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Objective:To prepare PEG-SH modified GNPs/miR-29 nanoparticles and to investigate the proliferation and differentiation of neural stem cells induced by PEG-SH modified GNPs/miR-29 nanoparticles.Methods:PEG-SH modified GNPs/miR-29 nanoparticles were developed by oxidation-reduction method and were tested for UV absorption spectrum, particle size distribution and zeta potential of nanoparticles. A total of 15 adult male Sprague Dawley (SD) rats were used to establish spinal cord injury model by modified Allen method. The artificial miR-29 and PEG-SH modified GNPs/miR-29 nanoparticles were implanted into the injury site of spinal cord respectively. The stability of miR-29 expression was analyzed by gel electrophoresis. The neural stem cells were isolated and cultured from 10 SPF grade neonatal rats. It was identified by Nestin, GFAP and NSE antibodies. The activity and proliferation of neural stem cells in synthetic miR-29, PEG-SH GNPs and PEG-SH GNPs/miR-29 nanoparticles group was detected by CCK-8 assay. Neural stem cells were cultured with synthetic miR-29, PEG-SH GNPs and PEG-SH GNPs/miR-29 nanoparticles for 1 week. The density, length and number of neuritis were investigated.Results:The solution of PEG-SH modified GNPs showed a brownish red appearance. The spheres were in uniform distribution under transmission electron microscope. The results of UV absorption spectrum showed a single peak wave. The peak value of UV absorption was near 523 nm. The zeta potential increased gradually with the increased content of PEG-SH. The peak value of zeta potential was 22.5±5.2 mV. With the increase of content of PEG, the particle size of PEG-SH modified GNPs rapidly reached peak value at the early stage and then decreased rapidly to a relatively stable level. The synthetic miR-29 and PEG-SH modified GNPs/miR-29 nanoparticles were implanted into the injury site of spinal cord. At 0-6 h, clear band was observed in the synthetic miR-29 group. However, the band was disappeared rapidly at 12-24 h. In PEG-SH GNPs/miR-29 group, clear band were always observed. The OD values of miR-29 group were 0.34±0.17, 0.78±0.31, 1.28±0.68, 1.64±0.38 at 1, 3, 5 and 7 d after inoculation respectively. There was no significant difference in OD values compared with DMEM group. There was no significant difference in OD values among GNPs, PEG-SH GNPs, PEG-SH GNPs/miR-29 and DMEM group. The density (56.38±3.65 μm 2), length (78.25±3.72 μm) and the number [(356±34.52) /1,000×high power field] of neurites in PEG-SH GNPs/miR-29 group were higher than those in miR-29 group, PEG-SH modified GNPs group and saline group. However, there was no significant difference in the density, length and number of neurite between PEG-SH GNPs/miR-29 and serum group. Conclusion:PEG-SH modified GNPs/miR-29 nanoparticless have good biological properties. It can induce the proliferation and differentiation of neural stem cells with protective effects on miR-29.
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Objective To investigate the characteristics of brain network based on brain electrical activity induced by somatosensory electrical stimulation,and to provide a theoretical basis for further understanding the mechanism of brain neural plasticity induced by somatosensory electrical stimulation.Methods Ten healthy subjects were selected and a somatosensory electrical stimulation experiment was constructed based on the directed transfer function (DTF).In the experiment,the DTF causal connection matrixes of the 32-channel EEG data of Delta,Theta,Alpha and Beta bands were obtained under the somatosensory electrical target and non-target stimulation,and the differences of clustering coefficient and global efficiency between two stimulation states were contrasted based on graph theory.Results Under the target stimulation and non-target stimulation states,the regions with stronger DTA causal connections were mainly concentrated in FCz,Cz,CPz and Pz channels.The causal connection intensity under target stimulation state was greater than that of non-target stimulation.Also,in the Delta,Theta,and Alpha bands,the clustering coefficient under the target stimulation state was significantly higher than that in the non-target stimulation state (P＜0.05).In the Delta and Theta bands,the global efficiency of the target stimulation state was significantly higher than that of the non-target stimulation state (P＜0.05).Conclusions Somatosensory electrical stimulation can activate and induce EEG brain networks.In the target stimulation state,the role of the parietal lobe in the EEG causal network is enhanced,which helps to induce attention to specific brain region plasticity,and thus realizing the nerve rehabilitation in the brain regions of interest.While in the non-target stimulation state,the synergistic interactions between brain regions were enhanced,which helps to activate and induce a wide range of associations in the whole brain network,so as to promote the global neural activity in the brain.
