Anti-tumor mechanism study on saffron by network pharmacology and reverse molecular docking / 药学实践杂志

Objective To explore the anti-tumor mechanism of saffron (Crocus sativus L.) by network pharmacology and reverse molecular docking techniques. Methods The main chemical components of saffron were obtained by searching published literature and TCMSP database. The potential targets of these components were predicted using PharmMapper server. The corresponding target genes were identified from UniProt database. The underlying anti-tumor targets of saffron were obtained by mapping the disease genes of cancer or tumor with GeneCards, OMIM and TTD databases. Cytoscape software was used to construct the action target network of saffron active components. The protein-protein interaction analysis was performed by String database, and the GO function and KEGG pathway enrichment analysis were performed by Metascape platform. Finally, molecular docking was performed to evaluate the binding of main components with their potential targets. Results A total of 9 active ingredients in saffron including quercetin, kaempferol, isorhamnetin, picrocrocin and crocin I, were identified, which might act on 37 key targets including AKT1, CCND1, MMP9, EGFR, TP53, involved in P53, TNF and other signaling pathways. Molecular docking indicated modest binding potency through hydrogen bonding, and hydrophobic interactions. Conclusion The anti-tumor effect of saffron was evaluated via the network of components-targets-pathways, which might provide a foundation for further research.

Follow control of upper limb rehabilitation training based on Kinect and NAO robot / 生物医学工程学杂志

Gesture imitation is a common rehabilitation strategy in limb rehabilitation training. In traditional rehabilitation training, patients need to complete training actions under the guidance of rehabilitation physicians. However, due to the limited resources of the hospital, it cannot meet the training and guidance needs of all patients. In this paper, we proposed a following control method based on Kinect and NAO robot for the gesture imitation task in rehabilitation training. The method realized the joint angles mapping from Kinect coordination to NAO robot coordination through inverse kinematics algorithm. Aiming at the deflection angle estimation problem of the elbow joint, a virtual space plane was constructed and realized the accurate estimation of deflection angle. Finally, a comparative experiment for deflection angle of the elbow joint angle was conducted. The experimental results showed that the root mean square error of the angle estimation value of this method in right elbow transverse deflection and vertical deflection directions was 2.734° and 2.159°, respectively. It demonstrates that the method can follow the human movement in real time and stably using the NAO robot to show the rehabilitation training program for patients.

Detection of inferior myocardial infarction based on morphological characteristics / 生物医学工程学杂志

Early accurate detection of inferior myocardial infarction is an important way to reduce the mortality from inferior myocardial infarction. Regrading the existing problems in the detection of inferior myocardial infarction, complex model structures and redundant features, this paper proposed a novel inferior myocardial infarction detection algorithm. Firstly, based on the clinic pathological information, the peak and area features of QRS and ST-T wavebands as well as the slope feature of ST waveband were extracted from electrocardiogram (ECG) signals leads Ⅱ, Ⅲ and aVF. In addition, according to individual features and the dispersion between them, we applied genetic algorithm to make judgement and then input the feature with larger degree into support vector machine (SVM) to realize the accurate detection of inferior myocardial infarction. The proposed method in this paper was verified by Physikalisch-Technische Bundesanstalt (PTB) diagnostic electrocardio signal database and the accuracy rate was up to 98.33%. Conforming to the clinical diagnosis and the characteristics of specific changes in inferior myocardial infarction ECG signal, the proposed method can effectively make precise detection of inferior myocardial infarction by morphological features, and therefore is suitable to be applied in portable devices development for clinical promotion.

