Using modular identification methods in gene-drug multiplex networks to infer new gene-drug associations can identify new therapeutic target genes for known drugs. In this paper, based on the gene expression data and drug response data of lung cancer in the genomics of drug sensitivity in cancer (GDSC) database, a multiple network algorithm is proposed. First, a heterogeneous network of genes of lung cancer and drugs in different cell lines is constructed, and then a network module identification method based on graph entropy is used. In this heterogeneous network, network modules are identified, and five lung cancer gene-drug association modules are identified through iterative convergence. Compared with other methods, the algorithm has better results in terms of running time, accuracy and robustness, and the identified modules have obvious biological significance. The research results in this article have guiding significance for the medication and treatment of lung cancer, and can provide references for the treatment of other diseases with the same targeted genes.
ObjectiveTo introduce a new method for identifying intersegmental planes during thoracoscopic segmentectomy using pulmonary circulation single-blocking in the target segment. MethodsTo retrospectively analyze the clinical data of 83 patients who underwent thoracoscopic pulmonary segmentectomy from January 2019 to March 2020 using the pulmonary circulation single-blocking method. There were 33 males and 50 females, with a median age of 54 (46-65) years, and they were divided into a single vein group (SVG, n=31) and a single artery group (SAG, n=52), and the clinical data of two groups were compared. ResultsThe intersegmental planes were identified successfully in both groups and there were no statistically significant differences between the two groups in terms of intersegmental plane management (P=0.823), operating time (P=0.786), intraoperative blood loss (P=0.775), chest drainage time (P=0.659), postoperative hospital stay (P=0.824) or the incidence of postoperative complications (P=1.000). ConclusionThe use of pulmonary circulation single-blocking for intersegmental plane identification during thoracoscopic segmentectomy is safe and feasible, and the intersegmental plane can be satisfactorily identified by the single-blocking of arteries or veins.
Carbapenemase producing Enterobacteriaceae (CPE) has emerged as a significant global public health challenge and placing infected patients at risk of potentially untreatable infections. When resistance to carbapenems occurs, there are often few alternative treatments available. Numerous international guidelines have performed systematic and evidence review to identify new strategies to prevent the entry and spread of CPE in healthcare settings. Several key strategies have been shown to be highly effective. Firstly a new strategy that is proven to be effective is the early identification of the CPE carrier patients through active surveillance cultures. While waiting for the screening results, suspected CPE carriers will be put on preemptive isolation in single room and healthcare worker will at the same time practice contact precautions. The active surveillance culture and prompt preemptive isolation will limit the entry and spread of CPE from getting into hospital. Secondly, it is of utmost importance to incorporate enforcement of the basic infection prevention and control best practices in the hospital including, full compliance to hand hygiene, appropriate use of personal protective equipment, execute antibiotic stewardship program to control abuse of antibiotics, effective environmental cleaning and decontamination, staff education and feedback, as well as surveillance of healthcare-associated infections. Such a holistic approach has been shown to be effective in inhibiting CPE from gaining foothold in the hospital.
In order to develop safe training intensity and training methods for the passive balance rehabilitation training 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.
In this paper, the research has been conducted by the Microsoft kinect for windows v2 for obtaining the walking trajectory data from hemiplegic patients, based on which we achieved automatic identification of the hemiplegic gait and sorted the significance of identified features. First of all, the experimental group and two control groups were set up in the study. The three groups of subjects respectively completed the prescribed standard movements according to the requirements. The walking track data of the subjects were obtained straightaway by Kinect, from which the gait identification features were extracted: the moving range of pace, stride and center of mass (up and down/left and right). Then, the bayesian classification algorithm was utilized to classify the sample set of these features so as to automatically recognize the hemiplegia gait. Finally, the random forest algorithm was used to identify the significance of each feature, providing references for the diagnose of disease by ranking the importance of each feature. This thesis states that the accuracy of classification approach based on bayesian algorithm reaches 96%; the sequence of significance based on the random forest algorithm is step speed, stride, left-right moving distance of the center of mass, and up-down moving distance of the center of mass. The combination of step speed and stride, and the combination of step speed and center of mass moving distance are important reference for analyzing and diagnosing of the hemiplegia gait. The results may provide creative mind and new references for the intelligent diagnosis of hemiplegia gait.
