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Objective: There have been no systematic reviews, let alone meta-analyses, of randomized controlled trials (RCTs) comparing tongxinluo capsule (TXL) and beta-blockers in treating angina pectoris. This study aimed to evaluate the efficacy of TXL and beta-blockers in treating angina pectoris by a meta-analysis of eligible RCTs. Methods: The RCTs comparing TXL with beta-blockers (including metoprolol) in treating angina pectoris were searched and retrieved from databases including PubMed, Chinese National Knowledge Infrastructure, and WanFang Data. Eligible RCTs were selected according to prespecified criteria. Meta-analysis was performed on the odds ratios (OR) of symptomatic and electrocardiographic (ECG) improvements after treatment. Subgroup analysis, sensitivity analysis, meta-regression, and publication biases analysis were conducted to evaluate the robustness of the results. Results: Seventy-three RCTs published between 2000 and 2014 with 7424 participants were eligible. Overall ORs comparing TXL with beta-blockers were 3.40 (95% confidence interval [CI], 2.97-3.89; p<0.0001) for symptomatic improvement and 2.63 (95% CI, 2.29-3.02; p<0.0001) for ECG improvement. Subgroup analysis and sensitivity analysis found no statistically significant dependence of overall ORs on specific study characteristics except efficacy criteria. Meta-regression found no significant except sample sizes for data on symptomatic improvement. Publication biases were statistically significant. Conclusion: TXL seems to be more effective than beta-blockers in treating angina pectoris, on the basis of the eligible RCTs. Further RCTs are warranted to reduce publication bias and verify efficacy. [ABSTRACT FROM AUTHOR]

Background: Dinoponera quadriceps is a predatory giant ant that inhabits the Neotropical region and subdues its prey (insects) with stings that deliver a toxic cocktail of molecules. Human accidents occasionally occur and cause local pain and systemic symptoms. A comprehensive study of the D. quadriceps venom gland transcriptome is required to advance our knowledge about the toxin repertoire of the giant ant venom and to understand the physiopathological basis of Hymenoptera envenomation. Results: We conducted a transcriptome analysis of a cDNA library from the D. quadriceps venom gland with Sanger sequencing in combination with whole-transcriptome shotgun deep sequencing. From the cDNA library, a total of 420 independent clones were analyzed. Although the proportion of dinoponeratoxin isoform precursors was high, the first giant ant venom inhibitor cysteine-knot (ICK) toxin was found. The deep next generation sequencing yielded a total of 2,514,767 raw reads that were assembled into 18,546 contigs. A BLAST search of the assembled contigs against non-redundant and Swiss-Prot databases showed that 6,463 contigs corresponded to BLASTx hits and indicated an interesting diversity of transcripts related to venom gene expression. The majority of these venom-related sequences code for a major polypeptide core, which comprises venom allergens, lethal-like proteins and esterases, and a minor peptide framework composed of inter-specific structurally conserved cysteine-rich toxins. Both the cDNA library and deep sequencing yielded large proportions of contigs that showed no similarities with known sequences. Conclusions: To our knowledge, this is the first report of the venom gland transcriptome of the New World giant ant D. quadriceps. The glandular venom system was dissected, and the toxin arsenal was revealed; this process brought to light novel sequences that included an ICK-folded toxins, allergen proteins, esterases (phospholipases and carboxylesterases), and lethal-like toxins. These findings contribute to the understanding of the ecology, behavior and venomics of hymenopterans. [ABSTRACT FROM AUTHOR]

Potential drug targets for the disease treatment can be identified from microarray studies on differential gene expression of patients and healthy participants. Here, we describe a method to use the information of differentially expressed (DE) genes obtained from microarray studies to build molecular interaction networks for identification of pivotal molecules as potential drug targets. The quality control and normalization of the microarray data are conducted with R packages simpleaffy and affy, respectively. The DE genes with adjusted P values less than 0.05 and log fold changes larger than 1 or less than -1 are identified by limma package to construct a molecular interaction network with InnateDB. The genes with significant connectivity are identified by the Cytoscape app jActiveModules. The interactions among the genes within a module are tested by psych package to determine their associations. The gene pairs with significant association and known protein structures according to the Protein Data Bank are selected as potential drug targets. As an example for drug target screening, we demonstrate how to identify potential drug targets from a molecular interaction network constructed with the DE genes of significant connectivity, using a microarray dataset of type 2 diabetes mellitus.

Meta-analysis statistically assesses the results (e.g., effect sizes) across independent studies that are conducted in accordance with similar protocols and objectives. Current genomic meta-analysis studies do not perform extensive re-analysis on raw data because full data access would not be commonplace, although the best practice of open research for sharing well-formed data have been actively advocated. This chapter describes a simple and easy-to-follow method for conducting meta-analysis of multiple studies without using raw data. Examples for meta-analysis of microRNAs (miRNAs) are provided to illustrate the method. MiRNAs are potential biomarkers for early diagnosis and epigenetic monitoring of diseases. A number of miRNAs have been identified to be differentially expressed, i.e., overexpressed or underexpressed, under diseased states but only a small fraction would be highly effective biomarkers or therapeutic targets of diseases. The meta-analysis method as described in this chapter aims to identify the miRNAs that are consistently found dysregulated across independent studies as biomarkers.

