The WinBUGS software can be called from either R (provided R2WinBUGS as an R package) or Stata software for network meta-analysis. Unlike R, Stata software needs to create relevant ADO scripts at first which simplify operation process greatly. Similar with R, Stata software also needs to load another package when drawing network plots. This article briefly introduces how to implement network meta-analysis using Stata software by calling WinBUGS software.
Objective To evaluate the potential roles of celecoxib on proliferation and cell cycle progression of colon adenocarcinoma cells and on the hepatic metastasis of nude mice. Methods The human colon cancer cells HT-29 and HCT-116 were employed in the study. After treatment with celecoxib, the inhibitory effects of celecoxib on the proliferation of cancer cells were quantified by MTT assay, and the cell cycle progression was detected by flow cytometry, tumor cells were inoculated in nude mice, and the hepatic metastasis was detected. Results ①Celecoxib inhibited the proliferation of the tumor cells in time and dose-dependent manners （P＜0.05，P＜0.01）. The inhibitory effect on HT-29 cells was ber than that on HCT-116 cells （P＜0.05）. ②Celecoxib changed cell cycle progression of both kinds of cells, and decreased the proliferation index of both kinds of cells too. ③Celecoxib could inhibit the growth of the hepatic metastatic tumor obviously. Conclusion Celecoxib may inhibit the activity of cyclooxygenase-2, and resulting in the inhibition of division and proliferation, apoptosis of tumor cells and interfering in metastasis and relapse of colon cancer.
The theoretical foundation of relevant packages of R software for network meta-analysis is mainly based on Bayesian statistical model and a few of them use generalized linear model. Network meta-analysis is performed using GeMTC R package through calling the corresponding rjags package, BRugs package, or R2WinBUGS package (namely, JAGS, OpenBUGS, and WinBUGS software, respectively). Meanwhile, GeMTC R package can generate data storage files for GeMTC software. Techonically, network meta-analysis is performed through calling the software based on Markov Chain Monte Carlo method. In this article, we briefly introduce how to use GeMTC R package to perform network meta-analysis through calling the OpenBUGS software.
ObjectiveTo summarize the experience of diagnosis and treatment on primary gastric lymphoma. MethodsThirtyseven patients, proved by pathology, were included in the study. ResultsAmong clinical presentation, the upper abdominal pain, intestinal bleeding, and weight loss were common. Only 4 cases were diagnosed as PGL in 33 cases with the examination of Xray barium meal, 88.5% ( 23 of 26 cases) were missdiagnosed as gastric ulcer under gastroscopy. All cases underwent operation, among them 33 had been performed a radical operation. The survival period was over 5 years in 12 of 25 patients who have been followed up. ConclusionThe multiple biopsy sampling from submucosal layer via gastroscope may improve diagnostic rate on primary gastric lymphoma. Operative removal of the tumor should be the first choice of treatment. Additional chemotherapy after the surgery increases the fiveyear survival rate.
The aggregate data drug information system (ADDIS) software is a non-programming software which is based on the Bayesian framework and using the Markov chain Monte Carlo (MCMC) method for prior assessment and implementation. The operation is fairly easy for users. The consequent results and relevant plots could be output automatically by the software after users assess the consistency of model and convergence diagnostics. The major disadvantage of ADDIS is the more complicated data entry. This article introduces how to perform network meta-analysis using ADDIS software.
Objective To systematically review the correlation between polymorphism of DNA methyltransferase 1(DNMT1) rs16999593 and the susceptibility of breast cancer. Methods Databases such as PubMed, EMbase, Web of Science, Chinese Biomedical Literature Database, CNKI, WanFang, and VIP database were searched from inception to Mar. 2017 to collect case-control studies on the correlation between DNMT1 rs16999593 C/T polymorphism and the susceptibility of breast cancer. Two reviewers independently identified the literatures according to inclusion and exclusion criterias, extracted data, and assessed the quality of the included studies. The meta-analysis was performed by using RevMan 5.3 software. Results A total of 5 studies involving 1 741 cases and 1 917 control subjects were included. The results of meta-analysis showed that, dominate model ［TT+TC vs. CC: OR=0.63, 95% CI was (0.30, 1.30), P=0.21］, homozygous model ［TT vs. CC: OR=1.01, 95% CI was (0.70, 1.47), P=0.95］, heterozygous model ［TC vs. CC: OR=0.44, 95% CI was (0.18, 1.04), P=0.06］, and additive model ［T vs. C: OR=1.29, 95% CI was (0.90, 1.86), P=0.16］ were not significantly related to breast cancer, but recessive gene model was related to breast cancer ［TT vs. TC+CC: OR=1.74, 95% CI was (1.01, 3.00), P=0.04］. Conclusion The current studies showed that, DNMT1 rs16999593 TT genotype decreases the susceptibility of breast cancer.
