Deep brain stimulation (DBS), which usually utilizes high frequency stimulation (HFS) of electrical pulses, is effective for treating many brain disorders in clinic. Studying the dynamic response of downstream neurons to HFS and its time relationship with stimulus pulses can reveal important mechanisms of DBS and advance the development of new stimulation modes (e.g., closed-loop DBS). To exhibit the dynamic neuronal firing and its relationship with stimuli, we designed a two-dimensional raster plot to visualize neuronal activity during HFS (especially in the initial stage of HFS). Additionally, the influence of plot resolution on the visualization effect was investigated. The method was then validated by investigating the neuronal responses to the axonal HFS in the hippocampal CA1 region of rats. Results show that the new design of raster plot is able to illustrate the dynamics of indexes (such as phase-locked relationship and latency) of single unit activity (i.e., spikes) during periodic pulse stimulations. Furthermore, the plots can intuitively show changes of neuronal firing from the baseline before stimulation to the onset dynamics during stimulation, as well as other information including the silent period of spikes immediately following the end of HFS. In addition, by adjusting resolution, the raster plot can be adapted to a large range of firing rates for clear illustration of neuronal activity. The new raster plot can illustrate more information with a clearer image than a regular raster plot, and thereby provides a useful tool for studying neuronal behaviors during high-frequency stimulations in brain.
On the basis of Poincare scatter plot and first order difference scatter plot, a novel heart rate variability (HRV) analysis method based on scatter plots of RR intervals and first order difference of RR intervals (namely, RdR) was proposed. The abscissa of the RdR scatter plot, the x-axis, is RR intervals and the ordinate, y-axis, is the difference between successive RR intervals. The RdR scatter plot includes the information of RR intervals and the difference between successive RR intervals, which captures more HRV information. By RdR scatter plot analysis of some records of MIT-BIH arrhythmias database, we found that the scatter plot of uncoupled premature ventricular contraction (PVC), coupled ventricular bigeminy and ventricular trigeminy PVC had specific graphic characteristics. The RdR scatter plot method has higher detecting performance than the Poincare scatter plot method, and simpler and more intuitive than the first order difference method.
In this paper , the statistic significance and clinical application of forest plots in a meta-analysis have been fully discussed. If the horizontal line represents the 95% confidence interval of the indexes including odds ratio, relative risk, weighted mean difference, and standard mean difference crosses the vertical line, the effect of test group is not signficant with that of control group; if the horizontal line lies to the right of the vertical line, it indicates that the test group is significantly effctive. If the horizontal line lies to the left of the vertical line, it indicates that the control group is more effective. In addition, it doesn’t mean that clinical application is more beneficial, if the treatment study has more effect, because experimental factor can be positive or negative.
ObjectiveTo review recent literature on three-dimensional (3-D) plotting as a rapid prototyping method for the manufacturing of patient specific biomaterial scaffolds and tissue engineering constructs. MethodsLiterature review and description of own recent work. ResultsIn contrast to many other rapid prototyping technologies which can be used only for the processing of distinct materials, 3-D plotting can be utilized for all pasty biomaterials and therefore opens up many new options for the manufacturing of bi- or multiphasic scaffolds or even tissue engineering constructs, containing e. g. living cells. Conclusion3-D plotting is a rapid prototyping technology of growing importance which provides flexibility concerning choice of material and allows integration of sensitive biological components.
Predicting the termination of paroxysmal atrial fibrillation (AF) may provide a signal to decide whether there is a need to intervene the AF timely. We proposed a novel RdR RR intervals scatter plot in our study. The abscissa of the RdR scatter plot was set to RR intervals and the ordinate was set as the difference between successive RR intervals. The RdR scatter plot includes information of RR intervals and difference between successive RR intervals, which captures more heart rate variability (HRV) information. By RdR scatter plot analysis of one minute RR intervals for 50 segments with non-terminating AF and immediately terminating AF, it was found that the points in RdR scatter plot of non-terminating AF were more decentralized than the ones of immediately terminating AF. By dividing the RdR scatter plot into uniform grids and counting the number of non-empty grids, non-terminating AF and immediately terminating AF segments were differentiated. By utilizing 49 RR intervals, for 20 segments of learning set, 17 segments were correctly detected, and for 30 segments of test set, 20 segments were detected. While utilizing 66 RR intervals, for 18 segments of learning set, 16 segments were correctly detected, and for 28 segments of test set, 20 segments were detected. The results demonstrated that during the last one minute before the termination of paroxysmal AF, the variance of the RR intervals and the difference of the neighboring two RR intervals became smaller. The termination of paroxysmal AF could be successfully predicted by utilizing the RdR scatter plot, while the predicting accuracy should be further improved.
Network plots can clearly present the relationships among the direct comparisons of various interventions in a network meta-analysis. Currently, there are some methods of drawing network plots. However, the information provided by a network plot and the interface-friendly degree to a user differ in the kinds of software. This article briefly introduces how to draw network plots using the network package and gemtc package that base on R Software, Stata software, and ADDIS software, and it also compares the similarities and differences among them.
