Objective To investigate the efficacy and safety of montelukast sodium combined with fluticasone propionate in treatment of children with cough variant asthma.Methods Two hundred and forty children diagnosed as cough variant asthma in our hospital during February 2013 to January 2015 were randomized into three groups.Children in group Mon + Flu were given montelukast sodium combined with inhaled fluticasone propionate,children in group Flu was given inhaled corticosteroids alone and children in group Mon was given montelukast sodium alone.Cough,lung function and adverse reactions were observed after 8 and 12 weeks of treatment and the recurrences of cough symptoms were followed up within 24 weeks.Results After 8 weeks of treatment,the score of cough in group Mon + Flu (1.1 ± 0.7) was lower than those in groups Flu (1.7 ±0.8) and Mon (1.6 ±0.8) (t =4.973,4.353,P ＜0.05),while there was no significant difference between group Flu and group Mon(t =0.560,P ＞ 0.05).Meantime,the percentage of predicted in FEV1 in group Mon+ Flu (93.4 ± 15.8) was significantly higher than those in group Flu (87.4 ± 11.0) and group Mon (86.5 ± 9.8) (t =2.804,3.315,P ＜ 0.05).The percentage of predicted in PEF in group Mon + Flu(89.8 ± 15.4)was significantly higher than those in group Flu(84.9 ± 13.4)and group Mon(85.1 ± 12.3) (t =2.126,2.124,P ＜ 0.05),and there was no significant difference between latter two groups (t =0.525,0.082,P ＞ 0.05).After 12 weeks of treatment,there was no significant difference in scores of cough and percentage of predicted in FEV1 and PEF among three groups (P ＞ 0.05).There was no significant difference in incidence of adverse reactions among three groups (x2 =1.026,P ＞ 0.05).The recurrence rate of group Mon + Flu (3.85％) and group Flu(5.26％) were significantly lower than that of group Mon (17.33％) (x2 =7.428,5.505,P ＜ 0.05),while there was no difference between groups Mon + Flu and Flu (P ＞ 0.05).Conclusions For children with cough variant asthma montelukast sodium combined with fluticasone propionate has better efficacy than monotherapy in 8 weeks of treatment,but there was no difference in 12 weeks of treatment.The recurrence rate in group Mon + Flu and group Flu is lower than that in group Mon.

Objective To discuss the growth suppressing, apoptosing effect of new type tumor-supressor gene-p33ING1 in stomach cancer cell strain, and to explore new strategies and methods in tumor therapy. Methods The PCDNA3/p33ING1 nuclear expressing microsome was constructed, p33ING1 and wt-p53 were implanted to human stomach cancer cell both and to evaluate the effect of p33ING1 and p53 toward stomach cancer cell and synergism between them. Results The PCDNA3/p33ING1 nuclear expressing microsome was successfully constructed. The human stomach cancer cell strain SSCG-7901 under implantation of p33ING1 and wt-p53 showed a significant decrease in cell growth, the coupling time was delayed, DNA synthetic phase was shortened and G0/G1 phase prolonged. The cell collapse increased. Conclusions Despite of the tumor-inhibiting effect and biochemical activation of p33ING1, it also plays a role with p53 gene in controling growth of stomach cancer cell, inducing cell collapse and hampering cell proliferation cycle. P33ING1 and p53 are synergistic to each other.

Objective:To understand the current status and existing problems of medical students' cognition of new medical ethics view, and to provide reference for the innovation of medical ethics education mode. Methods:A self-designed questionnaire was used to investigate the medical students in a university in Changsha. A total of 450 questionnaires were distributed and 440 questionnaires were collected. Results:Medical students generally had a better understanding of the new medical ethics view and could establish a"patient centered" service concept. But the medical ethics cognition of some medical students was not consistent with the medical ethics behavior, and the medical value orientation was not clear. Conclusion:In order to improve the medical ethics cognition level of medical students, it needs to establish a new medical ethics education mode with the integration of school, society and family, make medical ethics education integrate with clinical practice effectively, strengthen medical students' legal education meanwhile, and effectively carry out the new medical ethics view for medical students.

OBJECTIVETo clone and express VP1-VP4 genes encoding the structural proteins of Coxsackie virus A16 and analyze the antigenicity of the expressed recombinant proteins.

