Homeostatic regulation of brain functions by endocannabinoid signaling

Humans have been using Cannabis and its extracts for a few thousand years as a medicinal and recreational drug. How- ever, the chemical component in Cannabis sativa, △9-tet- rahydrocannabinol （△9-THC）, an exogenous cannabinoid, remained unknown until it was isolated and identified as the main psychoactive ingredient （Gaoni and Mechoulam, 1964）.

An improved empirical green function method to extract microseismic signals

In mining, reservoir impoundment and hydraulic fracturing exploitation, the induced microseismic clusters may present complex waveforms at receivers since the individual events generally arrive very close. And the routine methods for arrival picking are insufficiently efficient due to these strong influences. Here, we modified the empirical green function method and applied it to extract the green functions and the radiation coefficients of microseismic events with the largest energy in clusters.Multiple-channel records were used to estimate an "average" source spectrum and then the "average" source wavelet was removed from the records by deconvolution. We applied this method to the real data,and the result indicated clear improvement in extracting the dominant event of the clusters.

MiR-19a-3p regulates the Forkhead box F2-mediated Wnt/β-catenin signaling pathway and affects the biological functions of colorectal cancer cells

BACKGROUND Colorectal cancer(CRC)is one of the most common malignancies worldwide.AIM To explore the expression of microRNA miR-19a-3p and Forkhead box F2(FOXF2)in patients with CRC and the relevant mechanisms.METHODS Sixty-two CRC patients admitted to the hospital were enrolled into the study group,and sixty healthy people from the same period were assigned to the control group.Elbow venous blood was sampled from the patients and healthy individuals,and blood serum was saved for later analysis.MiR-19a-3p mimics,miR-19a-3p inhibitor,miR-negative control,small interfering-FOXF2,and short hairpin-FOXF2 were transfected into HT29 and HCT116 cells.Then quantitative polymerase chain reaction was performed to quantify the expression of miR-19a-3p and FOXF2 in HT29 and HCT116 cells,and western blot(WB)analysis was conducted to evaluate the levels of FOXF2,glycogen synthase kinase 3 beta(GSK-3β),phosphorylated GSK-3β(p-GSK-3β),β-catenin,p-β-catenin,α-catenin,Ncadherin,E-cadherin,and vimentin.The MTT,Transwell,and wound healing assays were applied to analyze cell proliferation,invasion,and migration,respectively,and the dual luciferase reporter assay was used to determine the correlation of miR-19a-3p with FOXF2.RESULTS The patients showed high serum levels of miR-19a-3p and low levels of FOXF2,and the area under the curves of miR-19a-3p and FOXF2 were larger than 0.8.MiR-19a-3p and FOXF2 were related to sex,tumor size,age,tumor-nodemetastasis staging,lymph node metastasis,and differentiation of CRC patients.Silencing of miR-19a-3p and overexpression of FOXF2 suppressed the epithelialmesenchymal transition,invasion,migration,and proliferation of cells.WB analysis revealed that silencing of miR-19a-3p and FOXF2 overexpression significantly suppressed the expression of p-GSK-3β,β-catenin,N-cadherin,and vimentin;and increased the levels of GSK-3β,p-β-catenin,α-catenin,and Ecadherin.The dual luciferase reporter assay confirmed that there was a targeted correlation of miR-19a-3p with FOXF2.In addition,a rescue experiment revealed that there were no differences in cell proliferation,invasion,and migration in HT29 and HCT116 cells co-transfected with miR-19a-3p-mimics+sh-FOXF2 and miR-19a-3p-inhibitor+si-FOXF2 compared to the miR-negative control group.CONCLUSION Inhibiting miR-19a-3p expression can upregulate the FOXF2-mediated Wnt/β-catenin signaling pathway,thereby affecting the epithelial-mesenchymal transition,proliferation,invasion,and migration of cells.Thus,miR-19a-3p is likely to be a therapeutic target in CRC.

Modeling Distortion Signals of Power Grid Based on Wiener-G Functionals

The uniform mathematical model of distortion signals in power grid has been setup with the theory of Wiener-G Functional. Firstly,the Matlab simulation models were established. Secondly,the Wiener kernel of power load was found based on the Gaussian white noise as input. And then the uniform mathematical model of the power grid signal was established according to the homogeneous of the same order of Wiener functional series. Finally,taking three typical distortion sources which are semiconductor rectifier,electric locomotive and electric arc furnace in power grid as examples,we have validated the model through the Matlab simulation and analyzed the simulation errors. The results show that the uniform mathematical model of distortion signals in power grid can approximation the actual model by growing the items of the series under the condition of the enough storage space and computing speed.

