Keystone Symposia: Transmembrane Signaling by GPCRs and Channels

Description Cellular membranes present natural borders for signal transduction between cells and their environment. Nature developed different strategies to enable signals to cross the membrane barrier. The goal of this meeting is to discuss the molecular mechanisms of transmembrane signaling on the basis of three protein classes, i.e.

Multi-channel neural signal stimulating module and in-vivo experiments

The module for function electrical stimulation （FES） of neurons is designed for the research of the neural function regeneration microelectronic system, which is an in-body embedded micro module. It is implemented by using discrete devices at first and characterized in vitro. The module is used to stimulate sciatic nerve and spinal cord of rats and rabbits for in-vivo real-time experiments of the neural function regeneration system. Based on the module, a four channel module for the FES of neurons is designed for 12 sites cuff electrode or 10 sites shaft electrode. Three animal experiments with total five rats and two rabbits were made. In the in-vivo experiment, the neural signals including spontaneous and imitated were regenerated by the module. The stimulating signal was used to drive sciatic nerve and spinal cord of rats and rabbits, successfully caused them twitch in different parts of their bodies, such as legs, tails, and fingers. This testifies that the neural function regeneration system can regenerate the neural signals.

Measuring Absolute Delay of RNSS Signal Channel Using Digital Envelope Detection

The absolute delay caused by equipment of radio navigation satellite service (RNSS) signal channel must be calibrated in the application of positioning. The measurement accuracy of absolute delay will affect the positioning precision of RNSS user. An absolute delay measurement technique using digital envelope detection was developed for RNSS signal transmission channel. The RNSS transmission signal of navigation satellite and the one pulse per second (1PPS)generated by satellite time keeping system were sampled synchronously. With sampling data of 1PPS,the reference point of the absolute delay can be decided at first,and then sampling data of RNSS transmission signal were truncated. The truncated data were processed using digital envelop detection algorithm to search the phase converting points of RNSS signal. Finally,the absolute delay of RNSS signal transmitting channel was calculated. Uncertainty of measurement with proposed technique is lower than 0. 2 ns as the sampling frequency is 10 GHz.

Photonic radio frequency channelizers based on Kerr optical micro-combs

We review recent work on broadband RF channelizers based on integrated optical frequency Kerr micro-combs combined with passive micro-ring resonator filters,with microcombs having channel spacings of 200 and 49 GHz.This approach to realizing RF channelizers offers reduced complexity,size,and potential cost for a wide range of applications to microwave signal detection.

The Reconstructing of Low Signal-noise Ratio Single Ion Channel Signal from Patch-clamp Recordings Sampled in the Colored Background Noise

The single ion channel signal is an ionic current that can be recorded by the patch clamp technique. Hidden Markov model (HMM) algorithm has been used to convert the low signal noise ratio (SNR) noisy recording into an idealized quantal one in the case of white background noise. The traditional HMM algorithm is extended and adapted to the colored background noise. A new algorithm called EHMM (Extended HMM) algorithm is proposed, and mainly validated by simulation. Results show that it’s effective.

Effect of G_(αq/11) Protein and ATP-sensitive Potassium Channels on Ischemic Preconditioning in Rat Hearts

Objectives To investigate the effect of Gαq/11 signaling pathway and ATP-sensitive potassium channel ( KATP channel ) on ischemic preconditioning (IPC) protection in rat hearts. Methods Two series of experiments were performed in Wistar rat hearts. In the first series of experiment, ischemic preconditioning was induced by left anterior descending occlusion (three, 5 min episodes separated by 5 min of reperfusion), ischemia-reperfusion injury was induced by 30 min coronary artery occlusion followed by 90 min reperfusion. Hemodynamics, infarct size and scores of ventricular arrhythmias were measured. The expression of Gαq/11 protein in the heart was measured by Western blot analysis in the second series. Results Ischemic preconditioning rats showed decreased infarct size and scores of ventricular arrhythmia vs non-IP control rats. The effect of IPC was significantly attenuated by glibenclamide (1 mg/kg, ip), a nonselective KATP channel inhibitor. IPC caused a significant increase in the expression of Gαq/11 protein. Conclusions Activations of Gαq/11 signal pathway and KATP channel played significant roles in the classical cardioprotection of ischemic precon-ditioning rat heart and might be an important mechanism of signal transduction pathway during the ischemic preconditioning.

Robust signal recognition algorithm based on machine learning in heterogeneous networks

There are various heterogeneous networks for terminals to deliver a better quality of service. Signal system recognition and classification contribute a lot to the process. However, in low signal to noise ratio（SNR） circumstances or under time-varying multipath channels, the majority of the existing algorithms for signal recognition are already facing limitations. In this series, we present a robust signal recognition method based upon the original and latest updated version of the extreme learning machine（ELM） to help users to switch between networks. The ELM utilizes signal characteristics to distinguish systems. The superiority of this algorithm lies in the random choices of hidden nodes and in the fact that it determines the output weights analytically, which result in lower complexity. Theoretically, the algorithm tends to offer a good generalization performance at an extremely fast speed of learning. Moreover, we implement the GSM/WCDMA/LTE models in the Matlab environment by using the Simulink tools. The simulations reveal that the signals can be recognized successfully to achieve a 95% accuracy in a low SNR（0 dB） environment in the time-varying multipath Rayleigh fading channel.

Signal processing for noncoherent underwater acoustic communication approaching channel capacity

Noncoherent underwater acoustic communication channel in adverse conditions is modeled as a phase-random Rayleigh fading channel,and its capacity curve is derived.To approach the channel capacity curve,the concatenated code of the nonbinary LDPC code and the constant weight code is proposed for noncoherent communication which can late be iteratively decoded in the probability domain.Without information of channel amplitude or phase in the receiver,statistic parameters of the respective signal and noise bins were estimated based on the moment estimation method,the posterior probabilities of the constant weight code words were further calculated,and the nonbinary LDPC code was decoded with the nonbinary factor graph algorithm.It is verified by simulations that by utilizing the proposed concatenated code and its processing algorithm,gap to channel capacity curve is reduced by 3 dB when compared to the existing method.Underwater communication experiments were carried out in both deep ocean（vertical communication,5 km）and shallow lake（horizontal communication,near 3 km,delay spread larger than 50 ms）,in which the signal frequency band was 6 kHz to10 kHz,and the data transmission rate Was 357 bps.The proposed scheme can work properly in both experiments with a signal-to-noise ratio threshold of 2 dB.The performance of the proposed algorithm Was well verified by the experiments.

Robust and Passive Motion Detection with COTS WiFi Devices

Device-free Passive（DfP） detection has received increasing attention for its ability to support various pervasive applications. Instead of relying on variable Received Signal Strength（RSS）, most recent studies rely on finer-grained Channel State Information（CSI）. However, existing methods have some limitations, in that they are effective only in the Line-Of-Sight（LOS） or for more than one moving individual. In this paper, we analyze the human motion effect on CSI and propose a novel scheme for Robust Passive Motion Detection（R-PMD）. Since traditional low-pass filtering has a number of limitations with respect to data denoising, we adopt a novel Principal Component Analysis（PCA）-based filtering technique to capture the representative signals of human motion and extract the variance profile as the sensitive metric for human detection. In addition, existing schemes simply aggregate CSI values over all the antennas in MIMO systems. Instead, we investigate the sensing quality of each antenna and aggregate the best combination of antennas to achieve more accurate and robust detection. The R-PMD prototype uses off-the-shelf WiFi devices and the experimental results demonstrate that R-PMD achieves an average detection rate of 96.33% with a false alarm rate of 3.67%.