Clinical research progress in treatment of shoulder hand syndrome afterstroke with characteristic acupuncture combined with rehabilitation training / 国际中医中药杂志

The method of acupuncture combined with rehabilitation training in the treatment of shoulder hand syndrome after stroke is reliablet, quick, with simple operation and less adverse reactions. Among them, characteristic acupuncture could focus on the targeted points with obvious effect than ordinary acupuncture, and the combination with rehabilitation training could greatly improve the curative effect. However, there still exist some problems in the current research, such as the difficulty of conducting blind clinical trials of acupuncture therapy; the lack of follow-up data in the evaluation of curative effect, the uncertainty of long-term curative effect; the small sample size of clinical research, etc., so multi-centered and large sample RCT research are still needed.

High throughput detection and characterization of red blood cells deformability by combining optical tweezers with microfluidic technique / 生物医学工程学杂志

A high throughput measurement method of human red blood cells (RBCs) deformability combined with optical tweezers technology and the microfluidic chip was proposed to accurately characterize the deformability of RBCs statistically. Firstly, the effective stretching deformation of RBCs was realized by the interaction of photo-trapping force and fluid viscous resistance. Secondly, the characteristic parameters before and after the deformation of the single cell were extracted through the image processing method to obtain the deformation index of area and circumference. Finally, statistical analysis was performed, and the average deformation index parameters (

Automatic clustering method of flow cytometry data based on -distributed stochastic neighbor embedding / 生物医学工程学杂志

The traditional method of multi-parameter flow data clustering in flow cytometry is to mainly use professional software to manually set the door and circle out the target cells for analysis. The analysis process is complex and professional. Based on this, a clustering algorithm, which is based on -distributed stochastic neighbor embedding ( -SNE) algorithm for multi-parameter stream data, is proposed in the paper. In this algorithm, the Euclidean distance of sample data in high dimensional space is transformed into conditional probability to represent similarity, and the data is reduced to low dimensional space. In this paper, the stained human peripheral blood cells were treated by flow cytometry, and the processed data were derived as experimental sample data. The -SNE algorithm is compared with the kernel principal component analysis (KPCA) dimensionality reduction algorithm, and the main component data obtained by the dimensionality reduction are classified using -means algorithm. The results show that the -SNE algorithm has a good clustering effect on the cell population with asymmetric and trailing distribution, and the clustering accuracy can reach 92.55%, which may be helpful for automatic analysis of multi-color multi-parameter flow data.