Preventive Intrathecal Injection of Bupivacaine Alleviated Microglia Activation and Neuropathic Pain in a Rat Model of Chronic Constriction Injury

Spinal microglia are crucial to neuronal hyper-excitability and pain hypersensitivity. The local anesthetic bupivacaine is commonly used for both peripheral and spinal anesthesia. The pain-relief effects resulting from the peripheral and systemic administration of bupivacaine have been previously reported. In this study, the preventive effects of intrathecal bupivacaine administration against neuropathic pain were revealed in a rat model of sciatic nerve chronic constriction injury (CCI). Using a CCI rat model, pain hypersensitivity, characterized by mechanical allodynia and thermal hyperalgesia, correlated well with microglia M1 polarization, activation and pro-inflammatory cytokine expression in both spinal cord dorsal horns and sciatic nerves. Bupivacaine attenuated pain behaviors and inflammatory alternations. We further identified that the Interferon Regulatory Factor 5 (IRF5)/P2X Purinoceptor 4 (P2X4R) and High Mobility Group Box 1 (HMGB1)/Toll-Like Receptor 4 (TLR4)/NF-κB inflammatory axes may each play pivotal roles in the acquisition of microglia M1 polarization and pro-inflammatory cytokine expression under CCI insult. The relief of pain paralleled with the suppression of microglia M1 polarization, elevation of microglia M2 polarization, and inhibition of IRF5/P2X4R and HMGB1/TLR4/NF-κB in both the spinal cord dorsal horns and sciatic nerve. Our findings provide molecular and biochemical evidence for the anti-neuropathic effect of preventive bupivacaine.     

Analysis of functional brain network based on electroencephalography and complex network

Microsystem Technologies - In this paper, electroencephalography data are used to establish a functional network connecting correlated human brain regions. Through analysis, it is found that the...     

TMAH-Catalyzed Transesterification of EPA and DHA in Encapsulated Fish Oil Products

Tetramethylammonium hydroxide (TMAH)-catalyzed transesterification was developed as a rapid and reliable method using gas chromatography (GC) to determine the total fatty acid profile and to quantify the ethyl esters of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in 20 brands of encapsulated fish oil products. The AOAC method with boron trifluoride (BF₃) as a catalyst was used as a reference. After the respective transesterifications of BF₃ and TMAH, seven brands of encapsulated fish oil showed a single peak of EPA or DHA in the chromatograms, while 13 brands showed a single peak in the chromatograms after BF₃ esterification, but doublet peaks of EPA or DHA after TMAH esterification. By comparing with the GC/MS NIST library and authentic standard fatty acids of ethyl esters, the two pairs of doublet peaks were confirmed the ethyl and methyl esters of EPA and DHA, while the sum of the peak areas of the doublet represented the content of EPA or DHA. The reaction time course concluded that optimal TMAH transesterification was obtained at 25 °C for 10 min and using GC columns of low to medium polarity including Rtx-wax and Rtx-2330 were able to differentiate and quantify the ethyl- and methyl-esterified EPA and DHA, while RT-2560 column with higher polarity than the two other columns was unable to resolve the ethyl ester from the methyl ester of EPA or DHA. An EPA/DHA ratio of ≥1.10 may serve as an indicator of fish oil fortified with the ethyl ester of EPA.     

Layerless Design of A Power-efficient Clustering Algorithm for Wireless Ad Hoc Networks under Fading

Traditional wireless ad hoc network power-efficient design proceeds separately on access and clustering algorithms by assuming perfect distance (that is, no fading and channel impairments) at most. In this paper, we discard the traditional layer-concept to tackle this important power-efficient wireless ad hoc networks under shadow fading, by identifying distance between a node pair as a sort of random distance to accommodate fading effect, which of course can be considered as a cross-layer design from traditional concept. By deriving the probability distribution of the distance between two nodes and the probability distribution of the distances between nodes and a randomly selected common reference node, the impacts of shadow fading on the link connectivity and node degree of the randomly constructed network topology are studied. Next, we propose a critical node first (CNF) based clustering algorithm to organize such a shadow faded random network topology into a power-efficient network architecture. By taking the shadow fading effects into considerations, our results show that the cluster-based network architecture generated by the proposed CNF-based clustering algorithm is power-efficient since the required number of exchanges of the cluster maintenance overheads is reduced.     

