Objective] Discussion on academic ideas and clinical experience of professor Dong in treatment of varicocele sterility.[Methods]From academic theory, etiology and pathogenesis, therapeutic principle treatment aspects in professor Dong diagnosis and treatment of varicocele sterility certificate academic view and clinical experience, to summarize its characteristic diagnostic medicine.[Results] Professor Dong considers varicocele infertility disease in liver and kidney, etiology and pathogenesis is kidney, liver, blood stasis, based on the kidney essence deficiency, diseases with ease, and blood stasis resistance as the standard, the causal, with kidney and liver qi activating blood method in the treatment of varicocele thought and method has achieved good clinical therapeutic effect. [Conclusion]The clinical experience of professor Dong in treatment of varicocele syndrome is effective, has the value of popularization and application.

AIM:To explore the fingerprint method for quality control of Danhong sterile powder for injection (Radix et Rhizoma salviae mihiorrhizae,Flos carthami).METHODS:The samples were determined by Agilent 1100 DAD-HPLC with SinoChrom ODS-BP column(250 mm×4.6 mm,5 μm),by gradient elution using methanol-0.1% phosphoric acid,as mobile phase 30 ℃ column temperature.flow rate of 1.0 mL/min,detection wavelength was set at 280 nm,and inject volume 20 μL.RESULTS:Its fingerprint exhibited better separation for each peak,revealing amount of finger information,Based on the ten batches of Danhong sterile powder for injection,according to the technical requirements of fingerprint on injection of Chinese traditional medicine.CONCLUSION:Proposed HPLC fingerprint can be used as the important evidences for the quality control of Danhong Injection.

AIM:To explore the fingerprint method for quality control of Danhong sterile powder for injection(Radix et Rhizoma salviae miltiorrhizae,Flos carthami).METHODS:The samples were determined by Agilent 1100 DAD-HPLC with SinoChrom ODS-BP column(250 mm?4.6 mm,5 ?m),by gradient elution using methanol-0.1% phosphoric acid,as mobile phase 30 ℃ column temperature,flow rate of 1.0 mL/min,detection wavelength was set at 280 nm,and inject volume 20 ?L.RESULTS:Its fingerprint exhibited better separation for each peak,revealing amount of finger information,Based on the ten batches of Danhong sterile powder for injection,according to the technical requirements of fingerprint on injection of Chinese traditional medicine.CONCLUSION:Proposed HPLC fingerprint can be used as the important evidences for the quality control of Danhong Injection.

A hybrid segmentation algorithm is proposed for automatic segmentation of blood cell images based on adaptive multi-scale thresholding and seeded region growing techniques. Firstly, an adaptive and scale space filter (ASSF) is applied to image histogram and a scale space image is built. According to the properties of the scale space image, proper thresholds can be obtained to separate the nucleus from the original image and the white blood cells are located. Secondly, the local color similarity and global morphological criteria constrain seeded region growing in order to finish the segmentation of the cytoplasm. The detection accuracy of white blood cell is 98% and the segmentation accuracy based on the subjective evaluation is 93%. Test shows that this algorithm is effective for automatic segmentation of white blood cells.
Algorithms ; Automation ; Blood Cells ; Cell Nucleus ; ultrastructure ; Color ; Cytoplasm ; ultrastructure ; Humans ; Image Enhancement ; Leukocytes

This paper explores the use of wavelet packet analysis to extract features from spontaneous electroencephalogram (EEG) during three different mental tasks. Artifact-free EEG segments are transformed to multi-scale representations by dyadic wavelet packet decomposition channel by channel. Their feature vectors formed by energy values of different sub-spaces EEG components are used as inputs of a radial basis function network to test the classification accuracies of three task pairs. The results indicate that the classification accuracies of the wavelet packet analysis method are significantly better than those of autoregressive model method. Wavelet packet analysis would be a promising method to extract features from EEG signals.
Electroencephalography ; Humans ; Mental Processes ; physiology ; Models, Statistical ; Multivariate Analysis ; Neural Networks (Computer) ; Regression Analysis ; Signal Processing, Computer-Assisted

The support vector machine (SVM) is a new learning technique based on the statistical learning theory. It was originally developed for two-class classification. In this paper, the SVM approach is extended to multi-class classification problems, a hierarchical SVM is applied to classify blood cells in different maturation stages from bone marrow. Based on stepwise decomposition, a hierarchical clustering method is presented to construct the architecture of the hierarchical (tree-like) SVM, then the optimal control parameters of SVM are determined by some criterion for each discriminant step. To verify the performances of classifiers, the SVM method is compared with three classical classifiers using 3-fold cross validation. The preliminary results indicate that the proposed method avoids the curse of dimensionality and has greater generalization. Thus, the method can improve the classification correctness for blood cells from bone marrow.
Algorithms ; Blood Cells ; classification ; Cluster Analysis ; Computational Biology ; methods ; Humans ; In Vitro Techniques ; Least-Squares Analysis ; Models, Biological ; Nonlinear Dynamics

Biological studies show that place cells are the main basis for rats to know their current location in space. Since grid cells are the main input source of place cells, a mapping model from grid cells to place cells needs to be constructed. To solve this problem, a neural network mapping model of back propagation error from grid cells to place cells is proposed in this paper, which can accurately express the location in a given region. According to the physiological characteristics of border cells' specific discharge to the environment, the periodic resetting of the grid field phase by border cells is realized, and the position recognition in any space is completed by this model. In this paper, we designed a simulation experiment to compare the activity of the theoretical place cell plate, and then compared the time consumption of the competitive neural network model and the positioning error of RatSLAM pose cells plate. The experimental results showed that the proposed model could obtain a single place field, and the algorithm efficiency was improved by 85.94% compared with the competitive neural network model in the time-consuming experiment. In the localization experiment, the mean localization error was 41.35% lower than that of RatSLAM pose cells plate. Therefore, the location cognition model proposed in this paper can not only realize the efficient transfer of information between grid cells and place cells, but also realize the accurate location of its own location in any spatial area.

The method of directly using speed information and angle information to drive attractors model of grid cells to encode environment has poor anti-interference ability and is not bionic. In response to the problem, this paper proposes a grid field calculation model based on perceived speed and perceived angle. The model has the following characteristics. Firstly, visual stream is decoded to obtain visual speed, and speed cell is modeled and decoded to obtain body speed. Visual speed and body speed are integrated to obtain perceived speed information. Secondly, a one-dimensional circularly connected cell model with excitatory connection is used to simulate the firing mechanism of head direction cells, so that the robot obtains current perception angle information in a biomimetic manner. Finally, the two kinds of perceptual information of speed and angle are combined to realize the driving of grid cell attractors model. The proposed model was experimentally verified. The results showed that this model could realize periodic hexagonal firing field mode of grid cells and precise path integration function. The proposed algorithm may provide a foundation for the research on construction method of robot cognitive map based on hippocampal cognition mechanism.
Action Potentials ; Computer Simulation ; Computer Systems ; Entorhinal Cortex ; Grid Cells ; Hippocampus ; Models, Neurological