To investigate the effect of MMP-26 on human glioma angiogenesis and the possible mechanism.Methods The MMP-26 plasmid and empty plasmid pcDNA3.1 were stably transfected into U251 cells to establish a nude mice xenograft model,and then an in vitro human tumor tissue-based three-dimensional angiagenic model.Tissue disks were visually assessed over time to determine the percentage of wells that developed an angiogenic response(I％) and the density and length of neovessel growth were graded at intervals using a semiquantitative visual growth-rating scheme (angiogenic index,AI,0-16scale) in groups of MMP-26 transfected U251 cells (U251-MMP-26),pcDNA3.1 vector-transfected U251 cells (U251-pcDNA3.1) and non-transfected U251 cells (U251).RT-PCR and immunohistochemistry were used to detect the expression of mRNA and protein of MMP-26 and VEGF in groups of U251-MMP-26,U251-pcDNA3.1 and U251.Immunohistochemical localization of CD31 was determined in the endothelial tubes invading the fibrin-thrombin clot matrix.Results Immunohistochemical endothelial cell markers CD31 was positive in the vascular tubes invading the fibrin-thrombin clot matrix,confirming their endothelial origin.The angiogenesis results showed that difference of length of micro capillaries,density of branches,and the area occupied between U251-MMP-26 groups and control groups were significant.The percentage of tumor implants that developed invasion (I％) and the angiogenic index AI in U251-MMP-26 group on day 14 were higher than those of U251-pcDNA3.1 group and U251 group (P ＜ 0.05).The trends of I％ and AI in 14 days were significant compared with those in control groups.The expression of mRNA and protein of MMP-26and VEGF in U251-MMP-26 group was significantly higher in U251-MMP-26 group than those in U251-pcDNA3.1 group and U251 group(P ＜0.01).Conclusion The effect of MMP-26 on promoting glioma angiogenesis may be related to the increased expression of VEGF,which can be used as targets for anti-tumor therapy.

OBJECTIVETo summarize the clinical features of those Duchenne and Becker muscular dystrophy (DMD and BMD) patients who are complicated with epilepsy, and try to analyze the genotype- phenotype correlation.

METHODBy a retrospective analysis of 307 patients with DMD and BMD who attended Peking University First Hospital from February 2006 to September 2014,7 patients complicated with epilepsy were identified and their clinical data were collected. The possible mechanism of epilepsy in DMD and BMD patients was proposed after analyzing the genotype-phenotype correlation.

RESULT(1) Among 307 DMD and BMD patients, 7 cases had epilepsy, the prevalence was 2. 28%. (2) The age of onset of epilepsy ranged from 8 months to 11 years. Focal seizure was the most common seizure type (6 cases) , while other seizure types were also involved, such as generalized tonic-clonic seizure. As to epilepsy syndromes, 1 boy was diagnosed as benign childhood epilepsy with centrotemporal spikes (BECT). Six patients were treated with 1 or 2 types of antiepileptic drugs and seizures were controlled well. On follow-up, 6 of the 7 children had normal mental development, while the remaining 1 patient was diagnosed as mild mental retardation. (3) DMD gene mutations of all 7 patients were analyzed. Exons deletions were found in 6 cases while point mutation was found in 1 case.

CONCLUSIONThe prevalence of epilepsy in DMD and BMD patients was higher than the prevalence in normal population. The age of onset of epilepsy varies, and focal seizure may be the most common seizure type. Some patients may also present as some kind of epilepsy syndrome, such as BECT. In most patients, seizures can be controlled well by 1 or 2 types of antiepiletic drugs. No clear correlation was found between genotype and phenotype in DMD and BMD patients who were complicated with epilepsy, probably due to limited number of cases.

Anticonvulsants ; therapeutic use ; Child ; Epilepsy ; complications ; drug therapy ; epidemiology ; Exons ; Genotype ; Humans ; Intellectual Disability ; etiology ; Male ; Muscular Dystrophy, Duchenne ; complications ; genetics ; Mutation ; Phenotype ; Prevalence ; Retrospective Studies ; Seizures ; Sequence Deletion

