Interplay Between Intracellular Transport Dynamics and Liquid‒Liquid Phase Separation.

Liquid‒liquid phase separation (LLPS) is a ubiquitous process in which proteins, RNA, and biomolecules assemble into membrane-less compartments, playing important roles in many biological functions and diseases. The current knowledge on the biophysical and biochemical principles of LLPS is largely from in vitro studies; however, the physiological environment in living cells is complex and not at equilibrium. The characteristics of intracellular dynamics and their roles in physiological LLPS remain to be resolved. Here, by using single-particle tracking of quantum dots and dynamic monitoring of the formation of stress granules (SGs) in single cells, the spatiotemporal dynamics of intracellular transport in cells undergoing LLPS are quantified. It is shown that intracellular diffusion and active transport are both reduced. Furthermore, the formation of SG droplets contributes to increased spatial heterogeneity within the cell. More importantly, the study demonstrated that the LLPS of SGs can be regulated by intracellular dynamics in two stages: the reduced intracellular diffusion promotes SG assembly and the microtubule-associated transport facilitates SG coalescences. The work on intracellular dynamics not only improves the understanding of the mechanism of physiology phase separations occurring in nonequilibrium environments but also reveals an interplay between intracellular dynamics and LLPS.

Noncontact Electromagnetic Wireless Recognition for Prosthesis Based on Intelligent Metasurface.

With the development of artificial intelligence and Internet of Things, hand gesture recognition techniques have attracted great attention owing to their excellent applications in developing human-machine interaction (HMI). Here, the authors propose a non-contact hand gesture recognition method based on intelligent metasurface. Owing to the advantage of dynamically controlling the electromagnetic (EM) focusing in the wavefront engineering, a transmissive programmable metasurface is presented to illuminate the forearm with more focusing spots and obtain comprehensive echo data, which can be processed under the machine learning technology to reach the non-contact gesture recognition with high accuracy. Compared with the traditional passive antennas, unique variations of echo coefficients resulted from near fields perturbed by finger and wrist agonist muscles can be aquired through the programmable metasurface by switching the positions of EM focusing. The authors realize the gesture recognition using support vector machine algorithm based on five individual focusing spots data and all-five-spot data. The influences of the focusing spots on the gesture recognition are analyzed through linear discriminant analysis algorithm and Fisher score. Experimental verifications prove that the proposed metasurface-based non-contact wireless design can realize the classification of hand gesture recognition with higher accuracy than traditional passive antennas, and give an HMI solution.

[Analysis on the Source Tracing and Pollution Characteristics of Rainfall Runoff in the Old Urban Area of Nanning City].

Rainfall runoff is one of the important sources of urban river pollution. In order to understand the pollution characteristics of rainfall runoff, the synchronous sampling and monitoring of rainfall runoff in the old urban area of Nanning were carried out; the pollution condition, initial scouring effect, and pollution contribution ratio of different underlying surfaces under different rainfall conditions were analyzed; and the calculation method and influence factor analysis of initial scouring of runoff pollution were discussed. According to the underlying surface of the vegetable market in the old urban area, the selection standard and necessity of the underlying surface of rainfall runoff were discussed. The results showed that the average concentration (EMC) of COD and TSS in roads and vegetable markets were greater than those in green spaces and roofs in the runoff pollution of the old urban area of Nanning, and the EMC values of nutrient pollutants in field rainfall runoff were ranked in decreasing order as vegetable markets, green spaces, roofs, and roads. Under the condition of heavy rain, each underlying surface had an obvious initial scouring effect, the average value of initial scouring coefficient (b) was 0.67, and there were many pollutants transported by roads and green spaces at the initial stage. Under light rain and moderate rain conditions, there was no obvious initial scouring effect, and the average b values were 0.83 and 0.94, respectively. The b value calculated by the whole process was preferred for evaluating the scouring effect. Based on multivariate statistical analysis, the EMC value of TSS in road runoff was significantly positively correlated with the total rainfall duration (RD), and the EMC value of TN in green land runoff was significantly negatively correlated with the average rainfall intensity (ARI). Whether the vegetable market was considered as the underlying surface had a great impact on the calculation results of nutrient pollution load but had little impact on the calculation results of COD and TSS load. The difference percentage of nutrient pollution load under heavy rain reached 80%. Under this condition, the difference percentage of pollutant EMC between the road and vegetable market reached 1012%.

Transcriptional profiling and network pharmacology analysis identify the potential biomarkers from Chinese herbal formula Huosu Yangwei Formula treated gastric cancer in vivo.

