Epilepsy is a neurological disease with disordered brain network connectivity. It is important to analyze the brain network mechanism of epileptic seizure from the perspective of directed functional connectivity. In this paper, causal brain networks were constructed for different sub-bands of epileptic electroencephalogram (EEG) signals in interictal, preictal and ictal phases by directional transfer function method, and the information transmission pathway and dynamic change process of brain network under different conditions were analyzed. Finally, the dynamic changes of characteristic attributes of brain networks with different rhythms were analyzed. The results show that the topology of brain network changes from stochastic network to rule network during the three stage and the node connections of the whole brain network show a trend of gradual decline. The number of pathway connections between internal nodes of frontal, temporal and occipital regions increase. There are a lot of hub nodes with information outflow in the lesion region. The global efficiency in ictal stage of α, β and γ waves are significantly higher than in the interictal and the preictal stage. The clustering coefficients in preictal stage are higher than in the ictal stage and the clustering coefficients in ictal stage are higher than in the interictal stage. The clustering coefficients of frontal, temporal and parietal lobes are significantly increased. The results of this study indicate that the topological structure and characteristic properties of epileptic causal brain network can reflect the dynamic process of epileptic seizures. In the future, this study has important research value in the localization of epileptic focus and prediction of epileptic seizure.
Microfluidic chips can be used to realize continuous cryoprotectants (CPA) loading/unloading for oocytes, reducing osmotic damage and chemical toxicity of CPA. In this study, five different Y-shape microfluidic chips were fabricated to realize the continuous CPA loading/unloading. The effects of flow rate, entrance angle, aspect ratio and turning radius of microchannels on the mixing efficiency of microfluidic chips were analyzed quantitatively. The experimental results showed that with the decrease of flow rates, the increase of aspect ratios and the decrease of turning raradius of microchannel, the mixing length decreased and the mixing velocity was promoted, while the entrance angle had little effect on the mixing efficiency. However, the operating conditions and structural parameters of the chips in practical application should be determined based on an overall consideration of CPA loading/unloading time and machining accuracy. These results would provide a reference to the application of microfluidic chip in CPA mixing.
目的:利用臭氧对粪便处理车间的臭气物质进行氧化分解时,臭氧的除臭效果和臭氧的适宜浓度。方法:在对京东某粪便处理车间大规模现场测试(官能法,化学法)的基础上,确定粪便处理车间的恶臭污染源,计算出臭氧氧化法的除臭效率。 结果:针对臭气成份与臭氧反应速度,绘制出了在粪便处理车间臭气浓度以及臭气主要成份硫化氢和氨随时间的衰减曲线;臭氧发生器启动后,臭气浓度迅速衰减,在第一个小时内臭气浓度衰减率为74%,硫化氢在第一个小时浓度衰减率为29%,第二个小时浓度衰减率为58.9%,氨2小时后总衰减率为56.8%;臭氧除臭时,粪便处理车间臭氧浓度应控制在0.03 ppm,此时臭气浓度为150,臭气强度为3级。 结论:该项研究为臭氧除臭装置和粪便处理车间利用臭氧氧化法除臭提供了设计依据。
In the present study, packaging system composed of pAAV-CMV-GFP, pAAV-RC and pHelper were transfected into human embryonic kidney 293 cells (HEK293 cells) mediated by polyethyleneimine (PEI) to explore an optimal transfection condition. Different total plasmid DNA dosages (1, 2, 3, 4, 5, 6μg) and different PEI/Plasmid ratios (1:1, 3:1, 5:1, 7:1) were tested with detection of green fluorescence protein (GFP) with ImagePro Plus6.0 Software. Then transfection efficiency of the optimized transfection system was further observed for different time periods(12, 24, 36, 48, 60, 72 h). The results showed that total plasmid dosage of 4μg/well with PEI/plasmid ratio of 3:1~5:1 was an efficient transfection condition. Transfection efficiency-time curve was an S-shaped curve. Transfection efficiency reached a plateau at 60 h after transfection. The optimized conditions for PEI-mediated transfection at the optimal time result in enhanced transfection efficiency of triple plasmid into HEK293 cells.
ObjectiveTo compare and evaluate the discrimination, validity, and reliability of different data envelopment analysis (DEA) models for measuring the effectiveness of models by selecting different input and output indicators of the model.MethodsData from health statistical reports and pilot program of diagnosis-related groups of tertiary hospitals in Hubei Province from 2017 to 2018 were used to analyze the discrimination, content and structure validity, and reliability of the models. Six DEA models were established by enriching the details of input and output on the basis of the input and output indicators of the conventional DEA model of hospitals.ResultsFrom the view of discrimination, the results of all models were left-skewed, the cost-efficiency model had the lowest left-skewed degree (skewness coefficient: -0.14) and was the flattest (kurtosis coefficient: -1.02). From the view of structure validity, the results of the cost-efficiency model were positively correlated with total weights, outpatient visits, and inpatient visits (r=0.328, 0.329, 0.315; P<0.05). From the perspective of content validity, the interpretation of model was more consistent with theory of production after revision of input and output indicators. From the view of reliability, the cost efficiency model had the largest correlation coefficient between the data of 2017 and 2018 (r=0.880, P<0.05).ConclusionsAfter refining the input and output indicators of the DEA model, the discrimination, validity, and reliability of the model are higher, and the results are more reasonable. Using indicators such as discrimination, validity, and reliability can measure the effectiveness of the DEA model, and then optimize the model by selecting different input and output indicators.