Objective:To compare the effectiveness of Logistic regression, BP neural network and support vector machine models in the prediction of 30-day risk of readmission in elderly patients with an exacerbation of chronic obstructive pulmonary disease (COPD) and to provide a scientific basis for the screening and prevention of high-risk patients with readmission.Methods:The COPD patient survey questionnaire was made, including the general data questionnaire, modified Medical Research Council dyspnea scale (mMRC), activities of daily living (ADL), the geriatric depression scale, the mini nutritional assessment-short form (MNA-SF) and COPD assessment test (CAT). Elderly COPD patients were selected from the department of respiratory medicine of 13 general hospitals in Ningxia from April 2019 to August 2020 by convenience sampling method, and they were followed up 30 days after discharge. To explore the risk factors of patient readmission, Logistic regression model, BP neural network model and support vector machine models were constructed based on the risk factors. According to the ratio of the training set to the testing set of 7∶3, the model was divided into the training set sample and the testing set sample. The prediction efficiency of the model was compared by the precision rate, recall rate and accuracy rate, F1 index and the area under the receiver operator characteristic curve (AUC).Results:A total of 1 120 patients were investigated, including 879 non-readmission patients and 241 readmission patients. Univariate regression analysis showed that there were statistically significant differences in age, education level, smoking status, proportion of diabetes and coronary heart disease, hospitalization times of acute exacerbation of COPD in the past 1 year, seasonal factors and long-term home oxygen therapy, regular medication, proportion of rehabilitation exercise, course of disease, ADL, depression status, mMRC, nutritional status between non-readmission patients and readmission patients. Binary Logistic regression analysis showed that education level, smoking status, coronary heart disease, hospitalization times of acute exacerbation of COPD in the past 1 year, seasonal factors, whether long-term home oxygen therapy, whether regular medication, nutritional status were the risk factors for 30-day acute exacerbation of readmission in elderly patients with COPD. The training set showed that the accuracy rate of Logistic regression model, BP neural network model and support vector machine models were 70.95%, 76.51% and 84.78%, respectively. The recall rates were 79.55%, 86.36% and 88.64%, respectively. The accuracy rates were 87.81%, 90.81% and 93.82%, respectively. F1 indexes were 0.75, 0.81 and 0.87, respectively. The AUC were 0.850, 0.893 and 0.921, respectively. The testing set showed that the precision rate of Logistic regression model, BP neural network model and support vector machine model were 78.38%, 80.65% and 88.57%, respectively. The recall rates were 70.73%, 60.98% and 75.61%, respectively. The accuracy rates were 85.82%, 84.40% and 90.07%, respectively. F1 indexes were 0.74, 0.69 and 0.82, respectively. The AUC were 0.814, 0.775 and 0.858, respectively.Conclusion:Comparing with Logistic regression and BP neural network, support vector machine model has better prediction effect, and can effectively predict the risk of acute exacerbation of readmission in elderly patients with COPD within 30 days.

Objective To develop an indicator system for the ability of main caregivers of premature in Neonatal Intensive Care Unit (NICU). Methods Delphi method was used to design index system and 16 experts were invited to participate the study. The questionnaire was consulted by emails and we took two rounds of consultation. Results The two rounds of consulting experts enthusiasm coefficients was 100% and the overall authority coefficients was 0.813 and 0.819. In the evaluation index system, there were 8 first grade indexes and 42 second grade indexes, including 11 items of basic care ability , 6 items of feeding and nutrition, 5 items of early itervention, 8 items of common symptoms and sign, 1 item of emergency, 5 items of safety prevention, 4 items of special care and 2 items of parentage. Conclusions The ability of main caregivers of premature in NICU evaluation index system which is designed using Delphi method is scientific and reliable. The results would have important significance to evaluate the level of main caregivers of premature in NICU.

Humans ; Proto-Oncogene Proteins p21(ras)/genetics* ; Prognosis ; Biomarkers, Tumor/genetics* ; Mutation/genetics* ; Colorectal Neoplasms/genetics* ; Proto-Oncogene Proteins B-raf/metabolism*

Objective: To understand the consistency of ALK Ventana-D5F3 immunohistochemistry (IHC) interpretation in Chinese lung adenocarcinoma among histopathologists from different hospitals, and to recommend solution for the problems found during the interpretation of ALK IHC in real world, with the aim of the precise selection of patients who can benefit from ALK targeted therapy. Methods: This was a multicenter and retrospective study. A total of 109 lung adenocarcinoma cases with ALK Ventana-D5F3 IHC staining were collected from 31 lung cancer centers in RATICAL research group from January to June in 2018. All cases were scanned into digital imaging with Ventana iSCANcoreo Digital Slide Scanning System and scored by 31 histopathologists from different centers according to ALK binary (positive or negative) interpretation based on its manufacturer′s protocol. The cases with high inconsistency rate were further analyzed using FISH/RT-PCR/NGS. Results: There were 49 ALK positive cases and 60 ALK negative cases, confirmed by re-evaluation by the specialist panel. Two cases (No. 2302 and No.2701) scored as positive by local hospitals were rescored as negative, and were confirmed to be negative by RT-PCR/FISH/NGS. The false interpretation rate of these two cases was 58.1% (18/31) and 48.4% (15/31), respectively. Six out of 31 (19.4%) pathologists got 100% accuracy. The minimum consistency between every two pathologists was 75.8%.At least one pathologist gave negative judgement (false negative) or positive judgement (false positive) in the 49 positive or 60 negative cases, accounted for 26.5% (13/49), 41.7% (25/60), respectively, with at least one uncertainty interpretation accounted for 31.2% (34/109). Conclusion There are certain heterogeneities and misclassifications in the real world interpretation of ALK-D5F3 IHC test, which need to be guided by the oncoming expert consensus based on the real world data.