An improved maximal information coefficient algorithm applied in the analysis of functional corticomuscular coupling for stroke patients / 生物医学工程学杂志

The functional coupling between motor cortex and effector muscles during autonomic movement can be quantified by calculating the coupling between electroencephalogram (EEG) signal and surface electromyography (sEMG) signal. The maximal information coefficient (MIC) algorithm has been proved to be effective in quantifying the coupling relationship between neural signals, but it also has the problem of time-consuming calculations in actual use. To solve this problem, an improved MIC algorithm was proposed based on the efficient clustering characteristics of K-means ++ algorithm to accurately detect the coupling strength between nonlinear time series. Simulation results showed that the improved MIC algorithm proposed in this paper can capture the coupling relationship between nonlinear time series quickly and accurately under different noise levels. The results of right dorsiflexion experiments in stroke patients showed that the improved method could accurately capture the coupling strength of EEG signal and sEMG signal in the specific frequency band. Compared with the healthy controls, the functional corticomuscular coupling (FCMC) in beta (14~30 Hz) and gamma band (31~45 Hz) were significantly weaker in stroke patients, and the beta-band MIC values were positively correlated with the Fugl-Meyers assessment (FMA) scale scores. The method proposed in this study is hopeful to be a new method for quantitative assessment of motor function for stroke patients.

Detection of inferior myocardial infarction based on densely connected convolutional neural network / 生物医学工程学杂志

Inferior myocardial infarction is an acute ischemic heart disease with high mortality, which is easy to induce life-threatening complications such as arrhythmia, heart failure and cardiogenic shock. Therefore, it is of great clinical value to carry out accurate and efficient early diagnosis of inferior myocardial infarction. Electrocardiogram is the most sensitive means for early diagnosis of inferior myocardial infarction. This paper proposes a method for detecting inferior myocardial infarction based on densely connected convolutional neural network. The method uses the original electrocardiogram (ECG) signals of serially connected Ⅱ, Ⅲ and aVF leads as the input of the model and extracts the robust features of the ECG signals by using the scale invariance of the convolutional layers. The characteristic transmission of ECG signals is enhanced by the dense connectivity between different layers, so that the network can automatically learn the effective features with strong robustness and high recognition, so as to achieve accurate detection of inferior myocardial infarction. The Physikalisch Technische Bundesanstalt diagnosis public ECG database was used for verification. The accuracy, sensitivity and specificity of the model reached 99.95%, 100% and 99.90%, respectively. The accuracy, sensitivity and specificity of the model are also over 99% even though the noise exists. Based on the results of this study, it is expected that the method can be introduced in the clinical environment to help doctors quickly diagnose inferior myocardial infarction in the future.

An automatic pulmonary nodules detection algorithm with multi-scale information fusion / 生物医学工程学杂志

Lung nodules are the main manifestation of early lung cancer. So accurate detection of lung nodules is of great significance for early diagnosis and treatment of lung cancer. However, the rapid and accurate detection of pulmonary nodules is a challenging task due to the complex background, large detection range of pulmonary computed tomography (CT) images and the different sizes and shapes of pulmonary nodules. Therefore, this paper proposes a multi-scale feature fusion algorithm for the automatic detection of pulmonary nodules to achieve accurate detection of pulmonary nodules. Firstly, a three-layer modular lung nodule detection model was designed on the deep convolutional network (VGG16) for large-scale image recognition. The first-tier module of the network is used to extract the features of pulmonary nodules in CT images and roughly estimate the location of pulmonary nodules. Then the second-tier module of the network is used to fuse multi-scale image features to further enhance the details of pulmonary nodules. The third-tier module of the network was fused to analyze the features of the first-tier and the second-tier module of the network, and the candidate box of pulmonary nodules in multi-scale was obtained. Finally, the candidate box of pulmonary nodules under multi-scale was analyzed with the method of non-maximum suppression, and the final location of pulmonary nodules was obtained. The algorithm is validated by the data of pulmonary nodules on LIDC-IDRI common data set. The average detection accuracy is 90.9%.

