Effect of Keishi-bukuryo-gan on autonomic nervous activity

桂枝茯苓丸の自律神経活動に対する効果を明らかとするために,レーザードプラ血流計,R-R間隔および収縮期血圧のスペクトル解析を用いて検討した。健常者8名を対象とし,自律神経活動の変化を桂枝茯苓丸料と微温湯において統計学的に解析した。桂枝茯苓丸により,皮膚血流量(SBF)は前値に比較して一旦15分後に減少し,90分後に有意に増加した。収縮期血圧低周波成分(SBP-LF)・収縮期血圧成分比(SBP-L/H)は前値に比較して一旦15分後に増加し,60及び90分後に有意に減少した。微温湯では有意な変化はみられなかった。SBFは交感神経活動にともない変化し,SBP-LF及びSBP-L/Hは交感神経活動と関連するとされている。今回の結果は,桂枝茯苓丸が交感神経活動に対する作用を有していることを示唆するものである。 In order to confirm any effects of Keishi-bukuryo-gan (KBG) on the autonomic nervous system, 8 healthy volunteers were evaluated with laser Doppler flowmetry and spectral analysis of the R-R intervals (RR) and systolic blood pressure (SBP). After evaluation of the "oketsu" score and measurement of the electrophysiological parameters (PRE), each subject was administered KBG or hot water. The same parameters were re-measured at 15, 30, 45, 60 and 90 minutes after their administration to each subject. Changes in the parameters after the administration of KBG or hot water were investigated compared with PRE. In the experiment with KBG, skin blood flow (SBF) was increased at 90 min, although it had been significantly decreased at 15 min. By spectral analysis, SBP-low frequency (LF) and SBP-low to high frequency ratio (L/H) were initially increased at 15 min, and then were significantly decreased at 60 and 90 min. As for hot water, there were no significant changes in any of the parameters. It is known that SBF changes with sympathetic nervous activity, and SBP-LF and SBP-L/H reflect sympathetic nervous activity. These results suggest that KBG has certain effects on sympathetic nervous activity

Targeting Lysophosphatidic Acid Signaling Retards Culture-Associated Senescence of Human Marrow Stromal Cells

Marrow stromal cells (MSCs) isolated from mesenchymal tissues can propagate in vitro to some extent and differentiate into various tissue lineages to be used for cell-based therapies. Cellular senescence, which occurs readily in continual MSC culture, leads to loss of these characteristic properties, representing one of the major limitations to achieving the potential of MSCs. In this study, we investigated the effect of lysophosphatidic acid (LPA), a ubiquitous metabolite in membrane phospholipid synthesis, on the senescence program of human MSCs. We show that MSCs preferentially express the LPA receptor subtype 1, and an abrogation of the receptor engagement with the antagonistic compound Ki16425 attenuates senescence induction in continually propagated human MSCs. This anti-aging effect of Ki16425 results in extended rounds of cellular proliferation, increased clonogenic potential, and retained plasticity for osteogenic and adipogenic differentiation. Expressions of p16Ink4a, Rb, p53, and p21Cip1, which have been associated with cellular senescence, were all reduced in human MSCs by the pharmacological inhibition of LPA signaling. Disruption of this signaling pathway was accompanied by morphological changes such as cell thinning and elongation as well as actin filament deformation through decreased phosphorylation of focal adhesion kinase. Prevention of LPA receptor engagement also promoted ubiquitination-mediated c-Myc elimination in MSCs, and consequently the entry into a quiescent state, G0 phase, of the cell cycle. Collectively, these results highlight the potential of pharmacological intervention against LPA signaling for blunting senescence-associated loss of function characteristic of human MSCs

A Case for Offloading Federated Learning Server on Smart NIC

Federated learning is a distributed machine learning approach where local weight parameters trained by clients locally are aggregated as global parameters by a server. The global parameters can be trained without uploading privacy-sensitive raw data owned by clients to the server. The aggregation on the server is simply done by averaging the local weight parameters, so it is an I/O intensive task where a network processing accounts for a large portion compared to the computation. The network processing workload further increases as the number of clients increases. To mitigate the network processing workload, in this paper, the federated learning server is offloaded to NVIDIA BlueField-2 DPU which is a smart NIC (Network Interface Card) that has eight processing cores. Dedicated processing cores are assigned by DPDK (Data Plane Development Kit) for receiving the local weight parameters and sending the global parameters. The aggregation task is parallelized by exploiting multiple cores available on the DPU. To further improve the performance, an approximated design that eliminates an exclusive access control between the computation threads is also implemented. Evaluation results show that the federated learning server on the DPU accelerates the execution time by 1.32 times compared with that on the host CPU with a negligible accuracy loss

Query Recommendation to Draw a Laugh from Web Searchers

iiWAS2019: The 21st International Conference on Information Integration and Web-based Applications & Services Munich Germany December, 2019autho