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Objective To explore the correlation between HIF-1α expression and RANKL/OPG pathway activation of fibroblast-like synoviocytes(FLSs)induced by Ti particles in aseptic loosening interfacial membrane. Method FLSs were extracted from the synovial tissue collected in surgeries and then co-cultured with Ti particles. QRT-PCR and Western blotting were conducted to measure the mRNA and protein expression of RANKL ,OPG and HIF-1αin FLSs at different concentration and time. Results Genes and protein expression levels of RANKL/OPG and HIF-1α were up-regulated with the increase of concentration of Ti particles. Expression of HIF-1α gene and protein increased time-dependently;the mRNA and protein expression of RANKL/OPG increased firstly and then declined alongside the increase of HIF-1αexpression. Conclusions Ti particles induce the up-regulation of HIF-1α expression and activate RANKL/OPG pathway. Up-regulation of HIF-1α may suppress the activation of RANKL/OPG pathway in FLSs of the interfacial membrane induced by Ti particles.
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Objective The single-trial extraction method of evoked potential has been one of the problems in EEG information processing field.According to the characteristics of somatosensory evoked electroencephalogram (EEG) with low signal-to-noise ratio and large parameter variation between trials,a novel single-trial extraction method for evoked potentials was proposed.This method aims to further improve the accuracy and characteristics of the single-trial extraction algorithm,preserve more dynamic characteristics between trials,and improve the estimation accuracy.Methods Based on wavelet filtering and multiple linear analysis,a new single-trial extraction method for EEG P300 parameters was proposed by applying the adaptive dynamic feature library.Four groups of wavelet filtered evoked EEG data were randomly selected,and used to build the feature library using overlapping average method and principal component analysis.For the single-trial extracted EEG data,the component with the highest correlation coefficient related with the current data was selected as the independent variable from the feature library,and the relevant multiple linear regression analysis was conducted.The single-trial evoked potential signal was reconstructed by the regression analysis results,in which the key features such as latency and amplitude were automatically extracted.Results Compared with the benchmark values determined by experts,the proposed algorithn can obtain more accurate estimation values of latency and amplitude in P300 components.The average difference of latency and amplitude by the proposed algorithm is (11.16±8.60) ms and (1.40±1.34)μV,respectively.These two values obtained by the proposed algorithm are much closer to that obtained by the commonly used overlapping average method of (23.26±25.76) ms and (2.52±2.50) μV,respectively.These results show that the proposed algorithm has significant advantages comparing with the traditional multiple linear regression analysis algorithm.Conclusions The dynamic updating principal component sample library of EEG data was applied to wavelet filtering and multiple linear regression,thus the dynamic characteristics were effectively preserved,and the accuracy of parameter estimation was improved.
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Objective The single-trial extraction method of evoked potential has been one of the problems in EEG information processing field.According to the characteristics of somatosensory evoked electroencephalogram (EEG) with low signal-to-noise ratio and large parameter variation between trials,a novel single-trial extraction method for evoked potentials was proposed.This method aims to further improve the accuracy and characteristics of the single-trial extraction algorithm,preserve more dynamic characteristics between trials,and improve the estimation accuracy.Methods Based on wavelet filtering and multiple linear analysis,a new single-trial extraction method for EEG P300 parameters was proposed by applying the adaptive dynamic feature library.Four groups of wavelet filtered evoked EEG data were randomly selected,and used to build the feature library using overlapping average method and principal component analysis.For the single-trial extracted EEG data,the component with the highest correlation coefficient related with the current data was selected as the independent variable from the feature library,and the relevant multiple linear regression analysis was conducted.The single-trial evoked potential signal was reconstructed by the regression analysis results,in which the key features such as latency and amplitude were automatically extracted.Results Compared with the benchmark values determined by experts,the proposed algorithn can obtain more accurate estimation values of latency and amplitude in P300 components.The average difference of latency and amplitude by the proposed algorithm is (11.16±8.60) ms and (1.40±1.34)μV,respectively.These two values obtained by the proposed algorithm are much closer to that obtained by the commonly used overlapping average method of (23.26±25.76) ms and (2.52±2.50) μV,respectively.These results show that the proposed algorithm has significant advantages comparing with the traditional multiple linear regression analysis algorithm.Conclusions The dynamic updating principal component sample library of EEG data was applied to wavelet filtering and multiple linear regression,thus the dynamic characteristics were effectively preserved,and the accuracy of parameter estimation was improved.
