随着人口的老龄化，越来越多的有症状或无症状的冠心病患者需接受非心脏外科手术。接受非心脏外科手术而死亡的患者大约有50%是由于心脏并发症所致［1］。围手术期发生的心脏并发症大约5%～10%为心肌梗死，主要发生于术后头3天，其病死率很高，可达32%～69%［2，3］。术后发生心肌梗死或不稳定型心绞痛的患者发生心血管问题的几率增加20倍［4］。因此，如何评估非心脏外科手术患者的心脏危险性，如何预防围手术期心脏并发症的发生，已成为外科医生十分关注的一个问题。
OBJECTIVE: To investigate the selection and identification of human keratinocyte stem cells(KSC) in vitro. METHODS: According to the characteristics of KSC which can adhere to extracellular matrix very fast, we selected 3 groups of different time(5 minutes, 20 minutes and 60 minutes) and unselected as control group. And the cells were identified by monoclone antibody of beta 1-integrin and cytokeratin 19 (Ck19), then the image analysis was done. Furthermore we analyzed the cultured cells with flow cytometer(FCM) and observed the ultrastructure of the cell by transmission electron microscope(TEM). RESULTS: The cell clones formed in all groups after 10 to 14 days, while the cells of 5 minute group grew more slowly than those of the other groups, however, the clones of this group were bigger. The expression of beta 1-integrin and Ck19 were found in all groups. The positive rate of beta 1-integrin was significant difference between 5 minute group and the other groups (P lt; 0.05). And the expression of Ck19 was no significant difference between 5 minute group and 20 minute group(P gt; 0.05), and between 60 minute group and control group. But significant difference was observed between the former and the later groups(P lt; 0.05). The result of FCM showed that most cells of the 5 minute group lied in G1 period of cell cycle, which was different from those of the other groups. At the same time, the cells of 5 minute group were smaller and contained fewer organelles than those of the other groups. CONCLUSION: The above results demonstrate that the cells of 5 minute group have a slow cell cycle, characteristics of immaturity, and behaving like clonogenic cells in vitro. The cells have the general anticipated properties for KSC. So the KSC can be selected by rapid attachment to extracellular matrix and identified by monoclone antibody of beta 1-integrin and Ck19.
ObjectiveTo evaluate the reporting quality of systematic reviews (SRs)/meta-analyses on acupuncture focusing on literature screening results and explore the influencing factors of the complete reporting.MethodsPubMed, EMbase, CNKI, WanFang Data, and VIP databases were searched to collect SRs/meta-analyses on acupuncture from inception to December 31st, 2019. Two reviewers independently screened literature, extracted data and evaluated the reporting quality of literature screening results of SRs/meta-analyses on acupuncture based on PRISMA statement. Logistic regression model analysis was applied to explore the influencing factors of the complete reporting rate of literature screening results. Statistical analysis was performed by using Excel 2016 and SPSS 16.0 software.ResultsA total of 1 227 SRs/meta-analyses were included. Only 62.3% SRs fully reported the four parts of literature screening results. The parts with a low reporting rate included the number of studies assessed for eligibility (73.2%) and the reasons for exclusions at each stage (67.0%). And the reporting rate of the literature screening flowchart was also low (63.6%). The reporting rate of literature screening results in Chinese SRs was lower than that in English SRs, and there was significantly statistical difference (P<0.001). Multivariate logistic regression analysis showed that the type of published journal, publication year, pages of article and the number of searched databases were correlated with the complete reporting rate of literature screening results (P<0.001).ConclusionsThe complete reporting rate of the literature screening results of SRs on acupuncture is low, especially in Chinese SRs. The complete reporting rate of literature screening results is significantly higher for SRs published after PRISMA statement, in SCI journals, with longer length and more searched databases.
Place cell with location tuning characteristics play an important role in brain spatial cognition and navigation, but there is relatively little research on place cell screening and its influencing factors. Taking pigeons as model animals, the screening process of pigeon place cell was given by using the spike signal in pigeon hippocampus under free activity. The effects of grid number and filter kernel size on the place field of place cells during the screening process were analyzed. The results from the real and simulation data showed that the proposed place cell screening method presented in this study could effectively screen out place cell, and the research found that the size of place field was basically inversely proportional to the number of grids divided, and was basically proportional to the size of Gaussian filter kernel in the overall trend. This result will not only help to determine the appropriate parameters in the place cell screening process, but also promote the research on the neural mechanism of spatial cognition and navigation of birds such as pigeons.
As the largest ecosystem of human body, intestinal microorganisms participate in the synthesis and metabolism of uric acid. Developing and utilizing intestinal bacteria to degrade uric acid might provide new ideas for the treatment of hyperuricemia. The fecal samples of people with low uric acid were inoculated into uric acid selective medium with the concentration of 1.5 mmol/L for preliminary screening, and the initially screened strains that may have degradation ability were domesticated by concentration gradient method, and the strains with high uric acid degradation rate were identified by 16S rRNA sequencing method. A strain of high-efficiency uric acid degrading bacteria was screened and domesticated from the feces of people with low uric acid. The degradation rate of uric acid could reach 50.2%. It was identified as Escherichia coli. The isolation and domestication of high efficient uric acid degrading strains can not only provide scientific basis for the study of the mechanism of intestinal microbial degradation of uric acid, but also reserve biological strains for the treatment of hyperuricemia and gout in the future.
