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The dentate gyrus (DG), a key hippocampal subregion in memory processing, generally resists phosphorylated tau accumulation in the amnestic dementia of the Alzheimer’s type due to Alzheimer’s disease (DAT-AD), but less is known about the susceptibility of the DG to other tauopathies. Here, we report stereologic densities of total DG neurons and tau inclusions in thirty-two brains of human participants with autopsy-confirmed tauopathies with distinct isoform profiles—3R Pick’s disease (PiD, N = 8), 4R corticobasal degeneration (CBD, N = 8), 4R progressive supranuclear palsy (PSP, N = 8), and 3/4R AD (N = 8). All participants were diagnosed during life with primary progressive aphasia (PPA), an aphasic clinical dementia syndrome characterized by progressive deterioration of language abilities with spared non-language cognitive abilities in early stages, except for five patients with DAT-AD as a comparison group. 51% of total participants were female. All specimens were stained immunohistochemically with AT8 to visualize tau pathology, and PPA cases were stained for Nissl substance to visualize neurons. Unbiased stereological analysis was performed in granule and hilar DG cells, and inclusion-to-neuron ratios were calculated. In the PPA group, PiD had highest mean total (granule + hilar) densities of DG tau pathology (p < 0.001), followed by CBD, AD, then PSP. PPA-AD cases showed more inclusions inmore »hilar cells compared to granule cells, while the opposite was true in PiD and CBD. Inclusion-to-neuron ratios revealed, on average, 33% of all DG neurons in PiD cases contained a tau inclusion, compared to ~ 7% in CBD, 2% in AD, and 0.4% in PSP. There was no significant difference between DAT-AD and PPA-AD pathologic tau burden, suggesting that differences in DG burden are not specific to clinical phenotype. We conclude that the DG is differentially vulnerable to pathologic tau accumulation, raising intriguing questions about the structural integrity and functional significance of hippocampal circuits in neurodegenerative dementias.

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As the size of data generated every day grows dramatically, the computational bottleneck of computer systems has shifted toward storage devices. The interface between the storage and the computational platforms has become the main limitation due to its limited bandwidth, which does not scale when the number of storage devices increases. Interconnect networks do not provide simultaneous access to all storage devices and thus limit the performance of the system when executing independent operations on different storage devices. Offloading the computations to the storage devices eliminates the burden of data transfer from the interconnects. Near-storage computing offloads a portion of computations to the storage devices to accelerate big data applications. In this article, we propose a generic near-storage sort accelerator for data analytics, NASCENT2, which utilizes Samsung SmartSSD, an NVMe flash drive with an on-board FPGA chip that processes data in situ. NASCENT2 consists of dictionary decoder, sort, and shuffle FPGA-based accelerators to support sorting database tables based on a key column with any arbitrary data type. It exploits data partitioning applied by data processing management systems, such as SparkSQL, to breakdown the sort operations on colossal tables to multiple sort operations on smaller tables. NASCENT2 generic sort provides 2more »× speedup and 15.2 × energy efficiency improvement as compared to the CPU baseline. It moreover considers the specifications of the SmartSSD (e.g., the FPGA resources, interconnect network, and solid-state drive bandwidth) to increase the scalability of computer systems as the number of storage devices increases. With 12 SmartSSDs, NASCENT2 is 9.9× (137.2 ×) faster and 7.3 × (119.2 ×) more energy efficient in sorting the largest tables of TPCC and TPCH benchmarks than the FPGA (CPU) baseline.« less

In the ion foreshock, hot flow anomalies (HFAs) and foreshock bubbles (FBs) are two types of foreshock transients that have the strongest fluctuations, which can disturb the magnetosphere‐ionosphere system and increase shock acceleration efficiency. They form due to interaction between the foreshock ions and solar wind discontinuities: the direction of the foreshock ion‐driven current and whether it decreases or increases the magnetic field strength behind the discontinuity determine whether the transient's formation can be promoted or suppressed. Thus, to predict the HFA and FB formation and forecast their space weather effects, it is necessary to predict the foreshock ion‐driven current direction. In this study, we derive analytical equations of foreshock ion velocities within discontinuities to estimate foreshock ion‐driven current direction, which provides a quantitative criterion of HFA and FB formation. To validate the criterion, we use Acceleration Reconnection Turbulence & Electrodynamics of Moon's Interaction with the Sun to observe pristine solar wind discontinuities and calculate discontinuity parameters. We use Magnetospheric Multiscale to observe the foreshock ion motion around the discontinuities and show that the data support our model. This study is another step toward a predictive model of HFA and FB formation so that we can forecast their spacemore »weather effects at Earth using solar wind observations at lunar orbit or L1.

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When a solar wind discontinuity interacts with foreshock ions, foreshock transients such as hot flow anomalies and foreshock bubbles can form. These create significant dynamic pressure perturbations disturbing the bow shock, magnetopause, and magnetosphere‐ionosphere system. However, presently these phenomena are not predictable. In the accompanying paper, we derived analytical equations of foreshock ion partial gyration around a discontinuity and the resultant current density. In this study, we utilize the derived current density strength to model the energy conversion from the foreshock ions, which drives the outward motion or expansion of the solar wind plasma away from the discontinuity. We show that the model expansion speeds match those from local hybrid simulations for varying foreshock ion parameters. Using MMS, we conduct a statistical study showing that the model expansion speeds are moderately correlated with the magnetic field strength variations and the dynamic pressure decreases around discontinuities with correlation coefficients larger than 0.5. We use conjunctions between ARTEMIS and MMS to show that the model expansion speeds are typically large for those already‐formed foreshock transients. Our results show that our model can be reasonably successful in predicting significant dynamic pressure disturbances caused by foreshock ion‐discontinuity interactions. We discuss ways to improvemore »the model in the future.

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