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Objective To explore a rapid bacterial identifying method based on the 16S rRNA gene sequence analysis technology to provide the scientific basis for the diagnosis and treatment of unknown pathogenic bacteria.Methods The pure colonies were iso-lated and cultured directly from a clinical patient′s sputum sample.The colony as a template for PCR amplification with universal primers to amplify 16S rRNA gene fragments of unknown bacteria.The product of PCR was sequenced directly,then the sequence result was compared by using the BLAST of NCBI and the pathogen was identified based on the sequence homology.Results 1 strain of unknown pathogen was identified as ochrobactrum by this test and confirmed by ABI bacterial rapid identification sys-tem.Conclusion This study simplifies the isolation and identification procedures of unknown pathogen from the clinical samples and establishes a simple method for the rapid identification of pathogens by using 16S rRNA gene amplification.
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Objective Dipole source analysis was employed to investigate the transient changes in brain mechanisms at earlier latencies.Methods Fourteen healthy volunteers were recruited in this research and evoked event-related potentials (ERPs) of unimodal and bimodal visual auditory stimuli were recorded by 64-electrodes electroencephalograph (EEG) recording system.All these earlier phases of the stimuli were divided into several subphases by specific time window for source analysis.Results The results showed that ERPs sources were mainly generated from visual and audio cortex,and there were changes in the location and strength of the dipole sources in each sub-phase.Conclusions The result of this study implies a serial processing of sensory information in human cortices in early phase of visual and auditory stimuli.
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Objective To investigate the cognitive difference between uni-modal (V,A) and bi-modal (VA)target stimuli from both vision and audition,and then to study the neural mechanisms of bi-modal enhancement.Methods This experiment adopted a speeded target stimuli detection task, both behavioral and electroencephalographic responses to uni-modal and bi-modal target stimuli which were combined from visual and auditory target stimuli,were recorded from 14 normal subjects using a 64-channel EEG NeuroScan system.The differences of cognitive between uni-modal and bi-modal stimulus were tested from both behavioral (reaction time (RT) and error rate (ER)) and event-related potentials (ERPs) (P2 latency and amplitude,P3 latency and amplitude)data,and the correlation between behavioral and ERPs results were analyzed.Results As a result,the RT,ER and P3 latency has significant difference between uni-modal and bi-modal target stimuli.In addition,there were significant correlation between behavioral data and P3 latency,especially from the RT and P3 latency.Conclusion By comparing the difference between uni-modal and bi-modal from both behavioral and ERPs results,we could reached the conclusion that the neural mechanism of bi-modal target detection was predominant over that of vision and audition uni-modal target detection,the enhancement take place not only involved in early ERP components (such as P1 and N1),but engaged at the late ERP components (such as P2 and P3).
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ObjectiveTo design multi-adaptive filter based on radial basis function (MAF-RBF) for efficiently extracting somatosensory evoked potential (SEP) in real-time SEP monitoring.MethodsWith the optimization of important parameters that influence the performance of radial basis function neural network,the performance of extracting SEP was compared to that of a multi-adaptive filter (MAF),which developed from the combination of well-developed adaptive noise canceller and adaptive signal enhancer.ResultsIn this simulation study,the outputs of MAF-RBF showed a similar waveform with SEP template signals,and a smoother waveform than the.output of MAF.ConclusionWith appropriate parameter values,MAF-RBFNN is able to extract the latency and amplitude of SEP from the extremely noisy background rapidly and reliably without averaging.
