Abstract There have been many types of bone-grafting operation dealing with the congenital pseudarthrosis of the tibia (CPAT), but the failure rate is fairly high. Since 1990, 2 children with CPAT, who had received repeated bone-grafting operation in failure, were treatedaccordingto the Ilizarovs theory and its related technique. The essentials of the operation were: (1) Thorough resection of abnormal bone tissues at pseudarthrosis might freshen the ends of the bone and facilitate bone union. (2) The firm fixation and constant compression force to the bone ends might promote bone healing. (3) The tibial lengthening was performed by osteotomy at the upper tibia. The pseudarthrosis was united in 2～3 months after operation. The patients were followed up from 1 to 3 years, and it was found that the remodelling of thebone was good, no recurrence occured. The advantages were: (1) The bone grafting was no longer necessary. (2) It could give a chance to equalizethe limb length. (3) It could enable early weight bearing and functional exercise.
Traditional sample entropy fails to quantify inherent long-range dependencies among real data. Multiscale sample entropy (MSE) can detect intrinsic correlations in data, but it is usually used in univariate data. To generalize this method for multichannel data, we introduced multivariate multiscale entropy into multiscale signals as a reflection of the nonlinear dynamic correlation. But traditional multivariate multiscale entropy has a large quantity of computation and costs a large period of time and space for more channel system, so that it can not reflect the correlation between variables timely and accurately. In this paper, therefore, an improved multivariate multiscale entropy embeds on all variables at the same time, instead of embedding on a single variable as in the traditional methods, to solve the memory overflow while the number of channels rise, and it is more suitable for the actual multivariate signal analysis. The method was tested in simulation data and Bonn epilepsy dataset. The simulation results showed that the proposed method had a good performance to distinguish correlation data. Bonn epilepsy dataset experiment also showed that the method had a better classification accuracy among the five data set, especially with an accuracy of 100% for data collection of Z and S.
With the range of application of computational biology and systems biology gradually expanding, the complexity of the bioprocess models is also increased. To address this difficult problem, it is required to introduce positive alternative analysis method to cope with it. Taking the dynamic model of the epidemic control process as research object, we established an evaluation model in our laboratory. Firstly, the model was solved with nonlinear programming method. The results were shown to be good. Based on biochemical systems theory, the ODE dynamic model was transformed into S-system. The eigen values of the model showed that the system was stable and contained oscillation phenomenon. Next the sensitivities of rate constant and logarithmic gains of the three key parameters were analyzed, as well as the robust of the system. The result indicated that the biochemical systems theory could be applied in different fields more widely.
NetMetaXL is a macro command to conduct network meta-analysis in the frame of Microsoft Excel on basis of Bayesian theory. This macro command, which was officially launched in 2014, integrates data extraction and entry, analysis results output and graph plotting as a whole. Currently, this version contains enough optional models, and all operations are through menu and easy to conduct; however, it is appropriate only for the network meta-analysis based on dichotomous variables, which still has fairly a lot to be enhanced and improved. This article gives a brief introduction based on examples to implement network meta-analysis using NetMetaXL.
M+N theory can be used as a method to improve the prediction accuracy in spectral analysis. The measured component, M kinds of non-measurement component, and N kinds of outside interference are induced into the entire measuring system, with the impact of "M" factors and "N" factors on the measurement accuracy considered systematically and comprehensively. Our human experiment system testing blood oxygen saturation based on "M+N" theory has been established. Dynamic spectrum method was used to eliminate the effects of different persons and different measuring parts which belonged to the system error of "N" factors. And then the D-value estimation was used to eliminate the effects of motion pseudo signal which belonged to the random error of "M" factors. Sixty two groups of valid data were obtained. The prediction model of blood oxygen saturation was built based on partial least squares regression method. The correlation coefficient and relative error were 0.796 8 and ±0.026 6, while the result of oximeter was 0.595 7 and relative error was ±0.076 0, respectively. The results show that the prediction accuracy of the measurement method based on the "M+N" theory is much higher than that of the oximeter.