Objective To investigate the effect of monocyte chemoattractant protein 1 (MCP-1) on the migration of the induced and differentiated mouse bone marrow mesenchymal stem cells (BMSCs) for raising the efficacy of intravenous transplantation of BMSCs. Methods The BMSCs were cultured with the method of differential adhesion and density gradient centrifugation of C57/BL10 mice, and were identified by alkal ine phosphatase Gomori modified staining after osteogenic inducing. At the 3rd passage, the BMSCs were induced to the myoblasts with 5-azacytidine (5-Aza). The chemotaxis of MCP-1 in the induced and differentiated BMSCs in vitro at concentrations of 25, 50, 100, 200, and 400 ng/mL was observed through the migration test, by counting the number of the migrated cells. The expression of the chemokine receptor 2 (CKR-2) in the induced and differentiated BMSCs was detected with the flow cytometry. Results The cells could be cultured with the methods of differential adhesion and density gradient centrifugation and still had higher prol iferative and differentiative potency; the induced cells at the 3rd passage could differenciate to the osteoblasts, confirming that the cells were BMSCs; the myogenic induced BMSCs possesed the sarcotubule structure. The number of the migrating BMSCs at MCP-1 concentrations of 25-400 ng/ mL were respectively 35.066 7 ± 6.584 2, 43.200 0 ± 6.460 8, 44.466 7 ± 4.823 5, 45.600 0 ± 8.650 3, and 50.733 3 ± 7.582 5; showing significant difference when compared with control group (28.333 3 ± 8.917 6, P lt; 0.05), and presenting significant difference among 25, 50, 400 ng/mL groups compared with each other (P lt; 0.05). The expression of CKR-2 in the mouse BMSCs (48.0%) was significantly higher (P lt; 0.001) than those of blank control (0.6%) and negative control (17.0%). Conclusion The results indicate that the MCP-1 can induce the migration of mouse BMSCs by MCP-1/CKR-2 pathway.
In this research a strain of isolated Pseudomonas alcaligenes which causes degradation of dexamethasone was acclimated further and its proteins of every position in the bacterium were separated by the osmotic shock method. The separated intracellular proteins which had the highest enzyme activity were extracted by the salting out with ammonium sulfate and were purified with the cation exchange chromatography and gel chromatography. The purified proteins which was active to cause degradation of dexamethasone had been detected were cut with enzyme and were analyzed with mass spectrometry. The results showed that the degradation rate to dexamethasone by acclimated Pseudomonas alcaligenes were increased from 23.63% to 52.84%. The degrading enzymes were located mainly in the intracellular of the bacteria and its molecular weight was about 41 kD. The specific activity of the purified degrading enzymes were achieved to 1.02 U·mg-1. Its 5-peptide amino acid sequences were consistent with some sequences of the isovaleryl-CoA dehydrogenase. The protein enzyme may be a new kind degrading enzyme of steroidal compounds. Our experimental results provided new strategies for cleanup of dexamethasone in water environment with microbial bioremediation technique.