TLR signaling that induces weak inflammatory response and SHIP1 enhances osteogenic functions

Toll-like receptor （TLR）-mediated inflammatory response could negatively affect bone metabolism. In this study, we determined how osteogenesis is regulated during inflammatory responses that are downstream of TLR signaling. Human primary osteoblasts were cultured in collagen gels. Pam3CSK4 （P3C） and Escherichia coli lipopolysaccharide （EcLPS） were used as TLR2 and TLR4 ligand respectively. Porphyromonas gingivalis LPS having TLR2 activity with either TLR4 agonism （Pg1690） or TLR4 antagonism （Pg1449） and mutant E. coli LPS （LPxE/LPxF/WSK） were used. IL-lp, SH2-containing inositol phosphatase-1 （SHIP1） that has regulatory roles in osteogenesis, alkaline phosphatase and mineralization were analyzed. 3α-Aminocholestane （3AC） was used to inhibit SHIP1. Our results suggest that osteoblasts stimulated by P3C, poorly induced IL-1β but strongly upregulated SHIP1 and enhanced osteogenic mediators. On the contrary, EcLPS significantly induced IL-1β and osteogenic mediators were not induced. While Pg1690 downmodulated osteogenic mediators, Pg1449 enhanced osteogenic responses, suggesting that TLR4 signaling annuls osteogenesis even with TLR2 activity. Interestingly, mutant E. coli LPS that induces weak inflammation upregulated osteogenesis, but SHIP1 was not induced. Moreover, inhibiting SHIP1 significantly upregulated TLR2-mediated inflammatory response and downmodulated osteogenesis. In conclusion, these results suggest that induction of weak inflammatory response through TLR2 （with SHIP1 activity） and mutant TLR4 ligands could enhance osteogenesis.

Kravchenko probabilityweight functions in problems of radar signals correlation processing

In this report the combined method of correlation radar signal(RS)processing based on the theory of atomic functions(AF)is examined.Examples of using of new Kravchenko probability weight functions(WF)designs are presented.Quality functional to estimate accuracy and efficiency of RS processing for concrete physical models is constructed.It is shown that the proposed approach significantly improves the quality of the coherent analysis of RS.

Weighted Multi-sensor Data Level Fusion Method of Vibration Signal Based on Correlation Function

As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.

Criterion for Blind Signals Separation Based on Correlation Function

Blind separation of source signals usually relies either on the condition of statistically independence or involving their higher-order cumulants. The model of two channels signal separation is considered. A criterion based on correlation functions is proposed. It is proved that the signals can be separated, using only the condition of noncorrelation. An algorithm is derived, which only involves the solution to quadric nonlinear equations.

电针联合低频经颅超声刺激对创伤性脑损伤大鼠脑电信号的影响

背景:创伤性脑损伤是由头部受到撞击、打击而导致大脑正常功能被破坏的疾病,目前需要寻找有效治疗方式和客观指标,帮助医生判别损伤状况及恢复患者脑功能。目的:探究电针联合低频经颅超声刺激对创伤性脑损伤大鼠脑电信号的影响。方法:将40只6周龄SPF级雄性SD大鼠随机分为假手术组、模型组、电针组、低频经颅超声刺激组和联合组(n=8),后4组采用Feeney自由落体法造模,假手术组只开骨窗而不打击。各干预组均于造模后1 d开始实施干预,电针组进行电针干预,低频经颅超声刺激组进行低频经颅超声刺激干预,联合组进行两者联合干预,共干预7 d。造模后8 h,用改良神经功能缺损评分评定大鼠神经功能缺损情况;干预7 d后观察大鼠Y迷宫自发轮流行为百分比,而后采集脑电信号,利用快速傅里叶变换分解出α、β、θ和δ波段,计算各频段振荡幅值、能量占比百分比以及Lempel-Ziv复杂度、样本熵。结果与结论:①造模后8 h,模型组、电针组、低频经颅超声刺激组和联合组的改良神经功能缺损评分显著高于假手术组(P<0.05);②造模后第7天,模型组的α波、δ波频带振荡幅值、δ波能量占比百分比显著高于假手术组(P<0.05),自发轮流行为百分比、α波、β波能量占比百分比、Lempel-Ziv复杂度、样本熵显著低于假手术组(P<0.05);③与模型组比较,联合组的α波、δ波频带振荡幅值显著下降(P<0.05),电针组、低频经颅超声刺激组、联合组的α波、β波频带能量占比百分比显著升高(P<0.05),δ波能量占比百分比显著下降(P<0.05);④与电针组和低频经颅超声刺激组相比,联合组的δ波能量占比百分比显著降低(P<0.05),自发轮流行为百分比、α波、β波能量占比百分比、Lempel-Zi复杂度、样本熵显著升高(P<0.05);⑤结果显示,创伤性脑损伤大鼠出现脑电信号异常,而电针联合低频经颅超声刺激干预后可以改善大鼠脑电信号的异常情况,提示脑电频域特征和非线性特征可用来评估创伤性脑损伤情况。