Objective To analyze the dynamic efficiency of township hospitals. Methods Based on the DEA-Malmquist index, this research analyzed the change of the total factor productivity indices and the decomposition items of 281 township hospitals in Hunan province with panel data from 2000 to 2008. Results Among 281 township hospitals, less than half increased their scale efficiency, while more than half increased their total factor productivity, technology, whole efficiency and technical efficiency. Increasing technology and whole efficiency was the best way to improve total factor productivity. Besides, increasing technical efficiency and scale efficiency was the best way to improve whole efficiency. Conclusions The improvement of scale efficiency is key to developing the central township hospitals, while the improvement of technology is the key to developing general township hospitals.
ObjectiveTo measure the total factor productivity and its component changes of public secondary general hospitals in China from 2012 to 2018.MethodsFrom February to September in 2019, stratified systematic sampling method was used to collect the panel data of input and output indicators from 2012 to 2018 of 511 public secondary general hospitals in 5 provinces of China (Shandong, Hubei, Hainan, Anhui, and Shanxi), and Bootstrap-Malmquist-data envelopment analysis was used to calculate the total factor productivity and its component changes of the hospitals.ResultsFrom 2012 to 2018, the total factor productivity of the 511 public secondary general hospitals decreased by 0.22%, technical efficiency decreased by 5.24%, technical changes increased by 5.29%, pure technical efficiency decreased by 1.40%, and scale efficiency decreased by 3.89%, respectively.ConclusionsIn the past 7 years, the total factor productivity of public secondary general hospitals in China has declined slightly, mainly due to the decline of scale efficiency and pure technical efficiency, and the technological progress is the main reason for its improvement. The implications for the public secondary general hospitals are three folds: avoiding blind expansion and exploring optimum scale of beds, strengthening the internal fine management to improve the management practice and technical efficiency, and promoting technological progress by healthcare cooperating organizations.
Objective To establish a cooperative decision-making model of county-level public hospitals, so as to freely select the best partner in different decision-making units and promote the optimal allocation of medical resources. Methods The input and output data of 10 adjacent county-level public hospitals in Henan province from 2017 to 2019 was selected. Based on the traditional data envelopment analysis (DEA) model, a generalized fuzzy DEA cooperative decision-making model with better applicability to fuzzy indicators and optional decision-making units was constructed. By inputting index information such as total number of employees, number of beds, annual outpatient and emergency volume, number of discharged patients, total income and hospital grade evaluation, the cooperation efficiency intervals of different hospitals were calculated to scientifically select the best partner in different decision-making units.Results After substituting the data of 10 county-level public hospitals in H1-H10 into the model, taking H2 hospital as an example to make cooperative decision, among the four hospitals in H1, H2, H7 and H10 of the same scale, under optimistic circumstances, the best partner of H2 hospital was H7 hospital, and the cooperation efficiency value was 1.97; in a pessimistic situation, the best partner of H2 hospital was H10 hospital, and the cooperation efficiency value was 0.98. The model had good applicability in the cooperative decision-making of county-level public hospitals. Conclusion The generalized fuzzy DEA model can better evaluate the cooperative decision-making analysis between county-level public hospitals.
Anxiety disorder is a common emotional handicap, which seriously affects the normal life of patients and endangers their physical and mental health. The prefrontal cortex is a key brain region which is responsible for anxiety. Action potential and behavioral data of rats in the elevated plus maze (EPM) during anxiety (an innate anxiety paradigm) can be obtained simultaneously by using the in vivo and in conscious animal multi-channel microelectrode array recording technique. Based on maximum likelihood estimation (MLE), the action potential causal network was established, network connectivity strength and global efficiency were calculated, and action potential causal network connectivity pattern of the medial prefrontal cortex was quantitatively characterized. We found that the entries (44.13±6.99) and residence period (439.76±50.43) s of rats in the closed arm of the elevated plus maze were obviously higher than those in the open arm [16.50±3.25, P<0.001; (160.23±48.22) s, P<0.001], respectively. The action potential causal network connectivity strength (0.017 3±0.003 6) and the global efficiency (0.044 2±0.012 8) in the closed arm were both higher than those in the open arm (0.010 4±0.003 2, P<0.01; 0.034 8±0.011 4, P<0.001), respectively. The results suggest that the changes of action potential causal network in the medial prefrontal cortex are related to anxiety state. These data could provide support for the study of the brain network mechanism in prefrontal cortex during anxiety.