METHODSThe VP1-VP4 cDNAs were amplified with RT-PCR from the extracted viral RNA and cloned into pMD19-T vectors. The VP1-VP4 genes were inserted to the multi-cloning sites of the plasmid pQE30a, and the protein expressions in E. coli M15 were induced by IPTG. After purification by washing with 8 mol/L urea under denaturing condition, the recombinant proteins were identified by Western blotting and ELISA for their immunogenicity against rabbit antisera of Coxsackie virus A16 and enterovirus 71, respectively.

RESULTSThe recombinant VP1-VP4 proteins were highly expressed in E. coli M15. The purified proteins could be recognized by rabbit antiserum of Coxsackie virus A16 and showed cross reactivity with the rabbit antiserum of Enterovirus 71.

CONCLUSIONThe recombinant Coxsackie virus A16 VP1-VP4 proteins obtained possess good antigenicity.

Antigens, Viral ; genetics ; immunology ; Capsid Proteins ; classification ; genetics ; immunology ; Cloning, Molecular ; Enterovirus A, Human ; genetics ; Gene Expression ; Genetic Vectors ; Plasmids ; Recombinant Proteins ; genetics ; immunology ; Reverse Transcriptase Polymerase Chain Reaction

BACKGROUND:Sarcopenia refers to age-related progressive,systemic muscle mass reduction and/or muscle strength decline or muscle physiological function decline,which is related to the occurrence of a variety of adverse outcomes in older adults.Exercise is considered to be one of the main strategies for combating sarcopenia in older adults,but there is a lack of specific intervention methods of different exercise patterns to intervene in sarcopenia. OBJECTIVE:To elaborate the main influencing factors of sarcopenia and the research progress of different exercise methods to improve sarcopenia in older adults,providing reference and basis for combating sarcopenia in older adults. METHODS:Web of Science,PubMed,CNKI,VIP,WanFang databases were retrieved for relevant literature published from January 2000 to October 2023 using the keywords of"sarcopenia,sport,exercise intervention,resistant training,aerobic exercise,whole body vibration training,mixed training,physical performance,muscle strength,muscle mass"in Chinese and English,respectively.A total of 126 articles were included for review. RESULTS AND CONCLUSION:Resistance exercise is still the most effective way to prevent and treat senile sarcopenia,and the effect of high-intensity resistance exercise is more significant.However,in practical application,we should pay attention to the gradual increase of training load intensity.Aerobic exercise combined with resistance exercise is more effective to improve muscle mass and function in the elderly than a single exercise mode.It is suggested that older adults can carry out the transition of low-intensity aerobic exercise in the early stage and increase resistance exercise individually in the late stage.Whole body vibration training is a new treatment method for the prevention and treatment of senile sarcopenia,but particular attention should be paid to the effects of frequency,amplitude,and duration on patients during practical application.Multicomponent exercise combines different exercise modes,which can give full play to their respective advantages,so as to personalize exercise interventions.

Objective To investigate the diagnostic value of Xpert MTB/RIF combined with metagenic high-throughput sequencing in bacterial negative tuberculosis.Methods Retrospective analysis of 70 patients diagnosed with bacterial negative pulmonary tuberculosis from December 2019 to May 2022 enrolled in the study.Xpert MTB/RIF testing,high-throughput metagenomic sequencing,and a combination of the two were performed,respectively.Solid culture and proportional methods were used to diagnose biochemical pathogens and analyze diagnostic efficacy.The receiver operating characteristic curve was drawn with the predicted value.Results The positive rate of Xpert MTB/RIF diagnosis was 75.57%,and the negative rate was 21.43%.The positive rate of high-throughput sequencing for metagenomics was 78.57%,while the negative rate was 21.43%;The positive rate of combined diagnosis was 88.57%,and the negative rate was 11.43%.The detection sensitivity of Xpert MTB/RIF was 77.55%,the specificity was 59.86%,and the area under the curve(AUC)was 0.827.The sensitivity of high-throughput sequencing for metagenomes was 77.47%,the specificity was 61.02%,and the AUC was 0.808.The sensitivity of the combined detection was 89.75%,the specificity was 89.57%,and the AUC was 0.925.The results showed that the diagnostic sensitivity and specificity of Xpert MTB/RIF combined with high-throughput metagenomic sequencing in bacterial negative pulmonary tuberculosis were higher than those of single detection(P<0.05).Conclusion Xpert MTB/RIF combined with metagenic high-throughput sequencing has good application value in the diagnosis of bacterial negative pulmonary tuberculosis,and is worthy of clinical application.

