4,892 research outputs found

    P2X1 and P2X5 subunits form the functional P2X receptor in mouse cortical astrocytes

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    ATP plays an important role in signal transduction between neuronal and glial circuits and within glial networks. Here we describe currents activated by ATP in astrocytes acutely isolated from cortical brain slices by non-enzymatic mechanical dissociation. Brain slices were prepared from transgenic mice that express enhanced green fluorescent protein under the control of the human glial fibrillary acidic protein promoter. Astrocytes were studied by whole-cell voltage clamp. Exogenous ATP evoked inward currents in 75 of 81 astrocytes. In the majority (~65%) of cells, ATP-induced responses comprising a fast and delayed component; in the remaining subpopulation of astrocytes, ATP triggered a smoother response with rapid peak and slowly decaying plateau phase. The fast component of the response was sensitive to low concentrations of ATP (with EC50 of ~40 nM). All ATP-induced currents were blocked by pyridoxal-phosphate-6-azophenyl-2',4'-disulfonate (PPADS); they were insensitive to ivermectin. Quantitative real-time PCR demonstrated strong expression of P2X1 and P2X5 receptor subunits and some expression of P2X2 subunit mRNAs. The main properties of the ATP-induced response in cortical astrocytes (high sensitivity to ATP, biphasic kinetics, and sensitivity to PPADS) were very similar to those reported for P2X1/5 heteromeric receptors studied previously in heterologous expression systems

    Embedding Principal Component Analysis for Data Reductionin Structural Health Monitoring on Low-Cost IoT Gateways

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    Principal component analysis (PCA) is a powerful data reductionmethod for Structural Health Monitoring. However, its computa-tional cost and data memory footprint pose a significant challengewhen PCA has to run on limited capability embedded platformsin low-cost IoT gateways. This paper presents a memory-efficientparallel implementation of the streaming History PCA algorithm.On our dataset, it achieves 10x compression factor and 59x memoryreduction with less than 0.15 dB degradation in the reconstructedsignal-to-noise ratio (RSNR) compared to standard PCA. More-over, the algorithm benefits from parallelization on multiple cores,achieving a maximum speedup of 4.8x on Samsung ARTIK 710

    Die FORTRAN-77 Version des Karlsruher Programmsystems KAPROS

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