Huosu Yangwei (HSYW) Formula is a traditioanl Chinese herbal medicine that has been extensively used to treat chronic atrophic gastritis, precancerous lesions of gastric cancer and advanced gastric cancer. However, the effective compounds of HSYW and its related anti-tumor mechanisms are not completely understood. In the current study, 160 ingredients of HSYW were identified and 64 effective compounds were screened by the ADMET evaluation. Furthermore, 64 effective compounds and 2579 potential targets were mapped based on public databases. Animal experiments demonstrated that HSYW significantly inhibited tumor growth in vivo. Transcriptional profiles revealed that 81 mRNAs were differentially expressed in HSYW-treated N87-bearing Balb/c mice. Network pharmacology and PPI network showed that 12 core genes acted as potential markers to evaluate the curative effects of HSYW. Bioinformatics and qRT-PCR results suggested that HSYW might regulate the mRNA expression of DNAJB4, CALD, AKR1C1, CST1, CASP1, PREX1, SOCS3 and PRDM1 against tumor growth in N87-bearing Balb/c mice.

A hybrid method for real-time stimulation artefact removal during functional electrical stimulation with time-variant parameters.

Objective. In this study, a hybrid method combining hardware and software architecture is proposed to remove stimulation artefacts (SAs) and extract the volitional surface electromyography (sEMG) in real time during functional electrical stimulations (FES) with time-variant parameters.Approach. First, an sEMG detection front-end (DFE) combining fast recovery, detector and stimulator isolation and blanking is developed and is capable of preventing DFE saturation with a blanking time of 7.6 ms. The fragment between the present stimulus and previous stimulus is set as an SA fragment. Second, an SA database is established to provide six high-similarity templates with the current SA fragment. The SA fragment will be de-artefacted by a 6th-order Gram-Schmidt (GS) algorithm, a template-subtracting method, using the provided templates, and this database-based GS algorithm is called DBGS. The provided templates are previously collected SA fragments with the same or a similar evoking FES intensity to that of the current SA fragment, and the lengths of the templates are longer than that of the current SA fragment. After denoising, the sEMG will be extracted, and the current SA fragment will be added to the SA database. The prototype system based on DBGS was tested on eight able-bodied volunteers and three individuals with stroke to verify its capacity for stimulation removal and sEMG extraction.Results.The average stimulus artefact attenuation factor, SA index and correlation coefficient between clean sEMG and extracted sEMG for 6th-order DBGS were 12.77 ± 0.85 dB, 1.82 ± 0.37 dB and 0.84 ± 0.33 dB, respectively, which were significantly higher than those for empirical mode decomposition combined with notch filters, pulse-triggered GS algorithm, 1st-order and 3rd-order DBGS. The sEMG-torque correlation coefficients were 0.78 ± 0.05 and 0.48 ± 0.11 for able-bodied volunteers and individuals with stroke, respectively.Significance.The proposed hybrid method can extract sEMG during dynamic FES in real time.

An Anti Stimulation Artifacts and M-waves Surface Electromyography Detector with a Short Blanking Time.

A surface electromyography (sEMG) detector, that not only removes stimulation artifacts entirely but also increases the recording time, has been developed in this paper. The sEMG detector consists of an sEMG detection circuit and a stimulation isolator. The sEMG detection circuit employs a stimulus isolate switch (SIS), a blanking (BLK) and non-linear feed-back (NFB) circuit to remove the artifacts and to increase the recording time. In the SIS, the connection between stimulator and stimulation electrodes, along with the stimulation electrodes and the ground are controlled by an opto-isolator, and the connection of instrument amplifier and the recording electrodes are controlled by CMOS-based switches. The mode switches of the BLK and the NFB circuit also employs CMOS-based switches. By an accurate timing adjustment, the voluntary EMG can be recorded during electrical stimulation. Two 6 able-bodied experiments have been performed to test the three anti-artifact sEMG detector: BLK, BLK&SIS, BLK&SIS&NFB. The results indicate that the BLK&SIS&NFB proposed in this work effectively removes stimulus artifacts and M-waves, and has a longer recording time compared with BLK and BLK&SIS circuits.

Electromyographic bridge for promoting the recovery of hand movements in subacute stroke patients: A randomized controlled trial.

OBJECTIVE: The electromyographic bridge (EMGB) detects surface electromyographic signals from a non-paretic limb. It then generates electric pulse trains according to the electromyographic time domain features, which can be used to stimulate a paralysed or paretic limb in real time. This strategy can be used for the contralateral control of neuromuscular electrical stimulation (NMES) to improve motor function after stroke. The aim of this study was to compare the treat-ment effects of EMGB vs cyclic NMES on wrist and finger impairments in subacute stroke patients. METHODS: A total of 42 hemiplegic patients within 6 months of their cerebrovascular accidents were randomly assigned to 4-week treatments with EMGB or cyclic NMES. Each group underwent a standard rehabilitation programme and 10 sessions per week of hand training with EMGB or cyclic NMES. Outcome measures were: Brunnstrom stage, upper extremity components of the Fugl-Meyer Assessment, Motor Status Scale, voluntary surface electromyographic ratio and active range of motion of the wrist and finger joints. RESULTS: The EMGB group showed significantly greater improvements than the cyclic NMES group on the following measures: Brunnstrom stages for the hand, upper extremity - Fugl-Meyer Assessment, Motor Status Scale, and the voluntary surface electromyographic ratio of wrist and finger extensors. Eleven and 4 participants of the EMGB group who had no active wrist and finger movements, respectively, at the start of the treatment could perform measurable wrist and finger extensions after EMGB training. The corresponding numbers in the cyclic NMES group were only 4 and 1. CONCLUSION: In the present group of subacute stroke patients, the results favour EMGB over cyclic NMES for augmenting the recovery of volitional wrist and finger motion.