Objective:To study the effect of video teaching combined with offline training in cardiopulmonary resuscitation training for new nurses outside hospital.Methods:From August 2017 to August 2018, 125 new nurses from Shanghai Changzheng Hospital were selected. New nurses in August 2017 were set as control group ( n=65). In August 2018, the new nurses were set as the observation group ( n=60). The control group used the traditional offline training mode to train cardiopulmonary resuscitation outside the hospital. The observation group used information platform video teaching combined with offline theoretical training to carry out cardiopulmonary resuscitation training. After systematic training, the results of cardiopulmonary resuscitation after training and the satisfaction of teaching were compared between the two groups. Results:Before training, there was no significant difference in the assessment results of cardiopulmonary resuscitation theory and operation between the two groups ( t values were 0.12, 1.23, P>0.05). After training the scores of cardiopulmonary resuscitation theory and operation examination in the observation group were 85.41±3.20, 92.40±2.50, and 82.52±4.50, 85.0±3.60 in the control group ( t value was 1.04,4.24, all P<0.05). Encouraging and enhancing the learning interest of new nurses, cultivating mutual supervision and mutual guidance, integrating theoretical knowledge with practical operation, improving and adjusting self-motivation, overall evaluation of teaching methods and total score in the observation group were 3.61±0.34, 3.54±0.20, 3.61±0.28, 3.87±0.20, 3.32±0.21, 17.95±0.26, and 2.60±0.41, 2.41±0.16, 2.55±0.35, 2.41±0.46, 2.58±0.20,12.55±0.32 in the control group ( t value was 2.187-2.452, P<0.05). Conclusion:Video teaching combined with offline training can improve the performance of new nurses in the training of high-quality cardiopulmonary resuscitation, stimulate the learning interest of nurses, and enhance the effect of high-quality cardiopulmonary resuscitation training.

Objective:To observe the effects of interleukin-17A (IL-17A) and interferon-γ (IFN-γ) on CD34 - orbital fibroblasts (OFs) in patients with Graves ophthalmopathy (GO), and to explore the pathogenesis of GO. Methods:Orbital adipose connective tissue and lacrimal gland tissue of 5 patients with GO were collected during orbital decompression surgery.These tissue was cultured by tissue explant culture method.CD34 - OFs were enriched by immunomagnetic beads after passage and expansion.The cultured cells were divided into transforming growth factor-β (TGF-β) group, TGF-β+ 10 ng/ml IL-17A group, TGF-β+ 100 ng/ml IL-17A group, TGF-β+ 1 ng/ml IFN-γ group and TGF-β+ 5 ng/ml IFN-γ group.The fibrosis of the cells was induced with 5 ng/ml TGF-β and then was treated with different concentrations of IL-17A or IFN-γ according to grouping.The expression of fibronectin, collagen type Ⅰ, α-smooth muscle actin (α-SMA) and tissue metalloproteinase inhibitor-1 (TIMP-1) in CD34 - OFs derived from both orbital adipose connective tissue and lacrimal gland tissue were detected by Western blot.This study protocol was approved by an Ethic Committee of Shanghai Ninth People's Hospital (SH9H-2020-TK195-1) and written informed consent was obtained from each patient. Results:For CD34 - OFs derived from orbital adipose connective tissue, the relative expressions of fibronectin, type Ⅰ collagen, α-SMA and TIMP-1 protein were significantly higher in the TGF-β+ 100 ng/ml IL-17A group than those in the TGF-β group and TGF-β+ 10 ng/ml IL-17A group (all at P<0.05); the relative expressions of fibronectin, type Ⅰ collagen and α-SMA in the cells in the TGF-β+ 5 ng/ml IFN-γ group were significantly lower than those in the TGF-β group and the TGF-β+ 1 ng/ml IFN-γ group (all at P<0.05). For CD34 - OFs derived from lacrimal gland, the relative expressions of fibronectin, type Ⅰ collagen, α-SMA and TIMP-1 protein in the TGF-β+ 100 ng/ml IL-17A group were significantly higher than those in the TGF-β group and the TGF-β+ 10 ng/ml IL-17A group (all at P<0.05); the relative expressions of fibronectin, type Ⅰ collagen and TIMP-1 protein in the TGF-β+ 1 ng/ml IFN-γ group were significantly higher than those in the TGF-β group and TGF-β+ 5 ng/ml IFN-γ group, and the relative expression of α-SMA protein was significantly higher than that in the TGF-β+ 5 ng/ml IFN-γ group (all at P<0.05). Conclusions:High level of IL-17A can promote the fibrosis of TGF-β-induced CD34 - OFs, and high level of IFN-γ inhibits the fibrosis of TGF-β-induced CD34 - OFs.