IP3R2及RYR2介导Ca^(2+)信号在急性一氧化碳中毒迟发性脑病小鼠模型中的表达

背景:研究发现星形胶质细胞中Ca^(2+)的表达与认知功能密切相关,目前由1,4,5-三磷酸肌醇受体(Inositol 1,4,5-trisphosphate receptors,IP3Rs)2、兰尼碱受体(ryanodine receptors,RYRs)2受体及其调控的Ca^(2+)信号通路已经成为认知障碍相关疾病研究的热点。目的:研究急性一氧化碳中毒迟发性脑病动物模型中,海马组织内星形胶质细胞和IP3R2、RYR2介导的Ca^(2+)信号的表达情况,探索急性一氧化碳中毒迟发性脑病可能的发病机制。方法:Morris水迷宫实验筛选认知功能合格的C57BL小鼠随机分为对照组、实验组,实验组小鼠采用静态吸入一氧化碳建立急性一氧化碳中毒迟发性脑病模型,对照组小鼠吸入等量空气。造模后第21天,利用Morris水迷宫、苏木精-伊红染色、Western blot、免疫荧光双标法、Ca^(2+)荧光探针检测中毒小鼠行为学及神经元改变、星形胶质细胞特异性标记物胶质纤维酸性蛋白及IP3R2、RYR2受体、星形胶质细胞内Ca^(2+)浓度变化。结果与结论:①Morris水迷宫实验发现与对照组相比,实验组小鼠逃避潜伏期明显延长(P<0.05);②苏木精-伊红染色表明实验组小鼠海马锥体细胞数减少、细胞结构紊乱、细胞核碎裂伴溶解;③免疫荧光检测表明海马区IP3R2、RYR2分别和胶质纤维酸性蛋白存在共表达,且实验组海马区IP3R2、RYR2和胶质纤维酸性蛋白表达均上调(P<0.05);④Western blot检测显示实验组海马区IP3R2、RYR2及胶质纤维酸性蛋白的蛋白表达均增多(P<0.05);⑤Ca^(2+)荧光探针法检测表明实验组小鼠海马区星形胶质细胞内Ca^(2+)浓度明显升高(P<0.05);⑥结果说明,星形胶质细胞可能通过介导IP3R2、RYR2受体影响Ca^(2+)信号,进而使一氧化碳中毒的小鼠认知功能受损,最终导致急性一氧化碳中毒迟发性脑病发生。

基于肝肾同源理论探讨肌筋膜触发点拔罐对腰椎间盘突出症的影响

目的基于肝肾同源理论探讨肌筋膜触发点拔罐对肝肾亏虚型腰椎间盘突出症患者腰椎功能及腰背伸肌群表面肌电指标的改善效果。方法选取河南省中医院骨科2022年3月至2024年3月收治的109例肝肾亏虚型腰椎间盘突出症患者作为研究对象,对照组54例给予CT引导下射频针刀联合脊得舒丸治疗,观察组55例在对照组基础上增加肌筋膜触发点拔罐,对比两组患者中医证候积分、腰椎功能、腰椎活动度、腰背肌表面肌电信号的变化、复发率及不良反应。结果治疗后,两组中医证候评分均降低(P<0.05),且观察组更低(P<0.05)。治疗后,两组腰椎功能评分及活动度均增加(P<0.05),且观察组更高(P<0.05)。治疗后,两组积分肌电值及平均功率频率均增加(P<0.05),且观察组更高(P<0.05)。观察组复发率3.70%低于对照组18.52%(P<0.05)。两组不良反应差异无统计学意义(P>0.05)。结论基于肝肾同源理论的肌筋膜触发点拔罐能够减轻肝肾亏虚型腰椎间盘突出症患者临床症状,改善腰椎功能,调节腰背伸肌群表面肌电,并降低复发率。

Application of Mellin Transform in Wideband Underwater Acoustic Signal Processing

According to the features of the wideband underwater acoustic signals,an algorithm for the wideband ambiguity function is put forward based on Mellin transform.The wideband acoustic signal processing using the fast Mellin transform is also explored.The theoretical analysis and simulation results show that the algorithm has not only high computation efficiency but also good concentration in wideband ambiguity domain.It suits for the wideband underwater acoustic signal processing.