Brain control is a new control method. The traditional brain-controlled robot is mainly used to control a single robot to accomplish a specific task. However, the brain-controlled multi-robot cooperation (MRC) task is a new topic to be studied. This paper presents an experimental research which received the "Innovation Creative Award" in the brain-computer interface (BCI) brain-controlled robot contest at the World Robot Contest. Two effective brain switches were set: total control brain switch and transfer switch, and BCI based steady-state visual evoked potentials (SSVEP) was adopted to navigate a humanoid robot and a mechanical arm to complete the cooperation task. Control test of 10 subjects showed that the excellent SSVEP-BCI can be used to achieve the MRC task by appropriately setting up the brain switches. This study is expected to provide inspiration for the future practical brain-controlled MRC task system.
ObjectiveTo research the value of virtual reality (VR) technology in the preoperative planning of transtrochanteric curved varus osteotomy for avascular necrosis of the femoral head (ANFH) in adults.MethodsBetween June 2018 and November 2018, 7 patients (11 hips) with ANFH, who were treated with transtrochanteric curved varus osteotomy, were enrolled in the study. There were 4 males (7 hips) and 3 females (4 hips) with an average age of 31.9 years (range, 14-46 years). Among them, 3 patients were unilateral ANFH and 4 patients were bilateral ANFH. There was 1 patient (1 hip) of traumatic ANFH, 2 patients (4 hips) of alcohol-induced ANFH, 2 patients (3 hips) of hormonal ANFH, and 2 patients (3 hips) of idiopathic ANFH. All hips were Association Research Circulation Osseous (ARCO) stage Ⅲ. There were 5 hips for Japanese Investigation Committee (JIC) type C1 and 6 hips for type C2. There were 5 hips for China-Japan Friendship Hospital (CJFH) type L1,1 for type L2, and 5 for type L3. The disease duration ranged from 5 to 12 months (mean, 8 months). Preoperative Harris score was 53.91±7.66. The neck-shaft angle ranged from 128 to 143° (mean, 133.9°). VR technology was adopted for the preoperative planning. CT data were imported into the software to construct the morphology of necrotic area, and the transrtrochanteric varus osteotomy was simulated. The varus angle was designed according to the integrity rate of femoral head. The planned varus angle was 6 to 16° (mean, 9.7°). The transtrochanteric curved varus osteotomy was performed according to the preoperative planning, and the varus angle and loading area were confirmed under fluoroscopy. If the planned varus angle was too small, it would continue to increase under the fluoroscopy until a satisfactory varus angle. Postoperative changes of the neck-shaft angle were calculated and compared with the preoperative planned varus angle (error). The hip function was assessed by using the Harris score.ResultsAll incisions healed by first intention. All patients were followed up 6-11 months with an average of 8 months. The X-ray film at 2 days after operation showed that the neck-shaft angle was 112-135° (mean, 123.4°). The difference of the neck-shaft angle between pre- and post-operation was 6-16° (mean, 11.0°). Among them, the difference of the neck-shaft angle was consistent with planned varus angle in 5 hips, while the error of the remaining 6 hips was 1-4°. There was 1 patient (1 hip) of osteotomy nonunion at 4 months after operation, 1 patient (1 hip) of proximal femur fracture at 2 months after operation. The rest 5 patients (9 hips) obtained union at the osteotomy. At last follow-up, the Harris score was 82.18±16.35, showing significant difference when compared with preoperative score (t=–5.195, P=0.000).ConclusionVR technology is a brand-new preoperative planning method for transtrochanteric curved varus osteotomy in treating ANFH.
R Software is an open, free of use and charge statistical software which has a powerful graphic capability; however, it requires more complex codes and commands to perform network meta-analysis, which causes errors and difficulties in operation. WinBUGS software is based on Bayesian theory, which has a powerful data processing capability, and especially its codes are simple and easy to operate for dealing with network meta-analysis. However, its function of illustrating statistical results is very poor. In order to fully integrate the advantages of R software and WinBUGS software, an R2WinBUGS package based on R software has been developed which builds a “bridge” across two of them, making network meta-analysis process conveniently, quickly and result illustration more beautiful. In this article, we introduced how to use the R2WinBUGS package for performing network meta-analysis using examples.
Network plots can clearly present the relationships among the direct comparisons of various interventions in a network meta-analysis. Currently, there are some methods of drawing network plots. However, the information provided by a network plot and the interface-friendly degree to a user differ in the kinds of software. This article briefly introduces how to draw network plots using the network package and gemtc package that base on R Software, Stata software, and ADDIS software, and it also compares the similarities and differences among them.