bias by 6.4 %) at the surface in d01. Model results show a significant improvement in d03 (P = 827.6 hPa, T = 19.8 degrees C, RH = 92.3 %), closer to the GVAX observations (P = 801.4 hPa, T = 19.5 degrees C, RH = 94.7 %). Interpolating the output from the coarser domains (d01, d02) to the altitude of the station reduces the biases in pressure and temperature; however, it suppresses the diurnal variations, highlighting the importance of well-resolved terrain (d03). Temporal variations in near-surface P, T, and RH are also reproduced by WRF in d03 to an extent (r>0:5). A sensitivity simulation incorporating the feedback from the nested domain demonstrates the improvement in simulated P, T, and RH over the CH. Our study shows that the WRF model setup at finer spatial resolution can significantly reduce the biases in simulated meteorology, and such an improved representation of the CH can be adopted through domain feedback into regional-scale simulations. Interestingly, WRF simulates a dominant easterly wind component at 1 km x 1 km resolution (d03), which is missing in the coarse simulations; however, the frequency of southeasterlies remains underestimated. The model simulation implementing a highresolution (3 s) topography input (SRTM) improved the prediction of wind directions; nevertheless, further improvements are required to better reproduce the observed local-scale dynamics over the CH.