Ultrasonic signal classification based on ambiguity plane feature

Ambiguity function （AF） is proposed to represent ultrasonic signal to resolve the preprocessing problem of different center frequencies and different arriving times among ultrasonic signals for feature extraction, as well as offer time-frequency features for signal classification. Moreover, Karhunen-Loeve （K-L） transform is considered to extract signal features from ambiguity plane, and then the features are presented to probabilistic neural network （PNN） for signal classification. Experimental results show that ambiguity function eliminates the difference of center frequency and arriving time existing in ultrasonic signals, and ambiguity plane features extracted by K-L transform describe the signal of different classes effectively in a reduced dimensional space. Classification result suggests that the ambiguity plane features obtain better performance than the features extracted by wavelet transform （WT）.

miRNA targeted signaling pathway in the early stage of denervated fast and slow muscle atrophy

Denervation often results in skeletal muscle atrophy.Different mechanisms seem to be involved in the determination between denervated slow and fast skeletal muscle atrophy.At the epigenetic level,mi RNAs are thought to be highly involved in the pathophysiological progress of denervated muscles.We used mi RNA microarrays to determine mi RNA expression profiles from a typical slow muscle（soleus muscle） and a typical fast muscle（tibialis anterior muscle） at an early denervation stage in a rat model.Results showed that mi R-206,mi R-195,mi R-23 a,and mi R-30 e might be key factors in the transformation process from slow to fast muscle in denervated slow muscles.Additionally,certain mi RNA molecules（mi R-214,mi R-221,mi R-222,mi R-152,mi R-320,and Let-7e） could be key regulatory factors in the denervated atrophy process involved in fast muscle.Analysis of signaling pathway networks revealed the mi RNA molecules that were responsible for regulating certain signaling pathways,which were the final targets（e.g.,p38 MAPK pathway; Pax3/Pax7 regulates Utrophin and follistatin by HDAC4; IGF1/PI3K/Akt/m TOR pathway regulates atrogin-1 and Mu RF1 expression via Fox O phosphorylation）.Our results provide a better understanding of the mechanisms of denervated skeletal muscle pathophysiology.

Wigner-Hough transform based on slice's entropy and its application to multi-LFM signal detection

To enhance the capacity of the radar-reconnaissance interception receiver recognizing linear frequency modulated (LFM) at a low signal-noise ratio, this paper presents WignerHough transform (WHT) of the LFM signal and its corresponding characteristics, derives the probability density functions of the LFM signal and Gaussian white noise within WHT based on entropy (WHTE), dimension under different assumptions and puts forward a WHT algorithm based on entropy of slice to improve the capacity of detecting the LFM signal. Entropy of the WHT domain slice is adopted to assess the information size of polar radius or angle slice, which is converted into the weight factor to weight every slice. Double-deck weight is used to weaken the influences of noise and disturbance terms and WHTE treatment and signal detection procedure are also summarized. The rationality of the algorithm is demonstrated through theoretical analysis and formula derivation, the efficiency of the algorithm is verified by simulation comparison between WHT, fractional Fourier transform and periodic WHT, and it is highlighted that the WHTE algorithm has better detection accuracy and range of application against strong noise background.

Adaptive Learning with Large Variability of Teaching Signals for Neural Networks and Its Application to Motion Control of an Industrial Robot

Recently, various control methods represented by proportional-integral-derivative （PID） control are used for robotic control. To cope with the requirements for high response and precision, advanced feedforward controllers such as gravity compensator, Coriolis/centrifugal force compensator and friction compensators have been built in the controller. Generally, it causes heavy computational load when calculating the compensating value within a short sampling period. In this paper, integrated recurrent neural networks are applied as a feedforward controller for PUMA560 manipulator. The feedforward controller works instead of gravity and Coriolis/centrifugal force compensators. In the learning process of the neural network by using back propagation algorithm, the learning coefficient and gain of sigmoid function are tuned intuitively and empirically according to teaching signals. The tuning is complicated because it is being conducted by trial and error. Especially, when the scale of teaching signal is large, the problem becomes crucial. To cope with the problem which concerns the learning performance, a simple and adaptive learning technique for large scale teaching signals is proposed. The learning techniques and control effectiveness are evaluated through simulations using the dynamic model of PUMA560 manipulator.

