Males typically have high rates of morbidity of primary bladder neck obstruction, while the existing urodynamic examination is invasive and more likely to cause false diagnosis. To build a non-invasive biomechanical detecting system for the male lower urinary tract, a finite element model for male lower urinary tract based on the collodion slice images of normal male lower urinary tract was constructed, and the fluid-structure interaction of the lower urinary tract was simulated based on the real urination environment. The finite element model of the lower urinary tract was validated by comparing the clinical experiment data with the simulation result. The stress, flow rate and deformation of the lower urinary tract were analyzed, and the results showed that the Von Mises stress and the wall shear stress at the membrane sphincter in the normal male lower urinary tract model reached a peak, and there was nearly 1 s delay than in the bladder pressure, which helped to validate the model. This paper lays a foundation for further research on the urodynamic response mechanism of the bladder pressure and flow rate of the lower urinary tract obstruction model, which can provide a theoretical basis for the research of non-invasive biomechanical detecting system.
Features and interaction between features of liver disease is of great significance for the classification of liver disease. Based on least absolute shrinkage and selection operator (LASSO) and interaction LASSO, the generalized interaction LASSO model is proposed in this paper for liver disease classification and compared with other methods. Firstly, the generalized interaction logistic classification model was constructed and the LASSO penalty constraints were added to the interactive model parameters. Then the model parameters were solved by an efficient alternating directions method of multipliers (ADMM) algorithm. The solutions of model parameters were sparse. Finally, the test samples were fed to the model and the classification results were obtained by the largest statistical probability. The experimental results of liver disorder dataset and India liver dataset obtained by the proposed methods showed that the coefficients of interaction features of the model were not zero, indicating that interaction features were contributive to classification. The accuracy of the generalized interaction LASSO method is better than that of the interaction LASSO method, and it is also better than that of traditional pattern recognition methods. The generalized interaction LASSO method can also be popularized to other disease classification areas.
Fatigue is an exhaustion state caused by prolonged physical work and mental work, which can reduce working efficiency and even cause industrial accidents. Fatigue is a complex concept involving both physiological and psychological factors. Fatigue can cause a decline of concentration and work performance and induce chronic diseases. Prolonged fatigue may endanger life safety. In most of the scenarios, physical and mental workloads co-lead operator into fatigue state. Thus, it is very important to study the interaction influence and its neural mechanisms between physical and mental fatigues. This paper introduces recent progresses on the interaction effects and discusses some research challenges and future development directions. It is believed that mutual influence between physical fatigue and mental fatigue may occur in the central nervous system. Revealing the basal ganglia function and dopamine release may be important to explore the neural mechanisms between physical fatigue and mental fatigue. Future effort is to optimize fatigue models, to evaluate parameters and to explore the neural mechanisms so as to provide scientific basis and theoretical guidance for complex task designs and fatigue monitoring.
Atherosclerosis is a complex disease characterized by lipid accumulation in the vascular wall and influenced by multiple genetic and environmental factors. To understand the mechanisms of molecular regulation related to atherosclerosis better, a protein interaction network was constructed in the present study. Genes were collected in nucleotide database and interactions were downloaded from Biomolecular Object Network Database (BOND). The interactional data were imported into the software Cytoscape to construct the interaction network, and then the degree characteristics of the network were analyzed for Hub proteins. Statistical significance pathways and diseases were figured out by inputting Hub proteins to KOBAS2.0. The complete pathway network related to atherosclerosis was constructed. The results identified a series of key genes related to atherosclerosis, which would be the potential promising drug targets for effective prevention.
The eye-computer interaction technology based on electro-oculogram provides the users with a convenient way to control the device, which has great social significance. However, the eye-computer interaction is often disturbed by the involuntary eye movements, resulting in misjudgment, affecting the users’ experience, and even causing danger in severe cases. Therefore, this paper starts from the basic concepts and principles of eye-computer interaction, sorts out the current mainstream classification methods of voluntary/involuntary eye movement, and analyzes the characteristics of each technology. The performance analysis is carried out in combination with specific application scenarios, and the problems to be solved are further summarized, which are expected to provide research references for researchers in related fields.