Lung nodule segmentation based on fuzzy c-means clustering and improved random walk algorithm / 生物医学工程学杂志

Accurate segmentation of pulmonary nodules is an important basis for doctors to determine lung cancer. Aiming at the problem of incorrect segmentation of pulmonary nodules, especially the problem that it is difficult to separate adhesive pulmonary nodules connected with chest wall or blood vessels, an improved random walk method is proposed to segment difficult pulmonary nodules accurately in this paper. The innovation of this paper is to introduce geodesic distance to redefine the weights in random walk combining the coordinates of the nodes and seed points in the image with the space distance. The improved algorithm is used to achieve the accurate segmentation of pulmonary nodules. The computed tomography (CT) images of 17 patients with different types of pulmonary nodules were selected for segmentation experiments. The experimental results are compared with the traditional random walk method and those of several literatures. Experiments show that the proposed method has good accuracy in the segmentation of pulmonary nodule, and the accuracy can reach more than 88% with segmentation time is less than 4 seconds. The results could be used to assist doctors in the diagnosis of benign and malignant pulmonary nodules and improve clinical efficiency.

Automatic multi-region segmentation of intracoronary optical coherence tomography images based on neutrosophic theory / 生物医学工程学杂志

Optical coherence tomography (OCT) has become a key technique in the diagnosis of coronary artery stenosis, which can identify plaques and vulnerable plaques in the image. Therefore, this technique is of great significance for the diagnosis of coronary heart disease. However, there is still a lack of automatic, multi-region, high-precision segmentation algorithms for coronary OCT images in the current research field. Therefore, this paper proposes a multi-zone, fully automated segmentation algorithm for coronary OCT images based on neutrosophic theory, which achieves high-precision segmentation of fibrous plaques and lipid regions. In this paper, the method of transforming OCT images into T in the area of neutrosophics is redefined based on the membership function, and the segmentation accuracy of fiber plaques is improved. For the segmentation of lipid regions, the algorithm adds homomorphic filter enhancement images, and uses OCT to transform OCT images into I in the field of neutrosophics, and further uses morphological methods to achieve high-precision segmentation. In this paper, 40 OCT images from 9 patients with typical plaques were analyzed and compared with the results of manual segmentation by doctors. Experiments show that the proposed algorithm avoids the over-segmentation and under-segmentation problems of the traditional neutrosophic theory method, and accurately segment the patch area. Therefore, the work of this paper can effectively improve the accuracy of segmentation of plaque for doctors, and assist clinicians in the diagnosis and treatment of coronary heart disease.

Effectiveness analysis of muscle fatigue in rehabilitation based on surface electromyogram / 生物医学工程学杂志

Muscle fatigue has widespread application in the field of rehabilitation medicine. The paper studies the muscle fatigue using surface electromyogram (sEMG) in the background of rehabilitation training system. The sEMG and ventilatory threshold of vastus lateralis, rectus femoris and erector spinae are collected synchronously and the electromyogram fatigue threshold (EMG ) of different sEMG was analyzed by increasing load cycling experiments of 10 healthy subjects. This paper also analyzes the effect of isotonic and isometric contraction on EMG . Results showed that the appeared time of EMG was earlier than that of ventilatory threshold in the incremental load cycling. While the differences were subtle and EMG was verified to be effective. EMG has been proven effective for different muscle contraction by comparing the EMG of vastus lateralis and erector spinae. EMG could be used to keep muscle injuries from overtraining in the process of rehabilitation. Therefore, EMG has a great significance for femoral shaft fractures's fatigue monitoring in rehabilitation training.