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Objective The aim of this study was to observe the outcome and evaluate the clinical efficacy of pulsed electromagnetic fields (PEMF) on pain management in patients with osteoporosis.MethodsA total of 58 patients with osteoporosis were treated with PEMF stimulation.Pains as main indicators of their symptom were evaluated before and after treatments.The clinical outcomes were assessed by observing the visual analogue scale (VAS).Statistical analysis was carried out to support the data.Results After PEMF treatment,the patients exhibited significant pain relief from mean VAS of 6.97±1.83 to 3.36±1.69(t-test,P＜0.05 ).Of the 58 patients,28 obtained significant symptom alleviation and 18 obtained moderate symptom alleviation,while 8 obtained slight alleviation,indicating the total clinical efficacy of 93%(54/58).Conclusion The current study provides the clinical outcomes indicating that PEMF may help to release the pain from primary osteoporosis and it might be an applicable supplementary treatment method for the osteoporosis related pain.
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ObjectiveTo efficiently detect somsatosensory evoked potential (SEP) using field programmable gate array (FPGA) real-time system, fixed-point algorithm based adaptive noise canceller (ANC) was designed to improve signal to noise ratio (SNR). MethodsWith the optimization of important parameters that influence the performance of fixed-point algorithm ANC, the performance was compared to that of floating-point algorithm ANC which was isolated from the effect of quantization error. Results In the simulation study, the outputs of fixed-point-based ANC showed a little higher distortion from real SEP signals than that of floating-point algorithm ANC. In the optimal selection of μ value, fixed-point algorithm ANC could get as good results as floating-point algorithm. Conclusion With appropriate parameter values, fixed-point algorithm ANC is able to improve SNR of SEP as well as that of fixed-point algorithm ANC.
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Objective To investigate the effects of low frequency pulsed magnetic fields (LF-PMFs) on proliferation, the cell cycle, apoptosis, migration, cytoskeleton formation and nitric oxide (NO) secretion in cardiac microvascular endothelial cells (CMECs). Methods LF-PMFs with rectangular and triangular waveforms at 15 Hz were tested. The CMECs were randomly divided into a control group, 0.6 mT group, 1.2 mT group, 1.8 mT group and 2.4 mT group. Except for the control group, the CMECs were exposed to LF-PMFs 4 h/day for 5 days. Results After 5 days of intervention with rectangular wave LF-PMFs the proliferation of CMECs accelerated and NO secretion was enhanced significantly. The percentages of cells at ( S+G2 ) phase increased significantly, whereas apoptosis rates were significantly lower than in the control group. The migration of CMECs was facilitated, stress fibers increased and cytoskeleton components were reorganized. After 5 days of intervention with triangular wave LF-PMFs proliferation of CMECs accelerated and NO secretion was significantly enhanced. The percentages of cells at(S+G2)phase and migration increased, while apoptosis was inhibited. Cytoskeleton components were reorganized after exposure to 0.6 mT and 2.4 mT triangular waveform LF-PMFs. No significant change was detected with 1.2 mT and 1.8 mT triangular waveform LF-PMFs with regard to these variables. Conclusions The effects of LF-PMFs on proliferation, the cell cycle, apoptosis, migration, cytoskeleton formation and NO secretion function of CMECs were infiuenced by the waveform in addition to it's intensity and frequency.
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Objective: To establish the determination of adenosine in Ganping Capsules. Methods: HPLC method was developed for the determination of adenosine in Ganping Capsules on Kromasil C 18 (150mm? 4.6mm i.d.) in 0.05mol/L KH 2PO 4 methanol (88∶12, V/V,pH 4.7) as a mobile phase (1.0mL/min). The UV detection wavelength was set at 260nm. Adenosine was extracted with 10% methanol water. Results: The recoveries was 98%～102% and the linear equation was Y=2537.4X+100.81. The correlation coefficient was r =0.9999(n=5). Conclusion: The method is simple, rapid and accurate.