Extraction and analysis of electroencephalogram (EEG) signal characteristics of patients with autism spectrum disorder (ASD) is of great significance for the diagnosis and treatment of the disease. Based on recurrence quantitative analysis (RQA)method, this study explored the differences in the nonlinear characteristics of EEG signals between ASD children and children with typical development (TD). In the experiment, RQA method was used to extract nonlinear features such as recurrence rate (RR), determinism (DET) and length of average diagonal line (LADL) of EEG signals in different brain regions of subjects, and support vector machine was combined to classify children with ASD and TD. The research results show that for the whole brain area (including parietal lobe, frontal lobe, occipital lobe and temporal lobe), when the three feature combinations of RR, DET and LADL are selected, the maximum classification accuracy rate is 84%, the sensitivity is 76%, the specificity is 92%, and the corresponding area under the curve (AUC) value is 0.875. For parietal lobe and frontal lobe (including parietal lobe, frontal lobe), when the three features of RR, DET and LADL are combined, the maximum classification accuracy rate is 82%, the sensitivity is 72%, and the specificity is 92%, which corresponds to an AUC value of 0.781. The research in this paper shows that the nonlinear characteristics of EEG signals extracted based on RQA method can become an objective indicator to distinguish children with ASD and TD, and combined with machine learning methods, the method can provide auxiliary evaluation indicators for clinical diagnosis. At the same time, the difference in the nonlinear characteristics of EEG signals between ASD children and TD children is statistically significant in the parietal-frontal lobe. This study analyzes the clinical characteristics of children with ASD based on the functions of the brain regions, and provides help for future diagnosis and treatment.
ObjectiveTo investigate the association between tumor necrosis factor (TNF)-α gene polymorphism and susceptibility to chronic obstructive pulmonary disease (COPD) in eastern Heilongjiang province.MethodsA total of 347 COPD patients in the Department of Respiratory Medicine, the First Affiliated Hospital of Jiamusi University, were enrolled from January 2016 to January 2017. In the same period, 338 healthy subjects in the hospital physical examination center were selected as controls. The genotype of the two groups was analyzed by high resolution melting (HRM) and gene sequencing. The genotype and allele probability of the two groups were compared and analyzed by the SHEsis genetic imbalance haplotype analysis.ResultsBoth TNF-a –308 G/A co-dominant model and recessive model have significant differences between COPD patients and healthy subjects (P=0.036, OR 1.512, 95%CI 1.023 – 2.234; P=0.027, OR 1.202, 95%CI 1.024 – 1.741). –850G/A co-dominant model (P=0.000, OR 1.781, 95%CI 1.363 – 2.329), dominant model (P=0.000, OR 0.391 7, 95%CI 1.363 – 2.329) and hyper-dominant model (P=0.000, OR 2.680, 95%CI 1.728 – 4.156) in the two groups were statistically different. The haploid analysis and haploid genotype analysis showed statistically significant differences (all P<0.05, OR>1, 95%CI>1) at +489, –308, –850 sites by allele A, G, A, respectively between the two groups. There was a significant difference in the lung function between the –308G/A, –863C/A mutant genome and the wild type (P=0.038, P=0.02) in COPD patients according to the classification of lung function.ConclusionsA allele in TNF-α –308 and G allele in TNF-α –850 locus may be risk factors for COPD in the eastern Heilongjiang Province, and the risk of homozygous genotype is higher. +489A, –308G and –850A respectively may be the predisposing factor of COPD while the three genotypes of AGA patients were at higher risk. TNF-α –308 A allele and –863 A allele are related to lung function deterioration, and the two sites with A allele in patients with COPD indicate poor lung function.
ObjectiveTo explore the application of enhanced funnel plots (EFP) and trial sequential analysis (TSA) in robustness assessment of meta-analysis results.MethodsData were extracted from published meta-analysis. The EFP was used to evaluate the robustness of the significance and heterogeneity of the current meta-analysis. The TSA was used to judge the sufficiency of the cumulative sample size of the current meta-analysis and to assess the robustness of conclusions based on current evidence.ResultsThe EFP showed that the meta-analysis results of low-density lipoprotein (LDL) was robust, and the meta-analysis results of triglyceride (TG), total cholesterol (TC) and high-density lipoprotein (HDL) were not stable. The TSA showed that the cumulative sample size of LDL had reached the required information size (RIS), and the current conclusion was stable. The cumulative Z value of TG, TC and HDL neither reached the RIS nor passed through the TSA monitoring boundary or futility boundary, indicating that current conclusions were not robust.ConclusionsThe combination of EFP and TSA can make a comprehensive judgment on the robustness of current meta-analysis results, and provide methodological support in the robustness assessment of results for future systematic reviews and meta-analyses.
Lorenz plot (LP) method which gives a global view of long-time electrocardiogram signals, is an efficient simple visualization tool to analyze cardiac arrhythmias, and the morphologies and positions of the extracted attractors may reveal the underlying mechanisms of the onset and termination of arrhythmias. But automatic diagnosis is still impossible because it is lack of the method of extracting attractors by now. We presented here a methodology of attractor extraction and recognition based upon homogeneously statistical properties of the location parameters of scatter points in three dimensional LP (3DLP), which was constructed by three successive RR intervals as X, Y and Z axis in Cartesian coordinate system. Validation experiments were tested in a group of RR-interval time series and tags data with frequent unifocal premature complexes exported from a 24-hour Holter system. The results showed that this method had excellent effective not only on extraction of attractors, but also on automatic recognition of attractors by the location parameters such as the azimuth of the points peak frequency (APF) of eccentric attractors once stereographic projection of 3DLP along the space diagonal. Besides, APF was still a powerful index of differential diagnosis of atrial and ventricular extrasystole. Additional experiments proved that this method was also available on several other arrhythmias. Moreover, there were extremely relevant relationships between 3DLP and two dimensional LPs which indicate any conventional achievement of LPs could be implanted into 3DLP. It would have a broad application prospect to integrate this method into conventional long-time electrocardiogram monitoring and analysis system.