Coronary vessel intimal sequence extraction based on prior boundary constraints in optical coherence tomography image / 生物医学工程学杂志

Optical coherence tomography (OCT) is a new technique applied in cardiovascular system. It can detect vessel intimal, small structure of plaque surface and discover small lesions with its high axial resolution and quantification character. Especially with the application of OCT in characterization of coronary atherosclerotic plaque, diagnosis and treatment strategy making, optimizing percutaneous coronary intervention therapy and assessment after stent planting make the OCT become an efficient tool for cardiovascular disease diagnosis and treatment. This paper presents a novel coronary vessel intimal sequence extraction method based on prior boundary constraints in OCT image. On the basis of conventional Chan-Vese model, we modified the evolutionary weight function to control the evolutionary rate of boundary by adding local information of boundary curve. At the same time, we added the gradient energy term and intimal boundary constraint term based on priori boundary condition to further control the evolutionary of boundary curve. At last, coronary vessel intimal is extracted in a sequence way. The comparison with vessel intimal, manual segmented by clinical scientists (golden standard), indicates that our coronary vessel intimal extraction method is robust to intimal boundary blur, distortion, guide wire shadow and plaque disturbs. The results of this study can be applied to clinical aid diagnosis and precise diagnosis and treatment.

Utilization of and satisfaction at community health service：Comparative analysis between mi-grant workers and non-migrant workers in Shenzhen / 中国卫生政策研究

Objective:To explore the utilization of and satisfaction at community health service between migrant and non-migrant workers in Shenzhen city. Methods: Random sampling was used and 8000 community residents in Shenzhen city were investigated, and the data was analyzed with SPSS 18. 0. Results:There was statistically signifi-cant difference on the times of seeking community health services last year between migrant workers and non-migrant workers ( P<0. 0001 ) , and the proportion of more than three times service utilization of migrant workers were greater than that of non-migrant workers. The top three elements inpluencing satisfaction at community health service between migrant and non-migrant workers were service attitude ( 73. 29% vs. 73. 46%) , technical level ( 65. 29% vs. 67. 50%), and its convenience of seeking a doctor (63. 16% vs. 64. 98%). 73. 47% of users (migrant workers:74. 16%, non-migrant workers:69. 71%) were willing to accept the system of first contact in community health in-stitutions. Conclusions:The utilization of community health service has increased since implementing the system of first contact in community health institutions. Both migrant workers and non-migrant workers were very satisfied with the community health services, and the differences on satisfaction between the two groups were not significant. It is feasible to gradually promote the system of first contact in community health institutions over China.

A Standing Balance Evaluation Method Based on Largest Lyapunov Exponent / 生物医学工程学杂志

In order to evaluate the ability of human standing balance scientifically, we in this study proposed a new evaluation method based on the chaos nonlinear analysis theory. In this method, a sinusoidal acceleration stimulus in forward/backward direction was forced under the subjects' feet, which was supplied by a motion platform. In addition, three acceleration sensors, which were fixed to the shoulder, hip and knee of each subject, were applied to capture the balance adjustment dynamic data. Through reconstructing the system phase space, we calculated the largest Lyapunov exponent (LLE) of the dynamic data of subjects' different segments, then used the sum of the squares of the difference between each LLE (SSDLLE) as the balance capabilities evaluation index. Finally, 20 subjects' indexes were calculated, and compared with evaluation results of existing methods. The results showed that the SSDLLE were more in line with the subjects' performance during the experiment, and it could measure the body's balance ability to some extent. Moreover, the results also illustrated that balance level was determined by the coordinate ability of various joints, and there might be more balance control strategy in the process of maintaining balance.

Optimal solution and analysis of muscular force during standing balance / 生物医学工程学杂志

The present study was aimed at the optimal solution of the main muscular force distribution in the lower extremity during standing balance of human. The movement musculoskeletal system of lower extremity was simplified to a physical model with 3 joints and 9 muscles. Then on the basis of this model, an optimum mathematical model was built up to solve the problem of redundant muscle forces. Particle swarm optimization (PSO) algorithm is used to calculate the single objective and multi-objective problem respectively. The numerical results indicated that the multi-objective optimization could be more reasonable to obtain the distribution and variation of the 9 muscular forces. Finally, the coordination of each muscle group during maintaining standing balance under the passive movement was qualitatively analyzed using the simulation results obtained.