Objective:This study aims to compare the application value of Autoregressive Integrated Moving Average model (ARIMA ) and deep learning model inprediction and analysis of liposuction operation data.Methods:The patients who met inclusion criteria and underwent liposuction surgery in the Plastic Surgery Hospital of Chinese Academy of Medical Sciences from January 2019 to September 2019 were enrolled in this study. For each patient, 250~400 s operation data including kinematics and mechanical data were collected by a senior plastic surgeon, usingthe liposuction operation recording system which consists of optical tracking and force sensing equipment. After pretreatment, the collected data were divided into one liposuction reciprocating cycle as one set of data. ARIMA model and deep learning model were used to analyze the collected datafor establishing prediction models of liposuction operation. Using Matlab2017, 30 couplesofliposuction data setwereextractedby simple random sampling, andthe DTW valueofeachcoupleofdatasetswascalculated as test standard. Then, the DTW values between 30 sets of predicted data and actual data based on the ARIMA model and the deep learning model were calculated respectively and compared with the test standard to verify the prediction result of the two models. Matlab2017 was used for statistical analysis. Independent sample t-test was used to compare the two groups, and P<0. 05 indicates that the difference is statistically significant.Results:18 patients were enrolled. All patients were females at 23-49 years old, with the mean age of 36. 6 years old. Liposuction was performed in the abdomen, thighs, and waist. A total of 16 800 sets of liposuction cycle data were obtained. The mean DTW value of test standard was 0. 048±0. 028. The meanDTW value between the ARIMA model predicted data and the actual data was 0. 660±0. 577, which was statistically significant compared with the test standard ( P< 0. 05) . The meanDTW value between the deep learning model predicted data and the actual data was 0. 052±0. 030, which was no significant difference compared with the test standard ( P> 0. 05 ). Conclusions:Compared with ARIMA model, deep learning model can predict liposuction operation data more accurately, and has better adaptability and real-time performance.

Objective:This study aims to compare the applicability value of autoregressive integrated moving average model(ARIMA) and deep learning model inprediction and analysis of liposuction operation data.Methods:The patients who met inclusion criteria and underwent liposuction surgery in the Plastic Surgery Hospital of Chinese Academy of Medical Sciences from January 2019 to September 2019 were enrolled in this study. For each patient, 250-400 s operation data including kinematics and mechanical data were collected by a senior plastic surgeon, using the liposuction operation recording system which consists of optical tracking and force sensing equipment. After pretreatment, the collected data were divided into one liposuction reciprocating cycle as one set of data. ARIMA model and deep learning model were used to analyze the collected data for establishing prediction models of liposuction operation. Using Matlab 2017, 30 couples of liposuction data set were extracted by simple random sampling, and the dynamic time warping (DTW) value of each couple of data sets was calculated as test standard. Then, the DTW values between 30 sets of predicted data and actual data based on the ARIMA model and the deep learning model were calculated respectively and compared with the test standard to verify the prediction results of the two models. Matlab 2017 was used for statistical analysis. Independent sample t-test was used to compare the two groups, and P<0.05 indicated statistically significant difference. Results:Eighteen patients were enrolled. All patients were females at 23-49 years old, with the mean age of 36.6 years old. Liposuction was performed in the abdomen, thighs, and waist. A total of 16 800 sets of liposuction cycle data were obtained. The mean DTW value of test standard was 0.048±0.028. The mean DTW value between the ARIMA model predicted data and the actual data was 0.660±0.577, which was statistically significant compared with the test standard ( P<0.05). The mean DTW value between the deep learning model predicted data and the actual data was 0.052±0.030, which was not significantly different compared to the test standard ( P>0.05). Conclusions:Compared with ARIMA model, deep learning model can predict liposuction operation data more accurately, and has better adaptability and real-time performance.