An Image-guided Endoscope System for the Ureter Detection

Mobile Networks and Applications - The ureter injury occasionally happens in the gynecology, abdominal and urinary surgeries. The medical negligence may cause severe problems for the hospital, and...     

A face robot for autonomous simplified musical notation reading and singing

This research is aimed to devise an anthropomorphic robotic head with a human-like face and a sheet of artificial skin that can read a randomly composed simplified musical notation and sing the corresponding content of the song once. The face robot is composed of an artificial facial skin that can express a number of facial expressions via motions driven by internal servo motors. Two cameras, each of them installed inside each eyeball of the face, provide vision capability for reading simplified musical notations. Computer vision techniques are subsequently used to interpret simplified musical notations and lyrics of their corresponding songs. Voice synthesis techniques are implemented to enable the face robot to sing songs by enunciating synthesized sounds. Mouth patterns of the face robot will be automatically changed to match the emotions corresponding to the lyrics of the songs. The experiments show that the face robot can successfully read and then accurately sing a song which is assigned discriminately.     

An integrated temporal error concealment for H.264/AVC based on spatial evaluation criteria

Owing to error-prone transmission networks, the compressed video bit stream is prone to packet loss in the transmission channel. This loss causes serious distortion and the distortion will propagate to successive frames, especially in highly compressed video coding standard. Therefore, it is very important to efficiently enhance the restored result. In this paper, an integrated temporal error concealment technique for H.264/AVC is proposed. The technique could effectively restore the corrupted data by adaptively integrating error concealment approaches with the adaptive weight-based switching algorithm. The integrated mechanism is based on spatial evaluation criteria, judged by boundary distortion estimation and texture intensity. Experimental results show that the technique could effectively enhance the performance of error concealment.     

A fast multilayer neural-network training algorithm based on thelayer-by-layer optimizing procedures

A faster new learning algorithm to adjust the weights of the multilayer feedforward neural network is proposed. In this new algorithm, the weight matrix (W(2)) of the output layer and the output vector (Y) of the previous layer are treated as two variable sets. An optimal solution pair (W(2)*,Y(P)*) is found to minimize the sum-square-error of the patterns input. Y(P)* is then used as the desired output of the previous layer. The optimal weight matrix and layer output vector of the hidden layers in the network is found with the same method as that used for the output layer. In addition, the dynamic forgetting factors method makes the proposed new algorithm even more powerful in dynamic system identification. Computer simulation shows that the new algorithm outmatches other learning algorithms both in converging speed and in computation time required.     

A material removal model for polishing glass–ceramic and aluminum magnesium storage disks

In this paper, a model is proposed to more closely describe the relationships between polishing parameters and the material removal rate for the commonly used storage disks in PC. Experiments were conducted to verify this model. It is shown that the proposed model predicts the material removal rate more accurately than existing models. The proposed model is expected to apply to different materials polished by similar processes. The FEM analysis of the applied polishing pressure well explained the current empirical results.     

CORDIC-based FPGA hardware design method for biped walking gait

In this paper, a simple oscillator-based biped walking method is described and a CORDIC-based FPGA hardware design method is proposed to effectively generate a walking gait in a biped robot. Based on the simple oscillator-based model, some equations represented by sinusoidal functions are proposed to describe a biped walking as a complete walking process with three modes (starting mode, gait cycle mode, and ending mode) and six phases. In these six phases, these oscillation parameters can be represented by the swing length, the step length, and the lifting height of the biped robot. Then an FPGA hardware structure based on the CORDIC operator named circular rotation is proposed and implemented on an FPGA chip. Finally, some comparison of the proposed CORDIC-based FPGA hardware method and the software method are presented. We can see that the proposed hardware method significantly reduces the processing time to generate gait trajectories of a biped robot.