Research on the weak acoustic signal features based on magneto-acoustic effect

The electrical characteristics of tissue yield valuable information for the early diagnosis of pathological changes. Magneto-acoustic tomography( MAT) is a novel functional imaging approach for imaging electrical conductivity. It combines the advantages of high spatial resolution of ultrasonic imaging and high contrast ratio of electrical impedance tomography. It has potential application value in the early tumor diagnosis and bioelectricity monitoring. The analysis and detection of the magneto acoustic signal have a key role in improving the contrast resolution,imaging resolution and reconstruction accuracy of the electrical conductivity image. In this paper,the amplitude,the waveform characteristics and the frequency characteristics of the magnetic sound signal are review ed by the theoretical research,simulation and testing experiments of the weak magneto-acoustic signal.

The Upstream ＂Strong Signals＂ of the Water Vapor Transport over the Tibetan Plateau during a Heavy Rainfall Event in the Yangtze River Basin

A heavy rainfall event that occurred over the middle and lower reaches of the Yangtze River Basin （YRB） during July 11-13 2000 is explored in this study. The potential/stream function is used to analyze the upstream ＂strong signals＂ of the water vapor transport in the Tibetan Plateau （TP）. The studied time period covers from 2000 LST 5 July to 2000 LST 15 July （temporal resolution： 6 hours）. By analyzing the three-dimensional structure of the water vapor flux, vorticity and divergence prior to and during the heavy rainfall event, the upstream ＂strong signals＂ related to this heavy rainfall event are revealed. A strong correlation exists between the heavy rainfall event in the YRB and the convective clouds over the TE The ＂convergence zone＂ of the water vapor transport is also identified, based on correlation analysis of the water vapor flux two days and one day prior to, and on the day of, the heavy rainfall. And this ＂convergence zone＂ coincides with the migration of the maximum rainfall over the YRB. This specific coupled structure actually plays a key role in generating heavy rainfall over the YRB. The eastward movement of the coupled system with a divergence]convergence center of the potential function at the upper/lower level resembles the spatiotemporal evolution of the heavy rainfall event over the YRB. These upstream ＂strong signals＂ are clearly traced in this study through analyzing the three-dimensional structure of the potential/stream function of upstream water vapor transport.

Synthetic Aperture Radar Raw Signals Simulation of Extended Scenes

A synthetic aperture radar (SAR) raw signal simulation algorithm for extended scenes is presented. This algorithm is based on the SAR two-dimensional system transform function (STF). To cope with range-variant nature of SAR STF and increase the speed of this algorithms, new formulas for range-variant phase corrections in range-Doppler (RD) domain are developed. In this way, many azimuth lines can be simulated with the same SAR STF. It only needs two-dimensional fast Fourier transform code and complex multiplications. Comparing with time-domain simulation algorithm, it is very simple and thus efficient. Simulation results have shown that this algorithm is accurate and efficient. Key words synthetic aperture radar - raw signal simulation - system transform function CLC number TP 751. 1 Foundation item: Supported by the National Natural Science Foundation of China (40376051)Biography: Sun Jin-yao (1967-), female, Ph. D. candidate, research direction: SAR image simulation and 3D recover for SAR image.

LPI radar signal detection based on the combination of FFT and segmented autocorrelation plus PAHT

This paper proposes a desirable method to detect different kinds of low probability of intercept (LPI) radar signals, targeted at the main intra-pulse modulation method of LPI radar signals including the signals of linear frequency modulation, phase code, and frequency code. Firstly, it improves the coherent integration of LPI radar signals by adding the periodicity of the ambiguity function. Then, it develops a frequency domain detection method based on fast Fourier transform (FFT) and segmented autocorrelation function to detect signals without features of linear frequency modulation by virtue of the distribution characteristics of noise signals in the frequency domain. Finally, this paper gives a verification of the performance of the method for different signal-to-noise ratios by conducting simulation experiments, and compares the method with existing ones. Additionally, this method is characterized by the straightforward calculation and high real-time performance, which is conducive to better detecting all kinds of LPI radar signals.