Objective As the intracranial aneurysm diagnosed by digital subtraction angiography (DSA) examination,the patient's cerebral vessels models of intracranial aneurysms were built by 3D Printer.According to the models,the size,shape,orientation of the aneurysms,as well as the relationship between the parent artery and the branch vessels were analyzed to provide reference for craniotomy.Methods The 11 patients with intracranial aneurysms diagnosed by DSA were prospectively selected in this study from May 1,2016 to June 30,2016.The DSA data of the patients were output in DICOM format,after format conversion and three-dimensional reconstruction by MIMICS software,the selected target regions were modeled by 3D printers in different proportions (1∶1 and 1∶3).Results The cerebral vascular 3D printing models could reflect the shape,size and distribution of the cerebral vascular and orientation of the intracranial aneurysms.It could also show the relationship between the aneurysm and parent arteries along with vascular branches.It was showed that the original size and different amplified model could provide reference for the aneurysm clipping surgery.Conclusion The 3D printing technology can be used into the production of human cerebral vascular models,which can provide a physical model for diagnosis and treatment of intracranial aneurysms,and it can also provide useful reference for preoperative and intraoperative aneurysm clip selection and clamping method decision during the aneurysm clip surgery.

Objective: To summarize the clinical effects of Shuxuening Injection on diseases and evaluate the quality of evidence to provide reference for the clinical application of Shuxuening Injection. Methods: Journal articles and conference papers were retrieved from the databases CNKI, Wanfang, VIP, CBM, EMbase, Pubmed and Cochrane with thematic word"Shuxuening"in Chinese and English, then all forms of clinical studies were screened and the disease types and frequency were analyzed, the dominant disease types of Shuxuening Injection were identified. Futhermore, RCT was extracted, and the literature quality was graded using the cochrane manual recommendation method, and its effectiveness and safety were evaluated. Results: All clinical research results show that Shuxuening Injection to treat disease with as many as 74 kinds of varieties, mainly circulation system disease and neural system disease, followed by endocrine disease, respiratory disease, scattered remaining research in ten other system diseases. These researches appeared with the highest frequency of the three diseases were cerebral infarction and its aftermath, angina pectoris and coronary heart disease, diabetes mellitus and its complication. A total of 337 RCT articles were included, all of which were of poor quality. In general, the efficiency of Shuxuening Injection treatment group was significantly higher than that of the control group, with a total efficiency of 84.48％. There were 21.96％ references to adverse reactions, but all of them were minor adverse reactions, such as pruritus, which generally got better by itself or after treatment. Conclusion:Shuxuening Injection has a wide range of clinical application and remarkable effect, especially for the ischemic diseases of cardiovascular and cerebrovascular diseases with good efficacy, less adverse reactions and safety. However, the quality of evidence is generally poor, which needs further study.

Objective:To investigate the influencing factors of operation time for laparos-copic sleeve gastrectomy (LSG) and analyze the learning curve of LSG in sarcopenic obesity (SO) and non-sarcopenic obesity (NSO).Methods:The retrospective cohort study was conducted. The clinical data of 240 obesity patients who underwent LSG in the Fujian Medical University Union Hospital from January 2018 to June 2022 were collected. There were 52 males and 188 females, aged (30±8)years. Patients underwent L3 vertebral body horizontal axial computer tomography (CT) scanning before and after receiving LSG to accurately segment muscles and fats. Observation indicators: (1) treatment and follow-up; (2) influencing factors of operation time for LSG; (3) cumulative sum (CUSUM) of learning curve; (4) comparison of clinical data between