ObjectiveTo investigate the correlation between expression of stromal interaction molecule 1 (STIM1) and tumor malignant degree or lymph node metastasis in patients with gastric cancer. MethodsA total of 83 patients with gastric cancer treated in the Affiliated Hospital of Southwest Medical University and Sichuan Mianyang 404 Hospital from October 2018 to April 2021 were collected. The expression of STIM1 protein in the gastric cancer tissues and the corresponding adjacent normal gastric tissues was detected by immunohistochemistry method. Meanwhile the correlation between the expression of STIM1 protein and clinicopathologic features or postoperative lymph node status of the patients with gastric cancer was analyzed. ResultsThe positive rate of STIM1 protein expression in the gastric cancer tissues was 95.2% (79/83), including 62 (74.7%) patients with high expression (STIM1 scoring 5–7) and 21 (25.3%) patients with low expression (STIM1 scoring 2–4), which in the corresponding adjacent normal gastric tissues was 41.0% (34/83), the difference was statistically significant (χ2=58.078, P<0.001). The expression of STIM1 protein was not related to gender, age, and tumor size of the patients with gastric cancer (P>0.05), while the proportions of the patients with high expression of STIM1 protein in the gastric cancer patients with low/undifferentiated tumor, T3+T4 of infiltration depth, TNM stage Ⅲ, and lymph node metastasis were higher than those with high/medium differentiation (χ2=11.052, P=0.001), T1+T2 of infiltration depth (χ2=24.720, P<0.001), TNM stage Ⅰ+Ⅱ (χ2=9.980, P=0.002), and non-lymph node metastasis (χ2=6.097, P=0.014). The expression intensity of STIM1 protein was positively correlated with the number of lymph node metastasis (r=0.552, Z=–3.098, P=0.002) and the rate of lymph node metastasis (r=0.561, Z=–6.387, P<0.001). ConclusionsPositive rate of STIM1 protein expression in gastric cancer tissues is relatively high. STIM1 protein expression in gastric cancer tissue is closely related to tumor malignancy and lymph node metastasis, so it might play an important role in progression of gastric cancer.
Integrating visualization toolkit and the capability of interaction, bidirectional communication and graphics rendering which provided by HTML5, we explored and experimented on the feasibility of remote medical image reconstruction and interaction in pure Web. We prompted server-centric method which did not need to download the big medical data to local connections and avoided considering network transmission pressure and the three-dimensional (3D) rendering capability of client hardware. The method integrated remote medical image reconstruction and interaction into Web seamlessly, which was applicable to lower-end computers and mobile devices. Finally, we tested this method in the Internet and achieved real-time effects. This Web-based 3D reconstruction and interaction method, which crosses over internet terminals and performance limited devices, may be useful for remote medical assistant.
ObjectiveTo summarize the current status of research in the correlation between the liver diseases and oral microbiota, to provide the scientific basis for the prevention and treatment of oral diseases in the patients with liver diseases, and to provide the guidance for further research on the biomarkers for the noninvasive diagnosis of liver diseases.MethodThe related literatures about the studies of correlation between liver diseases and oral microbiota were reviewed by searching the databases such as the PubMed, Web of Science, CNKI, and Wanfang, etc.ResultsAs the second richest microbiota, the oral flora closely interacted with the hepatitis, alcoholic liver disease, non-alcoholic fatty liver disease, cirrhosis, liver cancer, etc. Meanwhile, the prognosis of patients underwent liver transplantation was also closely correlated to oral flora.ConclusionsSpecific oral flora in patients with different liver diseases may be a potential non-invasive diagnostic biomarker. At the same time, it is necessary to pay attention to oral health and maintain oral microbiota balance for preventing and treating of liver diseases.
Real-world studies (RWSs) data are based on real medical scenes and reflect clinical facts. Besides, RWSs adapts to the characteristics of therapeutic principles of traditional Chinese medicine and the medical reality of the combination of Western and traditional Chinese medicine, which makes the safety assessment of herb-drug interaction more efficient and economical. During RWSs, more attention should be paid on the validity and reliability of data, especially the standardization of the data collection process and its contents. The safety assessment of herb-drug interaction will combine the methods of active surveillance study, big data analysis, and be based on precision medicine in the future
Brain-computer interface (BCI) can establish a direct communications pathway between the human brain and the external devices, which is independent of peripheral nerves and muscles. Compared with invasive BCI, non-invasive BCI has the advantages of low cost, low risk, and ease of operation. In recent years, using non-invasive BCI technology to control devices has gradually evolved into a new type of human-computer interaction manner. Moreover, the control strategy for BCI is an essential component of this manner. First, this study introduced how the brain control techniques were developed and classified. Second, the basic characteristics of direct and shared control strategies were thoroughly explained. And then the benefits and drawbacks of these two strategies were compared and further analyzed. Finally, the development direction and application prospects for non-invasive brain control strategies were suggested.