Real-time and wearable functional electrical stimulation system for volitional hand motor function control using the electromyography bridge method.

Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy. A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method. Through a series of novel design concepts, including the integration of a detecting circuit and an analog-to-digital converter, a miniaturized functional electrical stimulation circuit technique, a low-power super-regeneration chip for wireless receiving, and two wearable armbands, a prototype system has been established with reduced size, power, and overall cost. Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects, the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy. Test results showed that wrist flexion/extension, hand grasp, and finger extension could be reproduced with high accuracy and low latency. This system can build a bridge of information transmission between healthy limbs and paralyzed limbs, effectively improve voluntary participation of hemiplegic patients, and elevate efficiency of rehabilitation training.

The Principle of the Micro-Electronic Neural Bridge and a Prototype System Design.

The micro-electronic neural bridge (MENB) aims to rebuild lost motor function of paralyzed humans by routing movement-related signals from the brain, around the damage part in the spinal cord, to the external effectors. This study focused on the prototype system design of the MENB, including the principle of the MENB, the neural signal detecting circuit and the functional electrical stimulation (FES) circuit design, and the spike detecting and sorting algorithm. In this study, we developed a novel improved amplitude threshold spike detecting method based on variable forward difference threshold for both training and bridging phase. The discrete wavelet transform (DWT), a new level feature coefficient selection method based on Lilliefors test, and the k-means clustering method based on Mahalanobis distance were used for spike sorting. A real-time online spike detecting and sorting algorithm based on DWT and Euclidean distance was also implemented for the bridging phase. Tested by the data sets available at Caltech, in the training phase, the average sensitivity, specificity, and clustering accuracies are 99.43%, 97.83%, and 95.45%, respectively. Validated by the three-fold cross-validation method, the average sensitivity, specificity, and classification accuracy are 99.43%, 97.70%, and 96.46%, respectively.

A frequency and pulse-width co-modulation strategy for transcutaneous neuromuscular electrical stimulation based on sEMG time-domain features.

OBJECTIVE: Surface electromyography (sEMG) is often used as a control signal in neuromuscular electrical stimulation (NMES) systems to enhance the voluntary control and proprioceptive sensory feedback of paralyzed patients. Most sEMG-controlled NMES systems use the envelope of the sEMG signal to modulate the stimulation intensity (current amplitude or pulse width) with a constant frequency. The aims of this study were to develop a strategy that co-modulates frequency and pulse width based on features of the sEMG signal and to investigate the torque-reproduction performance and the level of fatigue resistance achieved with our strategy. APPROACH: We examined the relationships between wrist torque and two stimulation parameters (frequency and pulse width) and between wrist torque and two sEMG time-domain features (mean absolute value (MAV) and number of slope sign changes (NSS)) in eight healthy volunteers. By using wrist torque as an intermediate variable, customized and generalized transfer functions were constructed to convert the two features of the sEMG signal into the two stimulation parameters, thereby establishing a MAV/NSS dual-coding (MNDC) algorithm. Wrist torque reproduction performance was assessed by comparing the torque generated by the algorithms with that originally recorded during voluntary contractions. Muscle fatigue was assessed by measuring the decline percentage of the peak torque and by comparing the torque time integral of the response to test stimulation trains before and after fatigue sessions. MAIN RESULTS: The MNDC approach could produce a wrist torque that closely matched the voluntary wrist torque. In addition, a smaller decay in the wrist torque was observed after the MNDC-coded fatigue stimulation was applied than after stimulation using pulse-width modulation alone. SIGNIFICANCE: Compared with pulse-width modulation stimulation strategies that are based on sEMG detection, the MNDC strategy is more effective for both voluntary muscle force reproduction and muscle fatigue reduction.

Design of a pulse-triggered four-channel functional electrical stimulator using complementary current source and time division multiplexing output method.

In this paper, a four-channel pulse-triggered functional electrical stimulator using complementary current source and time division output method is proposed for the research and application of functional electrical stimulation (FES). The high-voltage compliance and output impedance is increased by adopting the complementary current source, which can also realize the linear voltage-to-current conversion and high channel isolation. A high-voltage analog switch chip MAX14803, combined with a FIFO queue algorithm in the microprocessor, is used to setup the H-bridge and multiplexers for the four-channel time division multiplexing output. With this method, the size and cost of the key components are reduced greatly. The stimulating core circuit area is 30 × 50 mm(2). According to the experiments, the stimulator can achieve the four-channel charge-balanced biphasic stimulation with a current range between 0 and 60 mA and a single-phase pulse amplitude up to 60 V.