patients in the initial and profi-cient stages. Measurement data with normal distribution were represent as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M(IQR), and comparison between groups was conducted using the non-parameter test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The CUSUM of learning curve was calculated and the fitting process was conducted on scatter plot of learning curves. Results:(1) Treatment and follow-up. Of the 240 patients, there were 97 cases of SO and 143 cases of NSO. All 240 patients underwent LSG successfully, without conversion to open surgery. The operation time of 240 patients was (108±23)minutes. None of patient died during the perioperative period and all patients underwent follow-up during the postoperative 6 months. (2) Influencing factors of operation time for LSG. Results of multivariate analysis showed that SO was an independent factor influencing operation time for LSG ( odds ratio=2.207, 95% confidence interval as 1.207-4.038, P<0.05). (3) CUSUM of learning curve. Results of CUSUM of operation time in patients of SO and NSO showed that the best fit equation of patients of SO was y=-4E-08x 6+1E-05x 5-0.001 1x 4+0.063 1x 3-1.89x 2+28.126x-48.671 (x means the number of surgical cases), with goodness-of-fit R 2 as 0.833, and the best fit equation of patients of NSO was y=3E-09x 6-1E-06x 5+0.000 2x 4-0.010 9x 3+0.063 8x 2+12.053x-65.025 (x means the number of surgical cases), with goodness-of-fit R 2 as 0.716. Based on the trend of CUSUM of learning curve of operation time, the peak value of number of surgical cases in patients of SO and NSO was 81 and 36, respec-tively, which was used to divide the learning curve as two stages of the initial stage and the proficient stage. (4) Comparison of clinical data between patients in the initial and proficient stages. ① Of the 97 patients of SO, there were 81 cases and 16 cases in the initial stage and the proficient stage of LSG, with the operation time, postoperative duration of hospital stay as (119±23)minutes, (5.9±2.3)days and (106±21)minutes, (4.7±0.5)days, showing significant differences between them ( t=2.074, 2.147, P<0.05). ②Of the 143 patients of NSO, there were 36 cases and 107 cases in the initial stage and the proficient stage of LSG, with gender (female), height, preoperative body mass, defatted body mass, operation time, postoperative duration of hospital stay, body mass at postoperative 6 month, body mass index (BMI) at postoperative 6 month, percentage of excess weight loss (EWL%) at postoperative 6 month, cases with EWL% >100% at postoperative 6 month, excess BMI at post-operative 6 month as 20, (170±10)cm, (110±25)kg, (57±12)kg, (108±22)minutes, (6.1±1.6)days, (80±16)kg, (27.63±4.22)kg/m2, 83%±35%, 9, 1.99(6.03)kg/m2 and 87, (164±8)cm, (99±20)kg, (52±12)kg, (100±19)minutes, (4.7±1.1)days, (71±16)kg, (25.89±4.48)kg/m2, 103%±42%, 48, 0.31(5.82)kg/m2, showing significant differences between them ( χ2=9.484, t=3.266, 2.424, 2.141, 2.137, 5.821, 2.740, 1.993, -2.524, χ2=4.432, Z=-2.300, P<0.05). Conclusions:SO is an independent factor influencing operation time for LSG. It is suggested that the surgeons need to finish 81 cases and 36 cases master LSG in patients of SO and NSO.

Objective:To investigate the mechanism of action and prognostic value of Dynamin 3 (DNM3) in gastric cancer.Methods:The bioinformatic analysis, experimental study and retrospective cohort study was conducted. The clinicopathological data, fresh gastric cancer tissues, paired normal tissues and the corresponding paraffin sections of 153 gastric cancer patients who underwent radical gastrectomy in Fujian Medical University Union Hospital from January 2013 to July 2018 were collected. Tissues and the corresponding paraffin sections were subjected to quanti-tative real-time polymerase chain reaction, immunoblotting assay, flow cytometric cell cycle assay and immunohistochemical staining, respectively, and clinicopathological data were used for prognostic analysis. The stomach adenocarcinoma (STAD) dataset from the Cancer Genome Atlas (TCGA) database was collected for bioinformatic analysis. Observation indicators: (1) DNM3 gene expression in TCGA-STAD in gastric cancer; (2) mutations and copy number alterations of DNM3 in gastric