Mild cognitive impairment (MCI) is a clinical transition state between age-related cognitive decline and dementia. Researchers can use neuroimaging and neurophysiological techniques to obtain structural and functional information about the human brain. Using this information researchers can construct the brain network based on complex network theory. The literature on graph theory shows that the large-scale brain network of MCI patient exhibits small-world property, which ranges intermediately between Alzheimer's disease and that in the normal control group. But brain connectivity of MCI patients presents topologically structural disorder. The disorder is significantly correlated to the cognitive functions. This article reviews the recent findings on brain connectivity of MCI patients from the perspective of multimodal data. Specifically, the article focuses on the graph theory evidences of the whole brain structural and functional and the joint covariance network disorders. At last, the article shows the limitations and future research directions in this field.
Present study used diffusion tensor image and tractography to construct brain white matter networks of 15 cerebral palsy infants and 30 healthy infants that matched for age and gender. After white matter network analysis, we found that both cerebral palsy and healthy infants had a small-world topology in white matter network, but cerebral palsy infants exhibited abnormal topological organization: increased shortest path length but decreased normalize clustering coefficient, global efficiency and local efficiency. Furthermore, we also found that white matter network hub regions were located in the left cuneus, precuneus, and left posterior cingulate gyrus. However, some abnormal nodes existed in the frontal, temporal, occipital and parietal lobes of cerebral palsy infants. These results indicated that the white matter networks for cerebral palsy infants were disrupted, which was consistent with previous studies about the abnormal brain white matter areas. This work could help us further study the pathogenesis of cerebral palsy infants.
Regurgitation is an abnormal condition happens when left ventricular assist devices (LVADs) operated at a low speed, which causes LVAD to fail to assist natural blood-pumping by heart and thus affects patients’ health. According to the degree of regurgitation, three LVAD’s regurgitation states were identified in this paper: no regurgitation, slight regurgitation and severe regurgitation. Regurgitation index (RI), which is presented based on the theory of dynamic closed cavity, is used to grade the regurgitation of LVAD. Numerical results showed that when patients are in exercising, resting and sleeping state, the critical speed between slight regurgitation and no regurgitation are 6 650 r/min, 7 000 r/min and 7 250 r/min, respectively, with corresponding RI of 0.401, 0.300 and 0.238, respectively. And the critical speed between slight regurgitation and severe regurgitation are 5 500 r/min, 6 000 r/min and 6 450 r/min, with corresponding RI of 0.488, 0.359 and 0.284 respectively. In addition, there is a negative relation correction between RI and rotational speed, so that grading the LVAD’s regurgitation can be achieved by determining the corresponding critical speed. Therefore, the detective parameter RI based on the signal of flow is proved to be able to grade LVAD’s regurgitation states effectively and contribute to the detection of LVAD’s regurgitation, which provides theoretical basis and technology support for developing a LVADs controlling system with high reliability.
Objective To evaluate the effect of situational leadership theory training on head nurses’ leadership style in nursing management, and summarize the application methods of situational leadership theory. Methods In December 2013, by means of convenience cluster sampling method, 154 head nurses of West China Hospital of Sichuan University were selected for a Leadership Style Self-rating Questionnaire survey, of whom 84 attended the situational leadership theory training one month ago. The questionnaire score was compared between the trained head nurses (the trained group) and the non-trained ones (the non-trained group). Results A total of 154 questionnaires were issued, and 109 valid ones were recovered, in whom 72 were trained by the situational leadership theory while the other 37 were not. The average scores of head nurses’ flexibility and efficacy in the trained group (22.35±5.12 and 55.67±7.59) were higher than those in the non-trained group (19.03±4.05 and 50.95±5.30), and the proportions of head nurses with high flexibility and high efficacy in the trained group (61.1% and 31.9%) were higher than those in the non-trained group (32.4% and 8.1%), and the differences above were statistically significant (P<0.05). Conclusions The training of the situational leadership theory can improve the application of theory to clinical nursing management and promote the head nurses’ flexibility and efficacy to accelerate their work enthusiasm and personal improvement. It can also promote team cohesion and sense of accomplishment by creating a positive team atmosphere to make the efficient usage of limited human resources.