1,066 research outputs found

    Diabetic neuropathy: inhibitory G protein dysfunction involves PKC-dependent phosphorylation of G oα

    Full text link
    We examined the hypothesis that decreased inhibitory G protein function in diabetic neuropathy is associated with increased protein kinase C (PKC)-dependent phosphorylation of the G oα subunit. Streptozotocin-induced diabetic rats were studied between 4 and 8 weeks after onset of diabetes and compared with aged-matched healthy animals as controls. Opioid-mediated inhibition of forskolin-stimulated cyclic AMP was significantly less in dorsal root ganglia (DRGs) from diabetic rats compared with controls. Activation of PKC in DRGs from control rats was associated with a significant decrease in opioid-mediated inhibition of forskolin-stimulated cyclic AMP that was similar to the decrease in inhibition observed in DRGs from diabetic rats. Both basal and PKC-mediated labeling of G oα with 32 P i was significantly less in DRGs from diabetic rats, supporting increased endogenous PKC-dependent phosphorylation of G oα . Probing of immunoprecipitated G oα with an anti-phospho-serine/threonine specific antibody revealed a significant increase in baseline phosphorylation in diabetic DRGs. Activation of PKC produced a significant increase in phosphorylation in control DRGs but no significant increase in G oα in diabetic DRGs. Phosphorylation of PKC-α was increased, PKC-β II was unchanged and PKC-δ decreased in diabetic DRGs. These results suggest that diminished inhibitory G protein function observed in DRGs neurons from diabetic rats involves an isoform-specific PKC-dependent pathway.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66385/1/j.1471-4159.2003.01912.x.pd

    RF-Transformer: A Unified Backscatter Radio Hardware Abstraction

    Full text link
    This paper presents RF-Transformer, a unified backscatter radio hardware abstraction that allows a low-power IoT device to directly communicate with heterogeneous wireless receivers at the minimum power consumption. Unlike existing backscatter systems that are tailored to a specific wireless communication protocol, RF-Transformer provides a programmable interface to the micro-controller, allowing IoT devices to synthesize different types of protocol-compliant backscatter signals sharing radically different PHY-layer designs. To show the efficacy of our design, we implement a PCB prototype of RF-Transformer on 2.4 GHz ISM band and showcase its capability on generating standard ZigBee, Bluetooth, LoRa, and Wi-Fi 802.11b/g/n/ac packets. Our extensive field studies show that RF-Transformer achieves 23.8 Mbps, 247.1 Kbps, 986.5 Kbps, and 27.3 Kbps throughput when generating standard Wi-Fi, ZigBee, Bluetooth, and LoRa signals while consuming 7.6-74.2 less power than their active counterparts. Our ASIC simulation based on the 65-nm CMOS process shows that the power gain of RF-Transformer can further grow to 92-678. We further integrate RF-Transformer with pressure sensors and present a case study on detecting foot traffic density in hallways. Our 7-day case studies demonstrate RFTransformer can reliably transmit sensor data to a commodity gateway by synthesizing LoRa packets on top of Wi-Fi signals. Our experimental results also verify the compatibility of RF-Transformer with commodity receivers. Code and hardware schematics can be found at: https://github.com/LeFsCC/RF-Transformer

    Squeal reduction of a disc brake system with fuzzy uncertainties

    Get PDF
    Automotive brake squeal has become one of the major concerns in the automotive industry. The researches on suppressing brake squeal are of great practical significances. However, most of the existing researches have not taken into account the parameters uncertainties, although it is well known that uncertain factors widely exist in the brake systems. To reduce disc brake squeal more effectively, a practical approach for the stability analysis and improvement of an automotive disc brake system with fuzzy uncertainties is proposed. In the proposed approach, the uncertainties associated with friction coefficient, material properties and loading properties are taken into consideration, and the uncertain parameters of the brake system are represented by fuzzy numbers. The brake system stability is investigated by performing complex eigenvalue analysis (CEA), and response surface methodology (RSM) is employed to approximate the implicit relationship between the dominant unstable mode and system parameters. Then, the stability analysis model of the brake is constructed based on RSM, CEA and fuzzy analysis. As a numerical example, the stability analysis of a commercial disc brake system with fuzzy uncertainties is carried out, and the influences of different uncertain parameters on system stability are investigated. The analysis results show that the stability of the fuzzy brake can be improved effectively by increasing the specific modulus of back plate. The proposed approach can be considered as a potential method for squeal reduction of automotive disc brake systems under fuzzy case

    Dynamic response of a quantum wire structure

    Get PDF
    Version of RecordPublishe
    corecore