Abstract： Pulmonary metastasectomy is an option for patients with metastatic tumor of lung. Numerous retrospectivestudies have demonstrated that complete control of primary tumor and complete resection of metastases limited to thelungs may be associated with prolonged survival. Speci?c issues require consideration when planning pulmonary metastasectomy. Regardless of histological type of primary tumor, complete resection is the most important prognostic factor. The other two important prognostic factors are long disease interval and limited number of metastatic tumor of lung. Hand-assisted thoracoscopic surgery for bilateral lung metastasectomy through sternocostal triangle access is recommended. Pulmonary hilar and mediastinal lymph node metastases are some relative contraindications for this surgery. Nowdays preoperative imaging examinations still have limitations in detecting all the lung metastases. Some data emphasize the importance of considering patients for extended resection in metastatic tumor of lung. Repeat resection after previous metastasectomies can be of benefit under certain circumstances so we should remove as little healthy lung tissue as possible. In this review, we discuss about some disputed issues in order to establish a useful criterion for consideration of pulmonary metastasectomy.
In order to solve the current problems in medical equipment maintenance, this study proposed an intelligent fault diagnosis method for medical equipment based on long short term memory network(LSTM). Firstly, in the case of no circuit drawings and unknown circuit board signal direction, the symptom phenomenon and port electrical signal of 7 different fault categories were collected, and the feature coding, normalization, fusion and screening were preprocessed. Then, the intelligent fault diagnosis model was built based on LSTM, and the fused and screened multi-modal features were used to carry out the fault diagnosis classification and identification experiment. The results were compared with those using port electrical signal, symptom phenomenon and the fusion of the two types. In addition, the fault diagnosis algorithm was compared with BP neural network (BPNN), recurrent neural network (RNN) and convolution neural network (CNN). The results show that based on the fused and screened multi-modal features, the average classification accuracy of LSTM algorithm model reaches 0.970 9, which is higher than that of using port electrical signal alone, symptom phenomenon alone or the fusion of the two types. It also has higher accuracy than BPNN, RNN and CNN, which provides a relatively feasible new idea for intelligent fault diagnosis of similar equipment.
ObjectivesTo explore the effect of the deep learning algorithm convolutional neural network (CNN) in screening of randomized controlled trials (RCTs) in Chinese medical literatures.MethodsLiterature with the topic " oral science” published in 2014 were retrieved from CNKI and exported citations containing title and abstract. RCTs screening was conducted by double independent screening, checking and peer discussion. The final results of the citations were used for CNN algorithm model training. After completing the algorithm model training, a prospective comparative trial was organized by searching all literature with the topic "oral science" published in CNKI from January to March 2018 to compare the sensitivity (SEN) and specificity (SPE) of algorithm with manual screening. The initial results of a single screener represented the performance of manual screening, and the final results after peer discussion were used as the gold standard. The best thresholds of algorithm were determined with the receptor operative characteristic (ROC) curve.ResultsA total of 1 246 RCTs and 4 754 non-RCTs were eventually included for training and testing of CNN algorithm model. 249 RCTs and 949 non-RCTs were included in the prospective trial. The SEN and SPE of manual screening were 98.01% and 98.82%. For the algorithm model, the SEN of RCTs screening decreased with the increase of threshold value while the SPE increased with the increase of threshold value. After 27 changes of threshold value, ROC curve were obtained. The area under the ROC curve was 0.9977, unveiling the optimal accuracy threshold (Threshold=0.4, SEN=98.39%, SPE=98.84%) and high sensitivity threshold (Threshold=0.06, SEN=99.60%, SPE=94.10%).ConclusionsA CNN algorithm model is trained with Chinese RCTs classification database established in this study and shows an excellent classification performance in screening RCTs of Chinese medical literature, which is proved to be comparable to the manual screening performance in the prospective controlled trial.
Hypertension is the primary disease that endangers human health. A convenient and accurate blood pressure measurement method can help to prevent the hypertension. This paper proposed a continuous blood pressure measurement method based on facial video signal. Firstly, color distortion filtering and independent component analysis were used to extract the video pulse wave of the region of interest in the facial video signal, and the multi-dimensional feature extraction of the pulse wave was preformed based on the time-frequency domain and physiological principles; Secondly, an integrated feature selection method was designed to extract the universal optimal feature subset; After that, we compared the single person blood pressure measurement models established by Elman neural network based on particle swarm optimization, support vector machine (SVM) and deep belief network; Finally, we used SVM algorithm to build a general blood pressure prediction model, which was compared and evaluated with the real blood pressure value. The experimental results showed that the blood pressure measurement results based on facial video were in good agreement with the standard blood pressure values. Comparing the estimated blood pressure from the video with standard blood pressure value, the mean absolute error (MAE) of systolic blood pressure was 4.9 mm Hg with a standard deviation (STD) of 5.9 mm Hg, and the MAE of diastolic blood pressure was 4.6 mm Hg with a STD of 5.0 mm Hg, which met the AAMI standards. The non-contact blood pressure measurement method based on video stream proposed in this paper can be used for blood pressure measurement.