cancer; (3) methylation level of promoter of DNM3 in gastric cancer; (4) relative protein expression of DNM3 and p53 in gastric cancer; (5) DNM3 correlation and enrichment analysis; (6) ratio of G0/G1 phase, S phase and G2/M phase of cell cycle progression; (7) correlation between immune cell infiltration and DNM3 in gastric cancer; (8) correlation between results of immunohistochemical (IHC) staining and clinical features; (9) analysis of independent factors influencing 5-year overall survival rate of gastric cancer patients. Measurement data with normal distribution were represented as Mean±SD, and comparison among multiple groups was conducted using the ANOVA and further comparison between two groups was conducted using the LSD. Comparison between two groups was conducted using the t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers or percentages, and compari-son between groups was conducted using the chi-square test or Fisher exact probability. Comparison of ordinal data was conducted using the rank sum test. The Pearson correlation coefficient or Spearman correlation coefficient was used to test the correlation between groups. Univariate and multivariate analyses were conducted using the COX proportional risk regression model. The Kaplan-Meier method was used to draw survival curves and calculate survival rates, and the Log-Rank test was used for survival analysis. The Benjamini-Hochberg false discovery rate correction was used for adjusting of the P-value. Results:(1) DNM3 gene expression in TCGA-STAD. The expression levels of DNM3 gene in the 27 tumor tissues and paired normal tissues of the TCGA-STAD database were 0.775(0.605,1.161) and 1.216(0.772,1.681), showing a significant difference between them ( Z=?2.64, P<0.05). The messenger RNA (mRNA) expression levels of DNM3 gene in 48 pairs of gastric cancer tissues and paired normal tissues of the author′s center were 4.370(2.870,6.040) and 2.520(0.850,4.170), showing a significant difference between them ( Z=?4.39, P<0.05). (2) Mutations and copy number alterations of DNM3 in gastric cancer. There were 16 gastric cancer patients in the TCGA-STAD database with DNM3 mutation or somatic copy number alterations, including 6 cases with missense mutations, 1 case with truncated mutation, 8 cases with copy number gain and 1 case with copy number loss. The mRNA expression levels of DNM3 gene before and after mutation in the 370 gastric cancer patients of the TCGA-STAD database were 6.13(5.40,7.08) and 5.02(3.98,5.46), showing a significant difference between them (Log 2FC=?1.11, Z=?2.59, P<0.05). (3) Methylation level of promoter of DNM3 in gastric cancer. There were 372 gastric cancer patients in the TCGA-STAD database undergoing DNM3 methylation and mRNA examinations, and the results showed that levels of methylation and mRNA expression of DNM3 was 0.198 (-0.458, 0.301) and 6.014 (5.141, 6.628), respectively. The levels of methylation in DNM3 was negatively correlated with its mRNA expression ( r=?0.38, P<0.05). Results of follow-up in 32 patients showed that the 3-year overall survival rate of 16 cases with high levels of methylation in DNM3 and 16 cases with low levels of methylation in DNM3 was 18.8% and 41.3%, respectively, showing a significant difference between them ( hazard ratio=1.40, P<0.05). Results of immunoblot-ting assay showed that the relative expression level of DNM3 protein in the AGS cells treated with 0, 0.5, and 1.0 μmol/L of 5-azacytidin was 0.270±0.020, 0.357±0.051 and 0.599±0.039, respectively, showing a significant difference among the three groups ( F=57.84, P<0.05). The relative expression level of DNM3 protein in the HGC-27 cells treated with 0, 0.5, and 1.0 μmol/L of 5-azacytidin was 0.316±0.038, 0.770±0.031 and 0.877±0.052, respectively, showing a significant difference among the three groups ( F=156.30, P<0.05). (4) Relative protein expression of DNM3 and p53 in gastric cancer. Results of immunoblotting assay showed that the relative expression of DNM3 and p53 protein was 0.688±0.047 and 0.872±0.041 in the AGS cells transfected with pCMV-DNM3 plasmid, versus 0.249±0.029 and 0.352±0.020 in the AGS cells transfected with control plasmid, showing significant differences in the above indicators between the two types of