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.
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 establish a simple and efficient method to isolate and culture the umbilical vein vascular endothelial cells in canine. Methods Twelve umbilical cords [(13.0 ± 1.5) cm in length] were taken from 12 newborn pups of Beagles. And then the vascular endothelial cells were isolated from these umbilical cords digested by 1% collagenase type I for 5, 7, and 10 minutes respectively (4 umbilical cords in each group). After cultured, the vascular endothelial cells were identified by morphology, immunofluorescence, and flow cytometry. And the growth curvature of umbilical vein vascular endothelial cells was detected by MTT assay. Results Few vascular endothelial cells were collected at 5 and 10 minutes after digestion; many vascular endothelial cells were seen at 7 minutes, and became cobblestone with culture time, with a large nucleus; after passage, cell morphology had no obvious change. Fluorescence microscope results showed that positive von Willebrand factor (vWF) and CD31 cells were observed in most of cells. The flow cytometry test displayed that the positive cell rates of vWF and CD31 were 99.0% ± 0.7% and 98.0% ± 1.2%, respectively. The above results indicated that cultured cells were vascular endothelial cells. MTT assay showed that vascular endothelial cells proliferation increased significantly with culture time. Conclusion Enzyme digestion is a convenient method to isolate vascular endothelial cells from canine umbilical vein, and a large number of cells and high purity of cells can be obtained by the method.
Acute respiratory distress syndrome (ARDS) is a serious threat to human life and health disease, with acute onset and high mortality. The current diagnosis of the disease depends on blood gas analysis results, while calculating the oxygenation index. However, blood gas analysis is an invasive operation, and can’t continuously monitor the development of the disease. In response to the above problems, in this study, we proposed a new algorithm for identifying the severity of ARDS disease. Based on a variety of non-invasive physiological parameters of patients, combined with feature selection techniques, this paper sorts the importance of various physiological parameters. The cross-validation technique was used to evaluate the identification performance. The classification results of four supervised learning algorithms using neural network, logistic regression, AdaBoost and Bagging were compared under different feature subsets. The optimal feature subset and classification algorithm are comprehensively selected by the sensitivity, specificity, accuracy and area under curve (AUC) of different algorithms under different feature subsets. We use four supervised learning algorithms to distinguish the severity of ARDS (P/F ≤ 300). The performance of the algorithm is evaluated according to AUC. When AdaBoost uses 20 features, AUC = 0.832 1, the accuracy is 74.82%, and the optimal AUC is obtained. The performance of the algorithm is evaluated according to the number of features. When using 2 features, Bagging has AUC = 0.819 4 and the accuracy is 73.01%. Compared with traditional methods, this method has the advantage of continuously monitoring the development of patients with ARDS and providing medical staff with auxiliary diagnosis suggestions.
ObjectiveTo explore value of ultrasound real-time elastography (RTE) technology for identification of benign and malignant solid thyroid nodules.MethodsA retrospective analysis was performed on 125 patients with thyroid nodules who underwent ultrasound RTE in this hospital from February 2018 to August 2019. All patients underwent RTE on the basis of conventional ultrasound. The ultrasound elasticity contrast index (ECI) was used as the evaluation index and the pathological examination result was used as the gold standard. The receiver operating characteristic (ROC) curve analysis was used to evaluate the value of ECI in the identification of benign and malignant solid thyroid nodules. Logistic regression analysis was used to analyze the influencing factors of ECI.ResultsAmong the 125 patients with solid thyroid nodules, 51 were malignant nodules, 74 were benign nodules. The ECI value of patients with benign thyroid nodules was lower than that of patients with malignant nodules (2.71±0.83 versus 3.42±1.14, t=–4.030, P<0.001). The result of ROC analysis showed that the cutoff value of ECI to distinguish benign and malignant solid thyroid nodules was 3.07, area under curve of ROC was 0.806 [95%CI (0.717, 0.894), P<0.001], sensitivity was 80.3%, specificity was 70.4%. The multivariate logistic regression analysis showed that the thyroid nodules with diffuse lesions, calcification, and maximum nodule diameter ≥1 cm were the risk factors for elevated ECI values (P<0.05). For the solid thyroid nodules without diffuse lesions, without calcification, and maximum nodule diameter <1 cm, ECI had the higher sensitivity, specificity, accuracy, and positive predictive value for the differential diagnosis of benign and malignant thyroid nodules (all exceed 80%), but these indexes were lower (under 60%) for the differential diagnosis of solid thyroid nodules with diffuse diseases, with calcification, and maximum nodule diameter ≥1 cm.ConclusionsECI obtained by ultrasound RTE can be used to differentiate solid thyroid nodules from benign ones. The presence or absence of diffuse lesions, calcification, and maximum nodule diameter are the influencing factors for ECI to differentiate solid thyroid nodules. In clinical diagnosis, it should be paid attention to the comprehensive analysis of the above factors.
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.
The early damage detection and evaluation are of great significance in treatment and prognosis to the left ventricular function for children with tumor. In this paper, it is reported that the early damage of the left ventricular function was observed by pulsed wave Doppler (PWD) and tissue Doppler imaging (TDI) in our laboratory. Eighty children half a year to fourteen years old were included in this study. The cardiac function indices in chemotherapy group and control group were measured and compared. The results showed that there was significant difference in mitral and tricuspid annulus flow spectrum between the two groups. Compared with PWD, TDI is more prompt, objective and accurate in detecting early damage of left ventricular function in children with tumor.And TDI is a good method for early identification of ventricular function damage in children with tumor.
Identification of real-time uterine contraction status is very significant to labor analgesia, but the traditional uterine contraction analysis algorithms and systems cannot meet the requirement. According to the situations mentioned above, this paper designs a set of algorithms for the real-time analysis of uterine contraction status. The algorithms include uterine contraction signal preprocessing, uterine contraction baseline extraction based on histogram and linear iteration and an algorithm for the real-time analysis of uterine contraction status based on finite state machines theory. It uses the last uterine status and a series of state transfer conditions to identify the current uterine contraction status, as well as a buffer mechanism to avoid false status transitions. To evaluate the performance of the algorithm, we compare it with an existing uterine contraction analysis algorithm used in the electronic fetal monitor. The experiments show that our algorithm can analyze the uterine contraction status while monitoring the uterine contraction signal in a real-time. Its sensitivity reaches 0.939 9 and its positive predictive value is 0.869 3, suggesting that the algorithm has high accuracy and meets the need of clinical monitoring.
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.
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.