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.

The lower expression of CD20 antigen molecules on the B cell membrane is the primary characteristic of B-chronic lymphocytic leukemia (B-CLL). In this paper, we combined laser scanning confocal microscopy (LSCM) and quantum dots labeling to detect the expression and distribution of CD20 molecules on CD20+B lymphocyte surface. Simultaneously, we investigated the morphology and ultrastructure of the B lymphocytes that belonged to the normal persons and B-CLL patients through utilizing the atomic force microscope (AFM). In addition, we measured the force spectroscopy of CD20 antigen-antibody binding using the AFM tips modified with CD20 antibody. The fluorescent images indicated that the density of CD20 of normal CD20+B lymphocytes was much higher than that of B-CLL CD20+B cells. The AFM data show that ultrastructure of B-CLL CD20+B lymphocytes became more complicated. Moreover, the single molecular force spectroscopy data show that the special force of CD20 antigen-antibody was four times bigger than the nonspecific force between the naked AFM tip and cell surface. The force map showed that CD20 molecules distributed homogeneously on the normal CD20+B lymphocytes, whereas, the CD20 molecules distributed heterogenous on B-CLL CD20+B lymphocytes. Our data provide visualized evidence for the phenomenon of low-response to rituximab therapy on clinical. Meanwhile, AFM is possible to be a powerful tool for development and screening of drugs for pharmacology use.
Antigen-Antibody Reactions ; immunology ; Antigens, CD20 ; immunology ; B-Lymphocytes ; immunology ; ultrastructure ; Binding Sites, Antibody ; Cell Membrane ; immunology ; Humans ; Leukemia, Lymphocytic, Chronic, B-Cell ; immunology ; Microscopy, Atomic Force ; Microscopy, Confocal ; Quantum Dots

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).

Abnormal changes during fat formation are closely related to the prevalence of many diseases. In order to understand the formation mechanism of fat, we used atomic force microscopy (AFM) to characterize the morphology and mechanical properties of porcine preadipocytes during the differentiation. Preadipocytes and adipocytes were different morphologically. The surface roughness of adipocytes was less than preadipocytes by detection of the ultrastructure. The mechanical properties of preadipocytes were changed during differentiation with AFM-based force spectroscopy. Preadipocytes were 20% higher than adipocytes in the adhesion force, stiffness and Young's modulus. Therefore, AFM analysis of membrane changes related to adipocytes formation provided quantitative data in the nanometer level for further studying the formation mechanism of the adipocytes.
Adipocytes ; cytology ; ultrastructure ; Adipogenesis ; Animals ; Cell Differentiation ; physiology ; Cells, Cultured ; Microscopy, Atomic Force ; Swine

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.

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.