cells ( t=13.77,19.74, P<0.05). The relative expression of DNM3 and p53 protein was 0.969±0.069 and 1.464±0.081 in the HGC-27 cells transfected with pCMV-DNM3 plasmid, versus 0.456±0.048 and 0.794±0.052 in the HGC-27 cells transfected with control plasmid, showing significant differences in the above indicators between the two types of cells ( t=10.57, 12.06, P<0.05). (5) DNM3 correlation and enrichment analysis. Results of correlation analysis showed that DNM3 was positively correlated with genes such as RBMS3, CNTN4 and PDE1A ( r=0.52, 0.52, 0.50, P<0.05) and negatively correlated with genes such as SLC25A39, PAICS and GAPDH ( r=?0.41, ?0.40, ?0.40, P<0.05) in gastric cancer. Results of gene set enrichment analysis showed that the set of genes related to ribosome and oxidative phosphorylation were upregulated in gastric cancer patients with DNM3 low expression [normalized enrichment score (NES)=?3.30, ?2.16, P<0.05], while the set of genes related to immunomodulatory interactions between lymphocytes and non-lymphoid cells were upregulated in gastric cancer patients with DNM3 high expression (NES=1.67, P<0.05). Results of gene ontology analysis showed that the low expression of DNM3 was associated with the separation of mitotic sister chromatid (No.0000070), nonsense-mediation of nuclear transcriptional mRNA catabolic process, sister chromatid separation (No.0000819), nuclear transcriptional mRNA catabolic process and regulation of oxidative phos-phorylation (NES=?2.29, ?3.10, ?2.33, ?2.56, ?2.68, P<0.05). Results of Kyoto encycl opedia of genes and genomes analysis showed that metabolic pathway related to ribosome and oxidative phosphory-lation were upregulated and crosstalked in gastric cancer with low expression of DNM3 (NES=?3.34, ?2.21, P<0.05). (6) Ratio of G0/G1 phase, S phase and G2/M phase of cell cycle progression. Results of flow cytometric cell cycle experiments showed that the proportions of G0/G1 phase, S phase and G2/M phase in the cell cycle was 65.1%±3.0%, 17.3%±3.0% and 17.6%±1.0% in the AGS cells transfected with pCMV-DNM3 plasmid, versus 53.4%±4.0%, 26.3%±2.0% and 20.3%±3.0% in the AGS cells transfected with control plasmid, showing significant differences in the proportions of G0/G1 phase and S phase in the two types of cells ( t=4.05, 4.32, P<0.05). (7) Correlation between immune cell infiltration and DNM3 in gastric cancer. Results of immune cell infiltration examination showed that the expression level of DNM3 was positively associated with mast cells, NK cells, pDCs, B cells, follicular helper T cells, effector memory T cells, T cells, central memory T cells, CD8 T cells, DC cells, macrophages, γ-δ T cells (Tgd), iDCs and eosinophils infiltration (Spearman correlation coefficients as 0.41, 0.29, 0.26, 0.20, 0.22, 0.22, 0.13, 0.16, 0.15, 0.14, 0.14, 0.17, 0.18, 0.22, P<0.05) and negatively associated with Th17 cell, Th2 cells and NK CD56 dim cells infiltration ( r=?0.18, ?0.23, ?0.10, P<0.05). (8) Correlation between results of IHC staining and clinical features. Results of IHC staining analysis showed that the IHC score of DNM3 was 3(2,4) in the 105 gastric cancer tissues, versus 6(4,9) in the 105 paired normal tissues, showing a significant difference between them ( Z=-7.35, P<0.05). There were significant differences in gender, tumor location and N stating between the 70 patients with low expression of DNM3 and the 35 patients with high expression of DNM3 ( χ2=4.29, 7.67, 6.86, P<0.05). (9) Analysis of independent factors influencing 5-year overall survival rate of gastric cancer patients. Results of multivariate analysis showed that stage pT3?4 and low IHC score of DNM3 were independent risk factors for 5-year overall survival rate of gastric cancer patients ( hazard ratio=1.91, 0.51, 95% confidence interval as 1.06?3.43, 0.26?0.98, P<0.05). The 5-year overall survival rate was 44.3% in patients with low expression of DNM3, versus 65.7% in gastric cancer patients with high expression of DNM3, showing a significant difference between them ( χ2=5.02, P<0.05). Conclusion:DNM3 is a tumor suppressor and an independent predictor of poor prognosis for gastric cancer, which may regulate gastric cancer cell cycle and immunosuppression in the tumor microenvironment through methylation.