Effect of Wudi Dan on vitality and apoptosis of cartilage chondrocytes after osteoarthritis / 中国组织工程研究

BACKGROUND:Studies have found that Wudi Dan can suppress local inflammatory response of the lesioned joints to protect the articular cartilage. OBJECTIVE:To verify the effect of Wudi Dan on chondrocyte viability and apoptosis as wel as the therapeutic effect on osteoarthritis. METHODS:Rat chondrocytes were cultured in serum medium containing Wudi Dan, and the effects of Wudi Dan on cel viability and apoptosis were observed by comparison with the control group. Rabbit model of knee osteoarthritis was constructed using modified Hulth method. Rabbit models were divided into two groups:Wudi Dan group treated with Wudi Dan and control group treated with normal saline, twice a day, consecutively for 4 weeks. Therapeutic effect of Wudi Dan on knee osteoarthritis was observed;cel viability and apoptosis were observed under microscope;the levels of interleukin-1 and matrix metal oproteinase-3 were determined using immunohistochemical method. RESULTS AND CONCLUSION:The apoptotic rate of chondrocytes was significantly lower in the Wudi Dan group than the control group. Pathological findings of the rabbit knee joints showed that the control group had more severe damage to the articular cartilage than the Wudi Dan group. Immunohistochemical staining revealed that in the Wudi Dan group, the cytoplasm and extracel ular matrix were colored light and there were a smal number of positive cel s as wel as low expression of interleukin-1 and matrix metal oproteinase-3. The results suggest that Wudi Dan can effectively protect against articular cartilage lesions, reduce inflammation, and have a good therapeutic effect on osteoarthritis. Its mechanism may be related to inhibition of chondrocyte apoptosis, reduction of cytokine production and inhibition of protein expression of matrix metal oproteinase.

A modeling method for human standing balance system based on T-S fuzzy identification / 生物医学工程学杂志

In order to develop safe training intensity and training methods for the passive balance rehabilitation train- ing system, we propose in this paper a mathematical model for human standing balance adjustment based on T-S fuzzy identification method. This model takes the acceleration of a multidimensional motion platform as its inputs, and human joint angles as its outputs. We used the artificial bee colony optimization algorithm to improve fuzzy C--means clustering algorithm, which enhanced the efficiency of the identification for antecedent parameters. Through some experiments, the data of 9 testees were collected, which were used for model training and model results validation. With the mean square error and cross-correlation between the simulation data and measured data, we concluded that the model was accurate and reasonable.

An improved wavelet threshold algorithm for ECG denoising / 生物医学工程学杂志

Due to the characteristics and environmental factors, electrocardiogram (ECG) signals are usually interfered by noises in the course of signal acquisition, so it is crucial for ECG intelligent analysis to eliminate noises in ECG signals. On the basis of wavelet transform, threshold parameters were improved and a more appropriate threshold expression was proposed. The discrete wavelet coefficients were processed using the improved threshold parameters, the accurate wavelet coefficients without noises were gained through inverse discrete wavelet transform, and then more original signal coefficients could be preserved. MIT-BIH arrythmia database was used to validate the method. Simulation results showed that the improved method could achieve better denoising effect than the traditional ones.

Linear features analysis of human body balance regulation under passive movement / 生物医学工程学杂志

In order to find the linear region of adjustment process about human body balance under the passive movement, and provide the basis for the unified evaluation criteria of passive balance test, an equipment was built with pulsed excitation source and wave detector of gravity's center. The pulsed excitation source was a multi-dimensional motion platform with high accuracy. The wave detector was a force platform. Human body and force platform were treated as a whole object, and the dynamic model of the object was built using the method of system identification. The balance ability was evaluated by setting time. In the pulse excitement range from 2mm to 20 mm with 2mm increments, balance ability of 5 students was evaluated and analyzed respectively. Results showed that response curve of human balance regulation was a typical second order linear system characteristic, and in a large enough linear region, the evaluating result had good consistency.