Introduction: Past studies of network meta-analysis focused on evaluating drug combinations in treating type 2 diabetes but not on evaluating antidiabetic drugs in monotherapy. Clinical guidelines (eg, NICE (National Institute of Health and Care Excellence) clinical guidelines 66 and 87) were based only on the findings of individual clinical trials and pairwise meta-analysis in evaluating monotherapy. This study aims to fill this gap of research by conducting a Bayesian network meta-analysis to compare major antidiabetic drugs, including metformin, glimepiride, glyburide, glipizide, repaglinide, nateglinide, sitagliptin, vildagliptin, saxagliptin and SGLT-2 (sodium-glucose transporter-2) inhibitors., Methods and Analyses: Randomised controlled trials (RCTs) on the drug therapy of type 2 diabetes with outcome measures including glycosylated haemoglobin or fasting blood glucose will be included. The quality of included RTCs will be evaluated according to the Cochrane Collaboration's risk of bias tool. Traditional pairwise meta-analysis and Bayesian network meta-analysis will be conducted to compare the efficacies of antidiabetic drugs. Sensitivity analysis on the sample size of RCTs, meta-regression analysis on the follow-up periods, dosages and baselines of outcome measure, contradiction analysis between pairwise and network meta-analyses, and publication bias analysis, will be performed., Ethics and Dissemination: Ethical approval is not required because this study includes no confidential personal data and interventions on the patients. Pairwise and network meta-analyses are based on the published RCT reports of eligible drugs in treating type 2 diabetes. The results of this study will be disseminated by a peer-reviewed publication., Protocol Registration Number: PROSPERO CRD42014010567., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Introduction: There were 11 pairwise meta-analysis on the efficacy of β-blockers (including atenolol, propranolol, bisoprolol, metoprolol and nadolol), calcium channel blockers (including amlodipine, diltiazem, felodipine, nifedipine and verapamil), and nitrates (including isosorbide dinitrate, isosorbide mononitrate and nitroglycerin) in treating stable angina pectoris. No network meta-analytic study has been published to evaluate the efficacies of these antianginal drugs. Current clinical guidelines (eg, National Institute of Health and Care Excellence (NICE) clinical guideline 126) are only based on the findings of limited clinical trials and pairwise meta-analysis. This study aims to fill this gap of research by conducting a Bayesian network meta-analysis to compare all these antianginal drugs., Methods and Analyses: Randomised controlled trials (RCT) on the drug therapy of stable angina pectoris with multiple outcome measures, selected from symptomatic relief, ECG tests, exercise tests, heart rates and blood pressures, etc, will be included. Overall effect sizes will be represented as mean differences with 95% credible intervals (CrI) for continuous outcome data and as ORs with 95% CrI for dichotomous outcome data. Bayesian network meta-analysis by WinBUGS will be conducted to compare the efficacies of these drugs. Sensitivity analysis on the quality of RCTs and subgroup analysis on the category of included drugs will be performed., Ethics and Dissemination: Ethical approval is not required because this study includes no confidential personal data and interventions on the patients. Network meta-analysis is based on the RCT reports of eligible drugs in treating stable angina pectoris. The results of this study will be disseminated by an open access and peer-reviewed publication., Trial Registration Number: PROSPERO CRD42014007113., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Background: Chinese patent medicines Compound Danshen Dripping Pills (DSP) and Di'ao Xinxuekang (DXK) capsules were both found effective in treating angina pectoris. However, there is no systematic review comparing their efficacy., Objective: This systematic review aims to compare the efficacy of DSP and DXK in treating angina pectoris based on randomized controlled trials (RCTs) comparing their efficacy., Search Strategy: RCT reports published between 1994 and 2011 were retrieved from databases including China Doctoral Dissertations Full-text Database, Chinese Journal Full-text Database, China Master's Theses Full-text Database, Wanfang Data, Cochrane Library, Excerpts Medica Database, ScienceDirect, MEDLINE (EBSCOhost) and PubMed. The last retrieval was performed on April 7, 2011., Inclusion Criteria: RCT reports comparing the effects of DSP and DXK were included, regardless publishing language., Data Extraction and Analysis: Included RCT reports were assessed for their study quality by using the Jadad scale and the Cochrane risk of bias tool. Data including overall effect and electrocardiography (ECG) improvements were extracted from the included RCTs for meta-analysis. The effect sizes based on overall and ECG diagnosis were measured by odds ratio (OR) and 95% confidence interval (CI). Subgroup analysis and sensitivity analysis were also performed., Results: Nine RCT reports with 926 participants were included. Eight were scored 2 and the other one was scored 4 by using the Jadad scale. The OR between DSP and DXK based on overall diagnosis was 2.06 (95% CI: 1.03-4.12; P(overall)=0.04). Six out of the nine included RCTs reported ECG data. The OR between DSP and DXK based on the ECG diagnosis was 1.92 (95% CI: 1.23-3.00; P(ECG)=0.004). The OR results were stable under subgroup analysis and sensitivity analysis., Conclusion: DSP was consistently more effective than DXK according to meta-analysis, which was verified by subgroup analysis and sensitivity analysis. However, more RCTs of higher quality are needed for further confirmation.