ObjectiveTo compare the biological features of early and late endothelial progenitor cells (EPCs) by isolating and culturing early and late EPCs from the human peripheral blood so as to find some unique properties of EPCs and to propose a suitable strategy for EPCs identification. MethodsMononuclear cells were isolated from the human peripheral blood using density gradient centrifugation. Then, the cells were inoculated in human fibronectin-coated culture flasks and cultured in endothelial cell basal medium 2. After 4-7 days and 2-3 weeks culture, early and late EPCs were obtained respectively. The morphology, proliferation potential, surface markers, cytokine secretion, angiogenic ability, and nitric oxide (NO) release were compared between 2 types of EPCs. Meanwhile, the human aortic endothelial cells (HAECs) were used as positive control. ResultsThe morphology of early and late EPCs was different:early EPCs formed a cell cluster with a spindle shape after 4-7 days of culture, and late EPCs showed a cobblestone appearance. Late EPCs were characterized by high proliferation potential and were able to form capillary tubes on Matrigel, but early EPCs did not have this feature. Both types EPCs could ingest acetylated low density lipoprotein and combine with ulex europaeus Ⅰ. Flow cytometry analysis showed that early EPCs did not express CD34 and CD133, but expressed the CD14 and CD45 of the hematopoietic stem cell markers;however, late EPCs expressed CD31 and CD34 of the endothelial cell markers, but did not express CD14, CD45, and CD133. By RT-PCR analysis, the expressions of vascular endothelial growth receptor 2 and vascular endothelial cadherin in early EPCs were significantly lower than those in the late EPCs and HAECs (P<0.05), but no significant difference was found in the expression of von Willebrand factor and endothelial nitric oxide synthase (eNOS) between 2 type EPCs (P>0.05). The concentrations of vascular endothelial growth factor, granulocyte colony-stimulating factor, and interleukin 8 were significantly higher in the supernatant of early EPCs than late EPCs (P<0.05). Western blot assay indicated eNOS expressed in both types EPCs, while the expression of eNOS in late EPCs was significantly higher than early EPCs at 5 weeks (P<0.05). Both cell types could produce similar amount of NO (P>0.05). ConclusionThe expression of eNOS and the production of NO could be used as common biological features to identify EPCs, and the strategy of a combination of multiple methods for EPCs identification is more feasible.
Objective To evaluate the effectiveness and safety of pure carbon dioxide (CO2) combined with a modified inflation-deflation technique for identifying the intersegmental plane during thoracoscopic segmentectomy. Methods A prospective study was conducted, enrolling 30 patients diagnosed with pulmonary nodules who underwent thoracoscopic anatomical segmentectomy at the Department of Thoracic Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, from March 2024 to March 2025. Patients were randomly assigned to one of two groups using a random number table: A pure oxygen group (O2 group, n=15, 8 females, 7 males, age 28-75 years) and a pure carbon dioxide group (CO2 group, n=15, 8 females, 7 males, age 37-69 years). All patients underwent preoperative three-dimensional computed tomography bronchovascular angiography to reconstruct pulmonary vessels, bronchi, and the virtual intersegmental plane. The time to identification of the ideal intersegmental plane was recorded intraoperatively, along with arterial blood gas measurements before lung inflation and at 5 and 15 minutes after lung inflation on the surgical side. Results The time to identify the intersegmental plane was significantly shorter in the CO2 group compared to the O2 group [(151.1±39.5) s vs. (998.7±78.9) s, P<0.001], and there were no significant fluctuations in intraoperative oxygen saturation in patients in the CO2 group. Furthermore, there were no statistically significant differences between the two groups in terms of operation duration, intraoperative blood loss, postoperative extubation time, total postoperative chest tube drainage, postoperative length of hospital stay, or postoperative complication rate (all P>0.05). Conclusion Pure CO2 combined with a modified inflation-deflation technique can rapidly, accurately, and clearly identify the intersegmental plane, and its safety is non-inferior to that of the pure O2 method, making it worthy of clinical promotion and application.
Based on bioelectrical impedance theory and pattern recognition algorithm, we in this study measured varieties of people's bioelectrical impedance in hands and identified different people according to their bioelectrical impedance. We designed a bioelectrical impedance collection circuit with AD5933 chip to measure the impedance in different people's hands, and we obtained the bioelectrical impedance spectrum for each person under 1-100 kHz electrical stimulation. We calculated the segmentation slopes of bioelectrical impedance spectrum, and took the slopes as characteristic parameters. In order to promote the recognition rate and prevent the overfitting of the model, we divided the people into the training set and the test set, and designed a 3 layer back propagation neural network model to train and test the samples. The results showed that back propagation neural network model could identify the test set effectively. The recognition rate of the training sets was as high as 97.62%, recognition rate of validation sets was 88.79%, recognition rate of test sets was 86.34%, and the synthetical recognition rate was 94.22%. It gives a clue that the network can perfectly recognize people in the training network as well as strangers that comes from the outside of the tests. Our work can verify the feasibility and reliability of using bioelectrical impedance and pattern recognition algorithm for identification, and can provide a simple and supplementary way to identify people.